Bioresource Technology 102 (2011) 10585–10591

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Bioresource Technology

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Analysis of petroleum biodesulfurization in an airlift bioreactor usingresponse surface methodology

Zahra Azimzadeh Irani a,b, Mohammad Reza Mehrnia a,⇑, Fatemeh Yazdian c, Majid Soheily b,Ghasemali Mohebali b, Behnam Rasekh b

a School of Chemical Engineering, University College of Engineering, University of Tehran, P.O. Box 11155-4563, Tehran, Iranb Research Institute of Petroleum Industry, P.O. Box 14665-1998, Tehran, Iranc Department of Life Science Engineering, Faculty of Disciplinary New Science and Technologies, University of Tehran, P.O. Box 14395-1561, Tehran, Iran

a r t i c l e i n f o

Article history:Received 29 May 2011Received in revised form 26 August 2011Accepted 29 August 2011Available online 5 September 2011

Keywords:Petroleum biodesulfurizationGordonia alkanivorans RIPI90AAirlift bioreactorVolumetric gas liquid mass transfercoefficientResponse Surface Methodology

0960-8524/$ - see front matter � 2011 Elsevier Ltd. Adoi:10.1016/j.biortech.2011.08.120

⇑ Corresponding author. Tel.: +98 21 66112184; faxE-mail address: mmehrnia@ut.ac.ir (M.R. Mehrnia

a b s t r a c t

For the first time, growing cells of Gordonia alkanivorans RIPI90A were used for biodesulfurization (BDS)of diesel. This process was carried out in an internal airlift bioreactor. BDS parameters (oil/water phaseratio and initial sulfur concentration) were optimized in flasks using response surface methodology. Pre-dicted results were found to be in good agreement with experimental results. Initial sulfur concentrationhad a remarkable effect on BDS process. Maximum removal of sulfur (21 mg/l) can be achieved at oil/water phase ratio of 25% (v/v) and initial sulfur concentration of 28 mg/l. Moreover, effect of superficialgas velocity (Ug) and working volume (v) on volumetric gas liquid mass transfer coefficient was studied inan airlift bioreactor for BDS of diesel. The best results were achieved at Ug and v of 2.5 l/min and 6.6 l,respectively. Subsequently, BDS of diesel was investigated in an airlift bioreactor under optimized condi-tions. Sulfur reduction after 30 h was 14 mg/l.

� 2011 Elsevier Ltd. All rights reserved.

1. Introduction

Sulfur oxide emissions to the atmosphere due to the combustionof sulfur containing compounds in fossil fuels such as diesel and gas-oline can cause acid rain and air pollution (EPA, 2011). Sulfur freediesel is ordered by strict current environmental regulations(McFarland, 1998; Oshiro et al., 1999; Monticello, 2000; Maghsoudiet al., 2001). Diesel can be treated by hydrodesulfurization (HDS)method (Chowdhury et al., 2002; Soleimani et al., 2007). HDS is car-ried out at high temperature and high pressure on a catalyst (CoMo,NiMo, etc.) in the presence of hydrogen. Most sulfur in diesel can betreated easily in this process but recalcitrant organic sulfur part canbe removed under invasive and costly conditions (McHale, 1981; Maet al., 1994; Monticello, 1998; Singh et al., 2001). Other methodssuch as biodesulfurization (BDS) remove recalcitrant molecules un-der ambient pressures and temperatures (Arenskötter et al., 2004;Caro et al., 2008). The remained recalcitrant molecules are mainlyfrom the dibenzothiphene (DBT) chemical group (Monticello,1998). It has been previously reported that Gordonia alkanivorans RI-PI90A can convert DBT and DBT containing hexadecane to 2-hydrox-ybiphenyl (2-HBP) via 4S pathway during both the growth and

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: +98 21 66954041.).

resting stages in a biphasic system (Mohebali et al., 2007a,b). Di-methyl sulfoxide (DMSO) was also reported as an appropriate sulfursource for the mass production of G. alkanivorans RIPI90A and the ef-fect of DMSO concentrations was investigated on the growth rate ofthis strain (Mohebali et al., 2008).

