The kinetics of ferrous ion oxidation by Leptospirillum ferriphilum in continuous culture: The effect of pH

Hydrometallurgy 106 (2011) 5–11

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Hydrometallurgy j o u r n a l h o m e p a g e : w w w. e l s ev i e r. c o m / l o c a t e / h yd r o m e t

The kinetics of ferrous ion oxidation by Leptospirillum ferriphilum in continuous culture: The effect of pH Tunde V. Ojumu a,⁎, Jochen Petersen b a b

Department of Chemical Engineering, Cape Peninsula University of Technology, P.O Box 652 Cape Town, 8000 South Africa Centre for Bioprocess Engineering Research, Department of Chemical Engineering, University of Cape Town; Private Bag X3, Rondebosch 7701, South Africa

a r t i c l e

i n f o

a b s t r a c t

Article history: Received 11 August 2010 Received in revised form 29 October 2010 Accepted 3 November 2010 Available online 23 November 2010

The kinetics of ferrous ion oxidation by Leptospirillum ferriphilum were studied in continuous culture with a focus on the effect of solution pH (pH 0.8–2.0), assuming that the effect of pH on cell metabolism can be independently studied of reactor context and other reactions common in bioleach heaps. A simplified competitive ferric ion inhibition model and the Pirt Equation were used to analyze the experimental data. The results showed that the maximum specific activity of L. ferriphilum has a symmetrical bell-shaped curve max 2 + gave a highest value of relationship with pH. The maximum specific ferrous-iron oxidation rate, qFe 14.54 mmol Fe2+(mmol C h)− 1 at pH 1.3, and was described by a quadratic function. The steady state carbon biomass in the reactor and the apparent affinity constant, K′Fe2 +, also increased with increase in pH; however, a slight increase in the carbon biomass was observed beyond pH 1.6. The results also showed that ferric ion precipitation is significant beyond pH 1.3 and about 13% total iron from the feed was lost at pH 2.0. The maximum biomass yield increased linearly with pH, while the culture maintenance coefficient was significantly small in all experiments and was minimum at pH 1.3. The values are indicative of actively growing chemostat cultures. This study shows that microbial ferrous ion oxidation by L. ferriphilum may be sustained at pH lower than pH 0.8 as the microbial activity is much higher than reported values for common mesophilic acidophiles. This may have implications on how bioleach heap operations can be started-up to improve metal recovery. © 2010 Elsevier B.V. All rights reserved.

Keywords: Microbial ferrous ion oxidation Kinetics pH effect Bioleaching Leptospirillum ferriphilum

1. Introduction Solution pH is critical to the availability of the ferric ion reagent for the leaching of most sulphide minerals. A high pH environment is not only detrimental to the ferrous ion oxidizing ability of acidiophilic bacteria; it may also reduce heap permeability due to ferric ion precipitation within the heap bed. Solution pH is also one of the key factors affecting the ferrous ion oxidation by certain microorganisms. A high proton environment is necessary for the biooxidation process (Eq. (1)), as this facilitates the electron transport system within the chemo-lithotrophic autotrophic bacteria for the cell nutritional purpose, as described by Ingledew (1982). bacteria

4Fe þ 4H þ O2 → 4Fe þ 2H2 O 2þ

þ

3þ

ð1Þ

In bioleaching, it is also necessary to keep iron in solution by preventing the precipitation of ferric ion as hydroxyl and sulphate complexes which reduce the amount of ferric ion in the leaching medium. Apart from iron conservation, du Plessis et al. (2007) and ⁎ Corresponding author. Tel.: + 27 21 460 3162; fax: + 27 21 460 3854. E-mail address: [email protected] (T.V. Ojumu). 0304-386X/$ – see front matter © 2010 Elsevier B.V. All rights reserved. doi:10.1016/j.hydromet.2010.11.007

van Aswegen et al. (2007) reported that a pH greater than 2.0 has a negative effect on microbial population. Ferric ion precipitates, such as jarosite, represent one of the challenges in bioleach heap operations: it occupies the space on the biomass carrier material (i.e. the ore surface) creating diffusion barriers, and if not dislodged, the precipitate can clog up the heap bed, thus reducing its permeability. This challenge is managed in tank bioleach reactors by operating at pH values around 1.5. However, bioleach heaps are marked by a wide pH gradient between feed and effluent (typically pH 1.0–2.5). Furthermore, liquid channelling through the heap bed can result in erratic pH variations, making its control difficult to manage. A number of studies have been carried out on the effects of pH on microbial ferrous ion oxidation (Breed and Hansford, 1999; Nemati et al., 1998; Özkaya et al., 2007c). Although a wide range of optimum pH 1.5 – 3.5 was reported in Nemati et al. (1998) for At. ferrooxidans, recent studies have shown that solution pH greater than 2.0 can lead to high risk of bacterial de-activation, resulting in loss of the microbial culture (Penev and Karamanev, 2010; Plumb et al., 2008; van Aswegen et al., 2007). Studies on a heap bioleach operation in the South America have shown that while the fresh feed contained 8 g L− 1 (~pH 0.9) of sulphuric acid as free acid, the effluent stream gave a high pH value of between 2.2 and 2.4 (Ojumu et al., 2006).

