Chemical Engineering Science 61 (2006) 1237–1246www.elsevier.com/locate/ces

A simple model to predict the removal of oil suspensions from water usingthe electrocoagulation technique

Manuel Carmonaa,∗, Mohamed Khemisb, Jean-Pierre Leclercb, François Lapicqueb

aDepartment of Chemical Engineering, University of Castilla—La Mancha, Avda. de Camilo José Cela s/n, 13004 Ciudad Real, SpainbLaboratoire des Sciences du Génie Chimique, CNRS-ENSIC, BP 451, F-54001 Nancy, France

Received 30 November 2004; received in revised form 26 July 2005; accepted 23 August 2005Available online 30 September 2005

Abstract

A simple model has been developed to predict the removal of hydrocarbon fractions from wastewater using sacrificial Al anodes. Themodel was successfully applied to the interpretation of experimental data obtained in a laboratory electrochemical cell operated in a batchwisemanner. The adsorption equilibrium of organic matter on Al hydroxide was modelled using three equations, with the best results obtainedusing a Langmuir-type equation. The model was able to describe the effects of current density and pollutant concentration on the efficiency ofwastewater treatment. Different values were obtained for the parameters depending on the nature of the hydrocarbon suspension. Aluminiumhydroxide showed a far higher affinity for the oil/kerosene suspension but exhibited a higher capacity to remove heavy oil suspensions. Theremoval rates of pollutants were found to depend on the initial concentration and the current density. When the current density was sufficient todestabilise the emulsion, the zeta potential of the clear fraction measured at pH 7.0 became positive. This change was also characterised by asignificant reduction in turbidity. Furthermore, the application of higher current densities did not allow further treatment of the water. However,the efficiency of emulsion destabilisation was found to depend on the concentration and current densities that were too low were ineffective.� 2005 Elsevier Ltd. All rights reserved.

Keywords: Adsorption; Emulsion; Turbidity; Zeta potential

1. Introduction

Oil/water (O/W) emulsions are widely used in metal indus-tries, e.g., rolling mills, forges and metal workshops, becausethese emulsions exhibit properties that include lubrication, sur-face cooling, cleaning and corrosion prevention—all of whichare required by metals under mechanical operations. The mainproblem encountered with O/W emulsions is the substantialdegradation of some components with time at the workingtemperature, which usually ranges from 45 ◦C to 90 ◦C. Theseemulsions therefore need to be regularly replaced, often severaltimes per year. The emulsions have high oil contents, in therange 1 × 10−1–30 kg/m3 depending on the specific applica-tion, and metal contents and used oil suspensions are toxic andmust be treated in such a way that water recycling is possible.

∗ Corresponding author. Tel.: +34 926 295437; fax: +34 926 295318.E-mail address: Manuel.cfranco@uclm.es (M. Carmona).

0009-2509/$ - see front matter � 2005 Elsevier Ltd. All rights reserved.doi:10.1016/j.ces.2005.08.030

According to current environmental regulations, hydrocarbonconcentrations in wastewater must be below 1 × 10−2 kg/m3

(Ríos et al., 1998).Several techniques have been applied to treat these types of

waste. Lin and Lan (1998) used combined ultrafiltration andion exchange, reaching removal yields up to 91%. Ríos et al.(1998) employed inorganic salts as coagulants and removedmore than 90% of the initial oil content. Oil destabilisationwas reported by these authors to be favoured at higher temper-atures. Poolea and Cord-Ruwisch (2004) described the abilityof the aerobic microbial cultures to destabilise the emulsionand found that removal yields could reach 97% after 7 days oftreatment. Mostefa and Tir (2004) found that electrochemicalmethods in combination with a chemical process were suitablefor the separation of oil from oily wastewater and achieveda separation yield of almost 99% in the treatment of a con-centrated emulsion of 4 w/w%. Electrocoagulation has beenused for the treatment of wastewater by various authors, andseveral differences were found in comparison to the chemical

1238 M. Carmona et al. / Chemical Engineering Science 61 (2006) 1237–1246

coagulation process (Kumar et al., 2004; Larue and Vorobiev,2003; Holt et al., 2002).

Electrocoagulation (EC) is an effective process for the desta-bilisation of finely dispersed particles by removing hydrocar-bons, greases, suspended solids and even heavy metals fromdifferent types of waste water (Inan et al., 2004; Kumar etal., 2004; Chen et al., 2002; Sanchez-Calvo et al., 2003; Sauret al., 1996; Hosny, 1996). Aluminium or iron are usuallyused as electrodes and their cations are generated by disso-lution of sacrificial anodes upon the application of a directcurrent. The metal ions generated are hydrolysed in the elec-trochemical cell to produce metal hydroxide ions and onlyneutral M(OH)3 has a very low solubility (Duan and Gre-gory, 2003), mainly at pH values in the range 6.0–7.0 (Pinottiand Zaritzky, 2001; Gregor et al., 1997). Metal species reactwith negatively charged particles in the water to form flocs(Chen et al., 2002; Saur et al., 1996). The in situ generationof coagulants means that electrocoagulation processes do notrequire the addition of any chemicals. The gases producedduring the electrolysis of water and metal dissolution (Picardet al., 2000) allow the resulting flocs to flotate (Saur et al.,1996).

