Abstract
Cotton cloth waste was used as a precursor to prepare activated carbon (ACCs) chemically activated with phosphoric acid. Adsorption behavior of prepared ACCs was correlated with physicochemical proprieties. The pore volume and BET surface of ACCs were determined by nitrogen adsorption isotherms and scanning electron microscopy was used to observe their surface morphologies. Fourier transform infrared (FTIR) spectroscopy analysis and pH point zero charge (pHPZC) were conducted to determine chemical properties. Under the optimal conditions: 50% impregnation ratio and thermal treatment under N2 flow at 600 °C during 60 min, the activated carbon prepared exhibits a high surface area 1,150 m2/g, 0.501 cm3/g micropore volume and an excellent adsorption performance. The adsorbed amount of clofibric acid is found to be 9.98 and 83 mg/g at, respectively, initial CA concentration of 10 and 100 mg/L at pH 3.0 and 20 °C. Diffusion and chemisorption are the steps controlling the adsorption of CA onto ACC 50% and the equilibrium data were well described by Freundlich isotherm.
HIGHLIGHTS
Activated carbons have been prepared from cotton cloth waste with chemical activation.
Chemical activation produces carbon with a high surface BET and microporosity.
Adsorbent showed high-capacity for the recovery of the clofibric acid.
Cotton cloth waste is potentially promising for the preparation of effective adsorbent.
Graphical Abstract
INTRODUCTION
Rapid urbanization and industrialization have caused serious environmental problems, especially water contamination, over the last few decades. This has resulted in a decrease in water quality, mostly due to emerging pollutants such as organic micropollutants and heavy metal. Among these organic micropollutants, pharmaceuticals are of increasing concern because of their toxicity and non-biodegradability, which can lead to irreversible long-term side effects to aquatic organisms (Martin et al. 2011; Hasan et al. 2013).
Although it is unlikely that these pollutants would be found at concentrations to induce acute effects, it is obvious that they may be present at concentrations able to cause chronic effects for humans. For example, Cabera-Lafourie et al. (2012) have reported concentrations of carbamazepine, clofibric acid, diclofenac and caffeine in wastewater effluent of 463, 772, 50 and 5,650 ng/L, respectively.
Clofibric acid is the metabolite and active principle of the blood lipid regulators clofibrate, etofylline clofibrate, and etofibrate, and is also considered a potential endocrine disruptor, since it interferes with the synthesis of cholesterol (Silva & Faria 2009). Nowadays, this metabolite is regarded as one of the most persistent drug residues with an estimated persistence in the environment of 21 years, being frequently detected in environmental monitoring of pharmaceuticals all around the world (Dordio et al. 2009).
Accordingly, the removal of this pharmaceutical micropollutant from wastewater has become one of the most challenging issues, requiring the development of a sustainable, efficient, and flexible treatment method. Numerous methods, such as biodegradation, electrochemical, ozonation, coagulation and flocculation, and membrane filtration, have been extensively used to remove pharmaceuticals from wastewaters. However, the complex structure of the pharmaceutical, the formation of toxic by-products, and the high cost of operation or maintenance are the main disadvantages of these methods. Compared with the above methods, adsorption is considered as a promising method for removing various pollutants from wastewater due to its economical, renewable, and flexible operation.
Different adsorbents can be employed, but activated carbons are the most widely used, either as powders, grains or fibers (felt or cloth), because of their physical and chemical properties (Miguel et al. 2005). The textural and chemical characteristics of the activated carbon depend both on the nature of the precursor used as well as the methods and conditions of production (Sun et al. 2012a).