6

T.V. Ojumu, J. Petersen / Hydrometallurgy 106 (2011) 5–11

Therefore it is necessary to investigate the kinetics of microbial ferrous-iron oxidation over a wider range of pH as previously studied. Breed (2000) and Breed and Hansford (1999) report studies carried out within a narrower range, pH 1.1–1.7 Plumb et al. (2008) reported that Leptospirillum ferriphilum has a relatively broad pH range for the oxidation of ferrous ion with an optimum at pH 2.0 while Coram and Rawlings (2002) reported an optimum pH range of 1.4 to 1.8. Although both the latter studies were carried out under batch operation, they cannot be compared as the bases of measurement were different. While the former was based on microbial activity, microbial growth was used for the latter. It was recently shown that microbial ferrous ion oxidation by L. ferriphilum can be achieved at pH below 1.0 (Kinnunen and Puhakka, 2005; Özkaya et al., 2007a; Özkaya et al., 2007c; Penev and Karamanev, 2010). However, limited data still exists on the kinetics of microbial ferrous-iron oxidation by this organism. This paper discusses the results of the kinetics of ferrous ion oxidation by L. ferriphilum in a chemostat, over a wide range of pH relevant to bioleach heap operations (Plumb et al., 2008), with a view to understanding how the kinetics and the microbial activity change over a range of pHs away from the previously studied optimum. This study was based on the assumption that the ferrous ion oxidation subprocess can be studied independently of reactor configuration and other equally competing processes and/or reactions common in bioleach heaps. The results of this study would provide an insight into how heap bioleach systems should be managed with respect to pH variations. 2. Methodology

ferrous ion oxidation usually results in an increase in pH as protons are consumed in the reaction (Eq. (1)), the bioreactor pH was maintained at the desired value by adjusting the feed pH slightly lower than the target pH. All the experiments were carried out at dilution rates ranging between 0.015 and 0.100 h− 1 corresponding to reactor residence times of 10–66 h. New experiments were usually restarted with 50% of stock culture in a batch mode, and were later switched into continuous mode at a solution potential of about 600 mV (vs. Ag/AgCl) (Ojumu et al., 2009). The bioreactor was cleaned periodically and wall growth was minimised by transferring bioreactor solution liquor into a pre-cleaned and identical bioreactor (Ojumu et al., 2009; Ojumu et al., 2008). The cleaning intervals depended on the operating pH, unlike in our previous study in which cleaning depended on operating temperature (Ojumu et al., 2009). Cleaning was more frequent (after two residence time from desired steady state) at pH greater than pH 1.3. The wall growth was found to be insignificant at pH below 1.3 (data not shown) when cleaning was less frequent. 2.3. Total iron and ferrous-iron determination Ferrous ion concentrations were determined by titration with 0.0149 M potassium dichromate solution using barium diphenylamine sulphonate (BDS) indicator. Total iron concentration was also determined as ferrous ion by reducing the (oxidized ferric) sample to ferrous ion with stannous chloride prior to titration with potassium dichromate (Ojumu, 2008). The measurement of redox potential using Metrohm redox electrodes (Pt–Ag/AgCl) allows the determination of ferric-to-ferrous ion ratio. By establishing a calibration curve for the electrode (data not shown) and using the Nernst equation, the values of these ratios can be calculated (Penev and Karamanev, 2010).

2.1. The growth medium and bacterial culture 3. Results and discussion Analytical-grade reagents were used for all the experiments. The ferrous ion media consisted of 12 g L− 1 of Fe2+ (added as FeSO4.7H2O), 1.11 g L− 1 K2SO4, 0.53 g L− 1 (NH4)2HPO4, 1.83 g L− 1 (NH4)2SO4 and 10 mL of Vishniac trace element solution (Vishniac and Santer, 1957) adjusted to the desired pH. The inoculum containing L. ferriphilum was obtained originally from a vat-type two-stage continuous bioleaching mini-plant treating a pyrite-arsenopyrite concentrate, at the Gamsberg mine, South Africa, in the 1990s and has been maintained in a laboratory stock culture on ferrous ion in a continuous stirred tank bioreactor at 72 h residence time (Ojumu et al., 2009) ever since. The culture was sent away for gene analysis near the completion of the experiment to determine the strain, which was confirmed to be 98% L. ferriphillum.

