Multi-walled carbon nanotubes (MWCNTs) were purified and oxidized by a 4 mol L−1 mixture of H2SO4:H2O2 and then were used as adsorbent for tetracycline (TC) adsorption from aqueous solutions. The purified MWCNTs were characterized using Fourier transform infrared spectroscopy, field emission scanning electron microscopy, energy dispersive X-ray spectroscopy, X-ray diffraction, and N2 adsorption/desorption isotherms. The adsorption of TC onto the MWCNT was investigated as a function of the initial pH of the solution, adsorbent dosage, and background electrolyte cations and anions. The results of the one-way analysis of variance (ANOVA) showed that Fe3+ ion significantly affected and decreased TC adsorption onto the MWCNT (P-value < 0.05), while other studied cations and anions did not affect TC adsorption (P-value>0.05). Nonlinear pseudo-first-order, pseudo-second-order, general order, and Avrami fractionary-order kinetic models were used to investigate the kinetics of TC adsorption. The fractionary-order kinetic model provided the best fit to experimental data. In addition, the adsorption isotherms data were well described by nonlinear equation of the Liu isotherm model with the maximum adsorption capacity of 253.38 mg g−1. The results of this study indicate that the oxidized MWCNTs can be used as an effective adsorbent for TC removal from aqueous solutions.

INTRODUCTION

Traditionally, the chemical compounds used for eradicating or inhibiting the growth of microorganisms are known as antibiotics. However, this term also includes antibacterial, antiviral, antifungal, and antitumor compounds (Homem & Santos 2011). In recent years, pharmaceutical antibiotics, due to their great therapeutic values, are widely used in human therapy to prevent infections. They are also used in the livestock and farming industries against disease-producing bacteria, and for growth rate promotion (Zhao et al. 2012; Safari et al. 2015). The extensive and indiscriminate use of pharmaceutical antibiotics has raised significant concerns because they have the potential to create adverse effects such as acute and chronic toxicity. Additionally, they affect aquatic photosynthetic organisms and disrupt indigenous microbial populations. The emergence of new strains of bacteria, which are resistant to these antibiotics, is another major concern. This, in turn, may result in untreatable livestock diseases. Subsequently, possible transmission of such strains to humans may lead to untreatable human diseases (Homem & Santos 2011; Gao et al. 2012; Zhao et al. 2012).

Since a small portion of most antibiotics, including tetracycline (TC), could be metabolized or absorbed by the body of a treated human or animal, large fractions of these substances are excreted through urine and feces as unchanged parent compounds (Gao et al. 2012; Kyzas et al. 2015). Antibiotics can be released into the environment from many sources such as effluents from municipal wastewater treatment plants and effluents from pharmaceutical manufacturing plants because conventional water and wastewater treatment technologies cannot remove antibiotics completely. The application of animals’ manure and sewage sludge to agricultural fields, as fertilizers, is another major source that release antibiotics into the environment through runoff, leaching, and other ways. Residues of these antibiotics discharged from above-mentioned sources are frequently detected in soil, surface water, groundwater, and even drinking water (Zhang et al. 2011c; Thayyath et al. 2015; Terzopoulou et al. 2016).

Thus, to prevent and minimize the risks related to antibiotics, effluent-containing antibiotics must be treated by an appropriate technique. Several methods have been evaluated to remove antibiotics from aqueous solutions, including conventional techniques (biological process, filtration, coagulation, flocculation and sedimentation), advanced oxidation process (AOPS), membrane treatment, adsorption, and combined methods (Homem & Santos 2011; Jaafarzadeh et al. 2015; Ma et al. 2015; Kakavandi et al. 2016). Each of these methods has different removal efficiency, capital costs, advantage, disadvantage, and operating rates. Previous studies (Homem & Santos 2011; Kakavandi et al. 2014) reported that physical techniques, particularly adsorption, are appropriate and more efficient than chemical processes for the removal of recalcitrant and organic compounds. In addition, the adsorption method can produce a high quality effluent without the presence of hazardous substances (Shirmardi et al. 2013b; Vosoughi Niri et al. 2014). The adsorption of TC has been evaluated by several materials as adsorbent including bamboo charcoal (Liao et al. 2013), montmorillonite (Zhao et al. 2012), bio-char (Liu et al. 2012b), graphene oxide (Gao et al. 2012), soil and sediment (Zhang et al. 2011c), activated carbon (Martins et al. 2015; Zhang et al. 2015), multi-walled carbon nanotubes (MWCNTs) (Zhang et al. 2011b) and single-walled carbon nanotubes (Ji et al. 2009). Carbon nanotubes, due to their relatively large specific surface areas, unique hollow and porous structure, high mechanical strength, small size and remarkable electrical conductivities, have been utilized as a new and promising adsorbent to remove many kinds of organic and inorganic contaminants (Shirmardi et al. 2012; Yu et al. 2014a; Babaei et al. 2015). For instance, Yu et al. (2016) investigated the adsorptive removal of ciprofloxacin (CPX) by MWCNTs with different oxygen contents. The authors reported that with increasing the oxygen content of the MWCNT from 2.0% to 5.9%, the normalized maximum adsorption capacity of CPX increases. Zhang et al. (2011a) evaluated the adsorption of sulfamethoxazole (SMX) on functionalized carbon nanotubes and reported that various mechanisms such as electrostatic interaction, hydrophobic interaction, π-π, and hydrogen bonds play roles in SMX adsorption. It should be pointed out that surface chemical functionalization of MWCNT could improve its adsorptive capacity by introducing various functional groups as well as providing new adsorption sites for the adsorption of target pollutants. Additionally, the hydrophobicity of CNTs can be decreased by functional groups; consequently, the adsorption of organic compounds with relatively low molecular weight and polar properties increases considerably. Despite of the availability of different modification methods, oxidation has been proved as a simple method for producing hydroxyl and carbonyl groups to the sidewalls of CNTs (Zhang et al. 2011a; Yu et al. 2014b). In this study, since MWCNTs have not been oxidized by a mixture of H2SO4:H2O2 for the adsorption of TC from the aqueous solutions, we first oxidized and purified the MWCNT and then investigated its efficiency for TC adsorption. The effects of basic variables such as pH of solution, MWCNT dosage, background electrolytes, contact time, and initial concentration on the adsorption of TC were evaluated. The kinetics and isotherms of adsorption of TC on MWCNT were also investigated.

