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Adsorption of Cu(II) on humic acids derived from different organic materials
Journal of Integrative Agriculture 2015, 14(1): 168–177 Available online at www.sciencedirect.com
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RESEARCH ARTICLE
Adsorption of Cu(II) on humic acids derived from different organic materials LI Cui-lan1, JI Fan1, WANG Shuai2, ZHANG Jin-jing1, GAO Qiang1, WU Jing-gui1, ZHAO Lan-po1, WANG Li-chun3, ZHENG Li-rong4 1
College of Resource and Environmental Science, Jilin Agricultural University, Changchun 130118, P.R.China Institute of Plant Science, Jilin Agricultural Science and Technology College, Jilin 132101, P.R.China 3 Institute of Agricultural Resources and Environments, Jilin Academy of Agricultural Sciences, Changchun 130124, P.R.China 4 Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, P.R.China 2
Abstract The adsorption of Cu(II) from aqueous solution onto humic acid (HA) which was isolated from cattle manure (CHA), peat (PHA), and leaf litter (LHA) as a function of contact time, pH, ion strength, and initial concentration was studied using the batch method. X-ray absorption spectroscopy (XAS) was used to examine the coordination environment of the Cu(II) adsorbed by HA at a molecular level. Moreover, the chemical compositions of the isolated HA were characterized by elemental analysis and solid-state 13C nuclear magnetic resonance spectroscopy (NMR). The kinetic data showed that the adsorption equilibrium can be achieved within 8 h. The adsorption kinetics followed the pseudo-second-order equation. The adsorption isotherms could be well fitted by the Langmuir model, and the maximum adsorption capacities of Cu(II) on CHA, PHA, and LHA were 229.4, 210.4, and 197.7 mg g–1, respectively. The adsorption of Cu(II) on HA increased with the increase in pH from 2 to 7, and maintained a high level at pH>7. The adsorption of Cu(II) was also strongly influenced by the low ionic strength of 0.01 to 0.2 mol L–1 NaNO3, but was weakly influenced by high ionic strength of 0.4 to 1 mol L–1 NaNO3. The Cu(II) adsorption on HA may be mainly attributed to ion exchange and surface complexation. XAS results revealed that the binding site and oxidation state of Cu adsorbed on HA surface did not change at the initial Cu(II) concentrations of 15 to 40 mg L–1. For all the Cu(II) adsorption samples, each Cu atom was surrounded by 4 O/N atoms at a bond distance of 1.95 Å in the first coordination shell. The presence of the higher Cu coordination shells proved that Cu(II) was adsorbed via an inner-sphere covalent bond onto the HA surface. Among the three HA samples, the adsorption capacity and affinity of CHA for Cu(II) was the greatest, followed by that of PHA and LHA. All the three HA samples exhibited similar types of elemental and functional groups, but different contents of elemental and functional groups. CHA contained larger proportions of methoxyl C, phenolic C and carbonyl C, and smaller proportions of alkyl C and carbohydrate C than PHA and LHA. The structural differences of the three HA samples are responsible for their distinct adsorption capacity and affinity toward Cu(II). These results are important to achieve better understanding of the behavior of Cu(II) in soil and water bodies in the presence of organic materials.
Received 22 August, 2013 Accepted 28 November, 2013 Correspondence ZHANG Jin-jing, Tel: +86-431-84532955, E-mail: [email protected]; ZHENG Li-rong, Tel: +86-1088235980, E-mail: [email protected] © 2015, CAAS. All rights reserved. Published by Elsevier Ltd. doi: 10.1016/S2095-3119(13)60682-6
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Keywords: humic acid, Cu(II), adsorption, organic material, 13C NMR, XAS
1. Introduction Humic substances (HS) are the most widely distributed natural nonliving organic compounds occurring in soils, waters, sediments, peat, and other organic wastes (Xu and Huang 2010; Zhang et al. 2013). One of the most striking features of HS is their strong interaction with inorganic and organic pollutants. Humic acid (HA) represents the major extractable component of HS. The interactions between HA and metal ions are important in controlling the behavior and fate of trace metals in the environment (Theng 2012). In natural environments, copper (Cu) is an essential micronutrient for all living organisms, but can become toxic when it presents in excessive concentrations (Wright and Welbourn 2002). Moreover, Cu has a strong affinity for HS (Arias et al. 2002; Zhang et al. 2010). Adsorption is one of the most important interactions between Cu(II) and HS. Thus, understanding the adsorption properties of Cu(II) onto HS is important to minimize the potentially harmful effects of Cu(II) in the environment. The use and management of organic materials are important global issues (Khalil et al. 2005). In agriculture, organic materials with various origins and natures have been widely used for improving soil fertility and increasing crop productivity (Li and Wu 2013). These organic materials are rich natural sources of HA in the environment (Davies and Ghabbour 1998; Ribeiro et al. 2001; Hur et al. 2011). Meanwhile, HA from different sources of organic materials, called HA-like fractions in some situations, have significant effects on the composition, structure, and functionality of HA in native soil amended with these organic materials (Brunetti et al. 2007). Thus, determining the adsorption characteristics of Cu(II) on organic material-derived HA for reasonable usage of organic materials and forecast of Cu(II) behaviors in various environments is crucial. Although previous studies have examined the adsorption properties of Cu(II) on some organic materials (Gardea-Torresdey et al. 1996), few studies have been conducted to compare the differences of Cu(II) adsorption behaviors on HA derived from organic materials of different sources.
Macroscopic batch adsorption experiments and microscopic spectroscopic techniques can be combined to elucidate the mechanisms of Cu(II) adsorption on HS. Synchrotron-based X-ray absorption spectroscopy (XAS), including X-ray absorption near-edge structure (XANES) spectroscopy and extended X-ray absorption fine structure (EXAFS) spectroscopy, is a useful technique that can provide molecular-level information about the local chemical environments of trace metals in HS (Xia et al. 1997; Ginder-Vogel and Sparks 2010). Meanwhile, the mechanisms of Cu(II) adsorption on HS also depend on the chemical structure of the latter. Elemental analysis and solid-state 13C nuclear magnetic resonance (NMR) technology are powerful tools for describing their structural characteristics (Rice and MacCarthy 1991; Simpson et al. 2011). The present study aims to determine the adsorption behaviors of Cu(II) on HA isolated from three organic materials (i.e., cattle manure, peat, and leaf litter) at different contact times, pH, ion strengths, and initial Cu concentrations by batch experiments, and to examine the coordination environment of Cu(II) adsorbed by HA at a molecular level using XAS techniques. The chemical compositions of the isolated HA are characterized by elemental analysis and solid-state 13 C NMR spectroscopy.
2. Results and discussion 2.1. Characterization of HA The pH values were 4.64, 4.09 and 4.26, and the cation exchange capacity (CEC) values were 340.7, 257.5 and 182.8 cmol (+) kg–1 for HA from the cattle manure (CHA), peat (PHA), and leaf litter (LHA), respectively. The elemental composition and atomic ratios of the three HA samples are presented in Table 1. The compositional values obtained were within the ranges reported in Rice and MacCarthy (1991). The C and O contents, as well as the C/N ratio of HA, tended to increase in the order LHA
Table 1 Ash contents, elemental composition, and atomic ratios of HA from cattle manure (CHA), peat (PHA), and leaf litter (LHA) HA samples CHA PHA LHA
Ash (g kg–1) 11.2 36.2 78.1
C (g kg–1) 561.6 559.1 539.6
H (g kg–1) 55.3 57.8 58.3
N (g kg–1) 31.0 33.3 34.2
S (g kg–1) 5.61 3.04 5.53
O (g kg–1) 335.3 310.5 284.2
H/C 1.182 1.241 1.297
C/O 2.234 2.401 2.531
C/N 21.1 19.6 18.4
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maturity, and polarity of HA, respectively (Nierop et al. 1999;
phobicity degree was similar.
Xing et al. 2005). Therefore, our results suggested that CHA was the least aliphatic, the least mature and the most polar,
2.2. Adsorption kinetics
whereas LHA was the most aliphatic, the most mature and the least polar among the three HA samples. The 13C NMR spectra of HA are shown in Fig. 1. The three HA samples exhibited very similar functional group types. All spectra were identified as alkyl C (0–50 ppm), methoxyl C (50–60 ppm), carbohydrate C (60–110 ppm), aryl C (110–145 ppm), phenolic C (145–160 ppm), and carbonyl C (160–200 ppm). On the other hand, the relative intensities of the C functional groups differed among the three HA samples (Table 2). Alkyl C and carbohydrate C tended to increase in the order CHA
LHA
PHA
CHA 200 180 160 140 120 100 80
60
40
20
0
Fig. 1 13C CPMAS TOSS NMR spectra of humic acid (HA) from cattle manure (CHA), peat (PHA) and leaf litter (LHA).