Sulfur containing feedstock and the biocatalyst, usuallysuspended in the aqueous phase have to be contacted with eachother in a bioreactor. In order to avoid mechanical stirring, whichputs stress on capability of microorganism, different types of biore-actors have been proposed, the majority of which are loop bioreac-tors (Mehrnia et al., 2004a,b; Yazdian et al., 2009, 2010). Loopbioreactors are characterized by a definitely directed circulationflow, which can be driven in fluid or fluidized systems by a propelleror jet drive and most typically in gas–liquid systems by an airliftdrive or liquid pump. They are particularly suitable for fluid sys-tems requiring high dispersion priority. On the other hand, theirsimple constructions and operation result in low investment andoperational costs (Mehrnia et al., 2004a,b; Yazdian et al., 2009,2010). The use of multistage airlift reactors may reduce the costof mixing and overcome poor reaction kinetics and to achieve con-tinues growth and regeneration of the biocatalyst in the same sys-tem rather than in a separate reactor (Monticello, 1998). In thedesign of the draft tube airlift reactor, higher oxygen utilization isan advantage over mechanically stirred bioreactors. Therefore, ifwhole cells were used as biocatalyst, then less shear damage would

10586 Z.A. Irani et al. / Bioresource Technology 102 (2011) 10585–10591

occur. The absence of mechanical stirring systems also translatesinto lower capital and operating costs (Mehrnia et al., 2004b). Thedraft tube airlift bioreactor was studied using water in kerosene mi-cro emulsions (Mehrnia et al., 2004a). The effect of draft tube areaversus the top section area on various parameters was studied. Also,the effect of gas flow rate on recirculation and gas carry over due toincomplete gas disengagement was considered (Mehrnia et al.,2004b). The oil/water ratio and viscosity effects on gas hold-upand mass transfer coefficient was tested as well (Mehrnia et al.,2005; Yazdian et al., 2009, 2010). In addition, the significance of ri-ser to down comer cross sectional area, volume of gas–liquid sepa-rator value and superficial gas velocity amount on mixing time, gashold-up and volumetric gas–liquid mass transfer coefficients in anexternal airlift loop bioreactor were investigated (Yazdian et al.,2009). BDS of water–kerosene emulsions with resting cells of differ-ent strains was studied at 100 ml scale and in an airlift bioreactor(Sanchez et al., 2008). Moreover, an experimental and modelingstudy of BDS of hydrodesulfurized diesel in a trickle bed reactor(Mukhopadhyaya et al., 2006) and an airlift reactor (Nandi, 2010)was also performed.

Response Surface Methodology (RSM) is used to examine therelationship between one or more response variables and a set ofquantitative experimental factors. This method is often employedafter a ‘‘vital few’’ controllable factors have been identified in orderto find the factor settings that optimize the response. Central Com-posite Design (CCD) and Box-Behnken Design (BBD) of RSM arefractional factorial designs for optimization of variables with a lim-ited number of experiments (Hasan et al., 2010; Wu et al., 2010).

Investigations on BDS processes have been mostly devoted tothe physiology of organisms, metabolic pathways of sulfur reduc-tion and kinetic parameters of the reaction of both model and die-sel oils (Folsom et al., 1999; Chang et al., 2001; Guchhait et al.,2005; Rashtchi et al., 2006; Guobin et al., 2006; Mohebali et al.,2007, 2008; Hewitt and Nienow, 2007; Caro et al., 2008; Azim-zadeh Irani et al., 2011). Moreover, in the previous works for BDSprocesses of fossil fuels in the airlift bioreactors (Folsom et al.,1999; Guobin et al., 2006; Yang et al., 2007; Sanchez et al., 2008;Nandi, 2010), there is no data for significant factors and especiallyoptimization of operational parameters based on statisticalanalysis.