MATERIALS AND METHODS

Reagents and solutions

The analytical high performance liquid chromatography (HPLC) grade TC with the purity of ≥88% was purchased from Sigma-Aldrich Chemical Co. (USA), and was used without further purification. The chemical structure and some main characteristics of TC are presented in Table 1. Methanol and acetonitrile (both HPLC grade), and oxalic acid dehydrate were purchased from Merck company, Germany. MWCNTs were purchased from the Iranian Research Institute of Petroleum Industry (IRIPI). These CNTs were synthesized in the CH4/H2 mixture at 700 °C by a chemical vapor deposition method using Co-Mo particles as catalysts. The method of synthesis has been previously described in the literature (Dehghani et al. 2013; Derakhshani & Naghizadeh 2013). The diameter and the length of the MWCNT were in the range of 10–30 nm and 10 μm, respectively. In addition, the purity of the CNTs was more than 95%. All above-mentioned information was provided by the IRIPI.

Table 1

Chemical structure and main characteristics of TC antibiotic

NameChemical formulaMolecular weightMolecular structurepKa1pKa2pKa3
TC C22H24N2O8·xH2444.43  3.3 7.68 9.68 
NameChemical formulaMolecular weightMolecular structurepKa1pKa2pKa3
TC C22H24N2O8·xH2444.43  3.3 7.68 9.68 

Deionized water was used throughout the experiments to prepare working solutions. The stock solution of TC was prepared freshly by weighing and dissolving the desired amount of TC in deionized water, and was kept in the dark below 4 °C. The required concentrations for the experiments were obtained by diluting the stock solution to 100 mL, brown, volumetric flasks.

All other chemicals used were analytical reagent grade and were used without further purification.

Treatment and characterization of the adsorbent

In order to oxidize, purify, and remove the amorphous carbon and Co-Mo catalysts from the MWCNT, 4 g of the as-received MWCNT were immersed in 200 mL mixture of H2SO4:H2O2 (both 4 mol L−1) with the volumetric ratio of 70:30. The mixture was then heated and refluxed at 120 °C for 2 h under continuous magnetic stirring. Afterwards, the mixture was filtrated and washed with deionized water several times until the pH of the suspension reached about 6, and then was dried at 80 °C in an oven overnight.

The treated MWCNTs were characterized using Fourier transform infrared spectroscopy (FTIR) (Perkin-Elmer Spectrum One) to identify the surface functional groups of the oxidized MWCNT. The MWCNT and KBr were previously dried at 120 °C for 8 h, stored in a capped flask, and kept in a desiccator before performing the analysis (Ribas et al. 2014). The spectra are recorded for the MWCNT sample in the spectral range of 4,000–400 cm−1.

The MWCNT was also characterized by employing field emission scanning electron microscope (FESEM, model Mira 3-XMU) to observe surface morphologies of the adsorbent. The FESEM device was equipped with an energy dispersive X-ray spectrometer (EDS) analyzer; thus, we performed the EDS analysis to identify the elemental composition of the MWCNT. The adsorbent was also characterized by X-ray diffraction (XRD) with a Philips Xpert MPD diffractometer (The Netherlands) operating at 40 kV and 40 mA with Cu Kα radiation (λ = 1.5406 Å). Measurements were done with scanning step width of 0.02 ° and time of 3 s, over the 2θ range of 10–90 °.

The N2 adsorption–desorption isotherms of the MWCNT were carried out at liquid nitrogen boiling point (77 K) using a surface analyzer. Before the analysis, the sample was degassed for 4 h at 300 °C under vacuum. The specific surface area, pore size and volume of the adsorbent were evaluated using the Brunauer, Emmett, and Teller multipoint technique and the Barrett, Joyner, and Halenda method, respectively (Machado et al. 2012).

Adsorption experiments

To investigate the adsorption of TC onto the MWCNT, batch adsorption experiments were carried out using a series of 100 mL, brown, volumetric flasks containing 50 mL TC solution of known concentration. We used this type of flask to prevent possible light degradation of TC. The flasks were then transferred into an incubator shaker and agitated at 200 rpm at 20 °C. A series of adsorption experiments were performed to evaluate the effects of operational parameters such as solution pH, adsorbent dosage, background electrolytes, contact time, and initial concentration of TC. In addition, the adsorption kinetics and isotherms were analyzed. The experimental solutions with different initial concentrations were obtained by diluting the stock solution in the required proportions.

Effect of solution pH

The first step in this work was to study the effect of pH on TC adsorption. To determine the optimum pH at which maximum adsorption could be achieved, the initial pH of the solutions (50 mL, initial concentration 50 mg L−1) was adjusted from 3 to 11 using 0.1 mol L−1 HCl or NaOH. The adsorbent dosage and the agitation time were 0.5 g L−1 and 4 h, respectively. In addition, another set of brown flasks containing the same concentrations of TC without the adsorbent were used as blanks to investigate whether pH of the adsorbate solution would have some effect on TC adsorption.