The effect of contact time on the adsorption of Cu(II) on HA is shown in Fig. 2, and the corresponding kinetic parameters from the pseudo-first-order, pseudo-second-order Elovich and intraparticle diffusion equations are listed in Table 3. The shapes of kinetic curves for the three HA samples were similar, which was ascribed to their similar structures and functional groups. The adsorption occurred rapidly within the first 30 min, and then increased slowly. The adsorption equilibrium was finally reached within 8 h. The oxygen-containing functional groups, especially the carboxyl group, are believed to have a vital role in the binding of metal ions by humic substances (Zhang et al. 2013). The exposure of these groups to HA surfaces is responsible for the rapid adsorption of Cu(II) by HA (Gardea-Torresdey et al. 1996). The pseudo-second-order equation fitted the kinetic data better than the pseudo-first-order, Elovich and intraparticle diffusion equations, as given by the higher coefficient of determination R2 (>0.99) from the former. Meanwhile, the calculated qe values from the pseudo-second-order equation were close to the experimental data. The adsorption data for the intraparticle diffusion equation showed two-linear plots representing the surface or film diffusion and a gradual adsorption stage, respectively (Liang et al. 2013). The pseudo-second-order equation was based on the assumption that the rate-limiting step may be chemical adsorption (Li et al. 2010). Therefore, these results indicated that chemical adsorption rather than intraparticle diffusion was the rate-controlling step. Among the three HA samples, the adsorption amount of Cu(II) was the greatest for CHA, followed by that of PHA and LHA.
2.3. Effects of pH and ion strength The effect of pH on Cu(II) adsorption on HA is shown in Fig. 3-A. The equilibrium pH was slightly lower than the initial pH, indicating that H+ was released from the HA surface into solution during the adsorption process. A similar result
Table 2 Relative carbon distribution (%) in different regions of chemical shift in 13C CPMAS TOSS NMR spectra of HA from CHA, PHA and LHA HA samples CHA PHA LHA 1) 2) 3)
0–50 13.7 15.5 17.9
50–60 14.0 11.9 10.7
Chemical shift regions (ppm) 60–110 110–145 22.0 22.0 23.4 23.8 27.7 19.4
145–160 14.0 11.8 11.3
A/O–A, alkyl C/O–alkyl C=(0–50)/(50–110) Alip/Arom, aliphatic C/aromatic C=[(0–50)+(50–110)]/(110–160) HB/HI, hydrophobic C/hydrophilic C=[(0–50)+(110–160)]/[(50–110)+(160–200)]
160–200 14.3 13.7 12.9
A/O–A1) 0.382 0.439 0.465
Alip/Arom2) HB/HI3) 1.376 1.429 1.830
0.993 1.043 0.947
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Cu(II) adsorbed (mg g−1)
A 150 140 130 120
CHA PHA
110
LHA
100 0
300
600
900
1 200
1 500
Time (min)
Cu(II) adsorbed (mg g−1)
B 150 140 130 120 110 100 0
10
20
30
40
Time0.5 (min0.5)
tion of H+ in the solution decreased and the surface negative charge of HA increased; thus, the adsorption of Cu(II) on HA gradually increased. When pH was above 8, the removal of Cu(II) was mainly controlled by the precipitation of Cu(OH)2(s) on the HA surface (Alvarez-Puebla et al. 2004). In general, surface complexation is pH dependent (Tan et al. 2008; Wang et al. 2009). Therefore, the pH dependent adsorption of Cu(II) on HA suggested that the process was dominated by surface complexation. The effect of ionic strength on the adsorption of Cu(II) on HA is shown in Fig. 3-B. The adsorption amounts of Cu(II) on HA decreased with the increase of NaNO3 concentrations from 0.01 to 1 mol L–1. When the ionic strength was lower than 0.2 mol L–1, the adsorption of Cu(II) was generally sensitive to changes in the ionic strength. However, the changes in ionic strength caused only a relatively small change for Cu(II) adsorption when the ionic strength was higher than 0.4 mol L–1. The decrease in Cu(II) adsorption with increasing ion strength was attributed to the competitive adsorption of Cu2+ with Na+ on the HA surface and the compression of the double layers at the solid/liquid interface (Wang et al. 2009; Liang et al. 2013). The adverse effect of ionic strength on Cu(II) adsorption suggested that ion exchange contributes to the adsorption process (Li et al. 2009; Wang et al. 2009).
2.4. Adsorption isotherms
Fig. 2 Adsorption kinetics of Cu(II) on HA from CHA, PHA and LHA. Solid (A) and dotted (B) lines represent the experimental curves and model fitting of intraparticle diffusion equation, respectively.
was reported for Cu(II) adsorption onto commercial-derived HA (Li et al. 2010). The adsorption of Cu(II) on HA increased slowly at the pH range of 2 to 5, then increased abruptly at pH 5 to 7, and finally reached the maximum and remained constant at pH>7. The low Cu(II) adsorption at low pH can be due to the competition between H+ and Cu2+ for the same sites on the HA surface. With increasing pH, the concentra-
The adsorption isotherms of Cu(II) on HA are shown in Fig. 4, and the parameters of the Langmuir and the Freundlich equations obtained by fitting the isotherms are given in Table 4. All the three HA samples displayed similar shapes of adsorption isotherms. The amount of adsorbed Cu(II) on HA increased with the increase in Cu(II) concentrations. The adsorption data can be well described by both Langmuir and Freundlich equations with R2 values greater than 0.972. However, the Langmuir equation provided a better fit, with R2 values ranging from 0.988 to 0.994. Based on the Langmuir equation, the maximum
Table 3 Adsorption kinetic parameters derived from pseudo-first-order, pseudo-second-order, Elovich and intraparticle diffusion equations for Cu(II) adsorption on HA from CHA, PHA and LHA HA samples
Pseudo-first-order1) qe1 R2 k × 10–1 1
Pseudo-second-order2) qe2 k2×10–1 R2
Elovich3) b
a
R
2
Intraparticle diffusion4) kid C R2
CHA
21.35
0.052
0.738
141.6
0.017
0.999
6.21× 1010
4.30
0.933
0.593
124.6 0.670
PHA
18.88
0.047
0.684
135.3
0.017
0.999
9.26× 10
3.57
0.943
0.502
120.6 0.700
LHA
19.22
0.058
0.782
128.2
0.019
0.999
4.59× 10
4.23
0.942
0.584
116.4 0.676
1)
–1
12 9
qe1, adsorption amount at equilibrium in pseudo first order equation (mg g ); k1, rate constant of pseudo first order adsorption (min–1); R2, coefficient of determination. 2) qe2, adsorption amount at equilibrium in pseudo second order equation (mg g–1); k2, rate constant of pseudo second order adsorption (g mg–1 min–1). 3) a, Elovich constants (mg g–1 min–1); b, Elovich constants (g mg–1). 4) kid, rate constant of intraparticle diffusion adsorption (mg g–1 min–0.5); C, intraparticle diffusion constants.
172
120
10
8
6
4
2
0
6
80
Final pH
Adsorption (%)
100
60
4
40
2
20 0
200
8
Cu(II) adsorbed (mg g−1)
A
LI Cui-lan et al. Journal of Integrative Agriculture 2015, 14(1): 168–177
CHA CHA 0
2
P HA P HA 4 6 Initial pH
LHA LHA
0 10
8
Cu(II) adsorbed (mg g−1)
80 CHA PHA △ LHA
40
0
10 20 30 40 50 60 70 Equilibrium concentration of Cu(II) (mg L−1)
80
Fig. 4 Adsorption isotherms of Cu(II) on HA from CHA, PHA and LHA. Solid and dotted lines represent the model fitting of Langmuir and Freundlich equations, respectively. Arrows indicate the samples used for the XAFS analysis.
