Abstract
A nano spherical CaCO3 (NSC) derived from solid waste (precipitated from tris(α-chloropropyl) phosphate and triethyl phosphate mixed wastewater) was prepared as adsorbent for phosphorus removal from aqueous solution. Response surface methodology (RSM) was used to develop an approach for the evaluation of phosphorus adsorption process, and Box-Behnken design was performed to investigate the effects of various experimental parameters (temperature, contact time, initial pH and dosage of absorbent) on phosphorus adsorption. The model results of experimental data gave a high correlation coefficient (R2 = 0.9658), and a predictive model of quadratic polynomial regression equation and optimum level values were established successfully. It was found that the adsorption efficiency and adsorption capacity reached 97.05% and 123.79 mg/g, respectively, under conditions of temperature of 45 °C, initial pH 5.3, contact time of 11 h, and absorbent amount of 392 mg/L. X-ray diffraction (XRD) analysis testified new phase, Ca10(PO4)6CO3, was produced in the adsorption process. Apart from that, adsorption behavior fitted well with the Langmuir isotherm model and logistic growth model. The thermodynamic study indicated that phosphorus removal by NSC as adsorbent was a spontaneous, endothermic, and mainly chemical adsorption process.
INTRODUCTION
The release of phosphorus from municipal wastewater, industrial discard solution, agricultural areas runoff and landfill leachate often cause water pollution. Excessive phosphate in water body can cause abnormal growth of microorganisms and algae, which will deteriorate the water quality and eventually lead to eutrophication (Yu et al. 2017). Therefore, although phosphorus is a necessary element for biological growth, its concentration in water must be limited to a reasonable value (Choi et al. 2016). Various approaches had been developed for the removal of phosphate from water, including chemical precipitation, adsorption, biological removal, reverse osmosis, membrane and ion exchange, among them, biological removal, chemical precipitation and adsorption are the most common methods. Biological phosphorus removal is a low-cost and environmentally friendly method, but microorganisms are very sensitive to the requirements of water quality, and the change of operating conditions will have a great effect on the adsorption effect (Diamadopoulos et al. 2007). Chemical precipitation is usually used to remove phosphorus by adding metal ions, such as Al3+, Fe2+/Fe3+ and Mg2+, which will consume a lot of coagulants and produce a large amount of unmanageable sludge (Ahmad et al. 2016). The removal of phosphate from water by adsorption has attracted much attention due to its advantages of low cost, simple operation and less sludge output (Ko et al. 2016).
Recently, metallic oxide and hydroxide materials, such as alumina, Fe-Al binary oxide (Tofik et al. 2016), cobalt hydroxide (Zolgharnein et al. 2017) with nanostructures have gained special attention in adsorption due to small particle size, large specific surface area, high in situ reactivity and weak diffusion resistance. Moreover, at a relatively low value of pH, the surface protonation of these kinds of nanoscale adsorbents will be enhanced. Increased protonation would increase the positively charged sites, enlarging the attraction force existing between the sorbent surface and the negatively charged (PO2−4, HPO−4 and H2PO−4) anions, which lead adsorption of phosphate (Tofik et al. 2016; Zolgharnein et al. 2017). In other studies, calcium was used to decorate sludge derived carbon (Kong et al. 2018), clad clinoptilolite (Zhou et al. 2017) and synthesize hydrocalumite (Oladoja et al. 2014) to enhance the adsorption capacity. Because the release of Ca2+ in aqueous solution precipitated phosphate on the surface of the adsorbent and, of course, environmental friendliness of calcium is also the reason to be chosen. The surface of CaCO3 has positively charged sites to attract negative ions in the case of pH < 8 (Somasundaran & Agar 1967) and obviously, CaCO3 has a large proportion of calcium itself. There are some reports of natural calcite for phosphate removal, but the research on the synthesis of nano CaCO3 has not received much attention. An experiment confirmed that removal rate of phosphate (concentration of phosphorus is 50 mg/L) by nano CaCO3 reached 98% at the condition of room temperature, initial pH 12, contact time of 30 min and absorbent amount of 20 g/L, of which the adsorption capacity was 2.45 mg/g (Cheng & Xie 2008). Adsorption isotherms and kinetics were studied in aforementioned phosphorus adsorption studies. Langmuir and Freundlich models are common adsorption isotherms and, in these papers, adsorption processes conformed to Langmuir isotherm (Cheng & Xie 2008; Oladoja et al. 2014; Zolgharnein et al. 2017; Kong et al. 2018), which means that these materials are monolayer adsorption (Liu et al. 2016). In the above papers, the kinetic parameters for the sorption of phosphate onto the different materials were obtained by fitting the time–concentration profile data to the pseudo-first-order and pseudo-second-order kinetic models, and the results showed that the pseudo-second-order gave the best description of the sorption process (Oladoja et al. 2014; Tofik et al. 2016; Zhou et al. 2017; Zolgharnein et al. 2017; Kong et al. 2018). Of course, the adsorption model is not fixed, which depends on the properties of adsorption materials. For example, the process of phosphorus adsorption was also well described by Freundlich isotherm (Tofik et al. 2016) and power function model (Yu et al. 2017).
