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Competitive sorption of Cu(II) and Ni(II) ions from aqueous solutions: Kinetics, thermodynamics and desorption studies
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JTICE-861; No. of Pages 11 Journal of the Taiwan Institute of Chemical Engineers xxx (2014) xxx–xxx
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Competitive sorption of Cu(II) and Ni(II) ions from aqueous solutions: Kinetics, thermodynamics and desorption studies Meghna Kapur, Monoj Kumar Mondal * Department of Chemical Engineering and Technology, Indian Institute of Technology (Banaras Hindu University), Varanasi 221005, Uttar Pradesh, India
A R T I C L E I N F O
A B S T R A C T
Article history: Received 25 October 2013 Received in revised form 28 January 2014 Accepted 25 February 2014 Available online xxx
Extensive study has been done in the context of single metal adsorption from aqueous solutions but the present study approaches the simultaneous sorption of metal ions. Aim of the present work is to characterize the coal dust for its ability to remove Cu(II) and Ni(II) from aqueous solutions. Variation of the working parameters viz., pH, contact time, adsorbent dose, metal ion concentrations, temperature were done in a range to optimize ideal conditions for the adsorption of ions from a binary metal solution containing Cu(II) and Ni(II) in a batch mode. Adsorption was found to be exothermic and the parameter estimation viz. DG8, DH8, DS8 showed it to be thermodynamically favorable. Second order kinetics was fitted well for bi-component adsorption and Langmuir isotherm strongly supported the mechanism. Coexistence of the ions affected the adsorption capacity and showed antagonistic manner in comparison to the single metal. Desorption experiments showed that the coal dust can be used effectively upto three cycles and proper disposal has also been mentioned. ß 2014 Taiwan Institute of Chemical Engineers. Published by Elsevier B.V. All rights reserved.
Keywords: Adsorption Cu(II) and Ni(II) Coal dust Isotherms Regeneration
1. Introduction Water is getting contaminated in various ways. Industries and agriculture makes the way of chemicals to enter into the water streams. Numbers of organic, inorganic, phenolic and metallic species enters the water bodies and becomes lethal after crossing a certain limit in the metabolic system. Researchers have shown interest in treating such effluents by applying techniques such as coagulation [1], chemical precipitation [2], ion exchange [3], membrane separation [4], electrochemical treatment [5] and adsorption [6]. By considering cost, time needed for purification, chemical inputs, flexibility and design simplicity, the outcomes of adsorption are better than any other techniques. Few commercial adsorbents zeolites [7], activated alumina [8], silica gel [9] and activated carbon [10] were used for water treatment as they possess high surface area but owing to high initial investments, researchers shifted toward more environment friendly low cost adsorbents. Lignin and cellulose bearing plant materials viz. saw dust [11], fruit peels [12,13], rice husk [14] has been given preference for heavy metal removal from solutions. Certain agricultural wastes
* Corresponding author. Tel.: +91 9452196638; fax: +91 5422367098. E-mail address: [email protected] (M.K. Mondal).
viz. grape stalks [15], sunflower stalks [16], tamarind seeds [17] have also been investigated as adsorbents. Fly ash (an industrial waste) generated from coal combustion residue is found to be silica and alumina rich and thus has potential for metal adsorption [18]. Steel plants generate a large volume of granular blast furnace slag [19], sludge [20] and dust [21] which were evaluated as adsorbents. Mostly single metal adsorption from aqueous solutions have drawn the attention of investigators, but it is necessary to draw the attention toward the simultaneous removal of more than one heavy metal, as in general various species are present in the effluents. In the case of multicomponent adsorption of metals, the factors which affect the removal efficiency are nature of adsorbent (metal binding site, presence of different functional groups), metallic properties (concentration, ionic size, standard redox potential, electronegativity) and the pH of the solution. The approach of the present work is for simultaneous removal of Cu(II) and Ni(II), which are present in the water discharged from the electroplating machinery, alloy making and microelectronics industries. As prescribed by Bureau of Indian Standards the safe limit for discharge of Cu(II) through industries is 1.5 mg/L and for drinking water it is set to be 0.05 mg/L while in case of Ni(II) the acceptable limit is 0.02 mg/L. Heavy metal concentrations in waste waters vary from 0.5 to a high value of 1000 mg/L. Waste streams from electroplating industries contains Cu(II) upto 500 mg/L [22] and
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Please cite this article in press as: Kapur M, Mondal MK. Competitive sorption of Cu(II) and Ni(II) ions from aqueous solutions: Kinetics, thermodynamics and desorption studies. J Taiwan Inst Chem Eng (2014), http://dx.doi.org/10.1016/j.jtice.2014.02.022
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JTICE-861; No. of Pages 11 2
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the rinse water of plating industries may have Ni(II) in the range of 2–900 mg/L [23]. This paper brings in picture (i) the feasibility of coal dust for simultaneous removal of Cu(II) and Ni(II) from aqueous solutions (ii) effect of working parameters (pH, time of contact, agitation speed, temperature, initial metal concentration) (iii) kinetics behind the process (iv) suitability of adsorption isotherm models for metals in individual and multicomponent aqueous solutions (v) regeneration and reuse of the adsorbent.
2. Experimental 2.1. Adsorbent The adsorbent used for simultaneous removal of metallic species from aqueous solutions is coal dust. It has been collected from Northern Coal fields Limited (NCL) Singrauli (M.P.), India. Naturally obtained coal dust was sieved and dried at 105 8C to make it moisture free. It was kept in a vacuum dessicator for future use. 2.2. Reagents All the chemicals used were of analytical grades. Stock solution (1000 mg/L) of Cu(II) was prepared by dissolving 3.802 g of cupric nitrate [Cu(NO3)23H2O] in 1000 mL of double distilled water and for Ni(II) 6.73 g of ammonium nickel(II) sulphate [(NH4)2SO4NiSO46H2O] was dissolved in 1000 mL of double distilled water. Working solutions were prepared by diluting the stock solutions in the desired ratio. The 0.1 M NaOH and 0.1 M HCl were used for pH adjustments of the test solutions. 2.3. Instrumentation Solution pH was tested by a digital pH meter (LI 120, Elico India), calibrated using buffer solutions (pH 4.0, 7.0 and 9.2). Adsorbent was made moisture free by drying in an oven (S.M. Scientific Instruments Pvt. Ltd., New Delhi). Mean particle diameter was determined using CIS-50 ANKERSMID particle size analyzer. In the batch system the required temperature and constant agitation speed was set by a temperature controlled water bath shaker (NSW-133). Spectral analysis of the adsorbent before and after adsorbing metal ions was done using NICHOLET 5700 spectrophotometer (Thermo electron). Sample was mixed with a dry alkali halide (KBr), which is transparent in the midinfrared region (4000–400 cm1) and made into a 1 cm disc. Spectrum was obtained by passing infrared radiation through the sample and determining the fraction absorbed at a particular energy. This analysis relates the surface of the adsorbent to the modes of the vibrations of functional groups present on it, responsible for the adsorption. To test the mineral identification and crystallinity of the adsorbent X-ray diffraction studies were done. Pattern was recorded by a Philips 1710 X-ray diffractometer with a Cu Ka target of radiation wavelength 1.542 A˚ operating at 40 kV and 40 mA. Peaks obtained signify whether the sample is crystalline with sharp peaks or it is amorphous in nature showing broad peaks. Crystallite size can be determined further in case of crystalline material. The Brunauer–Emmett–Teller (BET) surface area of the coal dust was investigated by N2 adsorption– desorption method using Micromeritics ASAP 2020, V302G single port. Liquid nitrogen was used as the cold bath (77 K). The porous structures were studied through BJH (Barret–Joyner–Halenda) data. Concentration of copper and nickel in the test solutions were calculated by developing colored complexes for each metal and
tested at suitable wavelengths using UV–Vis spectrophotometer (ELICO SL 159 UV–Vis Spectrum). 2.4. Batch adsorption studies For studying the adsorption characteristics of coal dust for the removal of binary species from aqueous solutions batch adsorption studies were performed by variation of parameters. Experiments were performed at room temperature (28 2 8C) by diluting the stock solutions of Cu(II) and Ni(II). Dilution was done to obtain solutions in the range of 5–500 mg/L. Batches of metal solution and adsorbent were run for the contact time (0–90 min). Various parameters viz. pH (2–7), adsorbent dose (2–12 g/L), speed of agitation (0–200 rpm), initial metal concentrations (5–100 mg/L) and temperature (20–40 8C) were studied in the given respective ranges, to obtain the optimum conditions for adsorption to occur. Adsorbent and the adsorbate solution was contacted in a batch wise manner and after adsorption the coal dust was filtered and thus separated from the solution. Analysis of metal concentrations in the test solution before and after adsorption was done by spectrophotometric method. Dimethylglyoxime method was followed for Ni(II) at 445 nm and sodium dimethyl dithiocarbamate method for Cu(II) at 457 nm [24]. Removal efficiency of the adsorbate or metal ions at each interval of time is given by % Removal of CuðIIÞ or NiðIIÞ ions ¼
Co C f 100 Co
(1)
Adsorption capacity (mg/g) is calculated using following equation: q¼
ðC o C e ÞV W
(2)
where q is the adsorption capacity of the adsorbent in (mg/g). Initial, final and equilibrium concentrations of the metal ions are denoted by Co, Cf and Ce, respectively. W is the mass of the adsorbent (g) taken in V volume of solution (L). 2.5. Batch desorption studies Studies for regenerating metal loaded adsorbent are necessary so that the adsorbent can be freed from the metals and can be reused or disposed off without imposing any burden on the environment. For desorbing metals the selection of a suitable eluent is essential. Desorption can be done using distilled water, mineral acids (HCl, HNO3, H2SO4) or EDTA solution and the ions released into eluent can be analyzed. Present work deals on regenerating coal dust using dilute solutions of HCl, HNO3, H2SO4 and distilled water. Desorption efficiency at each cycle has been calculated using the following equation: Desorption efficiency ¼
Concentration of metal desorbed Concentration of metal loaded 100
(3)
3. Adsorption kinetics Kinetics explains the progress of adsorption with time. It is a means for understanding the dynamics of adsorption process. Parameters obtained through kinetic studies can be used for designing up the operation. Reactions are in general described by the order and the rate of the reaction at which it is occurring. Kinetics is explained using pseudo-first order kinetics, pseudosecond order rate kinetics, Elovich model and intraparticle diffusion model.
Please cite this article in press as: Kapur M, Mondal MK. Competitive sorption of Cu(II) and Ni(II) ions from aqueous solutions: Kinetics, thermodynamics and desorption studies. J Taiwan Inst Chem Eng (2014), http://dx.doi.org/10.1016/j.jtice.2014.02.022
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of Cu(II) and Ni(II) ions were obtained by using the following equations:
3.1. Pseudo-first order kinetics The general expression of the pseudo-first order kinetics model as proposed by Lagergren [25] is
Kc ¼
dqt ¼ k1 ðqe qt Þ dt
DG0 ¼ RT ln Kc
(4)
By applying boundary conditions qt = 0 at t = 0 and qt = qt at t = t, it can be linearized to get ðk1 Þt logðqe qt Þ ¼ log qe 2:303
C Ae Ce
ln K c ¼
(11)
DS0
!
R
(12)
DH 0
!