120 90
CHA
60
P HA
30
LHA
0 0.0
120
0
B 180 150
160
0.2
0.4 0.6 NaNO3 (mol L−1)
0.8
1.0
Fig. 3 Effect of pH (A) and ionic strength (B) on the adsorption of Cu(II) on HA from CHA, PHA and LHA. For pH experiment, solid and dotted lines represent the percentage adsorption vs. initial pH and initial pH vs. final pH, respectively.
adsorption capacities of Cu(II) (qm) on CHA, PHA, and LHA were 229.4, 210.4, and 197.7 mg g–1, respectively. The order of qm values for the three HA samples was identical to that of the Langmuir constant kL and the Freundlich constant kF. This finding suggested that the adsorption energy and capacity of CHA for Cu(II) were higher than those of PHA and LHA. The 1/n values in the Freundlich equation were less than 1, indicating that the adsorption was favorable over the entire range of Cu(II) concentrations studied, and the adsorption process was heterogeneous (Xu et al. 2012). The degree of adsorption favorability and
heterogeneity was the highest for CHA, followed by that of PHA and LHA, respectively. These results implied that CHA may have more important roles than PHA and LHA in controlling the fate, transport, and bioavailability of Cu(II) in the environment. By examining the relationship between the adsorption isotherm parameters (qm, kL, n, kF) and the chemical and spectroscopic characteristics of HA, we found that the isotherm parameters was in the same order as those of methoxyl C, phenolic C, carbonyl C, and C/N ratio, but opposite to those of alkyl C, carbohydrate C, and H/C, C/O, alkyl C/O-alkyl C and aliphatic C/aromatic C ratios. This finding may imply that the paraffin, lignin-derived moieties, and degrees of alkylation, aromaticity, maturity and polarity of HA are all responsible for its Cu(II) adsorption behavior. The greater adsorption capacity and affinity of CHA for Cu(II) may be due to its larger proportion of methoxyl C, phenolic C and carbonyl C, as well as its higher degree of maturity, smaller proportion of alkyl C and carbohydrate C, and lower degree of alkylation, polarity and aliphaticity compared with PHA and THA. The positive contribution of carboxyl and phenolic groups and the aromatic compounds in HA for adsorbing Cu(II) has been previously reported (Stevenson
Table 4 Adsorption isotherm parameters derived from Langmuir and Freundlich equations for Cu(II) adsorption on HA from CHA, PHA and LHA HA samples CHA PHA LHA 1) 2)
qm 229.4 210.4 197.7
Langmuir equation1) kL 0.071 0.063 0.047
R2 0.989 0.994 0.988
1/n 0.421 0.439 0.481
Freundlich equation2) kF 34.07 28.16 20.66
qm, maximum adsorption quantity (mg g–1); kL, Langmuir constants (L mg–1); R2, coefficient of determination. n, Freundlich constants (dimensionless); kF, Freundlich constants (mg g–1 (mg L–1)–1/n).
R2 0.977 0.975 0.972
LI Cui-lan et al. Journal of Integrative Agriculture 2015, 14(1): 168–177
A Normalized absorbance
CHA CHA PHA PHA LHA LHA
8 960
8 980
9 000 9 020 9 040 Energy (eV)
9 060
9 080
B
CHA CHA
k3χ(k)
PHA PHA LHA LHA 2
4
6
8
10
12
k(Å−1) C
CHA F(R)
CHA PHA PHA LHA LHA
0
2
4 R(Å)
6
8
Fig. 5 Normalized Cu K-edge XANES spectra (A), k3-weighted EXAFS spectra (B) and corresponding radial structure functions (C) for Cu(II) adsorbed on HA from CHA, PHA and lLHA. The initial Cu(II) concentrations are 20, 40, 15, 40, 15 and 40 mg L–1 from top to bottom in each sub-figure, respectively. Solid lines and open circles represent the experimental and fitted data, respectively.
1994; Ashley 1996; Gardea-Torresdey et al. 1996).
2.5. XAS spectra The normalized Cu K-edge XANES spectra, k3-weighted EXAFS spectra and corresponding radial structure functions (RSF) produced by Fourier transformations over the k range
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of 2.8-12.1 Å for the Cu(II) adsorption samples are shown in Fig. 5. The XANES spectra were similar, indicating that the binding site and the oxidation state of the Cu adsorbed on the HA surface were similar (Xia et al. 1997; Fang et al. 2011). All RFS were dominated by the peak centered at about 1.5 Å, which corresponded to the first Cu coordination shell consisting of O or N (O/N) atom. EXAFS was difficult to differentiate N from O because of the similar electron backscattering properties of the two atoms (Cheah et al. 1998). The next small peak centered at about 2.2 Å represented the second shell C atom, and the more distance peaks between 3 and 4.5 Å derived from the third shell O or C (O/C) atom and the Cu-C-O multiple scattering path (Xia et al. 1997; Strawn and Baker 2009). The structural parameters derived from best fitting of the first shell EXAFS signal are listed in Table 5. The Rf values were between 0.02 and 0.37%, indicating that the quality of the fits were good (Johnson and Kropf 2002). For the first coordination shell, each Cu atom was surrounded by 4 O/N atoms at a bond distance of 1.95 Å. Previous EXAFS results obtained from well-defined Cu(II)-containing compounds showed that Cu usually has a 6-coordinate structure with 4 equatorial O/N atoms at 1.90–1.97 Å and 2 axial O atoms at 2.15–2.78 Å in the first coordination shell (Karlsson 2005). Given the minimal contribution of the 2 axial O atoms to the EXAFS signal due to their large σ2 (Cheah et al. 2000; Karlsson 2005; Karlsson et al. 2006; Strawn and Baker 2008), the axial Cu-O backscattering pair was not included in the fits of EAXFS spectra for the present research. Thus, the 4 O/N atoms were most likely positioned in the equatorial plane of a Jahn-Teller distorted elongated octahedron (Karlsson et al. 2006). The average coordination environment for Cu(II) adsorbed on HA from organic materials in our study was in accordance to that for Cu(II) complexed/bound/adsorbed by HS from soils (Xia et al. 1997; Strawn and Baker 2009). Although the adsorbate concentrations affected the adsorption capacity of Cu(II) on HA, no obvious influence was observed on the structure of the adsorbed Cu in the range of Cu(II) concentration tested. On the other hand, Table 5 showed that the N values tended to decrease from 4.28 to 3.73 for CHA, from 4.29 to 3.98 for PHA, and from 3.93 to 3.60 for LHA, with initial Cu(II) concentrations from 15 to 40 mg L–1. The decreasing degree of disorder (as expressed by the Debye-Waller factor, σ2) could account for the decrease in N values. In addition, the decrease in N values was also possibly due to the electrostatic repulsion and the steric hindrance between the adsorbed Cu(II) under high Cu(II) concentrations, as interpreted by Zhao et al. (2011) based on the adsorption of Pb(II) on birnessites. Considering the large fitting errors that resulted from the
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the HA surface. Among the three HA samples, CHA had the greatest adsorption capacity and affinity for Cu(II), followed by PHA and LHA. The structural differences of the three HA samples are responsible for their distinct Cu(II) adsorption properties. Our results provide valuable information on the interaction of Cu(II) with HA extracted from different organic materials.
Table 5 EXAFS structural parameters of the first coordination shell for Cu(II) adsorbed on HA from CHA, PHA and LHA at different initial Cu(II) concentrations1) HA samples CHA PHA LHA
Cu(II) (mg L–1) 20 40 15 40 15 40
N2)
R3)
σ2 4)
ΔE05)
Rf6)
4.28 3.73 4.29 3.98 3.93 3.60
1.95 1.95 1.95 1.95 1.95 1.95
0.004 0.002 0.004 0.003 0.003 0.002
1.71 2.87 1.61 0.96 1.71 3.47
0.04 0.37 0.02 0.02 0.02 0.03
1)
4. Materials and methods
2
Amplitude reduction factor S 0 was fixed at 0.7 for all the samples. 2) N, coordination number. 3) R, bond distance (Å). 4) 2 σ , Debye-Waller factor (Å2). 5) ΔE0, energy shift (eV). 6) Rf, goodness-of-fit parameter (%).
4.1. Organic materials Cattle manure and fallen tree leaf samples were collected from a dairy farm and on campus, respectively, at Jilin Agricultural University, Jilin Province, Northeast China. Peat samples were obtained from Longtian Peat Co. Ltd., Jilin Province, Northeast China. All samples were air dried, smashed, and passed through a 2-mm sieve. The basic properties of the organic materials are reported in Table 6.
small peak intensities (Ippolito et al. 2013), the N values from the higher Cu coordination shells were not quantitatively analyzed in the present research. The bond distances of Cu-C and Cu-O/C obtained from EXAFS fitting of all Cu(II) adsorption samples were 2.75 and 3.70 Å, respectively. These bond distances were also in good agreement with those previously reported for Cu(II) adsorption on soil HA (Strawn and Baker 2009). The presence of the higher Cu coordination shells proved that Cu(II) was adsorbed via an inner-sphere covalent bond onto the HA surface.
