Effective and selective removal of aromatic amines from water by Cu 2+ -treated chitosan/alumina nanocomposite

Abstract

The pollution of natural waters with aromatic amines is of serious environmental concern. The aim of this work was to enhance the ability of chitosan for selective and effective removal of aromatic amines from natural waters. The chitosan was modified with the inclusion of nano-Al₂O₃ and then the impregnation with Cu²⁺ solution. The study on the chemical structure of the modified adsorbent by Fourier transform infrared spectroscopy showed the formation of a complex between amine groups of the chitosan and Cu(II) on the adsorbent surface. It was found that the modified adsorbent, Cu–chitosan/nano-Al₂O₃, has more porous surface morphology and so more specific surface area available for adsorption. The adsorption properties of the modified adsorbent toward aniline and dimethyl aniline as typical aromatic amines were investigated using kinetics and isotherm studies at room temperature. The adsorption equilibrium data were fitted well by the Freundlich isotherm model. The kinetic data exhibited a non-linear fit to pseudo-second-order model for both aniline and dimethyl aniline. The adsorption capacity of Cu–chitosan/nano-Al₂O₃ was much higher than that of neat chitosan and chitosan/nano-Al₂O₃. The adsorbent had high selectivity for adsorption of aniline and dimethyl aniline in the presence of chloride, nitrate, sulfate, phosphate, and carbonate as natural waters common anions. The modified adsorbent exhibited good regeneration ability. The results showed that the introduced adsorbent can be employed as an effective chitosan-based adsorbent for selective removal of aromatic amines from natural waters.

Keywords

Pollution aromatic amines biopolymer adsorption water

Introduction

The pollution of natural waters by synthetic organic materials is a serious environmental problem (Schwarzenbach et al., 2010; Vörösmarty et al., 2010). Aromatic amines, a class of organic pollutants, can enter bodies of water from many industries associated with pharmaceuticals, pesticides, dyestuffs, petrochemicals, cosmetics, textiles, paper, plastics, and agrochemical production (Pinheiro et al., 2004). The occurrence of these materials in natural waters even at low concentrations has marked negative impact on living organisms and human health (Liu et al., 2012). Furthermore, these compounds are hard to decompose by natural chemical and biological processes. Accordingly, aromatic amines are classified as refractory organic materials by U.S. Environmental Protection Agency (USEPA) (Sun et al., 2009; Zhao et al., 2002) and Europe’s Economic Community (EEC) (Li and Jin, 2009). Therefore, removal of aromatic amines from water is of great importance.

Various treatment methods such as oxidation by ozone (Qi et al., 2002), membrane processes (Ho et al., 1982; Sarode et al., 2001), dialysis (Klein et al., 1972), reverse osmosis (Gómez et al., 2009; Hidalgo et al., 2011), photocatalytic degradation (Kamble et al., 2003), biodegradation (Gheewala and Annachhatre, 1997), and adsorption (Datta et al., 2003) are commonly applied to remove aromatic amines from water. Among these methods, adsorption is considered as a more simple and cost-effective technique for removal of contaminants from water. Various adsorbents such as activated carbon powders and fibers (Chai et al., 2007; Han et al., 2006), carbon nanotubes (Yang et al., 2008), iron oxide magnetite nanoparticles (Bettini et al., 2015b; Kakavandi et al., 2013), montmorillonite (Essington, 1994), Cr-bentonite (Zheng et al., 2009), MCM-41 mesoporous material (Eimer et al., 2003), tetraborate-modified Kaolinite (Unuabonah et al., 2008), sulfonic-functionalized styrene-divinyle benzene co-polymer (Jianguo et al., 2005), and methacrylic acid-modified silica gel (An et al., 2009) have been developed to remove aromatic amines from water.

Biomaterials based on renewable resources such as chitosan and cellulose are of great interest as potential adsorbents for removal of various contaminants from water (Annadurai et al., 2002; Bettini et al., 2014; Crini and Badot, 2008; Gerente et al., 2007). Chitosan, a natural biopolymer, is used extensively as an adsorbent for removal of heavy metals and dyes from contaminated waters (Ngah et al., 2011). The presence of a large number of amino and hydroxyl functional groups as active adsorption sites in the chitosan structure, and its non-toxicity, biodegradability, abundance and low cost, make it a promising adsorbent for aquatic systems (Kumar, 2000). Chitosan-based adsorbents have been also used for removal of organic contaminants from water (Ali et al., 2012; Crisafully et al., 2008). To the best of our knowledge, there is no published study about the removal of aromatic amines from water using chitosan-based adsorbent. Considering chemical structure of chitosan and aromatic amines, a weak interaction, and thus a low adsorption capacity is expected due to the presence of electron-rich functional groups in both chitosan and aromatic amines structures. Therefore, we decided to develop a chitosan-based adsorbent for effective and selective removal of aromatic amines from water.

In the present study, a chitosan-based adsorbent was prepared and employed as adsorbent for the removal of aromatic amines. The porosity of the chitosan beads increased with the inclusion of nano-Al₂O₃ to obtain chitosan/Al₂O₃ nanocomposite. The nanocomposite was treated with Cu²⁺ solution to form Cu–chitosan/Al₂O₃ nanocomposite. It should be noted that metallic ions such as Cu²⁺ can be chelated by amine functional groups of chitosan. The main reason for this treatment is that amine containing compounds such as aromatic amines have great tendency to Cu(II) on the adsorbent surface (Le Cocq et al., 2012). Indeed, the condition for chemical adsorption of aromatic amines is provided by applying this modification. The adsorption behavior of aniline (An) and N,N-dimethy aniline (DMA) as predominant aromatic amines in contaminated waters was investigated. Chitosan and chitosan/Al₂O₃ nanocomposite were also prepared and their properties and behaviors were compared with those of Cu–chitosan/Al₂O₃ nanocomposite.