RT
(13)
(5)
where qe and qt are the amounts of metal adsorbed (mg/g) at equilibrium time and at any time t, respectively; k1 (min1) is the first order rate constant. 3.2. Pseudo-second order kinetics Kinetics in the form of pseudo-second order [26] is described by the following equation: dqt ¼ k2 ðqe qt Þ2 dt
3
(6)
where Kc is the equilibrium constant at temperature T, R is the universal gas constant (8.314 103 kJ/mol K) and CAe and Ce are the equilibrium concentrations of adsorbate on the adsorbent and in the solution, respectively. Activation energy deciphers the nature of the process and can be determined through Arrhenius equation: k ¼ AeEa =RT
(14)
which linearizes into ln k ¼ ln A
Ea RT
(15)
Simplified form of the equation obtained after integration under boundary conditions qt = 0 at t = 0 and qt = qt at t = t is as follows:
Ea is the activation energy (kJ/mol), A is the frequency factor (min1) and T temperature in Kelvin.
t 1 t ¼ þ qt k2 q2e qe
4. Adsorption isotherms
(7)
where k2 (g/mg min) is the second order rate constant. 3.3. Elovich kinetics Elovich equation is applied for chemisorption kinetics. It is often evaluated for heterogeneous surfaces [27] and devised as dqt ¼ a expðbqt Þ dt
(8)
alongwith the boundary conditions it was assumed that ab t, which yields qt ¼
1
b
lnðabÞ þ
1
b
lnðtÞ
(9)
qt ¼ A þ Bln t where a and b are the Elovich constants. a (mg/g min) represents the rate of chemisorption at zero coverage and b (g/mg) is related to the extent of surface coverage and activation energy for chemisorptions.
4.1. Langmuir model Langmuir isotherm works on following assumptions [29]: Applicable for monomolecular layer adsorption. Sites are homogeneous with equal affinity toward adsorbate. Adsorption at one site does not affect the adjacent site. To determine the maximum adsorption capacity for single metal solution, following equation is employed: (Non-linear form) qe ¼
3.4. Intraparticle diffusion This model regarding intraparticle diffusion proposed by Weber and Morris [28] is as follows: qt ¼ K id t 1=2
Isotherms are the means of analyzing the adsorbate concentration in the solution and the amount adsorbed by a specific mass of adsorbent. Isotherms determine the adsorption capacity of the adsorbent. They mainly depend upon the nature and type of the system. Experiments were carried out to evaluate the best fit adsorption isotherm for describing the process at a fixed temperature by varying initial concentrations of metal ions.
(10)
where Kid (mg/g min1/2) is the intraparticle diffusion rate constant. If a plot of qt against square root of contact time results a straight line passing through origin, the model is followed otherwise film diffusion plays an important role instead of intraparticle diffusion during the adsorption process. 3.5. Thermodynamic studies and activation energy Thermodynamic parameters such as change in standard free energy (DG8), enthalpy (DH8) and entropy (DS8) for the adsorption
qo bC e 1 þ bC e
(16)
(Linear form) Ce 1 Ce þ ¼ qe qo b qo
(17)
where Ce is the equilibrium concentration (mg/L), qe is the amount adsorbed per unit mass of adsorbent at equilibrium (mg/g). The qo and b are the Langmuir constants related to the adsorption capacity and energy of adsorption, respectively. 4.2. Freundlich model This model is applied for heterogeneous surfaces ln qe ¼ ln K f þ
1 ln C e n
(18)
Please cite this article in press as: Kapur M, Mondal MK. Competitive sorption of Cu(II) and Ni(II) ions from aqueous solutions: Kinetics, thermodynamics and desorption studies. J Taiwan Inst Chem Eng (2014), http://dx.doi.org/10.1016/j.jtice.2014.02.022
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Freundlich constants Kf and n related to adsorption capacity and intensity, respectively. 4.3. Redlich–Peterson model Redlich–Peterson (R–P) isotherm model is applicable in both homogeneous as well as heterogeneous systems as it is an improvement over Langmuir and Freundlich models. It is expressed as qe ¼
K RCe
(19)
b
1 þ aR Ce
where KR is R–P isotherm constant (L/g), aR is R–P isotherm constant (mg1) and b is the exponent (0 < b< 1), Ce is the equilibrium concentration (mg/L). In the linearized form, it is represented as Ce 1 ¼ ln aR þ b ln C e (20) ln K R qe
Table 2 Spectral analysis of coal dust before and after adsorption of Cu(II) and Ni(II) ions. Band positions (cm1)
Assignment
Before adsorption
After adsorption
Differences
3693.81 3387.11 2924.18 692.47
3691.88 3412.19 2922.25 690.54
+1.93 25.08 +1.93 +1.93
–OH group –OH stretching vibrations Asymmetrical –CH stretching CH bending vibrations
Table 3 Peak positions and d-spacing values of the minerals on the XRD diffractogram identified in coal dust. Peak positions in degrees (2u) angle
d-Spacing (A˚)
Possible mineral
12.41 19.90 20.89 24.92 26.69 29.63
7.12 4.46 4.25 3.57 3.33 3.01
Kaolinite Illite Quartz Kaolinite Quartz Calcite
5. Error analysis Due to linearization of the non-linear isotherm models some errors get inherited due to which the fit between experimental data and the model predicted values as explained by correlation coefficient does not put such a meaning thus error analysis conformity is required. 5.1. Chi-square test The Chi-square test can be examined by using following equation: 2
x ¼
2 X qe;exp qe;model
(21)
qe;model
5.2. Root mean square error (RMSE) The analysis for RMSE can be accomplished as X qe;exp qe;model RMSE ¼ qe;model
!2 (22)
6. Results and discussion 6.1. Adsorbent characterization Certain physical characteristics which define the adsorbent are listed in Table 1. The functional groups detected on the adsorbent surface with the help of spectral bands using FTIR spectroscopy before and after adsorption of Cu(II) and Ni(II) ions are pictured in Fig. 1(a) and (b), respectively. Spectrum shows the strong absorption Table 1 Characteristics of the coaldust. Parameters
Values
Moisture (%) Ash (%) Volatile matter (%) Fixed carbon (%) pHZPC Bulk density (g/cm3) Particle size (mm)
1.259 2.25 2.3 94.19 2.9 0.7457 30.99
of free hydroxyl groups of alcohols and phenols at wavenumbers 3693.81 and 3620.51 cm1. The OH stretching vibrations are seen at 3387.11 cm1. Peak at 2924.18 cm1is for asymmetrical C–H stretching of methylene group while symmetrical bending vibrations of –CH methyl groups are present at 1379.15 cm1. The band positions at 1112.96 and 1031.95 cm1 show C–O stretching vibrations. Strong –CH bending vibrations (out of plane) are seen at the peaks 914.29, 794.70 and 692.47 cm1. Skeletal vibrations of C–C stretching within the ring are seen at 1589.40 cm1 and weak bands of S–S stretching vibrations are present at 468.72 cm1. Additionally most of the peaks in spectra of coal between 1100 and 400 cm1 can be assigned to clay minerals such as quartz, kaolinite, illite and the montmorillonite group. Peaks at 468.72, 538.16, 692.47, 794.70, 914.29 and 1031.95 cm1 attributes these minerals. The Si–O–Si stretching vibration shows absorption at 1031 cm1. Studies of the adsorbent after adsorbing heavy metals from the aqueous solutions indicate the participation of free hydroxyl (–OH) groups, –CH stretching and –OH stretching vibrations (Table 2). The peaks of X-ray diffraction represent slight crystalline nature of the coal dust. XRD analysis shows the presence of quartz (SiO2), kaolinite [Al2Si2O5(OH4)], illite [KAl2(OH)2AlSi3(O,OH)10] and calcite (CaCO3) minerals. The corresponding peak positions and d-spacing values are listed in Table 3. Pattern obtained for adsorbent before and after adsorbing the metal ions is shown in Fig. 2(a) and (b), respectively. After adsorbing the metal ions, the intensity of the peaks were seen to be slightly diminished which attributes to the adsorption of metal ions on the upper layer of the coal dust by means of physisorption. N2 gas adsorption–desorption isotherms for the coal dust as obtained through BET is presented in Fig. 3. It shows that the isotherm belongs to type-IV adsorption–desorption isotherm with H3 type of hysteresis loop indicating the presence of mesoporosity with affinity for adsorption. This is in accordance with BDDT (Brunauer, Deming, Deming and Teller) classification [30]. The path dependent adsorption–desorption behavior leading to hysteresis is an indicator of the porous nature of the sample. Coal dust has a wide pore size distribution and thus a wide distribution of surface area can be seen. The BET surface area is 12.66 m2/g, whereas BJH adsorption/desorption surface area of pores is 6.879/6.6283 m2/g. The single point total pore volume of pores (d < 9.474 A˚) is found to be 0.004238 cm3/g, whereas cumulative adsorption/desorption pore volume of the pores (17 A˚ < d< 3000 A˚) is 0.032150/0.030116 cm3/g, respectively.
Please cite this article in press as: Kapur M, Mondal MK. Competitive sorption of Cu(II) and Ni(II) ions from aqueous solutions: Kinetics, thermodynamics and desorption studies. J Taiwan Inst Chem Eng (2014), http://dx.doi.org/10.1016/j.jtice.2014.02.022
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5
(a) 20 %T 17.5
15
1379.15
1589.40
538.16 1031.95
2.5
468.72
914.29
1112.96
5
3387.11
3693.81
7.5
692.47
794.70
2357.09 2924.18
10
3620.51
% Transmittance
12.5
0 4000 MK1
375 0
4000 MK 2
3750
350 0
3250
300 0
2750
2500
2250
2000
1750
150 0
125 0
1000
750
Wave numbers (cm-1)
500 1/c m
(b) 16 %T
12
690.54
0 3500
3250
3000
2750
2500
2250
2000
1750
1500
1250
1000
750
468.72
538.16
914.29
1379.15
1031.95
2
1112.96
3691.88
4
3412.19
6
1589.40
2922.25
8
794.70
2357.09
10
3620.51
% Transmittance
14
500 1/c m
Wave numbers (cm-1) Fig. 1. FTIR plot of coal dust (a) before adsorption and (b) after adsorption of Cu(II) and Ni(II).
The average pore diameter by BET method was found to be 13.3876 A˚, whereas the BJH adsorption/desorption average pore diameter is 186.939/181.740 A˚. Analysis of BJH adsorption pore distribution shows that micropores have a area of almost 7%, 82% area is occupied by mesopores and macropores are 12% while that of desorption shows that mesopores account for 95% area. Coal dust is found to consist mainly of mesopores. This is the factor most desirable for the liquid phase adsorptive removal of metal ions [31]. 6.2. Effect of pH By solid addition method [31] the point of zero charge (pHZPC) of the coal dust was found to be 2.9 and it gave a clear picture of adsorption of ionic species above this pHZPC. For determining the
optimum pH for removal of Cu(II) and Ni(II) ions from the aqueous solutions, initial pH of the system was set in the range of 2 to 7. Solution containing 10 mg/L of each metal with an adsorbent dose of 10 g/L was shaken for 60 min. Fig. 4 shows that with the increase in pH from 2 to 4, the adsorption percentage of Cu(II) increased from 60 to 97.32% and thereafter it falls to 83.7% at pH 7. Similar pattern was observed for Ni(II) ions with a maximum adsorption of 100% at a pH 4. Thus pH 4 was selected as optimum for further studies of binary adsorption from aqueous solutions. At a low pH the surface of the adsorbent gets protonated and thus H+ ions causes hindrance for the metal ions to adsorb at the surface of coal dust but at a slightly higher pH i.e. above pHZPC value of 2.9 the surface acquires negative charge sufficient to bind cationic species. Thus electrostatic attraction works behind the removal. Similar findings have been reported in the past [32]. Binding occurs
Please cite this article in press as: Kapur M, Mondal MK. Competitive sorption of Cu(II) and Ni(II) ions from aqueous solutions: Kinetics, thermodynamics and desorption studies. J Taiwan Inst Chem Eng (2014), http://dx.doi.org/10.1016/j.jtice.2014.02.022
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6
(a)
Cu (II) Ni (II)
3500
100
3000
2500
2000
% Removal
Intensity (cps)
80
1500
1000
60
40
500
20 0 0
10
20
30
40
50
60
70
80
90
0
2-theta (deg)
(b)
1
2
3
4
5
6
7
Initial pH
3000
Fig. 4. Effect of initial pH on Cu(II) and Ni(II) removal by coaldust (temperature: 30 8C; pH: 4; adsorbent dose: 10 g/L; metal concentration: 10 mg/L; time: 60 min; particle size: 30.99 mm).