The simplified ferric ion inhibition model, Eq. (2), suggested by Boon and Hansford (Boon et al., 1995b) was used to analyze the data. Other equations used were Pirt Equation, Eq. (3) (Pirt, 1982) and the degree-of-reduction balance equation, Eq. (4). The theoretical formulation of these equations has been described in detail in the literature (Boon et al., 1995a; Boon et al., 1995b; Breed and Hansford, 1999; max Ojumu, 2008) and is not repeated here. The parameters, qFe 2+ , the maximum specific ferrous ion oxidation rate and K′Fe2 +, the apparent affinity constant, were determined by fitting the experimental data to Eq. (2) using a Solver routine in Excel as described previously (Ojumu, 2008; Ojumu et al., 2009). The biomass concentrations, CX, were determined from carbon dioxide utilization rates, rCO2, and dilution rates, D, according to Eq. (5) (Breed and Hansford, 1999).

2.2. Microbial ferrous-iron oxidation under continuous operation A series of continuous culture experiments with L. ferriphilum were performed in a stirred tank double walled bioreactor with 1 litre working volume. The diagrammatic representation of experimental setup was shown recently (Ojumu et al., 2009) and has been described in detail elsewhere (Boon, 1996; Ojumu, 2008). The temperature of the bioreactor was maintained at 42 °C – the temperature at which the specific microbial activity was maximum (Ojumu et al., 2009). The growth medium contained 12 ± 0.5 g L− 1 of Fe2+ added as FeSO4.7H2O, the aeration rate was maintained between 330 and 400 mL min− 1 and the stirring speed was controlled at 400 rpm. The dried off-gas from the bioreactor and the reference air were analyzed for oxygen and carbon dioxide concentration using a Hartmann & Braun Magnos 6 G oxygen analyzer and Uras 4 NDIR industrial photometer respectively. Experiments were conducted at solution pHs of 0.80, 1.00, 1.30, 1.50, 1.70, 2.00 with deviation of ±0.05 using a Metrohm 744 pH meter (Metrohm, Switzerland) which was calibrated at pH 1.00 and pH 7.00 with buffers (supplied by Merck, South Africa). Although

qFe2+ =

qFe2+ =

′2 1 + K Fe

+

q max 2+  Fe 3+   2+  Fe = Fe

−rFe2+ D = max YFe2 + CX

+ mFe2+

ð2Þ

ð3Þ

X

−rFe2+ = −4rO2 −4:2rCO2

ð4Þ

CX = −rCO2 = D

ð5Þ

3.1. The validity of data – mass balance vs. degree-of-reduction balance Fig. 1 compares the data obtained from two independent measuring techniques – the − rFe2 + obtained by a simple ferrous ion balance over the chemostat and that obtained using the off-gas measurements using the degree-of-reduction balance equation, Eq. (4). The figure suggests good agreement between both methods.

T.V. Ojumu, J. Petersen / Hydrometallurgy 106 (2011) 5–11

(mmol.L-1.h-1)

20

7

2004) and increase protons in solution by hydrolysis (for example, Eq. 6), its formation is undesirable in bioleach operation as it reduces the available oxidizing reagent (ferric ion), critical to leaching of most sulphide minerals. The precipitates could also clog the heap bed and prevent flow of pregnant leach solution.

15

3þ

þ

þ

2

3FeðaqÞ þ KðaqÞ þ 2SO4ðaqÞ þ 6H2 OðlÞ → KFe3 ðSO4 Þ2 ðOHÞ6ðsÞ þ 6HðaqÞ ð6Þ 10 pH 0.80 pH 1.00 pH 1.30

5

pH 1.60

pH 2.00 0 0

5

10 2+

15

20

2+

− rFe2+ = D ([ Fe ] inlet − [ Fe ]oulet ) (mmol.L-1.h-1) Fig. 1. Parity plot comparing the data obtained from the chemostat substrate balance vs. the degree-of-reduction balance.

This approach is used to check the validity and consistency of the off gas measurement (Boon, 1996; Ojumu, 2008). Although the off-gas data over-estimated − rFe2 +, a relative standard deviation of less than 9% is considered to be acceptable and valid for both − rO2and − rCO2 (Ojumu et al., 2009). 3.2. Dissolved iron balance The iron balance results showed that the total free iron in solution at steady state decreased, as the solution pH increased from 0.8 to 2.0 (Fig. 2). The soluble iron in the bioreactor was determined from the filtrate of the effluent passing through 0.45 um filter paper. The iron balance was determined by comparing the total soluble iron concentration in the feed stream with that in the effluent. It was assumed that the loss of iron was due to ferric ion precipitation and this was calculated as a difference between total soluble iron in the feed and the filtrate from the bioreactor effluent. Although jarosite formation may facilitate microbial growth (Kinnunen and Puhakka,

