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Abstract

The use of bottom ash of expired drugs incineration for removal of Cu(II) ions from aqueous solution has been investigated. Analytical techniques have been employed to find characteristics of adsorbent materials. The removal of Cu(II) was conducted in batch system, and the effects of pH, adsorbent dosage, initial concentrations of copper ions, and contact time on adsorption efficiency were studied. Optimum adsorption was achieved at a pH 5 and equilibrium was established within 15 min of the process. The equilibrium adsorption data were analyzed using eight adsorption isotherm models: Langmuir, Freundlich, Temkin, Redlich–Peterson, Dubinin–Radushkevich, Toth, Harkin–Jura and Halsey isotherms. The energy value obtained by application of Dubinin–Radushkevich model was 2.593 kJ/mol indicating that physisorption was the dominant mechanism of sorption. The values of the correlation coefficient (R²) of the isotherms gave the best fit (>0.99) with the Langmuir, Toth, and Redlich–Peterson isotherms. The adsorption capacity (q_m) from the Langmuir isotherm for Cu(II) was found as 13.335 mg/g. The equation constant n of Toth isotherm model is found to be close to 1 (0.945), confirming that the adsorbent studied presents homogeneous surface under conditions used. It is concluded that bottom ash of expired drugs incineration can be used as an effective adsorbent for removing Cu(II) from aqueous solution.

Keywords

Bottom ash expired drugs adsorption water treatment isotherm model

Introduction

The presence of heavy metals in water courses constitutes one of the most serious pollution problems. Nondegradable and very toxic, they can affect the quality of water supply and cause many problems on aquatic life. Even at low concentrations, these elements can be accumulated through the food chain and affect animals, plant life, and therefore human health. Copper is one of these elements which constitute a real health hazard. Though essential for human health, it can be very harmful above specified concentrations limits, causing anemia, kidney damage, stomach intestinal distress, coma, and eventual death (Kanda et al., 2003). Copper is also considered like irritant to the skin giving dermatitis, itching, and keratinization of the sole of feet and hands (Sitting, 1981). This trace element can be responsible for “pink disease” among infants when a concentration of 0.8 mg/l in water is consumed and is carcinogenic to animals. Once copper is released in water it can eliminate all fish as well as marine plants for miles downstream from the source. This metal is widespread in the environment because it is released naturally and mainly through human activity. It is used as an excellent conductor of electricity and in all gauges of wires for circuits. It is also utilized in electroplating, in paints, in analytical reagents, in pigments, in fertilizer industry, and in many other fields (Gupta et al., 2000). In addition, copper mining wastes as well as acid mine drainage contributes widely to copper release. Copper can also be found in food as contaminant, for example, in mushrooms, liver, shellfish, chocolate, and nuts (Nuhoglu et al., 2003). According to the Agency for Toxic Substances and Disease Registry (U.S. Department of Health and Human Services, Public Health service Atlanta, 1999), the maximum recommended concentration of Cu(II) for drinking water by Environment Protection Agency is around 1.0 mg/l, therefore efforts must be deployed to meet this requirement. Several treatment technologies such as solvent extraction, ion exchange, and precipitation have been suggested and employed to remove heavy metals from aqueous solution. But these technologies are not only expensive, but they also create another problem with metal-bearing sludge (Brady et al., 1994). Adsorption is one of the most cost-effective treatment technologies, but the adsorbents used can be very expensive, thus cheap and efficient material are needed to be used as suitable adsorbents. In this paper, efforts have been made to investigate the use of bottom ash of expired drugs incineration (BAEDI) as an economical and available adsorbent for removing copper from aqueous solutions. As a first step, characterization of the BAEDI was carried out in order to examine the possibility of its use as adsorbent. Later the adsorption capacity was evaluated under various conditions of pH, contact time, copper concentration, and BAEDI dosage. The adsorption isotherms were studied to explain the probable mechanism of adsorption and to provide several information such as maximum sorption capacity, energy of sorption, homogeneity/heterogeneity, affinity between sorbent and adsorbent that can be useful for the comprehension of the process taking place.

Several kinds of bottom ash of waste incineration have been suggested as adsorbent in sorption process but the one we propose in this study present the particularity to be nearly free from heavy metals.