2500
Intensity (cps)
2000
While increasing pH, a point is achieved where the metal solubility decreases and results in precipitation as metal hydroxides [33]. For a 10 mg/L of solution of Cu(II) and Ni(II) the pH for precipitation is found to be 6 and 8.5, respectively [34]. So the chosen pH 4, which is much below than the pH of metal precipitation is optimum for future experiments.
1500
1000
500
6.3. Effect of contact time 0 0
10
20
30
40
50
60
70
80
90
2-theta (deg) Fig. 2. XRD plot of coal dust (a) before adsorption and (b) after adsorption of Cu(II) and Ni(II).
between the metal and free hydroxyl (–OH) groups, –CH stretching and –OH stretching vibrations, moreover the coal dust is predominantly mesoporous as explained earlier, most of the cations get adsorbed into the mesopores.
Solution containing 10 mg/L of Cu(II) and Ni(II) at a pH 4 was kept at a constant shaking for 90 min with adsorbent dose of 10 g/ L. It can be well inferred from Fig. 5 that for Cu(II) a significant change is noticed from 10 to 60 min but after 60 min there was even less than 1% change and for Ni(II) change was insignificant just after 30 min of contact time. So the duration at which equilibrium was found to be established between the adsorbate concentration in solution and on the adsorbent was 60 min for the bisolute system. Reason behind this may be that in the initial stages of adsorption all the adsorptive sites are vacant, as the time proceeds the rate of occupancy of sites gets rapid and after a certain
100 90 80
Cu (II) Ni (II)
% Removal
70 60 50 40 30 20 10 0 0
10
20
30
40
50
60
70
80
90
Contact time (min)
Fig. 3. N2 gas adsorption–desorption isotherm for coal dust.
Fig. 5. Effect of contact time on Cu(II) and Ni(II) removal by coaldust (temperature: 30 8C; pH: 4; adsorbent dose: 10 g/L; metal concentration: 10 mg/L; particle size: 30.99 mm).
Please cite this article in press as: Kapur M, Mondal MK. Competitive sorption of Cu(II) and Ni(II) ions from aqueous solutions: Kinetics, thermodynamics and desorption studies. J Taiwan Inst Chem Eng (2014), http://dx.doi.org/10.1016/j.jtice.2014.02.022
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90
90
80
80
70
70
60
% Removal
% Removal
100
Cu (II) Ni (II)
100
60 50
7
Cu (II) Ni (II)
50 40 30
40
20
30
10
20
0
10
0
2
4
6
8
10
12
Adsorbent dose (g/L)
0 0
10
20
30
40
50
60
70
80
90
100
Initial metal concentrations (mg/L)
Fig. 7. Effect of adsorbent dose on Cu(II) and Ni(II) removal by coaldust (temperature: 30 8C; pH: 4; metal concentration:10 mg/L; time: 60 min; particle size: 30.99 mm).
Fig. 6. Effect of initial metal concentration on Cu(II) and Ni(II) removal by coaldust (temperature: 30 8C; pH: 4; adsorbent dose: 10 g/L; time: 60 min; particle size: 30.99 mm).
Cu (II) Ni (II)
100
duration a repulsive force comes into play between the ionic species in the solution and the sites already occupied by the same species.
80
With an adsorbent dose of 10 g/L and contact time of 60 min, the initial concentrations of the solution containing Cu(II) and Ni(II) at a pH 4 were set in the range of 5–100 mg/L. Coal dust have shown great adsorptive capacity for both the metals upto 20 mg/L as can be seen in Fig. 6 but percentage removal decreased to 80 and 77.95 for Cu(II) and Ni(II), respectively, on increasing the concentration to 100 mg/L. It is clear that low metal concentrations utilize higher energy sites but as the metal concentration increases the higher energy sites get saturated and adsorption shifts to the lower energy sites therefore resulting a drop in the efficiency. 6.5. Effect of adsorbent dose Experiment was performed to fix the optimum adsorbent dose required to adsorb the Cu(II) and Ni(II) ions from the aqueous solutions at a pH 4 and contact time 60 min for 10 mg/L solution of each metal ion in the binary solution. Variation of amount of adsorbent was done from 2 to 12 g/L. As it can be observed from Fig. 7 the percentage removal for Cu(II) varied within the range of 94–97% but for Ni(II) the change was prominent, it increased from 77.98% to 100% for dose range 2 to 10 g/L and finally became stagnant for 10 and 12 g/L. Thus 10 g/L was selected as the adsorbent dose for the binary metal solution. This could be attributed to the fact that on increasing the adsorbent amount for same concentration of metal solution, the number of sites available for adsorption goes on increasing but a stage comes after which removal attains its maximum limit and further increase had no effect. 6.6. Effect of agitation speed For no agitation condition the adsorption percentage was found to be 2.06 and 1.98 for Cu(II) and Ni(II) ions, respectively. With a higher agitation speed of 25 rpm the removal slightly increased to 20.1% and 19.34% which finally reached 97% and 100% for Cu(II)
% Removal
6.4. Effect of initial metal concentrations
60
40
20
0 0
20
40
60
80
100
120
Agitation speed (rpm) Fig. 8. Effect of agitation speed on Cu(II) and Ni(II) removal by coaldust (temperature: 30 8C; pH: 4; adsorbent dose: 10 g/L; metal concentration: 10 mg/ L; time: 60 min; particle size: 30.99 mm).
and Ni(II) ions, respectively, at 120 rpm. It may be concluded that increased agitation provided better adsorbate–adsorbent contacting. Fig. 8 shows the clear demarcation of removal efficiency for the effect of agitation in the range of 0 to120 rpm for 10 mg/L solution at a pH 4 and contact time 60 min. 6.7. Effect of temperature Experiments were performed to visualize the temperature effect on the adsorption mechanism. To find out the endothermic or exothermic nature of the process by the adsorption from bicomponent system, temperature variation was done between 20 and 40 8C for 100 mg/L of solution at pH 4. Adsorption efficiency for each temperature calculated from a series of contact time has been summarized in Fig. 9. Studies showed that increasing temperature does not support the adsorption as the removal percentage for both the metals was found to decrease, suggesting exothermic reaction behind the mechanism. Increased mobility of the ions may be one
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Table 4 Kinetic parameters for adsorption of Cu(II) and Ni(II) using coal dust. Copper(II)
Species Temperature (8C) Pseudo-first order kinetics
qe (mg/g) k1 (min1) R2 qe (mg/g) k2 (g/mg min) R2 A B R2 Kid (mg/g min1/2) R2
Pseudo-second order kinetics
Elovich model
Intraparticle diffusion
Nickel(II)
20
30
40
20
30
40
1.29 0.032 0.972 8.064 0.08 0.999 6.065 0.453 0.913 0.182 0.969
2.944 0.055 0.894 8.264 0.037 0.997 4.804 0.76 0.935 0.303 0.976
2.2646 0.046 0.868 7.7519 0.0485 0.997 4.831 0.656 0.94 0.261 0.977
0.9015 0.0276 0.854 7.8125 0.1204 0.999 6.46 0.302 0.823 0.123 0.905
2.69 0.046 0.808 8.0 0.03765 0.994 4.72 0.708 0.847 0.288 0.926
2.009 0.0368 0.936 7.09 0.0463 0.997 4.18 0.647 0.898 0.261 0.961
of the reasons for causing desorption on increasing temperature and thus decreasing affinity of adsorbate–adsorbent system. 6.8. Adsorption kinetics
(a)
For the pseudo-first order model the parameters qe (mg/g) and k1 were evaluated at temperatures 20–40 8C through a plot of log(qe qt) vs. t. The model was tested for both the metals of the binary solute system and the values of the parameters calculated using Eq. (5) are listed in Table 4. In the case of Cu(II) R2 values ranged between 0.868 and 0.972 similarly for Ni(II) it was between 0.808 and 0.936. In comparison to this the second order kinetics explained by Eq. (7) was fitted through graphical analysis of t/qt vs. t represented in Fig. 10 for Cu(II) and Ni(II), respectively, and was found to be supporting the dynamics of the sorption as its correlation coefficient values approached unity for both Cu(II) and Ni(II). Elovich model stated as Eq. (9) describes the kinetics of ion exchange system. It was applied over the entire set of temperatures for 100 mg/L solution containing both the metals in the same ratio. The results were depicted by graphs between qt and ln t. Elovich constants are listed in Table 4 alongwith the R2 (0.913– 0.94 for Cu(II) and 0.823–0.847 for Ni(II)) which shows the kinetics
o
Temperature ( C) For Cu (II) 20 30 40
7
6
t/qt(min.g)/mg
5
4
3
2
1
0 0
10
20
30
40
50
t (min) o
Temperature ( C) For Cu (II) 20 30 40 For Ni (II) 20 30 40
100
80
8
o
Temperature ( C) For Ni (II) 20 30 40
7 6
t/qt (min.g)/mg
% Removal
90
(b)
70
60
5 4 3 2 1
50 0
10
20
30
40
50
60
Contact time (min)
0 0
10
20
30
40
50
t (min) Fig. 9. Effect of temperature on Cu(II) and Ni(II) removal by coaldust (pH: 4; adsorbent dose: 10 g/L; metal concentration: 100 mg/L; time: 60 min; particle size: 30.99 mm).
Fig. 10. Pseudo-second order kinetics for (a) Cu(II) and (b) Ni(II) adsorption on coal dust.
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Table 5 Thermodynamic parameters for adsorption of Cu(II) and Ni(II) using coal dust.
DG8 (kJ/mol)
Cu(II) Ni(II)
20 8C
30 8C
40 8C
10.12 3.46
10.07 3.49
8.38 4.43
DH8 (kJ/mol)
DS8 (kJ/mol K)
35.30 9.619
0.0849 0.0207
Table 6 Isotherm constants for monocomponent adsorption on coal dust. Adsorbate
Copper(II) Nickel(II)
Freundlich constants
Redlich–Peterson constants
b (mg1)
Langmuir constants qo (mg/g)
Kf
n
KR (L/g)
aR (mg1)
B
0.066 0.0686
21.739 20.408
6.19 6.055
4.52 4.62
2 2
0.124 0.1547
0.951 0.915
Table 7 Comparison of the experimental and calculated qe values evaluated from the mono-component isotherm models. Co (mg/L)
Copper(II) 100 200 300 400 500 R R2
Ce (mg/L)
qe,exp (mg/g) Langmuir
Freundlich
R–P
10 33.32 116.56 209.96 290
9 16.68 18.34 19 21
8.64 14.94 19.23 20.27 20.65 0.99756 0.995 0.3415 0.019426
10.29 13.43 17.71 20.17 21.67 0.9193 0.845 1.0553 0.064505
9.48 14.87 18.72 19.96 20.54 0.99745 0.994 0.3052 0.017934
12.02 34.82 120.9 220 300
8.79 16.51 17.91 18 20
9.22 14.38 18.21 19.13 19.46 0.99724 0.994 0.42319 0.02401
10.36 13.03 17.05 19.41 20.75 0.8857 0.784 1.338 0.085809
9.5959 13.974 17.98 19.53 20.28 0.9940 0.988 0.653 0.039381
x2 RMSE Nickel(II) 100 200 300 400 500 R R2
qe,calc (mg/g)
x2 RMSE
does not follow ion exchange mechanism. To decide the rate controlling mechanism for adsorption by coal dust, intraparticle diffusion model was tested using Eq. (10) and it was evident that the plot of qt vs. t1/2 for both the metals did not pass through origin indicating there is some degree of film diffusion control and not only intraparticle diffusion is controlling. Thus it can be concluded that second order kinetics alongwith combined film and intraparticle diffusion is strongly followed by both the metal ions in a bi-solute system.