Effect of MWCNT dosage

The MWCNT at different dosages (0.1, 0.25, 0.5, 0.75, and 1 g L−1) were added to the flasks containing two initial TC concentrations of 50 and 100 mg L−1. The other variables such as the contact time and solution pH were fixed at 4 h and the natural pH of the solutions, respectively.

Effect of anions and cations on the adsorption

In order to study the effects of different anions and cations on the adsorption of TC, 1 g L−1 of the MWCNT was added to the solutions containing 1 mM sodium salts of nitrate, bicarbonate, and sulfate anions or chloride salts of cations such as potassium, magnesium, nickel, lithium, and ferric ions. In addition, the initial TC concentration and pH of the solutions were 100 mg L−1 and natural pH, respectively. Other parameters were kept constant. One-way analysis of variance (ANOVA) test was used to compare the results of this run.

Effect of contact time and kinetic studies

The experiments for investigating the effect of contact time and adsorption kinetics were carried out by adding 1 g L−1 of the adsorbent into the initial TC concentration of 75 and 100 mg L−1. The contact time ranged from 5 to 420 min, and when the predetermined time elapsed, the sample was withdrawn and filtered using a syringe membrane filter with the pore size of 0.22 μm. The filtrate was kept in a refrigerator below 4 °C before the measurement of the residual TC concentration. It is worth noting that in this stage of the study, pH was the natural pH (close to 4.71) of the prepared solutions. For kinetics study, nonlinear pseudo-first-order, pseudo-second-order, general-order, Avrami fractionary-order kinetic models, and intra-particle diffusion model were employed to fit the kinetic data. These models are given by Equations (1)–(5), respectively (Weber & Morris 1963; Ho 2006; Liu & Liu 2008; Liu & Shen 2008; Cardoso et al. 2011; Machado et al. 2012).
formula
1
formula
2
formula
3
formula
4
formula
5
where t is the contact time (min); qt is the amount of adsorbate (TC in this study) adsorbed at time t (mg g−1); qe is the amount of adsorbate adsorbed at the equilibrium (mg g−1); kf is the pseudo-first-order rate constant (min−1); ks is the pseudo-second-order rate constant (g mg−1min−1); kN is the general order rate constant [min−1× (g mg−1)n−1]; n is the order of kinetic adsorption (n could be an integral or a fractional number). kAV is the Avrami kinetic constant (min−1); nAV is a fractionary reaction order (Avrami) which can be related to the adsorption mechanism.

Equilibrium studies

To obtain the adsorption isotherms, 1 g L−1 of the MWCNT were added to TC solutions with the concentration ranging from 10 mg L−1 to 300 mg L−1 at contact time 4 h, temperature 20 °C, and natural pH. In this work, nonlinear equations of the Langmuir (Langmuir 1918), Freundlich (Freundlich 1906), Liu (Liu et al. 2003), and Redlich–Peterson (Redlich & Peterson 1959) isotherm models, as respectively shown in Equations (6)–(9), were used to fit the experimental data. These models are widely used to fit the adsorption of various contaminants on carbon-based adsorbents such as CNTs (Shirmardi et al. 2013a), activated carbon (Saucier et al. 2015a) and biochars (Mohan et al. 2011).
formula
6
formula
7
formula
8
formula
9
where qe is the amount of adsorbate (TC) adsorbed at the equilibrium (mg g−1); Ce is the equilibrium concentration of the adsorbate (mg L−1); Qmax is the maximum adsorption capacity of the adsorbent (mg g−1); KL is the Langmuir equilibrium constant (L mg−1); KF is the Freundlich equilibrium constant [mg g−1× (mg L−1)−1/nF]; Kg is the Liu equilibrium constant (L mg−1); nF and nL are the dimensionless exponents of the Freundlich and Liu models, respectively. KRP and aRP are Redlich–Peterson constants with the respective units of L g−1 and (mg L−1)g, and g is the Redlich–Peterson exponent (dimensionless), whose value should be ≤1.

TC determination

At the end of each run, after filtering, the residual concentration of TC in the solution was analyzed by a Knauer HPLC instrument, equipped with a Eurospher column (5 μm 4.6 mm × 250 mm) and an ultimate variable wavelength UV detection 2500, at a wavelength of 360 nm. The column temperature, the injection volume of the sample, and the flow rate were 35 °C, 100 μL, and 1 mL min−1, respectively. The mobile phase used for elution was a mixture of oxalic acid (0.01 M):methanol:acetonitrile with a volumetric ratio of 70:20:10. The residual concentration of TC in the solutions was calculated from the areas under the curves extrapolated automatically by the software. The standards of TC (initial concentration of 0.01, 0.1, 1, 5, 10, 20, 50, and 100 mg L−1) were prepared and analyzed by the HPLC at operating conditions to form the calibration curve. The determination coefficient (R2) for TC was obtained to be 0.9999. The retention time of TC was about 6.7 min. The same procedure has been used by other researchers for TC determination (Liu et al. 2012a; Alavi et al. 2015).

The TC removal percentage, the amounts of TC adsorbed at time t (qt, mg g−1) and at equilibrium (qe, mg g−1) were calculated through the following equations, respectively (Shirmardi et al. 2013a, 2013b):
formula
10
formula
11
formula
12
where Co and Ce (mg L−1) are the initial and equilibrium concentrations of TC in the solution; M (g) is the mass of MWCNT, V (L) is the volume of the solution, and Ct (mg L−1) and qt (mg g−1) are the concentration of TC at time t and the amount of TC adsorbed onto MWCNT at time t, respectively.

