Abstract

This study aims to discover the impact of composting and pyrolysis on the adsorption performance of Auricularia auricula dreg (AAD) for Cd(II) in aqueous solution. Auricularia auricula dreg (AAD), Auricularia auricula dreg biochar (AADB) and Auricularia auricula dreg compost (AADC) were used to remove Cd(II) from aqueous solution, and their adsorption conditions and mechanisms were compared. The adsorption quantity of three adsorbents reached the maximum (AAD: 80.0 mg/g, AADB: 91.7 mg/g, AADC: 93.5 mg/g) under same conditions (adsorbent dosage of 1 g/L, pH 5.0, biosorption temperature of 25 °C, and biosorption time of 120 min). All Cd(II) biosorption processes onto three adsorbents complied with the Langmuir isotherm model and the pseudo-second-order kinetic equation, and spontaneously occurred in an order of AADC > AADB > AAD. The difference in biosorption quantity relied on variation in surface structure, crystal species and element content caused by composting or pyrolysis. Composting enhanced the changes in surface structure, crystal species, functional groups and ion exchange capacity of the AAD, resulting in AAD had greatly improved the biosorption quantity of Cd(II). Pyrolysis increased the adsorption of Cd(II) mainly by increasing the Brunauer–Emmett–Teller (BET) surface area, the particle size and pH, in the same time, providing more oxygen-containing functional groups.

INTRODUCTION

Cadmium, as one of the most toxic heavy metals causing abdominal pain, nausea, muscle cramps, bone marrow damage, and kidney stones (Lee et al. 2012), has been classified as class I carcinogen by the international cancer institute. Cadmium-containing industrial wastewater has seriously threatened human health and caused ecological damage. China's environmental protection law stipulates that the maximum allowable emission concentration of cadmium in industrial wastewater is 1.0 mg/L and the maximum allowable emission concentration of cadmium is 0.1 mg/L. The traditional methods including chemical precipitation, electrolysis, biosorption, membrane separation and ion exchange have been employed to treat the industrial wastewater (Bayo 2012), among which biosorption method has more advantages in cost, operation process and high efficiency for low concentration metal-contaminated water.

Auricularia auricula dreg (AAD) is an agricultural by-product with a wide range of sources and a relative low price in mushroom production. The main components of this waste dreg include sugars, organic acids, and biologically active substances, on which distribute hydroxyl, carboxyl, amide, and phosphate groups that can chelate heavy metal ions in wastewater. In our previous study, AAD has been used to remove lead(II) and Cr(VI) (Dong et al. 2017; Song et al. 2017a) and chemically modified AAD has been used to adsorb Cd(II) (Song et al. 2017b), however, its biosorption efficiency is still lower than that of other biosorbents derived from agricultural byproduct (Mukherjee et al. 2011). To improve the biosorption capacity, a physical process such as pyrolysis and composting is also employed to treat the adsorbents. Biochar is a highly aromatic and difficult-to-penetrate solid material resulting from pyrolysis under hypoxia or low oxygen. The aromatic sheets provide biochar with a loose and porous structure, moreover, a large number of oxygen-containing groups such as phenolic hydroxyl, carboxyl and carbonyl groups formed during pyrolysis are beneficial to the biosorption of metallic ions (Kumar et al. 2013; Regmi et al. 2012; Lin et al. 2012). Composting is an aerobic process that decomposes the organic material into humus-like material (Naja & Volesky 2006). After composting, the agricultural waste changes to a highly porous and complex mixtures with abundant functional groups and strong ion exchange capacity. During composting, organic matter is decomposed and transformed into stable humic compounds, which have the ability to combine with metal ions. In the composting process, many hydrophilic groups will be produced, which will increase the adsorption of heavy metal ions in the compost. Studies have shown that compost has a highly complex mixture of polymer functional groups and high ion exchange capacity. Moreover, the compost is also rich in lignin and chitin, which are the reasons why compost has a good adsorption effect on metal ions in high-concentration metal ion industrial wastewater (Mattuschka & Straube 1993).

This study aims to compare the biosorption for Cd(II) among the three kinds of adsorbents prepared from Auricularia auricula dreg. The optimal experimental conditions including pH, adsorbent dosage, biosorption temperature and biosorption time were explored in the batch experiments. The biosorption characteristics were discussed by isotherm, kinetic equation and thermodynamic analysis. The biosorption mechanisms were revealed by scanning electron microscopy (SEM), surface area analyzer, Fourier transform infrared (FTIR) spectroscopy, X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS) and analysis in pH, zeta potential, Brunauer–Emmett–Teller (BET), cation exchange capacity (CEC) and oxygen-containing functional groups.

MATERIALS AND METHODS

Adsorbents preparation

Auricularia auricula dreg was provided by Xiangfang edible fungi plant, Harbin, China. AAD was rinsed with distilled water, dried to constant weight at 70 °C, and ground into powders less than 0.3 mm in diameter. Auricularia auricula dreg bichar (AADB) was obtained by heating ADD in a muff oven at 500 °C for 120 min. Auricularia auricula dreg compost (AADC) was prepared by mixing AAD with cow dung at ratio of 1:1 and fermenting at room temperature for 3 months, then the acquired adsorbent was dried and ground into powders in a diameter of 0.3 mm.

Chemicals and reagents

All chemicals used in this study were of analytical grade. The stock solution (1 g/L) of Cd(II) was prepared by dissolving 2.7442 g of cadmium nitrate (Cd(NO3)2.4H2O) (Guangfu Fine Chemical, Tianjin, China) in 1 L of deionized water and work solution at desired concentration was prepared by diluting stock solution. The initial pH was adjusted with 0.1 M NaOH (Kermel Chemical Reagent Co., Ltd, Tianjin, China) or 0.1 M HCl (Pilot Chemical Co., Shanghai, China) solution.

Batch biosorption experiments

The batch biosorption experiments were conducted in 150 mL Erlenmeyer flask containing 100 mL of diluted Cd(II) solution. The experiments were operated at different conditions: pH of 2, 3, 4, and 5, adsorbent dosage of 1, 2, 3, 4, and 5 g/L, biosorption temperature of 20, 25, 30, and 35 °C, and biosorption time of 20, 40, 60, 80, 100, and 120 min. When the biosorption reached equilibrium, the samples were filtered and the residual amount of Cd(II) was determined using atomic absorption spectrophotometer (AA-6800 model, Shimadzu-GL, Japan). The biosorption quantity (Q) for Cd(II) were calculated with the following equations: 
formula
(1)
where C0 and Ce are the initial and the equilibrium concentration of Cd(II) in solution (mg/L), respectively; m is mass of adsorbent (g) and v is the volume of reaction solution (L).