Experimental

Materials

Medium molecular weight chitosan with deacetylation degree of 85–95% was purchased from Sigma-Aldrich Chemicals. The nano-filler, γ-Al₂O₃ with average particle size of 20–30 nm supplied by TECNAN Nanoproducts was employed for adsorbents preparation. All other chemicals including aniline, N,N-dimethyl aniline, oxalic acid, hydrochloric acid, and sodium hydroxide were of analytical grade and purchased from Sigma-Aldrich Chemicals. Distilled water was used for preparation of all solutions.

Preparation of adsorbents

In order to prepare chitosan/nano-Al₂O₃ beads, γ-Al₂O₃ nanoparticles were dried in an oven for 6 h at 100℃. The dried nano-filler was mixed with oxalic acid solution for 5 h at room temperature. The acid-treated nano-filler was then filtered, washed with water, and dried in an oven at 80℃ for 3 h. About 10 g of medium molecular weight chitosan was slowly mixed with 200 mL of 10 wt.% oxalic acid solution to form a viscous mixture. The mixture, then, was diluted with 200 mL distilled water and heated to 50℃ to facilitate mixing. About 0.4 g of acid-treated nano-Al₂O₃ was added to the mixture and stirred for 24 h. Excess oxalic acid in the mixture was neutralized with NaOH solution to settle chitosan/nano-Al₂O₃ beads. The chitosan/nano-Al₂O₃ beads were filtered, washed with water completely, and dried in an oven at 60℃ for three days.

In order to prepare Cu-bonded chitosan/Al₂O₃ nanocomposite, the chitosan/nano-Al₂O₃ beads were mixed with CuSO₄ solution for 2 h. The concentration of CuSO₄ and chitosan/nano-Al₂O₃ beads in the mixture was selected based on maximum adsorption capacity of the prepared adsorbent. In the optimum condition, the molar ratio of Cu²⁺ to glucosamine groups of the adsorbent was 1.3. Then, the modified adsorbent was filtered, washed with water and dried.

All chemicals employed for preparation of the adsorbent are abundant and commercially available that enables the preparation of the adsorbents with reasonable cost.

Characterization of adsorbents

Surface morphology of adsorbents was studied using scanning electron microscopy (SEM) and atomic force microscopy (AFM). A Vega Tescan SEM (Czech Republic) and a Dual scope C-21 AFM from DME Instruments (Denmark) were employed for morphological studies. Fourier transform infrared (FTIR) spectra of adsorbents were recorded on Bruker Tensor 27 spectrometer (Germany). X-ray diffraction (XRD) patterns of specimens were obtained using a Siemens D-500 X-ray diffractometer (Germany) with wavelength, λ = 1.54 Å (Cu–K_α), at a tube voltage of 25 kV, and a tube current of 30 mA.

The surface area of all adsorbents was determined on the basis of Brunauer–Emmett–Teller (BET) adsorption/desorption isotherm (Lowell and Shields, 2013) using a Quantachrome ChemBET-3000 instrument by means of adsorption/desorption of pure nitrogen gas at 77 k.

To determine pH at the point of zero charge (pH_pzc), batch equilibration method was applied (Lataye et al., 2006). A certain amount of each adsorbent (0.2 g) was introduced into a known volume (100 mL) of 0.1 mol/L KNO₃ solution. The ionic strength of solutions in all experiments was kept constant by using of KNO₃ as inert background electrolyte. The pH values of KNO₃ solutions were adjusted from 4 to 10 by addition of 0.1 M HCl or NaOH solutions. The initial pH (pH_i) of the solutions was determined exactly and recorded. Suspensions were allowed to equilibrate for 48 h in a shaker at room temperature. Then, the suspensions were filtered and the pH values of the filtrates (pH_f) were measured. The pH_pzc for the adsorbents was determined by plotting ΔpH (pH_i–pH_f) versus pH_i. The point of intersection with pH_i-axis is considered as pH_pzc.

Batch adsorption experiments

All batch adsorption studies were performed with aqueous solutions of aniline (An) and dimethylaniline (DMA) with certain concentrations (40, 80, 120, 160, and 200 mg/L). The pH of solutions was adjusted in desired amount using 0.1 M HCl or NaOH solutions. Equilibrium isotherm measurements were carried out by constant solution volume of 50 mL and adsorbent amount of 0.05 g, and varying amounts of An or DMA concentrations at room temperature. The solutions of aromatic amines in the presence of adsorbents were allowed to attain equilibrium by stirring at 100 r/min in a water bath for 4 h. After equilibration, adsorbents were filtered from solutions and filtrates were analyzed for An or DMA.

The amount of An and DMA adsorbed (mg) per unit mass of the adsorbent (g), q_e, was obtained by using the following equation

q_{e} = \frac{(C_{i} - C_{e}) V}{m}

(1)

where C_i and C_e are initial and equilibrium concentrations in mg/L, m is the dry mass of adsorbent in gram and V is volume of solution in liters.

Kinetic studies were carried out by measurement of An or DMA concentration at certain time intervals to determine the rate of aromatic amines removal by adsorbents with the initial An and DMA concentration of 40 mg/L for all adsorbents.

Analytical method

The concentration of the aromatic amines in the aqueous solutions was analyzed using UV spectrophotometry (Łabudzińska and Gorczyńska, 1994; Pinheiro et al., 2004) at the wavelength of maximum absorbance (280–300 nm). Measurements were carried out by using a Shimadzu UV-1800 spectrophotometer.

Interfering effect

In order to determine the interfering effect of common natural water anions including chloride, nitrate, sulfate and phosphate on the aromatic amines adsorption, the experiments were performed with 40 mg/L An or DMA solutions containing 400 mg/L of the interfering anion in the form of its sodium salt.

Desorption and regeneration

To investigate the regeneration ability of Cu–chitosan/nano-Al₂O₃ adsorbent, it was reused in repeated adsorption–desorption cycles and its capacity was determined after each cycle. The adsorption experiment was carried out using 0.05 g of the adsorbent in 50 mL solutions with An and DMA concentration of 40 mg/L. For desorption experiment, the loaded adsorbent was filtered and washed with distilled water. Then, it was placed in 50 mL of Cu²⁺ solution (10 g/L) and stirred at 100 r/min for 2 h at room temperature. Afterward, the adsorbent was filtered and washed with distilled water completely. The regenerated adsorbent was dried in an oven at 60℃ for reuse in the next cycle.