4.2. Isolation and characterization of HA The extraction and purification of HA were carried out according to the procedure described in previous studies (Unsal and Ok 2001; Zhang et al. 2011) with some modifications. Briefly, 50 g of each sample was extracted six times with a solution of 0.1 mol L–1 NaOH and 0.1 mol L–1 Na4P2O7, precipitated with 6 mol L–1 HCl to pH 1, purified by three cycles of NaOH-dissolution and HCl-flocculation steps, dialyzed against distilled water, and then freeze dried. The pH of HA was determined with a PHS-3C digital pH meter (Shanghai Precision and Scientific Instrument Co., Ltd., China) in a suspension with a ratio of 1:2.5 of sample:water (mg mL–1), and the CEC was measured as suggested by Yan (1988). Elemental analysis (C, H, N, and S) was conducted on a Vario MICRO elemental analyzer (Elementar, Germany), and O content was calculated by mass difference. Ash content was determined by
3. Conclusion The adsorption of Cu(II) on HA was strongly dependent on pH and low ionic strength of 0.01–0.2 mol L–1 NaNO3. The adsorption kinetics followed the pseudo-second-order equation, and the adsorption isotherms could be well fitted by the Langmuir model. No obvious influence of adsorbate concentrations was observed on the local chemical environment of Cu(II) adsorbed on HA. For all the Cu(II) adsorption samples, Cu(II) was coordinated by 4 O/N atoms at a distance of 1.95 Å in the first coordination shell. The presence of the higher Cu coordination shells proved that Cu(II) was adsorbed via an inner-sphere covalent bond onto Table 6 Some chemical properties of organic materials used Organic materials Peat Cattle manure Leaf litter 1)
pH (H2O) 4.49 7.89 5.91
TOC (g kg–1)1) 327.3 331.5 333.9
TN (g kg–1)2) 22.7 18.9 12.2
TOC, total organic carbon. TN, total nitrogen. 3) WSFC, carbon content of water soluble fraction. 4) HEC, carbon content of total alkali-soluble humic extract. 5) HAC, carbon content of humic acid fraction. 6) FAC, carbon content of fulvic acid fraction. 2)
C/N 14.4 17.5 27.4
WSFC (g kg–1)3) 11.3 15.5 38.7
HEC (g kg–1)4) 128.4 91.8 64.4
HAC (g kg–1)5) 96.4 61.8 36.5
FAC (g kg–1)6) 32.0 30.0 27.9
HAC/ FAC 3.01 2.06 1.31
LI Cui-lan et al. Journal of Integrative Agriculture 2015, 14(1): 168–177
thermogravimetric analysis performed with a DTG-60 thermal analyzer (Shimadzu, Japan) from room temperature to 800°C at a heating rate of 5°C min –1. Solid-state 13 C cross-polarization magic-angle-spinning and totalsideband-suppression (CPMAS TOSS) NMR spectra were obtained with a Bruker AVANCE III 400 WB spectrometer (Switzerland) at 100.6 MHz under spinning speed of 5 kHz, contact time of 2 ms, and recycle time of 6 s.
equilibrium, V (L) is the volume of the solution, m (g) is the mass of the adsorbents, and C0 and Ce (mg L–1) are the initial and the equilibrium Cu(II) concentrations, respectively. The adsorption kinetics data were fitted with the pseudofirst-order model (eq. (3)), the pseudo-second-order model (eq. (4)), the Elovich model (eq. (5)), and the intraparticle diffusion model (eq. (6)): ln(qe−qt)=lnqe−k1t (3) t 1 t = + qt k2qe2 qe qt=bln(ab)+bln t
4.3. Adsorption experiments Batch adsorption experiments were carried out in 50 mL polyethylene centrifuge tubes containing 5 mg of HA sample and 25 mL of Cu(II) solution with the desired concentrations. Cu(II) was added as Cu(NO3)2·3H2O. The solution pH was adjusted to the desired value by the addition of 0.1 mol L–1 HNO3 or 0.1 mol L–1 NaOH before the adsorption experiment. The ionic strength of the solution was controlled using varying concentrations of NaNO3. The mixtures were gently shaken in a temperature-controlled water bath shaker at 298 K. After the specified contact time, the suspensions were centrifuged at 12 000 r min–1 for 15 min, and then filtered using 0.45-μm filters. The final pH was also recorded, and the Cu(II) concentrations in the filtrates were determined by a TAS-990 flame atomic absorption spectrophotometer (Beijing Purkinje General Instrument Co., Ltd., China). All experiments were run in duplicate or triplicate.
175
(4)
(5) (6) –1 Where, qt and qe (mg g ) are the adsorption amount at time t (min) and at equilibrium, respectively; k1 (min–1), k2 (g mg–1 min–1), and kid (mg g–1 min–0.5) are the rate constant of the pseudo first order, pseudo second order, and intraparticle diffusion adsorption, respectively; and a (mg g–1 min–1), b (g mg–1), and C are constants. The adsorption isotherm data were fitted with the Langmuir model (eq. (7)) and the Freundlich model (eq. (8)): qt=kidt0.5+C
qe=
kL q m C e 1+kLCe
(7)
qe=kFCe1/n
Cu K-edge XAS measurements were performed at the beamline 1W1B, Beijing Synchrotron Radiation Facility (BSRF), China. The storage ring was operated at 2.5 GeV with maximum beam current of 200 mA. A Si (111) doublecrystal monochromator was used. The wet solid samples obtained by centrifugation after adsorption experiments were loaded into a Teflon sample holder and sealed with Kapton tape. Spectra were collected over the range of 8 835 to 9 965 eV in fluorescence mode using a Lytle detector under ambient conditions.
(8) Where, qm (mg g–1) and kL (L mg–1) are the Langmuir constants related to the maximum adsorption capacity and energy or intensity of adsorption, respectively; and kF (mg g–1 (mg L–1)–1/n) and 1/n are the Freundlich constants representing the adsorption capacity and the adsorption intensity or heterogeneity of adsorbent, respectively. The XAS data were analyzed with the Athena and Artemis programs of the IFEFFIT computer package (Zabinsky et al. 1995; Newville 2001). For the fitting of the first coordination shell, the amplitude reduction factor (S02) was kept constant at 0.7. The values of the coordination number (N), bond distance (R), Debye-Waller factor (σ2), and energy shift (ΔE0) were allowed to vary. The goodness-of-fit parameter R-factor (Rf) was used to evaluate the quality of the fit. Accuracy estimates of the fitted parameters were ±0.01 Å for R and ±20% for N.
4.5. Data analysis
Acknowledgements
The amounts and percentage of adsorbed Cu(II) were calculated by the mass balance equations (eqs). (1) and (2):
This work was supported by the Key Technologies R&D Program of China (2013BAD07B02 and 2013BAC09B01), the Special Fund for Agro-Scientific Research in the Public Interest of China (201103003), the Postdoctoral Project of Jilin Province, China (01912), and the Doctoral Initiative Foundation of Jilin Agricultural University, China (201216). Valuable comments by three anonymous reviewers greatly improved the manuscript.