The total amount of fiber products, including synthetic and natural fibers, reached 94.7 106 tons in 2017. The largest portion of synthetic fibers is polyester at 54 106 tons and that of natural fibers is cotton at 25.4 106 tons (Kawamura et al. 2020). Despite the abundance of different synthetic and natural fiber products, their waste management from an environmental perspective remains poorly investigated. The interest in activated carbon cloths (ACCs) has significantly increased due to the growing number of new applications, as molecular sieves, catalysts or electrodes. ACCs present technological advantages over the traditional powders or granular forms of activated carbons, including high adsorption capacity, uniform porosity as well as high rates of adsorption/desorption from the gas or liquid phase and possibility for regeneration (Ramos et al. 2011).
Thus, the objective of this study is to valorize cotton cloth waste into activated carbons to be used for the removal of pharmaceutical residues, such as clofibric acid (CA) from aqueous solutions. The activation being chemically carried out with H3PO4, the effect of the impregnation ratio on the physico-chemical characteristics of activated carbons (ACCs) is studied in order to optimize the operating conditions of preparation allowing a good elimination of CA by adsorption. The effect of several operating parameters, such as pH, contact time, and initial CA concentration on the adsorption capacity is investigated. Kinetic models are used to identify the possible mechanisms of such adsorption process. The Langmuir, Freundlich, Sips, Redlich–Peterson and Generalized models are used to analyse the adsorption equilibrium.
EXPERIMENTAL METHOD
Materials
Cotton cloth waste used was provided from a clothing production factory (ALCOST-Bejaia-Algeria). The thermogravimetric analysis (TGA 2050, TA Instruments, USA) of the cotton waste showed the presence of a single peak corresponding to cellulose (Supplementary Figure 1). Phosphoric acid (85% purity) and clofibric acid (2-(p-chlorophenoxy)-2-methylpropionic acid, 99.99%) were obtained from Biochem Chemopharm. Nitrogen gas was of industrial grade (99% purity).
Activated carbons preparation
The activated carbons preparation procedure used was in accordance with the method proposed by Boudrahem et al. (2011).
Physical characterization of the activated carbons
The surface morphology of ACCs was examined by scanning electron microscopy (SEM JSM 820, Jeol Ltd, Japan) equipped with a energy-dispersive X-ray (EDX) analyzer (Princeton Gamma-Tech Instr., Spirit, USA), allowing an elemental analysis.
The surface area, micropore volume and pore size distribution were determined using the nitrogen adsorption–desorption isotherms at 77 K (Micromeritics Tristar II 3020). The surface areas (SBET) were calculated by the BET method assuming that the surface area occupied by a nitrogen molecule is 0.162 nm2. The total pore volumes, VP, were estimated on the basis of the liquid volume of nitrogen adsorbed at a relative pressure of 0.46. The microporous volumes (pores <2 nm) were determined according to the Dubinin-Radushkevich equation (Boudrahem et al. 2011).
The microporous surface area (Smic) is the difference between the BET surface area (SBET) and the mesoporous surface area (Smes).
Chemical characterization of the activated carbon cloths
Surface chemical properties of the ACCs were characterized by the Fourier transform infrared spectroscopy (Shimadzu FTIR-8300, Japan) in the 4,000–400 cm−1 wave number range. The pH point zero charge (pHPZC) of the ACCs was determined using the method reported by Khenniche & Aissani (2010). The net charge of the carbon surface is positive at pH solutions lower than pHPZC and it is negative at a pH solution higher than pHPZC.
Batch adsorption measurements
RESULTS AND DISCUSSION
Nitrogen isotherms and surface area
One of the primary parameters affecting the physico-chemical properties of chemically activated carbon is the ratio of impregnation agent. Cheng et al. (2014) explained that the reactants penetrate deep into the structure of the carbon, causing the development of the pores. The reactant remains inside the precursor during the thermal treatment causing the microporosity creation.
Figure 1 presents the nitrogen adsorption–desorption isotherms of the prepared ACCs. The obtained results show that ACC 75%, ACC 50%, ACC 25% and ACC 0% are type I (microporous solids) according to the IUPAC classification (Guo & Rockstraw 2006). The adsorption curve rises sharply at relative pressure of P/P0 less than 0.2 and then approaches a plateau with increasing relative pressure. The same behavior was observed by Ramos et al. (2011).