Results and discussion

Morphological properties of adsorbents

The surface morphology of the adsorbents was characterized by using SEM. Micrographs of chitosan, chitosan/nano-Al₂O₃, and Cu–chitosan/nano-Al₂O₃ beads are shown in Figure 1. It is obvious that the inclusion of nano-Al₂O₃ in the chitosan matrix leads to a more porous surface morphology for chitosan/nano-Al₂O₃ and Cu–chitosan/nano-Al₂O₃ adsorbents compared to neat chitosan beads. Increased roughness of chitosan/nano-Al₂O₃ and Cu–chitosan/nano-Al₂O₃ adsorbents may provide more surface area for aromatic amines adsorption.

Figure 1.

SEM micrographs of (a) neat chitosan, (b) chitosan/nano-Al₂O₃ and (c) Cu–chitosan/nano-Al₂O₃.

To further verify the results of SEM studies, the specific surface area was determined for all adsorbents using BET isotherm for nitrogen adsorption/desorption as shown in Figure 2. The specific surface area for chitosan, chitosan/nano-Al₂O₃ and Cu–chitosan/nano-Al₂O₃ was 6.1, 41, and 31 m²/g, respectively. The surface area for nano-Al₂O₃ containing adsorbents was much higher than that of pristine chitosan. The presence of nano-Al₂O₃ may induce the formation of more porous surface morphology as confirmed by SEM imaging. The modified adsorbent, Cu-chitosan/nano-Al₂O₃, exhibited lower surface area compared to chitosan/nano-Al₂O₃ adsorbent. The bonding of Cu²⁺ to chitosan on the adsorbent surface may reduce the surface area somewhat.

Figure 2.

N₂ adsorption/desorption isotherms at 77 k for neat chitosan, chitosan/nano-Al₂O₃ and Cu–chitosan/nano-Al₂O₃.

Figure 3 illustrates AFM phase image of Cu–chitosan/nano-Al₂O₃ adsorbent. An advantage of AFM imaging is the relatively high contrast between soft and hard phases. There is a difference between stiffness of chitosan biopolymer and crystalline alumina regions of Cu–chitosan/Al₂O₃ nanocomposites, and it is sufficient for contrast development. When the AFM tip scans across the alumina phase, it works in repulsive regime with the bright phase contrast, whereas the dark contrast represents the soft chitosan phase, where the tip works in attractive regime. The bright spherical particles in the figure correspond to nano-Al₂O₃ phases dispersed in the dark polymeric matrix. The images reveal a relatively uniform dispersion of alumina nanoparticles in the chitosan matrix with little agglomeration which confirms the formation of chitosan-matrix nanocomposites.

Figure 3.

AFM phase images of Cu–chitosan/nano-Al₂O₃; scan sizes: (a) 1 µm and (b) 500 nm.

XRD studies of adsorbents

Figure 4 presents XRD patterns for neat chitosan, nano-Al₂O₃, chitosan/nano-Al₂O₃, and Cu–chitosan/nano-Al₂O₃. For neat chitosan, two peaks around 2θ = 7.8° and 10.9° relate to the hydrated crystalline structure of chitosan and the characteristic peak at 2θ = 19.9° indicates the amorphous structure of chitosan. For the nano-Al₂O₃ sample, all peaks in the XRD pattern match with standard value of γ-Al₂O₃ crystalline phase according to the Joint Committee on Powder Diffraction Standards (JCPDS) file No. 29–63. Furthermore, the broadening of XRD peaks indicates the nanocrystallinity of the γ-Al₂O₃ sample. The most prominent peaks in the γ-Al₂O₃ diffractogram appeared at 2θ = 45.6° (400 reflection) and 66.9° (440 reflection) which correspond with the values mentioned in the literature (Ogawa et al., 1984; Wang et al., 2005). By analyzing the XRD pattern of chitosan/nano-Al₂O₃ sample, the main crystalline phases were identified as chitosan, nano-Al₂O₃, and Na₂C₂O₄. The diffraction peaks for chitosan were the same as those of neat chitosan with little shifts in peaks positions. The reflections for sodium oxalate appeared at 2θ = 31.63°, 34.43°, 38.54°, and 30.82°. The presence of oxalate phase in chitosan/nano-Al₂O₃ structure is expected as it has been reported that carboxylate group of oxalate has an electrostatic interaction with amine groups of chitosan (Boddu et al., 2003). Due to the nano-size nature and low concentration of nano-Al₂O₃ in chitosan/nano-Al₂O₃ composition, the characteristic peaks of nano-Al₂O₃ are of low intensities which are covered by reflection peaks of other phases. In the Cu–chitosan/nano-Al₂O₃ sample, copper ammine sulfate, Cu(NH₃)₂SO₄, and copper oxalate, Cu(C₂O₄) were also identified from its diffractogram in addition to chitosan and alumina phases. The diffraction peak at 2θ = 23° is associated with (NH₃)₂CuSO₄ phase. The reflection peaks at 2θ = 23°, 35.5°, and 39° correspond to Cu(C₂O₄) phase. The peak appeared at 2θ = 30° relates to sodium carbonate or bicarbonate phases. The presence of Cu(NH₃)₂SO₄ phase in the sample confirms the formation of a bond between chitosan and Cu(II) on the adsorbent surface.

Figure 4.

XRD patterns of neat chitosan, nano-Al₂O₃, chitosan/nano-Al₂O₃ and Cu–chitosan/nano-Al₂O₃.