Material and methods

Adsorbent and characteristics

The expired drugs (amoxicillin, paracetamol, voltarene) were incinerated in Nar 500 (ECFERAL Algeria) incinerator under a temperature of approximately 850℃. BAEDI sample was utilized as an adsorbent in this study. Conventional analytical techniques were employed to ascertain the characteristics of the adsorbent. The moisture content was determined by weighing 5 g of BAEDI. The sample was placed in the oven and heated for 24 h at a constant temperature of 105℃. Once removed the sample was put rapidly into a desiccator in order to avoid moisture uptake from atmosphere. The sample was reweighed. The loss of mass constitutes the amount of moisture content of the BAEDI. Bulk density was determined according to Archimedes’s principle (Toshiguki and Yukata, 2003) using 5 cm³ pycnometer. pH was measured using a pH meter (HANNA pH211). The point of zero charge (PZC) was determined by the use of the solid addition method (Oladoja and Aliu, 2009). Forty-five milliliters of (0.01 M) NaCl solution was transferred into a series of 50 ml conical flasks. The pH values of the solution were adjusted from 2 to 10 by adding either (0.1 M) NaOH or (0.1 N) HNO₃. After making the total volume of the solution exactly 50 ml in each flask by adding NaCl, the accurate pH₀ values of the solutions were noted. BAEDI (0.15 g) was added to each flask. The suspension was then agitated for 48 h. The pH values of the supernatant liquid were noted. The difference (ΔpH = pH_f − pH_i) between the initial pH (pH_i) and final pH (pH_f) values was plotted against the pH_i. The point of intersection of the resulting curve with pH_i gave the PZC. All chemicals and reagents used in this study were supplied by Panreac Barcelona Spain. The specific surface of the BAEDI was measured by BET method at 77 K using a Micromeritics ASAP 2010 (BET surface area measurements) apparatus. Chemical composition of the BAEDI was analyzed by X-ray fluorescence (XRF-40 Philips). FTIR spectra of the samples were obtained on PerkinElmer Model System 2000 using KBr pellet method.

Preparation of synthetic stock solution

A total of 3.96 g of (CuSO₄, 5H₂O) 99% was dissolved in 1 l of distilled water to prepare 1000 mg/l of copper stock solution. Samples of different concentrations were prepared from this stock solution by appropriate dilutions. The pH values of the solution were adjusted from 3 to 8 by adding either (0.1 M) HNO₃ or NaOH (0.1 M). Batch adsorption experiments were carried out by shaking a series of bottles containing various amounts of BAEDI and copper at different pHs. When the adsorption was realized, the ash particles were separated from suspensions by filtration and the residual concentration of copper was determined using an Atomic Absorption Spectrometer PERKIN ELMER A700 at a wavelength of 324.8 nm.

Experimentation

Batch adsorption tests were carried out to study the effect of various parameters on the adsorption efficiency of copper ions on BAEDI. Parameters such as pH of the mixed solution, quantity of the adsorbent, initial quantity of copper ion, and agitation time were studied. The amount of Cu(II) adsorbed per unit of BAEDI (milligram copper per gram BAEDI) was calculated according to a mass balance on the copper concentration (equation (1))

q_{e} = [(C_{i} - C_{e}) * V] / m

(1)

where C_i and C_e were the initial and final concentrations of copper in the solution. V is the volume of the solution used to acquire the experimental adsorption isotherms and m is the mass of adsorbent (in gram) used. The experimental procedure for the study of each parameter is discussed below.

Effect of pH of the aqueous solution

To study the influence of pH on copper adsorption, 100 ml of the concentration (50 mg/l) was taken in each of conical flask. A total of 0.2 g of BAEDI was added to each solution. The pH values of the solution were adjusted to 3, 4, 5, 6, 7, and 8 and the flasks were further agitated until equilibrium was obtained. At the end of mixing, the BAEDI particles were separated from suspensions by filtration. In addition to adsorption tests, a set of blank tests were conducted without BAEDI in order to evaluate the removal by metal hydroxide precipitation at various pHs (5–11). The initial concentration of these aqueous solutions was 50 mg/l and the final concentration was measured by atomic absorption spectroscopy.

Effect of dose of adsorbent

The adsorption of Cu(II) on BAEDI was studied by changing the quantity of BAEDI in the test solution while keeping the initial Cu(II) concentration (50 mg/l) and temperature as constant at equilibrium time (0.1–0.4 g) of adsorbent were added to 100 ml of copper solution 50 mg/l at pH = 5.

Effect of initial copper concentration

The adsorption experiments were carried out in the copper concentration range of 5–1000 mg at pH = 5 and 3 g/l of BAEDI.

Effect of contact time

The effect of contact time on removal of copper ions was studied for a period of 70 min. A total of 0.3 g of the BAEDI was added to different conical flasks containing 100 ml of 50 mg/l solution at optimal value of pH. The flasks were closed and placed in a rotary shaker, and for each of the different contact times chosen (1, 2.5, 3.5, 5, 6.5, 9, 10, 12, 13.5, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 70 min) the content of each flask was filtered and analyzed.