Although the electrocoagulation technique has been avail-able for more than a century, it now appears now to be oneof the most effective approaches. The design of an industrialplant and an electrocoagulation cell is mainly based on empir-ical knowledge, with little consideration of the electrocoagu-lation mechanism (Sanchez-Calvo et al., 2003). Hosny (1996)used a pseudo-first order kinetic with respect to the oil concen-tration to predict its time variation at different current densitieswith good accuracy. Nevertheless, this model is not able to pre-dict oil removal when the concentration tends to its asymptoticlevel at the end of the operation. In addition, this approach doesnot provide physical interpretation of the oil removal processfrom the liquid phase. The present paper involves the descrip-tion of a simple model for the prediction of the elimination ofsuspended organic matter and this relies upon the adsorptionproperties exhibited by aluminium hydroxide complexes (Inanet al., 2004; Kumar et al., 2004; Bache and Papavasilopoulos,2003).

The main objectives of the present study, which was con-ducted with two different organic emulsions, are asfollows:

(i) To develop a mathematical model that allows the pre-diction of the decrease in the amount of organic sus-pensions in the liquid phase with time, taking intoaccount the physicochemical interactions between theorganic matter and aluminium hydroxides at pH val-ues > 6.5. Kobya et al. (2003) found that under theseconditions the interactions can be considered as beingdue to physical adsorption of the organic matter on thecoagulants.

(ii) To evaluate the effects of the various physical parameterson the adsorption isotherm.

(iii) To select the most suitable adsorption model for the re-liable prediction of the course of electrocoagulation runsfor the removal O/W emulsions from wastewater.

2. Mathematical model

Model equations were derived on the basis of the followingsimplifying assumptions:

(i) The amount of aluminium (Al3+) that is produced in thecell is � times higher than the value predicted by Faraday’slaw. Experiments carried out by Khemis et al. (2004) withAl electrodes showed that the quantity of Al species dis-solved was higher than the value predicted by Faraday’slaw at alkaline pH for current densities varying from 100to 300 A/m2, with little effect on the nature of the sus-pended matter. The value of � was taken as 1.5 in theapplication of the model and this is in accordance with ex-perimental data published previously. Indeed, oxidation ofaluminium is produced in two ways: electrochemical oxi-dation at the anode and chemical attack on both electrodesurfaces (Cañizares et al., 2005; Kobya et al., 2003; Picardet al., 2000; Chen et al., 2000).The electrochemical oxidation reaction at the anode is rep-resented as

Al0 ⇒ Al3+ + 3e−. (1)

The presence of chloride ions catalyses the aluminium cor-rosion and this corrosion can produce more aluminiumhydroxide flocs (Shen et al., 2003). The cathode may bechemically attacked by OH− at high pH values with ahigh rate of hydrogen formation (Bayramoglu et al., 2004).Thus, the following overall reactions Eqs. (2) and (3) canenhance the dissolution of aluminium on the surface of thetwo electrodes depending on the pH (Chen et al., 2000).

2Al0 + 6H+ ⇒ 2Al3+ + 3H2(g), (2)

2Al0 + 6H2O + 2OH− ⇒ 2Al(OH)−4 + 3H2(g). (3)

In addition, the water reduction occurs on the cathode andleads to a great formation of OH− ions. These ions favorthe aluminium dissolution as mentioned above.

2H2O + 2e− ⇒ 2OH− + H2(g). (4)

(ii) The Al3+ species produced in the cell is entirely convertedto aluminium hydroxide Al(OH)3 in the reactor under thephysicochemical conditions of the process. This assump-tion is consistent with the electrocoagulation mechanismproposed by Saur et al. (1996) in which the reaction lead-ing to Al complex formation is fast and leads to variousforms of hydroxide. Al(OH)3 is the main species for pHvalues close to 7, according to the predominant zone dia-gram for aluminium hydroxide (Holt et al., 2002).

(iii) The metal hydroxides form the nucleus of colloidal parti-cles and adsorption takes place around the nucleus (Inanet al., 2004).

