Fixed bed studies for the sorption of chromium(VI) onto tea factory waste

Chemical Engineering Science 61 (2006) 4363 – 4372 www.elsevier.com/locate/ces

Fixed bed studies for the sorption of chromium(VI) onto tea factory waste Emine Malkoc ∗ , Yasar Nuhoglu Department of Environmental Engineering, Faculty of Engineering, Atatürk University, 25240 Erzurum, Turkey Received 23 June 2005; received in revised form 30 January 2006; accepted 5 February 2006 Available online 11 April 2006

Abstract The adsorption of Cr(VI) ions from aqueous solutions onto waste of tea factory in fixed beds was investigated. Experiments were carried out as a function of liquid flow rate, initial feed of Cr(VI) concentration, particle size, feed solution pH and bed depth. The bed capacities were found to increase with decreasing flow rate and particle size. The maximum bed capacities for the tested flow rates were found to be 55.65, 40.41 and 33.71 mg g−1 at 5, 10 and 20 ml min−1 , respectively. When the initial Cr(VI) concentration is increased from 50 to 200 mg l−1 , the corresponding adsorption bed capacity appears to increase from 27.67 to 43.67 mg g−1 . The longest breakthrough time and maximum of Cr(VI) adsorption is obtained at the lowest examined pH value. Decrease in the particle size from 1.00–3.00 to 0.15–0.25 mm resulted in significant increase in the treated volume, breakthrough time and bed capacity. Breakthrough volume varies with bed depth and the treated volume considerably increases from about 4200 to 11 800 ml as the bed depth increases from 5 to 30 cm. Thomas model for tea factory waste on Cr(VI) adsorption was used to predict the breakthrough curves under varying experimental conditions. This study indicated that the tea factory waste can be used as an effective and environmentally friendly adsorbent for the treatment of Cr(VI) ions in aqueous solutions. 䉷 2006 Elsevier Ltd. All rights reserved. Keywords: Fixed bed; Adsorption; Waste tea; Thomas model; Breakthrough curve

1. Introduction Heavy metals such as mercury, lead, cadmium, copper, chromium and nickel are toxic even in extremely minute quantities on human health and to the fauna and flora of receiving water. It is known that legal standards on environmental control are becoming strict and, as a result, the discharge of heavy metals into aquatic bodies and sources of potable water is being rigorously controlled. Chromium is widely used in electroplating, leather tanning, metal finishing and chromate preparation. Chromium exists in two stable oxidation states Cr(III) and Cr(VI). The Cr(VI) state is of particular concern because of its toxicity (Selvaraj et al., 2003). Chromate and dichromate ions affect digestive organs and have caused widespread dermatitis and penetrating ulcers in the hands and forearms (Rojas et al., 2005). The daily maximum permissible concentration of total chromium in effluents in the US for plants discharging 38 000 l or more per calendar day of electroplating process wastewater ∗ Corresponding author. Tel.: +90 442 231 4602; fax: +90 442 236 0957.

E-mail address: [email protected] (E. Malkoc). 0009-2509/$ - see front matter 䉷 2006 Elsevier Ltd. All rights reserved. doi:10.1016/j.ces.2006.02.005

is 7 mg l−1 and four day average value limits is 4 mg l−1 (US EPA, 1984). Drinking water levels which are considered “safe” for short-term exposures: for a 10-kg child consuming 1 l of water per day, a 1- to 10-day exposure to 1 mg l−1 , a longer-term (7 years) exposure to 0.2 mg l−1 . Chromium has the potential to cause the following health effects from long-term exposures at levels above the MCL: damage to liver, kidney circulatory and nerve tissues, dermatitis (US EPA, 1995). The removal of Cr(VI) from industrial effluents is important before discharging them into aquatic environments or onto land. A wide range of physical and chemical processes is available for the removal of Cr(VI) from wastewater. Currently, the more common processes for eliminating chromium are adsorption by activated carbon, reverse osmosis and chemical reactions that involve reduction and precipitation (Tiravanti et al., 1997; Sag and Aktay, 2001; Rojas et al., 2005; Sarin and Pant, 2005). These treatments are neither complete nor satisfactory because of their high cost and inefficiency in achieving safe discharges or avoiding secondary pollution (Rojas et al., 2005). Also, these methods are ineffective for Cr(VI) concentrations lower than 100 mg l−1 and prohibitively costly (Garg et al., 2004).