After catalytic oxidation of tris(α-chlorophyll) phosphate and triethyl phosphate wastewater from a chemical plant, 50 mg/L phosphate-P was found in the water. In order to remove this phosphorus, CaCl2 and Na2CO3 were added to the water, resulting in a large number of calcium containing solid wastes (CSW). In the present study, nano CaCO3 powder was prepared from CSW and its removal conditions were further investigated, which improved adsorption capacity from 2.45 mg P/g CaCO3 to 123.79 mg P/g CaCO3.
METHODS
The preparation of the adsorbent
All chemical reagents are of analytical grade. The CSW (components were listed in Table 1) was washed with deionized water and then oven-dried at 105 °C to constant weight. The CSW was dissolved by 4 M HCl with a dosage of 2.4 mL/g, and the obtained solution was added with 20% Ca(OH)2 suspension until the pH was 10 to precipitate Al3+, Fe3+, Mg2+ and PO3−4. After centrifugal separation of the precipitates, solution pH was adjusted to 6.5 with 1 M HCl to convert excessive Ca(OH)2 to CaCl2. The CaCl2 solution was diluted to 0.3 mol/L and sealed for the next experiment. Nano spherical calcium carbonate (NSC) was synthesized according to the following procedure (Fang & Shen 2002). First, 0.3 g ethylenediaminetetraacetic acid (EDTA) was added into a 250 mL of 0.3 mol/L Na2CO3 solution, under stirring at speed of 800 rpm. 250 mL of 0.3 mol/L CaCl2 solution dropped into the above solution within 5 min and then, 0.3 g Na2HPO4 was added into the mixed solution. The mixture was stirred continuously for 15 min at 10 °C in biochemistry cultivation cabinet (SPX-150SHII, China) and then it was separated by centrifuge (LXJ-IIB, China) and washed with deionized water. After that, the solid was oven-dried at 105 °C. Finally, the NSC was ground and sealed for further experiments.
Components of calcium containing solid wastes (CSW)
Component . | CaO . | Al2O3 . | Fe2O3 . | MgO . | P2O5 . | SiO2 . | H2O . |
---|---|---|---|---|---|---|---|
Content (%) | 11.9 | 1.9 | 1.3 | 2.0 | 2.9 | 5.2 | 61.9 |
Component . | CaO . | Al2O3 . | Fe2O3 . | MgO . | P2O5 . | SiO2 . | H2O . |
---|---|---|---|---|---|---|---|
Content (%) | 11.9 | 1.9 | 1.3 | 2.0 | 2.9 | 5.2 | 61.9 |
Batch adsorption experiments
Analytical method
RESULTS AND DISCUSSION
Characteristics of the adsorbent
The morphology of NSC surface in magnification is indicated in Figure 1(a) and 1(b). It implies that NSC was spherical in shape and the particle size was mainly 40–70 nm. Figure 2(a) is X-ray diffraction pattern of NSC before adsorption. Diffraction peaks were observed at 2Theta = 29.400, 35.968, 39.408, 43.157, 47.505 and 48.503 which were corresponding to 104, 110, 11-3, 202, 018 and 11-6 planes, respectively, marching calcite crystal of CaCO3 (PDF#47-1743). Those diffraction peaks could also be observed after phosphorus removal. Also, new peaks at 2Theta = 25.951, 31.503 and 32.187 shown in Figure 2(b) were corresponding to 002, 330 and −202 planes, respectively, which belonged to lattice planes of Ca10(PO4)6CO3 (PDF#35-0180). The generation of new crystals inferred chemical adsorption in solution. Adsorbed solution was dilute in different concentrations and tested by ICP. None Al3+, Fe3+ and other impurity ions appeared in the solution, which suggested that NSC will not bring harmful impurities to aqueous solution.