(iv) Solute concentration gradients do not exist inside the solidparticle: the concentration inside the particle is the ex-ternal solid concentration or the equilibrium concentra-tion. Growth of the solid particles around the hydroxide

M. Carmona et al. / Chemical Engineering Science 61 (2006) 1237–1246 1239

nanoparticles is ensured by the adsorption of organic mat-ter: initial solid particles are small in size and they grow byadsorption of organic species. The adsorption changes theproperties of aluminium hydroxide and allows flotation.

(v) The solid phase is always in equilibrium with the liq-uid phase. Freshly formed “sweep flocs” of amorphousAl(OH)3 have a large surface area and this allows a rapidexternal mass transfer rate: the overall process of adsorp-tion and trapping of colloidal particles is therefore a fastprocess (Kobya et al., 2003).

(vi) The oil does not undergo any chemical reaction within thereactor.

Taking into account the assumptions outlined above, themodel was developed as follows:

The flux of Al3+ species produced in the cell is given by

NAl3+ = �I

nI, (5)

where � is the faradaic yield of Al dissolution, I is the current,n is the number of electrons involved in the anode oxidation,and I is the Faraday constant.

Taking into account assumption (ii), Eq. (5) becomes

mAl(OH)3 = �I

nIPMAl(OH)3 , (6)

where mAl(OH)3 is the weight flux of Al(OH)3 and PMAl(OH)3

is the molecular weight of the Al(OH)3.The cell considered in the model was a parallel plate elec-

trode reactor, as used in previous investigations (Khemis et al.,2004). The hydrodynamic behaviour of the electrochemical cellwas assumed to be that of a plug flow reactor. Despite gas for-mation, the liquid flow rate in the cell was assumed to be un-changed. The mass balance for Al hydroxide in the cell can bewritten as

�CcAl(III)

�t= −u

�CcAl(III)

�x+ �

h

i

nIPMAl(OH)3 , (7)

where CcAl(III) is the aluminium hydroxide concentration in the

electrocoagulation cell at x, h is the electrode gap, CAl(III) is thealuminium hydroxide concentration in the reactor, i the currentdensity and u is the superficial velocity. Initial and boundaryconditions for the electrochemical cell are:

t = 0; 0 < x�L; CcAl(III) = 0, (8)

t > 0; x = 0; CcAl(III) = CAl(III), (9)

where L is the electrode length.The mass balance for the stirred-tank reactor is

dCAl(III)V

dt= F(Cc

Al(III)|x=L − CAl(III)), (10)

where V is the volume of the reactor and F is the liquid recir-culation flow rate.

Three different adsorption equilibrium isotherms were testedin order to model the experimental data.

Eq. (11) is a Langmuir-type empirical equation (LTEE) de-rived from ion exchange and has been successfully applied invarious investigations (Monteagudo et al., 2003; Bilba et al.,1999; De Lucas et al., 1998; Fernández et al., 1995; Costaet al., 1984).

q∗ = n∞KC∗

C0 + (K − 1)C∗ , (11)

where n∞ is the aluminium hydroxide capacity, q∗ and C∗ are,respectively, the solid and liquid phase equilibrium concentra-tions, C0 is the initial organic concentration, and K is the sep-aration factor.

Eq. (12) is the Langmuir equation (LE) that has been usedfor various gas–solid and liquid–solid isotherms. This equationis applicable for monolayer models, assuming that all activesites of the solid have the same affinity for the solute underinvestigation (Chern and Chien, 2002; Langmuir, 1915).

q∗ = n∞I KIC

∗

1 + KIC∗ , (12)

where n∞I is the total monolayer capacity of the Al hydroxide

and KI is the conditional Langmuir equilibrium constant.Eq. (13) is the Freundlich isotherm (FE), which is a con-

secutive layer model with unlimited sorption sites (Chern andChien, 2002; Freundlich and Heller, 1939).

q∗ = KIIC∗m, (13)

where KII is the conditional Freundlich stability constant andm is the mass action stoichiometric coefficient, which is equalto or lower than unity.

Taking into account assumptions (iv) and (v), the mass bal-ance between the liquid and the solid phase at the equilibriumcondition can be expressed as follows:

q∗ = C0 − C∗

CAl(III). (14)

The two-equation system was solved for each isotherm modelconsidered and this yielded the following relations:

For LTEE, the solution depends on the K value:

If K �= 1, C∗2 + (C0(2 − K) + n∞KCAl(III))

K − 1C∗

− C20

K − 1= 0, (15)

If K = 1, C∗ = C20

C0 + n∞CAl(III). (16)

For the Langmuir isotherm,

C∗2 + (1 + n∞I KICAl(III) − KIC0)

KIC∗ − C2

0

KI= 0. (17)

For the Freundlich isotherm,

KIICAl(III)C∗m + C∗ − C0 = 0. (18)