The textural characteristics of ACCs, mainly: total surface area (SBET), total porous volume (VP), microporous surface area (Smic), mesoporous surface area (Smes), microporous volume (Vmic), mesoporous volume (Vmes) and average pore diameter (dp) were determined and are reported in Table 1. It is obvious that phosphoric acid is very efficient to produce activated carbons with high porosity and that the impregnation ratio has a significant influence on porosity development. Indeed, it appears that an increase of H3PO4/precursor weight ratio does not only contributes on increasing the microporosity, but it also improves the formation of the mesoporous structure. The formation of mesopores has been attributed to the widening of micropores in coal-based carbons during phosphoric acid activation.
Parameters Impregnation ratio . | Vp (cm3/g) . | Vmic (DR) (cm3/g) . | Microporosity Vμ/Vtot (%) . | Vmes (cm3/g) . | Mesoporosity Vmes/Vtot (%) . | SBET (m2/g) . | Smes (m2/g) . | Smic (m2/g) . | dp = 4 Vp/SBET (Å) . | pHpzc . | qe. (mg/g) . |
---|---|---|---|---|---|---|---|---|---|---|---|
0% | 0.112 | 0.088 | 78.88 | 0.023 | 21.12 | 247 | 108 | 139 | 20.43 | 7.4 | 18 |
25% | 0.363 | 0.340 | 93.85 | 0.022 | 6.15 | 847 | 198 | 649 | 17.84 | 4.1 | 71 |
50% | 0.504 | 0.501 | 99.43 | 0.002 | 0.56 | 1,150 | 518 | 631 | 18.05 | 3.7 | 83 |
75% | 0.283 | 0.228 | 80.63 | 0.054 | 19.37 | 609 | 215 | 394 | 22.93 | 3.4 | 68 |
Parameters Impregnation ratio . | Vp (cm3/g) . | Vmic (DR) (cm3/g) . | Microporosity Vμ/Vtot (%) . | Vmes (cm3/g) . | Mesoporosity Vmes/Vtot (%) . | SBET (m2/g) . | Smes (m2/g) . | Smic (m2/g) . | dp = 4 Vp/SBET (Å) . | pHpzc . | qe. (mg/g) . |
---|---|---|---|---|---|---|---|---|---|---|---|
0% | 0.112 | 0.088 | 78.88 | 0.023 | 21.12 | 247 | 108 | 139 | 20.43 | 7.4 | 18 |
25% | 0.363 | 0.340 | 93.85 | 0.022 | 6.15 | 847 | 198 | 649 | 17.84 | 4.1 | 71 |
50% | 0.504 | 0.501 | 99.43 | 0.002 | 0.56 | 1,150 | 518 | 631 | 18.05 | 3.7 | 83 |
75% | 0.283 | 0.228 | 80.63 | 0.054 | 19.37 | 609 | 215 | 394 | 22.93 | 3.4 | 68 |
The maximum values for the microporosity (99.43%) and the SBET (1,150 m2/g) are obtained with 50% impregnation ratio. Beyond a value of 50%, SBET, Smic and Sext of ACCs decrease. The same trend was observed for pore volumes (total, microporous, and mesoporous). This observation is probably due to the dehydrated excess acid that forms an insulating layer around the particles that partly prevents the penetration of the activating agent into the cotton cloth and the effect of the surrounding atmosphere inhibiting free formation of the internal porosity (Nahil & Williams 2012).