Özkaya et al. (2007b) reported that less than 30% of ferric-iron precipitated as jarosite during a microbial ferrous-iron oxidation experiment using L. ferriphilum in a fluidised bed reactor with 7 g/L ferrous-iron at pH 1.5 to 2.0. In this study the iron lost due to ferric precipitation increased from 0.3 to 13% due to increase in solution pH from pH 0.8 to 2.0 as shown in Fig. 2. However it should be noted that these were average values over the entire range of dilution rates investigated. Much higher degree of precipitation observed at lower dilution rates was responsible for the significant standard deviation of the data at higher pHs. As the solution pH increased beyond 1.3, cleaning of the bioreactor became more frequent (depending on the residence time/dilution rate) in order to minimise the interference of ferric precipitation on the experimental data. It should also be noted that although a higher ferrous-iron concentration was used in this study, it is difficult to compare these studies as they were carried out in different reactor systems. 3.3. Biomass concentration vs. pH The steady state biomass concentration CX, Eq. (5), varied slightly, increasing from low to intermediate dilution rate where the highest biomass was obtained (i.e. between 0.05 and 0.06 h− 1) (Ojumu et al., 2009). It then declined as the system approaches wash out (see Fig. 3). This trend was expected and has been reported previously (Boon, 1996; Breed et al., 1999; Ojumu, 2008; van Scherpenzeel et al., 1998). Although some authors attributed the flatness of the CX vs. D to wall growth (Gahan et al., 2010; Sundkvist et al., 2008), our own work confirmed the same trend in an experiment where the cleaning of the bioreactor was carried out systematically and frequently to minimize wall growth (Ojumu et al., 2009). We agree with this trend which was further supported by substituting a reasonable guess value of 2.50

20 12.0

Feed stream Effluent stream Percentage iron loss

8

4.0 4 2.0

0.0 0.5

Biomass, Cx (mmol C. L -1)

12

Iron loss (%)

Free iron (g L-1)

8.0

6.0

2.00

16

10.0

pH 2.00 pH 1.60 pH 1.30 1.50

pH 1.00 pH 0.80

1.00 pH 0.80 pH 1.00 pH 1.30 pH 1.60 pH 2.00

0.50

0 1

1.5

2

Solution pH

0.00 0.00

0.02

0.04

0.06

Dilution rate, D Fig. 2. Total iron balance (measured as free iron) in feed and effluent stream of the bioreactor, and percentage iron loss due to ferric precipitation as a function of solution pH [errors expressed as standard deviation of the mean values obtained over all residence times investigated at each pH].

0.08

0.10

(h-1)

Fig. 3. Variation of biomass concentration CX with dilution rate for studies showing the effect of solution pH on microbial ferrous ion oxidation [the dotted lines indicate the trends of biomass with pH].

T.V. Ojumu, J. Petersen / Hydrometallurgy 106 (2011) 5–11

3.5

0.15

pH control 2.5

0.1 2

rse1 O2

1.5

0.05

se3 C X

rCO se22 1

0 10

15

20

25

30

35

40

45

r CO 2 Carbon dioxide utilization rate ,(mmol C .L-1.h-1)

0.2

3

2

C X Biomass concentration,(mmol C.L-1) r O Oxygen utilization rates,(mmol .L-1.h-1)

8

50

Time (hours) Fig. 4. The effect of adjusting solution pH of a chemostat previously at pH 1.30 to pH 1.00 at the same residence time, 16 h on O2, CO2 uptake rates and biomass concentration.

maximum biomass yield, into the equation derived for CX by the authors (Gahan et al., 2010; Sundkvist et al., 2008). Assuming a negligible maintenance coefficient value (typical of an actively growing culture), the same trend can be obtained for the CX vs. the D curves (analysis not shown). From Fig. 3 the dilution rate at which the microbial population peaked appeared to be independent of the solution pH, as it remained the same over the range of pH investigated. The biomass concentration increased as the pH increased from 0.8 to 2.0. The figure also shows that the biomass did not increase significantly from pH 1.3 to pH 2.0, which might explain the conclusion made by Breed and Hansford (1999) that CX is independent of pH in the range 1.1 – 1.7. It can be seen from Fig. 4 that the steady state biomass concentration, CX decreases as the solution pH of the chemostat is decreased from 1.3 to 1.0, primarily due to a drop in rCO2while rO2remains more or less constant. A possible explanation for this trend is that a high acid environment beyond the optimum may impose additional stress on the cell since the microbial cytoplasm must be maintained closed to neutrality. The decrease in the biomass could also be related to lower solubility of CO2 at lower pH. 3.4. Energetic parameters – yield and maintenance coefficients The parameters were determined by assuming that the energy derived from ferrous ion oxidation is channelled to microbial growth and cell maintenance (Pirt, 1982). The maximum biomass max yield, YFe 2 +X and maintenance coefficient, mFe2 +, on ferrous ion (Table 1) were determined using the Pirt equation (Ojumu, 2008). By plotting the specific ferrous ion utilization rate vs. dilution rate max (Fig. 5a), YFe 2 +X and mFe2 + can be obtained from the slope and intercept of the resulting linear graph. The results, (Fig. 5b), showed that the maintenance coefficient can be represented by a quadratic function as determined in a previous study (Ojumu et al., 2009). A minimum mFe2 +occurred at around pH 1.3, and it increases on either side of the minimum. However, the values are very small, not contributing