In this study, the growing cells of G. alkanivorans RIPI90A wereused for BDS of diesel in an internal airlift bioreactor. The effect ofinitial sulfur concentration on growth and sulfur reduction duringthe growth phase were investigated. The RSM technique was usedto optimize the BDS of diesel by RIPI90A cells between twovariables (oil/water phase ratio and initial sulfur concentration)in batch shake flasks. Moreover, superficial gas velocity (Ug) andworking volume (v; related to the liquid level above the risersection) were used to optimize gas liquid mass transfer coefficient(kLa) in an airlift bioreactor for an emulsion of 30:70 diesel/water.Finally, BDS process was investigated under the optimum condi-tions in the airlift bioreactor as well.

2. Methods

2.1. Biocatalyst

The biocatalyst used was growing cells of G. alkanivoransRIPI90A. This strain was selected among 23 strains that were gath-ered on the basis of their growth rate and extent of desulfurizationfrom all around Iran. The detailed description of the biocatalyst isreported by Mohebali et al. (2007a,b). This aerobic Gram (+) strainwas maintained as a suspension in nutrient broth containing 20%(v/v) glycerol, at �70 �C and also on glass beads under the sameconditions.

2.2. Chemicals

All chemicals were of analytical grade. Normal hexadecane andDBT were purchased from Merck. N,N0-dimethylformamide (DMF)were obtained from Riedel- de Haën.

2.3. Diesel

Diesel oil having the following specification was used; initialboiling point: 250 �C final boiling point: 385 �C specific gravity:8370 kg/m3 and sulfur content: 30 mg/l.

2.4. Micro-organism and culture conditions

The culture was initially grown in 250 ml Erlenmeyer flask con-taining 100 ml of minimal salt (MS) medium having the composi-tion (gram per liter of deionized water) KH2PO4 (6), Na2HPO4 (4),NH4NO3 (1.2), MgCl2 � 6H2O (0.75), MnCl2 � 4H2O (0.004),CaCl2 � 2H2O (0.001), FeCl3 (0.001), containing 2 g/L sodium benzo-ate as carbon source (MS-SB) medium. DMF was used as co-solventin which DBT was dissolved and then added to the medium as sul-fur source. The pH was adjusted prior to autoclaving to 7.08. Allinoculated liquid media were incubated at 30 �C on a rotary shakeroperated at 120 rpm for 72 h.

2.5. Batch growth and biodesulfurization study

In this study, diesel with different initial sulfur concentrationswas used. It is assumed that all the sulfur compounds in dieseloil were lumped into a pseudo-compound and then diluted at dif-ferent dilution ratios using hexadecane to give final sulfur concen-trations. Batch experiments were performed in 100 ml Erlenmeyerflasks containing MS-SB supplemented with diesel oil at desiredoil/water phase ratios and initial sulfur concentrations. The reac-tion broths were always prepared with 10% (v/v) of initial biomassconcentration. The flasks were incubated at 30 �C on a rotary sha-ker operated at 120 rpm for a period of 30 h (Azimzadeh Irani et al.,2011). Following incubation, the content of each flask was centri-fuged (12000 rpm, 5 min). The organic phase was analyzed forremaining sulfur concentration in the sample by UV-fluorescencedetection (vario TRACE) for quantification of total sulfurconcentration.

2.6. Bioreactor description

Hydrodynamic characterization and BDS assays were evaluatedin an internal airlift bioreactor. Reactor vessel was 0.12 m in diam-eter and its overall height was 0.7 m. The draft-tube, 0.07 m ininternal diameter and 0.35 m tall, was located 0.06 m above thebottom of tank. The vessel was sparged in the concentric zonethrough a 0.0006 m diameter sparger. The working volume andthe overall volume of the reactor were 5 and 8 L, respectively. Adissolved oxygen electrode (Metteler Toledo, Switzerland) and apH-meter (Metteler Toledo, Switzerland) were placed in the biore-actor. Air was supplied to the reactor through a filter and arotameter.