Morphological characterization of the ACCs
The SEM micrographs of the non-activated carbon cloth, the ACC 50% and the fibers extremities ACC 50% are presented in Figure 2(a)–2(e). The fibers surface of the non-activated carbon cloth is smooth without any cracks, breaking or any other visible damages (Figure 2(b)). In fact, the non-porosity of the fibers surface confirms the lower BET surface measured. Concerning the fibers surface of the ACC 50%, it exhibits roughness (Figure 2(d)) which can be attributed to the larger release of volatile matter highlighted by the low yield of carbon obtained when 50% of activating ratio is used. In addition, the mean diameter of fibers ACC 50% is larger than the one of the non-activated carbon cloth, which is due to the infiltration of H3PO4 in the inner of the fibers causing their swelling. When they swell under the effect of H3PO4, they develop cracks (Figure 2(d)) and micropores in accordance with the shape of the nitrogen adsorption isotherm.
FTIR analysis
The FTIR spectra of the prepared ACCs were presented in Figure 3.
A band at 3,399 cm−1 is attributed to the OH group of the phenol function (Khenniche & Aissani 2010). The band between 3,100 and 3,600 cm−1 corresponds to the vibration of the hydroxyl groups fixed on the carbon surface and chimisorbed water on carbon (Pakula et al. 2005). The presence of bands at 2,922 cm−1 and 2,850 cm−1 correspond to stretching C-H groups and they represent aliphatic, olefinic and aromatic structures. The first one could correspond to band of CH2 groups, while the second one to -O-CH3 or two bands of aldehyde groups; when the activated ratio increases then these two bands tend to disappear (Ahmad et al. 2007). The peaks at 2,300 and 2,370 cm−1 are characteristic of the C ≡ C stretching vibration of alkyne groups (Gurten et al. 2012); however, they are not present in the spectra of the ACC 75%. The bands appearing around 1,715 cm−1 and 1,600 cm−1 correspond to the C = O of carbonyl-containing groups (ketones, aldehydes, lactones, and carboxyl groups) (Gupta et al. 2017). The peak at 1,556 cm−1 is a characteristic of the C = O stretch of the carbonyl group in a quinone and represents the γ-pyrone structure with strong vibrations from a combination of C = O and C-C (Zheng et al. 2014). The broad band at 1,300–500 cm−1 was assigned to the C–O stretching and O–H bending modes such as phenols, alcohols, esters and carboxylic acids appearing in the carbons activated with H3PO4 (50 and 75%) (Rangel-Mendez & Streat 2002). The presence of hydroxyl groups of phenolic and carboxylic gives an acidic character to activated carbon surface whereas carbonyl and quinone groups confer a basic character to the adsorbent surface (Ahmad et al. 2007).
The most important changes introduced by the increase of the acid concentration are the development of the oxygen-containing functional groups including acidic hydroxyl, carboxyl and phenolic hydroxyl on the carbon surface. This result is confirmed by the decrease in pHPZC when the impregnation ratio increases (Table 1).
Adsorption of clofibric acid
Effect of impregnation ratio on adsorption amount of clofibric acid
The effect of impregnation ratio on the clofibric acid (CA) adsorption onto ACCs is presented in Table 1. A higher elimination of CA is observed when the impregnation ratio is increased from 0 to 50%. This may be attributed to the increase in adsorbent surface area, microporosity development and availability of more adsorption sites resulting from the increase of impregnation ratio. For an impregnation ratio greater than 50%, a decrease of CA adsorption is observed, which could be attributed to the decrease of surface area and pore volume. Thus, 50% seems to represent the optimal impregnation ratio that leads to a maximum adsorption of the CA from the aqueous solutions. This result is probably due to the homogeneous distribution of the pore size with more than 99% of microporosity. All described adsorption experiments in the following were conducted with activated carbon prepared from cotton cloth waste impregnated with 50% chemical ratio.