6.10. Monocomponent adsorption Adsorption data at equilibrium were analyzed in the range of 100–500 mg/L of solution for each component. The adsorbent dosage was fixed at 10 g/L for a pH 4. The parameters obtained through Langmuir, Freundlich and Redlich–Peterson isotherms for
6.9. Thermodynamic and determination of activation energy All the values of the thermodynamic parameters are listed in Table 5. Negative values of DG8 reveal that the mechanism of metal adsorption from the aqueous solutions is feasible and shows spontaneity for both the metals, thus supports the physical nature of adsorption. Exothermicity is indicated by the negative values of DH8 in both the cases while low degree of freedom of the system is reported by the negative values of DS8 due to strong adsorbate– adsorbent interaction. The value of Ea as calculated from the plot of ln k vs. 1/T comes out to be 19.50 kJ/mol for Cu(II) and 36.988 kJ/mol for Ni(II). Negative values suggest there is no energy barrier for adsorption and the reaction is exothermic [35].
Fig. 11. Single and binary adsorption of Cu(II) and Ni(II) on coal dust. The solid lines represent the fitting of data by Langmuir isotherms.
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Distilled water 0.1N H2SO4 0.1N HNO3 0.1N HCl
100 90 80
% Desorption
70 60 50 40 30 20 10 0 Cu (II)
Ni (II)
Fig. 12. Desorption of Cu(II) and Ni(II) from respective metal loaded coal dust using different eluents.
each metal ion were given in Table 6. To quantify between the experimental and predicted values, statistical analysis using regression coefficient (R), correlation coefficient (R2) and error analysis using Chi-square (x2) and root mean square error (RMSE) were performed for all sets of isotherms. It was seen that for both the metals Langmuir model had better applicability, then followed by Redlich–Peterson model (Table 7). For mono component adsorption the metal loading capacity as calculated for Cu(II) was found to be 21.739 mg/g and for Ni(II) was 20.408 mg/g. In the case of R–P isotherm model the value of b lies between 0 and 1 for both the metals, which shows the favorable adsorption. Parameter estimation of both the models (Langmuir and R–P) shows that Cu(II) ions have more affinity than Ni(II) ions to get adsorbed on the coal dust surface for single solute containing solution. 6.11. Bi-component adsorption In a bi-component system, for studying the interaction of the two metals in the system, 1:1 ratio of the metal concentration was chosen in the range of 100–500 mg/L. Langmuir isotherm model was applied over the experimental data as demonstrated in Fig. 11. Adsorption capacities as obtained in case of single metal (Cu(II) or Ni(II)) system and in binary system (Cu(II) and Ni(II)) are presented in Table 8. Effect of ionic concentrations [36] on the adsorption process may be seen through the ratio of sorption capacity for a metal ion along with other ion (qmix) to the sorption capacity when present alone (qo) in the aqueous system. When qmix =qo > 1, the sorption capacity is enhanced by the presence of other metal ions or is said to be showing synergism; Table 8 Langmuir isotherm constants for single- and multi-component adsorption of Cu(II) and Ni(II) on coal dust. Metal ions
Cu(II) Ni(II) Cu(II) Ni(II)
System
Cu(II) alone Ni(II) alone Cu + Ni Cu + Ni
Langmuir constants qo (mg/g)
b (mg1)
R2
qmix/qo
21.739 20.408 8.403 7.352
0.066 0.068 0.044 0.037
0.995 0.994 0.991 0.994
0.386 0.360
qmix =qo ¼ 1, system shows no interaction between the species; qmix =qo < 1, there is suppression of the adsorption capacity due to the presence of other ion or shows antagonistic interaction of the two ions. Values of qmix =qo are shown in Table 8 which indicate that the adsorbing power of coal dust decreases for the aqueous system containing more than one metal. Study indicates the antagonistic behavior as there exists a competition between the Cu(II) and Ni(II) ions for the adsorbing sites. Moreover the coal dust has preference for Cu(II) ions even in the binary solution which may be the result of different electronegativity and ionic potential of the metal ions [37]. 6.12. Desorption study and adsorbent disposal Regeneration studies for metal loaded adsorbent were done using 0.1 N HCl, 0.1 N HNO3, 0.1 N H2SO4 and distilled water. Desorption efficiency of each eluent is plotted in Fig. 12. Cu(II) ions showed better desorption than Ni(II) ions for all the eluents. Distilled water had minimum efficiency of 32.1% for Cu(II) and 25% for Ni(II), respectively, while it was much better for 0.1 N H2SO4 (72.5% for Cu(II) and 67.12% for Ni(II)) and (73.3% for Cu(II) and 52.7% for Ni(II)) for 0.1 N HNO3. But 0.1 N HCl responded well as an adsorbent desorber which can be related to the higher acidity of HCl. It desorbed 99.63% of Cu(II) ions and 71.3% of Ni(II) ions. Finally 0.1 N HCl was selected as the regenerating eluent and it was tested over number of adsorption–desorption cycles. Metal loaded coal dust was dipped into 100 mL of 0.1 N HCl and it was agitated for an hour. The filtrate was tested for desorption efficiency of the eluent. Coal dust thus regenerated was again used for adsorption. Four times such adsorption–desorption cycles were run and the efficiencies are noted in Table 9. Results show that upto III cycle adsorption percentage touched 93.1 for Cu(II) and 87 for Ni(II) instead of 97% for Cu(II) and 100% for Ni(II) ions in the I cycle. But for IV cycle there was a considerable loss in adsorption alongwith a 10% loss in the mass of adsorbent. The studies indicate the reusability of the coal dust upto three stages. The metal solution obtained after desorption could be send back for industrial use and as the coal dust has high calorific value of about 4000 kcal/kg which provides it’s applicability of being used as a fuel.
Please cite this article in press as: Kapur M, Mondal MK. Competitive sorption of Cu(II) and Ni(II) ions from aqueous solutions: Kinetics, thermodynamics and desorption studies. J Taiwan Inst Chem Eng (2014), http://dx.doi.org/10.1016/j.jtice.2014.02.022
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JTICE-861; No. of Pages 11 M. Kapur, M.K. Mondal / Journal of the Taiwan Institute of Chemical Engineers xxx (2014) xxx–xxx Table 9 Data for adsorption–desorption cycles using 0.1 N HCl for coal dust regeneration. Cycles
I II III IV
% Adsorption
% Desorption
Cu(II)
Ni(II)
Cu(II)
Ni(II)
97 95.3 93.1 79.2
100 92.32 87 65.9
99.03 88.6 77.3 50.46
71.3 62.49 51.1 42.7
7. Conclusion Coal dust has proved its potential for simultaneous adsorption of Cu(II) and Ni(II) ions from aqueous solutions. From the experimental studies it has been observed that for a dosage of 10 g/L and metal concentration 10 mg/L almost 100% removal of ions was achieved at a pH 4 within a time span of 60 min. Metal adsorption was feasible and spontaneous and both the metals were found to follow pseudo-second order kinetics. Results were in good agreement with the Langmuir isotherms for single as well as multisolute system. Both the metals had competitive relation as single metal adsorption was better than bicomponent adsorption. In addition to this Cu(II) showed superior adsorption properties in comparison to Ni(II) ions. Thus coal dust can be used for individual and simultaneous removal of Cu(II) and Ni(II) from the solutions. Acknowledgment Authors are thankful to Indian Institute of Technology (Banaras Hindu University), India for extending all necessary facilities and supports to undertake the work. References [1] Chang Q, Wang G. Study on the macromolecular coagulant PEX which traps heavy metals. Chem Eng Sci 2007;62:4636–43. [2] Mirbagheri SA, Hosseini SN. Pilot plant investigation on petrochemical wastewater treatment for the removal of copper and chromium with the objective of reuse. Desalination 2005;171:85–93. [3] Rengaraj S, Joo CK, Kim Y, Yi J. Kinetics of removal of chromium from water and electronic process wastewater by ion exchange resins: 1200H, 1500H and IRN97H. J Hazard Mater 2003;102:257–75. [4] Korus I, Loska K. Removal of Cr(III) and Cr(VI) ions from aqueous solutions by means of polyelectrolyte-enhanced ultrafiltration. Desalination 2009;247: 390–5. [5] Heidmann I, Calmano W. Removal of Zn(II), Cu(II), Ni(II), Ag(I) and Cr(VI) present in aqueous solutions by aluminium electrocoagulation. J Hazard Mater 2008;152:934–41. [6] Bhatnagar A, Minocha AK. Biosorption optimization of nickel removal from water using Punica granatum peel waste. Colloids Surf B 2010;76:544–8. [7] Wang S, Peng Y. Natural zeolites as effective adsorbents in water and wastewater treatment. Chem Eng J 2010;156:11–24. [8] Naiya TK, Bhattacharya AK, Das SK. Adsorption of Cd(II) and Pb(II) from aqueous solutions on activated alumina. J Colloid Interface Sci 2009;333:14–26. [9] Wang H, Kang J, Liu H, Qu J. Preparation of organically functionalized silica gel as adsorbent for copper ion adsorption. J Environ Sci 2009;21:1473–9.
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[10] Gabaldon G, Marzal P, Ferrer J, Seco A. Single and competitive adsorption of Cd2+ and Zn2+ onto a granular activated carbon. Water Res 1996;30:3050–60. [11] Kalavathy MH, Miranda LR. Comparison of copper adsorption from aqueous solution using modified and unmodified Hevea brasiliensis saw dust. Desalination 2010;255:165–74. [12] Thirumavalavan M, Lai YL, Lee JF. Fourier transform infrared spectroscopic analysis of fruit peels before and after the adsorption of heavy metal ions from aqueous solution. J Chem Eng Data 2011;56:2249–55. [13] Ajmal M, Rao RAK, Ahmad R, Ahmad J. Adsorption studies on Citrus reticulata (fruit peel of orange): removal and recovery of Ni(II) from electroplating wastewater. J Hazard Mater 2000;79:117–31. [14] Khalid N, Ahmad S, Kiani SN, Ahmed J. Removal of lead from aqueous solutions using rice husk. Sep Sci Technol 1998;33:2349–62. [15] Villaescusa I, Fiol N, Martinez M, Miralles N, Poch J, Serarols J. Removal of copper and nickel ions from aqueous solutions by grape stalks wastes. Water Res 2004;38:992–1002. [16] Sun G, Shi W. Sunflower stalks as adsorbents for the removal of metal ions from wastewater. Ind Eng Chem Res 1998;37:1324–8. [17] Gupta S, Babu BV. Utilization of waste product (tamarind seeds) for the removal of Cr(VI) from aqueous solutions: equilibrium, kinetics, and regeneration studies. J Environ Manage 2009;90:3013–22. [18] Panday KK, Prasad G, Singh VN. Copper(II) removal from aqueous solutions by fly ash. Water Res 1985;19:869–73. [19] Gupta VK, Rastogi A, Dwivedi MK, Mohan D. Process development for the removal of zinc and cadmium from wastewater using slag—a blast-furnace waste material. Sep Sci Technol 1997;32:2883–912. [20] Lopez-Delgado A, Perez C, Lopez FA. Sorption of heavy metals on blast furnace sludge. Water Res 1998;32:989–96. [21] Patnaik LN, Das CP. Removal of hexavalent chromium by blast furnace flue dust. Ind J Environ Health 1995;37:19–25. [22] Dermentzis K, Davidis A, Papadopoulou D, Christoforidis A, Ouzounis K. Copper removal from industrial wastewaters by means of electrostatic shielding driven electrodeionization. J Eng Sci Technol Rev 2009;2:131–6. [23] Patterson JW. Industrial wastewater treatment technology. 2nd ed. Stoneham, MA: Butterworth Publisher; 1985. [24] APHA. Standard methods for examination of water and wastewater. 14th ed. Washington, DC: American Public Health Association; 1975. [25] Lagergren S. Zurtheorie der sogenannten adsorption gelo¨sterstoffe. KungligaSvenska Vetenskapsakademiens Handlingar 1898;24:1–39. [26] McKay G, Ho YS. Pseudo-second order model for sorption processes. Process Biochem 1999;34:451–65. [27] Cheung CW, Porter JF, Mckay G. Sorption kinetics for the removal of copper and zinc from effluents using bone char. Sep Purif Technol 2000;19:55–64. [28] Weber WJ, Morris JC. Equilibria and capacities for adsorption on carbon. J Sanit Eng Div 1964;90:79–107. [29] Langmuir I. The adsorption of gases on plane surfaces of glass, mica and platinum. J Am Chem Soc 1918;40:1361–7. [30] Brunauer S, Deming LS, Deming WE, Teller E. On a theory of the Van der Waals adsorption of gases. J Am Chem Soc 1940;62:1723–32. [31] Srivastava VC, Mall ID, Mishra IM. Characterization of mesoporous rice husk ash (RHA) and adsorption kinetics of metal ions from aqueous solution onto RHA. J Hazard Mater 2006;134:257–67. [32] Brown PA, Gill SA, Allen SJ. Metal removal from wastewater using peat. Water Res 1997;33:2469–79. [33] Kolthoff IM, Sandell EB, Mechan EJ, Bruckenstein S. Quantitative chemical analysis. London: Macmillan; 1971. [34] Saeed A, Iqbala M, Akhtar MW. Removal and recovery of lead(II) from single and multimetal (Cd, Cu, Ni, Zn) solutions by crop milling waste (black gram husk). J Hazard Mater 2005;117:65–73. [35] Kapur M, Mondal MK. Mass transfer and related phenomena for Cr(VI) adsorption from aqueous solutions onto Mangifera indica sawdust. Chem Eng J 2013;218:138–46. [36] Mohan D, Chander S. Single component and multicomponent metal ions adsorption by activated carbons. Colloids Surf A 2001;177:183–96. [37] Allen SJ, Brown PA. Isotherm analyses for single component and multi-component metal sorption onto lignite. J Chem Technol Biotechnol 1995;62: 17–24.