1240 M. Carmona et al. / Chemical Engineering Science 61 (2006) 1237–1246

The final model is formed by three equations, namely thepartial differential equation (7), differential equation (10) andfinally, one of Eqs. (15)–(18)—the choice of which dependson the isotherm used. Partial differential equation (7) is trans-formed into a system of l ordinary differential equations, withl being the number of nodes along the length of the cell. Thel + 1 differential equations were integrated numerically by thefourth-order Runge–Kutta method (Press et al., 1992). In thecase of the Freundlich isotherm, the Newton–Raphson methodwas used to find the positive root of Eq. (18) (Press et al.,1992). Two parameters are involved in the adsorption isotherm;Marquardt’s algorithm (Marquardt, 1963) was used to estimatethese parameters from the experimental data obtained in thepresent work or reported previously (Khemis et al., 2004).

A visual basic application was developed for the calculations.

3. Simulation results

Simulations were carried out to observe the effect of phys-ical parameters on the treatment process. The electrochemicalcell described in the experimental section was considered forthe calculations. Initial tests showed the low impact of the num-ber of nodes, i.e., the number of stirred vessels in the cascadesimulating the plug flow. In fact, modelling the cell by a singlestirred vessel led to Al hydroxide concentrations that were 3%lower in the tank reactor than the value obtained with a seriesof 100 small CSTRs with the same total volume.

The effect of the flow rate through the cell on the averageAl(III) concentration in the cell and in the reactor is shown inFig. 1. Lower flow rates result in higher Al(III) concentrationsin the cell and this is due to longer residence times. The concen-tration difference between the cell and the tank reactor is thenincreased. Conversely, smaller differences are obtained for highflow rates, but the gas generated at the electrodes can accumu-late in the cell and increase the ohmic resistance and thereforethe voltage required. As can be seen in Fig. 1, the model rep-resents very well the experimental data for aluminium forma-tion regardless of the current density used. However, flow ratesthat are too high may be detrimental to agglomerate formationduring the emulsion destabilisation. For the experimental set-up described below, a velocity in the order 6.2 × 10−2 m/s,corresponding to a flow rate of 6.2 × 10−6 m3/s in the cell un-der investigation, was found to correspond to suitable operatingconditions.

The effect of current density on the abatement yield of thecontaminant is represented in Fig. 2. The removal yield of wasteis higher with high current densities. This is due to high forma-tion rates of Al(OH)3 in the cell. However, for long operationtimes the liquid concentration reaches an asymptotic level andapplying further increases in current to the cell has no effect.This behaviour indicates that an optimum electrical charge canbe found and this corresponds to minimum energy consump-tion in the treatment.

The effect of the separation factor on the response curves fora fixed set of parameters is shown in Fig. 3. As expected, theremoval of pollutant from the wastewater decreases with lowerK values. The lowest value of K used gives an equilibrium

0 500 1000 1500 2000 2500 30000.0

0.2

0.4

0.6

0.8

1.0

Con

cent

ratio

n of

Al3+

[kg/

m3 ]

Time [s]

Model

Fig. 1. Flow effect on the gradient of aluminium hydroxide concentrationbetween the EC cell and the reactor.

0 1000 2000 3000 4000 5000 6000

0.2

0.4

0.6

0.8

1.0

100 A/m2

200 A/m2

300 A/m2C

/C0

Time [s]

Fig. 2. Effects of the current density on the adsorption curves, C/C0 vs. t(F = 6.2 × 10−6 m3/s; K = 1.1; n∞ = 10 kg/kg; C0 = 50 kg/m3).

0 300 600 900 12000.0

0.2

0.4

0.6

0.8

1.0 K=1 K=10 K=50

C/C

0

Time [s]

Fig. 3. Effects of the separation factor on the adsorption curves, C/C0 vs. t(F = 6.2 × 10−6 m3/s; i = 300 A/m2; n∞ = 10 kg/kg; C0 = 50 kg/m3).

isotherm with a linear shape, but when the K value increasesthe equilibrium becomes more favourable and the solid tends toreach immediately its maximum capacity and a sharp increasein the removal of pollutant from the liquid phase is observed.

M. Carmona et al. / Chemical Engineering Science 61 (2006) 1237–1246 1241

4. Experimental section

Chemical. Aluminium alloy A-U4G (2017-Al) was used asthe electrode material and had the following metal contents:Cu (4%), Fe (0.7%), Mg (0.7%), Mn (0.7%), Si (0.5%), Zn(0.25%) and Cr (0.1%). Sodium chloride of analytical gradewas supplied by Prolabo, France. The soluble oil (Sol 1000TM,Molydal, France) consisted of mineral oils (70%), glycol ethers,amines and chlorinated alkanes. Kerosene (BP 175–325 ◦C)was supplied by Sigma-Aldrich, France. Demineralized waterwas used with a conductivity value lower than 5 �s/cm.

