Prediction of Breakthrough Curves for Adsorption of Complex Organic

Aug 30, 2006 - Planter 1978, 54, 749. (2) Ahmad, A. L.; Ismail, S.; Bhatia, S. Water recycling from palm oil mill effluent (POME) using membrane techn...
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Ind. Eng. Chem. Res. 2006, 45, 6793-6802

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Prediction of Breakthrough Curves for Adsorption of Complex Organic Solutes Present in Palm Oil Mill Effluent (POME) on Granular Activated Carbon A. L. Ahmad,* M. F. Chong, and S. Bhatia School of Chemical Engineering, Engineering Campus, UniVersiti Sains Malaysia, Seri Ampangan, 14300 Nibong Tebal, Penang, Malaysia

The adsorption of pretreated palm oil mill effluent (POME) onto a granular activated carbon (GAC) fixed bed has been studied using the incorporation of ideal adsorbed solution theory (IAST) into the homogeneous surface diffusion model (HSDM). The pretreated POME is a complex solution of a ternary system containing three major organic solutes of carbohydrate constituents, protein, and ammoniacal nitrogen. The incorporation of IAST into HSDM allows multicomponent adsorption predictions using single-solute equilibrium isortherms. Batch adsorption and fixed-bed adsorption were conducted to obtain the experimental data for a multicomponent adsorption system using pretreated POME. The residence time in the bed was varied by manipulating the bed length and the feed flowrate. On the basis of the comparison of the experimental breakthrough curves with the simulation results, IAST gives a good prediction of multicomponent adsorption on GAC when it is incorporated into HSDM. Introduction

Table 1. Characteristic and Distribution of Chemical Constituents of Raw POME

Palm oil mill effluent (POME) is the thick, brownish, viscous liquid waste discharged from the palm oil mills during the extraction of palm oil from the fruits and is nontoxic but has an unpleasant odor. It is predominantly organic in nature and highly polluting.1 POME is a colloidal suspension of 95-96% water, 0.6-0.7% oil, and 4-5% total solids, including 2-4% suspended solids originating from a mixture of sterilizer condensate, separator sludge, and hydrocyclone wastewater.2 The POME is a very complex mixture of organic matters, and all specific components of the organic matters could not be determined. The distribution of chemical constituents of POME has been determined and analyzed by several researchers1,3,4 and is summarized in Table 1. The high biological oxygen demand (BOD) and chemical oxygen demand (COD) of the POME are contributed by four major groups of organic matters, which are oil and grease, carbohydrate constituents, protein, and ammoniacal nitrogen. The pretreatment of POME employed in the present study is the flocculation process using polymers to remove the suspended solids, oil, and grease, and subsequently, COD is reduced. However, the pretreatment of POME is unable to remove the brownish color and the unpleasant odor.2 Granular activated carbon (GAC) adsorption is used to remove the remaining organic solutes present in the pretreated POME that generally contributed to the brownish color and the unpleasant odor. The pretreated POME forms a complex organic solution. The organic solutes present can be grouped into three major groups, which are carbohydrate constituents, protein, and ammoniacal nitrogen. The removal efficiency of organic solutes is largely dependent on the interactions of the competing organic solutes that are present in the pretreated POME. To design a GAC adsorption system, the information regarding the removal capacity of an organic solute in the presence of other competing organic solutes (multicomponent system) is required. The most common simulation model used for the prediction of GAC adsorption in a multicomponent system is based on * To whom correspondence should be addressed. E-mail: chlatif@ eng.usm.my.

parameter

concentration

pH oil and grease, mg/L biological oxygen demand (BOD), mg/L chemical oxygen demand (COD), mg/L total solids, mg/L suspended solids, mg/L ammoniacal nitrogen, mg/L

4.7 4000 25 000 50 000 40 500 18 000 35

a) mineral, mg/L

3 560

phosphorus, mg/L potassium, mg/L magnesium, mg/L calcium, mg/L boron, mg/L iron, mg/L manganese, mg/L copper, mg/L zinc, mg/L

180 2270 615 439 7.6 46.5 2.0 0.89 2.3

c) carbohydrate constituents, mg/L

3 900

glucose, mg/L reducing sugars, mg/L starch, mg/L pectin, mg/L others, mg/L

140 1450 360 328 1622

d) protein, mg/L

2830

amino acids, mg/L peptides, mg/L others, mg/L

not available not available not available

the incorporation of ideal adsorbed solution theory (IAST) into kinetic models.5 Lo and Alok6 proposed a simulation model based on the incorporation of the IAST into the kinetic homogeneous surface diffusion model (HSDM) to make it possible to predict the effluent concentration of synthetic organic chemicals (SOCs) from groundwater (a multicomponent adsorption system). By using the IAST, the single-solute behavior represented by the Freundlich adsorption isotherm can be related to the HSDM for predicting multicomponent adsorption. In many cases when IAST is used, the model was tested using a simple synthetic wastewater sample instead of the real system,