FTIR studies

FTIR spectrometry is a useful technique to identify the presence of certain functional groups on a material surface as a specific chemical bond often has a unique energy adsorption band (Bettini et al., 2014, 2015a). Therefore, chemical properties of three types of adsorbents were evaluated by FTIR spectrometry as shown in Figure 5. The most important characteristic bands for pristine chitosan can be assigned as follows: 3400–3200 cm⁻¹ (a broad band corresponds to –OH and –NH stretching vibration), 2920 and 2865 cm⁻¹ (stretching vibration of aliphatic C–H bonds), 1659 cm⁻¹ (bending vibration of –NH in primary amines), 1382 cm⁻¹ (deformation vibration of –NH in primary amines) and 1081 cm⁻¹ (stretching vibration of –CO in –COH). Compared to the spectrum of neat chitosan, two new bands at 775 and 515 cm⁻¹ appeared in the spectrum of chitosan/nano-Al₂O₃ which correspond to stretching and bending vibration of Al–O bond. The presence of characteristics bands of chitosan in chitosan/nano-Al₂O₃ spectrum without significant changes indicates that the incorporation of nano-Al₂O₃ into chitosan bead has no significant effect on chitosan structure. In the spectrum of Cu–chitosan/nano-Al₂O₃, the noticeable point is the absence of a broad band between 3400 and 3200 cm⁻¹ observed for chitosan and chitosan/nano-Al₂O₃. This indicates the formation of complexes between amine and hydroxyl groups on the chitosan surface and copper ions.

Figure 5.

FTIR spectra of (a) chitosan, chitosan/nano-Al₂O₃ and Cu–chitosan/nano-Al₂O₃ before adsorption and (b) Cu–chitosan/nano-Al₂O₃ after adsorption.

To understand the nature of aromatic amines adsorption on Cu–chitosan/nano-Al₂O₃, FTIR spectra of the modified adsorbent after adsorption of An and DMA were also obtained as presented in Figure 5. It is noticeable that the two spectra are so similar. After adsorption of An and DMA on the modified adsorbent, two major changes can be seen in the related spectra. One is a significant increase of the intensity of bands around 1650–1400 cm⁻¹ and 3400–3200 cm⁻¹ assigned to bending vibration of –NH groups in primary amines and stretching vibration of –OH and –NH groups of chitosan in the adsorbent composition, respectively. It may be due to the formation of a complex between aromatic amines and Cu(II) on the adsorbent surface and weakening of N–Cu and O–Cu bonds and so strengthening of N–H and O–H groups. Another is the appearance of new peaks at 1620 and 1363 cm⁻¹ corresponding to stretching vibration of C–C bond of benzene ring, and at 1319 cm⁻¹ corresponding to stretching vibration of C–N bond in aromatic amines. The emergence of these new peaks in the FTIR spectra can be attributed to the presence of aromatic amines adsorbed on the modified adsorbent. Briefly, the FTIR results suggest that the nature of aromatic amines adsorption on Cu–chitosan/nano-Al₂O₃ is based on the chemical bonding between aromatic amines and Cu(II) on the adsorbent surface.

Adsorption isotherms

Adsorption isotherms describe the equilibrium distribution of an adsorbate between a solid phase as adsorbent and a liquid phase at constant temperature and provide a quantitative measure of the adsorption efficiency and the nature of adsorption. The most prevalent isotherm models, namely Langmuir and Freundlich isotherms (Foo and Hameed, 2010) were examined in the present study. Langmuir isotherm can be expressed as:

q_{e} = q_{m} K_{L} C_{e} / (1 + K_{L} C_{e})

(2)

where q_e (mg/g) is the adsorption capacity at equilibrium, C_e (mg/L) is the equilibrium concentration of the amines in solution, K_L (L/mg) is the Langmuir constant corresponding to the free energy of adsorption, and q_m (mg/g) is the maximum adsorption capacity according to monolayer coverage of the adsorbent surface by aromatic amines.

The Freundlich isotherm is defined by the following equation

q_{e} = K_{F} (C_{e}) 1 / n

(3)

where K_F ((mg/g)/(mg/L)^1/n) is the Freundlich constant indicating the relative adsorption capacity and n is another Freundlich constant showing the adsorption intensity. The value of 1/n indicates the type of isotherm to be irreversible (1/n = 0), desired (0 < 1/n < 1) and undesired (1/n > 1).

The experiments for studying the adsorption isotherms were conducted using aqueous solution of the aromatic amines with initial concentrations varying from 40 to 200 mg/L at neutral pH range (pH = 6.5–7.0), adsorption time of 4 h at room temperature. The data for adsorption of An and DMA by three types of the adsorbents were fitted to non-linear model of Langmuir and Freundlich isotherms as shown in Figures 6 and 7, respectively. The fitting parameters along with the isotherm constants for both models are given in Table 1. The fitting parameters, correlation coefficient (R²), sum of square errors (SSE) and root mean square error (RMSE), indicate that the adsorption data are in relatively good agreement with both isotherm models. For the modified adsorbent, Freundlich model with higher R² and lower SSE and RMSE values seems to be better model to describe the adsorption data. According to the fitting data obtained from Langmuir model, the magnitude of maximum adsorption capacity (q_m) for three types of adsorbents toward both aromatic amines is in the order chitosan < chitosan/nano-Al₂O₃ < Cu–chitosan/nano-Al₂O₃. It implies that the incorporation of the particulate nano-filler into chitosan bead and the surface modification with Cu²⁺ have considerable effect on chitosan efficiency for the adsorption of aromatic amines. Based on the results of morphological studies, the surface area of the chitosan bead increases with the inclusion of a nano-filler such as nano-Al₂O₃ and it may provide more adsorption sites for aromatic amines adsorption. For Cu²⁺-treated chitosan/nano-Al₂O₃ adsorbent, more favorable conditions may be provided through chelating of aromatic amines by Cu(II) on the adsorbents surface as indicated by XRD and FTIR studies.

Figure 6.

Fitting of adsorption data to Langmuir model for adsorption of (a) aniline and (b) dimethyl aniline on chitosan, chitosan/nano-Al₂O₃ and Cu–chitosan/nano-Al₂O₃.

Figure 7.

Fitting of adsorption data to Freundlich model for adsorption of (a) aniline and (b) dimethyl aniline on chitosan, chitosan/nano-Al₂O₃ and Cu–chitosan/nano-Al₂O₃.

Table 1.