Please cite this article in press as: Kapur M, Mondal MK. Competitive sorption of Cu(II) and Ni(II) ions from aqueous solutions: Kinetics, thermodynamics and desorption studies. J Taiwan Inst Chem Eng (2014), http://dx.doi.org/10.1016/j.jtice.2014.02.022
JTICE-861; No. of Pages 11 Journal of the Taiwan Institute of Chemical Engineers xxx (2014) xxx–xxx
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Competitive sorption of Cu(II) and Ni(II) ions from aqueous solutions: Kinetics, thermodynamics and desorption studies Meghna Kapur, Monoj Kumar Mondal * Department of Chemical Engineering and Technology, Indian Institute of Technology (Banaras Hindu University), Varanasi 221005, Uttar Pradesh, India
A R T I C L E I N F O
A B S T R A C T
Article history: Received 25 October 2013 Received in revised form 28 January 2014 Accepted 25 February 2014 Available online xxx
Extensive study has been done in the context of single metal adsorption from aqueous solutions but the present study approaches the simultaneous sorption of metal ions. Aim of the present work is to characterize the coal dust for its ability to remove Cu(II) and Ni(II) from aqueous solutions. Variation of the working parameters viz., pH, contact time, adsorbent dose, metal ion concentrations, temperature were done in a range to optimize ideal conditions for the adsorption of ions from a binary metal solution containing Cu(II) and Ni(II) in a batch mode. Adsorption was found to be exothermic and the parameter estimation viz. DG8, DH8, DS8 showed it to be thermodynamically favorable. Second order kinetics was fitted well for bi-component adsorption and Langmuir isotherm strongly supported the mechanism. Coexistence of the ions affected the adsorption capacity and showed antagonistic manner in comparison to the single metal. Desorption experiments showed that the coal dust can be used effectively upto three cycles and proper disposal has also been mentioned. ß 2014 Taiwan Institute of Chemical Engineers. Published by Elsevier B.V. All rights reserved.
Keywords: Adsorption Cu(II) and Ni(II) Coal dust Isotherms Regeneration
1. Introduction Water is getting contaminated in various ways. Industries and agriculture makes the way of chemicals to enter into the water streams. Numbers of organic, inorganic, phenolic and metallic species enters the water bodies and becomes lethal after crossing a certain limit in the metabolic system. Researchers have shown interest in treating such effluents by applying techniques such as coagulation [1], chemical precipitation [2], ion exchange [3], membrane separation [4], electrochemical treatment [5] and adsorption [6]. By considering cost, time needed for purification, chemical inputs, flexibility and design simplicity, the outcomes of adsorption are better than any other techniques. Few commercial adsorbents zeolites [7], activated alumina [8], silica gel [9] and activated carbon [10] were used for water treatment as they possess high surface area but owing to high initial investments, researchers shifted toward more environment friendly low cost adsorbents. Lignin and cellulose bearing plant materials viz. saw dust [11], fruit peels [12,13], rice husk [14] has been given preference for heavy metal removal from solutions. Certain agricultural wastes
* Corresponding author. Tel.: +91 9452196638; fax: +91 5422367098. E-mail address: [email protected] (M.K. Mondal).
viz. grape stalks [15], sunflower stalks [16], tamarind seeds [17] have also been investigated as adsorbents. Fly ash (an industrial waste) generated from coal combustion residue is found to be silica and alumina rich and thus has potential for metal adsorption [18]. Steel plants generate a large volume of granular blast furnace slag [19], sludge [20] and dust [21] which were evaluated as adsorbents. Mostly single metal adsorption from aqueous solutions have drawn the attention of investigators, but it is necessary to draw the attention toward the simultaneous removal of more than one heavy metal, as in general various species are present in the effluents. In the case of multicomponent adsorption of metals, the factors which affect the removal efficiency are nature of adsorbent (metal binding site, presence of different functional groups), metallic properties (concentration, ionic size, standard redox potential, electronegativity) and the pH of the solution. The approach of the present work is for simultaneous removal of Cu(II) and Ni(II), which are present in the water discharged from the electroplating machinery, alloy making and microelectronics industries. As prescribed by Bureau of Indian Standards the safe limit for discharge of Cu(II) through industries is 1.5 mg/L and for drinking water it is set to be 0.05 mg/L while in case of Ni(II) the acceptable limit is 0.02 mg/L. Heavy metal concentrations in waste waters vary from 0.5 to a high value of 1000 mg/L. Waste streams from electroplating industries contains Cu(II) upto 500 mg/L [22] and
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Please cite this article in press as: Kapur M, Mondal MK. Competitive sorption of Cu(II) and Ni(II) ions from aqueous solutions: Kinetics, thermodynamics and desorption studies. J Taiwan Inst Chem Eng (2014), http://dx.doi.org/10.1016/j.jtice.2014.02.022
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M. Kapur, M.K. Mondal / Journal of the Taiwan Institute of Chemical Engineers xxx (2014) xxx–xxx
the rinse water of plating industries may have Ni(II) in the range of 2–900 mg/L [23]. This paper brings in picture (i) the feasibility of coal dust for simultaneous removal of Cu(II) and Ni(II) from aqueous solutions (ii) effect of working parameters (pH, time of contact, agitation speed, temperature, initial metal concentration) (iii) kinetics behind the process (iv) suitability of adsorption isotherm models for metals in individual and multicomponent aqueous solutions (v) regeneration and reuse of the adsorbent.
2. Experimental 2.1. Adsorbent The adsorbent used for simultaneous removal of metallic species from aqueous solutions is coal dust. It has been collected from Northern Coal fields Limited (NCL) Singrauli (M.P.), India. Naturally obtained coal dust was sieved and dried at 105 8C to make it moisture free. It was kept in a vacuum dessicator for future use. 2.2. Reagents All the chemicals used were of analytical grades. Stock solution (1000 mg/L) of Cu(II) was prepared by dissolving 3.802 g of cupric nitrate [Cu(NO3)23H2O] in 1000 mL of double distilled water and for Ni(II) 6.73 g of ammonium nickel(II) sulphate [(NH4)2SO4NiSO46H2O] was dissolved in 1000 mL of double distilled water. Working solutions were prepared by diluting the stock solutions in the desired ratio. The 0.1 M NaOH and 0.1 M HCl were used for pH adjustments of the test solutions. 2.3. Instrumentation Solution pH was tested by a digital pH meter (LI 120, Elico India), calibrated using buffer solutions (pH 4.0, 7.0 and 9.2). Adsorbent was made moisture free by drying in an oven (S.M. Scientific Instruments Pvt. Ltd., New Delhi). Mean particle diameter was determined using CIS-50 ANKERSMID particle size analyzer. In the batch system the required temperature and constant agitation speed was set by a temperature controlled water bath shaker (NSW-133). Spectral analysis of the adsorbent before and after adsorbing metal ions was done using NICHOLET 5700 spectrophotometer (Thermo electron). Sample was mixed with a dry alkali halide (KBr), which is transparent in the midinfrared region (4000–400 cm1) and made into a 1 cm disc. Spectrum was obtained by passing infrared radiation through the sample and determining the fraction absorbed at a particular energy. This analysis relates the surface of the adsorbent to the modes of the vibrations of functional groups present on it, responsible for the adsorption. To test the mineral identification and crystallinity of the adsorbent X-ray diffraction studies were done. Pattern was recorded by a Philips 1710 X-ray diffractometer with a Cu Ka target of radiation wavelength 1.542 A˚ operating at 40 kV and 40 mA. Peaks obtained signify whether the sample is crystalline with sharp peaks or it is amorphous in nature showing broad peaks. Crystallite size can be determined further in case of crystalline material. The Brunauer–Emmett–Teller (BET) surface area of the coal dust was investigated by N2 adsorption– desorption method using Micromeritics ASAP 2020, V302G single port. Liquid nitrogen was used as the cold bath (77 K). The porous structures were studied through BJH (Barret–Joyner–Halenda) data. Concentration of copper and nickel in the test solutions were calculated by developing colored complexes for each metal and
tested at suitable wavelengths using UV–Vis spectrophotometer (ELICO SL 159 UV–Vis Spectrum). 2.4. Batch adsorption studies For studying the adsorption characteristics of coal dust for the removal of binary species from aqueous solutions batch adsorption studies were performed by variation of parameters. Experiments were performed at room temperature (28 2 8C) by diluting the stock solutions of Cu(II) and Ni(II). Dilution was done to obtain solutions in the range of 5–500 mg/L. Batches of metal solution and adsorbent were run for the contact time (0–90 min). Various parameters viz. pH (2–7), adsorbent dose (2–12 g/L), speed of agitation (0–200 rpm), initial metal concentrations (5–100 mg/L) and temperature (20–40 8C) were studied in the given respective ranges, to obtain the optimum conditions for adsorption to occur. Adsorbent and the adsorbate solution was contacted in a batch wise manner and after adsorption the coal dust was filtered and thus separated from the solution. Analysis of metal concentrations in the test solution before and after adsorption was done by spectrophotometric method. Dimethylglyoxime method was followed for Ni(II) at 445 nm and sodium dimethyl dithiocarbamate method for Cu(II) at 457 nm [24]. Removal efficiency of the adsorbate or metal ions at each interval of time is given by % Removal of CuðIIÞ or NiðIIÞ ions ¼
Co C f 100 Co
(1)
Adsorption capacity (mg/g) is calculated using following equation: q¼
ðC o C e ÞV W
(2)
where q is the adsorption capacity of the adsorbent in (mg/g). Initial, final and equilibrium concentrations of the metal ions are denoted by Co, Cf and Ce, respectively. W is the mass of the adsorbent (g) taken in V volume of solution (L). 2.5. Batch desorption studies Studies for regenerating metal loaded adsorbent are necessary so that the adsorbent can be freed from the metals and can be reused or disposed off without imposing any burden on the environment. For desorbing metals the selection of a suitable eluent is essential. Desorption can be done using distilled water, mineral acids (HCl, HNO3, H2SO4) or EDTA solution and the ions released into eluent can be analyzed. Present work deals on regenerating coal dust using dilute solutions of HCl, HNO3, H2SO4 and distilled water. Desorption efficiency at each cycle has been calculated using the following equation: Desorption efficiency ¼
Concentration of metal desorbed Concentration of metal loaded 100
(3)
3. Adsorption kinetics Kinetics explains the progress of adsorption with time. It is a means for understanding the dynamics of adsorption process. Parameters obtained through kinetic studies can be used for designing up the operation. Reactions are in general described by the order and the rate of the reaction at which it is occurring. Kinetics is explained using pseudo-first order kinetics, pseudosecond order rate kinetics, Elovich model and intraparticle diffusion model.