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The process of adsorption is a well established and powerful technique for wastewater treatment. Activated carbon has traditionally been the most widely used adsorbent for heavy metals. The need for safe and economical methods for removing heavy metals from contaminated waters has resulted in the search for alternative materials that may be useful to reduce the metal content to the levels established by the legislation. Tea factory waste has been used as adsorbent for copper(II) and cadmium(II) by Çay et al. (2004). Their experimental results show that it may be used effectively in the removal of copper(II) and cadmium(II) ions from aqueous solutions. A thorough literature survey indicated that tea factory waste has not been used as an adsorbent for the removal of Cr(VI) ions in batch and fixed bed thus far. The removal of hexavalent chromium has been studied using diatomite treated with microemulsion (Dantas et al., 2001), bagasse and fly ash (Rao et al., 2002), maple sawdust (Yu et al., 2003), green algae (Malkoc and Nuhoglu, 2003), beech sawdust (Acar and Malkoc, 2004) and Mucor mold (Tewari et al., 2005). Tea plants (Camellia sinensis (L) Kuntze) are commonly grown in the Eastern Black Sea region of Turkey. Dried and cured leaves are widely used for a beverage, which has a stimulant effect due to caffeine. High quality tea is harvested from the three top leaves of the shoot on tea plant in the teagarden. Tea is considered an astringent, a stimulant, and acts as a nerve sedative, frequently relieving headaches. It may also cause unpleasant nerve and digestive disturbances. While tea producer cuts the top tea leaves with special tea shears, some overgrown woody shoots, which may include six to seven top leaves, gets mixed in the tea harvest. During the tea production procedure, this woody overgrown shoots were not treated by tea factory and formed into tea factory waste. There are much tea factories in the Eastern Black Sea region and they produce about 30 000 tons of tea factory wastes. Tea factory wastes are not used for any purpose and it deposits in depository area or are occasionally discharged in small bays in the Black Sea (Malkoc, 2005). Most previous research using biosorbents for metal ions is based on batch kinetic and batch equilibrium studies. However, in the practical operation of full-scale biosorption processes, continuous-flow fixed bed columns are often preferred. In such systems, the concentration profiles in the liquid and adsorbent phases vary in both space and time. As a result, design and optimization of fixed bed columns are difficult to carry out a priori without a quantitative approach. From the perspective of process modeling, the dynamic behavior of a fixed bed column is described in terms of breakthrough curve (Chu, 2004). The time for breakthrough appearance and the shape of the breakthrough curve are very important characteristics for determining the operation and the dynamic response of an adsorption column. The breakthrough curves show the loading behavior of metal to be removed from solution in a fixed bed and is usually expressed in terms of adsorbed metal concentration (Cad ), inlet metal concentration (C0 ), outlet metal concentration (Ct ) or normalized concentration defined as the ratio of effluent metal concentration to inlet metal concentration (Ct /C0 ) as a function of time or volume of effluent for a given bed height (Aksu

and Gönen, 2004). Effluent volume (Veff ) can be calculated as Veff = Qt,

(1)

where t and Q are the total flow time (min) and volumetric flow rate (ml min−1 ). The area under the breakthrough curve (A) obtained by integrating the adsorbed concentration (Cad ; mg l−1 ) versus t (min) plot can be used to find the total adsorbed metal quantity (maximum column capacity). Total adsorbed metal quantity (qtotal ; mg) in the column for a given feed concentration and flow rate is calculated as
t=ttotal QA Q qtotal = Cad dt. (2) = 1000 1000 t=0 Total amount of metal ion sent to column (mtotal ) is calculated as mtotal =

C0 Qt total . 1000

Total removal is calculated as qtotal × 100. Total removal % = mtotal

(3)

(4)

Equilibrium metal uptake (qeq ) (or maximum capacity of the column) in the column is defined by Eq. (5) as the total amount of metal sorbed (qtotal ) per g of sorbent (X) at the end of total flow time (Aksu and Gönen, 2004) qeq =

qtotal . X

(5)

Tea factory waste as an adsorbent for Cr(VI) is an economical material, which has been used fixed bed for the removal of Cr(VI) from aqueous solutions. The objectives of the present study is to adsorb Cr(VI) from aqueous solution by waste tea using fixed-bed column. The important design parameters such as column bed height, flow rate of metal solution into column, pH of solution, initial concentration of metal solution and particle size of waste tea have been investigated. The breakthrough curves for the adsorption of metals were analyzed using the Thomas model. 2. Methods 2.1. Adsorbent The tea factory waste was obtained from tea plants located in Black Sea region in Giresun-Eynesil, Turkey. It is ground in a blender and sieved to constant size (1.00–3.00 mm). The chemical and physical characteristics of the tea waste is presented in Table 1. Prior to the experiments, other soluble dirtiness and colored components were removed from the waste tea by washing with distilled water in a glass container for many times until a colorless solution of tea waste was spectrometrically observed at room temperature. Decolorized and cleaned tea waste was dried at room temperature for three days by spreading on a gauze. Scanning electron microscopy (SEM) of material using waste of tea factory was carried out in a JEOL JSM T-330 unit. In

E. Malkoc, Y. Nuhoglu / Chemical Engineering Science 61 (2006) 4363 – 4372 Table 1 Physical and chemical properties of waste tea used in the experiments

Units 0.112 0.39

1 3

2 300

Physical characteristic Bulk density (g cm−3 ) BET surface area (m2 g−1 )

100

Percent (%) 11.01 6.04 80.24 2.97 94.06

6

1.Column 2.Termostat 3.Rotameter 4.Pump 5.Feed storage 6.Sample collection

100

Chemical characteristic (Çay et al., 2004) Moisture Water soluble components Insoluble components Ash Total loss of ignition

4365

100

4

5

Fig. 3. Experimental system for fixed bed operation.

of particles after adsorption in Fig. 2 that the pores and surfaces of adsorbent were covered and became smooth by adsorbate. 2.2. Adsorbate

Fig. 1. SEM micrograph of the particles of waste tea before Cr(VI) adsorption.