Biosorption isotherm model

Biosorption isotherm refers to the relationship of the metal ion concentration between the liquid phase and the solid phase (adsorbent) reaching equilibrium at a certain temperature (Hu et al. 2011; Kwon & Jeon. 2012). In this study, Langmuir and Freundlich isotherm models were used to fit the experimental data. The biosorption isotherms were carried out at 303 K, the adsorbent dosage of 1 g/L, the rotation speed of 160 r/min, the biosorption time of 120 min, the solution pH of 5, and the initial concentration of Cd(II) varying from 25–100 mg/L. The Langmuir and Freundlich isotherm equation were expressed as follows.

Langmuir isotherm equation (Langmuir 1918): 
formula
(2)
Freundlich isotherm equation (Freundlich & Helle 1939): 
formula
(3)
where Qe is the equilibrium biosorption quantity of Cd(II) (mg/g); Qmax is the maximum biosorption quantity in theory (mg/g); Ce is the equilibrium concentration of Cd(II) in solution (mg/L; and KL is the Langmuir equilibrium biosorption constant (L/mg)); KF is the Freundlich constant associated with the biosorption quantity; n represents a constant relating to the biosorption intensity.

Biosorption kinetics

Pseudo-first-order model and pseudo-second-order model were used to describe the biosorption characteristics. The experiment was carried out at 303 K, the adsorbent dosage of 1 g/L, pH 5, and initial concentration of 100 mg/L. The concentration of Cd(II) was measured after the sample was taken at 20, 40, 60, 80, 100 and 120 min, respectively. The kinetic models were expressed as follows.

The pseudo-first-order kinetic model: 
formula
(4)
The pseudo-second-order kinetic model: 
formula
(5)
where qe is the biosorption quantity of Cd(II) at equilibrium (mg/g); qt is the biosorption quantity at time t (mg/g); t is the biosorption time (min); k1 is the rate constant of pseudo-first-order biosorption (1/min); k2 is the rate constant of pseudo-second-order biosorption (g/mg·min).

Biosorption thermodynamics

The thermodynamic study was carried out at 298 K. Gibbs free energy (ΔG°) was given as follows: 
formula
(6)
 
formula
(7)
where R is the universal gas constant (8.314 J/(mol·K)); T is the absolute temperature in Kelvin (K); K is for biosorption equilibrium constant; qe is the biosorption quantity of Cd(II) (mg/g); ce is the equilibrium concentration of Cd(II).

Biosorption mechanism

Scanning electron microscopy (SEM) (QuANTA200 model, American FEI, USA) and energy-dispersive X-ray spectroscopy (EDX) (LEO 1455 VP/EDX Oxford 300, UK) were used to analyze the surface morphology and element content of adsorbents; Fourier transform infrared spectrometer (Alpha, Bruker, Germany) was used to analyze the functional groups; X-ray diffraction (XRD) (D/max2200 model, Hitachi, Japan) was employed to detect the crystalline structure; the element composition of adsorbent loaded with cadmium ions was analyzed by XPS (VG Scientific EACALab220i-XL). Surface area analyzer (ASAP 2020, Micromeritics, USA) was applied to determine the specific surface area, the pore volume and the pore diameter of three adsorbents; pH meter (Corning, Model 140) was used to measure the pH of the adsorbents; the potential of the fine particles (Zeta) of the sample were measured by a type of micro-electrophoresis apparatus (JS94F). Cation exchange capacity (CEC) was measured with sodium acetate-flame photometric method. Boehm titrations were used to differentiate and quantify oxygen based functional groups.

RESULTS AND DISCUSSION

Batch biosorption experiments

Effect of solution pH

The effect of solution pH has a great influence on the biosorption process of heavy metal ions. In this study, the solution pH between 2 and 5 was set to prevent the formation of cadmium precipitates (Chen & Chen 2009). The effect of solution pH on Cd(II) biosorption onto the three kinds of adsorbents is shown in Figure 1(a). At pH 2 to 5, the biosorption quantity of the three adsorbents obviously increased with the increased pH value and reached maximum of 80.0, 91.7 and 93.5 mg/g for AAD, AADB and AADC at pH 5, respectively. Apparently, at all tested pH, the biosorption quantity of AADC and AADB were higher than that of AAD, and the maximum biosorption quantities of AADC and AABD were higher than that of AAD by 14.4% and 12.7%, respectively. The effect of solution pH on biosorption efficiency was correlated with the participation of functional groups in the adsorption (Nomanbhay & Palanisamy 2004). From the FTIR analyses, it could be seen that AADC and AADB had more functional groups than AAD. In the same time, from the later results analysis of biosorption mechanism, it also could be concluded that composting and pyrolysis had a great influence on AAD, which could make more active sites exposed to adsorb Cd(II). At low pH, more H+ occupied biosorption sites on the adsorbent surface rather than Cd(II); when pH rose, more negatively charged groups appeared on the adsorbent surface and more Cd(II) ions were adsorbed.

Figure 1

(a) Effect of solution pH on Cd(II) biosorption (25 °C, 150 r/min, adsorbent dosage of 1 g/L, biosorption time of 120 min, Cd(II) initial concentration of 100 mg/L); (b) Effect of adsorbent dosage on Cd(II) biosorption (25 °C, 150 r/min, biosorptiontime of 120 min, pH 5, Cd(II) initial concentration of 100 mg/L); (c) Effect of temperature on Cd(II) biosorption (adsorbent dosage of 1 g/L, 150 r/min, pH 5, biosorption time of 120 min, Cd(II) initial concentration of 100 mg/L); and (d) Effect of biosorption time on Cd(II) biosorption (25 °C, adsorbent dosage of 1 g/L, 150 r/min, pH 5, Cd(II) initial concentration of 100 mg/L).