SEM, TEM and XRD analysis of NSC: (a) SEM of NSC before adsorption; (b) TEM of NSC before adsorption.
SEM, TEM and XRD analysis of NSC: (a) SEM of NSC before adsorption; (b) TEM of NSC before adsorption.
XRD analysis of NSC: (a) XRD patterns of NSC before adsorption; (b) XRD patterns of NSC after adsorption at initial pH of 5.5.
XRD analysis of NSC: (a) XRD patterns of NSC before adsorption; (b) XRD patterns of NSC after adsorption at initial pH of 5.5.
The RSM design for adsorption studies
The statistical analysis
The solution temperature, contact times, initial pH and adsorbent dosage were chosen as the independent variables based on previous experiments (Choi et al. 2016; Yu et al. 2017; Zhang et al. 2018), while the adsorption rate as the response. Box-Behnken Design was conducted as experiment method. Twenty-five kinds of experimental combinations were designed in the experiment. In order to reduce the error, the center point was repeated five times. Therefore, a total of 29 experimental runs were carried out and the experimental scheme and results are listed in Table 2.
Factors, levels and date of Box-Behnken design
Variables . | Code . | Level of factors . | . | ||
---|---|---|---|---|---|
− 1 . | 0 . | 1 . | |||
Temperature (oC) | X1 | 35 | 40 | 45 | |
Contact time (h) | X2 | 9 | 10 | 11 | |
Initial pH | X3 | 5 | 5.5 | 6 | |
Adsorbent dosage (mg/L) | X4 | 300 | 350 | 400 | |
Run . | Coded levels . | Adsorption rate (%) . | |||
X1 . | X2 . | X3 . | X4 . | ||
1 | 35 | 10 | 5.5 | 400 | 89.33 |
2 | 45 | 9 | 5.5 | 350 | 92.76 |
3 | 40 | 9 | 5.5 | 400 | 93.24 |
4 | 40 | 10 | 5.5 | 350 | 93.33 |
5 | 40 | 10 | 6.0 | 300 | 84.43 |
6 | 40 | 9 | 5.0 | 350 | 90.71 |
7 | 40 | 11 | 5.5 | 300 | 87.46 |
8 | 45 | 10 | 5.5 | 300 | 87.85 |
9 | 45 | 10 | 5.0 | 350 | 91.59 |
10 | 35 | 9 | 5.5 | 350 | 87.74 |
11 | 40 | 10 | 6.0 | 400 | 89.47 |
12 | 40 | 10 | 5.0 | 300 | 85.23 |
13 | 40 | 11 | 5.5 | 400 | 93.78 |
14 | 40 | 11 | 5.0 | 350 | 93.93 |
15 | 35 | 11 | 5.5 | 350 | 90.26 |
16 | 40 | 10 | 5.5 | 350 | 92.13 |
17 | 45 | 10 | 5.5 | 400 | 95.74 |
18 | 45 | 11 | 5.5 | 350 | 95.42 |
19 | 40 | 10 | 5.5 | 350 | 92.57 |
20 | 35 | 10 | 5.5 | 300 | 85.87 |
21 | 35 | 10 | 5.0 | 350 | 89.62 |
22 | 40 | 10 | 5.0 | 400 | 91.31 |
23 | 40 | 10 | 5.5 | 350 | 92.23 |
24 | 35 | 10 | 6.0 | 350 | 86.40 |
25 | 40 | 10 | 5.5 | 350 | 92.63 |
26 | 40 | 9 | 5.5 | 300 | 86.54 |
27 | 40 | 11 | 6.0 | 350 | 89.27 |
28 | 45 | 10 | 6.0 | 350 | 90.25 |
29 | 40 | 9 | 6.0 | 350 | 89.47 |
Variables . | Code . | Level of factors . | . | ||
---|---|---|---|---|---|
− 1 . | 0 . | 1 . | |||
Temperature (oC) | X1 | 35 | 40 | 45 | |
Contact time (h) | X2 | 9 | 10 | 11 | |