4.4. XAS measurements
qe=(C0−Ce)
V m
Adsorption (%)=
(1) (C0−Ce) C0
×100
(2)
Where, qe (mg g–1) is the amount of Cu(II) adsorbed at
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Karlsson T. 2005. Complexation of cadmium, copper and methyl mercury to functional groups in natural organic matter. Studied by X-ray absorption spectroscopy and binding affinity experiments. Ph D thesis, Swedish University of Agricultural Sciences, Swedish. Li J, Hu J, Sheng G, Zhao G, Huang Q. 2009. Effect of pH, ionic strength, foreign ions and temperature on the adsorption of Cu(II) from aqueous solution to GMZ bentonite. Colloids and Surfaces (A: Physicochemical and Engineering Aspects), 349, 195-201. Li J, Wu J. 2013. Compositional and structural difference of fulvic acid from black soil applied with different organic materials: Assessment after three years. Journal of Integrative Agriculture, 12, 1865-1871. Li Y, Yue Q, Gao B. 2010. Adsorption kinetics and desorption of Cu(II) and Zn(II) from aqueous solution onto humic acid. Journal of Hazardous Materials, 178, 455-461. Liang X, Xu Y, Wang L, Sun Y, Lin D, Sun Y, Qin X, Wan Q. 2013. Sorption of Pb2+ on mercapto functionalized sepiolite. Chemosphere, 90, 548-555. Newville M. 2001. IFEFFIT: Interactive XAFS analysis and FEFF fitting. Journal of Synchrotron Radiation, 8, 324-332. Nierop K G J, Buurman P, de Leeuw J W. 1999. Effect of vegetation on chemical composition of H horizons in incipient podzols as characterized by 13C NMR and pyrolysis-GC/MS. Geoderma, 90, 111-129. Ribeiro J S, Ok S S, Garrigues S, de la Guardia M. 2001. FTIR tentative characterization of humic acids extracted from organic materials. Spectroscopy Letters, 34, 179-190. Rice J A, MacCarthy P. 1991. Statistical evaluation of the elemental composition of humic substances. Organic Geochemistry, 17, 635-648. Simpson A J, McNally D J, Simpson M J. 2011. NMR spectroscopy in environmental research: From molecular interactions to global processes. Progress in Nuclear Magnetic Resonance Spectroscopy, 58, 97-175. Stevenson F J. 1994. Humus Chemistry: Genesis, Composition, and Reactions. John Wiley & Sons, New York. Strawn D G, Baker L L. 2008. Speciation of Cu in a contaminated agricultural soil measured by XAFS, μ-XAFS, and μ-XRF. Environmental Science and Technology, 42, 37-42. Strawn D G, Baker L L. 2009. Molecular characterization of copper in soils using X-ray absorption spectroscopy. Environmental Pollution, 157, 2813-2821. Tan X, Chang P, Fan Q, Zhou X, Yu S, Wu W, Wang X. 2008. Sorption of Pb(II) on Na-rectorite: Effects of pH, ionic strength, temperature, soil humic acid and fulvic acid. Colloids and Surfaces (A: Physicochemical and Engineering Aspects), 328, 8-14. Theng B K G. 2012. Humic substances. Developments in Clay Science, 4, 391-456. Unsal T, Ok S S. 2001. Description of characteristics of humic substances from different waste materials. Bioresource Technology, 78, 239-242. Wang S, Hu J, Li J, Dong Y. 2009. Influence of pH, soil humic/fulvic acid, ionic strength, foreign ions and addition
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ScienceDirect
RESEARCH ARTICLE
Adsorption of Cu(II) on humic acids derived from different organic materials LI Cui-lan1, JI Fan1, WANG Shuai2, ZHANG Jin-jing1, GAO Qiang1, WU Jing-gui1, ZHAO Lan-po1, WANG Li-chun3, ZHENG Li-rong4 1
College of Resource and Environmental Science, Jilin Agricultural University, Changchun 130118, P.R.China Institute of Plant Science, Jilin Agricultural Science and Technology College, Jilin 132101, P.R.China 3 Institute of Agricultural Resources and Environments, Jilin Academy of Agricultural Sciences, Changchun 130124, P.R.China 4 Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, P.R.China 2
Abstract The adsorption of Cu(II) from aqueous solution onto humic acid (HA) which was isolated from cattle manure (CHA), peat (PHA), and leaf litter (LHA) as a function of contact time, pH, ion strength, and initial concentration was studied using the batch method. X-ray absorption spectroscopy (XAS) was used to examine the coordination environment of the Cu(II) adsorbed by HA at a molecular level. Moreover, the chemical compositions of the isolated HA were characterized by elemental analysis and solid-state 13C nuclear magnetic resonance spectroscopy (NMR). The kinetic data showed that the adsorption equilibrium can be achieved within 8 h. The adsorption kinetics followed the pseudo-second-order equation. The adsorption isotherms could be well fitted by the Langmuir model, and the maximum adsorption capacities of Cu(II) on CHA, PHA, and LHA were 229.4, 210.4, and 197.7 mg g–1, respectively. The adsorption of Cu(II) on HA increased with the increase in pH from 2 to 7, and maintained a high level at pH>7. The adsorption of Cu(II) was also strongly influenced by the low ionic strength of 0.01 to 0.2 mol L–1 NaNO3, but was weakly influenced by high ionic strength of 0.4 to 1 mol L–1 NaNO3. The Cu(II) adsorption on HA may be mainly attributed to ion exchange and surface complexation. XAS results revealed that the binding site and oxidation state of Cu adsorbed on HA surface did not change at the initial Cu(II) concentrations of 15 to 40 mg L–1. For all the Cu(II) adsorption samples, each Cu atom was surrounded by 4 O/N atoms at a bond distance of 1.95 Å in the first coordination shell. The presence of the higher Cu coordination shells proved that Cu(II) was adsorbed via an inner-sphere covalent bond onto the HA surface. Among the three HA samples, the adsorption capacity and affinity of CHA for Cu(II) was the greatest, followed by that of PHA and LHA. All the three HA samples exhibited similar types of elemental and functional groups, but different contents of elemental and functional groups. CHA contained larger proportions of methoxyl C, phenolic C and carbonyl C, and smaller proportions of alkyl C and carbohydrate C than PHA and LHA. The structural differences of the three HA samples are responsible for their distinct adsorption capacity and affinity toward Cu(II). These results are important to achieve better understanding of the behavior of Cu(II) in soil and water bodies in the presence of organic materials.
Received 22 August, 2013 Accepted 28 November, 2013 Correspondence ZHANG Jin-jing, Tel: +86-431-84532955, E-mail: [email protected]; ZHENG Li-rong, Tel: +86-1088235980, E-mail: [email protected] © 2015, CAAS. All rights reserved. Published by Elsevier Ltd. doi: 10.1016/S2095-3119(13)60682-6
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Keywords: humic acid, Cu(II), adsorption, organic material, 13C NMR, XAS
1. Introduction Humic substances (HS) are the most widely distributed natural nonliving organic compounds occurring in soils, waters, sediments, peat, and other organic wastes (Xu and Huang 2010; Zhang et al. 2013). One of the most striking features of HS is their strong interaction with inorganic and organic pollutants. Humic acid (HA) represents the major extractable component of HS. The interactions between HA and metal ions are important in controlling the behavior and fate of trace metals in the environment (Theng 2012). In natural environments, copper (Cu) is an essential micronutrient for all living organisms, but can become toxic when it presents in excessive concentrations (Wright and Welbourn 2002). Moreover, Cu has a strong affinity for HS (Arias et al. 2002; Zhang et al. 2010). Adsorption is one of the most important interactions between Cu(II) and HS. Thus, understanding the adsorption properties of Cu(II) onto HS is important to minimize the potentially harmful effects of Cu(II) in the environment. The use and management of organic materials are important global issues (Khalil et al. 2005). In agriculture, organic materials with various origins and natures have been widely used for improving soil fertility and increasing crop productivity (Li and Wu 2013). These organic materials are rich natural sources of HA in the environment (Davies and Ghabbour 1998; Ribeiro et al. 2001; Hur et al. 2011). Meanwhile, HA from different sources of organic materials, called HA-like fractions in some situations, have significant effects on the composition, structure, and functionality of HA in native soil amended with these organic materials (Brunetti et al. 2007). Thus, determining the adsorption characteristics of Cu(II) on organic material-derived HA for reasonable usage of organic materials and forecast of Cu(II) behaviors in various environments is crucial. Although previous studies have examined the adsorption properties of Cu(II) on some organic materials (Gardea-Torresdey et al. 1996), few studies have been conducted to compare the differences of Cu(II) adsorption behaviors on HA derived from organic materials of different sources.
Macroscopic batch adsorption experiments and microscopic spectroscopic techniques can be combined to elucidate the mechanisms of Cu(II) adsorption on HS. Synchrotron-based X-ray absorption spectroscopy (XAS), including X-ray absorption near-edge structure (XANES) spectroscopy and extended X-ray absorption fine structure (EXAFS) spectroscopy, is a useful technique that can provide molecular-level information about the local chemical environments of trace metals in HS (Xia et al. 1997; Ginder-Vogel and Sparks 2010). Meanwhile, the mechanisms of Cu(II) adsorption on HS also depend on the chemical structure of the latter. Elemental analysis and solid-state 13C nuclear magnetic resonance (NMR) technology are powerful tools for describing their structural characteristics (Rice and MacCarthy 1991; Simpson et al. 2011). The present study aims to determine the adsorption behaviors of Cu(II) on HA isolated from three organic materials (i.e., cattle manure, peat, and leaf litter) at different contact times, pH, ion strengths, and initial Cu concentrations by batch experiments, and to examine the coordination environment of Cu(II) adsorbed by HA at a molecular level using XAS techniques. The chemical compositions of the isolated HA are characterized by elemental analysis and solid-state 13 C NMR spectroscopy.