Figure 1

(a) Effect of solution pH on Cd(II) biosorption (25 °C, 150 r/min, adsorbent dosage of 1 g/L, biosorption time of 120 min, Cd(II) initial concentration of 100 mg/L); (b) Effect of adsorbent dosage on Cd(II) biosorption (25 °C, 150 r/min, biosorptiontime of 120 min, pH 5, Cd(II) initial concentration of 100 mg/L); (c) Effect of temperature on Cd(II) biosorption (adsorbent dosage of 1 g/L, 150 r/min, pH 5, biosorption time of 120 min, Cd(II) initial concentration of 100 mg/L); and (d) Effect of biosorption time on Cd(II) biosorption (25 °C, adsorbent dosage of 1 g/L, 150 r/min, pH 5, Cd(II) initial concentration of 100 mg/L).

Effect of adsorbent dosage

The adsorbent dosage determines the amount of active sites for Cd biosorption and directly affects the biosorption quantity. From Figure 1(b), when the adsorbent dosage ascended from 1 g/L to 5 g/L, the biosorption quantity of AADC decreased from 93.5 mg/g to 19.4 mg/g, and that of AADB from 91.7 mg/g to 19.2 mg/g, but both were higher than that of AAD at corresponding dosage (from 80.0 mg/g to 18.2 mg/g). No matter what the dosage was, the adsorption quantity of AADC and AADB was higher than that of AAD. When the adsorbent dosage increased, overlap and polymerization occurred between the adsorbents. When the adsorbent overlapped or polymerized, the effective sites with ion exchange activity were also reduced, resulting in a decreased biosorption (Huang et al. 2008; Hu et al. 2014). For AADB and AADC, pyrolysis and composting could provide more hydrogen and ammonia than AAD, more adsorbent dosage meant more hydroxide and ammonia which was helpful to adsorb Cd(II). Considering the effect of adsorbent dosage on the biosorption quantity, this experiment selected the adsorbent dosage of 1 g/L for subsequent experiments.

Effect of temperature

Since biosorption process might involve both endothermic and exothermic process, the temperature must be an important factor in Cd(II) biosorption. In this study, the biosorption quantities of three adsorbents were all increased rapidly (62.0 mg/g to 93.5 mg/g, 58.5 mg/g to 91.7 mg/g and 59.0 mg/g to 80.0 mg/g for AADC, AADB and AAD, respectively) as temperature elevated from 20 °C to 25 °C. This might be due to the presence of chemisorption during the biosorption process. Chemisorption is an endothermic process in which the system absorbs heat from surroundings, therefore higher temperature favors the occurrence of this process. When the temperature rose, the ion velocity of the solution increased, accelerating the diffusion of the adsorbent, and promoting the effective collision between the metal ions and the adsorbent surface (Kumar & Chakraborty 2009; Kumar et al. 2011). When the temperature rose from 25 °C to 35 °C, the biosorption quantity of the three adsorbents were all decreased from 93.5 mg/g to 65.0 mg/g, 91.7 mg/g to 63.0 mg/g and 80.0 mg/g to 62.0 mg/g for AADC, AADB and AAD, respectively. This might be due to the presence of physical process during the biosorption. The physical biosorption mainly carried out at a low temperature, and the desorption might occur with the increase of temperature (Lodeiro et al. 2006; Luo et al. 2011). Obviously, the maximum biosorption quantity for each biosorbent was obtained at 25 °C in the order of AADC > AADB > AAD. However, there was one point to note that when temperature ascended to 30 °C, the biosorption quantity of AAD only changed slightly.

Effect of biosorption time

The effect of biosorption time is shown in Figure 1(d). From 20 min to 120 min, the biosorption quantities of AADC, AADB and AAD were increased from 52.0 mg/g to 93.5 mg/g, 50.0 mg/g to 91.7 mg/g, and 30.0 mg/g to 80.0 mg/g, respectively. It could be seen clearly that the variation tendency of biosorption quantities of AADC and AADB were more alike. And the maximum biosorption quantities of AADC and AABD were 14.4% and 12.7% higher than that of AAD, respectively. The adsorption efficiency of AADB and AADC was better than that of AAD; the reason might be that many basic properties such as specific surface area, porosity, element content and functional groups were changed during pyrolysis and composting. These were mentioned in the analyses of the following mechanisms. From the figure, it can be deduced that the sorption speed in the early stage was fast, and it gradually slowed down in the later stage. This was mainly due to the mass transfer impetus that resulted from the difference in Cd(II) concentration on the adsorbent surface and in the solution, which facilitated the ion exchange. With the progress of biosorption, the differential between the concentration of Cd(II) gradually narrowed and the biosorption sites for Cd(II) to occupy also reduced, resulting in a slower biosorption rate and a final biosorption equilibrium.

Biosorption isotherms

The isothermal model can be used to estimate the affinity between the adsorbate and the adsorbent and describe the surface characteristics of the adsorbent (Tan & Xiao 2009). The Langmuir isotherm model is derived from the assumption of monolayer biosorption between gas and solid phases, which is commonly used to determine the adsorption properties of metal ions at the interface of solid materials (Vimala & Das 2009). The Freundlich isotherm biosorption model is commonly used in the biosorption process of inorganic or organic matter to simulate the biosorption under irrational conditions and the multilayer biosorption mechanism (Torab-Mostaedi et al. 2013). As seen from Figure 2 and Table 1, the experimental data of the three adsorbents conformed to both Langmuir and Freundlich models, indicating that monolayer biosorption and multilayer biosorption coexisted in these biosorption processes. And the higher R2 value of the Langmuir model indicated that the Langmuir model was better to describe the biosorption and monolayer biosorption might dominate the process. According to the average biosorption energy (E) given in Table 1, it was inferred that the biosorption process was mainly chemibiosorption (Oguz 2005). Meanwhile, based on Langmuir model, the theoretical maximum biosorption quantity for Cd(II) of the three biosorbents was AADC > AADB > AAD. A comparison of biosorption quantity between other adsorbents and the three adsorbents is shown in Table 2, apparently, though the biosorption quantity of AAD was 14.0% and 15.2% lower than that of AADB and AADC, respectively, they were all higher than that of other adsorbents, indicating the Auricularia auricula dreg derived adsorbents performed better in the biosorption of Cd(II).