Adsorption isotherms

The equilibrium retention of adsorbate onto adsorbent is well described by mathematical models based on some assumptions related to the type of coverage, the homogeneity and heterogeneity of the solid surface, and the interaction between adsorbate species. These models called adsorption isotherm may explain the probable mechanism of adsorption. In the present study, equilibrium data were analyzed using the Langmuir, Freundlich, Temkin Redlich–Peterson, Dubinin–Radushkevich (D–R), Toth, Harkin–Jura, and Halsey isotherms.

Langmuir adsorption isotherm

The Langmuir isotherm (Langmuir, 1916) based upon three assumptions, sorption is limited to monolayer coverage, all surface sites are identical and can accommodate only one adsorbed atom, and interaction forces between adsorbed atoms are negligible. The Langmuir equation may be written as

q_{e} = q_{m} \frac{{bC}_{e}}{1 + {bC}_{e}}

(2)

Equation (2) can be expressed in its linear form as

\frac{C_{e}}{q_{e}} = \frac{1}{q_{m}} c_{e} + \frac{1}{q_{m} b}

(3)

where q_e is the equilibrium amount adsorbed per unit mass of BAEDI (mg/g), C_e is the equilibrium concentration of copper (mg/l), q_m (mg/g) is the maximum amount of adsorbed copper per unit mass of BAEDI corresponding to complete coverage of the adsorptive sites, and b (l/mg) is the Langmuir constant related to the energy of adsorption.

A plot of (C_e/q_e) versus (C_e) gives a straight line, if the sorption process is described by the Langmuir isotherm equation. The values of q_m and b are obtained from the slope and intercept of the straight line plot.

Furthermore, favorability of adsorption of copper on BAEDI was tested using the essential characteristics of the Langmuir isotherm model, expressed in terms of a dimensionless constant called separation factor R_L, which is defined by the following relationship

R_{L} = \frac{1}{1 + {bC}_{0}}

(4)

where C₀ (mg/l) is initial metal ion concentration. The R_L value for the adsorption of Cu(II) on BAEDI indicates the adsorption nature to be either unfavorable if R_L > 1, linear if R_L = 1 favorable if 0 < R_L < 1 (Dabhade et al., 2009).

Freundlich adsorption isotherm

This model is used to describe the adsorption occurring onto heterogeneous surface (Hutson and Yang, 2000). It is described by the empirical equation proposed by Freundlich

q_{e} = k_{f} C_{e}^{1 / n}

(5)

where k_F and n are Freundlich isotherm constants. k_F (l/g) is an approximate indicator of adsorption capacity. k_F value increases with adsorption intensity, while (n) indicates the favorability of adsorption (Vaishnav et al., 2012). If n values lies between 1 and 10 the adsorption is said favorable (Chantawong et al., 2003). Linearizing equation (4) we have

k_F and n are obtainable from the plots of ln q_e versus ln C_e.

The Temkin isotherm

Temkin and Pyzhev (1940) suggested that because of indirect adsorbate/sorbate interactions the heat of adsorption of all the atoms adsorbed would linearly decrease with coverage. The Temkin isotherm may be written as

q_{e} = \frac{RT}{b} \ln (A_{T} C_{e})

(7)

Equation (7) can be expressed in its linear form as

q_{e} = B \ln A_{T} + B \ln C_{e}

(8)

where

B = \frac{RT}{b}

A_T is Temkin isotherm equilibrium binding constant (l/g), b is Temkin isotherm constant related to heat of sorption (J/mol), R is universal gas constant (8.314 J/mol/K), T is temperature at 298 K. The plot of (q_e) versus (ln C_e) enables the determination of the isotherm constants.

Redlich–Peterson isotherm

Redlich–Peterson model, unlike the Freundlich and Langmuir isotherms, can be applied to both heterogeneous and homogeneous system. It is considered as a compromise between these two models (Jossens et al., 1978). The R–P isotherm can be applied in the following equation

q_{e} = \frac{K_{RP} C_{e}}{(1 + a_{RP} C_{e}^{β})}

(9)

Equation (9) can be expressed in its linear form as

\frac{C_{e}}{q_{e}} = \frac{1}{K_{RP}} + \frac{\propto RP}{K_{RP}} C_{e}^{β}

(10)

where K_RP (l/g), α_RP (l/mg), and β are Redlich–Peterson constants. The value of β lies between 0 and 1. The Redlich–Peterson isotherm constants can be determined from the plot between (C_e/q_e) versus (C_e^β). However, the application is more complex in this term since the isotherm incorporates three unknown parameters α_RP, K_RP, and β. Therefore, a minimization procedure is adopted to obtain the maximum value of coefficient of determination R², between the theoretical data for q_e obtained from the linearized form of Redlich–Peterson isotherm equation and the experimental data.