10.1021/ie0603722 CCC: $33.50 © 2006 American Chemical Society Published on Web 08/30/2006

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and the multicomponent system is obtained by adding the desired compounds into pure water.6,7 The single-solute behavior represented by the adsorption isotherms for each component can be easily obtained by conducting a batch adsorption test using the synthetic solution containing that particular solute. However, this is not the case when it comes to industrial application. Application of GAC adsorption in industrial wastewater treatment involves complex solutions, and all specific components could not be determined. In addition, the individual components contained in the industrial wastewater could not be separated out to form a single-component system in order to obtain the single-solute behavior. Thus, in the present study, representative solutes are used to represent the components contained in the industrial wastewater. The synthetic sample containing that particular representative solute is used to obtain the single-solute behavior in equilibrium. The multicomponent calculations are performed on the real system of industrial wastewater by using the single-solute data obtained from the synthetic sample. Information on the removal efficiency of the organic solutes from pretreated POME using GAC is important for pilot-scale investigation and scale-up for industrial application. Adsorption of organic solutes of pretreated POME using GAC involves complex solutions system. The objective of the current study is to evaluate the applicability of HSDM in predicting the breakthrough curves for the complex system of pretreated POME by using the incorporation of IAST. The IAST application needs single-solute data, and the model allows multicomponent calculations to be performed using the single-solute isotherm relationships. Because of the complexity of the pretreated POME system, the single-solute isotherm for each component is obtained by using a synthetic sample where the representative solute was added into the pure water. The pretreated POME contains three major groups of organic solutes, carbohydrate constituents, protein, and ammoniacal nitrogen, which contributed to the brownish color, unpleasant odor, and high COD. The soluble starch, soy protein, and ammonium chloride are used as the representative solutes to represent the carbohydrate constituents, protein, and ammoniacal nitrogen, respectively, for single-solute isotherm prediction. The result obtained from the single-solute isotherm is used for breakthrough curves prediction for the real system using pretreated POME. The soluble starch is chosen to represent the carbohydrate constituents in the pretreated POME because it is the single component that has the highest concentration among other components in the carbohydrate constituents’ category, as shown in Table 1.1,3,4 The soy protein is chosen to represent the protein in the pretreated POME, as soy protein is the most readily available and compatible protein compared with the proteins of animals origin. Nitrogen in POME is originally present in the form of organic (protein) nitrogen, and as time progressed, the organic nitrogen was gradually converted to ammoniacal nitrogen and appeared as the dissolved form of ionic ammonium in POME.4 Thus, ammonium chloride is used to represent the ionic ammonium in the POME as ammoniacal nitrogen. In the industrial application of wastewater treatment, the COD is often used as the indicating parameter on the pollution level of a particular wastewater. Thus, a standard discharge limit of COD is imposed by the Department of Environment (DOE) of Malaysia based on the Environmental Quality Act 1976. A standard discharge limit of ammoniacal nitrogen is also imposed on the POME treatment. The organic matters of carbohydrate constituents, protein, and ammoniacal nitrogen are the major

components contributing to the high COD of POME. The correlation of these components with COD is indeed very important for industrial application. In the present study, the effluent concentrations of each solute are correlated to the COD to evaluate the efficiency of COD removal using adsorption on GAC. Modeling of Adsorption Process The rate of mass transfer of the adsorbate (organic solutes) onto the adsorbent (fixed-bed GAC) is based on the diffusion of adsorbate from the bulk solution through the stagnant film surrounding the particle external surface (external film mass transfer). Once reaching the surface, adsorption occurs instantaneously and equilibrium is established between the adsorbate in the fluid and that on the adsorbent surface. The adsorbed material then diffuses into the pores in the adsorbed state.6,8 In the fixed-bed operation, the mass transfer of the singlesolute adsorption is described by the mathematical model of HSDM developed by previous researchers.8 The HSDM considers the mass balance on the liquid phase and the GAC particle. The liquid-phase mass balance describes the spatial and temporal variations of the adsorbate concentration in the solution. The mass balance on the liquid phase that contains only solute i in the fixed-bed GAC adsorption system is represented as

∂Ci ∂Ci 3 (1 - ) ) -Vs kfi (Ci - Csi) ∂t ∂z R 

(1)

where Ci is the bulk liquid-phase concentration of adsorbate i, t is the time parameter, z is the coordinate along the longitudinal bed axis,  is the porosity of the GAC bed, R is the adsorbent particle radius, kfi is the external mass transfer coefficient of adsorbate i, Csi is the equilibrium concentration of adsorbate i, and Vs is the influent approach velocity which is defined as9