Initial pH | X3 | 5 | 5.5 | 6 | |
Adsorbent dosage (mg/L) | X4 | 300 | 350 | 400 | |
Run . | Coded levels . | Adsorption rate (%) . | |||
X1 . | X2 . | X3 . | X4 . | ||
1 | 35 | 10 | 5.5 | 400 | 89.33 |
2 | 45 | 9 | 5.5 | 350 | 92.76 |
3 | 40 | 9 | 5.5 | 400 | 93.24 |
4 | 40 | 10 | 5.5 | 350 | 93.33 |
5 | 40 | 10 | 6.0 | 300 | 84.43 |
6 | 40 | 9 | 5.0 | 350 | 90.71 |
7 | 40 | 11 | 5.5 | 300 | 87.46 |
8 | 45 | 10 | 5.5 | 300 | 87.85 |
9 | 45 | 10 | 5.0 | 350 | 91.59 |
10 | 35 | 9 | 5.5 | 350 | 87.74 |
11 | 40 | 10 | 6.0 | 400 | 89.47 |
12 | 40 | 10 | 5.0 | 300 | 85.23 |
13 | 40 | 11 | 5.5 | 400 | 93.78 |
14 | 40 | 11 | 5.0 | 350 | 93.93 |
15 | 35 | 11 | 5.5 | 350 | 90.26 |
16 | 40 | 10 | 5.5 | 350 | 92.13 |
17 | 45 | 10 | 5.5 | 400 | 95.74 |
18 | 45 | 11 | 5.5 | 350 | 95.42 |
19 | 40 | 10 | 5.5 | 350 | 92.57 |
20 | 35 | 10 | 5.5 | 300 | 85.87 |
21 | 35 | 10 | 5.0 | 350 | 89.62 |
22 | 40 | 10 | 5.0 | 400 | 91.31 |
23 | 40 | 10 | 5.5 | 350 | 92.23 |
24 | 35 | 10 | 6.0 | 350 | 86.40 |
25 | 40 | 10 | 5.5 | 350 | 92.63 |
26 | 40 | 9 | 5.5 | 300 | 86.54 |
27 | 40 | 11 | 6.0 | 350 | 89.27 |
28 | 45 | 10 | 6.0 | 350 | 90.25 |
29 | 40 | 9 | 6.0 | 350 | 89.47 |
The determination coefficient and residuals of analysis of variance (ANOVA) were used as criterions to check the statistical adequacy of the model. According to the analysis software (Design Expert V8.0), the model has high values of the determination coefficient (R2 = 0.9658) and the adjusted determination coefficient (R2adj = 0.9315), which meant that only 3.42% of the total variation is not explained by the regression model and the model parameters were significant (Shojaeimehr et al. 2014). The results of ANOVA were presented in Table 3. The low probability (p < 0.05) with F value (28.22) implied that the model predicted the adsorption rate of phosphorus appropriately. Moreover, the insignificant lack of fit (p = 0.1151 > 0.05) suggested that it is not significantly relative to the pure error and, thus, Equation (4) and the model were accurate for the experiment (Asfaram et al. 2015). The significance of the parameter coefficients, the associated standard error, and the effect of each terms in Equation (4) are also presented in Table 3. According to p values (<0.05 is significant), it can be obtained that all the first-order main effects are highly significant. In the quadratic term, temperature and adsorption dosage (X1X4), contact times and initial pH (X2X3), quadratic temperature (X21), quadratic initial pH (X23) and quadratic adsorption dosage (X24) show high significant effects. Other variables have non-significant effect on phosphorus removal due to high p values.