significantly to the microbial energy demand. This is typical of an actively growing culture in a chemostat (Ojumu, 2008; Ojumu et al., 2009). It is this small magnitude of the maintenance coefficient that is responsible for the trend of CX vs. D curves (Fig. 3), when substituted into the theoretical equation for CX developed by Sundkvist et al. (2008). max The maximum biomass yield on ferrous ion,YFe 2 +X, increases linearly with increasing solution pH within the pH range investigated (Fig. 5b). The low maximum biomass yield at pH 0.8 can be attributed to proton inhibition or CO2 limitation in high proton environment, similar to CX, while the high value at pH 2.0 appeared to be contradictory to the fact that microbial cell/oxidizing activity is adversely affected at pH beyond 2.0 (van Aswegen et al., 2007). This high value might be due to the microbial attachment to ferric precipitate (jarosite) at high pH (Kinnunen and Puhakka, 2004). 3.5. The kinetic parameters max The maximum specific ferrous ion, qFe 2 + and the apparent affinity constant,K′Fe2 +, shown in Table 1 were averages of the values obtained from Lineweaver–Burk plot of Eq. 2 (figure not shown) and the fit of the experimental data to the same equation (Fig. 6) using sum of square error minimization technique as described previously (Ojumu et al., 2009). There is a good agreement between experimental and predicted values of qFe2 +(shown by the solid lines in Fig. 6). The maximum specific rates qFe2 +max varied with solution pH in a quadratic fashion (Eq. (7)) as shown in Fig. 7, increasing from pH 0.8 to a maximum value at pH 1.3, and decrease thereafter with further increase in pH. The decreased rates at lower pH (though still higher than values reported for common mesophiles like At. ferrooxidans (Boon, 1996)), indicated an inhibitory effect as the cell was faced with the challenge of maintaining neutrality of the cytoplasmic pH. The reduction of qFe2 +maxat increasing pH (above 1.3) could be explained by the fact that protons are an essential reagent of the oxidation process. Although maximum biomass yield and concentration

Table 1 The energetic and kinetic parameters of L. ferriphilum at various solution pH. pH

0.8 1.0 1.3 1.6 2.0

Energetic parameters

Kinetic parameters

Overall model prediction

2 max YFe 2 +X× 10

mFe2 +

R2

max qFe 2+

K′Fe2 +× 102

R2

max qFe 2+

K′Fe2 +× 102

R2

0.70 0.75 0.80 0.86 1.00

0.61 0.37 0.09 0.11 0.57

0.989 0.997 0.993 0.968 0.986

9.71 12.87 14.54 12.00 10.42

0.067 0.078 0.141 0.111 0.367

0.989 0.997 0.993 0.968 0.986

10.02 12.6 14.72 13.77 11.21

0.052 0.090 0.162 0.234 0.330

0.863 0.934 0.947 0.803 0.813

2+ − 1 2+ max max Units: YFe 2 +X [mmol C (mmolFe ) ], mFe2 +[mmolFe2+ (mmol C h)− 1], qFe 2 +X [mmol C (mmol Fe h)− 1] K′Fe2 +dimensionless.

T.V. Ojumu, J. Petersen / Hydrometallurgy 106 (2011) 5–11

0.014

1

2.00

0.00 0.00

0.02

0.04

0.06

0.08

YFe

2+

4.00

max

pH 0.80 pH 1.00 pH 1.30 pH 1.60 pH 2.00

R =0 .991

YFemax =0 .003 pH 0.005 2+ X

0.8

0.010

0.7 0.6

0.008

0.5 0.006

0.4 0.3

0.004

0.002

0.10

0.9

R 2 =0 .973

2+

(mmol C.(mmol Fe2+)-1)

6.00

X

8.00

2+

(mmol Fe2+. (mmol C)-1.h-1)

10.00

4.11 pH +2. 99

2

(mmol Fe2+. (mmol C)-1.h-1)

mFe2+ =1.45( pH ) 0.012

12.00

2

0.000 0.5

1

Dilution rate, D (h-1)

1.5

max Fe 2+ X

Y

0.2

m Fe 2+

0.1

mFe

14.00

qFe

9

0 2.5

2

Solution pH

Fig. 5. (a) Variation of specific microbial ferrous ion oxidation rate with dilution rate. (b) Variation of maximum biomass yield and maintenance on ferrous ion utilisation with solution pH.

increased with increase in pH while qFe2 +max decreased with increased pH above pH 1.3, the result indicated that biomass activity was inhibited under this condition, and that the cells were less efficient as the cell concentration increases, since qFe2 +max (i.e. oxidation rate per cell) declined (Petersen and Ojumu, 2007). This observation supported the trend reported by van Aswegen et al. (2007). The results suggest that a solution pH of 1.3 appear to be an optimum condition for the cell where microbial activity was maximum. The apparent affinity constant, K′Fe2 +appeared to be linearly dependent on pH (Fig. 7), it increases with increase in solution pH. This can be represented by a linear function, Eq. (8). q

max

Fe2+

2

= 33:63ð pHÞ−11:54ð pHÞ −9:49;