A stock solution of hexavalent chromium (1000 mg l−1 ) was prepared in distilled water with potassium dichromate. All working solutions of varying Cr(VI) concentrations (50, 75, 100, 200 mg l−1 ) were obtained by diluting the stock solution with distilled water. 2.3. Experimental set-up

Fig. 2. SEM micrograph of the particles of waste tea after Cr(VI) adsorption.

A schematic diagram for the pilot plant fixed-bed column systems is shown in Fig. 3. The fixed-bed columns were made of Perspex tubes 2.0 cm internal diameter and 30 cm in height. The bed length used in the experiments was 10 cm. In a typical experiment the known concentration of Cr(VI) solutions was pumped at a fixed flow rate to filled the bed height. The particle size of adsorbent used in the experiment was 1.00–3.00 mm. The pH of the solutions was maintained constant at 2.0. The pH of the solution was adjusted with diluted sulfuric acid and diluted ammonia solutions. The temperature of stream feeding solution and of the column was controlled at 25 ◦ C through a thermostatic bath. The bed porosity was 0.42. The bed porosity which is the fraction of total volume that is void is defined as porosity = volume void/volume of entire bed. 2.4. Analytical methods

order to see the surfaces of particles after and before adsorption, SEM images for the samples of the raw and treated adsorbents were obtained (Figs. 1 and 2). It is clearly seen from the surfaces

Liquid samples of the concentration of Cr(VI) in the exit of the column were collected at 1, 15, 30 and 60 min, and then the samples were collected periodically per 1 h until Ct /C0
0.90.

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100 98

Transmittance

96 94 92 90 88 86 84 82 0

500 1000 1500 2000 2500 3000 3500 4000 4500 Frequency / cm-1

(a) 85

Transmittance

80

Ct 1 = , C0 1 + exp((kTH /Q)(q0 X − C0 Veff ))

75

70

65

60 0 (b)

through data obtained from the column studies were examined using the kinetic model developed by the Thomas model (1948). Successful design of a column adsorption process requires prediction of the concentration–time profile or breakthrough curve for the effluent. The maximum adsorption capacity of an adsorbent is also needed in design. Traditionally, the Thomas model is used to fulfill the purpose (Aksu and Gönen, 2004). The Thomas or reaction model, which assumes Langmuir kinetics of adsorption–desorption and no axial dispersion, is derived from the adsorption that the rate driving force obeys second-order reversible reaction kinetics. Thomas’ solution also assumes a constant separation factor but it is applicable to either favorable or unfavorable isotherms. The primary weakness of the Thomas solution is that its derivation is based on second-order reaction kinetics. Adsorption is usually not limited by chemical reaction kinetics but is often controlled by interphase mass transfer. This discrepancy can lead to some error when this method is used to model adsorption process (Rao and Viraraghavan, 2002; Aksu and Gönen, 2004). The expression of the Thomas model for an adsorption column is as follows (Fu and Viraraghavan, 2003):

500 1000 1500 2000 2500 3000 3500 4000 4500 Frequency /cm-1

Fig. 4. The FTIR spectra of waste tea: (a) before adsorption, (b) after adsorption.

Cr(VI) concentration was then determined using an indirect UV-visible spectrophotometric method based on the reaction of Cr(VI) and diphenyl carbazid, which forms a red–violet colored complex. The absorbance of the colored complex was measured in a double beam spectrophotometer at 540 nm wavelength (Acar and Malkoc, 2004). 2.5. Fourier transform infrared spectroscopy

(6)

where kTH is the Thomas rate constant (ml min−1 mg−1 ), q0 the maximum solid-phase concentration of the solute (mg g−1 ), Veff the effluent volume (ml), X the mass of adsorbent (g), and Q the flow rate (ml min−1 ). The linearized form of the Thomas model is as follows:   kTH q0 X kC 0 Veff C0 − . (7) −1 = ln Ct Q Q The kinetic coefficient kTH and the adsorption capacity of the bed q0 can be determined from a plot of ln[(C0 /Ct )−1] against t at given conditions. The breakthrough curves showed the superposition of experimental results (points) and the theoretical calculated points (lines). Linear regression coefficients (R 2 ) showed the fit between experimental data and linearized forms of Thomas equations while the average percentage errors (
%) calculated according to Eq. (8) indicated the fit between the experimental and predicted values of Ct /C0 used for plotting breakthrough curves N i=1 [((Ct /C0 )exp − (Ct /C0 )theo )/(Ct /C0 )exp ] × 100, ε= N (8)

The infrared spectra were obtained (and transferred to Microsoft Excel) using Perkin–Elmer Spectrum One FTIR spectrometer. The FTIR spectra before and after adsorption of tea factory waste are shown in Fig. 4a and b.

where N is the number of measurements.