ANOVA for response surface quadratic model
Source . | Sum of squares . | df . | Mean square . | F-value . | P-value . |
---|---|---|---|---|---|
Model | 250.10 | 14 | 17.86 | 28.22 | <0.0001 |
X1 | 49.57 | 1 | 49.57 | 78.30 | <0.0001 |
X2 | 7.78 | 1 | 7.78 | 12.28 | 0.0035 |
X3 | 14.30 | 1 | 14.30 | 22.59 | 0.0003 |
X4 | 104.96 | 1 | 104.96 | 165.78 | <0.0001 |
X1X2 | 4.90E-03 | 1 | 4.90E-03 | 7.74E-03 | 0.9311 |
X1X3 | 0.88 | 1 | 0.88 | 1.40 | 0.2571 |
X1X4 | 4.91 | 1 | 4.91 | 7.75 | 0.0146 |
X2X3 | 2.92 | 1 | 2.92 | 4.62 | 0.0496 |
X2X4 | 0.04 | 1 | 0.04 | 0.06 | 0.8147 |
X3X4 | 0.27 | 1 | 0.27 | 0.43 | 0.5240 |
X21 | 4.56 | 1 | 4.56 | 7.20 | 0.0178 |
X22 | 0.11 | 1 | 0.11 | 0.17 | 0.6823 |
X23 | 32.31 | 1 | 32.31 | 51.04 | <0.0001 |
X24 | 37.70 | 1 | 37.70 | 59.54 | <0.0001 |
Residual | 8.86 | 14 | 0.63 | ||
Lack of fit | 7.97 | 10 | 0.80 | 3.58 | 0.1151 |
Pure error | 0.89 | 4 | 0.22 | ||
Cor total | 258.96 | 28 |
Source . | Sum of squares . | df . | Mean square . | F-value . | P-value . |
---|---|---|---|---|---|
Model | 250.10 | 14 | 17.86 | 28.22 | <0.0001 |
X1 | 49.57 | 1 | 49.57 | 78.30 | <0.0001 |
X2 | 7.78 | 1 | 7.78 | 12.28 | 0.0035 |
X3 | 14.30 | 1 | 14.30 | 22.59 | 0.0003 |
X4 | 104.96 | 1 | 104.96 | 165.78 | <0.0001 |
X1X2 | 4.90E-03 | 1 | 4.90E-03 | 7.74E-03 | 0.9311 |
X1X3 | 0.88 | 1 | 0.88 | 1.40 | 0.2571 |
X1X4 | 4.91 | 1 | 4.91 | 7.75 | 0.0146 |
X2X3 | 2.92 | 1 | 2.92 | 4.62 | 0.0496 |
X2X4 | 0.04 | 1 | 0.04 | 0.06 | 0.8147 |
X3X4 | 0.27 | 1 | 0.27 | 0.43 | 0.5240 |
X21 | 4.56 | 1 | 4.56 | 7.20 | 0.0178 |
X22 | 0.11 | 1 | 0.11 | 0.17 | 0.6823 |
X23 | 32.31 | 1 | 32.31 | 51.04 | <0.0001 |
X24 | 37.70 | 1 | 37.70 | 59.54 | <0.0001 |
Residual | 8.86 | 14 | 0.63 | ||
Lack of fit | 7.97 | 10 | 0.80 | 3.58 | 0.1151 |
Pure error | 0.89 | 4 | 0.22 | ||
Cor total | 258.96 | 28 |
The optimization of adsorption process
In order to optimize the optimum conditions for phosphorus adsorption, it was necessary to study the effect of each variable on the adsorption efficiency. According to the results of the Box-Behnken Design, the factors with significant interaction effects were selected and the three dimensional response surface plots were drawn for investigation. Figure 3(a) shows the simultaneous effect of temperature and dosage of adsorbent on phosphorus adsorption rate (X1X4) when the other factors were maintained in the constant value. In constant adsorbent dosage, phosphorus adsorption rate increases with temperature increasing. This phenomenon may be due to the promotion of the molecules movement and ion diffusion (Zhang et al. 2018) at high temperature. The dosage of adsorbent extremely influenced the amount of adsorption. At a stable temperature, the adsorption rate enhances with the increase of the dosage of adsorbent which is likely to be the consequence of the greater amount of surface area and available binding sites on the surface of the adsorbent with the addition of NSC (Wang et al. 2014). However, when the dosage of adsorbent continues to be raised, the adsorption rate increases very slowly, and the dosage exceeds 375 mg/L, the adsorption rate remains basically unchanged. In other words, the adsorption capacity is increased first and then reduced. Too many adsorbents brought out unsaturation of the active sites during the adsorption process is one of the principles (Liu et al. 2011). Also, an opposite presumption is that particle aggregation phenomenon can cause the decrease of the total surface active sites (Shojaeimehr et al. 2014).