2. Results and discussion 2.1. Characterization of HA The pH values were 4.64, 4.09 and 4.26, and the cation exchange capacity (CEC) values were 340.7, 257.5 and 182.8 cmol (+) kg–1 for HA from the cattle manure (CHA), peat (PHA), and leaf litter (LHA), respectively. The elemental composition and atomic ratios of the three HA samples are presented in Table 1. The compositional values obtained were within the ranges reported in Rice and MacCarthy (1991). The C and O contents, as well as the C/N ratio of HA, tended to increase in the order LHA
Table 1 Ash contents, elemental composition, and atomic ratios of HA from cattle manure (CHA), peat (PHA), and leaf litter (LHA) HA samples CHA PHA LHA
Ash (g kg–1) 11.2 36.2 78.1
C (g kg–1) 561.6 559.1 539.6
H (g kg–1) 55.3 57.8 58.3
N (g kg–1) 31.0 33.3 34.2
S (g kg–1) 5.61 3.04 5.53
O (g kg–1) 335.3 310.5 284.2
H/C 1.182 1.241 1.297
C/O 2.234 2.401 2.531
C/N 21.1 19.6 18.4
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maturity, and polarity of HA, respectively (Nierop et al. 1999;
phobicity degree was similar.
Xing et al. 2005). Therefore, our results suggested that CHA was the least aliphatic, the least mature and the most polar,
2.2. Adsorption kinetics
whereas LHA was the most aliphatic, the most mature and the least polar among the three HA samples. The 13C NMR spectra of HA are shown in Fig. 1. The three HA samples exhibited very similar functional group types. All spectra were identified as alkyl C (0–50 ppm), methoxyl C (50–60 ppm), carbohydrate C (60–110 ppm), aryl C (110–145 ppm), phenolic C (145–160 ppm), and carbonyl C (160–200 ppm). On the other hand, the relative intensities of the C functional groups differed among the three HA samples (Table 2). Alkyl C and carbohydrate C tended to increase in the order CHA
LHA
PHA
CHA 200 180 160 140 120 100 80
60
40
20
0
Fig. 1 13C CPMAS TOSS NMR spectra of humic acid (HA) from cattle manure (CHA), peat (PHA) and leaf litter (LHA).
The effect of contact time on the adsorption of Cu(II) on HA is shown in Fig. 2, and the corresponding kinetic parameters from the pseudo-first-order, pseudo-second-order Elovich and intraparticle diffusion equations are listed in Table 3. The shapes of kinetic curves for the three HA samples were similar, which was ascribed to their similar structures and functional groups. The adsorption occurred rapidly within the first 30 min, and then increased slowly. The adsorption equilibrium was finally reached within 8 h. The oxygen-containing functional groups, especially the carboxyl group, are believed to have a vital role in the binding of metal ions by humic substances (Zhang et al. 2013). The exposure of these groups to HA surfaces is responsible for the rapid adsorption of Cu(II) by HA (Gardea-Torresdey et al. 1996). The pseudo-second-order equation fitted the kinetic data better than the pseudo-first-order, Elovich and intraparticle diffusion equations, as given by the higher coefficient of determination R2 (>0.99) from the former. Meanwhile, the calculated qe values from the pseudo-second-order equation were close to the experimental data. The adsorption data for the intraparticle diffusion equation showed two-linear plots representing the surface or film diffusion and a gradual adsorption stage, respectively (Liang et al. 2013). The pseudo-second-order equation was based on the assumption that the rate-limiting step may be chemical adsorption (Li et al. 2010). Therefore, these results indicated that chemical adsorption rather than intraparticle diffusion was the rate-controlling step. Among the three HA samples, the adsorption amount of Cu(II) was the greatest for CHA, followed by that of PHA and LHA.
2.3. Effects of pH and ion strength The effect of pH on Cu(II) adsorption on HA is shown in Fig. 3-A. The equilibrium pH was slightly lower than the initial pH, indicating that H+ was released from the HA surface into solution during the adsorption process. A similar result
Table 2 Relative carbon distribution (%) in different regions of chemical shift in 13C CPMAS TOSS NMR spectra of HA from CHA, PHA and LHA HA samples CHA PHA LHA 1) 2) 3)
0–50 13.7 15.5 17.9
50–60 14.0 11.9 10.7
Chemical shift regions (ppm) 60–110 110–145 22.0 22.0 23.4 23.8 27.7 19.4
145–160 14.0 11.8 11.3
A/O–A, alkyl C/O–alkyl C=(0–50)/(50–110) Alip/Arom, aliphatic C/aromatic C=[(0–50)+(50–110)]/(110–160) HB/HI, hydrophobic C/hydrophilic C=[(0–50)+(110–160)]/[(50–110)+(160–200)]
160–200 14.3 13.7 12.9
A/O–A1) 0.382 0.439 0.465
Alip/Arom2) HB/HI3) 1.376 1.429 1.830
0.993 1.043 0.947
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Cu(II) adsorbed (mg g−1)
A 150 140 130 120
CHA PHA
110
LHA
100 0
300
600
900
1 200
1 500
Time (min)
Cu(II) adsorbed (mg g−1)
B 150 140 130 120 110 100 0
10
20
30
40
Time0.5 (min0.5)
tion of H+ in the solution decreased and the surface negative charge of HA increased; thus, the adsorption of Cu(II) on HA gradually increased. When pH was above 8, the removal of Cu(II) was mainly controlled by the precipitation of Cu(OH)2(s) on the HA surface (Alvarez-Puebla et al. 2004). In general, surface complexation is pH dependent (Tan et al. 2008; Wang et al. 2009). Therefore, the pH dependent adsorption of Cu(II) on HA suggested that the process was dominated by surface complexation. The effect of ionic strength on the adsorption of Cu(II) on HA is shown in Fig. 3-B. The adsorption amounts of Cu(II) on HA decreased with the increase of NaNO3 concentrations from 0.01 to 1 mol L–1. When the ionic strength was lower than 0.2 mol L–1, the adsorption of Cu(II) was generally sensitive to changes in the ionic strength. However, the changes in ionic strength caused only a relatively small change for Cu(II) adsorption when the ionic strength was higher than 0.4 mol L–1. The decrease in Cu(II) adsorption with increasing ion strength was attributed to the competitive adsorption of Cu2+ with Na+ on the HA surface and the compression of the double layers at the solid/liquid interface (Wang et al. 2009; Liang et al. 2013). The adverse effect of ionic strength on Cu(II) adsorption suggested that ion exchange contributes to the adsorption process (Li et al. 2009; Wang et al. 2009).
2.4. Adsorption isotherms
Fig. 2 Adsorption kinetics of Cu(II) on HA from CHA, PHA and LHA. Solid (A) and dotted (B) lines represent the experimental curves and model fitting of intraparticle diffusion equation, respectively.
was reported for Cu(II) adsorption onto commercial-derived HA (Li et al. 2010). The adsorption of Cu(II) on HA increased slowly at the pH range of 2 to 5, then increased abruptly at pH 5 to 7, and finally reached the maximum and remained constant at pH>7. The low Cu(II) adsorption at low pH can be due to the competition between H+ and Cu2+ for the same sites on the HA surface. With increasing pH, the concentra-
The adsorption isotherms of Cu(II) on HA are shown in Fig. 4, and the parameters of the Langmuir and the Freundlich equations obtained by fitting the isotherms are given in Table 4. All the three HA samples displayed similar shapes of adsorption isotherms. The amount of adsorbed Cu(II) on HA increased with the increase in Cu(II) concentrations. The adsorption data can be well described by both Langmuir and Freundlich equations with R2 values greater than 0.972. However, the Langmuir equation provided a better fit, with R2 values ranging from 0.988 to 0.994. Based on the Langmuir equation, the maximum
Table 3 Adsorption kinetic parameters derived from pseudo-first-order, pseudo-second-order, Elovich and intraparticle diffusion equations for Cu(II) adsorption on HA from CHA, PHA and LHA HA samples
Pseudo-first-order1) qe1 R2 k × 10–1 1
Pseudo-second-order2) qe2 k2×10–1 R2
Elovich3) b
a
R
2
Intraparticle diffusion4) kid C R2
CHA
21.35
0.052
0.738
141.6
0.017
0.999
6.21× 1010
4.30
0.933
0.593
124.6 0.670
PHA
18.88
0.047
0.684
135.3
0.017
0.999
9.26× 10
3.57
0.943
0.502
120.6 0.700
LHA
19.22
0.058
0.782
128.2
0.019
0.999
4.59× 10
4.23
0.942
0.584
116.4 0.676
1)
–1
12 9
qe1, adsorption amount at equilibrium in pseudo first order equation (mg g ); k1, rate constant of pseudo first order adsorption (min–1); R2, coefficient of determination. 2) qe2, adsorption amount at equilibrium in pseudo second order equation (mg g–1); k2, rate constant of pseudo second order adsorption (g mg–1 min–1). 3) a, Elovich constants (mg g–1 min–1); b, Elovich constants (g mg–1). 4) kid, rate constant of intraparticle diffusion adsorption (mg g–1 min–0.5); C, intraparticle diffusion constants.