2.6. Mathematical modeling of breakthrough curves

3.1. Effect of volumetric flow rate

Various mathematical models can be used to describe fixedbed adsorption. Among these the Thomas model (1948) is simple to use in the design of a fixed-bed adsorption column and the Thomas solution is one of the most general and widely used methods in column performance theory. Therefore, the break-

Typical experimental and predicted breakthrough curves are shown in Fig. 5. Cr(VI) adsorption in fixed bed column from an influent solution 100 mg l−1 was tested at three flow rates in the range 5–20 ml min−1 . Fig. 5 shows that the breakthrough curves shifted towards the origin with decreasing flow rate.

3. Results and discussion

E. Malkoc, Y. Nuhoglu / Chemical Engineering Science 61 (2006) 4363 – 4372

1

1

0.8

0.8

0.6

Ct/C0

Ct/Co 0.4

50 mg/L,exp 75 mg/L,exp 100 mg/L,exp 200 mg/L,exp 50 mg/L,theo 75 mg/L,theo 100 mg/L,theo 200 mg/L,theo

0.6

5 ml/min, exp 10 ml/min, exp 20 ml/min, exp 5 ml/min, theo 10 ml/min, theo 20 ml/min, theo

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0.4

0.2 0.2

0 0

3000

6000 9000 Veff (ml)

12000

15000

Fig. 5. The measured and modeled breakthrough curves for adsorption of Cr(VI) onto waste tea at different flow rates (C0 = 100 mg l−1 , bed depth = 10 cm, particle size = 1.0–3.0 mm, pH = 2.0).

Lower flow rates result in high residence times in the column. It is well known that because of the relatively slow loading kinetics of waste tea, relatively long residence times are needed. In actual column operation, any volume element of the solution is in contact with a given layer of the bed for only a limited period of time, usually insufficient for attainment of equilibrium. Thus the failure of attaining local equilibrium results in lower uptake of Cr(VI) from the influent solution (Inglezakis and Grigoropoulou, 2004). When the flow rate was increased from 5 to 20 ml min−1 the time required for complete column saturation decreased from 1440 to 600 min. As seen in Fig. 5, a shallow breakthrough curve is obtained at the highest flow rate tested. If the saturation time of the solute in the fixed bed column is not long enough for the adsorption equilibrium to be reached at high flow rate (20 ml min−1 ), Cr(VI) solution leaves the adsorption column before the equilibrium occurs. The maximum bed capacities decreased with the increase in flow rates. Results are given in Fig. 5 and show that the uptake of metal ions onto the waste tea decreases when the flow rate through the bed increases. An increase in the flow rate reduces the volume treated efficiently until breakthrough point and therefore decreases the service time of the bed. This is due to the decrease in contact time between the metal ions and the waste tea at higher linear flow rates. As the adsorption rate is controlled by intraparticulate diffusion, an early breakthrough occurs leading to a low bed adsorption capacity (Taty-Costodes et al., 2005) (Table 3). These results are also in agreement with those referred to the literatures (Zulfadhly et al., 2001; Aksu and Gönen, 2004). When the flow rate decreases the contact time in the

0 0

2000

4000 6000 Veff (ml)

8000

10000

Fig. 6. The measured and modeled breakthrough curves for adsorption of Cr(VI) onto waste tea at different feed concentration (Q = 10 ml min−1 , bed depth = 10 cm, particle size = 1.0–3.0 mm, pH = 2.0).

column is longer, intra-particulate diffusion then becomes effective. Thus the Cr(VI) ions have more time to diffuse amidst the particles of waste tea and a better adsorption capacity is obtained (Table 3). At a higher linear flow rate, the adsorbent gets saturated early, certainly because of a reduced contact time, a larger amount of Cr(VI) ions are adsorbed on the waste tea and there is a weak distribution of the liquid into the column, which leads to a lower diffusivity of the solute amidst the particles of the waste tea. This shows an increase in the uptake of the metal ions due to the intra-particulate phenomena (Taty-Costodes et al., 2005). The maximum bed capacities for tested flow rates of 5, 10 and 20 ml min−1 were 55.65, 40.41 and 33.71 mg g−1 , respectively. It was also found that the biosorbent gets saturated early at higher flow rate (20 ml min−1 ). 3.2. Effect of feed Cr(VI) concentration The breakthrough curves of Cr(VI) ion concentrations were obtained at increasing initial feed Cr(VI) ions concentrations in the range 50–200 mg l−1 at constant flow rate, pH and bed height. Fig. 6 describes the breakthrough characteristics at these concentrations. Adsorbent of waste tea gets saturated early at high concentration. The breakthrough time considerably decreases from about 660 min to less than 360 min as the concentration increases from 50 to 200 mg l−1 . A rise in the inlet metal concentration reduces the treated volume before the fixed bed adsorption bed gets saturated. A high metal concentration may saturate the waste of tea factory more quickly, thereby decreasing the breakthrough time.

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1

1

0.8

0.8

Ct/C0

0.6 0.6 Ct/C0

pH=2.0,exp pH=3.0,exp pH=4.0,exp pH=5.0,exp pH=2.0,theo pH=3.0,theo pH=4.0,theo pH=5.0,theo

0.4

5 cm,exp 10 cm,exp 20 cm,exp 30 cm,exp 5 cm,theo 10 cm,theo 20 cm,theo 30 cm,theo

0.4

0.2

0.2 0 0

3000

0 0

2000

4000

6000 Veff (ml)

8000

10000

9000 6000 Veff (ml)

12000

15000

12000

Fig. 7. The measured and modeled breakthrough curves for adsorption of Cr(VI) onto waste tea at solution pH (Q = 20 ml min−1 , bed depth = 30 cm, particle size = 1.0–3.0 mm, C0 = 100 mg l−1 ).