Vs )

Q πd2  4

(2)

where Q is the feed flowrate and d is the inside diameter of the fixed bed. The initial and boundary conditions of eq 1 are

t ) 0, 0 e z e L, Ci ) 0

(3a)

t > 0, z ) 0, Ci ) Cfi

(3b)

∂Ci )0 ∂z

(3c)

t > 0, z ) L,

where L is the bed length and Cfi is the concentration of adsorbate i in the feed. The external mass transfer coefficient of adsorbate i, kfi, can be evaluated by the correlation of Wilson and Geankoplis.10 For Reynolds numbers of 0.0015 e Re e 55,

Shi )

1.09 1/3 1/3 Sci Re 

(4)

where Shi is the Sherwood number of adsorbate i, Shi ) kfidp/ Dvi; Sci is the Schmidt number of adsorbate i, Sci ) µw/(FwDvi); and Re is the Reynolds number, Re ) dpFwVs/µw. dp is the particle diameter, Dvi is the molecular diffusion coefficient of adsorbate i, µw is the viscosity of water, and Fw is the density of water.

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The molecular diffusion coefficient, Dvi, for each of the adsorbates i can be estimated using Stokes-Einstein equation11 for a large molecule diffusing in a liquid solvent of small molecules.

Dvi )

9.96 × 10-16 T µwVAi1/3

d(ln C 0i )

(5)

where VAi is the molar volume of adsorbate i and T is the system temperature. The molecular diffusion coefficients, Dvi, estimated based on eq 5 for carbohydrate constituents, protein, and ammoniacal nitrogen are 3.45 × 10-11 m2/s, 2.91 × 10-11 m2/s, and 1.64 × 10-9 m2/s, respectively.10 For the HSDM, the internal mass balance on the GAC particle is as follows,8

( )

t ) 0, 0 e z e L, 0 e r e R, qi ) 0

(7a)

∂qi t > 0, r ) 0, )0 ∂r

(7b)

( ) ∂qi ∂r

n1q01 ) n2q02 ) ... ) njq0j

r)R

qi ∑ i)1

(12)

qi (i ) 1-N) qT

(13)

qT ) Zi )

Thus, the Ci can be expressed as

Ci ) ZiC 0i (i ) 1-N)

∫0

π0i A 0 ) dq ) ... (i ) 1-N) i RT d(ln q0i )

(7c)

(8)

where R is the universal gas constant, A is the surface area of the adsorbent, C 0i is the initial liquid-phase concentration of adsorbate i, q0i is the solid-phase surface loading corresponding to C 0i , and π0i is the spreading pressure of adsorbate i at equilibrium. The Freundlich adsorption isotherm is the most widely used empirical equation for describing an equilibrium behavior of a solute in a single-component aqueous-solid system6 and is expressed as

qei ) KiCei1/ni

(9)

where qei is the solid-phase surface loading at equilibrium for adsorbate i, Cei is the equilibrium liquid-phase concentration of

(14)

By combining eqs 12-14, eq 15 is obtained:12

Zi

N

)

qT

∑ i)1

(15)

q0i

By substitution of eq 11 into eq 15, eq 16 is obtained as N

q0i )

∑ nj qj j)1 (16)

ni

By combining eqs 9 and 16 with eq 14, the IAST based on the Freundlich isotherm is obtained. The equilibrium concentration of adsorbate i in the presence of other competing organic solutes (Csi) is expressed in term of the solid-phase loading of adsorbate i (qi) on the GAC particle at r ) R through the Freundlich parameters of Ki and ni.

( ) N

d(ln C 0i )

(11)

In the multicomponent adsorption system, the total solid-phase loading (qT) and the mass fraction of adsorbate i, Zi, are expressed in eqs 12 and 13, respectively.

1

where Fp is the GAC particle density. The mathematical model of HSDM describes the mass transfer of the single-solute system of adsorbate i. The incorporation of the IAST into the HSDM allows the prediction of a multicomponent adsorption system. The IAST model is based on the thermodynamic equivalence of the spreading pressure of each solute at equilibrium. The term “spreading pressure”, π, is defined as the difference between the interfacial tension of the pure solvent-solid interface and that of the solution-solid interface at the same temperature. The spreading pressure of a single solute will remain unchanged when it is mixed with other components in an adsorption system.5 Thus, the spreading pressure of adsorbate i, πi, is equal to that of each individual component and to that of the mixture, πm, and can be written as6 q0i

(10)

Equation 8 is simplified by the substitution of eq 10 as

(6)

where qi is the solid-phase loading of adsorbate i on the GAC particle, Dsi is the diffusivity of adsorbate i, and r is the radial axis of the GAC particle. The initial and boundary conditions of eq 6 are