Table 1

Parameters of Langmuir and Freundlich isotherm models

Models AAD AADB AADC 
Langmuir qmax (mg/g) 84.6 96.5 97.5 
KL (L/mg) 0.109 0.212 0.194 
R2 0.9964 0.9985 0.9949 
Freundlich 2.17 2.13 2.04 
KF (mg/g)/(mg/L)1/n 13.589 20.436 19.265 
R2 0.9503 0.9659 0.9770 
Models AAD AADB AADC 
Langmuir qmax (mg/g) 84.6 96.5 97.5 
KL (L/mg) 0.109 0.212 0.194 
R2 0.9964 0.9985 0.9949 
Freundlich 2.17 2.13 2.04 
KF (mg/g)/(mg/L)1/n 13.589 20.436 19.265 
R2 0.9503 0.9659 0.9770 
Table 2

Qmax of various adsorbents for Cd(II) biosorption

Adsorbent Qmax(mg/g) Reference 
S. platensis 73.6 Çelekli & Bozkurt (2011)  
Pomelo peel 21.8 Njoku et al. (2012)  
Ceramium virgatum 39.7 Sari & Tuzen (2008)  
Waste tea leaves 31.5 Tee & Khan (1988)  
Chlorella vulgaris 85.3 Aksu (2001)  
Chlamydomonas reinhardtii 42.6 Tuzun et al. (2005)  
Olive cake 65.4 Panda et al. (2007)  
Nile water algae 29.6 Wang et al. (2007)  
AAD 84.6 This study 
AADB 96.5 This study 
AADC 97.5 This study 
Adsorbent Qmax(mg/g) Reference 
S. platensis 73.6 Çelekli & Bozkurt (2011)  
Pomelo peel 21.8 Njoku et al. (2012)  
Ceramium virgatum 39.7 Sari & Tuzen (2008)  
Waste tea leaves 31.5 Tee & Khan (1988)  
Chlorella vulgaris 85.3 Aksu (2001)  
Chlamydomonas reinhardtii 42.6 Tuzun et al. (2005)  
Olive cake 65.4 Panda et al. (2007)  
Nile water algae 29.6 Wang et al. (2007)  
AAD 84.6 This study 
AADB 96.5 This study 
AADC 97.5 This study 
Figure 2

Langmuir (a), Freundlich (b) and isotherm models for Cd(II) biosorption.

Figure 2

Langmuir (a), Freundlich (b) and isotherm models for Cd(II) biosorption.

Biosorption kinetics

The pseudo-first-order kinetic and pseudo-second-order kinetic models were used to illustrate the kinetic characteristics of Cd(II) biosorption by the three biosorbents. As shown in Figure 3 and Table 3, the R2 values of pseudo-second-order kinetics were greater than the those of pseudo-first-order kinetics, indicating that the biosorption process of the three adsorbents was more suitable for the pseudo-second-order kinetic model. Compared with the R2 values of pseudo-first-order kinetics of AAD(0.9344), that of AADB(0.8494) and AADC(0.8024) were lower clearly. This might be due to composting and pyrolysis causing changes in the surface functional groups of the adsorbent, resulting in changes in functional groups involved in biosorption.

Table 3

Parameters of two kinetic models

Adsorbents Experimental Pseudo-first-order kinetics
 
Pseudo-second-order kinetics
 
qe (mg/g) k1 (1/min) qe (mg/g) R2 k2 (g/mg min) qe (mg/g) R2 
AAD 80.0 0.038 147.6 0.9344 0.141 × 10−3 121.9 0.9977 
AADB 91.7 0.044 149.1 0.8494 0.389 × 10−3 109.0 0.9998 
AADC 93.5 0.0381 126.4 0.8024 0.454 × 10−3 106.6 0.9997 
Adsorbents Experimental Pseudo-first-order kinetics
 
Pseudo-second-order kinetics
 
qe (mg/g) k1 (1/min) qe (mg/g) R2 k2 (g/mg min) qe (mg/g) R2 
AAD 80.0 0.038 147.6 0.9344 0.141 × 10−3 121.9 0.9977 
AADB 91.7 0.044 149.1 0.8494 0.389 × 10−3 109.0 0.9998 
AADC 93.5 0.0381 126.4 0.8024 0.454 × 10−3 106.6 0.9997 
Figure 3

Pseudo-first-order (a) and pseudo-second-order (b) kinetic model plot for Cd(II) biosorption.

Figure 3

Pseudo-first-order (a) and pseudo-second-order (b) kinetic model plot for Cd(II) biosorption.

The biosorption quantity of AAD, AADB and AADC obtained by pseudo-first-order kinetics was about 147.6 mg/g, 149.1 mg/g, 126.4 mg/g, respectively, while that obtained by pseudo-second-order kinetics was about 121.9 mg/g, 109.0 mg/g and 106.6 mg/g, which closer to that obtained from this experiment. Considering the results from isotherm and kinetic models, it could be deduced that the biosorption process was mainly dominated by a chemical process (Harja et al. 2012).

Thermodynamic modeling

As the result shows in Table 4, ΔG0 values of the three adsorbents were all less than 0 which indicated that the biosorption reaction was spontaneous. The smaller the Gibbs free energy, the greater the spontaneity of the reaction. From Table 4, it can be seen that the spontaneity of the three adsorbents was in the order of AADC > AADB > AAD.

Table 4

ΔG0 for Cd(II) biosorption onto three adsorbents

Thermodynamic parameter AAD AADB AADC 
ΔG0 (kJ/mol) −3.435 −5.952 −6.606 
Thermodynamic parameter AAD AADB AADC 
ΔG0 (kJ/mol) −3.435 −5.952 −6.606 

Biosorption mechanism

SEM-EDX analyses

The surface morphology of different adsorbents was observed under a scanning electron microscope at a magnification of 500 times. As seen in Figure 4, the surface of AAD had an irregularly lamellar and porous structure. These special structures would provide AAD the ability to adsorb heavy metals. Both AADC and AADB exhibited a relatively regular porous structure, and AADB had some tubular structures around the pores on its surface, which might be caused by the collapse of structures such as lignocellulose during carbonization (Park et al. 2015). It is these structures that give them good adsorption efficiency.

Figure 4

SEM images of the three adsorbents: (a) AAD, (b) AADB, and (c) AADC.

Figure 4

SEM images of the three adsorbents: (a) AAD, (b) AADB, and (c) AADC.