Effect of pH on the removal of clofibric acid
One of the main factors influencing the adsorption process is the pH of the effluents. Tests for pH values between 3 and 9 were performed to study its effect on the elimination of CA by ACC 50%. The results shown in Figure 4(a) indicate that the maximum uptake of CA is obtained at pH 3. The same value for the adsorption of CA onto other adsorbents was reported in the literature (Mestre et al. 2010; Neng et al. 2011; Hasan et al. 2012; Liu et al. 2013). CA is a weak electrolyte (pKa ∼ 3.6), so its ionization is strongly dependent on the pH. The speciation plot of CA is reported by Mestre et al. (2010). For a pH lower than 2, almost all the CA molecules are undissociated, at pH 3.6 around 50% of molecules are already in the dissociated form and at pH greater than 5, the dissociated form represents more than 99%. The pHPZC of ACC 50% is 3.7. Thus, the surface carries positive charge at pH solution lower than 3.7, neutral for pH = pHPZC and negative charge for pH solution greater than 3.7. The increase of the amount of CA adsorbed at lower pH is attributed to the anionic and molecular forms of the CA and the positive surface charge of the ACC 50%. Therefore, the anionic form of CA is attracted by the positive charges of the ACC 50%, while the molecular form of CA is linked to the adsorbent surface through dispersion forces and dipole attraction (Boudrahem et al. 2017).
When the pH increases (pH > pHPZC), the activated carbon surface is negatively charged and the anionic form of CA becomes progressively more important. This effect leads to the electrostatic repulsion between the ACC 50% and the CA molecules.
Effect of contact time and clofibric acid concentration
The effect of contact time on the adsorption of CA onto ACC 50% is shown in Figure 4(b). Initially, due to the availability of a large number of vacant surface sites, a rapid adsorption process was observed. This step is followed by a slower adsorption period before equilibrium is reached. Figure 4(b) shows that an increase in the initial CA concentration leads to an increase of the adsorption capacity of CA by ACC 50%. The amount absorbed at equilibrium increases as the initial AC concentration increases. It increases from 9.98 to 83 mg/g when the initial concentration is increased from 10 to 100 mg/L. This is a result of the increase in the driving force of the concentration gradient, with an increase in the CA initial concentration.
The FTIR spectra of ACC 50% before and after adsorption of CA (CA-ACC 50%) are shown in the Supplementary Figure 2. The spectra of CA-ACC 50% and the ACC 50% showed practically the same absorption bands because of the presence of functional groups, such as phenyl and carboxyl groups both on the CA molecule and on the activated carbon surface. The difference is the intensity of the peaks at 1,023 cm−1, and 1,556 cm−1 which are attributed to C-O (Zheng et al. 2014) and C = O (Kyzas & Deliyanni 2015), respectively. These bands are more intense in the spectrum corresponding to CA-ACC 50%, indicating the adsorption of CA onto ACC 50%.
Adsorption kinetics
The Lagergren pseudo-first-order and pseudo-second-order kinetic models
. | . | Pseudo-first-order kinetics . | Pseudo-second-order kinetics . | ||||
---|---|---|---|---|---|---|---|
C0 (mg/L) . | qe exp (mg/g) . | qe cal (mg/g) . | k1 (1/min) . | R2 . | qe cal (mg/g) . | k2 (g/mg min) . | R2 . |
100 | 83.33 | 77.62 | 0.05 | 0.874 | 83.77 | 0.002 | 0.985 |