Procedure. The experimental system is represented schemat-ically in Fig. 4. The system consisted of an EC cell, a re-actor, a peristaltic pump and a sampling valve. The EC cellcontained two parallel plate aluminium electrodes, each witha dimension of 100 mm × 50 mm × 12 mm and an effectivearea of 5.0 × 10−3 m2. The electrode gap was maintained con-stant at 20 mm. The reactor was a water-jacketed glass reser-voir with a capacity of 1.5 × 10−3 m3, hermetically sealed butprovided with three holes—two for wastewater recirculationand the other for purging the gases. The tank was magneti-cally stirred at 140 rpm. The peristaltic pump (Masterflex L/Smodel 752445) was calibrated prior to carrying out the experi-ments. The sampling system consisted of a standard three-portvalve. All experiments were carried out in a batchwise manner,with recirculation of the emulsion through the electrochemicalcell. For reasons discussed above, the flow rate was fixed at6.2 × 10−6 m3/s, which corresponds to a liquid velocity in thecell of 6.2 × 10−2 m/s.

Treatment of oil/water emulsions was carried out asdescribed previously (Khemis et al., 2004). In addition,oil/kerosene emulsions in water were also investigated. Forboth emulsions the current density was varied from 100 to300 A/m2. In all experiments, sodium chloride was addedat 1.5 kg/m3 to give sufficient conductivity in the mediumto be treated, as suggested by Sánchez-Calvo et al. (2003).The electrical conductivity of the resulting emulsions was inthe range 0.38–0.49 s/m at room temperature. Observation ofthe samples by microscopy showed that the characteristicsof both types of emulsion were not affected by the addi-tion of supporting electrolyte. The pH values of the mediaprepared were as close as possible to 9.0 for oil emulsionsand 8.6 for oil/kerosene mixtures. In spite of the evolutionof OH− at the cathode, the pH in the reactor increased byless than 0.5 during the run. This is due to the bufferingcharacter of Al(III) species, especially in this pH region(Kobya et al., 2003). All experiments were carried out at 25 ◦C.

The pH of liquid samples was adjusted to 7.0 (±0.2) by theaddition of aliquots of concentrated hydrochloric acid for opti-mal precipitation of aluminium hydroxide (Bard et al., 1985).The samples were kept for 24 h prior to analysis of the clearfraction. After each experiment the electrochemical cell wascleaned with detergent and then rinsed thoroughly to avoid pas-sivation of the electrode surface (Mollah et al., 2001).

Chemical analysis. The amount of pollutants contained in thesamples was followed by determination of chemical oxygen de-mand (COD), the total organic carbon (TOC), turbidity and zeta

Fig. 4. Schematic diagram of the experimental system.

potential. COD was determined using a standard calorimetrictechnique with an excess of Cr(VI)—sulfuric acid medium andmeasurement of the optical density of the recovered solutionat 520 nm using a Hach DR/2500 spectrophotometer. The TOClevels were determined through combustion of the samples at680 ◦C using a non-dispersive IR source (Tekmar DohrmannApollo 9000). The accuracy of both determinations was esti-mated at 3%. Wastewater turbidity in Nephelometric TurbidityUnits (NTU) was measured using a Hanna LP-2000 turbidime-ter. Zeta potential was measured using a Malvern Zetasizer3000HS.

5. Results and discussion

COD and TOC levels have previously been shown to bedirectly proportional to the amount of organic compounds inthe water. TOC was selected for analysis, since it appears toprovide a closer representation of the organic matter content.The most suitable isotherm model was selected by carrying outa set of experiments in which the current density was varied and50 kg/m3 oil/water emulsions were used. Reliable values for themodel parameters were obtained by fitting the experimental databy non-linear regression to the mathematical models describedabove.

The parameters found for the three isotherms studied areshown in Table 1.

The model accuracy was evaluated by calculating the coef-ficient of determination using the following formula:

R2 = 1 −∑nexp

i=1 (Cexp − C∗)∑nexp

i=1 (Cexp − Cexp), (19)

where Cexp is the experimental concentration of hydrocarbonsin the liquid phase, Cexp the average experimental concentrationand nexp is the number of experimental data considered.