Langmuir and Freundlich isotherm constants and related fitting parameters for adsorption of aniline and dimethyl aniline on chitosan, chitosan/nano-Al₂O₃ and Cu–chitosan/nano-Al₂O₃.

Isotherm	Aromatic amine	Isotherm constants and fitting parameters
Isotherm	Aromatic amine	Chitosan	Chitosan/Al₂O₃	Cu–chitosan/Al₂O₃
Langmuir	An	K_L = 0.01084 (L/mg) q_m = 38.88 (mg/g) SSE = 0.7391 R²= 0.9954 Adj-R²= 0.9939 RMSE = 0.4964	K_L = 0.01767 (L/mg) q_m = 40.30 (mg/g) SSE = 2.0450 R²= 0.9891 Adj-R²= 0.9854 RMSE = 0.8254	K_L = 0.01597 (L/mg) q_m = 84.27 (mg/g) SSE = 42.3400 R²= 0.9535 Adj-R²= 0.9380 RMSE = 3.757
Langmuir	DMA	K_L = 0.01463 (L/mg) q_m = 45.41 (mg/g) SSE = 3.8720 R²= 0.9828 Adj-R²= 0.9770 RMSE = 1.1360	K_L = 0.010872 (L/mg) q_m = 51.55 (mg/g) SSE = 6.3270 R²= 0.9795 Adj-R²= 0.9726 RMSE = 1.4520	K_L = 0.03166 (L/mg) q_m = 61.95 (mg/g) SSE = 26.7300 R²= 0.9482 Adj-R²= 0.9310 RMSE = 2.9850
Freundlich	An	K_F = 1.776 (mg/g)/(mg/L)^1/n n = 1.922 SSE = 4.1370 R²= 0.9743 Adj-R²= 0.9658 RMSE = 1.1740	K_F = 3.427 (mg/g)/(mg/L)^1/n n = 2.325 SSE = 2.1380 R²= 0.9886 Adj-R²= 0.9848 RMSE = 0.8441	K_F = 5.143 (mg/g)/(mg/L)^1/n n = 2.010 SSE = 6.9900 R²= 0.9923 Adj-R²= 0.9898 RMSE = 1.5260
Freundlich	DMA	K_F = 2.985 (mg/g)/(mg/L)^1/n n = 2.122 SSE = 1.5510 R²= 0.9931 Adj-R²= 0.9908 RMSE = 0.7190	K_F = 4.527 (mg/g)/(mg/L)^1/n n = 2.334 SSE = 0.2962 R²= 0.9990 Adj-R²= 0.9987 RMSE = 0.3142	K_F = 8.626 (mg/g)/(mg/L)^1/n n = 2.746 SSE = 1.3450 R²= 0.9974 Adj-R²= 0.9965 RMSE = 0.6697

SSE: sum square errors; RMSE: root mean square errors.

Adsorption kinetics

The prediction of the rate of adsorption for removal of a pollutant from aqueous solution is so important for scale-up and design purposes. The kinetic data for adsorption of the aromatic amines on the adsorbents were fitted to pseudo-first-order and pseudo-second-order kinetic models as shown by equations (4) and (5), respectively.

{dq}_{t} / dt = k_{1} (q_{e} - q_{t})

(4)

{dq}_{t} / dt = k_{2} (q_{e} - q_{t}) 2

(5)

where q_e (mg/g) is the adsorption capacity at equilibrium, q_t (mg/g) is the adsorption capacity at time t, and k₁ (1/min) and k₂ (g/mg.min) are pseudo-first-order and pseudo-second-order rate constants, respectively.

The non-linear forms of pseudo-first-order and pseudo-second-order kinetic models are expressed, respectively, by equations (6) and (7) obtained by integrating the differential equations with the boundary conditions of q_t = 0 at t = 0 and q_t = q_t at t = t.

q_{t} = q_{e} [1 - \exp (- k_{1} t)]

(6)

q_{t} = (q_{e}^{2} k_{2} t) / (1 + q_{e} k_{2} t)

(7)

The non-linear fitting method was employed to obtain the correlation between the experimental kinetic data and the kinetic models. Table 2 presents the value of the rate constants, k₁ and k₂, and the correlation parameters of both models for adsorption of An and DMA on three types of adsorbents. Although the fitting parameters are rather satisfactory for both kinetic models, the values of equilibrium uptakes predicted by pseudo-second-order kinetic model present considerable differences with experimental data. In other words, pseudo-first-order kinetic model has good compliance with kinetic data in the case of both fitting parameters and the predicted values of equilibrium uptake. Figure 8 shows experimental kinetic data and the pseudo-first-order non-linear model for adsorption of An and DMA for three types of adsorbents. It can be seen that the adsorption of An and DMA on three types of adsorbents is rather rapid and reaches to equilibrium state within the first 30 min of contact. The initial adsorption rate (V₀) for three types of adsorbents was calculated using pseudo-first-order kinetic by placing q_t = 0 at t = 0 in the kinetic model as follows

V_{0} = k_{1} q_{e}

(8)

Figure 8.

Pseudo-first-order kinetic model for adsorption of (a) aniline and (b) dimethyl aniline on chitosan, chitosan/nano-Al₂O₃ and Cu–chitosan/nano-Al₂O₃.

Table 2.

Parameters of pseudo-first-order and pseudo-second-order kinetic models fitting of aniline and dimethyl aniline adsorption data on chitosan, chitosan/nano-Al₂O₃, and Cu–chitosan/nano-Al₂O₃ adsorbents.