Also, it is clear that the maximum bed capacity of Cr(VI) decreased with the increase in the initial concentration influent Cr(VI). For tested different initial Cr(VI) concentration, maximum bed capacities at 50, 75, 100 and 200 mg l−1 Cr(VI) concentrations were 27.67, 34.46, 40.41 and 43.67 mg g−1 , respectively. Decreasing the feed Cr(VI) concentration increases the treated volume of feed metal concentration that can be processed, and shifts the breakthrough curve to the right. The driving force for adsorption is the concentration difference between the solute on the sorbent and the solute in the solution. A high concentration difference provides a high driving force for the adsorption process and this may explain why higher adsorption capacities were achieved in the column fed with a higher Cr(VI) concentration. The relatively low Cr(VI) retention for adsorbent can be attributed to the difference in the surface morphology. Adsorbent particles do not have many micro- or macropores, so its low surface area also results in lower sorption capacity (Aksu and Gönen, 2004). 3.3. Effect of solution pH The most important single parameter influencing the sorption capacity is the pH of adsorption medium. The initial pH of adsorption medium is related to the adsorption mechanisms onto the adsorbent surface from water and reflects the nature of the physicochemical interaction of the species in solution and the adsorptive sites of adsorbent (Aksu and Gönen, 2004). The pH of feed solution is an important controlling parameter in the heavy metal adsorption process and thus the role of hydrogen

Fig. 8. The measured and modeled breakthrough curves for adsorption of Cr(VI) onto waste tea at bed height (Q = 10 ml min−1 , C0 = 100 mg l−1 , particle size = 1.0–3.0 mm, pH = 2.0).

ion concentration was examined from solutions at different pH, covering a range of 2.0–5.0. As seen in Fig. 7, Cr(VI) adsorption on waste of tea factory, the highest maximum bed capacity and the longest breakthrough time is obtained at the lowest examined pH value. The maximum of Cr(VI) adsorption occurs at pH 2.0. It was shown that with an decrease in the influent feed solution pH, the breakthrough curves shifted from left to right, which indicated that more Cr(VI) ions were removed. The amounts of Cr(VI) ions adsorbed per unit weight of beds for pH 2.0, 3.0, and 5.0 were 33.71, 28.07 and 23.76 mg g−1 , respectively. It is well known that the dominant form of Cr(VI) at this pH value is the acid chromate ion species (HCrO− 4 ) and increasing the pH will shift the concentration of HCrO− 4 to other 2− 2− forms, CrO2 and Cr 2 O7 . At very low pH values, the surface of adsorbent would also be surrounded by the hydrogen ions which enhance the Cr(VI) interaction with binding sites of the adsorbent by greater attractive forces. As the pH increased, the overall surface charge on the adsorbent became negative and adsorption decreased (Aksu et al., 2002). Also, as pH of feed Cr(VI) concentration increased, breakthrough time or treated volume decreased. As observed from Fig. 7, the treated volume considerably decreases from about 9600 (breakthrough time 480 min) to 7200 ml (breakthrough time 360 min) as the solution pH increases from 2.0 to 5.0. 3.4. Effect of bed depth The breakthrough curves obtained for Cr(VI) ions adsorption are illustrated in Fig. 8 for different bed depth of waste of tea factory (5, 10, 20 and 30 cm), at a constant linear flow

E. Malkoc, Y. Nuhoglu / Chemical Engineering Science 61 (2006) 4363 – 4372

1

0.8

0.6 Ct/C0

rate of 10 ml min−1 . They follow the characteristic “S” shaped profile produced in ideal adsorption systems. Results indicate that the breakthrough volume varies with bed depth. When the bed depth is reduced, axial dispersion phenomena predominate in the mass transfer and reduce the diffusion of metallic ions. The solute (metallic ions) does not have enough time to diffuse into the whole of the adsorbent mass (Taty-Costodes et al., 2005). As observed from Fig. 8, the treated volume considerably increases from about 4200 to 11 800 ml as the bed depth increases from 5 to 30 cm. Also, an increase in the maximum bed adsorption capacity (q0,cal ) is noticed at the breakthrough point with the increase in bed depth (Table 3). This increase in the adsorption capacity with that in the bed depth can be due to the increase in the specific surface of the adsorbent which supplies more fixation binding sites. Then it follows that a delayed breakthrough of the pollutant leads to an increase in the volume of solution treated. The increase in adsorption with that in bed depth was due to the increase in adsorbent doses in larger beds which provide greater surface area (or adsorption sites). The maximum bed capacities for different bed depth, 5, 10, 20 and 30 cm, were 34.97, 40.41, 49.93 and 56.96 mg g−1 , respectively.

3.6. Fourier transform infrared spectroscopy (FTIR) analysis The functional groups before and after adsorption on waste tea and the corresponding infrared absorption frequencies are shown in Table 2.