D–R isotherm

The D–R model (Kilislio and Bilgin, 2003) can explain the physical and chemical characteristics of adsorption with its mean free energy. D–R model has commonly been applied in the following equation

ln q_{e} = ln q_{m} - β ɛ^{2}

(11)

where β is the activity coefficient related to mean adsorption energy (mol²/J²) and ɛ is the Polanyi potential

ɛ = RTln (1 + \frac{1}{C_{e}})

(12)

The mean adsorption energy E (KJ/mol) can be obtained by using the expression

E = \frac{1}{\sqrt{2 β}}

(13)

The adsorption process is said to be dominated by physisorption for the energy values less than 8 KJ/mol, by chemical ion exchange mechanism for those between 8 and 16 kJ/mol and by chemical particle diffusion for the greater than 16 kJ/mol (Bering et al., 1972).

Toth isotherm

Toth model is often useful for describing heterogeneous systems. Toth equation describes well many systems with submonolayer coverage (Artur et al., 2003). It has the form where K_L and n are the equation constants, and C_e is the equilibrium concentration. It is clear that for n = 1 this isotherm reduces to the Langmuir adsorption isotherm equation, therefore the parameter n is said to characterize the system heterogeneity. If it deviates further away from unity, the system is said to be more heterogeneous.

The Toth isotherm may be rearranged to give a linear transform

ln \frac{q_{e}^{n}}{q_{m}^{n} - q_{e}^{n}} = nln K_{L} + nln C_{e}

(15)

The values of parameters of Toth model can be evaluated by nonlinear curve fitting method using Sigma-plot software.

Harkin–Jura isotherm

The Harkin–Jura (Akmil, 2006) equation accounts for multilayer adsorption and can be explained by the existence of a heterogeneous pore distribution. The Harkins–Jura isotherm can be expressed in its linear form

\frac{1}{q_{e}^{2}} = \frac{B}{A} - \frac{1}{A} log C_{e}

(16)

where A and B are Harkin–Jura isotherm parameters.

Frenkel–Halsey–Hill isotherm

This model is suitable for multilayer adsorption and heteroporous adsorbents. The Halsey adsorption isotherm can be given as

q_{e} = Exp (\frac{\ln K_{H} - \ln C_{e}}{n})

(17)

The Frenkel–Halsey–Hill isotherm (Halsey, 1948) can be also expressed in its linear form

\ln q_{e} = \frac{1}{n} \ln K - \frac{1}{n} \ln C_{e}

(18)

Results and discussion

Characterization of adsorbent

The physical and chemical characteristics of BAEDI are presented in Table 1. The results of the zero point of charge of BAEDI which is the point of intersection of the resulting curve with pH_i (pH_pzc = 7.2) is shown in Figure 1. It was concluded that at pH less than 7.2 the surface of BAEDI is predominated by positive charges while at pH greater than 7.2 the surface is predominated by negative charges (Koel Banerjee, 2012). Thus, the negative charge density on the surface of the adsorbent increases with increasing pH beyond the PZC, resulting in enhancement in the copper ions uptake.

Table 1.

Major physical properties of BAEDI from drug incineration.

Properties	Value
% Moisture content	3.44
Bulk density (g/cm³)	1.134
pH	10.14
pH_pzc	7.2
Specific area (m²/g)	18.42

Figure 1.

Point of zero charge for BAEDI. BAEDI: bottom ash of expired drugs incineration.

The elemental composition of BAEDI is presented in Table 2. The main elements found in BAEDI include carbon and oxygen; the BAEDI contained metals calcium (Ca), titanium (Ti), aluminum (Al), magnesium (Mg), silicate (Si), potassium (K), sodium (Na); the main species expected to form anions are sulfur (S), chlorine (Cl), and phosphorus (P). No presence of potential heavy metals such as Pb, Cd, and Ni was observed and this can be attributed to the absence of these toxics elements in the expired drugs.

Table 2.

Elemental analyses of BAEDI.

Element	Content (%)
C	53.161
O	31.06
Na	0.176
Mg	0.425
Al	1.703
Si	0.527
P	0.498
S	0.053
Cl	0.032
K	0.440
Ca	7.873
Ti	4.038

BAEDI: bottom ash of expired drugs incineration.

The FT-IR technique was employed to identify some important functional groups, which are capable of adsorbing metal ions (Chandler, 1997; Meima and Comans, 1999). The FT-IR spectrum of BAEDI is shown in Figure 2. The main peaks identified are placed around 3472, 1611, 1444, 1000, and 500 cm ^− 1.

Figure 2.

FT-IR spectrum of BAEDI. BAEDI: bottom ash of expired drugs incineration.