K ′ 2+ = 2:4 × 10 Fe

−3

−3

ðpHÞ−1:5 × 10

;

2

ð7Þ

2

ð8Þ

R = 0:96 R = 0:93

Although Breed and Hansford (1999) also reported that the apparent affinity constant is linearly dependent on pH, they observed,

however, that the maximum biomass utilization rate remains constant and is independent on pH. It is noted here that the latter investigation was carried out over a comparatively narrow pH range (pH 1.1 to 1.7). However, by comparison with Breed and Hansford data (1999), it can be seen that the rate is relatively insensitive around the optimum pH (see Fig. 7). The data point at pH 1.6 is considered an outlier in this study. Tan et al. (1998) have shown, using statistical thermodynamic modelling, that several relationships, such as asymmetric and symmetric bell-shaped curves, exist between specific growth rate and solution pH. However, the relationship between the maximum max microbial specific iron utilization rates,qFe 2 +, and the solution pH in this study can be said to follow a bell-shaped curve (Plumb et al., 2008) with an optimum pH at about 1.3 (see Fig. 7). The quadratic function, Eq. (7) fits the data very accurately (R2 = 0.96). The fact that our study was conducted in a continuous mode precludes a direct comparison with the previous work of Plumb et al. (2008) which was conducted within the pH values similar to this study. However, it is unlikely that pH 2.0, associated with jarosite formation, would

16 20

0.007 = -11.54(pH)2+ 33.63(pH) -9.49 R2 = 0.964

pH 0.80

10

pH 1.00 pH 1.30

8

pH 1.60 pH 2.00

6 4

q

2

16

0.006

0.005 12

0.004

0.003

KFe qFe

8

2+

max 2+

0.002

2+

12

Breed & Hansford [4]

KFe

Maximum biomass activity

max 2+

Apparent affinity constant

qFe

max Fe2+

qFe

2+

(mmol Fe2+.(mmol C)-1h-1)

14

4 0.001

KFe

= 2.4 x 10-3 pH-1.5x10-3

2+

0 10

100

1000

10000

100000

[Fe3+]/[Fe2+]

R2 = 0.933

0 0

0.5

1

1.5

2

0 2.5

Solution pH Fig. 6. The plot of specific ferrous ion oxidation rate at different ferric-to-ferrous ratio [the solid lines represent the fit of experimental data to Eq. (2) Excel Solver routine while the dotted lines represent the plot of Eq. (7)].

max Fig. 7. Variation of maximum specific rates, qFe 2 + (for this study and Breed & Hansford data), and apparent affinity constant, K′Fe2 +, with solution pH.

10

T.V. Ojumu, J. Petersen / Hydrometallurgy 106 (2011) 5–11

represent an optimum condition for the oxidation of ferrous ion by L. ferriphilum (du Plessis et al., 2007; van Aswegen et al., 2007). Therefore by substituting the expressions for qFe2 +max and K′Fe2 +into the simplified competitive inhibition model, Eq. (2), a model which predicts qFe2 +as a function of the ferric to ferrous ion ratio across the range of solution pH investigated can be obtained (Eq. (9)).

qFe2+ =

2 33:63ð pHÞ−11:54ð pHÞ −9:49     1 + 2:4 × 10−3 ð pHÞ−1:5 × 10−3 Fe3 + = Fe2

+



ð9Þ

The model predicts experimental data to within 80–95%, as shown by the dotted lines in Fig. 6. 4. Conclusions This study has shown that the relationship between the specific microbial ferrous ion oxidation rate of L. ferriphilum and solution pH follows a symmetrical bell-shaped curve which can be described by a quadratic function Eq. (5). The biomass activity increased with increasing solution pH up to a maximum at pH 1.3, followed by a decreasing trend. The energetic parameters obtained from the Pirt equation showed that the maximum biomass yield on ferrous ion, unlike the effect of temperature (Ojumu et al., 2009), increased linearly with an increase in solution pH (Breed and Hansford, 1999). It was also shown that loss of iron due to ferric ion precipitation increased with the increase in solution pH; it was negligible at pH 0.8 while over 12% Fe(III) was lost at pH 2.0. This condition is undesirable in a typical bioleach heap operation, as usually a marginal iron concentration needs to be kept in solution in order to sustain the leaching process. The 12 g L− 1 total iron used in this study is much larger than the concentration in heaps (0.1–5 g L− 1). From the results extrapolated at lower potentials using Eq. (7), the maximum specific rates obtained at pH 0.8 (9.20 mmol Fe2+(mmol C)− 1 h− 1 ) was only about 75% of the rate achievable at pH 1.30. This value is still greater than the reported values for most mesophilic bioleaching microbes. In the context of heap bioleaching, the results of this study suggest that operating a bioleach heaps within pH 0.8 and 1.3 would conserve the low iron concentration associated with typical bioleach heaps. This challenge could be managed by keeping the solution pH at below 1.00 at start-up. However, lowering of pH would have to be done with some caution, as this could also increase the solution ionic strength due to the dissolution of gangue minerals. Therefore, periodic purging of the PLS would be necessary to remove undesired salts (cations and anions) once they reach a level where they may be toxic/inhibitory to the microbial community (Blight and Ralph, 2004; Shiers et al., 2005). The knowledge of the microbial tolerance limit of these salts is essential in this regard, some of which has been discussed previously (Blight and Ralph, 2004; Ojumu et al., 2008; Shiers et al., 2005).