0.15-0.25 mm,exp 0.25-0.50 mm,exp 0.50-1.00 mm,exp 1.00-3.00 mm,exp 0.15-0.25 mm,theo 0.25-0.50 mm,theo 0.50-1.00 mm,theo 1.00-3.00 mm,theo

0.4

0.2

0

3.5. Effect of particle size The experiments were carried out for four different particle (waste tea) sizes: 0.15–0.25, 0.25–0.50, 0.50–1.00 and 1.00–3.00 mm under constant flow rates (10 ml min−1 ), bed depth (10 cm) and initial feed Cr(VI) concentration (100 mg l−1 ). The amount of waste materials (completely filled in 10 cm) was taken as 12, 11, 10 and 3.5 g for 0.15–0.25, 0.25–0.50, 0.50–1.00 and 1.00–3.00 mm, respectively. Smaller than average size particles can produce a delay of the breakthrough while larger than average particles, which approach equilibrium more slowly, can cause the opposite effect on the breakthrough curve (Rivero et al., 2002) That is to say, in the finer particle size ranges, adsorption breakthrough curves followed a much more efficient profile than larger particle size ranges, in that the breakthrough time increased and the curves tended towards the classic “S” shaped profile. As observed from Fig. 9, decrease in the particle size from 1.00–3.00 (the largest particle size in this study) to 0.15–0.25 mm (the smallest size) resulted in significant increase in the treated volume, breakthrough time and bed capacity. This enhanced bed capacity is probably due to a higher overall rate of diffusion because of the higher available interfacial area and adsorbent dosage. For tested different particle size, maximum bed capacities and treated volume at 0.15–0.25, 0.25–0.50, 0.50–1.00 and 1.00–3.00 mm particle size were 54.68, 47.77, 44.03, 35.15 mg g−1 and 15 000, 12 600, 10 800, 7200 ml, respectively.

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0

5000

10000 Veff (ml)

15000

20000

Fig. 9. The measured and modeled breakthrough curves for adsorption of Cr(VI) onto waste tea at different particle sizes (Q = 10 ml min−1 , C0 = 100 mg l−1 , bed depth = 10 cm, pH = 2.0).

Table 2 The FTIR spectral characteristics of tea factory waste before and after adsorption IR peak

1 2 3 4 5 6 7 8 9 10

Frequency (cm−1 ) Before ads.

After ads.

Differences

3420 2915 2848 1631 1429 1345 1232 1141 1030 614

3407 2917 2849 1631 1429 1367 1237 1137 1035 583

−13 +2 +1 0 0 +22 −5 −4 +5 −31

Assignment

Bonded –OH groups Aliphatic C–H group Aliphatic C–H group C&O stretching Symmetric bending of CH3 Symmetric bending of CH3 –SO3 stretching C–O stretching of ether groups –C–C–group –CN stretching

As shown in Fig. 4a, b and Table 2, the spectra display a number of absorption peaks, indicating the complex nature of tea factory waste. The FTIR spectroscopic analysis indicated broad bands at 3420 cm−1 , representing bonded –OH groups. The bands observed at about 2915–2848 cm−1 could be assigned to the aliphatic C–H group. The peak around 1631 cm−1 corresponds to the C&O stretch. Symmetric bending of CH3 is observed to shift to 1429 and 1345 cm−1 . The peaks observed

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Table 3 Parameters predicted from the Thomas model and model deviations for Cr(VI) adsorption to waste of tea factory at different experimental conditions Exp. parameters

Q Initial pH Initial Cr(VI) conc. Particle size Bed depth Temperature q0,exp q0,cal kTH × 10−4 R2 (ml min−1 ) C0 (mg l−1 ) (mm) (cm) (◦ C) (mg g−1 ) (mg g−1 ) (ml min−1 mg−1 )