Best fitting was found using LTEE and Freundlich isotherms,as shown in Table 1. LTEE was finally selected for subsequent

1242 M. Carmona et al. / Chemical Engineering Science 61 (2006) 1237–1246

Table 1Parameters of the different empirical equations used to reproduce the equi-librium between the two phases for the oil emulsion and the coefficient ofdetermination, R2, for the EC process of oil emulsions at 298 K

Equation Parameters R2

q∗ = n∞KC∗C0+(K−1)C∗ n∞ K

78.904 2.963 0.973

q∗ = KIIC∗m m KII

0.658 7.229 0.972

q∗ = n∞I KIC

∗1+KIC

∗ n∞I KI

40.624 5.959 0.841

0 1500 3000 4500 6000 75000

10

20

30

40

50 100 A/m2

140 A/m2

170 A/m2

200 A/m2

260 A/m2

300 A/m2

Theoretical Model

Liqu

id p

hase

con

cent

ratio

nof

oil

[kg/

m3 ]

Time [s]

0 1500 3000 4500 6000 75000

20

40

60

80 100 A/m2

140 A/m2

170 A/m2

200 A/m2

260 A/m2

300 A/m2

Sol

id p

hase

con

cent

ratio

nof

oil

[kg/

kg]

Time [s]

(a)

(b)

Fig. 5. Oil concentration in the two phases using the LTEE: (a) Experimentaldata and theoretical prediction at different current densities; and (b) evolutionof the oil concentration on solid phase.

calculations because of its lower variation according to thecoefficients of determination obtained.

It can be seen from Fig. 5a that good agreement was foundbetween experimental data and the predictions yielded by theLTEE model. At low times, the high removal yield increasesregularly with current density. This effect is due to the higherformation rates of aluminium hydroxide, which in turn leads tohigher adsorption rates of oil from the liquid phase. However,for longer times the effect of the current is less significant.The amount of oil adsorbed onto the solid at each time canbe obtained by using the equilibrium relation Eq. (11); the

0 10 20 30 40 500

20

40

60

80

100

Freundlich equation Langmuir type equation Langmuir equation

q* [k

g/kg

]

C* [kg/m3]

Fig. 6. Equilibrium isotherms.

data are represented in Fig. 5b. As can be seen, the higherthe current density the lower the amount of oil on the solid atany given time. Nevertheless, the total removal of oil from theliquid phase is greater in this situation. This phenomenon canbe explained by considering Eq. (14), which indicates that theamount of Al(OH)3 is reciprocal to the amount of oil on thesolid at equilibrium. Thus, the higher the rate of formation ofaluminium hydroxide, the lower the time required for emulsionabatement.

It can be seen from Fig. 5b that the initially formed parti-cles are able to remove the maximum oil from the liquid phase.This observation can be explained in terms of the high organicconcentration and minimum amount of solid that exist underthese conditions. This behaviour would indicate that adsorptionand desorption phenomena could take place simultaneously inthe reactor: desorption of oil occurs from the old particles andadsorption onto new particles occurs toward the new instanta-neous equilibrium.

It can be concluded that high removal rates can be obtainedusing high current density with shorter operation times. Thisoperational procedure also allows passivation of the cathodesurface to be reduced (Mollah et al., 2001).

The differences exhibited by the three adsorption models canbe attributed to the form of the isotherms shown in Fig. 6,which gives the isotherm curves with parameter values reportedin Table 1. LTEE and FE isotherms are very similar and thedifferences obtained in the elimination levels can be explainedby the fact that the Freundlich equation predicts a higher solidcapacity for initial liquid phase concentration and, therefore,a higher initial elimination rate. The poor fitting given by theLangmuir isotherm could be due to the sharp profile exhibitedat low concentrations followed by a long plateau: for this reasonthe equilibrium constant may be significantly overestimated bythis model.

The amount of oil removed from the emulsion by electroco-agulation processes can be predicted with satisfactory accuracyusing an adsorption model whatever the current density. Thus,the lower the current, the longer the time required to reachthe asymptotic plateau. The predicted adsorption capacity de-duced from the experimental data for oil removal is very high,

M. Carmona et al. / Chemical Engineering Science 61 (2006) 1237–1246 1243

0 1500 3000 4500 6000 75000

50

100

150 100 A/m2

300 A/m2

200 A/m2

100 A/m2

Theoretical Model

Liqu

id p

hase

con

cent

ratio

n of

Oil/

Ker

osen

e [k

g/m

3 ]

Time [s]

Fig. 7. Behaviour of the different emulsion oil/kerosene in water by electro-coagulation. (F = 6.2 × 10−6 m3/s; T = 25 ◦C).

indicating a high affinity of aluminium hydroxide for the oil.Finally, it can be concluded that this model is reliable in pro-viding an insight into the behaviour of emulsions in electroco-agulation processes.

Oil/kerosene in water emulsions were prepared with akerosene/oil ratio of one. Experiments were carried out byvarying the emulsion concentration and the current density. Allthe experimental data were fitted by non-linear regression tothe mathematical model based on the LTEE isotherm. Valuesfor the parameters K and n∞ were determined to be 31.226and 60.258 kg/kg, respectively.