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of Cu(II) and Ni(II) ions were obtained by using the following equations:
3.1. Pseudo-first order kinetics The general expression of the pseudo-first order kinetics model as proposed by Lagergren [25] is
Kc ¼
dqt ¼ k1 ðqe qt Þ dt
DG0 ¼ RT ln Kc
(4)
By applying boundary conditions qt = 0 at t = 0 and qt = qt at t = t, it can be linearized to get ðk1 Þt logðqe qt Þ ¼ log qe 2:303
C Ae Ce
ln K c ¼
(11)
DS0
!
R
(12)
DH 0
!
RT
(13)
(5)
where qe and qt are the amounts of metal adsorbed (mg/g) at equilibrium time and at any time t, respectively; k1 (min1) is the first order rate constant. 3.2. Pseudo-second order kinetics Kinetics in the form of pseudo-second order [26] is described by the following equation: dqt ¼ k2 ðqe qt Þ2 dt
3
(6)
where Kc is the equilibrium constant at temperature T, R is the universal gas constant (8.314 103 kJ/mol K) and CAe and Ce are the equilibrium concentrations of adsorbate on the adsorbent and in the solution, respectively. Activation energy deciphers the nature of the process and can be determined through Arrhenius equation: k ¼ AeEa =RT
(14)
which linearizes into ln k ¼ ln A
Ea RT
(15)
Simplified form of the equation obtained after integration under boundary conditions qt = 0 at t = 0 and qt = qt at t = t is as follows:
Ea is the activation energy (kJ/mol), A is the frequency factor (min1) and T temperature in Kelvin.
t 1 t ¼ þ qt k2 q2e qe
4. Adsorption isotherms
(7)
where k2 (g/mg min) is the second order rate constant. 3.3. Elovich kinetics Elovich equation is applied for chemisorption kinetics. It is often evaluated for heterogeneous surfaces [27] and devised as dqt ¼ a expðbqt Þ dt
(8)
alongwith the boundary conditions it was assumed that ab t, which yields qt ¼
1
b
lnðabÞ þ
1
b
lnðtÞ
(9)
qt ¼ A þ Bln t where a and b are the Elovich constants. a (mg/g min) represents the rate of chemisorption at zero coverage and b (g/mg) is related to the extent of surface coverage and activation energy for chemisorptions.
4.1. Langmuir model Langmuir isotherm works on following assumptions [29]: Applicable for monomolecular layer adsorption. Sites are homogeneous with equal affinity toward adsorbate. Adsorption at one site does not affect the adjacent site. To determine the maximum adsorption capacity for single metal solution, following equation is employed: (Non-linear form) qe ¼
3.4. Intraparticle diffusion This model regarding intraparticle diffusion proposed by Weber and Morris [28] is as follows: qt ¼ K id t 1=2
Isotherms are the means of analyzing the adsorbate concentration in the solution and the amount adsorbed by a specific mass of adsorbent. Isotherms determine the adsorption capacity of the adsorbent. They mainly depend upon the nature and type of the system. Experiments were carried out to evaluate the best fit adsorption isotherm for describing the process at a fixed temperature by varying initial concentrations of metal ions.
(10)
where Kid (mg/g min1/2) is the intraparticle diffusion rate constant. If a plot of qt against square root of contact time results a straight line passing through origin, the model is followed otherwise film diffusion plays an important role instead of intraparticle diffusion during the adsorption process. 3.5. Thermodynamic studies and activation energy Thermodynamic parameters such as change in standard free energy (DG8), enthalpy (DH8) and entropy (DS8) for the adsorption
qo bC e 1 þ bC e
(16)
(Linear form) Ce 1 Ce þ ¼ qe qo b qo
(17)
where Ce is the equilibrium concentration (mg/L), qe is the amount adsorbed per unit mass of adsorbent at equilibrium (mg/g). The qo and b are the Langmuir constants related to the adsorption capacity and energy of adsorption, respectively. 4.2. Freundlich model This model is applied for heterogeneous surfaces ln qe ¼ ln K f þ
1 ln C e n
(18)
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Freundlich constants Kf and n related to adsorption capacity and intensity, respectively. 4.3. Redlich–Peterson model Redlich–Peterson (R–P) isotherm model is applicable in both homogeneous as well as heterogeneous systems as it is an improvement over Langmuir and Freundlich models. It is expressed as qe ¼
K RCe
(19)
b
1 þ aR Ce
where KR is R–P isotherm constant (L/g), aR is R–P isotherm constant (mg1) and b is the exponent (0 < b< 1), Ce is the equilibrium concentration (mg/L). In the linearized form, it is represented as Ce 1 ¼ ln aR þ b ln C e (20) ln K R qe
Table 2 Spectral analysis of coal dust before and after adsorption of Cu(II) and Ni(II) ions. Band positions (cm1)
Assignment
Before adsorption
After adsorption
Differences
3693.81 3387.11 2924.18 692.47
3691.88 3412.19 2922.25 690.54
+1.93 25.08 +1.93 +1.93
–OH group –OH stretching vibrations Asymmetrical –CH stretching CH bending vibrations
Table 3 Peak positions and d-spacing values of the minerals on the XRD diffractogram identified in coal dust. Peak positions in degrees (2u) angle
d-Spacing (A˚)
Possible mineral
12.41 19.90 20.89 24.92 26.69 29.63
7.12 4.46 4.25 3.57 3.33 3.01
Kaolinite Illite Quartz Kaolinite Quartz Calcite
5. Error analysis Due to linearization of the non-linear isotherm models some errors get inherited due to which the fit between experimental data and the model predicted values as explained by correlation coefficient does not put such a meaning thus error analysis conformity is required. 5.1. Chi-square test The Chi-square test can be examined by using following equation: 2
x ¼
2 X qe;exp qe;model
(21)
qe;model
5.2. Root mean square error (RMSE) The analysis for RMSE can be accomplished as X qe;exp qe;model RMSE ¼ qe;model
!2 (22)
6. Results and discussion 6.1. Adsorbent characterization Certain physical characteristics which define the adsorbent are listed in Table 1. The functional groups detected on the adsorbent surface with the help of spectral bands using FTIR spectroscopy before and after adsorption of Cu(II) and Ni(II) ions are pictured in Fig. 1(a) and (b), respectively. Spectrum shows the strong absorption Table 1 Characteristics of the coaldust. Parameters
Values
Moisture (%) Ash (%) Volatile matter (%) Fixed carbon (%) pHZPC Bulk density (g/cm3) Particle size (mm)
1.259 2.25 2.3 94.19 2.9 0.7457 30.99
of free hydroxyl groups of alcohols and phenols at wavenumbers 3693.81 and 3620.51 cm1. The OH stretching vibrations are seen at 3387.11 cm1. Peak at 2924.18 cm1is for asymmetrical C–H stretching of methylene group while symmetrical bending vibrations of –CH methyl groups are present at 1379.15 cm1. The band positions at 1112.96 and 1031.95 cm1 show C–O stretching vibrations. Strong –CH bending vibrations (out of plane) are seen at the peaks 914.29, 794.70 and 692.47 cm1. Skeletal vibrations of C–C stretching within the ring are seen at 1589.40 cm1 and weak bands of S–S stretching vibrations are present at 468.72 cm1. Additionally most of the peaks in spectra of coal between 1100 and 400 cm1 can be assigned to clay minerals such as quartz, kaolinite, illite and the montmorillonite group. Peaks at 468.72, 538.16, 692.47, 794.70, 914.29 and 1031.95 cm1 attributes these minerals. The Si–O–Si stretching vibration shows absorption at 1031 cm1. Studies of the adsorbent after adsorbing heavy metals from the aqueous solutions indicate the participation of free hydroxyl (–OH) groups, –CH stretching and –OH stretching vibrations (Table 2). The peaks of X-ray diffraction represent slight crystalline nature of the coal dust. XRD analysis shows the presence of quartz (SiO2), kaolinite [Al2Si2O5(OH4)], illite [KAl2(OH)2AlSi3(O,OH)10] and calcite (CaCO3) minerals. The corresponding peak positions and d-spacing values are listed in Table 3. Pattern obtained for adsorbent before and after adsorbing the metal ions is shown in Fig. 2(a) and (b), respectively. After adsorbing the metal ions, the intensity of the peaks were seen to be slightly diminished which attributes to the adsorption of metal ions on the upper layer of the coal dust by means of physisorption. N2 gas adsorption–desorption isotherms for the coal dust as obtained through BET is presented in Fig. 3. It shows that the isotherm belongs to type-IV adsorption–desorption isotherm with H3 type of hysteresis loop indicating the presence of mesoporosity with affinity for adsorption. This is in accordance with BDDT (Brunauer, Deming, Deming and Teller) classification [30]. The path dependent adsorption–desorption behavior leading to hysteresis is an indicator of the porous nature of the sample. Coal dust has a wide pore size distribution and thus a wide distribution of surface area can be seen. The BET surface area is 12.66 m2/g, whereas BJH adsorption/desorption surface area of pores is 6.879/6.6283 m2/g. The single point total pore volume of pores (d < 9.474 A˚) is found to be 0.004238 cm3/g, whereas cumulative adsorption/desorption pore volume of the pores (17 A˚ < d< 3000 A˚) is 0.032150/0.030116 cm3/g, respectively.
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(a) 20 %T 17.5
15
1379.15
1589.40
538.16 1031.95
2.5
468.72
914.29
1112.96
5
3387.11
3693.81
7.5
692.47
794.70
2357.09 2924.18
10
3620.51
% Transmittance
12.5
0 4000 MK1
375 0
4000 MK 2
3750
350 0
3250
300 0
2750
2500
2250
2000
1750
150 0
125 0
1000
750
Wave numbers (cm-1)
500 1/c m
(b) 16 %T
12
690.54
0 3500
3250
3000
2750
2500
2250
2000
1750
1500
1250
1000
750
468.72
538.16
914.29
1379.15
1031.95
2
1112.96
3691.88
4
3412.19
6
1589.40
2922.25
8
794.70
2357.09
10
3620.51
% Transmittance
14
500 1/c m
Wave numbers (cm-1) Fig. 1. FTIR plot of coal dust (a) before adsorption and (b) after adsorption of Cu(II) and Ni(II).