2.7. Gas–liquid volumetric mass transfer coefficient (kLa)measurement

Determination of kLa was performed with loop sparger in anemulsion of 30:70 diesel/water. This parameter was evaluated fordesired superficial gas velocity (Ug) and working volume (v). ThekLa was measured with dynamic gassing in method (Shariatiet al., 2007; Yazdian et al., 2009). For each test, the fluid was deaer-ated by bubbling nitrogen. After stopping the nitrogen flow and

Table 1Coded and non coded values of the variables.

Coded and non coded values for optimization of BDS process

Independent variables �1.41 �1 0 +1 +1.41Oil–water phase ratio (%, v/v) X1 – 30 40 50 �Initial sulfur concentration (mg/l) X2 – 7 17.5 28 �

Coded and non coded values for optimization of kLaSuperficial gas velocity (l/min) X1 0.17 1.00 3.00 5.00 5.83Working volume (l) X2 5.80 6.00 6.50 7.00 7.20

Z.A. Irani et al. / Bioresource Technology 102 (2011) 10585–10591 10587

allowing the exit of its bubbles, the air started to flow until thefluid became nearly saturated with oxygen. The kLa was calculatedas the slope of the linear equation:

� lnð1� EÞ ¼ kLaðt � t0Þ ð1Þ

In Eq. (1), E is the fractional approach to equilibrium and can beestimated using following equation:

E ¼ ðC � C0Þ=ðC� � CÞ ð2Þ

where C⁄ is the saturation concentration of dissolved oxygen, C0 isthe initial concentration of dissolved oxygen at time t0 when ahydrodynamic steady-state has been reestablished upon the begin-ning of aeration and C is the dissolved oxygen concentration at anytime t.

2.8. Experimental design

Optimization of BDS process of diesel oil by growing cells of G.alkanivorans RIPI90A was carried out in 100 ml scale. Oil/waterphase ratio (X1) and initial sulfur concentration (X2) that were se-lected due to several preliminary tests, were regarded as effectivefactors for this process and the influence of these parameters onsulfur reduction was studied. Optimization of kLa in the airlift reac-tor for loop sparger was carried out in an emulsion of 30:70 diesel/water. Superficial gas velocity, Ug(X1) and working volume, v(X2)were selected as effective factors. CCD and RSM were used in orderto investigate the relationship between these variables and theoptimum levels of them. For this purpose, 9 experimental runswere required as per three-level two-factor fractional factorialCCD. The coded and non coded values of the variables are shownin Table 1 while the results and predicted responses are presentedin Table 2. Data from CCD were subjected to a second-order multi-ple regression analysis to explain the behavior of the system usingthe least squares regression methodology to obtain the parameterestimators of the mathematical model. The result may be ex-pressed as follow:

Y ¼ b0 þX

bi � Xi þX

bii � X2i þ

Xbij � Xij ð3Þ

where Y is the response, Xi is the independent variable, b0 is aconstant, bi is the slope or linear effect of the input factor, bii isthe quadratic effect of input factor, bij is the linear by linear interac-tion effect between the input factor.

Table 2Results of Central Composite Design (CCD) for BDS and kLa optimization.

Std Oil/water phase ratio (%) Initial sulfur concentration (mg/l) Sulfur reduc

1 �1 �1 0.02 1 �1 1.03 �1 1 21.04 1 1 21.05 �1 0 9.56 1 0 9.57 0 �1 0.08 0 1 21.09 0 0 8.5

2.9. Software used

MINITAB 16 was used for this regression analysis of the data ob-tained and to estimate the coefficients of the regression equation.

3. Results and discussion

3.1. Behavior of growing cells in biphasic media

It has been reported previously that resting cells of G. alkanivo-rans RIPI90A can convert DBT to 2-HBP via 4S pathway in a bipha-sic system (Mohebali et al., 2007a). It is assumed that in biphasicmedia, the transfer of DBT from the oil to the aqueous phase isone of the most determinant parameter in the BDS process. There-fore, using hydrophobic biocatalysts such as G. alkanivorans RI-PI90A cells are preferable because they are capable to be joinedat the oil/water interface for the uptake of DBT there. It was shownthat, resting and also growing cells of this strain have an affinity fororganic sulfur substrates and their ability of stabilizing the oil/water emulsion is related to cell surface hydrophobicity that maybe related to its cell surface long mycolic acids (Mohebali et al.,2007b).