Flow rate

5 10 20

2.0 2.0 2.0

100 100 100

1.00–3.00 1.00–3.00 1.00–3.00

10 10 10

25 25 25

55.65 40.41 33.71

45.35 35.15 25.20

0.6 0.9 0.9

0.863 10.75 0.984 3.50 0.823 11.20

C0

10 10 10 10

2.0 2.0 2.0 2.0

50 75 100 200

1.00–3.00 1.00–3.00 1.00–3.00 1.00–3.00

10 10 10 10

25 25 25 25

27.67 34.46 40.41 43.67

23.52 35.40 35.15 48.66

0.5 0.6 0.9 1.0

0.893 0.924 0.984 0.977

pH

20 20 20 20

2.0 3.0 4.0 5.0

100 100 100 100

1.00–3.00 1.00–3.00 1.00–3.00 1.00–3.00

30 30 30 30

25 25 25 25

33.71 28.07 22.86 23.76

25.20 28.76 19.16 22.87

0.9 1.6 1.2 1.4

0.823 11.20 0.913 9.80 0.878 5.70 0.914 3.55

Bed height

10 10 10 10

2.0 2.0 2.0 2.0

100 100 100 100

1.00–3.00 1.00–3.00 1.00–3.00 1.00–3.00

5 10 20 30

25 25 25 25

34.97 40.41 49.93 56.96

39.19 35.15 59.60 55.4

1.0 0.9 0.9 0.9

0.922 4.50 0.983 3.50 0.862 32.18 0.949 6.18

Particle size 10 10 10 10

2.0 2.0 2.0 2.0

100 100 100 100

0.15–0.25 0.25–0.50 0.50–1.00 1.00–3.00

10 10 10 10

25 25 25 25

54.68 47.77 44.03 40.41

50.76 48.98 46.34 35.15

0.4 0.5 0.5 0.9

0.923 15.60 0.971 7.22 0.983 3.20 0.983 3.50

at 1232, 1141 and 1030 and 614 cm−1 could be assigned to –SO3 stretching, C–O stretching of ether groups, –C–C–group and –CN stretching, respectively. There were clear band shifts and intensity decrease of the band at 3420, 1232, 1141 and 614 cm−1 . As seen in Table 2, the spectral analysis before and after metal adsorption indicated that especially the bonded –OH groups, –SO3 stretching, C–O stretching and –CN stretching were especially involved in Cr(VI) biosorption(Park et al., 2005). Many studies have claimed that Cr(VI) was removed from the aqueous phase through an adsorption mechanism, whereby anionic Cr(VI) ion species bind to the positively charged groups of nonliving biomass (Malkoc and Nuhoglu, 2003; Acar and Malkoc, 2004; Park et al., 2004). It has been newly explained that Cr(VI) was completely reduced to Cr(III) by contact with biomass. Based on the present investigations, the following mechanism of Cr(VI) removal by nonliving biomass is proposed (Park et al., 2004, 2005). Cr(VI) can be removed from the aqueous phase by nonliving biomass through two mechanisms. In mechanism I (direct reduction), Cr(VI) is directly reduced to Cr(III) in the aqueous phase by contact with the electron-donor groups of the biomass, i.e., groups having lower reduction potential values than that of Cr(VI). Mechanism II (indirect reduction), however, consists of three steps: (1) the binding of anionic Cr(VI) ion species to the positively charged groups present on the biomass surface; (2) the reduction of Cr(VI) to Cr(III) by adjacent electron-donor groups; and (3) the release of the Cr(III) ions into the aqueous phase due to electronic repulsion between the positively charged groups and the Cr(III) ions, or the complexation of the Cr(III) with adjacent groups capable of Cr-binding (Park et al., 2005). Amino and carboxyl groups take part in reaction 1 in mechanism II. As the pH of the


%

8.23 4.66 3.50 3.08

aqueous phase is lowered, the large number of hydrogen ions can easily coordinate with the amino and carboxyl groups present on the biomass surface. Thus, low pH makes the biomass surface more positive. The more positive the surface charge of the biomass, the faster the removal rate of Cr(VI) in the aqueous phase, since the binding of anionic Cr(VI) ion species with the positively charged groups is enhanced (Malkoc and Nuhoglu, 2003; Park et al., 2005). The low pH also accelerates the reduction reaction in both mechanisms I and II, since the protons take part in this reaction. The solution pH is the most important controlling parameter in the practical use of nonliving biomass in the adsorption process (Nuhoglu and Oguz, 2003). Hence, it is of significance that the pH of wastewaters containing heavy metals is generally very acidic. Meanwhile, if there are a small number of electron-donor groups in the biomass or protons in the aqueous phase, the chromium bound to the biomass can remain in the hexavalent state. Therefore, a portion of mechanisms I and II depend on the biosorption system (solution pH, temperature, species on the biomass, and biomass and Cr(VI) concentrations) (Park et al., 2005).

3.7. Application of the Thomas model The advantage of this model is its simplicity and reasonable accuracy in breakthrough under various conditions. As observed from Figs. 5–9, the breakthrough curves showed the superposition of experimental results (points) and the theoretical calculated points (lines), for all experimental conditions. The column data for Cr(VI) were fitted to the linearized form of the Thomas model shown in Eq. (7). From linearized Thomas