70 | 63.00 | 30.00 | 0.02 | 0.562 | 62.00 | 0.003 | 0.987 |
50 | 43.45 | 15.04 | 0.02 | 0.544 | 43.00 | 0.005 | 0.991 |
30 | 26.23 | 14.22 | 0.0028 | 0.59 | 24.43 | 0.008 | 0.960 |
10 | 9.98 | 5.65 | 0.0006 | 0.522 | 9.65 | 0.014 | 0.970 |
. | Intra-particle diffusion . | Diffusion–chemisorption . | |||||
C0 (mg/L) . | kd1 . | R2 . | kd2 . | R2 . | KDC . | qe . | R2 . |
100 | 7.928 | 0.944 | 1.310 | 0.956 | 37.04 | 100 | 0.993 |
70 | 7.158 | 0.997 | 0.793 | 0.841 | 33.33 | 76.92 | 0.991 |
50 | 4.522 | 0.995 | 0.737 | 0.987 | 23.25 | 52.63 | 0.997 |
30 | 2.169 | 0.990 | 0.534 | 0.976 | 15.63 | 29.41 | 0.995 |
10 | 0.808 | 0.976 | 0.212 | 0.980 | 4.62 | 11.36 | 0.999 |
. | . | Pseudo-first-order kinetics . | Pseudo-second-order kinetics . | ||||
---|---|---|---|---|---|---|---|
C0 (mg/L) . | qe exp (mg/g) . | qe cal (mg/g) . | k1 (1/min) . | R2 . | qe cal (mg/g) . | k2 (g/mg min) . | R2 . |
100 | 83.33 | 77.62 | 0.05 | 0.874 | 83.77 | 0.002 | 0.985 |
70 | 63.00 | 30.00 | 0.02 | 0.562 | 62.00 | 0.003 | 0.987 |
50 | 43.45 | 15.04 | 0.02 | 0.544 | 43.00 | 0.005 | 0.991 |
30 | 26.23 | 14.22 | 0.0028 | 0.59 | 24.43 | 0.008 | 0.960 |
10 | 9.98 | 5.65 | 0.0006 | 0.522 | 9.65 | 0.014 | 0.970 |
. | Intra-particle diffusion . | Diffusion–chemisorption . | |||||
C0 (mg/L) . | kd1 . | R2 . | kd2 . | R2 . | KDC . | qe . | R2 . |
100 | 7.928 | 0.944 | 1.310 | 0.956 | 37.04 | 100 | 0.993 |
70 | 7.158 | 0.997 | 0.793 | 0.841 | 33.33 | 76.92 | 0.991 |
50 | 4.522 | 0.995 | 0.737 | 0.987 | 23.25 | 52.63 | 0.997 |
30 | 2.169 | 0.990 | 0.534 | 0.976 | 15.63 | 29.41 | 0.995 |
10 | 0.808 | 0.976 | 0.212 | 0.980 | 4.62 | 11.36 | 0.999 |
kd1 and kd2 in (g/mg min).
On the basis of the correlation coefficients and the difference between (qe,exp) and (qe,cal) (Table 2), the adsorption for the CA onto ACC 50% is better described by the pseudo-second-order model, which was developed basically based on the assumption that the rate-limiting step may be chemisorption, promoted by either valency forces, through sharing of electrons between adsorbent and adsorbate, or covalent forces through the exchange of electrons between the involved parts.
Intra-particle diffusion model
Generally, if the plot of qt versus gives a straight line, the adsorption process is controlled by intraparticle diffusion. Otherwise, the adsorption process is influenced by two or more diffusion steps. The intraparticle diffusion curve for the adsorption of CA onto ACC 50% is shown in Figure 5, and the model parameters are summarized in Table 2.
As shown in Figure 5, the plot reveals two straight lines and that the first straight line does not pass through the origin. This result indicates that the adsorption of CA onto the ACC 50% is not only controlled by intraparticle diffusion. Other diffusion processes could be involved. Further research is therefore needed and is discussed in the following section.
Diffusion–chemisorption model
It can be found that the curve fitted well with the diffusion–chemisorption model (Table 2), which demonstrates that the adsorption of CA onto ACC 50% can be described using the diffusion–chemisorption model. On the basis of this outcome, it can be concluded that diffusion–chemisorption is the main controlling step.
Adsorption isotherms and modeling
Adsorption isotherms provide information about the capacity of the adsorbent and the nature of solute–sorbent interaction. The isotherm data were treated according to five isotherm models: Freundlich, Langmuir, Sips, Redlich–Peterson and Generalized model (Table 3).