In order to investigate the effect of sulfur on growth of theorganism, the growth of bacterium was monitored periodicallyfor different initial sulfur concentrations. The evolutions of the bio-mass concentration are shown in Fig. 1. As shown in this figure, theamount of maximum growth increases with increase of initial sul-fur concentration and maximum growth is obtained at 28 mg/l.This may be due to the increase of sulfur compounds availabilitythat causes better growth of biomass in biphasic media. Fig. 2shows sulfur reduction of diesel by growing cells of G. alkanivoransRIPI90A during the growth phase for different initial sulfur concen-trations. As shown in this figure, as the availability of initial sulfursubstrate increases, better growth of biomass causing higher rateof sulfur consumption. The capability of G. alkanivorans RIPI90Afor BDS process via 4s pathway and inhibition effects of 2-HBP pro-duction (Mohebali et al., 2007a) and transition from late exponen-tial to stationary phase, may cause the sulfur reduction ratebecomes constant after 30 h (Azimzadeh Irani et al., 2011).

3.2. Regression analysis

A quadratic polynomial model was established on the experi-mental results of CCD to identify the relationship between re-sponses and variables. The proposed model based on theregression coefficients for the sulfur reduction can be stated as:

Y ¼ 8:83þ 0:17X1 þ 10:33X2 þ 0:5X21 þ 1:5X2

2 � 0:25X1X2 ð4Þ

where Y is the response value of sulfur reduction (mg/l), X1 is theoil/water phase ratio (%) and X2 is the initial sulfur concentration(mg/l). The linear and square effects of X2 were found to be signif-icant (P < 0.1). A positive sign of the coefficient represents a syner-gistic effect, while a negative sign indicates an antagonistic effect.

tion (mg/l) Predict (mg/l) Ug (l/min) v (l) kLa (s�1) Predict (s�1)

0.083 �1 �1 0.0025 0.0030.92 1 �1 0.0066 0.007

21.25 �1 1 0.0150 0.01621.08 1 1 0.0058 0.006

9.17 �1.41 0 0.0119 0.0119.50 1.41 0 0.0056 0.0060.00 0 �1.41 0.0011 0.002

20.67 0 1.41 0.0110 0.0118.83 0 0 0.020 0.020

0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

1.8

0 5 10 15 20 25 30 35

Time (h)

Dry

Cel

l Wei

ght (

g/l

)

: 12 mg/l, : 14 mg/l, : 21mg/l, : 28mg/l

Fig. 1. Biomass growth of Gordonia alkanivorans RIPI90A for different initial sulfur concentrations.

Table 3ANOVA of the model for sulfur reduction (mg/l).

Term Degree of freedom Mean square F P

Model 5 129.217 930.36 0.000X1 1 0.167 1.20 0.353X2 1 640.667 4612.80 0.000

X21

1 0.500 3.60 0.154

X22

1 4.500 32.40 0.011

X1X2 1 0.250 1.80 0.272Residual 3 0.139 – –

R2 = 0.9994, R2 (adjusted) = 0.9983.

Table 4ANOVA of the model for kLa (s�1).

Term Degree of freedom Mean square F-value Probe

Constant 5 0.000060 72.11 0.003X1 1 0.000025 29.59 0.012X2 1 0.000083 99.60 0.002X1X2 1 0.000044 110.29 0.002

X21

1 0.000091 169.81 0.001

X22

1 0.000141 53.34 0.005

Residual 3 0.000001 – –

R2 = 0.9917, R2 (adjusted) = 0.9780.

Fig. 2. Sulfur reduction of diesel by growing cells of Gordonia alkanivorans RIPI90A during the growth phase for different initial sulfur concentrations.