The elemental composition of three adsorbents are shown in Table 5. The relative weight (in percent) of C of AADB was obviously higher than that of AADC and AAD, but that of N and O were obviously less than that of AADC and AAD, which might be due to the dehydration of hemicellulose, cellulose, lignin and other substances, the polycondensation of aromatic ring into carbon, and the release of volatile organic compounds. It could also be seen from the XRD analysis that a large amount of nitrate-containing substances existed on AADC after composting, which was also the reason for the increase in the content of N. After biosorption, the content of Na, Mg, Al and Si for the three adsorbents were all increased, and Cd(II) appeared on the biosorbents after biosorption. The relative weight (in percent) of Cd on AADC was obviously higher than that on AADB and AAD. This was in line with the results of the batch biosorption experiments that the biosorption efficiency of AADC was higher than that of AADB and AAD.

Table 5

Elemental composition of three adsorbents

Element AAD (Wt%)
 
AADB (Wt%)
 
AADC (Wt%)
 
Native AAD AAD-Cd Native AADB AADB-Cd Native AADC AADC-Cd 
41.94 47.69 49.13 52.34 26.54 32.07 
11.55 9.73 14.03 9.57 18.98 19.34 
37.48 35.89 30.04 25.88 42.68 26.24 
Na 0.87 1.45 0.92 1.20 1.70 1.87 
Mg 0.48 0.54 0.74 1.03 1.00 1.15 
Al 0.45 0.37 0.06 0.24 0.27 1.90 
Si 0.61 0.83 0.34 1.92 1.60 2.28 
0.07 0.00 1.71 1.13 0.43 2.51 
Cl 0.06 0.04 0.17 0.05 0.57 0.09 
0.12 0.00 2.04 0.54 1.11 1.26 
Ca 1.03 0.57 0.09 3.72 1.11 3.94 
Pt 5.34 2.09 0.73 1.49 4.01 4.15 
Cd 0.00 0.80 0.00 0.89 0.00 3.20 
Element AAD (Wt%)
 
AADB (Wt%)
 
AADC (Wt%)
 
Native AAD AAD-Cd Native AADB AADB-Cd Native AADC AADC-Cd 
41.94 47.69 49.13 52.34 26.54 32.07 
11.55 9.73 14.03 9.57 18.98 19.34 
37.48 35.89 30.04 25.88 42.68 26.24 
Na 0.87 1.45 0.92 1.20 1.70 1.87 
Mg 0.48 0.54 0.74 1.03 1.00 1.15 
Al 0.45 0.37 0.06 0.24 0.27 1.90 
Si 0.61 0.83 0.34 1.92 1.60 2.28 
0.07 0.00 1.71 1.13 0.43 2.51 
Cl 0.06 0.04 0.17 0.05 0.57 0.09 
0.12 0.00 2.04 0.54 1.11 1.26 
Ca 1.03 0.57 0.09 3.72 1.11 3.94 
Pt 5.34 2.09 0.73 1.49 4.01 4.15 
Cd 0.00 0.80 0.00 0.89 0.00 3.20 

FTIR analyses

The FTIR profiles and functional groups of three biosorbents before and after biosorption are given in Figure 5 and Table 6. It could be seen clearly that all three adsorbents contained -OH, CO32− and PO43−. For AAD, there were C = O and -NH presented at the peak of 1,620 cm−1 and 1,480 cm−1, but the peak intensity was not strong, indicating that the number of functional groups involved in biosorption was not as great as that in AADC. For AADB, the intensity of the peaks in the range of 800–1,500 cm−1 was obviously stronger than those of other two adsorbents which indicated this region contained relatively abundant functional groups and might play a major role in the biosorption process. The functional groups involved in biosorption were mainly CO32−, -C-O-C- and PO43−. It also could be seen clearly from Table 6 that compared with the other two adsorbents, AADB lacked many functional groups, such as -CH and -NH which might be caused by pyrolysis (Baldock & Smernik 2002) which was one of the reasons why its adsorption efficiency was not as good as AADC. For AADC, the peaks near 2,900–3,000 cm−1 were symmetric or asymmetric C-H and -CH2 stretching vibration of aliphatic acids. The diffuse peak near 3,280 cm−1 was derived from the broad peak of stretching vibration of -OH. The absorption peak shifted after biosorption indicated its involvement in the biosorption reaction. The diffuse peak near 1,480 cm−1 and 1,620 cm−1 were the stretching vibration of -NH and the peak near 1,620 cm−1 was C = O absorption peak in carboxyl group and ketone. After biosorption, they all had a significant changes in vibration frequency which might be due to surface biosorption and complexation (Tan & Xiao 2009). Compared with AAD, the increased intensity of -NH in AADC might be the conversion of inorganic ammonia to organic ammonia during composting (Rumapar et al. 2013). As described above, the difference in functional groups contained in the three adsorbents has a great influence on the adsorption of cadmium, which could explain the results of the batch biosorption experiments. As shown in Figure 5, with the peaks before and after the adsorption were compared, it could be seen from FTIR image that the intensity of the characteristic peaks of the three adsorbents changed greatly before and after biosorption, indicating that chemical changes including redox, ion exchange, and coordination might occur during the whole process. And the positional shifts and the generation of new peaks indicated that these biosorptions were all a combination of physical and chemical processes.

Table 6

The wavenumbers and functional groups of three adsorbents

AAD wavenumber (cm−1)
 
AADB wavenumber (cm−1)
 
AADC wavenumber (cm−1)
 
Functional groups 
Native AAD AAD-Cd Native AADB AADB-Cd Native AADC AADC-Cd 
3,315 3,310 3,323 3,324 3,280 3,290 -OH (Lin et al. 2012
2,990 2,984 absent absent 3,000 2,990 -CH (Safari et al. 2013
1,490 1,490 absent absent 1,480 1,490 -NH (Wahab et al. 2010
852 852 867 875 871 873 CO32− (Kalinke et al. 2016
1,406 1,408 1,398 1,399 1,410 1,413 
1,620 1,621 absent absent 1,620 1,625 C = O of COOH and -NH (Wahab et al. 2010
absent 1,820 1,805 1,804 absent absent C = O (Li et al. 2007
1,030 1,030 1,032 1,032 1,030 1,028 PO43− and Si-O-Si (Kalinke et al. 2016
absent absent 1,256 1,260 absent absent -C-O-C- 
2,920 2,920 absent absent 2,920 2,920 -CH (Safari et al. 2013
AAD wavenumber (cm−1)
 
AADB wavenumber (cm−1)
 
AADC wavenumber (cm−1)
 