The bands around 3472 and 1611 cm ^− 1 are associated to stretching and deformation vibrations of OH and H–O–H groups. The peak at around 1444 cm ^− 1 might be assigned to the presence of O–C–O stretching vibration in carbonate. The peak around 1000 cm ^− 1 is attributed to asymmetric stretching vibrations of Si–O/Al–O bonds. The peak around 500 cm ^− 1 is caused by the in-plane bending vibration of Si–O–Si (Fernandez et al., 2004; Han et al., 2010; Hanif et al., 2009; Johnson et al., 1995; Moller, 2004; Rendek et al., 2007). FTIR studies reveal that several function groups which are able to bind with heavy metal ions, in particular Cu(II) ions, are present in BAEDI.

Batch studies

Effect of pH

The percentage removal of copper from the aqueous solution is strongly affected by the pH of the solution as illustrated in Figure 3.

Figure 3.

Effect of pH solution on the removal of copper (1) with use of bottom ash and (2) without use of bottom ash.

Figure 4.

Effect of pH copper adsorption capacity.

As pH increased from 3 to 8, it can be expected that the BAEDI surface became more negatively charged. With increasing pH beyond the PZC the negative charge density on the surface of the adsorbent increased, resulting in enhancement in the removal of copper. However, as can be seen in Figure 3 copper ions precipitation began from pH 6. Theoretically when the ion product exactly equals the value of solubility product constant (Ksp) precipitation will start. For a solution of 50 mg/l copper ion precipitation starts at pH equal to 5.72. The curves observed in Figure 3 exhibited a distinct improvement in copper removal when BAEDI was used. The removal of copper from the aqueous solution passed from 59 to 99% by using BAEDI at pH 8. This is due to the availability of more negatively charged surface facilitating greater copper removal by electronic attraction mechanism. At lower pH values (3 to 5) no precipitation occurred, removal was totally assured by adsorption, and rose to more than 60%. The major mechanism responsible for metal uptake in this range may be ion exchange and electronic attraction. Though adsorption may give best results at pH values greater than 7.2 as illustrated in Figure 4, we opted for the pH value of 5 to avoid precipitation.

Effect of adsorbent dose

The percent removal of copper II increased with the increase in adsorbent dosage due to the increase in adsorbent surface area as shown in Figure 5. The maximum removal rate of 80% occurred at the concentration of 3 g/l of adsorbent. After this point, further increase in BAEDI dosage brought no increase in percent removal. This may due to the overlapping of the adsorption sites as a result of overcrowding of adsorbent particles or else to the screening effect of the outer layer imposed by the high adsorbent dosage, thereby shielding the active sites from metal (Tumain et al., 2008). In certain cases, the excess particles can be deposited on the walls of the container creating heterogeneity in the solution. Thus, no contact with metal solution occurred.

Figure 5.

Effect of BAEDI dose on copper removal. BAEDI: bottom ash of expired drugs incineration.

Effect of initial copper concentration

The result on the effect of initial copper ions concentration in the solution on the rate of metal adsorption on BAEDI is shown in Figure 6.

Figure 6.

Effect of initial copper concentration on adsorption capacity.

First an increase in adsorption capacity with increase in metal ion concentration was observed. This may be explained by the presence of more copper ions in solution available for binding onto the active sites of the BAEDI. Subsequently, the adsorption reached to a saturation value, this can be due to the fact that all adsorbents have a limited number of active sites and at higher concentrations the active sites became saturated (Barbosa et al., 2000).

Effect of agitation time

As shown in Figure 7 adsorption was a function of time. It was noticed that in the initial stage the adsorbed concentrations vary considerably and at some point of time, the rate of adsorption became constant.

Figure 7.

Effect of contact time on copper adsorption capacity.

The initial rapid uptake can be explained by the presence of large number of vacant sites, as time proceeds the adsorption concentration reached a constant value beyond which no more copper ion was removed from solution. This is due to the accumulation of metal ions on the vacant sites. The adsorption attained a state of dynamic equilibrium between the amount of the copper ions desorbing from the BAEDI and the amount of metal being adsorbing onto the same adsorbent (Bello et al., 2010). The equilibrium was reached rapidly after 15 min as this may be interesting for practical application of adsorption in wastewater treatment.

Adsorption isotherms

The adsorption isotherm was obtained by plotting the weight of copper adsorbed per unit weight of BAEDI (q_e) against the equilibrium concentration of the solute in solution at constant temperature (298 K) and pH = 5 (Figure 8).

Figure 8.

Isotherm adsorption of copper onto BAEDI. BAEDI: bottom ash of expired drugs incineration.

The Langmuir, Freundlich, Temkin, Redlich–Peterson, D–R, Toth, Harkin–Jura and Halsey isotherms were applied in this study. The values of model parameters are evaluated using Sigma plot software (version 12).

The isotherm models and correlation coefficients for each model are summarized in Table 3.