πm A ) RT

) ni

d(ln q0i )

N

∂qi Dsi ∂ 2 ∂qi ) 2 r ∂t ∂r r ∂r

t > 0, r ) R, kfi(Ci - Csi) ) FpDsi

adsorbate i, Ki is the Freundlich capacity parameter, and 1/ni is the Freundlich intensity parameter. On the basis of the Freundlich isotherm of eq 9, a relationship for predicting multicomponent adsorption can be derived12 as

Csi )

qi N

qj ∑ j)1

∑ nj q j j)1 niKi

ni

(i ) 1-N)

(17)

By incorporating the IAST of eq 17 into the kinetic model of HSDM (eqs 1-7), the effluent concentration of the organic solutes (carbohydrate constituents, protein, and ammoniacal nitrogen) in the multicomponent (pretreated POME) adsorption system can be predicted. Solution of the equations will give the breakthrough curves for the complex system of pretreated POME in terms of the effluent concentration of each adsorbate as a function of the operation time of the GAC bed. In the application of adsorption on GAC in the wastewater treatment, the chemical oxygen demand (COD) is often used to monitor the efficiency of the treatment method. The COD is closely related to the concentrations of the organic solutes in

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Table 2. Particle Size Distribution of GAC Determined by Sieve Analysis sieve opening (µm)

mass fraction, ∆xi

3000 2000 1000 500 355 250 pan

0 0.2763 0.6959 0.0161 0.0117

average size, dpi (µm)

∆xidpi (µm)

2500.0 1500.0 750.0 427.5 302.5 125

691 1044 12 1

the system. A linear correlation is used in the present study to relate the concentrations of all solutes in the system with the COD as follows,13 N

CCOD )

∑ biCi i)1

(i ) 1-N)

(18)

where the term CCOD is the total COD concentration in the system and bi is the dimensionless coefficient of adsorbate i. Experimental Section Granular Activated Carbon. The adsorbent used in the present study was granular activated carbon manufactured from coconut shell, supplied by Envilab Sdn. Bhd. with the following properties: apparent density, 498 kg m-3; particle density, 740 kg m-3; and porosity, 0.50. The particle-size distribution of the GAC was determined by sieve analysis,14 as shown in Table 2. The average particle size of 1.75 mm was obtained (calculated 6 dpi∆xi where dpi is the average particle size for each as ∑i)1 pair of consecutive sieves and ∆xi is the increment of weight fraction in each pair). To remove any fines attached to the GAC particles and any leachable matter, the GAC was further washed several times with distilled water. The activated carbon was considered fit for use when the distilled water obtained after washing was visibly clear. After washing the GAC, it was airdried at room temperature. After the GAC was completely dried, it was stored in a glass bottle until use. Batch Adsorption Studies. The batch adsorption tests were conducted to obtain the single-solute behavior in equilibrium for each component. The working solutions used to conduct batch adsorption tests were prepared by using soluble starch, soy protein, and ammonium chloride supplied by Merck, Germany. These compounds were highly pure with 99% purity. The working solutions concentrations were 10 600 mg/L, 18 300 mg/L, and 78 mg/L for soluble starch, soy protein, and ammonium chloride, respectively. The solutions were prepared by adding the required amount to the distilled water. The soluble starch, soy protein, and ammonium chloride present in the working solutions served as the representative solutes for the carbohydrate constituents, protein, and ammoniacal nitrogen, respectively, for single-solute isotherm prediction in the pretreated POME system. The concentrations of the representative solutes in the working solutions were set at the same concentration as the organic solutes in the pretreated POME. The preweighed quantities of GAC were contacted in a 500mL stoppered glass bottle with 200 mL of working solutions for 24 h using a shaker with temperature controlled at 25 °C. The amounts of activated carbon in the bottles were varied so as to give a wide range of equilibrium concentrations. The initial pH was adjusted to 4.7 (the same pH as the pretreated POME) by using hydrochloric acid or sodium hydroxide in order to eliminate the pH effect. After 24 h, the bottles were taken out