Good agreement between experiment and theory was ob-tained for oil/kerosene in water emulsions, as shown in Fig. 7.The electrocoagulation process is able to remove large amountsof hydrocarbons from wastewater but the removal rate dependson the current density. When a minimum current density is ap-plied to the highest concentration, the removal yield decreaseslinearly with time, but the use of a low current rate means thatthe liquid cannot be treated within the time period ascribed.However, for higher current densities, treatment of the waste issuccessfully achieved by the process regardless of the concen-tration.

The course of hydrocarbon removal from the wastewaters isconsistent with the variations of turbidity [Fig. (8)] and zetapotential [Fig. (9)] during the treatment process. Considerationof Fig. 8 suggests that the most concentrated emulsions cannotbe destabilised by electrocoagulation with the lowest currentdensity. In the other cases, however, turbidity can be reduced toa great extent. Changes in turbidity exhibited the same trendsas in previous studies (Holt et al., 2002) and electrocoagula-tion follows a three-stage process: in the first stage, turbidityincreases due to formation of aluminium hydroxide particlesfrom the electrodes (Larue and Vorobiev, 2003); a “reactive”stage then occurs, with a sharp decrease in turbidity; the fi-nal stage is characterised by almost constant turbidity levels,which correspond to the final concentration of suspensions thatcannot be removed by the electrochemical process.

The time variations in the zeta potential are shown in Fig. 9and suggest that the addition of Al3+ neutralizes the negative

0 1500 3000 4500 6000 7500

0

1x105

2x105

3x105

4x105

5x105

100 A/m2; C0=150 kg/m3

300 A/m2; C0=150 kg/m3

200 A/m2; C0=100 kg/m3

100 A/m2; C0=50 kg/m3

Tur

bidi

ty [N

TU

]

Time [s]

Fig. 8. Turbidity evolution with the time for different experiments studied.

Fig. 9. Zeta potential evolution with the time for different experiments studied,measured at pH 7.0.

charges on the particle surfaces for sufficient current densityin relation to the suspension concentration. The zeta potentialof the clear fraction from the samples measured at pH 7.0 be-comes positive when the emulsion is demulsified: this situationis encountered under the same conditions as found for the tur-bidity and the TOC level, namely high current density and/orlow to moderate concentrations. In addition, both turbidity andTOC still show appreciable decays when the zeta potential iszero. However, the time required for the maximum reductionin turbidity and TOC is somewhat longer than that correspond-ing to the change in the sign of the zeta potential of the sam-ple. This indicates that even after the change in the sign of thezeta potential, adsorption of organic matter continues to someextent.

Different parameter values were obtained depending on thetype of emulsion studied. The separation factor (K) for theoil/kerosene emulsion was far higher than that for the oil/wateremulsion. This indicates that aluminium hydroxide prefers the“lighter” phase of the oil/kerosene suspension over the “heavy”ones obtained with oil alone. Nevertheless, the capacity param-eter (n∞) is higher for oil than for the oil/kerosene emulsion:

1244 M. Carmona et al. / Chemical Engineering Science 61 (2006) 1237–1246

20

40

60

80100

010203040506070

0

20

40

60

80

100

Time [s·10-2]

Hyd

roca

rbon

Rem

oval

[%]

Pow

er [W

atts

]

Optimal Condition

Fig. 10. Effect of the power and the treatment time on hydrocarbon removalfor the oil/kerosene emulsion in water. (F =6.2×10−6 m3/s; C0=100 kg/m3;K = 31.226; n∞ = 60.258 kg/kg).

aluminium hydroxide appears to be capable of adsorbing largeramounts of oil than oil/kerosene from the wastewater.

The effect of the power and treatment time on the hydro-carbon removal from the emulsion is shown in Fig. 10. Thecell voltage measured during the experiments was expressedthrough an empirical function of current density and initial con-centration: the law obtained was used to calculate the electri-cal power consumed. It can be observed that at lower timesthe slope of the iso-power lines moves from a minimum (low-est power) up to a maximum (highest power). Such behaviourwas also observed in Fig. 7, where 150 kg/m3 emulsions weretreated at various current densities. Thus, electrical power rep-resents a similar operating parameter for wastewater treatmentas current density. Moreover, it can be observed that the mini-mum power required to achieve a 78% abatement is about 10 W(equivalent to a current density of 137.4 A/m2) within the high-est operation time. However, this operating condition is of lim-ited practical use due to passivation of the electrode surfaces.On the other hand, it was observed that the time required toreach the same abatement decreases with increasing power con-sumed. Therefore, a minimum power of 35 W (equivalent to acurrent density of 294.2 A/m2) must be applied for a period of4500 s period to achieve an abatement yield over 90% with anAl consumption of almost 2 kg/m3 required (Fig. 10). Higherenergy consumption for a larger treatment period does not re-sult in significant further abatement. For the present system, atreatment period of 4500 s was also found to be the optimumtime (see Fig. 7) for all conditions, provided that the currentdensity was sufficient for destabilisation of the emulsions.