5. Nomenclature and units Symbol

Description

Unit

rFe2 + rO2 rCO2 qFe2 + max qFe 2+

Ferrous-iron oxidation rate Oxygen consumption rate Carbon dioxide consumption rate Specific ferrous-iron oxidation rate Maximum specific ferrous-iron oxidation rate Apparent substrate affinity constant Biomass concentration Dilution rate Maximum biomass yield constant Maintenance coefficient on ferrous-iron

mmol Fe2 +(L.h)-1 mmol O2(L.h)-1 mmol CO2(L.h)-1 mmol Fe2 +(mmol C h)-1 mmol Fe2 +(mmol C h)-1

K′Fe2 + CX D max YFe 2 +X mFe2 +

Dimensionless mmolC L-1 h− 1 mmol C (mmol Fe2 +)-1 mmol Fe2 +(mmol C h)-1

Acknowledgements The authors wish to acknowledge the contribution of Emeritus Professor Geoffrey S. Hansford (1939–2010) to this study. Geoff will be remembered for his formidable intellect, his compassion and his passion for research and scholarship. References Blight, K.R., Ralph, D.E., 2004. Effect of ionic strength on iron oxidation with batch cultures of chemo-lithotrophic bacterial. Hydrometallurgy 73, 325–334. Boon, M., 1996. Theoretical and experimental methods in the modelling of biooxidation kinetics of sulphide minerals, PhD Thesis. Technical University, Delft, Netherlands, 453 pp. Boon, M., Hansford, G.S., Heijnen, J.J., 1995a. Recent developments in modelling biooxidation kinetics. Part II: Kinetic modelling of the bio-oxidation of sulphide minerals in terms of critical sub-processes involved. In: Holmes, D.S., Smith, R.W. (Eds.), Proceedings of Engineering Foundation Conference, July 1994. Minerals Bioprocessing II. The Minerals Metals and Materials Society, Warrendale, Pennsylvania, pp. 63–68. Boon, M., Heijnen, J.J., Hansford, G.S., 1995b. Recent developments in modelling biooxidation kinetics. Part I. Measurement methods. In: Holmes, D.S., Smith, R.W. (Eds.), Proceedings of Engineering Foundation Conference, July 1994. Minerals Bioprocessing II. The Minerals Metals and Materials Society, Warrendale, Pennsylvania, pp. 41–61. Breed, A.W., 2000. Studies on the mechanism and kinetics of bioleaching with special reference to the bioleaching of refractory gold-bearing arsenopyrite/pyrite concentrates, PhD Thesis. University of Cape Town. Breed, A.W., et al., 1999. The effect of temperature on the continuous ferrous-iron oxidation kinetics of a predominantly Leptospirillum ferrooxidans culture. Biotechnology and Bioengineering 65, 44–53. Breed, A.W., Hansford, G.S., 1999. Effect of pH on ferrous-iron oxidation kinetics of a predominantly Leptospirillum ferrooxidans culture. Biochemical Engineering Journal 3, 193–201. Coram, N.J., Rawlings, D.E., 2002. Molecular Relationship between Two Groups of the Genus Leptospirillum and the Finding that Leptospirillum ferriphilum sp. nov. Dominates South African Commercial Biooxidation Tanks That Operate at 40 °C. Applied and Environmental Microbiology 68, 838–845. du Plessis, C.A., Batty, J.D., Dew, D.W., 2007. Commercial application of thermophile bioleaching. In: Rawlings, D.E., Johnson, D.B. (Eds.), Biomining. Springer, Berlin, pp. 57–80. Gahan, C.S., Sundkvist, J.-E., Dopson, M., Sandström, Å., 2010. Effect of chloride on ferrous iron oxidation by a Leptospirillum ferriphilum-dominated chemostat culture. Biotechnology and Bioengineering 106 (3), 422–431. Ingledew, W.J., 1982. Thiobacillus Ferrooxidans the bioenergetics of an acidophilic chemolithotroph. Biochimica et Biophysica Acta - Bioenergetics 683, 89–117. Kinnunen, P.H.-M., Puhakka, J.A., 2005. High-rate iron oxidation at below pH 1 and at elevated iron and copper concentrations by a Leptospirillum ferriphilum dominated biofilm. Process Biochemistry 40, 3536–3541. Kinnunen, P.H.M., Puhakka, J.A., 2004. High-rate ferric sulfate generation by a Leptospirillum ferriphilum-dominated biofilm and the role of jarosite in biomass retainment in a fluidized-bed reactor. Biotechnology and Bioengineering 85 (7), 697–705. Nemati, M., Harrison, S.T.L., Hansford, G.S., Webb, C., 1998. Biological oxidation of ferrous sulphate by Thiobacillus ferrooxidans: a review of kinetic aspects. Biochemical Engineering Journal 1, 171–190. Ojumu, T.V., 2008. The effects of solution conditions on the kinetics of microbial ferrous-iron oxidation by Leptospirillum Ferriphilum in continuous culture, PhD Thesis, University of Cape Town, South Africa, 245 pp. Ojumu, T.V., Hansford, G.S., Petersen, J., 2009. The kinetics of ferrous-iron oxidation by Leptospirillum ferriphilum in continuous culture: the effect of temperature. Biochemical Engineering Journal 46 (2), 161–168. Ojumu, T.V., Petersen, J., Hansford, G.S., 2008. The effect of dissolved cations on microbial ferrous-iron oxidation by Leptospirillum ferriphilum in continuous culture. Hydrometallurgy 94 (1–4), 69–76. Ojumu, T.V., Petersen, J., Searby, G.E., Hansford, G.S., 2006. A review of rate equations proposed for microbial ferrous-iron oxidation with a view to application to heap bioleaching. Hydrometallurgy 83, 21–28. Özkaya, B., Nurmi, P., Sahinkaya, E., Kaksonen, A.H., Puhakka, J.A., 2007a. Temperature effects on the iron oxidation kinetics of a Leptospirillum ferriphilum dominated culture at pH below one. Advanced Materials Research 20–21, 465–468. Özkaya, B., Sahinkaya, E., Nurmi, P., Kaksonen, A.H., Puhakka, J.A., 2007b. Iron oxidation and precipitation in a simulated heap leaching solution in a Leptospirillum ferriphilum dominated biofilm reactor. Hydrometallurgy 88 (1–4), 67–74. Özkaya, B., Sahinkaya, E., Nurmi, P., Kaksonen, A.H., Puhakka, J.A., 2007c. Kinetics of iron oxidation by Leptospirillum ferriphilum dominated culture at pH below one. Biotechnology and Bioengineering 97 (5), 1121–1127. Penev, K., Karamanev, D., 2010. Batch kinetics of ferrous iron oxidation by Leptospirillum ferriphilum at moderate to high total iron concentration. Biochemical Engineering Journal 50 (1–2), 54–62. Petersen, J., 2001. Understanding the Dynamics of Copper Sulphide Bioheap Leaching at Zaldivar. Petersen, J., Ojumu, T.V., 2007. The effect of total iron concentration and iron speciation on the rate of ferrous iron oxidation kinetics of Leptospirillum ferriphilum in continuous tank systems. Advanced Materials Research 20–21, 447–451.