10588 Z.A. Irani et al. / Bioresource Technology 102 (2011) 10585–10591

The interaction term of X1 and X2 had a negative relationship withthe BDS process while the variables X1, X2 and the quadratic termof X1 and X2 had positive effects. High value of the parameter esti-mate for X2 indicates the importance of initial sulfur concentrationin sulfur reduction. Regression analysis revealed a coefficient ofdetermination (R2) value of 0.9994 and adjusted coefficient ofdetermination (AdjR2) of 0.99 that indicates high dependence be-tween the observed and the predicted values of response (Table3).The relationship between mass transfer coefficient (kLa) andtwo variables in coded units can be expressed as:

Y ¼ 0:02� 0:001751X1 þ 0:003213X2 � 0:005606X21

� 0:006956X22 � 0:03325X1X2 ð5Þ

where Y is the response value of kLa, X1 is the superficial gas velocity(l/min) and X2 is working volume (l). The effect of all the linear,

square and interaction terms of X1 and X2 (P < 0.05) were found tobe significant on the kLa. A relatively high value of the parameterestimate for X2 and high values of coefficients of quadratic termof X2 and interaction term of X1 and X2 show a high value of signif-icance, indicating the importance of these variables on the kLa. Thevariable X2 had a positive significant relationship with the kLa whilethe variable X1 and quadratic terms of X1 and X2 and interactionterms of X1 and X2 had negative significant effects. Regression anal-ysis revealed a coefficient of determination (R2) value of 0.9917 andadjusted coefficient of determination (AdjR2) of 0.9780 that indi-cates high dependence between the observed and the predicted val-ues of response (Table 4).

3.3. Effect of parameters

The entire relationships between factors and response can bebetter understood by examining the planned series of contour

Fig. 3. Contour plot for sulfur reduction (mg/l).

Fig. 4. Contour plot for kLa (s�1).

Fig. 5. Process optimization curve for sulfur reduction.

Fig. 6. Process optimization curve for kLa.

Z.A. Irani et al. / Bioresource Technology 102 (2011) 10585–10591 10589

plots (Fig. 3 and Fig. 4) generated from the predicted models (Eqs.(4) and (5)).

Fig. 3 represents contour plot between the responses i.e. sulfurreduction (mg/l) and the combined effect of initial sulfur concentra-tion (mg/l) and oil/water phase ratio (%) on the removal of sulfur.The figure shows that the uptake was increased with the increasein initial sulfur substrate concentration and decrease of oil/waterphase ratio. Also, Fig. 4 represents contour plot between theresponses i.e. kLa (s�1) and the combined effect of superficial gasvelocity, Ug (l/min) and working volume, v (l) on the kLa (s�1). Thefigure shows that the value of kLa increased in the beginning anddecreased after increasing from middle values.

3.4. Interpretation of process optimization curve

Responses optimization helps to identify the factor settings thatoptimize a single response or a set of responses. It is useful indetermining the operating conditions that will result in a desirableresponse. In the present study, the goal for sulfur reduction usinggrowing cells of G. alkanivorans RIPI90A was to obtain a value ator near the target value of 21 mg/l. Uptake values less than 0 mg/l and greater than 28 mg/l were unacceptable. Both weight and

importance were set at 1. The optimum condition which is definedas the best combination of factor setting for achieving the opti-mum response, was found to be oil/water phase ratio (30%) andinitial sulfur concentration (28 mg/l) for a predicted response of21.25 and desirability score of 1 (Fig. 5).

In the airlift bioreactor, the goal for kLa was to obtain a value ator near the target value of 0.02. Moreover, kLa values less than0.001 and greater than 0.02 were unacceptable. Both weight andimportance were set at 1. The optimum condition which is definedas the best combination of factor setting for achieving theoptimum response, was found to be superficial gas velocity(2.5 l/min) and working volume (6.6 l) for a predicted response of0.0206 and desirability score of 1 (Fig. 6).

Table 5The sulfur removal comparison for different airlift bioreactors after 30 h.