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equation plots, the correlation coefficients (R 2 ), average percentage errors (
%), kTH and q0,cal were calculated for all tested experimental parameters and are shown in Table 3. As seen in Table 3 and Fig. 5, there was no good agreement between the experimental and predicted bed capacities at all tested experimental parameters. The correlation coefficients were between 0.823 and 0.984 at all tested experimental parameters. It is evident that q0,cal (mg g−1 ) values decrease and kTH (ml min−1 mg−1 ) values increase with increasing liquid flow rate (Q) (Table 3). Values of q0,cal obtained from the Thomas model were 45.35, 35.15 and 25.20 mg g−1 for 5, 10 and 20 ml min−1 , respectively. As shown in Table 3, the kTH value fairly decreases with increasing C0 . This is because the driving force of mass transfer in the liquid film is increased. The adsorption bed capacity values slightly increase with inlet Cr(VI) concentration (Table 3). The bed capacity of the column (q0,cal ) increases by about 63% when the inlet concentration varies from 50 to 200 mg l−1 . These results are in correlation with those observed when studying the breakthrough curves and explain the lower performance obtained when concentration is raised. The correlation coefficients are between 0.893 and 0.984. It is understood that the q0,cal value increases with increasing bed depth for Cr(VI) by waste of tea factory. However, increasing bed depth does not affect kTH value for waste tea bed. The correlation coefficients between the experimental and modeled values using Thomas model for all tested bed depth were between 0.862 and 0.983. The lowest adaptation was obtained at 20 cm bed depth and the experimental error was around 32.2%. The data in Table 3 also indicated that calculated q0,cal values are similar to experimental q0,exp values. As shown in Fig. 8, the experimental breakthrough curves were very close to the ones calculated according to Thomas model. Table 3 gives the results obtained from slopes and intercepts at different particle sizes, by calculations from Eq. (7). These results were compared with those obtained experimentally. The predicted q0,cal and kTH parameters show a good agreement with those obtained experimentally with a correlation coefficient superior to 0.92. The average percentage errors were between 3.2% and 15.6%. The highest average percentage errors were observed for the smallest particle size experiments. 4. Conclusion Adsorption of Cr(VI) ions through tea factory waste in a fixed bed column is an economically feasible technique for removing metal ions from a solution. These studies show that tea factory waste is an effective and inexpensive adsorbent for chromium(VI) removal from aqueous solutions. The adsorption breakthrough curves were obtained at different flow rates, feed Cr(VI) concentration, particle size, pH of feed solution and bed depth. The results indicate that an increase in flow rate decreases the volume treated until the saturation time and therefore decreases the capacity of the bed, probably due to the fact that contact times were insufficient for the adsorption equilibrium to be developed between the waste tea and the Cr(VI) ions. The highest bed capacity was observed at pH 2.0. Maxi-

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mum bed capacity of Cr(VI) decreased with the increase in the initial feed Cr(VI) concentration. As the particle size increased, the breakthrough curves tended towards the classic “S” shaped profile, and the saturation time and bed capacity decreased. The bed capacity of Cr(VI) adsorption on waste tea and saturation time was increased in the bed depth from 5 to 30 cm. Thomas model for the waste of tea factory on Cr(VI) adsorption was used to predict the breakthrough curves under varying experimental conditions. As seen in Table 3 and Figs. 5–9, this model gave good agreement between experimental and calculated breakthrough curves. This model was also successfully used for the prediction. Acknowledgment This research was supported by the Research Project Unit at the Atatürk University under the Project no. 2002/147. References Acar, F.N., Malkoc, E., 2004. The removal of chromium(VI) from aqueous solutions by Fagus orientalis L. Bioresource Technology 94 (1), 13–15. Aksu, Z., Gönen, F., 2004. Biosorption of phenol by immobilized activated sludge in a continuous packed bed: prediction of breakthrough curves. Process Biochemistry 39, 599–613. Aksu, Z., Acıkel, U., Kabasakal, E., Tezer, S., 2002. Equilibrium modeling of individual and simultaneous biosorption of chromium(VI) and nickel(II) onto dried activated sludge. Water Research 36 (12), 3063–3073. Çay, S., Uyanık, A., Öza¸sık, A., 2004. Single and binary component adsorption of copper(II) and cadmium(II) from aqueous solutions using tea-industry waste. Separation and Purification Technology 38, 273–280. Chu, K.H., 2004. Improved fixed-bed models for metal biosorption. Chemical Engineering Journal 97, 233–239. De Castro Dantas, T.N., Dantas Neto, A.A., De A. Moura, M.C.P., 2001. Removal of chromium from aqueous solutions by diatomite treated with microemulsion. Water Research 35 (9), 2219–2224. Fu, Y., Viraraghavan, T., 2003. Column studies for biosorption of dyes from aqueous solutions on immobilised Aspergillus niger fungal biomass. Water SA 29 (4), 465–472. Garg, V.K., Gupta, R., Kumar, R., Gupta, R.K., 2004. Adsorption of chromium from aqueous solution on treated sawdust. Bioresource Technology 92, 79–81. Inglezakis, V.J., Grigoropoulou, H., 2004. Effects of operating conditions on the removal of heavy metals by zeolite in fixed bed reactors. Journal of Hazardous Materials B 112, 37–43. Malkoç, E., 2005. Removal of heavy metals from waters by different adsorbent types. Ph.D. Thesis, Department of Environmental Engineering, Graduate School of Natural and Applied Sciences, Ataturk University, Erzurum, Turkey. Malkoc, E., Nuhoglu, Y., 2003. The removal of chromium(VI) from synthetic wastewater by Ulothrix zonata. Fresenius Environmental Bulletin 12 (4), 376–381. Nuhoglu, Y., Oguz, E., 2003. Removal of copper(II) from aqueous solutions by adsorption on the cone biomass of Thuja orientalis. Process Biochemistry 38, 1627–1631. Park, D., Yun, Y.-S., Park, J.M., 2004. Reduction of hexavalent chromium with the brown seaweed Ecklonia biomass. Environmental Science and Technology 38, 4860–4864. Park, D., Yun, Y.-S., Park, J.M., 2005. Studies on hexavalent chromium biosorption by chemically treated biomass of Ecklonia sp. Chemosphere 60, 1356–1364. Rao, M., Parwate, A.V., Bhole, A.G., 2002. Removal of Cr 6+ and Ni2+ from aqueous solution using bagasse and fly ash. Waste Management 22, 821–830.

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