Statistical evaluation of kinetic and isotherm parameters

In this work, the kinetic and equilibrium data were fitted by employing a nonlinear method, with successive interactions calculated by the Levenberg–Marquardt method. Interactions were also calculated using the Simplex method based on the nonlinear fitting facilities of the OriginPro 2015 software. The suitability of the models was evaluated using a determination coefficient (R2), an adjusted determination coefficient (R2adj) and a standard deviation (SD). The SD is a measurement of the difference between the theoretical value of q predicted by the model and the actual q measured experimentally. The respective mathematical expressions of R2, R2adj and SD are respectively given below by Equations (13)–(15).
formula
13
formula
14
formula
15
In these equations, represents individual value of q measured experimentally; represents individual value of q predicted by the model fitted; represents the average value of all q measured experimentally; n is the number of experiments performed; p represents the number of parameters of the fitted model (Saucier et al. 2015b).

RESULTS AND DISCUSSION

Characterization of the adsorbent

Figure 1 shows the FTIR vibrational spectrum of the MWCNT. The FTIR spectrum of the oxidized MWCNT shows a broad band at 3,426 cm−1, which refers to the OH stretching of the hydroxyl group, coming from acid treatment process. The band at 2,358 cm−1 can be associated with the OH stretching from strongly hydrogen bonded -COOH group (Morsy et al. 2014). The peaks observed at 1,571 and 1,630 cm−1 were assigned to C=C stretch and carbonyl group C=O, respectively (Machado et al. 2012). The peak at 1,450 cm−1 represents the C–C vibrational mode associated with the carbon backbone of the MWCNT (Chaudhary et al. 2014). The band at 1,129 cm−1 was assigned to C–O stretch (Salam & Burk 2008). The FTIR spectrum of the oxidized MWCNT confirms that oxygen-containing functional groups are abundant on the surface of MWCNT. Therefore, the presence of these groups can provide numerous adsorption sites on the surface of the MWCNT for the adsorption of TC molecules. The FESEM images of the oxidized MWCNT at various magnifications are depicted in Figure 2. It is clear that the MWCNT has a tubular shape with the external diameter of 18 nm (Figure 2). The EDS spectrum and the XRD pattern of the MWCNT are shown in Figure 3(a) and 3(b), respectively. The EDS spectrum of the MWCNT shows that C, O, Mo, and Co elements are present in the composition of the MWCNT. Carbon composes 90% (weight percent) and 96% (atomic percent) of the MWCNT. Table 2 presents the quantitative results of EDS analysis of the MWCNT. The XRD pattern of the MWCNT shows a broad peak at position 26.5 ° and several relatively weak peaks at positions 42.5 ° and 44.5 ° for 2θ, which can be indexed to carbon (C) phase (JCPDS card 00-026-1077). The other phases that were detected by XRD can be indexed to cobalt (JCPDS card 00-001-1255), molybdenum oxide (Mo18O52, JCPDS card 01-074-1664), molybdenum carbide (Mo2C, JCPDS card 01-072-1683), molybdenum carbonyl (Mo(CO)6, JCPDS card 00-012-0691), cobalt oxide (CoO, JCPDS card 01-075-0418), and cobalt molybdenum oxide (CoMoO4, JCPDS card 00-021-0868) (Figure 3(b)). The textural properties of the MWCNT are presented in Table 3. The relatively large pore diameter of the MWCNT could be attributed to the aggregated pores of the MWCNT. The formation of aggregated pores in the MWCNT is due to the entanglement of tens and hundreds of individual tubes, which are adhered to each other because of van der Waals attraction forces. Therefore, the aggregated pores have the dimensions of a mesopore or higher (Upadhyayula et al. 2009; Prola et al. 2013).
Table 2

Quantitative results of EDS analysis of the MWCNT

ElementLineIntensityKrWt%Atom%
Ka 1,138.1 0.7234 90.98 96.05 
Ka 17.3 0.0055 3.92 3.11 
Co Ka 22.2 0.0151 2.07 0.45 
Mo La 70.5 0.0234 3.03 0.40 
Total – – 0.7673 100.00 100.00 
ElementLineIntensityKrWt%Atom%
Ka 1,138.1 0.7234 90.98 96.05 
Ka 17.3 0.0055 3.92 3.11 
Co Ka 22.2 0.0151 2.07 0.45 
Mo La 70.5 0.0234 3.03 0.40 
Total – – 0.7673 100.00 100.00 
Table 3

Textural properties of the adsorbent

AdsorbentSurface area (m2/g)Total pore volume (cm3/g)Average pore diameter (nm)
MWCNT 221.908 0.716 2.722 
AdsorbentSurface area (m2/g)Total pore volume (cm3/g)Average pore diameter (nm)
MWCNT 221.908 0.716 2.722 
Figure 1

FTIR spectrum of the oxidized MWCNT.

Figure 1

FTIR spectrum of the oxidized MWCNT.

Figure 2

SEM images of the MWCNT at different magnifications.

Figure 2

SEM images of the MWCNT at different magnifications.

Figure 3

EDS spectrum (a) and XRD pattern (b) of the MWCNT.

Figure 3

EDS spectrum (a) and XRD pattern (b) of the MWCNT.