Isotherms . | References . | Constants . | . |
---|---|---|---|
Freundlich | Boudrahem et al. (2015), Huang & Su (2010) | KF (L1/n/mg1/n) | 25.8 |
1/n | 0.46 | ||
R² | 0.97 | ||
n | 2.22 | ||
Langmuir | Boudrahem et al. (2015), Huang & Su (2010) | qm (mg/g) | 49.94 |
KL (L/mg) | 1.89 | ||
R² | 0.494 | ||
Sips | Brdar et al. (2012), Boudrahem et al. (2015) | qm (mg/g) | 61.82 |
KL (L1/n/mg1/n) | 0.93 | ||
1/n | 0.77 | ||
R² | 0.544 | ||
n | 1.29 | ||
Redlich–Peterson | Brdar et al. (2012), Boudrahem et al. (2015) | AR (L/g) | 69.03 |
KF ( L1/n/mg1/n) | 0.99 | ||
1/n | 0.98 | ||
R² | 0.83 | ||
n | 1.02 | ||
Generalized model | Brdar et al. (2012), Boudrahem et al. (2015) | qm (mg/g) | 69.7 |
KL (L1/n/mg1/n) | 0.95 | ||
1/n | 0.87 | ||
R² | 0.76 | ||
n | 1.15 |
Isotherms . | References . | Constants . | . |
---|---|---|---|
Freundlich | Boudrahem et al. (2015), Huang & Su (2010) | KF (L1/n/mg1/n) | 25.8 |
1/n | 0.46 | ||
R² | 0.97 | ||
n | 2.22 | ||
Langmuir | Boudrahem et al. (2015), Huang & Su (2010) | qm (mg/g) | 49.94 |
KL (L/mg) | 1.89 | ||
R² | 0.494 | ||
Sips | Brdar et al. (2012), Boudrahem et al. (2015) | qm (mg/g) | 61.82 |
KL (L1/n/mg1/n) | 0.93 | ||
1/n | 0.77 | ||
R² | 0.544 | ||
n | 1.29 | ||
Redlich–Peterson | Brdar et al. (2012), Boudrahem et al. (2015) | AR (L/g) | 69.03 |
KF ( L1/n/mg1/n) | 0.99 | ||
1/n | 0.98 | ||
R² | 0.83 | ||
n | 1.02 | ||
Generalized model | Brdar et al. (2012), Boudrahem et al. (2015) | qm (mg/g) | 69.7 |
KL (L1/n/mg1/n) | 0.95 | ||
1/n | 0.87 | ||
R² | 0.76 | ||
n | 1.15 |
qm = maximum adsorption capacity; KL = Langmuir constant; KF and n = Freundlich constants; Kf and AR = Redlich–Peterson constants.
Figure 6 shows the experimental data for the adsorption of CA on ACC 50% at 20 °C and the predicted equilibrium curves. According to the classification of Giles et al. (1974), the isotherm is of L type, suggesting that ACC 50% has a high affinity for CA and there is no competition between the solvent and CA for site occupation (Ayranci & Hoda 2005).
The obtained isotherm parameters and R2 (Table 4) were determined by using a non-linear regression method. This mathematical technique is a rigorous method that uses the model equation in its original form.