Table 3.

Value of constants for each isotherm model used in the studies.

Isotherm model	Parameter	R²
Langmuir	b (l/mg) = 0.463	0.997
	qm (mg/l) = 13.33
	R_L = 0.041
Freundlich	n = 3.300	0.929
Freundlich	k_F = 4.071	0.929
Temkin	B = 5.835	0.946
	b_T (J/mol) = 424.401
	At (l/g) = 0.626
Redlich–Peterson (R–P)	ß = 0.945	0.999
	α_RP = 1.023
	K_RP = 1046
Dubinin–Radushkevich (D–R)	ß = 0.0744	0.7017
	E (kJ/mol) = 2.593
	q_m (mg/g) = 12.838
Toth	K = 0.4768	0.999
	n = 0.945
	q_m (mg/g) = 13.029
Harkins–Jura	A = 4.2918	−0.836
Harkins–Jura	B = 1.8884	−0.836
Frenkel–Halsey–Hill	n = −3.4467	0.907
Frenkel–Halsey–Hill	K = 0.0067	0.907

It is clear from Table 3 that the best model fit was achieved using a Langmuir, Redlich–Peterson, and Toth isotherm. As can be seen in Table 3 the value of correlation coefficient obtained for these three models (R² > 0.99) showed that these models are suitable to describe the adsorption of copper on BAEDI. From the data calculated in Table 3, the value of the maximum monolayer coverage (q_m) adsorption from Langmuir model was very close to the experimental value. The separation factor of Langmuir model R_L was greater than 0 but less than 1 indicating favorable adsorption. Redlich–Peterson model approximates Langmuir model at low solute concentration. The equation constant n of Toth isotherm model is found to be close to 1 (0.945) and this value confirms that the adsorbent studied presents homogeneous surface under conditions used, for this value Toth model is nearly reduced to the Langmuir adsorption isotherm equation. The D–R approach was applied to distinguish the physical and chemical adsorption of metal ions on the basis of its mean free energy E per molecule of adsorbent. The energy value obtained according to this model (2.593 kJ/mol) was less than 8 kJ/mol. This result indicates that the adsorption of copper ions onto BAEDI follows physisorption process. While the correlation coefficient in D–R model is comparatively small, the adsorbent capacity according to this model (12.838 mg/g) remains very close to the experimental value.

Relatively low values of correlation coefficient were obtained for the Harkin–Jura and Halsey isotherms, the models, unlike Langmuir isotherm, are suitable for heterogeneous surface of adsorbent, thus confirming the homogeneous nature of the adsorbent surface.

The maximum adsorption capacity values of various low-cost adsorbents have been reported in the literature. A comparison between these values and the one found in the present study is listed in Table 4.

Table 4.

The maximum adsorption capacities of various low-cost adsorbent for copper adsorption.

Author/year	Adsorbent	Capacity q_m
Tumain et al. (2008)	Elaeis guineensis kernel activated carbon	3.9293 mg/g
Abbas (2009)	Granular activated carbon	5.845 mg/g
Dinu and Dragan (2010)	Novel chitosan/clinoptilolite composite	11.32 mmol/l
Visa and Duta (2010)	Fly ash/TiO₂	7.8989–24.03 mg/g
Onundi et al. (2010)	Palm shell activated carbon	1.581 mg/g
Mohan and Gandhimathi (2009)	Coal fly ash	48 µg/g
Wang et al. (2016)	Bottom ash of municipal waste incineration converted to sorbent material	24 mg/g
Rahman and Islam (2009)	Maple wood sawdust	9.51 mg/g
Sh. Shahmohammadi et al. (2011)	Kaolinite	4.42 mg/g
Visa and Duta (2010)	Fly ash	12.78 mg/g
Shahmohammadi-Kalalagh and Babazadah (2014)	Kaolinite	4.625
Malarvizhi and Santhi (2013)	Hydrochloric acid, hydrofluoric acid-treated lignite fly ash	6.95 mg/g8.4 mg/g
Farouk and Yousef (2015)	Natural biosorbent	17.189
This study	Bottom ash of expired drugs incineration (BAEDI)	13.33 mg/g

It can be observed that the BAEDI shows reasonable capacity and can be used as a good and inexpensive adsorbent for removal of copper II ions from aqueous solution.

Conclusion

In this study, tests were performed to evaluate the use of bottom ash of some expired drug incineration (amoxicillin, paracetamol, voltarene) as an adsorbent for copper ions. In the first stage of the study, the characterization of the adsorbent was done. No presence of potential heavy metals was observed. The main elements found were carbon and oxygen. The effects of operating parameters such as pH, contact time, sorbent dose, and initial metal dose on copper sorption capacity of bottom ash were studied. The results suggest that the adsorption was influenced by pH solution, the concentration of the copper ions, dosages of adsorbents, and contact time. The optimum pH was 5 to avoid precipitation. It was found that adsorption of copper onto BAEDI is a very rapid process with equilibrium time of 15 min.