Effect of pH of adsorbate solution

The effect of solution pH on the adsorption of TC onto the MWCNT is shown in Figure 4. The solution pH significantly affected TC adsorption onto the MWCNT, mainly for pH values higher than 7. The adsorption percentage increases when the solution pH is increased from 3 to 5; it remains almost unchanged and there is no observable change in the adsorption of TC onto the MWCNT as the solution pH is further increased from 5 to 7. However, TC adsorption percentage decreases considerably as the pH is increased from 7 to 11. The adsorption percentage decreases when the pH is ≤ 3 or pH >7. For the initial TC concentration of 50 mg L−1, the removal percentage decreases from 84% to 54% when the solution pH is increased from 5 to 11 (Figure 4). The relationship between the solution pH and TC adsorption can be explained by considering both the surface charges and properties of the adsorbent and the pH-dependent speciation of TC antibiotic. Changing the solution pH cannot only affect the protonation–deprotonation transition of functional groups on an adsorbent but also can result in a change in chemical speciation of organic compounds (Zhang et al. 2011b). TC (symbolized as H2L) is an amphoteric molecule having multiple ionizable functional groups (such as amino, phenol, and alcohol) depending on the solution pH. Since TC has three pKa values (3.30, 7.68 and 9.68), it exists as cation (H3L+) due to the protonation of dimethyl-ammonium group when solution pH is below 3.3. At pH between 3.3 and 7.68, TC exists as a zwitterion (H2L0) due to the loss of a proton from the phenolic diketone moiety. At solution pH greater than 7.68, TC exists as anions (HL−1 and L−2) because of the loss of protons from the tri-carbonyl system and phenolic diketone moiety (Kang et al. 2011; Zhang et al. 2011b). At pH between 3.3 and 7.7, the most dominant adsorption mechanism is probably the non-electrostatic π-π dispersion interaction between bulk π systems on the MWCNT surface and TC molecules contained both benzene rings and double bonds (C=C, C=O), or hydrophobic interaction between the MWCNT and TC (Zhang et al. 2011b). In this pH range, TC exists as zwitterion, nearly all TC molecules carry no net electrical charge, and there is almost no electrostatic attraction or repulsion between TC molecules and the adsorbent. Thus, the increase of pH from 5 to 7 has no remarkable influence on the adsorption affinity of TC onto the MWCNT. However, the reduced TC adsorption at pH < 3.3 and pH > 7.7 can be justified by the increased formation of H+ or OH in the solution at the related pH. At pH above 9, the surface of the MWCNT is negatively charged; therefore, the electrostatic repulsion between the surface of the adsorbent and TC species (HL and L2−) reduces the TC adsorption (Yu et al. 2014a). It should be noted that the pH of the solutions was not fixed for the rest of our experiments since the pH of the prepared working solutions was in the range of 4–5, in which TC molecules are dominantly present as zwitterion. The results of the present study are consistent with the results of other researchers. For instance, Rivera-Utrilla et al. (2013) reported that the adsorption of TC on the activated carbon remained constant in the pH range of 2–7 and decreased as the pH was increased. Zhang et al. (2011c) also stated that the adsorption of TC on soil and sediment was relatively constant at pH 5–9 and decreased at pH > 9.
Figure 4

Effect of pH on the adsorption of TC onto MWCNT. Condition: temperature 20 °C; initial TC concentration 50 mg L−1; adsorbent dosage 0.5 g L−1.

Figure 4

Effect of pH on the adsorption of TC onto MWCNT. Condition: temperature 20 °C; initial TC concentration 50 mg L−1; adsorbent dosage 0.5 g L−1.

Effect of adsorbent dosage

Adsorbent dosage is another important parameter in the determination of adsorption capacity. The effect of the adsorbent dosage was investigated for the initial TC concentration of 50 mg L−1 and 100 mg L−1 by adding various amounts of MWCNT to TC solutions. Figure 5(a) and 5(b) show the adsorption percentage and the amount of TC adsorbed as a function of the MWCNT dosage, respectively. The increase in the percentage of TC removal with increasing adsorbent dosage could be attributed to the increase in the adsorbent surface area, which increases the number of adsorption sites available for adsorption, as already reported in the literature (Cardoso et al. 2011). On the other hand, by increasing the adsorbent dosage, the amounts of TC adsorbed onto the MWCNT decreases remarkably (Figure 5(b)). This phenomenon can be explained through two aspects. First, at a fixed concentration and volume of TC, the increase of the adsorbent dosage will lead to unsaturation of adsorption sites through the adsorption process; second, the particle aggregation due to higher mass of the adsorbent may result in a reduction in the adsorbent capacity. Therefore, such aggregation would lead to a decrease in the total surface area of the adsorbent and an increase in the diffusional path length (Cardoso et al. 2011).
Figure 5

Effect of MWCNT dosage on the adsorption of TC: (a) represents removal percentage and (b) represents the amount of TC adsorbed. Conditions: natural pH; temperature 20 °C; contact time 4 h.

Figure 5

Effect of MWCNT dosage on the adsorption of TC: (a) represents removal percentage and (b) represents the amount of TC adsorbed. Conditions: natural pH; temperature 20 °C; contact time 4 h.