The average pore diameter by BET method was found to be 13.3876 A˚, whereas the BJH adsorption/desorption average pore diameter is 186.939/181.740 A˚. Analysis of BJH adsorption pore distribution shows that micropores have a area of almost 7%, 82% area is occupied by mesopores and macropores are 12% while that of desorption shows that mesopores account for 95% area. Coal dust is found to consist mainly of mesopores. This is the factor most desirable for the liquid phase adsorptive removal of metal ions [31]. 6.2. Effect of pH By solid addition method [31] the point of zero charge (pHZPC) of the coal dust was found to be 2.9 and it gave a clear picture of adsorption of ionic species above this pHZPC. For determining the
optimum pH for removal of Cu(II) and Ni(II) ions from the aqueous solutions, initial pH of the system was set in the range of 2 to 7. Solution containing 10 mg/L of each metal with an adsorbent dose of 10 g/L was shaken for 60 min. Fig. 4 shows that with the increase in pH from 2 to 4, the adsorption percentage of Cu(II) increased from 60 to 97.32% and thereafter it falls to 83.7% at pH 7. Similar pattern was observed for Ni(II) ions with a maximum adsorption of 100% at a pH 4. Thus pH 4 was selected as optimum for further studies of binary adsorption from aqueous solutions. At a low pH the surface of the adsorbent gets protonated and thus H+ ions causes hindrance for the metal ions to adsorb at the surface of coal dust but at a slightly higher pH i.e. above pHZPC value of 2.9 the surface acquires negative charge sufficient to bind cationic species. Thus electrostatic attraction works behind the removal. Similar findings have been reported in the past [32]. Binding occurs
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(a)
Cu (II) Ni (II)
3500
100
3000
2500
2000
% Removal
Intensity (cps)
80
1500
1000
60
40
500
20 0 0
10
20
30
40
50
60
70
80
90
0
2-theta (deg)
(b)
1
2
3
4
5
6
7
Initial pH
3000
Fig. 4. Effect of initial pH on Cu(II) and Ni(II) removal by coaldust (temperature: 30 8C; pH: 4; adsorbent dose: 10 g/L; metal concentration: 10 mg/L; time: 60 min; particle size: 30.99 mm).
2500
Intensity (cps)
2000
While increasing pH, a point is achieved where the metal solubility decreases and results in precipitation as metal hydroxides [33]. For a 10 mg/L of solution of Cu(II) and Ni(II) the pH for precipitation is found to be 6 and 8.5, respectively [34]. So the chosen pH 4, which is much below than the pH of metal precipitation is optimum for future experiments.
1500
1000
500
6.3. Effect of contact time 0 0
10
20
30
40
50
60
70
80
90
2-theta (deg) Fig. 2. XRD plot of coal dust (a) before adsorption and (b) after adsorption of Cu(II) and Ni(II).
between the metal and free hydroxyl (–OH) groups, –CH stretching and –OH stretching vibrations, moreover the coal dust is predominantly mesoporous as explained earlier, most of the cations get adsorbed into the mesopores.
Solution containing 10 mg/L of Cu(II) and Ni(II) at a pH 4 was kept at a constant shaking for 90 min with adsorbent dose of 10 g/ L. It can be well inferred from Fig. 5 that for Cu(II) a significant change is noticed from 10 to 60 min but after 60 min there was even less than 1% change and for Ni(II) change was insignificant just after 30 min of contact time. So the duration at which equilibrium was found to be established between the adsorbate concentration in solution and on the adsorbent was 60 min for the bisolute system. Reason behind this may be that in the initial stages of adsorption all the adsorptive sites are vacant, as the time proceeds the rate of occupancy of sites gets rapid and after a certain
100 90 80
Cu (II) Ni (II)
% Removal
70 60 50 40 30 20 10 0 0
10
20
30
40
50
60
70
80
90
Contact time (min)
Fig. 3. N2 gas adsorption–desorption isotherm for coal dust.
Fig. 5. Effect of contact time on Cu(II) and Ni(II) removal by coaldust (temperature: 30 8C; pH: 4; adsorbent dose: 10 g/L; metal concentration: 10 mg/L; particle size: 30.99 mm).
Please cite this article in press as: Kapur M, Mondal MK. Competitive sorption of Cu(II) and Ni(II) ions from aqueous solutions: Kinetics, thermodynamics and desorption studies. J Taiwan Inst Chem Eng (2014), http://dx.doi.org/10.1016/j.jtice.2014.02.022
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90
90
80
80
70
70
60
% Removal
% Removal
100
Cu (II) Ni (II)
100
60 50
7
Cu (II) Ni (II)
50 40 30
40
20
30
10
20
0
10
0
2
4
6
8
10
12
Adsorbent dose (g/L)
0 0
10
20
30
40
50
60
70
80
90
100
Initial metal concentrations (mg/L)
Fig. 7. Effect of adsorbent dose on Cu(II) and Ni(II) removal by coaldust (temperature: 30 8C; pH: 4; metal concentration:10 mg/L; time: 60 min; particle size: 30.99 mm).
Fig. 6. Effect of initial metal concentration on Cu(II) and Ni(II) removal by coaldust (temperature: 30 8C; pH: 4; adsorbent dose: 10 g/L; time: 60 min; particle size: 30.99 mm).
Cu (II) Ni (II)
100
duration a repulsive force comes into play between the ionic species in the solution and the sites already occupied by the same species.
80
With an adsorbent dose of 10 g/L and contact time of 60 min, the initial concentrations of the solution containing Cu(II) and Ni(II) at a pH 4 were set in the range of 5–100 mg/L. Coal dust have shown great adsorptive capacity for both the metals upto 20 mg/L as can be seen in Fig. 6 but percentage removal decreased to 80 and 77.95 for Cu(II) and Ni(II), respectively, on increasing the concentration to 100 mg/L. It is clear that low metal concentrations utilize higher energy sites but as the metal concentration increases the higher energy sites get saturated and adsorption shifts to the lower energy sites therefore resulting a drop in the efficiency. 6.5. Effect of adsorbent dose Experiment was performed to fix the optimum adsorbent dose required to adsorb the Cu(II) and Ni(II) ions from the aqueous solutions at a pH 4 and contact time 60 min for 10 mg/L solution of each metal ion in the binary solution. Variation of amount of adsorbent was done from 2 to 12 g/L. As it can be observed from Fig. 7 the percentage removal for Cu(II) varied within the range of 94–97% but for Ni(II) the change was prominent, it increased from 77.98% to 100% for dose range 2 to 10 g/L and finally became stagnant for 10 and 12 g/L. Thus 10 g/L was selected as the adsorbent dose for the binary metal solution. This could be attributed to the fact that on increasing the adsorbent amount for same concentration of metal solution, the number of sites available for adsorption goes on increasing but a stage comes after which removal attains its maximum limit and further increase had no effect. 6.6. Effect of agitation speed For no agitation condition the adsorption percentage was found to be 2.06 and 1.98 for Cu(II) and Ni(II) ions, respectively. With a higher agitation speed of 25 rpm the removal slightly increased to 20.1% and 19.34% which finally reached 97% and 100% for Cu(II)
% Removal
6.4. Effect of initial metal concentrations
60
40
20
0 0
20
40
60
80
100
120
Agitation speed (rpm) Fig. 8. Effect of agitation speed on Cu(II) and Ni(II) removal by coaldust (temperature: 30 8C; pH: 4; adsorbent dose: 10 g/L; metal concentration: 10 mg/ L; time: 60 min; particle size: 30.99 mm).
and Ni(II) ions, respectively, at 120 rpm. It may be concluded that increased agitation provided better adsorbate–adsorbent contacting. Fig. 8 shows the clear demarcation of removal efficiency for the effect of agitation in the range of 0 to120 rpm for 10 mg/L solution at a pH 4 and contact time 60 min. 6.7. Effect of temperature Experiments were performed to visualize the temperature effect on the adsorption mechanism. To find out the endothermic or exothermic nature of the process by the adsorption from bicomponent system, temperature variation was done between 20 and 40 8C for 100 mg/L of solution at pH 4. Adsorption efficiency for each temperature calculated from a series of contact time has been summarized in Fig. 9. Studies showed that increasing temperature does not support the adsorption as the removal percentage for both the metals was found to decrease, suggesting exothermic reaction behind the mechanism. Increased mobility of the ions may be one
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Table 4 Kinetic parameters for adsorption of Cu(II) and Ni(II) using coal dust. Copper(II)
Species Temperature (8C) Pseudo-first order kinetics
qe (mg/g) k1 (min1) R2 qe (mg/g) k2 (g/mg min) R2 A B R2 Kid (mg/g min1/2) R2
Pseudo-second order kinetics
Elovich model
Intraparticle diffusion
Nickel(II)
20
30
40
20
30
40
1.29 0.032 0.972 8.064 0.08 0.999 6.065 0.453 0.913 0.182 0.969
2.944 0.055 0.894 8.264 0.037 0.997 4.804 0.76 0.935 0.303 0.976
2.2646 0.046 0.868 7.7519 0.0485 0.997 4.831 0.656 0.94 0.261 0.977
0.9015 0.0276 0.854 7.8125 0.1204 0.999 6.46 0.302 0.823 0.123 0.905
2.69 0.046 0.808 8.0 0.03765 0.994 4.72 0.708 0.847 0.288 0.926
2.009 0.0368 0.936 7.09 0.0463 0.997 4.18 0.647 0.898 0.261 0.961
of the reasons for causing desorption on increasing temperature and thus decreasing affinity of adsorbate–adsorbent system. 6.8. Adsorption kinetics
(a)
For the pseudo-first order model the parameters qe (mg/g) and k1 were evaluated at temperatures 20–40 8C through a plot of log(qe qt) vs. t. The model was tested for both the metals of the binary solute system and the values of the parameters calculated using Eq. (5) are listed in Table 4. In the case of Cu(II) R2 values ranged between 0.868 and 0.972 similarly for Ni(II) it was between 0.808 and 0.936. In comparison to this the second order kinetics explained by Eq. (7) was fitted through graphical analysis of t/qt vs. t represented in Fig. 10 for Cu(II) and Ni(II), respectively, and was found to be supporting the dynamics of the sorption as its correlation coefficient values approached unity for both Cu(II) and Ni(II). Elovich model stated as Eq. (9) describes the kinetics of ion exchange system. It was applied over the entire set of temperatures for 100 mg/L solution containing both the metals in the same ratio. The results were depicted by graphs between qt and ln t. Elovich constants are listed in Table 4 alongwith the R2 (0.913– 0.94 for Cu(II) and 0.823–0.847 for Ni(II)) which shows the kinetics
o
Temperature ( C) For Cu (II) 20 30 40
7
6
t/qt(min.g)/mg
5
4
3
2
1
0 0
10
20
30
40
50
t (min) o
Temperature ( C) For Cu (II) 20 30 40 For Ni (II) 20 30 40
100
80
8
o
Temperature ( C) For Ni (II) 20 30 40
7 6
t/qt (min.g)/mg
% Removal
90
(b)
70
60
5 4 3 2 1
50 0
10
20
30
40
50
60
Contact time (min)
0 0
10
20
30
40
50
t (min) Fig. 9. Effect of temperature on Cu(II) and Ni(II) removal by coaldust (pH: 4; adsorbent dose: 10 g/L; metal concentration: 100 mg/L; time: 60 min; particle size: 30.99 mm).
Fig. 10. Pseudo-second order kinetics for (a) Cu(II) and (b) Ni(II) adsorption on coal dust.
Please cite this article in press as: Kapur M, Mondal MK. Competitive sorption of Cu(II) and Ni(II) ions from aqueous solutions: Kinetics, thermodynamics and desorption studies. J Taiwan Inst Chem Eng (2014), http://dx.doi.org/10.1016/j.jtice.2014.02.022
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JTICE-861; No. of Pages 11 M. Kapur, M.K. Mondal / Journal of the Taiwan Institute of Chemical Engineers xxx (2014) xxx–xxx
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Table 5 Thermodynamic parameters for adsorption of Cu(II) and Ni(II) using coal dust.