Kinetic model	Aromatic amine	Kinetic and fitting parameters
Kinetic model	Aromatic amine	Chitosan	Chitosan/alumina	Cu–chitosan/alumina
Pseudo-first- order	An	k₁ = 0.01699 (min⁻¹) q_e = 16.99 (mg/g) q_e(Exp)¹= 16.08 (mg/g) V₀ = 0.2732 (mg/g.min) SSE = 2.231 R²= 0.9940 Adj-R²= 0.9937 RMSE = 0.352	k₁ = 0.01666 (min⁻¹) q_e = 21.17 (mg/g) q_e(Exp) = 20.97 (mg/g) V₀ = 0.3494 (mg/g.min) SSE = 9.698 R²= 0.9848 Adj-R²= 0.9840 RMSE = 0.734	k₁ = 0.01761 (min⁻¹) q_e = 36.01 (mg/g) q_e(Exp) = 34.53 (mg/g) V₀ = 0.6081 (mg/g.min) SSE = 26.42 R²= 0.9861 Adj-R²= 0.9854 RMSE = 1.211
Pseudo-first- order	DMA	k₁ = 0.02944 (min⁻¹) q_e = 19.61 (mg/g) q_e(Exp) = 20 (mg/g) V₀ = 0.5888 (mg/g.min) SSE = 2.291 R²= 0.9950 Adj-R²= 0.9947 RMSE = 0.3784	k₁ = 0.02328 (min⁻¹) q_e = 26.17 (mg/g) q_e(Exp) = 25.68 (mg/g) V₀ = 0.5978 (mg/g.min) SSE = 4.956 R²= 0.9942 Adj-R²= 0.9938 RMSE = 0.5565	k₁ = 0.02861 (min⁻¹) q_e = 35.42 (mg/g) q_e(Exp) = 35.15 (mg/g) V₀ = 1.0056 (mg/g.min) SSE = 6.376 R²= 0.9958 Adj-R²= 0.9955 RMSE = 0.6313
Pseudo- second- order	An	k₂ = 9.448 × 10⁻⁴ (g/mg.min) q_e = 20.64 (mg/g) q_e(Exp) = 16.08 (mg/g) SSE = 8.359 R²= 0.9776 Adj-R²= 0.9763 RMSE = 0.6815	k₂ = 5.730 × 10⁻⁴ (g/mg.min) q_e = 27.56 (mg/g) q_e(Exp) = 20.97 (mg/g) SSE = 5.803 R²= 0.9909 Adj-R²= 0.9904 RMSE = 0.5678	k₂ = 3.609 × 10⁻⁴ (g/mg.min) q_e = 46.62 (mg/g) q_e(Exp) = 34.53 (mg/g) SSE = 24.34 R²= 0.9872 Adj-R²= 0.9865 RMSE = 1.163
Pseudo- second- order	DMA	k₂ = 1.828 × 10⁻³ (g/mg.min) q_e = 22.54 (mg/g) q_e(Exp) = 20 (mg/g) SSE = 3.828 R²= 0.9917 Adj-R²= 0.9912 RMSE = 0.4891	k₂ = 7.538 × 10⁻⁴ (g/mg.min) q_e = 32.56 (mg/g) q_e(Exp) = 25.68 (mg/g) SSE = 11.51 R²= 0.9865 Adj-R²= 0.9856 RMSE = 0.8483	k₂ = 1.012 × 10⁻³ (g/mg.min) q_e = 40.78 (mg/g) q_e(Exp) = 35.15 (mg/g) SSE = 12.77 R²= 0.9916 Adj-R²= 0.9910 RMSE = 0.8934

The comparison of k₁ values shows no significant difference between adsorbents, while the magnitude of initial adsorption rates and maximum adsorption capacities for Cu–chitosan/nano-Al₂O₃ are much higher than those of neat chitosan and chitosan/nano-Al₂O₃ adsorbents. It implies that Cu–chitosan/nano-Al₂O₃ can more quickly absorb much higher amounts of aromatic amines during short time of exposure than neat chitosan and chitosan/nano-Al₂O₃ adsorbents. After initial adsorption, the adsorption rate of Cu–chitosan/nano-Al₂O₃ is almost the same as that of chitosan and chitosan/nano-Al₂O₃ adsorbents. Considering the results of kinetics studies, Cu–chitosan/nano-Al₂O₃ presents much better kinetic characteristics for effective removal of An and DMA as typical aromatic amines.

Effect of initial pH

The adsorption capacities of three types of adsorbents toward An and DMA were studied in the pH range of 4.0–11.0 at 25℃. Initial concentration of the aromatic amines was selected to be 40 mg/L. Figure 9 presents the adsorption capacities of three types of adsorbents versus the initial pH of the aromatic amine containing solution. A similar trend is observed for adsorption of An and DMA by each adsorbent. For neat chitosan bead, the adsorption capacity increases steeply with the increase of pH value from 4.0 to ∼7.2 and then decreases in the pH range 7.2–11.0. In the case of chitosan/nano-Al₂O₃ adsorbent, a gradual increase in the adsorption capacity is seen over pH range 4.0–8.0 and a decrease is observed at higher pH values. For Cu–chitosan/nano-Al₂O₃, the adsorption capacity increases with increase of pH from 4.0 to ∼7.2 and decreases at higher pH values. To explain the behaviors observed, the pH at the point of zero charge (pH_pzc) was determined for the adsorbents. The pH_pzc for chitosan, chitosan/nano-Al₂O₃ Na and Cu–chitosan/nano-Al₂O₃ was determined to be, respectively, 7.6, 8.15, and 6.3 using the results of batch equilibrium experiments as shown in Figure 10. At pH values lower than pH_pzc of an adsorbent, the surface is positively charged, while at pH values higher than the pH_pzc, the surface is negatively charged. The relation between pH value and the aromatic amines adsorption on chitosan and chitosan/nano-Al₂O₃ can be explained by the pH_pzc of the adsorbents. As pH increases up to the pH_pzc, the positively charged surface sites decrease, on the one hand, and the concentration of protonated aromatic amines as the positively charged species decreases on the other hand, causing an increase in the adsorption. Thus, the adsorption of the amines on chitosan and chitosan/nano-Al₂O₃ adsorbents can be addressed to the electrostatic interactions between the aromatic amines species and the surface of adsorbents. For Cu–chitosan/nano-Al₂O₃, the mechanism based on electrostatic interactions cannot describe the variation of aromatic amines adsorption against pH value duo to its different behavior. The adsorption of aromatic amines increases with increase of pH value up to ∼7.2 higher than the pH_pzc (6.3). In other word, a considerable increase occurs after the pH_pzc and it cannot be explained by electrostatic interactions on the surface. Furthermore, the adsorption capacity for Cu–chitosan/nano-Al₂O₃ is much higher than that of others. It suggests that the adsorption on the modified adsorbent may be occurred by complex formation rather electrostatic interactions as evidenced by FTIR and XRD studies. Aromatic amines such as aniline can react with Cu(II) at room temperature to form Cu(II)–aromatic amines complexes (Le Cocq et al., 2012). At pH > 7.2, the adsorption capacity decreases gradually but is still higher than that of neat chitosan and chitosan/nano-Al₂O₃ adsorbents. It may be due to the formation of Cu(II) hydrate in competition with the formation of the complex between Cu(II) and aromatic amines. Formation of copper oxide at pH values higher than 10 was clearly visible as the adsorbent color changes from blue to dark brown.