172
120
10
8
6
4
2
0
6
80
Final pH
Adsorption (%)
100
60
4
40
2
20 0
200
8
Cu(II) adsorbed (mg g−1)
A
LI Cui-lan et al. Journal of Integrative Agriculture 2015, 14(1): 168–177
CHA CHA 0
2
P HA P HA 4 6 Initial pH
LHA LHA
0 10
8
Cu(II) adsorbed (mg g−1)
80 CHA PHA △ LHA
40
0
10 20 30 40 50 60 70 Equilibrium concentration of Cu(II) (mg L−1)
80
Fig. 4 Adsorption isotherms of Cu(II) on HA from CHA, PHA and LHA. Solid and dotted lines represent the model fitting of Langmuir and Freundlich equations, respectively. Arrows indicate the samples used for the XAFS analysis.
120 90
CHA
60
P HA
30
LHA
0 0.0
120
0
B 180 150
160
0.2
0.4 0.6 NaNO3 (mol L−1)
0.8
1.0
Fig. 3 Effect of pH (A) and ionic strength (B) on the adsorption of Cu(II) on HA from CHA, PHA and LHA. For pH experiment, solid and dotted lines represent the percentage adsorption vs. initial pH and initial pH vs. final pH, respectively.
adsorption capacities of Cu(II) (qm) on CHA, PHA, and LHA were 229.4, 210.4, and 197.7 mg g–1, respectively. The order of qm values for the three HA samples was identical to that of the Langmuir constant kL and the Freundlich constant kF. This finding suggested that the adsorption energy and capacity of CHA for Cu(II) were higher than those of PHA and LHA. The 1/n values in the Freundlich equation were less than 1, indicating that the adsorption was favorable over the entire range of Cu(II) concentrations studied, and the adsorption process was heterogeneous (Xu et al. 2012). The degree of adsorption favorability and
heterogeneity was the highest for CHA, followed by that of PHA and LHA, respectively. These results implied that CHA may have more important roles than PHA and LHA in controlling the fate, transport, and bioavailability of Cu(II) in the environment. By examining the relationship between the adsorption isotherm parameters (qm, kL, n, kF) and the chemical and spectroscopic characteristics of HA, we found that the isotherm parameters was in the same order as those of methoxyl C, phenolic C, carbonyl C, and C/N ratio, but opposite to those of alkyl C, carbohydrate C, and H/C, C/O, alkyl C/O-alkyl C and aliphatic C/aromatic C ratios. This finding may imply that the paraffin, lignin-derived moieties, and degrees of alkylation, aromaticity, maturity and polarity of HA are all responsible for its Cu(II) adsorption behavior. The greater adsorption capacity and affinity of CHA for Cu(II) may be due to its larger proportion of methoxyl C, phenolic C and carbonyl C, as well as its higher degree of maturity, smaller proportion of alkyl C and carbohydrate C, and lower degree of alkylation, polarity and aliphaticity compared with PHA and THA. The positive contribution of carboxyl and phenolic groups and the aromatic compounds in HA for adsorbing Cu(II) has been previously reported (Stevenson
Table 4 Adsorption isotherm parameters derived from Langmuir and Freundlich equations for Cu(II) adsorption on HA from CHA, PHA and LHA HA samples CHA PHA LHA 1) 2)
qm 229.4 210.4 197.7
Langmuir equation1) kL 0.071 0.063 0.047
R2 0.989 0.994 0.988
1/n 0.421 0.439 0.481
Freundlich equation2) kF 34.07 28.16 20.66
qm, maximum adsorption quantity (mg g–1); kL, Langmuir constants (L mg–1); R2, coefficient of determination. n, Freundlich constants (dimensionless); kF, Freundlich constants (mg g–1 (mg L–1)–1/n).
R2 0.977 0.975 0.972
LI Cui-lan et al. Journal of Integrative Agriculture 2015, 14(1): 168–177
A Normalized absorbance
CHA CHA PHA PHA LHA LHA
8 960
8 980
9 000 9 020 9 040 Energy (eV)
9 060
9 080
B
CHA CHA
k3χ(k)
PHA PHA LHA LHA 2
4
6
8
10
12
k(Å−1) C
CHA F(R)
CHA PHA PHA LHA LHA
0
2
4 R(Å)
6
8
Fig. 5 Normalized Cu K-edge XANES spectra (A), k3-weighted EXAFS spectra (B) and corresponding radial structure functions (C) for Cu(II) adsorbed on HA from CHA, PHA and lLHA. The initial Cu(II) concentrations are 20, 40, 15, 40, 15 and 40 mg L–1 from top to bottom in each sub-figure, respectively. Solid lines and open circles represent the experimental and fitted data, respectively.
1994; Ashley 1996; Gardea-Torresdey et al. 1996).
2.5. XAS spectra The normalized Cu K-edge XANES spectra, k3-weighted EXAFS spectra and corresponding radial structure functions (RSF) produced by Fourier transformations over the k range
173
of 2.8-12.1 Å for the Cu(II) adsorption samples are shown in Fig. 5. The XANES spectra were similar, indicating that the binding site and the oxidation state of the Cu adsorbed on the HA surface were similar (Xia et al. 1997; Fang et al. 2011). All RFS were dominated by the peak centered at about 1.5 Å, which corresponded to the first Cu coordination shell consisting of O or N (O/N) atom. EXAFS was difficult to differentiate N from O because of the similar electron backscattering properties of the two atoms (Cheah et al. 1998). The next small peak centered at about 2.2 Å represented the second shell C atom, and the more distance peaks between 3 and 4.5 Å derived from the third shell O or C (O/C) atom and the Cu-C-O multiple scattering path (Xia et al. 1997; Strawn and Baker 2009). The structural parameters derived from best fitting of the first shell EXAFS signal are listed in Table 5. The Rf values were between 0.02 and 0.37%, indicating that the quality of the fits were good (Johnson and Kropf 2002). For the first coordination shell, each Cu atom was surrounded by 4 O/N atoms at a bond distance of 1.95 Å. Previous EXAFS results obtained from well-defined Cu(II)-containing compounds showed that Cu usually has a 6-coordinate structure with 4 equatorial O/N atoms at 1.90–1.97 Å and 2 axial O atoms at 2.15–2.78 Å in the first coordination shell (Karlsson 2005). Given the minimal contribution of the 2 axial O atoms to the EXAFS signal due to their large σ2 (Cheah et al. 2000; Karlsson 2005; Karlsson et al. 2006; Strawn and Baker 2008), the axial Cu-O backscattering pair was not included in the fits of EAXFS spectra for the present research. Thus, the 4 O/N atoms were most likely positioned in the equatorial plane of a Jahn-Teller distorted elongated octahedron (Karlsson et al. 2006). The average coordination environment for Cu(II) adsorbed on HA from organic materials in our study was in accordance to that for Cu(II) complexed/bound/adsorbed by HS from soils (Xia et al. 1997; Strawn and Baker 2009). Although the adsorbate concentrations affected the adsorption capacity of Cu(II) on HA, no obvious influence was observed on the structure of the adsorbed Cu in the range of Cu(II) concentration tested. On the other hand, Table 5 showed that the N values tended to decrease from 4.28 to 3.73 for CHA, from 4.29 to 3.98 for PHA, and from 3.93 to 3.60 for LHA, with initial Cu(II) concentrations from 15 to 40 mg L–1. The decreasing degree of disorder (as expressed by the Debye-Waller factor, σ2) could account for the decrease in N values. In addition, the decrease in N values was also possibly due to the electrostatic repulsion and the steric hindrance between the adsorbed Cu(II) under high Cu(II) concentrations, as interpreted by Zhao et al. (2011) based on the adsorption of Pb(II) on birnessites. Considering the large fitting errors that resulted from the
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the HA surface. Among the three HA samples, CHA had the greatest adsorption capacity and affinity for Cu(II), followed by PHA and LHA. The structural differences of the three HA samples are responsible for their distinct Cu(II) adsorption properties. Our results provide valuable information on the interaction of Cu(II) with HA extracted from different organic materials.