of the shaker and filtered through a Whatman filter. The filtrate was kept in a refrigerator prior to its analysis. Fixed-Bed Adsorption Studies. In the fixed-bed adsorption tests, the complex solution of pretreated POME (ternary system) was used. The pretreated POME was obtained by the flocculation process using polymers to remove the suspended solids, oil, and grease from the raw POME. The details on the pretreatment of raw POME is reported elsewhere.2 The raw POME was obtained from United Palm Oil Mill, Sungai Kecil, Nibong Tebal, Malaysia. The pretreated POME was pumped through a flowmeter into a GAC column. The bed porosity and the inner diameter of column were 0.5 and 50 mm, respectively. The desired residence time, τ ) L/Vs, was maintained by maintaining the feed flowrate by a peristaltic pump at the desired bed length. The effluent samples were taken at every time interval, and the concentrations were subsequently analyzed. A typical adsorption experimental run time was between 60 and 70 h. Analytical Procedure. The carbohydrate constituents of pretreated POME and soluble starch were determined using the colorimetric method with the phenol-sulfuric acid 98% reaction.15 The protein of pretreated POME and soy protein were measured by using the colorimetric method with a detergentcompatible formulation based on bicinchoninic acid (BCA protein assay, Pierce). The ammoniacal nitrogen of pretreated POME and ammonium chloride was determined using the preliminary distillation step followed by the titrimetric method with standard sulfuric acid titrant, 0.02 N.16 The COD was measured by using the colorimetric method at wavelength 600 nm with spectrophotometer CECIL 1000 series, Cambridge, U.K.16 Results and Discussion Equilibrium Isotherms. The single-solute equilibrium isotherms of soluble starch, soy protein, and ammonium chloride onto GAC were obtained from the batch adsorption tests at 25 °C and a pH of 4.7. The concentrations of the working solutions were 10 600 mg/L, 18 300 mg/L, and 78 mg/L for soluble starch, soy protein, and ammonium chloride, respectively. The equilibrium data were fitted to the Freundlich adsorption isotherm of eq 9 by using the linear regression method of log-relation between log qe (mg/g) and log Ce (mg/L) as shown by eq 19. Figure 1 shows the experimental isotherm data plotted in logarithmic scale in order to see the trend of the experimental points at low concentrations. As shown in Figure 1, the curve fitting using the Freundlich equation is comparable to the isotherm data obtained from the batch adsorption tests for all the adsorbates. The Freundlich parameters obtained based on eq 19 are shown in Table 3.

log qi ) log Ki +

1 log Cei ni

(19)

The simulation results of the IAST model and the experimental data for the ternary equilibrium system of soluble starch, soy protein, and ammonium chloride are depicted in Figure 2. On the basis of visual comparisons of the IAST model and the experimental data, the IAST model could predict the results adequately. Breakthrough Curves. The experimental breakthrough curves for carbohydrate constituents, protein, and ammoniacal nitrogen of pretreated POME were obtained based on the fixedbed adsorption tests. The fixed-bed adsorption tests were conducted using the complex solution of pretreated POME (ternary system) containing carbohydrate constituents (10 600 ( 210

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Figure 1. Freundlich equilibrium isotherm of (a) soluble starch, (b) soy protein, and (c) ammonium chloride. Table 3. Freundlich Parameters of Different Adsorbates solute soluble starch soy protein ammonium chloride

K

(mg/g)/(mg/L)1/n 4.83 × 10-3 4.42 × 10-3 5.11 × 10-5

1/n 1.0796 0.7692 0.5842

mg/L), protein (18 300 ( 370 mg/L), and ammoniacal nitrogen (78 ( 2 mg/L) at 25 °C and pH of 4.7. At the fixed solutes concentrations of pretreated POME, the fixed-bed adsorption tests were performed at different residence times by manipulating the bed length and feed flowrate. The experimental conditions are shown in Table 4. The experimental breakthrough curves are shown in Figures3 and 4. The simulation model based on the incorporation of IAST into the kinetic HSDM used for breakthrough curves prediction of a multicomponent system is written in Mathlab 7.1. The input parameters of the simulation model for defining the adsorption bed are bed diameter, bed length, feed flowrate, and bed porosity. The input parameters defining the GAC are particle radius and density. The other input parameters required are the initial concentrations, the external mass transfer coefficient, and the Freundlich parameters for each adsorbate of carbohydrate constituents, protein, and ammoniacal nitrogen present in the ternary system of pretreated POME. The Freundlich parameters are obtained based on the single-solute Freundlich adsorption isotherm of eq 9 for soluble starch, soy protein, and ammonium chloride (representative solutes). The diffusivities for each adsorbate, Dsi, are set as the fitting parameters, and the values are shown in Table 4. The variations of Dsi for each adsorbate are obtained as 10.64%, 10.26%, and 18.49% for carbohydrate constituents, protein, and ammoniacal nitrogen, respectively. On the basis of the calculated variations, the deviation is still satisfactory and the Dsi values are matched with their typical values in the literature.6-8 The present study involves components of a complex system, and Dsi for each adsorbate cannot be determined theoretically because the properties required are not available. In this case, the best option to obtain the Dsi is by parameter fitting.

The breakthrough curves of carbohydrate constituents, protein, and ammoniacal nitrogen of pretreated POME for each experimental condition regressed with the simulation model based on the incorporation of IAST into the kinetic HSDM were compared with the experimental breakthrough curves as shown in Figures 3 and 4. The predictability of the simulation model in the multicomponent system is evaluated quantitatively based on the analysis of the mean sum of percent errors, ∑%E.