Microorganism Substrate % Sulfur removal Remarks

RIPI 90A Diesel 50 This workGrowing cells30:70 diesel:aqueousRhodococcus sp. Diesel 0 Nandi (2010)Growing cells50:50 diesel:aqueousATCC 39327

Strain No. 06Kerosene 34

24Sanchez et al. (2008)Resting cells 50:50 kerosene:aqueous

Table 6The sulfur removal comparison for different bioreactors.

Microorganism Bioreactor Substrate % Sulfurremoval

Remarks

RIPI 90A Airlift Diesel 50 This work growing cells 30:70 diesel:aqueous After 30 hRhodococcus sp. Airlift Diesel 100 Nandi (2010) Growing cells50:50 diesel:aqueous

After 120 hATCC 39327

Strain No. 06Airlift Kerosene 64

53Sanchez et al. (2008) Resting cells 50:50 kerosene:aqueousAfter 7 days

R. globerulus DAQ3 Two-layer continues Diesel 12 Yang et al. (2007) Growing cells 20:80 diesel:aqueousAfter 120 h

Pseudomonas delafieldiiR-8

5-L reactor Diesel 47 Guobin et al. (2006) High cell concentration culture 16:84diesel:aqueousAfter 20 h

R. erythropolis I-19 Energy Bio systems Corp. 2 Lreactor

Middle distillate1850

67 Folsom et al. (1999) Resting cells 25:75 diesel:aqueous

Rhodococcus sp. Continues stirred tank Diesel 50–70 McFarland et al. (1998) Resting cells

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3.5. Sulfur removal of diesel oil in airlift bioreactor under optimizedconditions

In order to investigate the G. alkanivorans RIPI90A sulfurremoval under optimum conditions in the airlift bioreactor, thesuperficial gas velocity (Ug) and working volume (v) was set at2.5 l/min, 6.6 l respectively, and oil/water phase ratio of 30% andinitial sulfur concentration of 28 mg/l. The sulfur reduction in theairlift bioreactor was 14 mg/l after 30 h. The sulfur removal com-parison with previous works for different airlift bioreactors after30 h was shown in Table 5.As it is reported in Table 5, we obtainedbetter result. Although sulfur removal for ATCC 39327 and strainNo. 06 after 7 days were 64 and 53% respectively, high sulfurreduction rate is related to the first 24 h and no major changes isobserved in the last 48 h (Sanchez et al., 2008). Moreover, Rhodo-coccus sp. was used effectively to reduce sulfur level from500 mg/l to zero in 120 h but there is almost no change at first24 h and high sulfur reduction rate is related to last 48 h (Nandi,2010). The sulfur removal comparison with previous works for dif-ferent bioreactors was shown in Table 6. Although growing cells ofG. alkanivorans RIPI90A was used, sulfur removal of our work wasalmost similar to other works that used resting cells (Sanchez et al.,2008; Guobin et al., 2006; McFarland et al., 1998) or better (Yanget al., 2007). There are also better results than our work (Nandi,2010; Sanchez et al., 2008; Folsom et al., 1999). This is becauseof the difference of microorganisms and the operating conditions.Therefore, airlift bioreactors can be used as a potential for BDS pro-cesses of diesel or other fuels and the designed airlift bioreactor iswell-organized for this purpose.

4. Conclusion

RSM technique was used for optimization of BDS of diesel byRIPI90A cells in an airlift bioreactor. The initial sulfur concentrationwas selected as effective factor for optimization of sulfur reductionwhile superficial gas velocity (Ug) and working volume (v) wereselected as effective factors for optimization of liquid mass transfer

coefficient (kLa). The results of BDS under the optimum conditions(initial sulfur concentration, 28 mg/l; oil/water phase ratio, 30:70;superficial gas velocity, 2.51 l/min and working volume, 6.65 l)show that RSM is a helpful method to maximize sulfur reductionand the designed bioreactor is efficient for BDS of diesel.

Acknowledgements

The Iranian Research Institute of Petroleum Industry financedthis research. We thank Khalaf Faryadin and Rohollah Nikbakhtfor their contribution.

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