Table 5 EXAFS structural parameters of the first coordination shell for Cu(II) adsorbed on HA from CHA, PHA and LHA at different initial Cu(II) concentrations1) HA samples CHA PHA LHA
Cu(II) (mg L–1) 20 40 15 40 15 40
N2)
R3)
σ2 4)
ΔE05)
Rf6)
4.28 3.73 4.29 3.98 3.93 3.60
1.95 1.95 1.95 1.95 1.95 1.95
0.004 0.002 0.004 0.003 0.003 0.002
1.71 2.87 1.61 0.96 1.71 3.47
0.04 0.37 0.02 0.02 0.02 0.03
1)
4. Materials and methods
2
Amplitude reduction factor S 0 was fixed at 0.7 for all the samples. 2) N, coordination number. 3) R, bond distance (Å). 4) 2 σ , Debye-Waller factor (Å2). 5) ΔE0, energy shift (eV). 6) Rf, goodness-of-fit parameter (%).
4.1. Organic materials Cattle manure and fallen tree leaf samples were collected from a dairy farm and on campus, respectively, at Jilin Agricultural University, Jilin Province, Northeast China. Peat samples were obtained from Longtian Peat Co. Ltd., Jilin Province, Northeast China. All samples were air dried, smashed, and passed through a 2-mm sieve. The basic properties of the organic materials are reported in Table 6.
small peak intensities (Ippolito et al. 2013), the N values from the higher Cu coordination shells were not quantitatively analyzed in the present research. The bond distances of Cu-C and Cu-O/C obtained from EXAFS fitting of all Cu(II) adsorption samples were 2.75 and 3.70 Å, respectively. These bond distances were also in good agreement with those previously reported for Cu(II) adsorption on soil HA (Strawn and Baker 2009). The presence of the higher Cu coordination shells proved that Cu(II) was adsorbed via an inner-sphere covalent bond onto the HA surface.
4.2. Isolation and characterization of HA The extraction and purification of HA were carried out according to the procedure described in previous studies (Unsal and Ok 2001; Zhang et al. 2011) with some modifications. Briefly, 50 g of each sample was extracted six times with a solution of 0.1 mol L–1 NaOH and 0.1 mol L–1 Na4P2O7, precipitated with 6 mol L–1 HCl to pH 1, purified by three cycles of NaOH-dissolution and HCl-flocculation steps, dialyzed against distilled water, and then freeze dried. The pH of HA was determined with a PHS-3C digital pH meter (Shanghai Precision and Scientific Instrument Co., Ltd., China) in a suspension with a ratio of 1:2.5 of sample:water (mg mL–1), and the CEC was measured as suggested by Yan (1988). Elemental analysis (C, H, N, and S) was conducted on a Vario MICRO elemental analyzer (Elementar, Germany), and O content was calculated by mass difference. Ash content was determined by
3. Conclusion The adsorption of Cu(II) on HA was strongly dependent on pH and low ionic strength of 0.01–0.2 mol L–1 NaNO3. The adsorption kinetics followed the pseudo-second-order equation, and the adsorption isotherms could be well fitted by the Langmuir model. No obvious influence of adsorbate concentrations was observed on the local chemical environment of Cu(II) adsorbed on HA. For all the Cu(II) adsorption samples, Cu(II) was coordinated by 4 O/N atoms at a distance of 1.95 Å in the first coordination shell. The presence of the higher Cu coordination shells proved that Cu(II) was adsorbed via an inner-sphere covalent bond onto Table 6 Some chemical properties of organic materials used Organic materials Peat Cattle manure Leaf litter 1)
pH (H2O) 4.49 7.89 5.91
TOC (g kg–1)1) 327.3 331.5 333.9
TN (g kg–1)2) 22.7 18.9 12.2
TOC, total organic carbon. TN, total nitrogen. 3) WSFC, carbon content of water soluble fraction. 4) HEC, carbon content of total alkali-soluble humic extract. 5) HAC, carbon content of humic acid fraction. 6) FAC, carbon content of fulvic acid fraction. 2)
C/N 14.4 17.5 27.4
WSFC (g kg–1)3) 11.3 15.5 38.7
HEC (g kg–1)4) 128.4 91.8 64.4
HAC (g kg–1)5) 96.4 61.8 36.5
FAC (g kg–1)6) 32.0 30.0 27.9
HAC/ FAC 3.01 2.06 1.31
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thermogravimetric analysis performed with a DTG-60 thermal analyzer (Shimadzu, Japan) from room temperature to 800°C at a heating rate of 5°C min –1. Solid-state 13 C cross-polarization magic-angle-spinning and totalsideband-suppression (CPMAS TOSS) NMR spectra were obtained with a Bruker AVANCE III 400 WB spectrometer (Switzerland) at 100.6 MHz under spinning speed of 5 kHz, contact time of 2 ms, and recycle time of 6 s.
equilibrium, V (L) is the volume of the solution, m (g) is the mass of the adsorbents, and C0 and Ce (mg L–1) are the initial and the equilibrium Cu(II) concentrations, respectively. The adsorption kinetics data were fitted with the pseudofirst-order model (eq. (3)), the pseudo-second-order model (eq. (4)), the Elovich model (eq. (5)), and the intraparticle diffusion model (eq. (6)): ln(qe−qt)=lnqe−k1t (3) t 1 t = + qt k2qe2 qe qt=bln(ab)+bln t
4.3. Adsorption experiments Batch adsorption experiments were carried out in 50 mL polyethylene centrifuge tubes containing 5 mg of HA sample and 25 mL of Cu(II) solution with the desired concentrations. Cu(II) was added as Cu(NO3)2·3H2O. The solution pH was adjusted to the desired value by the addition of 0.1 mol L–1 HNO3 or 0.1 mol L–1 NaOH before the adsorption experiment. The ionic strength of the solution was controlled using varying concentrations of NaNO3. The mixtures were gently shaken in a temperature-controlled water bath shaker at 298 K. After the specified contact time, the suspensions were centrifuged at 12 000 r min–1 for 15 min, and then filtered using 0.45-μm filters. The final pH was also recorded, and the Cu(II) concentrations in the filtrates were determined by a TAS-990 flame atomic absorption spectrophotometer (Beijing Purkinje General Instrument Co., Ltd., China). All experiments were run in duplicate or triplicate.
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(4)
(5) (6) –1 Where, qt and qe (mg g ) are the adsorption amount at time t (min) and at equilibrium, respectively; k1 (min–1), k2 (g mg–1 min–1), and kid (mg g–1 min–0.5) are the rate constant of the pseudo first order, pseudo second order, and intraparticle diffusion adsorption, respectively; and a (mg g–1 min–1), b (g mg–1), and C are constants. The adsorption isotherm data were fitted with the Langmuir model (eq. (7)) and the Freundlich model (eq. (8)): qt=kidt0.5+C
qe=
kL q m C e 1+kLCe
(7)
qe=kFCe1/n
Cu K-edge XAS measurements were performed at the beamline 1W1B, Beijing Synchrotron Radiation Facility (BSRF), China. The storage ring was operated at 2.5 GeV with maximum beam current of 200 mA. A Si (111) doublecrystal monochromator was used. The wet solid samples obtained by centrifugation after adsorption experiments were loaded into a Teflon sample holder and sealed with Kapton tape. Spectra were collected over the range of 8 835 to 9 965 eV in fluorescence mode using a Lytle detector under ambient conditions.
(8) Where, qm (mg g–1) and kL (L mg–1) are the Langmuir constants related to the maximum adsorption capacity and energy or intensity of adsorption, respectively; and kF (mg g–1 (mg L–1)–1/n) and 1/n are the Freundlich constants representing the adsorption capacity and the adsorption intensity or heterogeneity of adsorbent, respectively. The XAS data were analyzed with the Athena and Artemis programs of the IFEFFIT computer package (Zabinsky et al. 1995; Newville 2001). For the fitting of the first coordination shell, the amplitude reduction factor (S02) was kept constant at 0.7. The values of the coordination number (N), bond distance (R), Debye-Waller factor (σ2), and energy shift (ΔE0) were allowed to vary. The goodness-of-fit parameter R-factor (Rf) was used to evaluate the quality of the fit. Accuracy estimates of the fitted parameters were ±0.01 Å for R and ±20% for N.
4.5. Data analysis
Acknowledgements
The amounts and percentage of adsorbed Cu(II) were calculated by the mass balance equations (eqs). (1) and (2):
This work was supported by the Key Technologies R&D Program of China (2013BAD07B02 and 2013BAC09B01), the Special Fund for Agro-Scientific Research in the Public Interest of China (201103003), the Postdoctoral Project of Jilin Province, China (01912), and the Doctoral Initiative Foundation of Jilin Agricultural University, China (201216). Valuable comments by three anonymous reviewers greatly improved the manuscript.
4.4. XAS measurements
qe=(C0−Ce)
V m
Adsorption (%)=
(1) (C0−Ce) C0
×100
(2)
Where, qe (mg g–1) is the amount of Cu(II) adsorbed at
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