∑%E ) n ∑ 1

[(

) ]

Xobserved - Xcalculated × 100 Xobserved

(20)

where n is the number of observations and X is the variable of Ci/Cfi. On the basis of eq 20, the mean sum of percent errors, ∑%E for all the breakthrough curves as shown in Figures 3 and 4, fall in the range of (3% - (9%. This indicates that the simulation results are in good agreement with the experimental data. Thus, the kinetic HSDM has been successfully applied in the prediction of breakthrough curves for the complex system of pretreated POME by using the incorporation of IAST. Both experimental data and simulation results for this ternary system show that protein is a strongly adsorbed species and is followed by carbohydrate constituents compared to the ammoniacal nitrogen. Therefore, in the complex system of pretreated POME, the adsorption of ammoniacal nitrogen has been inhibited by the presence of carbohydrate constituents and protein. This phenomenon can be explained by their differences in molecular size and solubility.17 The carbohydrate constituents and protein have larger molecular sizes compared to that of the ammoniacal nitrogen. This indicates that the solubility of ammoniacal nitrogen is greater than that of the carbohydrate constituents and protein, and this implies that the ammoniacal nitrogen stays in the liquid phase rather than the solid phase. Hence, the adsorption of ammoniacal nitrogen could be the least. Parts a-c of Figure 3 show the breakthrough curves of carbohydrate constituents, protein, and ammoniacal nitrogen with changing residence time (10, 20, and 30 min) by manipulating the bed length (10, 20, and 30 cm) at a constant

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Figure 2. Comparison of the IAST model with the experimental data of (a) soluble starch, (b) soy protein, and (c) ammonium chloride in ternary equilibrium system. Table 4. Experimental Conditions for Pretreated POME Fixed-Bed Adsorption Tests kfi × 107 (m/s)

Dsi × 1010(m2/s)

run

τ (min)

Q (mL/min)

Re

L (m)

(1)a

(2)a

(3)a

(1)a

(2)a

(3)a

1 2 3 4 5

10 20 30 10 30

9.43 9.43 9.43 18.86 6.29

0.3319 0.3319 0.3319 0.6638 0.2213

0.10 0.20 0.30 0.20 0.20

8.76 8.76 8.76 11.04 7.65

7.39 7.39 7.39 9.31 6.46

416 416 416 543 364

1.59 1.50 1.50 1.78 1.33

1.07 1.01 1.01 1.26 1.00

0.0075 0.0067 0.0063 0.0078 0.0047

a

(1) Carbohydrate constituents; (2) protein; and (3) ammoniacal nitrogen.

feed flowrate of 9.43 mL/min. Table 5 shows the saturation time, td (time when Ci/Cfi ) 1), for each organic solute in the pretreated POME adsorption based on the breakthrough curves. As shown from Figure 3 parts a-c, the breakthrough curves shifted gradually to the right and the saturation times for carbohydrate constituents, protein, and ammoniacal nitrogen increased as the bed length increased. On the basis of Table 5, the td increased from 50 to 67 h, 54 to 68 h, and 7 to 14 h for carbohydrate constituents, protein, and ammoniacal nitrogen, respectively, at increasing residence time. The observed behavior of the breakthrough curves was due to the increased residence time when the bed length increased. When the bed length increased at constant feed flowrate, the adsorption system had a lower volume of pretreated POME per unit volume of GAC applied. More solutes from the pretreated POME are adsorbed into the GAC bed, and this led to a higher saturation time. Parts a and b of Figure 4 and Figure 3b show the breakthrough curves of carbohydrate constituents, protein, and ammoniacal nitrogen with changing residence time (10, 20, and 30 min) by manipulating the feed flowrate (18.86, 9.43, and 6.29 mL/min). As shown from parts a and b of Figure 4 and Figure 3b, the breakthrough curves shifted gradually to the right and the saturation times for carbohydrate constituents, protein, and ammoniacal nitrogen increased as the feed flowrate decreased. On the basis of Table 5, the td increased from 47 to 66 h, 52

to 66 h, and 4 to 12 h for carbohydrate constituents, protein, and ammoniacal nitrogen, respectively, at increasing residence time. The observed behavior of the breakthrough curves was due to the increased residence time when the feed flowrate decreased. When the feed flowrate decreased at constant bed length, the adsorption system had a lower volume of pretreated POME per unit volume of GAC applied, and this led to a saturation time increase. On the basis of the breakthrough curves of Figures 3 and 4, it is observed that the breakthrough occurred almost immediately and there were a couple of points of inflection that occurred, especially for the breakthrough curves of carbohydrate constituents and protein where the Ct/C0 ratio increased rapidly in the first 10 h and became almost sluggish until saturation. This is due to the high feed concentration of the complex solution of pretreated POME. The carbohydrate constituents have a feed concentration of 10 600 mg/L, whereas protein has a feed concentration of 18 300 mg/L. Initially, although the driving force for mass transfer was high due to large adsorption sites available, the rate of mass transfer of adsorbate to the adsorption sites was unable to cope with the high feed concentration and not all of the adsorbate was transported to the adsorption sites within the designated residence time. Thus, some of the adsorbate was still in the liquid phase rather than in the solid phase. At the same time, the adsorption of ammoniacal nitrogen was inhibited by the presence of carbohydrate constituents and