Figure 9.

Effect of initial pH on adsorption of (a) aniline and (b) dimethyl aniline by neat chitosan, chitosan/nano-Al₂O₃ and Cu–chitosan/nano-Al₂O₃.

Figure 10.

Determination of pH_pzc for neat chitosan, chitosan/nano-Al₂O₃, and Cu–chitosan/nano-Al₂O₃ adsorbents.

Reusability of adsorbent

Considering economic aspects of an adsorption process for commercial applications, it is important that an adsorbent can be regenerated and reused in a cyclic manner. The reusability of the modified adsorbent was evaluated by determining the adsorption capacity after several regeneration cycles. Figure 11 shows the variation of the adsorption capacity after each adsorption–desorption cycle. A slight reduction in the adsorption capacity was observed for An and DMA after five cycles of the adsorption–desorption process. It indicates that the studied adsorbent can be regenerated and reused repeatedly and so has a high durability.

Figure 11.

Adsorption efficiency of Cu–chitosan/nano-Al₂O₃ toward aniline and dimethyl aniline versus regeneration cycle.

The modified adsorbent, Cu–chitosan/nano-Al₂O₃ showed desirable stability of its capacity when stored in air at room temperature so that there was no measureable change in its capacity after four weeks of preparation.

Interfering effects

The interfering effect of natural waters common anions (chloride, nitrate, phosphate, carbonate, and sulfate) on An and DMA adsorption by Cu–chitosan/nano-Al₂O₃ was studied. The concentration of interfering anions was selected to be 10 times higher than that of An and DMA. As shown in Figure 12, the presence of nitrate and chloride anions had no considerable effect on the adsorption capacities. In the presence of phosphate, carbonate and sulfate anions, the adsorption capacities were decreased slightly indicating low interfering effect of these anions.

Figure 12.

Adsorption capacity of aniline and dimethyl aniline in the presence of interfering anions (400 mg/L). The experiments conditions: aniline and dimethyl aniline concentration of 40 mg/L and the adsorbent amount of 1 g/L.

Conclusions

FTIR and XRD studies of the modified adsorbent indicated the presence of Cu(II) bonded to amine groups of chitosan on the surface.

Cu–chitosan/Al₂O₃ nanocomposite provided more surface area for adsorption compared to neat chitosan as confirmed by SEM and BET studies.

Experimental adsorption data could be well explained by both Freundlich and Langmuir isotherm models.

Maximum adsorption capacities for adsorption of An and DMA by the modified adsorbent were, respectively, 84 and 61 mg/g, much higher than those for neat chitosan

The adsorption of aromatic amines on the modified adsorbent was to be based on chemical bonding to Cu(II) on the adsorbent surface as confirmed by FTIR studies of the modified adsorbent after adsorption.

The modified adsorbent showed a reasonable selectivity for An and DMA in the presence of natural waters common anions.

The results showed that the Cu–chitosan/Al₂O₃ nanocomposite can be employed as a chitosan-based adsorbent for effective and selective removal of aromatic amines from natural water.

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) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was financially supported by the University of Maragheh.

References

Ali

Asim

Khan

(2012) Low cost adsorbents for the removal of organic pollutants from wastewater. Journal of Environmental Management 113: 170–183.

Feng

Gao

(2009) Adsorption of aniline from aqueous solution using novel adsorbent PAM/SiO₂. Chemical Engineering Journal 151(1): 183–187.

Annadurai

Juang

R-S

Lee

D-J

(2002) Use of cellulose-based wastes for adsorption of dyes from aqueous solutions. Journal of Hazardous materials 92(3): 263–274.

Bettini

Bonfrate

Syrgiannis

(2015a) Biocompatible collagen paramagnetic scaffold for controlled drug release. Biomacromolecules 16(9): 2599–2608.

Bettini

Pagano

Valli

(2014) Drastic nickel ion removal from aqueous solution by curcumin-capped Ag nanoparticles. Nanoscale 6(17): 10113–10117.

Bettini

Santino

Valli

(2015b) A smart method for the fast and low-cost removal of biogenic amines from beverages by means of iron oxide nanoparticles. RSC Advances 5(23): 18167–18171.

Boddu

Abburi

Talbott

(2003) Removal of hexavalent chromium from wastewater using a new composite chitosan biosorbent. Environmental Science & Technology 37(19): 4449–4456.

Chai

Ying

(2007) Electrosorption-enhanced solid-phase microextraction using activated carbon fiber for determination of aniline in water. Journal of Chromatography A 1165(1): 26–31.

Crini

Badot

P-M

(2008) Application of chitosan, a natural aminopolysaccharide, for dye removal from aqueous solutions by adsorption processes using batch studies: A review of recent literature. Progress in Polymer Science 33(4): 399–447.

10.

Crisafully

Milhome

MAL

Cavalcante

(2008) Removal of some polycyclic aromatic hydrocarbons from petrochemical wastewater using low-cost adsorbents of natural origin. Bioresource Technology 99(10): 4515–4519.

11.

Datta

Bhattacharya

Verma

(2003) Removal of aniline from aqueous solution in a mixed flow reactor using emulsion liquid membrane. Journal of Membrane Science 226: 185–201.

12.