DG8 (kJ/mol)
Cu(II) Ni(II)
20 8C
30 8C
40 8C
10.12 3.46
10.07 3.49
8.38 4.43
DH8 (kJ/mol)
DS8 (kJ/mol K)
35.30 9.619
0.0849 0.0207
Table 6 Isotherm constants for monocomponent adsorption on coal dust. Adsorbate
Copper(II) Nickel(II)
Freundlich constants
Redlich–Peterson constants
b (mg1)
Langmuir constants qo (mg/g)
Kf
n
KR (L/g)
aR (mg1)
B
0.066 0.0686
21.739 20.408
6.19 6.055
4.52 4.62
2 2
0.124 0.1547
0.951 0.915
Table 7 Comparison of the experimental and calculated qe values evaluated from the mono-component isotherm models. Co (mg/L)
Copper(II) 100 200 300 400 500 R R2
Ce (mg/L)
qe,exp (mg/g) Langmuir
Freundlich
R–P
10 33.32 116.56 209.96 290
9 16.68 18.34 19 21
8.64 14.94 19.23 20.27 20.65 0.99756 0.995 0.3415 0.019426
10.29 13.43 17.71 20.17 21.67 0.9193 0.845 1.0553 0.064505
9.48 14.87 18.72 19.96 20.54 0.99745 0.994 0.3052 0.017934
12.02 34.82 120.9 220 300
8.79 16.51 17.91 18 20
9.22 14.38 18.21 19.13 19.46 0.99724 0.994 0.42319 0.02401
10.36 13.03 17.05 19.41 20.75 0.8857 0.784 1.338 0.085809
9.5959 13.974 17.98 19.53 20.28 0.9940 0.988 0.653 0.039381
x2 RMSE Nickel(II) 100 200 300 400 500 R R2
qe,calc (mg/g)
x2 RMSE
does not follow ion exchange mechanism. To decide the rate controlling mechanism for adsorption by coal dust, intraparticle diffusion model was tested using Eq. (10) and it was evident that the plot of qt vs. t1/2 for both the metals did not pass through origin indicating there is some degree of film diffusion control and not only intraparticle diffusion is controlling. Thus it can be concluded that second order kinetics alongwith combined film and intraparticle diffusion is strongly followed by both the metal ions in a bi-solute system.
6.10. Monocomponent adsorption Adsorption data at equilibrium were analyzed in the range of 100–500 mg/L of solution for each component. The adsorbent dosage was fixed at 10 g/L for a pH 4. The parameters obtained through Langmuir, Freundlich and Redlich–Peterson isotherms for
6.9. Thermodynamic and determination of activation energy All the values of the thermodynamic parameters are listed in Table 5. Negative values of DG8 reveal that the mechanism of metal adsorption from the aqueous solutions is feasible and shows spontaneity for both the metals, thus supports the physical nature of adsorption. Exothermicity is indicated by the negative values of DH8 in both the cases while low degree of freedom of the system is reported by the negative values of DS8 due to strong adsorbate– adsorbent interaction. The value of Ea as calculated from the plot of ln k vs. 1/T comes out to be 19.50 kJ/mol for Cu(II) and 36.988 kJ/mol for Ni(II). Negative values suggest there is no energy barrier for adsorption and the reaction is exothermic [35].
Fig. 11. Single and binary adsorption of Cu(II) and Ni(II) on coal dust. The solid lines represent the fitting of data by Langmuir isotherms.
Please cite this article in press as: Kapur M, Mondal MK. Competitive sorption of Cu(II) and Ni(II) ions from aqueous solutions: Kinetics, thermodynamics and desorption studies. J Taiwan Inst Chem Eng (2014), http://dx.doi.org/10.1016/j.jtice.2014.02.022
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JTICE-861; No. of Pages 11 M. Kapur, M.K. Mondal / Journal of the Taiwan Institute of Chemical Engineers xxx (2014) xxx–xxx
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Distilled water 0.1N H2SO4 0.1N HNO3 0.1N HCl
100 90 80
% Desorption
70 60 50 40 30 20 10 0 Cu (II)
Ni (II)
Fig. 12. Desorption of Cu(II) and Ni(II) from respective metal loaded coal dust using different eluents.
each metal ion were given in Table 6. To quantify between the experimental and predicted values, statistical analysis using regression coefficient (R), correlation coefficient (R2) and error analysis using Chi-square (x2) and root mean square error (RMSE) were performed for all sets of isotherms. It was seen that for both the metals Langmuir model had better applicability, then followed by Redlich–Peterson model (Table 7). For mono component adsorption the metal loading capacity as calculated for Cu(II) was found to be 21.739 mg/g and for Ni(II) was 20.408 mg/g. In the case of R–P isotherm model the value of b lies between 0 and 1 for both the metals, which shows the favorable adsorption. Parameter estimation of both the models (Langmuir and R–P) shows that Cu(II) ions have more affinity than Ni(II) ions to get adsorbed on the coal dust surface for single solute containing solution. 6.11. Bi-component adsorption In a bi-component system, for studying the interaction of the two metals in the system, 1:1 ratio of the metal concentration was chosen in the range of 100–500 mg/L. Langmuir isotherm model was applied over the experimental data as demonstrated in Fig. 11. Adsorption capacities as obtained in case of single metal (Cu(II) or Ni(II)) system and in binary system (Cu(II) and Ni(II)) are presented in Table 8. Effect of ionic concentrations [36] on the adsorption process may be seen through the ratio of sorption capacity for a metal ion along with other ion (qmix) to the sorption capacity when present alone (qo) in the aqueous system. When qmix =qo > 1, the sorption capacity is enhanced by the presence of other metal ions or is said to be showing synergism; Table 8 Langmuir isotherm constants for single- and multi-component adsorption of Cu(II) and Ni(II) on coal dust. Metal ions
Cu(II) Ni(II) Cu(II) Ni(II)
System
Cu(II) alone Ni(II) alone Cu + Ni Cu + Ni
Langmuir constants qo (mg/g)
b (mg1)
R2
qmix/qo
21.739 20.408 8.403 7.352
0.066 0.068 0.044 0.037
0.995 0.994 0.991 0.994
0.386 0.360
qmix =qo ¼ 1, system shows no interaction between the species; qmix =qo < 1, there is suppression of the adsorption capacity due to the presence of other ion or shows antagonistic interaction of the two ions. Values of qmix =qo are shown in Table 8 which indicate that the adsorbing power of coal dust decreases for the aqueous system containing more than one metal. Study indicates the antagonistic behavior as there exists a competition between the Cu(II) and Ni(II) ions for the adsorbing sites. Moreover the coal dust has preference for Cu(II) ions even in the binary solution which may be the result of different electronegativity and ionic potential of the metal ions [37]. 6.12. Desorption study and adsorbent disposal Regeneration studies for metal loaded adsorbent were done using 0.1 N HCl, 0.1 N HNO3, 0.1 N H2SO4 and distilled water. Desorption efficiency of each eluent is plotted in Fig. 12. Cu(II) ions showed better desorption than Ni(II) ions for all the eluents. Distilled water had minimum efficiency of 32.1% for Cu(II) and 25% for Ni(II), respectively, while it was much better for 0.1 N H2SO4 (72.5% for Cu(II) and 67.12% for Ni(II)) and (73.3% for Cu(II) and 52.7% for Ni(II)) for 0.1 N HNO3. But 0.1 N HCl responded well as an adsorbent desorber which can be related to the higher acidity of HCl. It desorbed 99.63% of Cu(II) ions and 71.3% of Ni(II) ions. Finally 0.1 N HCl was selected as the regenerating eluent and it was tested over number of adsorption–desorption cycles. Metal loaded coal dust was dipped into 100 mL of 0.1 N HCl and it was agitated for an hour. The filtrate was tested for desorption efficiency of the eluent. Coal dust thus regenerated was again used for adsorption. Four times such adsorption–desorption cycles were run and the efficiencies are noted in Table 9. Results show that upto III cycle adsorption percentage touched 93.1 for Cu(II) and 87 for Ni(II) instead of 97% for Cu(II) and 100% for Ni(II) ions in the I cycle. But for IV cycle there was a considerable loss in adsorption alongwith a 10% loss in the mass of adsorbent. The studies indicate the reusability of the coal dust upto three stages. The metal solution obtained after desorption could be send back for industrial use and as the coal dust has high calorific value of about 4000 kcal/kg which provides it’s applicability of being used as a fuel.
Please cite this article in press as: Kapur M, Mondal MK. Competitive sorption of Cu(II) and Ni(II) ions from aqueous solutions: Kinetics, thermodynamics and desorption studies. J Taiwan Inst Chem Eng (2014), http://dx.doi.org/10.1016/j.jtice.2014.02.022
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JTICE-861; No. of Pages 11 M. Kapur, M.K. Mondal / Journal of the Taiwan Institute of Chemical Engineers xxx (2014) xxx–xxx Table 9 Data for adsorption–desorption cycles using 0.1 N HCl for coal dust regeneration. Cycles
I II III IV
% Adsorption
% Desorption
Cu(II)
Ni(II)
Cu(II)
Ni(II)
97 95.3 93.1 79.2
100 92.32 87 65.9
99.03 88.6 77.3 50.46
71.3 62.49 51.1 42.7
7. Conclusion Coal dust has proved its potential for simultaneous adsorption of Cu(II) and Ni(II) ions from aqueous solutions. From the experimental studies it has been observed that for a dosage of 10 g/L and metal concentration 10 mg/L almost 100% removal of ions was achieved at a pH 4 within a time span of 60 min. Metal adsorption was feasible and spontaneous and both the metals were found to follow pseudo-second order kinetics. Results were in good agreement with the Langmuir isotherms for single as well as multisolute system. Both the metals had competitive relation as single metal adsorption was better than bicomponent adsorption. In addition to this Cu(II) showed superior adsorption properties in comparison to Ni(II) ions. Thus coal dust can be used for individual and simultaneous removal of Cu(II) and Ni(II) from the solutions. Acknowledgment Authors are thankful to Indian Institute of Technology (Banaras Hindu University), India for extending all necessary facilities and supports to undertake the work. References [1] Chang Q, Wang G. Study on the macromolecular coagulant PEX which traps heavy metals. Chem Eng Sci 2007;62:4636–43. [2] Mirbagheri SA, Hosseini SN. Pilot plant investigation on petrochemical wastewater treatment for the removal of copper and chromium with the objective of reuse. Desalination 2005;171:85–93. [3] Rengaraj S, Joo CK, Kim Y, Yi J. Kinetics of removal of chromium from water and electronic process wastewater by ion exchange resins: 1200H, 1500H and IRN97H. J Hazard Mater 2003;102:257–75. [4] Korus I, Loska K. Removal of Cr(III) and Cr(VI) ions from aqueous solutions by means of polyelectrolyte-enhanced ultrafiltration. Desalination 2009;247: 390–5. [5] Heidmann I, Calmano W. Removal of Zn(II), Cu(II), Ni(II), Ag(I) and Cr(VI) present in aqueous solutions by aluminium electrocoagulation. J Hazard Mater 2008;152:934–41. [6] Bhatnagar A, Minocha AK. Biosorption optimization of nickel removal from water using Punica granatum peel waste. Colloids Surf B 2010;76:544–8. [7] Wang S, Peng Y. Natural zeolites as effective adsorbents in water and wastewater treatment. Chem Eng J 2010;156:11–24. [8] Naiya TK, Bhattacharya AK, Das SK. Adsorption of Cd(II) and Pb(II) from aqueous solutions on activated alumina. J Colloid Interface Sci 2009;333:14–26. [9] Wang H, Kang J, Liu H, Qu J. Preparation of organically functionalized silica gel as adsorbent for copper ion adsorption. J Environ Sci 2009;21:1473–9.
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Please cite this article in press as: Kapur M, Mondal MK. Competitive sorption of Cu(II) and Ni(II) ions from aqueous solutions: Kinetics, thermodynamics and desorption studies. J Taiwan Inst Chem Eng (2014), http://dx.doi.org/10.1016/j.jtice.2014.02.022