Functional groups 
Native AAD AAD-Cd Native AADB AADB-Cd Native AADC AADC-Cd 
3,315 3,310 3,323 3,324 3,280 3,290 -OH (Lin et al. 2012
2,990 2,984 absent absent 3,000 2,990 -CH (Safari et al. 2013
1,490 1,490 absent absent 1,480 1,490 -NH (Wahab et al. 2010
852 852 867 875 871 873 CO32− (Kalinke et al. 2016
1,406 1,408 1,398 1,399 1,410 1,413 
1,620 1,621 absent absent 1,620 1,625 C = O of COOH and -NH (Wahab et al. 2010
absent 1,820 1,805 1,804 absent absent C = O (Li et al. 2007
1,030 1,030 1,032 1,032 1,030 1,028 PO43− and Si-O-Si (Kalinke et al. 2016
absent absent 1,256 1,260 absent absent -C-O-C- 
2,920 2,920 absent absent 2,920 2,920 -CH (Safari et al. 2013
Figure 5

FTIR images of three adsorbents: (a) AAD, (b) AADB, and (c) AADC.

Figure 5

FTIR images of three adsorbents: (a) AAD, (b) AADB, and (c) AADC.

XRD analyses

A difference of the XRD profile of AADC, AADB and AAD before and after biosorption is shown in Figure 6 and the details of crystalline species are given in Table 7. All three adsorbents had a broad peak at the 2θ of 20–30°, which represented that these materials contained a high content of cellulose. As for AAD, the sharp peak at the 2θ about 14.437° was the crystal of CH4N2O!C2H2O. At the peaks around 21–23°, there was a broad peak which represented Na2Mg(PO3)4, Ca2Fe(CN)6 and Ca(NO2)2 and so on. As for AADB, the peaks at the 2θ about 29.062° and 26.212° represented FeSi2 and CaCO3, respectively, which were not available in AAD. As for AADC, there was a sharp peak at the 2θ about 26° and the major crystalline species was SiO2 which played an important role in the complexation and coordination of metal ions. Compared with AAD, there were many new peaks appeared, the elements contained in the substances represented by these peaks could also be seen in the elemental analysis. After the biosorption, the new peak at 2θ about 30.063° representing Cd4P2O9 appeared on AAD, indicating that Cd was well adsorbed. Compared with two other adsorbent materials, AAD was obviously missing some sharp peaks which can be seen in Figure 6. The absence of these sharp peaks might indicate that AAD lacked some functional groups than the other two adsorbents. This also explained why the biosorption efficiency of AAD was not as good as that of the other two adsorbents. After biosorption of AADB, the XRD diffraction peak did not change much, which can be clearly seen from Figure 6. From Table 7, it can be seen that after biosorption, the major crystalline species also lacked hydroxyl groups compared with AADC. After the biosorption of Cd(II) for AADC, various compounds containing Cd were present. These compounds had various groups such as hydroxyl, nitro, amino and phosphate groups. As above, it explained why the biosorption performance of AADC was better than that of AADB and AAD.

Table 7

The crystalline species of the three adsorbents before and after biosorption

AAD
 
AADB
 
AADC
 
Native AAD
 
AAD-cd
 
Native AADB
 
AADB-Cd
 
Native AADC
 
AADC-Cd
 
2θ Crystalline species 2θ Crystalline species 2θ Crystalline species 2θ Crystalline species 2θ Crystalline species 2θ Crystalline species 
23.266 Na2Mg(PO3)4 15.060 (NH4)8P6O19!2H215.003 C4H4CuO6!3H226.831 C2H2CaO4 21.238 MgAl2O4!7.9H227.165 CH6N2O2!0.5H2
14.437 CH4N2O!C2H2O4 15.029 Mg5(CO3)4(OH)2!8H217.796 CH6N2O2!0.5H229.756 (NH4)2CO3!H229.395 Na2CO3!10H217.894 Cd(OH)2 
26.243 SiO2 15.588 C4H10CdN4O6 17.408 Fe2O2CO3 29.198 2NH3!H229.454 FeSiO3 17.724 Cd(NO3)2!4H2
25.651 Ca5(SiO4)2CO3 30.063 Cd4P2O9 35.597 CaO2 29.766 (NH4)HCO3 26.708 SiO2 29.062 C2H2O4!2H2
24.231 C2CaO4 24.366 Al1.4Si0.3O2.7 35.743 MgC2 19.823 C2H2CdO4!2H219.364 CH4N2O!C2H2O4 29.756 (NH4)2CO3!H2
19.936 Si1.8Al0.2O1.2N1.8 22.032 SiO2 35.743 Fe2.35Si0.65O4 24.195 C4H16N8O4!Ca(NO3)2 24.366 C6H9AlO6 29.655 C2H8N2O4 
22.980 C11PF6 30.420 MgCO3!2H228.755 CH4N2O!HNO3 19.900 Cd(CN)2 29.756 (NH4)2CO3!H219.924 SiO2 
24.032 H4P2O6!2H214.970 NH4N(NO2)2 29.159 Ca(N3)2 20.305 Cd(NO3)2 26.667 C2H2MgO4!2H221.830 C3H3AlO6!CH2O2 
26.667 NH2NH2!HNO3 27.681 Na7[Al5Si7O24]CO3!3H220.465 Na6C60 23.707 C2CdO4!3H223.334 C12PF5.5 26.997 NH4Cl 
22.319 CH4N222.606 Cd(PO3)2 21.604 SiO2 15.290 Mg5(CO3)4(OH)2!4H222.237 CH4N215.290 (NH4)2Fe2(OH)4(CO3)2!H2
21.341 Ca2Fe(CN)6 26.466 Cd(OH)NO3!H225.502 CaN2O3 29.454 FeSiO3 18.126 C2MgO4!2H223.266 Mg(NH2)2 
21.604 Ca(NO2)2 30.484 CH6N2O2!0.5H229.062 FeSi2 19.364 CH4N2O!C2H2O4 19.999 Mg(NO3)2!6H219.823 C2H2CdO4!2H2
    26.212 CaCO3 27.039 Mg(NO3)2!6H229.454 Al(NO3)3!9H220.639 C20H52N4!88SiO2 
    35.597 Fe1.6SiO4 26.955 Cd3(PO4)2 27.857 Ca(N3)2!0.5H224.098 C4H7AlO5!2.5H2
    26.667 NH2NH2!HNO3 21.604 SiO2 26.831 NH3!H221.841 C2H7NO2 
AAD
 