Effect of cations and anions

The effects of background cations (Li+, K+, Mg2+, Ni2+ and Fe3+) and anions (HCO3, NO3, and SO42−) on the adsorption of TC onto the MWCNT were investigated using batch adsorption experiments, and the results are shown in Figure 6. As reported in the literature, the concentration of anions such as nitrate, bicarbonate, and sulfate and most of cations such as potassium, lithium, calcium, magnesium, and nickel in surface waters is usually less than 1 mM (Hem 1985; Bui & Choi 2010); therefore, we used 1 mM salts of these anions and cations to evaluate their effects on TC adsorption. The adsorption of TC in the presence of the anions and cations was compared to TC adsorption in the absence of the tested anions and cations (sample containing only the adsorbent and 100 mg L−1 TC). The ANOVA test results indicated that the tested anions and the monovalent and divalent cations did not significantly affect TC adsorption (p > 0.05). However, the presence of Ni2+ slightly decreases TC adsorption (Figure 6); this slight decrease can be considered as a competition of Ni2+ with TC species to adsorb on active sites of the adsorbent. On the other hand, the presence of the other anions and cations (except Fe3+) slightly increases TC adsorption onto the MWCNT (Figure 6); this increase in the adsorption may be attributed to surface bridging mechanism and the formation of surface complexes on the surface sites (Zhao et al. 2011). On the contrary, the presence of Fe3+ significantly affected and decreased the adsorption of TC (p < 0.05). This decrease in the adsorption of TC onto the MWCNT may be attributed to the highest tendency of Fe3+ to adhere to the negatively charged oxidized MWCNTs, which in turn reduces ion interaction sites (or available sites) on the surface of the oxidized MWCNT for TC adsorption. The results of this study are in good agreement with the results of the other researchers. For instance, Liu et al. (2012a) investigated the removal of TC from water by Fe-Mn binary oxide and reported that the presence of cations and anions such as Ca2+, Mg2+, CO32− and SO42− had no significant effect on the TC removal in their experimental conditions, while SiO32− and PO43− hindered the adsorption of TC. Zhao et al. (2011) evaluated the adsorption of TC onto goethite in the presence of metal cations and humic substances. They stated that at the studied pH range, the presence of five background electrolyte cations (Li+, Na+, K+, Ca2+, and Mg2+) with a concentration of 0.01 M had little effect on the TC adsorption. The adsorption of four pharmaceuticals (carbamazepine, diclofenac, ibuprofen, and ketoprofen) to silica as a function of ionic strength, anions, cations, and natural organic matter was investigated by Bui & Choi (2010). The authors reported that the tested anions did not significantly affect the adsorption of these pharmaceuticals to silica (p > 0.05). Their results also showed that divalent cations did not significantly affect the adsorption of carbamazepine and diclofenac; however, divalent cations at low concentrations (1 mM) increased the adsorption of ibuprofen and ketoprofen. In contrast with the present study, in that study the presence of Fe3+ significantly increased the adsorption of the pharmaceuticals, but in our study it significantly decreased the adsorption of TC. This difference may be ascribed to the different structures of both adsorbate and adsorbent used in the studies. Blank experiments were also run for both anions and cations at the same conditions to observe the changes in the initial concentration of TC because of possible reactions between TC and the tested anions and cations. The change in TC concentration in the blank samples was in the range of 0.2–2% for all cations and anions.
Figure 6

The adsorption of TC onto the MWCNT in the presence of 1 mM cations and anions, compared to control (initial TC 100 mg L−1). Error bars represent the SD of sample replicates. Conditions: natural pH; temperature 20 °C; contact time 4 h; adsorbent dosage 1 g L−1.

Figure 6

The adsorption of TC onto the MWCNT in the presence of 1 mM cations and anions, compared to control (initial TC 100 mg L−1). Error bars represent the SD of sample replicates. Conditions: natural pH; temperature 20 °C; contact time 4 h; adsorbent dosage 1 g L−1.

Kinetic studies

In the treatment of aqueous effluents by adsorption process, it is important to evaluate adsorption kinetics because they provide valuable pieces of information on the reaction pathways as well as on the mechanisms of the adsorption process (Cardoso et al. 2011). The kinetic plots for the adsorption of TC onto the MWCNT are shown in Figure 7. The fitting parameters of the kinetic models are presented in Table 4. In addition to the adjusted R2 value, the SD value was also used to explain the suitability of the fitted models as we fitted the experimental data to the nonlinear kinetic models. A higher SD value indicates that a higher deviation exists between q value calculated theoretically by the model and q value measured experimentally. It has been reported in the literature (Prola et al. 2013) that the best fit of the data is a function of the number of parameters in nonlinear models. Therefore, due to this fact, we considered the number of parameters of each model (p term in Equation (15)) for calculating the SD values and evaluating the kinetic models. The minimum SD value was used to divide the SD value of each model (SD ratio); and, subsequently, the fitness of each model was compared based on the SD ratio value. For the initial TC concentration of 75 and 100 mg L−1, the lowest SD values were obtained for the Avrami-fractional-order kinetic model. In this work, for TC concentration of 75 mg L−1, the SD ratio values for the pseudo-first-order, pseudo-second-order, and general order kinetic models were 5.19, 1.47, and 1.17, respectively, while the corresponding values for TC concentration of 100 mg L−1 were 3.95, 1.56, and 1.54, respectively. The results obtained by the fitted models clearly showed that the Avrami-fractional order kinetic model better explained the adsorption of TC onto the MWCNT because this model exhibited the SD ratio value of 1.00, which is a lower value when compared to the other kinetic models. Additionally, this model showed the highest R2adj value, as well as the qe values predicted by the fractionary-order were closer to the experimental qe values. It can be found in the literature that several kinetic processes of different adsorbents and adsorbates have been successfully explained by the Avrami kinetic equation (Cardoso et al. 2011). The Avrami exponent, nAV, is a fractionary number, which is associated with the possible changes in the adsorption mechanism during the adsorption process. Instead of following only an integer-kinetic order, the adsorption mechanism could follow multiple kinetic orders, which change during the contact of an adsorbate with an adsorbent (Royer et al. 2009). The nAV exponent is achieved from the multiple kinetic orders of an adsorption process. As mentioned, the Avrami kinetic model fit better our experimental data; therefore, we used the intra-particle diffusion model to investigate the influence of mass transfer resistance on the binding of TC to the adsorbent, MWCNT (see Table 3 and Figure 6(c) and 6(d)). Intra-particle diffusion constant (kid) in terms of mg g−1 min−0.5 can be obtained from the slope of the plot of qt (the amount adsorbed at any time) versus the square root of time. The plots of qt versus t0.5 are shown in Figure 7(c) and 7(d) for the two initial TC concentrations. The plots have three linear sections indicating that the adsorption process follows more than one adsorption rate (Ribas et al. 2014). Each linear can be attributed to each stage of the adsorption process. Accordingly, the process in which TC molecules diffuse to the surface of the adsorbent can be referred to the first linear section, which is the fastest sorption stage (Ribas et al. 2014). The second linear section is a delayed process and can be attributed to the intra-particle diffusion (Ribas et al. 2014). The third portion is obtained after the equilibrium and describes diffusion through smaller pores (Ribas et al. 2014). The kinetic studies reveal that the minimum contact time to reach the equilibrium for the adsorption of TC onto the MWCNT is about 120 min. For the rest of our experimental work, the contact time was fixed at 240 min to ensure that the equilibrium would be attained between the adsorbate even at higher concentrations and MWCNT as the adsorbent (Cardoso et al. 2011).
Table 4