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Figure 3. Breakthrough curves of carbohydrate constituents, protein, and ammoniacal nitrogen in pretreated POME system with changing bed length of (a) 10 cm, (b) 20 cm, and (c) 30 cm at constant feed flowrate of 9.43 mL/min. The notation (s) means simulation results.

protein, as discussed in the earlier section. Consequently, immediate breakthrough was observed, and for the first 10 h, the Ct/C0 ratio increased rapidly as the adsorption sites available decreased rapidly when the adsorption sites were filled with the adsorbate at high mass transfer rate. After the first 10 h, most of the adsorbent was plugged with adsorbate and the number of adsorption sites available had decreased. This resulted in a weaker driving force of mass transfer, impeding the

movement of adsorbate. Hence, the breakthrough curves became almost sluggish until the saturation was reached. To avoid the immediate breakthrough and points of inflection, the residence time must be increased by using a larger bed length or a lower feed flowrate to provide more adsorption sites. However, in the case of industrial application, long residence time is not favorable due to economic constraints. Thus, a residence time of >30 min is not investigated in the present study.

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Figure 4. Breakthrough curves of carbohydrate constituents, protein, and ammoniacal nitrogen in pretreated POME system with changing feed flowrate of (a) 18.86 mL/min and (b) 6.29 mL/min. The notation (s) means simulation results. Table 5. Saturation Time from Breakthrough Curves of Carbohydrate Constituents, Protein, and Ammoniacal Nitrogen in Pretreated POME Adsorption td (h)

a

run

τ (min)

(1)a

(2)a

(3)a

1 2 3 4 5

10 20 30 10 30

50 59 67 47 66

54 63 68 52 66

7 7 14 4 12

(1) Carbohydrate constituents; (2) protein; and (3) ammoniacal nitrogen. Figure 5. Comparison of experimental COD against calculated COD.

COD Correlation. The correlation in the present study related the concentrations of all organic solutes (Cp,carbohydrate, Cp,protein, and Cp,nitrogen) with the COD value in the adsorption system. The correlation was obtained by using the multivariable regression of the Levenberg-Marquardt method. The values of the dimensionless coefficients b1, b2, and b3 were 1.2599, 0.2708, and 0.5595, respectively, obtained using eq 18. The final correlation is given by eq 21.

CODcalculated ) 1.2599Cp,carbohydrate + 0.2708Cp,protein + 0.5595Cp,nitrogen (21)

The comparison of the experimental data and the model predictions is shown in Figure 5. It shows that the correlation was successfully applied in the prediction of COD concentration in the adsorption system with the mean sum of percent errors, ∑%E, of (6.7%. Figure 6 shows the breakthrough curves of COD for the pretreated POME adsorption on GAC based on the experimental conditions shown in Table 4. The simulation results based on the correlation of eq 21 show a good agreement with the experimental data with the mean sum of percent errors, ∑%E, of (2%-(6% for Runs 1-5. This demonstrates that, in the

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Figure 6. Breakthrough curves of COD for the pretreated POME adsorption on GAC. The notation (s) means simulation results.

ternary system of pretreated POME, the solutes of carbohydrate constituents, protein, and ammoniacal nitrogen had successfully correlated to its COD value. The breakthrough curves achieved saturation in terms of COD at 55, 59, 65, 55, and 66 h for Runs 1-5, respectively. Most of the COD were removed in the first hour as most of the organic solutes had also been removed in the first hour, as indicated in Figures 3 and 4. Initially, the number of adsorption sites available is higher and the driving force for the mass transfer is greater. Therefore, the adsorbate reaches the adsorption site with ease. With time, the number of active sites becomes less and the adsorbent is plugged with adsorbate, thus impeding the movement of adsorbate.18 By comparing the breakthrough curves of Figures 3 and 4 with Figure 6, the breakthrough curves of COD had a similar trend as the breakthrough curves of carbohydrate constituent for all the experimental conditions. This indicates that most of the COD in pretreated POME was contributed by the carbohydrate constituents, and this is in line with the results obtained in the multivariable regression of eq 21 where the coefficient of b1 obtained the highest value compared to the coefficients of b2 and b3. Conclusion A mathematical model suitable for the multicomponent adsorption system on GAC based on the incorporation of IAST into HSDM has been developed. The comparisons between the proposed model and the experimental data of ternary solutes system (pretreated POME) adsorption on GAC showed a good agreement and proved its utility in predicting the performance of the multicomponent adsorption system. The present study proved that, when complex organic solutions (pretreated POME) are used especially for industrial wastewater, the model needs only representative solutes to obtain the single-solute isotherm relationships. Once those isotherm relationships are obtained, the model allows multicomponent calculations to be performed. In the case of the pretreated POME adsorption system, the soluble starch, soy protein, and ammonium chloride had been successfully used as the representative solutes of carbohydrate constituents, protein, and ammoniacal nitrogen in the pretreated POME for multicomponent adsorption calculations. The correlation for the concentrations of the carbohydrate constituents, protein, and ammoniacal nitrogen of pretreated POME with the COD value has been successfully developed.