AADB
 
AADC
 
Native AAD
 
AAD-cd
 
Native AADB
 
AADB-Cd
 
Native AADC
 
AADC-Cd
 
2θ Crystalline species 2θ Crystalline species 2θ Crystalline species 2θ Crystalline species 2θ Crystalline species 2θ Crystalline species 
23.266 Na2Mg(PO3)4 15.060 (NH4)8P6O19!2H215.003 C4H4CuO6!3H226.831 C2H2CaO4 21.238 MgAl2O4!7.9H227.165 CH6N2O2!0.5H2
14.437 CH4N2O!C2H2O4 15.029 Mg5(CO3)4(OH)2!8H217.796 CH6N2O2!0.5H229.756 (NH4)2CO3!H229.395 Na2CO3!10H217.894 Cd(OH)2 
26.243 SiO2 15.588 C4H10CdN4O6 17.408 Fe2O2CO3 29.198 2NH3!H229.454 FeSiO3 17.724 Cd(NO3)2!4H2
25.651 Ca5(SiO4)2CO3 30.063 Cd4P2O9 35.597 CaO2 29.766 (NH4)HCO3 26.708 SiO2 29.062 C2H2O4!2H2
24.231 C2CaO4 24.366 Al1.4Si0.3O2.7 35.743 MgC2 19.823 C2H2CdO4!2H219.364 CH4N2O!C2H2O4 29.756 (NH4)2CO3!H2
19.936 Si1.8Al0.2O1.2N1.8 22.032 SiO2 35.743 Fe2.35Si0.65O4 24.195 C4H16N8O4!Ca(NO3)2 24.366 C6H9AlO6 29.655 C2H8N2O4 
22.980 C11PF6 30.420 MgCO3!2H228.755 CH4N2O!HNO3 19.900 Cd(CN)2 29.756 (NH4)2CO3!H219.924 SiO2 
24.032 H4P2O6!2H214.970 NH4N(NO2)2 29.159 Ca(N3)2 20.305 Cd(NO3)2 26.667 C2H2MgO4!2H221.830 C3H3AlO6!CH2O2 
26.667 NH2NH2!HNO3 27.681 Na7[Al5Si7O24]CO3!3H220.465 Na6C60 23.707 C2CdO4!3H223.334 C12PF5.5 26.997 NH4Cl 
22.319 CH4N222.606 Cd(PO3)2 21.604 SiO2 15.290 Mg5(CO3)4(OH)2!4H222.237 CH4N215.290 (NH4)2Fe2(OH)4(CO3)2!H2
21.341 Ca2Fe(CN)6 26.466 Cd(OH)NO3!H225.502 CaN2O3 29.454 FeSiO3 18.126 C2MgO4!2H223.266 Mg(NH2)2 
21.604 Ca(NO2)2 30.484 CH6N2O2!0.5H229.062 FeSi2 19.364 CH4N2O!C2H2O4 19.999 Mg(NO3)2!6H219.823 C2H2CdO4!2H2
    26.212 CaCO3 27.039 Mg(NO3)2!6H229.454 Al(NO3)3!9H220.639 C20H52N4!88SiO2 
    35.597 Fe1.6SiO4 26.955 Cd3(PO4)2 27.857 Ca(N3)2!0.5H224.098 C4H7AlO5!2.5H2
    26.667 NH2NH2!HNO3 21.604 SiO2 26.831 NH3!H221.841 C2H7NO2 
Figure 6

XRD diffraction peaks of three adsorbents (a were the native adsorbents; b were the adsorbents-Cd).

Figure 6

XRD diffraction peaks of three adsorbents (a were the native adsorbents; b were the adsorbents-Cd).

XPS analyses

The XPS scanning spectra of the three adsorbents after Cd2+ biosorption are shown in Figure 7. C 1s, N 1s and O 1s were the main peaks detected in the biomass spectrum. As shown in Figure 7, for the three adsorbents, the deconvolution of the C 1s spectra yielded peaks with corresponding binding energies of 284.8 eV for C-C and C-H species, 285.6 eV for C-N species, 286.3 eV for -C = N or C-OH species (Zhou et al. 2007). While for AADC, a peak at 287.3 eV which represented -C = O appeared. The deconvolution of the N 1s spectra yielded peaks with corresponding binding energies of 401.58 eV for NH4+ species, and new decomposed peaks with binding energy of 399.1 eV for -CN species and 399.73 eV for -NH species appeared in AAD and AADC (Pels et al. 1995). The increased intensity of -NH in AADC might be the conversion of inorganic ammonia to organic ammonia during composting which was consistent with the results of FTIR. The deconvolution of the O 1s spectra yielded peaks with corresponding binding energies of 531.0 eV for carbonyl oxygen of quinines, 532.6 eV for carbonyl oxygen atoms in esters, anhydrides and oxygen atoms in hydroxyl groups (Lakshminarayanan et al. 2004). Some new decomposed peaks (533.1 eV for -COO- and 534.3ev for -COOH) appeared in AAD and AADC. It could be seen clearly from the picture that the deconvolution spectra of each adsorbent was different in the peak of Cd 3d after Cd(II) adsorption, two peaks were observed on AADC, indicating the existence of two Cd chemical states with different binding energies. The Cd 3d peak of binding energy 405.99 eV could be attributed to the formation of an ester-cadmium complex (Sheng et al. 2004).

Figure 7

XPS spectra of AAD ((a) C 1s (b) N 1s (c) O 1s (d) N 1s), AADB ((e) C 1s (f) N 1s (g) O 1s (h) N 1s), AADC ((i) C 1s (j) N 1s (k) O 1s (l) N 1s).

Figure 7

XPS spectra of AAD ((a) C 1s (b) N 1s (c) O 1s (d) N 1s), AADB ((e) C 1s (f) N 1s (g) O 1s (h) N 1s), AADC ((i) C 1s (j) N 1s (k) O 1s (l) N 1s).