3D diagrams of significant interactions: (a) the effect of temperature and adsorbent dosage on phosphorus adsorption rate of NSC; (b) the effect of initial pH and contact time on phosphorus adsorption rate of NSC.
3D diagrams of significant interactions: (a) the effect of temperature and adsorbent dosage on phosphorus adsorption rate of NSC; (b) the effect of initial pH and contact time on phosphorus adsorption rate of NSC.
The fitting of isotherm, kinetics and thermodynamics relevant parameters: (a) experimental data and calculated kinetic equation; (b) Langmuir isotherm of phosphorus adsorption at different temperatures; (c) Freundlich isotherm of phosphorus adsorption at different temperatures; (d) ln(Cs/Ce) versus Cs curve on adsorption of phosphorus at different temperatures.
The fitting of isotherm, kinetics and thermodynamics relevant parameters: (a) experimental data and calculated kinetic equation; (b) Langmuir isotherm of phosphorus adsorption at different temperatures; (c) Freundlich isotherm of phosphorus adsorption at different temperatures; (d) ln(Cs/Ce) versus Cs curve on adsorption of phosphorus at different temperatures.
Adsorption kinetics
According to Equations (5)–(8), the following facts can be inferred. The pH value of the solution increased with the increase of the adsorption time, which formed more phosphate precipitates and promoted the ionization of CaCO3 in the previous hours. Thus, increment speed of adsorption rate was getting faster and faster. However, when the alkalinity of the solution was further increased, the ionization of calcium carbonate would be inhibited. Meanwhile, reduction of phosphorus concentration in solution led to the decrease of adsorption driving force. Both reduced the growth rate of adsorption and eventually achieved equilibrium. The final pH was 8.1 and the compound transformed from phosphate to Ca10(PO4)6CO3 shown in Figure 2(b).
Adsorption isotherm
The Langmuir and Freundlich isotherms at different temperatures were fitted in Figure 4(b) and 4(c), respectively. The calculated parameters of the equations for different experimental systems are listed in Table 4. The determination coefficients of Langmuir are higher than those of Freundlich at the temperatures of 303 K, 313 K and 323 K, which indicates that adsorbent may have homogeneous surfaces and monolayer adsorption (Liu et al. 2016). Moreover, when the temperature rises from 303 K to 323 K, the maximum adsorption capacity estimated by isotherm increases from 123.844 mg/g to 137.552 mg/g, thus, heating is beneficial to the increase of adsorption capacity and this phenomenon is consistent with the result of response surface experiment.