Adsorption equilibrium was described by the Langmuir isotherm as well as Toth and Redlich–Peterson models. It can be concluded that the BAEDI can be used for removal of copper ions from solutions with maximum metal uptake of 13.33 mg/g.

Adsorption of Cu(II) ions by BAEDI is an economically feasible technique for removing metal ions from a solution. The adsorbent is available and inexpensive. Furthermore, the recovery of ash from any kind of waste incineration should be encouraged in order to preserve natural resources, and the feature of this particular ash is the presence of less heavy metals in its composition. It is suspected that better results can be obtained with other heavy metals for which precipitation occurs beyond pH 7.2, a choice of greater value of pH can be made so that surface will be more negatively charged, thus resulting in the enhancement of metal removal.

Footnotes

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

References

Agency for Toxic Substances and Disease Registry (ATSDR) (1999) Toxicological Profiles. Atlanta: U.S. Department of Health and Human Services, Public Health Service.

Akmil

(2006) Applicability of the various adsorption models of three dyes adsorption onto activated carbon prepared waste apricot. Journal of Hazardous Materials 135: 232–241.

Artur

et al. (2003) Developing the solution analogue of the Toth adsorption isotherm equation. Journal of Colloid and Interface Science 266: 473–476.

Barbosa

VFF

MacKenzie

KJD

Thaumaturgo

(2000) Synthesis and characterization of materials based on inorganic polymers of alumina and silica: Sodium polysialate polymers. The International Journal of Inorganic Materials 2: 309–317.

Bello

et al. (2010) Kinetic and equilibrium studies of methylene blue removal from aqueous solution by adsorption on treated sawdust. Macedonian Journal of Chemistry and Chemical Engineering 29: 77–85.

Bering

Dubinin

Serpinsky

(1972) On thermodynamics of adsorption in micropores. Journal of Colloid and Interface Science 38: 185–194.

Brady

Stoll

Duncan

(1994) Biosorption of heavy metal cations by non-viable yeast biomass. Environmental Technology 15: 419–428.

Chandler

(1997) Municipal Solid Waste Incinerator Residues. Studies in Environmental Sciences, Amsterdam: Elsevier Science, pp. 67.

Chantawong

Harvey

Bashkin

(2003) Comparison of heavy metal adsorptions by thai kaolin and ball clay. Water Air and Soil Pollution 148: 111–125.

10.

Dabhade

et al. (2009) Adsorption of phenol on granular activated carbon from nutrient medium: Equilibrium and kinetic study. International Journal of Environmental Research 3(4): 557–568.

11.

Dinu

Dragan

(2010) Evaluation of copper (II) cobalt (II) and nickel (II) ions removal from aqueous solution using a novel chitosan/chinoptilolite composite: Kinetics and isotherms. Chemical Engineering Journal 160: 157–163.

12.

Farouk

Yousef

(2015) Equilibrium and kinetics studies of adsorption copper (II) on natural biosorbent. International Journal of Chemical Engineering and Application 6(5): 319–324.

13.

Fernandez

et al. (2004) Investigation of accelerated carbonation for the stabilization of municipal solid waste incinerator ashes and the sequestration of CO2. Green Chemistry 6: 428–436.

14.

Gupta

et al. (2000) Microbial biosorbents meeting challenges of heavy metal pollution in aqueous solutions. Current Science 78: 967–973.

15.

Halsey

(1948) Physical adsorption on nonuniform surfaces. The Journal of Chemical Physics 16: 931–937.

16.

Han

et al. (2010) Characterization of modified wheat straw, kinetic and equilibrium study about copper ion and methylene blue adsorption in batch mode. Carbohydrate Polymer 79: 1140–1149.

17.

Hanif

Bhatti

Hanif

(2009) Removal and recovery of Cu(II) And Zn(II) using immobilized Mentha Arvensis distillation waste biomass. Ecological Engineering 35: 1427–1434.

18.

Hutson ND and Yang RT (2000) Theoretical basis for the Dubinin-Radushkevitch (D-R) adsorption isotherm equation. Adsorption 3(3): 189–195.

19.

Johnson

Brandenberger

Baccini

(1995) Acid neutralizing capacity of municipal waste incinerator BAEDI. Environmental Science and Technology 29: 142–147.

20.

Jossens

et al. (1978) Thermodynamics of multi-solute adsorption from dilute aqueous solution. Chemical Engineering Science 33: 1097–1106.

21.