The experimental and simulation results illustrate that the pretreated POME adsorption on GAC was effective in removing the COD, as most of the COD were removed in the first hour and the adsorbent achieved saturation only after 55 h. Acknowledgment The authors would like to gratefully acknowledge Federal Land Development Authority Foundation (Yayasan Felda) of Malaysia for their financial support. The authors would also like to thank United Oil Palm Industry, Nibong Tebal, Pulau Pinang, for providing the sample of POME to conduct this research. Nomenclature A ) surface area of the adsorbent, m2 bi ) dimensionless coefficient Ci ) bulk liquid-phase concentration of the adsorbate i, mg/L Cfi ) concentration of the adsorbate i in the feed, mg/L C 0i ) initial liquid-phase concentration of adsorbate i, mg/L Cei ) equilibrium liquid-phase concentration of adsorbate i, mg/L Csi ) equilibrium concentration of adsorbate i, mg/L CCOD ) total COD concentration in the system, mg/L d ) inlet diameter, m dp ) particle diameter, m dpi ) average particle size for each pair of consecutive sieves, µm Dsi ) diffusivity coefficient of adsorbate i, m2/s Dvi ) molecular diffusion coefficient of the adsorbate i, m2/s ∑%E ) mean sum of percent errors, % Ki ) Freundlich capacity parameter, (mg/g)/(mg/L)1/n kfi ) external mass transfer coefficient of adsorbate i, m/s L ) bed length, m LB ) length of used bed, m 1/ni ) Freundlich intensity parameter Q ) feed flowrate, m3/s qi ) solid-phase loading of adsorbate i on the GAC particle, mg/g q0i ) solid-phase surface loading corresponding to C0i , mg/g qei ) solid-phase surface loading at equilibrium for adsorbate i, mg/g qT ) total mass of adsorbate, mg/g r ) radial axis of GAC particle, m R ) particle radius, m

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R ) universal gas constant, cal/mol‚K Re ) Reynolds number Sci ) Schmidt number of the adsorbate i Shi ) Sherwood number of the adsorbate i t ) time parameter, s tb ) the break-point time, s td ) the saturation time, s tt ) the time equivalent to the total capacity of the bed, s tu ) the time equivalent to the usable capacity of the bed up to the break-point time, s T ) temperature, K VAi ) molar volume of the adsorbate i, m3/kmol Vs ) influent water approach velocity, m/s ∆xi ) increment of weight fraction in each pair X ) variable of Ci/Cfi z ) coordinate along the longitudinal bed axis, m Zi ) mass fraction of adsorbate i  ) porosity of the GAC bed uw ) viscosity of water, Pa‚s Fp ) GAC particle density, kg/m3 Fw ) density of water, kg/m3 π ) spreading pressure, N/m π0i ) spreading pressure of the adsorbate i at equilibrium, N/m τ ) residence time, s Literature Cited (1) Hwang, T. K.; Ong, S. M.; Seow, C. C.; Tan, H. K. Chemical composition of palm oil mill effluents. Planter 1978, 54, 749. (2) Ahmad, A. L.; Ismail, S.; Bhatia, S. Water recycling from palm oil mill effluent (POME) using membrane technology. Desalination 2003, 157, 87. (3) Ho, C. C.; Tan, Y. K.; Wang, C. W. The distribution of chemical constituents between the soluble and the particulate fractions of palm oil mill effluent and its significance on its utilization/treatment. J. Agric. Wastes 1984, 11, 61. (4) Chow, M. C. Palm oil mill effluent analysis; Palm Oil Research Institute of Malaysia: Kuala Lumpur, Malaysia, 1991; pp 11-18.

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ReceiVed for reView March 26, 2006 ReVised manuscript receiVed July 12, 2006 Accepted August 1, 2006 IE0603722