T.V. Ojumu, J. Petersen / Hydrometallurgy 106 (2011) 5–11 Pirt, S.J., 1982. Maintenance energy: a general model for energy limited and energy sufficient growth. Archives of Microbiology 133, 300–302. Plumb, J.J., Muddle, R., Franzmann, P.D., 2008. Effect of pH on rates of iron and sulfur oxidation by bioleaching organisms. Minerals Engineering 21 (1), 76–82. Shiers, D.W., Blight, K.R., Ralph, D.R., 2005. Sodium sulphate and sodium chloride effects on batch culture of iron oxidising bacteria. Hydrometallurgy 80, 75–82. Sundkvist, J.E., Gahan, C.S., Sandström, Å., 2008. Modeling of microbial ferrous iron oxidation by Leptospirillum ferrooxidans in a continuous bioreactor. Biotechnology and Bioengineering 99 (2), 378–389.

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Tan, Y., Wang, Z.-X., Marshall, K.C., 1998. Modeling pH effects on microbial growth: a statistical thermodynamic approach. Biotechnology and Bioengineering 59 (6), 724–731. van Aswegen, P.C., van Niekerk, J., Olivier, W., 2007. The BIOX process for the treatment of refractory gold concentrates. In: Rawlings, D.E., Johnson, D.B. (Eds.), Biomining. Springer, Berlin, pp. 2–33. van Scherpenzeel, D.A., Boon, M., Ras, C., Hansford, G.S., Heijnen, J.J., 1998. Kinetics of ferrous iron oxidation by Leptospirillum bacteria in continuous cultures. Biotechnology Progress 14, 425–433. Vishniac, W., Santer, V., 1957. The Thiobacilli Bacteriology Reviews 21, 195–213.