Kinetic parameters obtained from the nonlinear models for the adsorption of TC onto the MWCNT

TC concentration mg L−1
Kinetic model75100
Pseudo-first-order 
 Kf (min−10.1162 0.06691 
 qe (mg g−170.03 89.82 
 h0 (mg g−1 min−18.138 6.011 
 SD (mg g−14.075 5.089 
 R2adj 0.9532 0.9614 
Pseudo-second-order 
 Ks (g mg−1 min−12.821.10−3 1.119.10−3 
 qe (mg g−173.83 95.93 
 h0 (mg g−1 min−115.38 10.30 
 SD (mg g−11.158 2.014 
 R2adj 0.9962 0.9940 
General order 
 KN [h−1(g mg−1)n−15.541.10−4 3.560.10−4 
 qe (mg g−176.07 98.30 
 n 2.415 2.261 
 h0 (mg g−1 min−119.39 11.50 
 SD (mg g−10.9190 1.986 
 R2adj 0.9976 0.9941 
Avrami fractionary 
 KAv (min −10.1288 0.064141 
 qe (mg g−173.08 93.32 
 nAV 0.4973 0.5958 
 h0 (mg g−1 min−19.414 5.986 
 SD (mg g−10.7851 1.288 
 R2adj 0.9983 0.9975 
Intra-particle diffusion 
 kid (mg g−1 min−0.5)a 5.080 3.460 
 R2 0.9495 0.9523 
TC concentration mg L−1
Kinetic model75100
Pseudo-first-order 
 Kf (min−10.1162 0.06691 
 qe (mg g−170.03 89.82 
 h0 (mg g−1 min−18.138 6.011 
 SD (mg g−14.075 5.089 
 R2adj 0.9532 0.9614 
Pseudo-second-order 
 Ks (g mg−1 min−12.821.10−3 1.119.10−3 
 qe (mg g−173.83 95.93 
 h0 (mg g−1 min−115.38 10.30 
 SD (mg g−11.158 2.014 
 R2adj 0.9962 0.9940 
General order 
 KN [h−1(g mg−1)n−15.541.10−4 3.560.10−4 
 qe (mg g−176.07 98.30 
 n 2.415 2.261 
 h0 (mg g−1 min−119.39 11.50 
 SD (mg g−10.9190 1.986 
 R2adj 0.9976 0.9941 
Avrami fractionary 
 KAv (min −10.1288 0.064141 
 qe (mg g−173.08 93.32 
 nAV 0.4973 0.5958 
 h0 (mg g−1 min−19.414 5.986 
 SD (mg g−10.7851 1.288 
 R2adj 0.9983 0.9975 
Intra-particle diffusion 
 kid (mg g−1 min−0.5)a 5.080 3.460 
 R2 0.9495 0.9523 

Conditions: temperature 20 °C; pH natural; adsorbent dosage 1 g L−1.

aSecond zone.

Figure 7

Kinetic curves for the adsorption of TC onto the MWCNT at 20 °C: (a) Co = 75 mg L−1; (b) Co = 100 mg L−1; (c) intra-particle diffusion for Co = 75 mg L−1; (d) intra-particle diffusion for Co = 100 mg L−1. Conditions: natural pH; adsorbent dosage 1 g L−1.

Figure 7

Kinetic curves for the adsorption of TC onto the MWCNT at 20 °C: (a) Co = 75 mg L−1; (b) Co = 100 mg L−1; (c) intra-particle diffusion for Co = 75 mg L−1; (d) intra-particle diffusion for Co = 100 mg L−1. Conditions: natural pH; adsorbent dosage 1 g L−1.

Equilibrium studies

Adsorption isotherms describe how the adsorbate molecules distribute between the liquid phase and the solid phase when the adsorption process reaches an equilibrium state. In other words, adsorption isotherms are used to describe the relationship between the amount of adsorbate adsorbed by the adsorbent (qe) and the adsorbate concentration remaining in the solution after the system has reached to the equilibrium state (Ce) at a constant temperature. In addition, some information about adsorption mechanism, the affinity of the adsorbate to the adsorbent, and surface properties can be obtained from the adsorption parameters of equilibrium models. In this study, the isotherms of adsorption of TC onto the MWCNT were carried out at 20 °C using the optimum experimental condition described previously. Figure 8 shows the adsorption isotherms of TC onto the MWCNT. The parameters predicted by the nonlinear adsorption models are presented in Table 5. Based on the SD values, it is clear that the Liu model best describes the equilibrium data since this model shows the lowest SD value. The SD ratio was used to compare the studied isotherm models. The procedure used for calculating the SD ratio is described in the previous section (kinetic studies). The SD values of the Langmuir, Freundlich, and Redlich–Peterson models are 3.98, 2.14, and 1.75 times higher than the SD value obtained for the Liu model (Table 5). The maximum amount of TC adsorbed onto the MWCNT (Qmax) predicted by the Liu model is 253.38 mg g−1, indicating this adsorbent is a good adsorbent for the removal of TC from aqueous solutions. It can be obviously seen from Figure 8 that with increasing the initial TC concentration from 10 to 300 mg L−1, the amount of TC adsorbed onto the MWCNT increases from 9.99 to 165.4 mg g−1, while the removal percentage decreases from 99.9% to 53.1%. To compare the efficiency of the MWCNT used in this work with other adsorbents, the maximum adsorption capacity of different adsorbents for the removal of TC is presented in Table 6. The values of Qmax were obtained at the best experimental conditions of each work.
Table 5