BET surface area, particle size, pH, Zeta potential, CEC and oxygen-containing functional groups

The BET surface area and the particle size are of great importance to the performance of adsorbents, because they determine the physical biosorption capacity of the biosorbents. As shown in Table 8, the surface area of AAD, AADB, AADC was 50.32 m2/g, 58.64 m2/g and 40.32 m2/g, respectively. The increased surface area of AADB might be due to the vanishing of a large amount of volatile components in the dreg and the formation of more pore structure during the pyrolysis process, while the decreased surface area of AADC might be ascribed to the substances produced during composting blocked relatively small pores. As shown in Table 8, the total pore volume of the three adsorbents was in the following order: AADC > AADB > AAD, which illustrated that AADC and AADB had better porosity than AAD, this result was consistent with that observed by electron microscopy.

Table 8

BET characteristics of AADC, AADB and AAD

Adsorbent BET surface area (m2/g) Total pore volume (cm3/g) Average pore diameter (Å) Micropore volume (cm3/g) Middle pore volume (cm3/g) 
AAD 50.32 0.0534 46.98 0.0255 0.0154 
AADB 58.64 0.0612 48.37 0.0392 0.0235 
AADC 40.32 0.0832 50.21 0.0551 0.0286 
Adsorbent BET surface area (m2/g) Total pore volume (cm3/g) Average pore diameter (Å) Micropore volume (cm3/g) Middle pore volume (cm3/g) 
AAD 50.32 0.0534 46.98 0.0255 0.0154 
AADB 58.64 0.0612 48.37 0.0392 0.0235 
AADC 40.32 0.0832 50.21 0.0551 0.0286 

The pH value of the adsorbents was determined by the national standard method. 2.50 g of biochar sample was weighed and placed in a 100 mL conical flask. Deionized water without CO2 was added (boiled by boiling method, that is, the deionized boil to volume reduction), 10% or more, capped with cold water is 50 mL without CO2 pure water, heated, gently boiled for 5 min, filtered, the primary filtrate was discarded, and the remaining liquid was cooled to room temperature, and the pH value was measured by pH meter. As shown in Figure 8, there are a lot of negative charges on the surface of AADC and AADB and the pHPZC of AAD, AADB and AADC were 3.10 mV, 2.19 mV and 2.02 mV, respectively. When the pH was 5, AADC had more negative charges which was beneficial to adsorb mental cations. The low isoelectric point of compost might be due to the existence of a large number of negative charges and quaternary amine functional groups on the surface of the compost. Because Cd(II) is cationic, a negatively charged adsorbent may be more effective in adsorbing it, which also explains that the AADC described above had the best adsorbing effect. The CEC and pH value of three adsorbents are shown in Table 9. It can be seen from Table 9 that the pH values of all three adsorbents were weakly alkaline and in the order of AADC > AADB > AAD. The higher the pH, the more negative the charge on the adsorbents and the higher the biosorption efficiency for cations (Gómez-Brandón et al. 2008). Based on the above experimental results, it could also be deduced that the AADC might have the best biosorption for Cd(II), which had been corroborated by the batch experiments.

Table 9

CEC and pH of three adsorbents

 AAD AADB AADC 
CEC (cmol kg−143 62 73 
pH 7.37 7.83 8.64 
 AAD AADB AADC 
CEC (cmol kg−143 62 73 
pH 7.37 7.83 8.64 
Figure 8

Zeta potential.

Figure 8

Zeta potential.

The adsorbent with more oxygen-containing functional groups on its surface generally has a higher CEC (Liang et al. 2006). Besides the properties of adsorbent itself, the pH value of adsorbent also affects its CEC (Cheng et al. 2014). From Table 9, it can be seen clearly that all three adsorbents showed higher CEC. The CEC of AADB (62 cmol kg−1) and AADC (73 cmol kg−1) were obviously higher than that of AAD (43 cmol kg−1) by 30.6% and 41.1%. High cation exchange capacity leads to good adsorption efficiency of the adsorbent. The CEC of AAD, AADB and AADC in Table 9 could explain that AADB and AADC have better adsorption efficiency than AAD in the previous batch biosorption experiments.

Mix 0.1 g of adsorbent sample 20 mL of solution containing 0.1 mol·L−1 of NaOH, 0.05 mol·L−1 of Na2CO3 and 0.1 mol·L−1 of NaHCO3), after shaking at 25 °C and 160 r/min for 24 h. The mixture was filtered, and supernatant was reacted with 0.1 mol·L−1 HCl solution with bromocresol green-methyl red as indicator. Table 10 lists the amounts of functional groups in three adsorbents determined by Boehm titration method. The content of acidic functional groups in AADC was 2.02 mmol/g, which was 9.41% and 22.77% higher than that of AADB and AAD, respectively, indicating that AADC probably had the largest cation exchange capacity and the strongest hydrophilicity among the three adsorbents. This was also in line with the previous description. It can also be seen from Table 10 that these acidic functional groups were mainly composed of carboxyl groups, phenolic hydroxyl groups and lactone groups. And the number of carboxyl groups and lactone groups were substantially more than that of phenolic hydroxyl groups.

Table 10

Oxygen-containing functional groups of three adsorbents

Adsorbent Acidic functional group (mmol/g) Carboxyl (mmol/g) Phenolic hydroxyl (mmol/g) Lactone group (mmol/g) 
AAD 1.56 0.71 0.32 0.53 
AADB 1.83 0.82 0.37 0.64 
AADC 2.02 0.68 0.55 0.79 
Adsorbent Acidic functional group (mmol/g) Carboxyl (mmol/g) Phenolic hydroxyl (mmol/g) Lactone group (mmol/g) 
AAD 1.56 0.71 0.32 0.53 
AADB 1.83 0.82 0.37 0.64 
AADC 2.02 0.68 0.55 0.79 

CONCLUSIONS

Batch biosorption experiments screened the best biosorption conditions which were adsorbent dosage of 1 g/L, pH at 5.0, biosorption temperature of 25 °C, and biosorption time of 120 min, respectively. The maximum biosorption quantity of the three adsorbents was in the following order: AADC > AADB > AAD. From the previous results, it could be seen that composting and pyrolysis did not affect the isotherm and kinetic experiments. According to the Langmuir model and pseudo-second-order model, the biosorption of Cd(II) onto three adsorbents was mainly a chemical process and occurred on a homogeneous and monolayer surface, and also spontaneously by analyses of thermodynamic. Through the analysis of the biosorption mechanism, it could be concluded that composting and pyrolysis had a huge impact on the structure and composition of the AAD, which had an impact on the biosorption process.

ACKNOWLEDGEMENTS

This work was financially supported by the National Key Research Project of China (Grant number: 2017YFD0801104).

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