Finally, Chen et al. (2002) developed a simplified model forthe estimation of the cell voltage and this involved the electrode

potential of the anode and cathode, the activation overpotential,concentration overpotential and ohmic potential drop. They es-timated the unknown overpotential by applying the Tafel equa-tion and Nernst equation. For non-passivated and passivatedaluminium electrodes, they found that the electrolysis voltagecan be expressed by

U0 = S + h

ki + K1 ln i + K2i

m1

km, (20)

where h is the electrode gap, k is the conductivity of the waterand i is the current density—the constants S, K1, K2, m1 andm must be determined experimentally. K2 has a value of zerofor non-passivated electrodes.

The basic electrode connection used is in monopolar mode.In this way, the total required cell voltage (U) is equal to thecell voltage (U0). Thus, using the same water and current den-sity allows the following equation to be drawn from the aboveequation for two different electrode gaps.

E2

E1= 1 − Ai2

kE1(h1 − h2), (21)

where E is the electrical power and subscripts 1 and 2 indicatethe conditions at the two different electrode gaps.

From this point of view, this expression can be used fornon-passivated and passivated electrodes. As can be seen, it ispossible to minimize the energy consumption by reducing theelectrode gaps of the electrochemical cell (h2 < h1) to a fewmillimetres. Studies concerning the influence of the electrodegap were carried out by Sanchez-Calvo et al. (2003) and Cameset al. (2001) for three different scales (laboratory, pilot plant andindustrial). Minimum energy consumption was also found forlower electrode gaps and it was determined that lower valuescan be used for larger scales.

6. Conclusions

A simple adsorption model to predict hydrocarbon removalfrom wastewater by electrocoagulation has been developed.Adsorption of organic matter on Al hydroxide particles wasmodelled using three different adsorption isotherms and theLangmuir-type equation led to the best results. The modelwas able to describe the effects of current density and pol-lutant concentration on the abatement of two different emul-sions (oil/water and oil/kerosene/water) as a function of onlytwo adsorption parameters. Different parameter values were ob-tained depending on the emulsion studied. Aluminium hydrox-ide has a marked preference for the “light” fractions consistingof oil/kerosene emulsions but its capacity to remove the heav-ier contaminant (a single oil emulsion) was slightly higher. Thedestabilisation of the oil/kerosene emulsion was shown to de-pend on the initial concentration and the current density. Whenthe current density was sufficient to destabilise the emulsion,the zeta potential became positive and a maximum reductionin the turbidity was obtained. However, low current densitiesare of low efficiency when applied to concentrated emulsionswithin the considered time period. The use of the adsorption

M. Carmona et al. / Chemical Engineering Science 61 (2006) 1237–1246 1245

model allows the minimum power required to achieve the max-imum hydrocarbon removal to be obtained without additionalexperimental data. Taking into account the cell voltage, it wasfound that a decrease in electrode gap leads to lower energyconsumption.

Notation

A electrode area, m2

C∗ concentration of oil in the solution phase atequilibrium, kg/m3

C0 initial concentration of oil in the solutionphase, kg/m3

Cexp experimental concentration of oil in the so-lution phase, kg/m3

CcAl(III) concentration of aluminium hydroxide in the

cell, kg/m3

CAl(III) concentration of aluminium hydroxide in thereactor, kg/m3

E = UI energy consumption, WF liquid flow rate, m3/sI Faraday constanth electrode gap, mi current density, A/m2

I cell current, Ak conductivity of water, s/mK separation factor, using LTEE model,

Eq. (11)KI Langmuir equilibrium constant, m3/kgKII Freundlich model parameter, m3m/kgm

l Number of nodes along the cell lengthL electrode length, mmAl(OH)3 mass flux of Al(OH)3, kg/sm exponent of the Freundlich equationn the number of electrons produced by anode

oxidationn∞ aluminium hydroxide capacity, Eq. (11),

kg/kgn∞

I monolayer capacity of aluminium hydroxide,Eq. (12), kg/kg

nexp total number of experimental data used in thenon-linear regression process

NAl3+ flux of Al3+ species formed by dissolution,mol/s

PMAl(OH)3 molecular weight of the Al(OH)3 (kg/mol)q∗ solid-phase concentration of oil, kg/kgT time, su superficial velocity, m/sU total required cell voltage, VU0 cell voltage between electrodes, VV volume of reactor, m3

x position along the cell length

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