Isotherm parameters for the adsorption of TC onto the MWCNT adsorbent

Isotherm modelParameterValue
Langmuir Qmax (mg g−1154.7 
KL (L mg−10.2743 
R2adj 0.9501 
SD (mg g−112.04 
Freundlich KF [mg g−1 (mg L−1)−1/nF53.27 
nF 4.089 
R2adj 0.9857 
SD (mg g−16.452 
Liu Qmax (mg g−1253.4 
Kg (L mg−10.03556 
nL 0.4203 
R2adj 0.9968 
SD (mg g−13.025 
Redlich–Peterson KRP L g−1 561.5 
aRP (mg L−1)g 9.434 
0.7818 
R2adj 0.9903 
SD (mg g−15.302 
Isotherm modelParameterValue
Langmuir Qmax (mg g−1154.7 
KL (L mg−10.2743 
R2adj 0.9501 
SD (mg g−112.04 
Freundlich KF [mg g−1 (mg L−1)−1/nF53.27 
nF 4.089 
R2adj 0.9857 
SD (mg g−16.452 
Liu Qmax (mg g−1253.4 
Kg (L mg−10.03556 
nL 0.4203 
R2adj 0.9968 
SD (mg g−13.025 
Redlich–Peterson KRP L g−1 561.5 
aRP (mg L−1)g 9.434 
0.7818 
R2adj 0.9903 
SD (mg g−15.302 

Conditions: adsorbent dosage 1 g L−1; natural pH; temperature 20 °C, and contact time 4 h.

Table 6

Maximum sorption capacity of different adsorbents used for the adsorption of TC

AdsorbentQmax (mg g−1)Reference
Carbon nanotubes (MWCNT) 253.38 Present study 
Montmorillonite 250 Zhao et al. (2012)  
Chitosan 23.92 Kang et al. (2010)  
Fe–TiO2–PPy 149.25 Thayyath et al. (2015)  
Zeolite beta 75.55 Kang et al. (2011)  
Graphene oxide 313.480 Gao et al. (2012)  
CNTs-3.2%O 269.25 Yu et al. (2014a)  
Bamboo charcoal 22.7 Liao et al. (2013)  
Alkali bio-char 58.8 Liu et al. (2012b)  
PC-based AC 1121.5 Zhang et al. (2015)  
NaOH-activated carbon 455.8 Martins et al. (2015)  
AdsorbentQmax (mg g−1)Reference
Carbon nanotubes (MWCNT) 253.38 Present study 
Montmorillonite 250 Zhao et al. (2012)  
Chitosan 23.92 Kang et al. (2010)  
Fe–TiO2–PPy 149.25 Thayyath et al. (2015)  
Zeolite beta 75.55 Kang et al. (2011)  
Graphene oxide 313.480 Gao et al. (2012)  
CNTs-3.2%O 269.25 Yu et al. (2014a)  
Bamboo charcoal 22.7 Liao et al. (2013)  
Alkali bio-char 58.8 Liu et al. (2012b)  
PC-based AC 1121.5 Zhang et al. (2015)  
NaOH-activated carbon 455.8 Martins et al. (2015)  
Figure 8

Isotherm curves for the adsorption of TC onto the MWCNT at 20 °C. Conditions: natural pH; adsorbent dosage 1 g L−1, contact time between the adsorbent and the adsorbate 4 h.

Figure 8

Isotherm curves for the adsorption of TC onto the MWCNT at 20 °C. Conditions: natural pH; adsorbent dosage 1 g L−1, contact time between the adsorbent and the adsorbate 4 h.

CONCLUSIONS

The adsorption of TC antibiotic onto the oxidized MWCNT as a novel adsorbent was carried out by using a batch adsorption technique. The effects of different operational parameters such as pH of solution, adsorbent dosage, background electrolytes, contact time, and initial TC concentration were evaluated. The optimum pH for TC adsorption was in the range of 5–7 and the adsorption reached the equilibrium after about 120 min. The ANOVA test results show that all the studied cations and anions (except Fe3+) did not significantly affect the adsorption of TC onto the MWCNT. The TC antibiotic interacted with the oxidized MWCNT at the solid/liquid interface as it suspended in water. The experimental data were fitted to four nonlinear kinetic models, and the Avrami fractionary-order kinetic model best described the kinetic of TC adsorption. However, the intra-particle diffusion model gave multiple linear regions suggesting that the adsorption could also follow multiple adsorption rates. Equilibrium data were fitted to four known isotherm models, and the Liu model gave the best fit with the maximum adsorption capacity of 253.38 mg g−1. The results of the present study indicate that oxidized MWCNT can be a good alternative adsorbent for the removal of TC and other pollutants from aqueous solutions.

ACKNOWLEDGEMENTS

The authors are grateful to the Vice Chancellery for Research Development and Technology of Ahvaz Jundishapur University of Medical Sciences, and Environmental Technologies Research Center (ETRC) for funding and providing necessary facilities to accomplish this research with project number of ETRC-9209. In addition, the authors are also grateful to the National Council for Scientific and Technological Development (CNPq, Brazil).

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