Adsorbent . | qmax (mg/g) . | C0 (mg/L) . | pH . | T(K) . | SBET (m2/g) . | References . |
---|---|---|---|---|---|---|
Cork-based activated carbon | 128–257 | 20–200 | 3.6 | 303 | 891–1,060 | Mestre et al. (2010) |
Metal–organic framework MIL-101 | 315 | 50–150 | 5 | 298 | 3,014 | Hasan et al. (2013) |
Rice straw biosorbent RSB | 126.3 | 5–100 | 2 | 301 | / | Liu et al. (2013) |
Mesoporous silica SBA-15 | 0.07 | 0.01–0.3 | 3 | 398 | 950 | Bui & Choi (2009) |
Raspberry-derived mesoporous carbon-tubules | 9.75 | 10–20 | 4 | 303 | 224 | Dubey et al. (2014) |
ACC 50% | 83.33 | 5–100 | 3 | 293 | 1,150 | Present study |
Adsorbent . | qmax (mg/g) . | C0 (mg/L) . | pH . | T(K) . | SBET (m2/g) . | References . |
---|---|---|---|---|---|---|
Cork-based activated carbon | 128–257 | 20–200 | 3.6 | 303 | 891–1,060 | Mestre et al. (2010) |
Metal–organic framework MIL-101 | 315 | 50–150 | 5 | 298 | 3,014 | Hasan et al. (2013) |
Rice straw biosorbent RSB | 126.3 | 5–100 | 2 | 301 | / | Liu et al. (2013) |
Mesoporous silica SBA-15 | 0.07 | 0.01–0.3 | 3 | 398 | 950 | Bui & Choi (2009) |
Raspberry-derived mesoporous carbon-tubules | 9.75 | 10–20 | 4 | 303 | 224 | Dubey et al. (2014) |
ACC 50% | 83.33 | 5–100 | 3 | 293 | 1,150 | Present study |
The values of the correlation coefficients (R2) suggest that the Freundlich model provides a good fit to the experimental data. The magnitude of the exponent n gives an indication on the favorability of adsorption. It is generally stated that n values in the range 2–10 represent good adsorption characteristics, while from 1 to 2 it is moderately difficult and less than 1, it is poor (Boudrahem et al. 2015). The fitting results show that the value of n is superior to 2 (2.22), indicating that the adsorption is good.
In order to check the validity of these models, it is interesting to recalculate the adsorbed amount using the calculated constant parameters determined by the non-linear forms. The simulated curves at 20 °C determined using Freundlich, Langmuir, Sips, Redlich–Peterson and the Generalized models are given in Figure 6. The results confirm that Freundlich's model is the one that best describes the adsorption isotherm.
As shown in Table 4, the ACC 50% can be used as an adsorbent with relatively high efficiency for CA removal and provides a higher surface area in comparison to other adsorbents.
It is important to highlight that a direct comparison between the adsorption capacities of various adsorbents is not possible due to the different operating conditions and the synthesis cost.
CONCLUSION
This study shows that cloth waste activated with H3PO4 may be used to prepare high microporous activated carbons. The adsorbents prepared keep the fiber form of the starting precursor and their characteristics depend on the impregnation ratio (mass of H3PO4/mass of precursor).
The maximum values for the microporosity (99.43%) and the SBET (1,150 m2/g) are obtained with 50% impregnation ratio. Beyond a value of 50%, the increase of impregnation ratio decreases SBET and improves the formation of the mesoporous structure. Under the optimal conditions, 50% impregnation ratio and thermal treatment under N2 flow at 600 °C during 60 min, the activated carbon prepared exhibits an excellent adsorption performance.
The adsorption kinetic of CA onto ACC 50% was well described by the pseudo-second-order model and diffusion–chemisorption is the dominant process controlling the adsorption of CA onto ACC 50%.
The adsorption kinetic of CA onto ACC 50% was well described by the pseudo-second-order model and the intraparticle diffusion model revealed that the adsorption of CA onto the ACC 50% is not only controlled by intraparticle diffusion. Application of the diffusion-chemisorption model confirms that diffusion and chemisorption are the dominant steps controlling the adsorption of CA onto ACC 50%.
Furthermore, the Freundlich model is the one that best describes the adsorption isotherm and, since n > 2 (n = 2.22), then the sorption process of CA onto ACC 50% is favorable. The amount of CA removed from a 100 mg/L CA solution is 83 mg/g and is total from a 10 mg/L CA solution. Therefore, cotton cloth residue is potentially promising for the preparation of economic and efficient activated carbons for the removal of clofibric acid from wastewater.
DATA AVAILABILITY STATEMENT
All relevant data are included in the paper or its Supplementary Information.