Kanda

Abu Al-Rub

Al-Dabaybeh

(2003) The aqueous adsorption of copper and cadmium ions sheep manure. Adsorption Science and Technology 21: 501–509.

22.

Kilislioqlu

Bilgin

(2003) Thermodynamic and kinetic investigation of uranium adsorption on Amberlite IR-118-H Resin. Applied Radiation and Isotopes 58: 155–160.

23.

Koel Banerjee

(2012) A novel agricultural waste adsorbent, watermelon shell for the removal of copper from aqueous Solutions. Iranica Journal of Energy and Environment 3(2): 143–156.

24.

Langmuir

(1916) The constitution and fundamental properties of solids and liquids. Journal of the American Chemical Society 38: 2221–2295.

25.

Malarvizhi

Santhi

(2013) Adsorption of copper (II) ions from aqueous solution by hydrochloric acid, hydrofluoric acid treated lignite fly ash. International Journal of Engineering Research and Application 3(5): 890–902.

26.

Meima

Comans

RNJ

(1999) The leaching of trace elements from municipal solid waste incinerator BAEDI at different stages of weathering. Applied Geochemistry 14: 159–171.

27.

Mohan

Gandhimathi

(2009) Removal of heavy metal ions from municipal solid wastes leachate using coal fly ash as adsorbent. Journal of Hazardous Materials 169: 351–359.

28.

Moller

(2004) Sampling of heterogeneous BAEDI from municipal waste incineration plants. Chemometrics and Intelligent Laboratory Systems 74: 171–176.

29.

Nuhoglu

Oguz

(2003) Removal of copper(II) from aqueous solutions by adsorption on the cone biomass of Thuja orientalis. Process Biochemistry 38: 1627–1631.

30.

Oladoja

Aliu

(2009) Snail shell as coagulant aid in the alum precipitation of malachite green from aqua system. Journal of Hazardous Materials 164: 1496–1502.

31.

Onundi

et al. (2010) Adsorption of copper, nickel and lead ions from synthetic semiconductor industrial waste water by shell active carbon. International Journal of Environment Science and Technology 7(4): 751–758.

32.

Rahman MS and Islam MR (2009) Effects of pH on isotherms modeling for Cu(II) ions adsorption using maple wood sawdust. Chemical Engineering Journal 149: 273–280.

33.

Rendek

Ducom

Germain

(2007) Influence of waste input and combustion technology on municipal solid waste incineration BAEDI quality. Waste Management 27: 1403–1407.

34.

Shahmohammadi-Kalalagh

Babazadah

(2014) Isotherms of the sorption of zinc and copper onto kaolinite: comparison of various errors functions. International Journal of Science and Technology 11: 111–118.

35.

Sitting

(1981) Handbook of Toxic and Hazardous Chemicals, Park Ridge, NJ: Noyes Publications.

36.

Temkin

Pyzhev

(1940) Recent modifications to Langmuir isotherms. Acta Physiochim URSS 12: 217–222.

37.

Toshiguki

Yukata

(2003) Pyrolysis of plant, animal and human wastes. Physical and chemical characterization of the pyrolytic product. Bioresource Technology 90(3): 241–247.

38.

Tumain

et al. (2008) Adsorption of copper from aqueous solution by Elaeis guineensis kernel active carbon. Journal of Engineering Science and Technology 3(2): 180–189.

39.

Vaishnav

et al. (2012) Adsorption studies of Zn (II) ions from wastewater using Calotropis procera as an adsorbent. Research Journal of Recent Sciences 1: 160–165.

40.

Visa

Duta

(2010) Adsorption behavior of cadmium and copper compounds on a mixture fly ash/TiO₂. Revue Roumaine de Chimie 55(3): 167–173.

41.

Wang

Huang

Lau

(2016) Conversion of municipal solid waste incineration bottom ash to sorbent material for pollutant removal from water. Journal of Taiwan Institute of Chemical Engineering 60: 275–286.

Adsorption of copper (II) ions from aqueous solution using bottom ash of expired drugs incineration

Abstract

Keywords

Introduction

Material and methods

Adsorbent and characteristics

Preparation of synthetic stock solution

Experimentation

Effect of pH of the aqueous solution

Effect of dose of adsorbent

Effect of initial copper concentration

Effect of contact time

Adsorption isotherms

Langmuir adsorption isotherm

Freundlich adsorption isotherm

The Temkin isotherm

Redlich–Peterson isotherm

D–R isotherm

Toth isotherm

Harkin–Jura isotherm

Frenkel–Halsey–Hill isotherm

Results and discussion

Characterization of adsorbent

Batch studies

Effect of pH

Effect of adsorbent dose

Effect of initial copper concentration

Effect of agitation time

Adsorption isotherms

Conclusion

Footnotes

Declaration of Conflicting Interests

Funding

References