Eimer

Costa

MBG

Pierella

(2003) Thermal and FTIR spectroscopic analysis of the interactions of aniline adsorbed on to MCM-41 mesoporous material. Journal of Colloid and Interface Science 263(2): 400–407.

13.

Essington

(1994) Adsorption of aniline and toluidines on montmorillonite. Soil Science 158(3): 181–188.

14.

Foo

Hameed

(2010) Insights into the modeling of adsorption isotherm systems. Chemical Engineering Journal 156(1): 2–10.

15.

Gerente

Lee

Cloirec

(2007) Application of chitosan for the removal of metals from wastewaters by adsorption – mechanisms and models review. Critical Reviews in Environmental Science and Technology 37(1): 41–127.

16.

Gheewala

Annachhatre

(1997) Biodegradation of aniline. Water Science and Technology 36(10): 53–63.

17.

Gómez

León

Hidalgo

(2009) Application of reverse osmosis to remove aniline from wastewater. Desalination 245(1): 687–693.

18.

Han

Quan

Chen

(2006) Electrochemically enhanced adsorption of aniline on activated carbon fibers. Separation and Purification Technology 50(3): 365–372.

19.

Hidalgo

León

Gomez

(2011) Modeling of aniline removal by reverse osmosis using different membranes. Chemical Engineering & Technology 34(10): 1753–1759.

20.

Hatton

Lightfoot

(1982) Batch extraction with liquid surfactant membranes: A diffusion controlled model. AIChE Journal 28(4): 662–670.

21.

Jianguo

Aimin

Hongyan

(2005) Adsorption characteristics of aniline and 4-methylaniline onto bifunctional polymeric adsorbent modified by sulfonic groups. Journal of Hazardous Materials 124(1): 173–180.

22.

Kakavandi

Jafari

Kalantary

(2013) Synthesis and properties of Fe₃O₄-activated carbon magnetic nanoparticles for removal of aniline from aqueous solution: equilibrium, kinetic and thermodynamic studies. Iranian Journal of Environmental Health Science & Engineering 10(1): 10–19.

23.

Kamble

Sawant

Schouten

(2003) Photocatalytic and photochemical degradation of aniline using concentrated solar radiation. Journal of Chemical Technology and Biotechnology 78(8): 865–872.

24.

Klein

Smith

Wendt

(1972) Solute separations from water by dialysis. I. The separation of aniline. Separation Science 7(3): 285–292.

25.

Kumar

MNR

(2000) A review of chitin and chitosan applications. Reactive and Functional Polymers 46(1): 1–27.

26.

Łabudzińska

Gorczyńska

(1994) Ultraviolet spectrophotometric method for the determination of aromatic amines in chemical industry waste waters. Analyst 119(6): 1195–1198.

27.

Lataye

Mishra

Mall

(2006) Removal of pyridine from aqueous solution by adsorption on bagasse fly ash. Industrial & Engineering Chemistry Research 45(11): 3934–3943.

28.

Le Cocq

Gizdavic-Nikolaidis

Easteal

(2012) Reactions of aniline with copper (II) compounds in relation to the formation of copper-polyaniline composites. Australian Journal of Chemistry 65(7): 723–729.

29.

Jin

(2009) Effect of hypersaline aniline-containing pharmaceutical wastewater on the structure of activated sludge-derived bacterial community. Journal of Hazardous Materials 172(1): 432–438.

30.

Liu

Guan

(2012) Hemoglobin immobilized with modified “fish-in-net” approach for the catalytic removal of aniline. Journal of Hazardous Materials 217: 156–163.

31.

Lowell

Shields

(2013) Powder Surface Area and Porosity, Netherlands: Springer Science & Business Media.

32.

Ngah

Teong

Hanafiah

(2011) Adsorption of dyes and heavy metal ions by chitosan composites: A review. Carbohydrate Polymers 83(4): 1446–1456.

33.

Ogawa

Hirano

Miyanishi

(1984) A new polymorph of chitosan. Macromolecules 17(4): 973–975.

34.

Pinheiro

Touraud

Thomas

(2004) Aromatic amines from azo dye reduction: Status review with emphasis on direct UV spectrophotometric detection in textile industry wastewaters. Dyes and Pigments 61(2): 121–139.

35.

X-H

Zhuang

Y-Y

Yuan

Y-C

(2002) Decomposition of aniline in supercritical water. Journal of hazardous materials 90(1): 51–62.

36.

Sarode

Verma

Bhattacharya

(2001) Analysis of retention and flux decline during ultrafiltration of limed sugarcane (clarified) juice. Chemical Engineering Communications 188(1): 179–206.

37.

Schwarzenbach

Egli

Hofstetter

(2010) Global water pollution and human health. Annual Review of Environment and Resources 35: 109–136.

38.

Sun

Liang

Zhao

(2009) Determination of aromatic amines in water samples by capillary electrophoresis with amperometric detection. Water Research 43(1): 41–46.

39.

Unuabonah

Adebowale

Dawodu

(2008) Equilibrium, kinetic and sorber design studies on the adsorption of Aniline blue dye by sodium tetraborate-modified Kaolinite clay adsorbent. Journal of Hazardous Materials 157(2): 397–409.

40.

Vörösmarty

McIntyre

Gessner

(2010) Global threats to human water security and river biodiversity. Nature 467(7315): 555–561.

41.

Wang

S-F

Shen

Zhang

W-D

(2005) Preparation and mechanical properties of chitosan/carbon nanotubes composites. Biomacromolecules 6(6): 3067–3072.

42.

Yang

Jing

(2008) Aqueous adsorption of aniline, phenol, and their substitutes by multi-walled carbon nanotubes. Environmental Science & Technology 42(21): 7931–7936.

43.

Zhao

Zhu

Lee

(2002) Analysis of aromatic amines in water samples by liquid–liquid–liquid microextraction with hollow fibers and high-performance liquid chromatography. Journal of Chromatography A 963(1): 239–248.

44.

Zheng

Liu

Zheng

(2009) Sorption isotherm and kinetic modeling of aniline on Cr-bentonite. Journal of Hazardous Materials 167(1): 141–147.