The Langmuir, Freundlich and thermodynamic model parameters at different temperatures
Parameter . | Temperature (K) . | ||
---|---|---|---|
303 . | 313 . | 323 . | |
Langmuir | |||
qmax (mg/g) | 124.844 | 128.866 | 137.552 |
Ka (L/mg) | 2.043 | 5.504 | 7.969 |
R2 | 0.981 | 0.950 | 0.994 |
Freundlich | |||
Kb | 75.966 | 101.401 | 114.033 |
n | 3.317 | 3.512 | 3.890 |
R2 | 0.961 | 0.927 | 0.881 |
Thermodynamics | |||
lnK0 | 13.528 | 14.473 | 15.241 |
ΔG°(kJ/mol) | −34.079 | −37.663 | −40.929 |
ΔH°(kJ/mol) | 69.760 | ||
ΔS°(kJ mol−1 K−1) | 0.343 |
Parameter . | Temperature (K) . | ||
---|---|---|---|
303 . | 313 . | 323 . | |
Langmuir | |||
qmax (mg/g) | 124.844 | 128.866 | 137.552 |
Ka (L/mg) | 2.043 | 5.504 | 7.969 |
R2 | 0.981 | 0.950 | 0.994 |
Freundlich | |||
Kb | 75.966 | 101.401 | 114.033 |
n | 3.317 | 3.512 | 3.890 |
R2 | 0.961 | 0.927 | 0.881 |
Thermodynamics | |||
lnK0 | 13.528 | 14.473 | 15.241 |
ΔG°(kJ/mol) | −34.079 | −37.663 | −40.929 |
ΔH°(kJ/mol) | 69.760 | ||
ΔS°(kJ mol−1 K−1) | 0.343 |
Adsorption thermodynamics
According to Equation (18), K0 can be obtained by plotting ln(Cs/Ce) versus Cs and extrapolating to zero Cs (Rawat et al. 1996). The intercept is the value of lnK0. Different temperatures were studied in Figure 4(d) and the results were listed in Table 4. The value of ΔG° is −34.079 kJ/mol, −37.663 kJ/mol and −40.929 kJ/mol at 303 K, 313 K and 323 K, respectively, ranges from −18 to −45 kJ/mol mean the coexistence of physical and chemical spontaneous adsorption. The positive value of ΔH° indicates an endothermic process, and the value of ΔH° is 69.760 > 40 kJ/mol which confirms that the adsorption of phosphorus by NSC is monolayer and mainly chemical adsorption (Emeniru et al. 2015), which corresponds with results of XRD. Meanwhile, with the positive value of ΔS° the randomness at the solid–liquid interface increases after adsorption (Gu et al. 2016). The adsorption capacity of NSC was compared with other sorbents in Table 5, which indicated NSC has a good ability to absorb phosphorus in an aqueous solution.
The comparison of the adsorption capacity between NSC and other kinds of sorbents
Sorbent . | Adsorption capacity to P (mg/g) . |
---|---|
NSC | 123.79 |
Lanthanum-doped ordered mesoporous hollow silica spheres (Huang et al. 2014) | 47.89 |
Fe-Al binary oxide (Tofik et al. 2016) | 16.4 |
Cobalt hydroxide nanoparticles (Zolgharnein et al. 2017) | 49.25 |
Calcium decorated sludge carbon (Kong et al. 2018) | 116.82 |
nano-CaO2-coated clinoptilolite (Zhou et al. 2017) | 50.25 |
Sorbent . | Adsorption capacity to P (mg/g) . |
---|---|
NSC | 123.79 |
Lanthanum-doped ordered mesoporous hollow silica spheres (Huang et al. 2014) | 47.89 |
Fe-Al binary oxide (Tofik et al. 2016) | 16.4 |
Cobalt hydroxide nanoparticles (Zolgharnein et al. 2017) | 49.25 |
Calcium decorated sludge carbon (Kong et al. 2018) | 116.82 |
nano-CaO2-coated clinoptilolite (Zhou et al. 2017) | 50.25 |
CONCLUSIONS
Box-Behnken Design of RSM model (R2 = 0.9658) can accurately describe the adsorption of NSC on phosphorus in aqueous solution. When the phosphorus-P was 50 mg/L, the optimal adsorption rate (R = 97.05%) of RSM prediction were at the condition of temperature of 45 °C, initial pH 5.3, contact time of 11 h and absorbent amount of 392 mg/L. Corresponding adsorption capacity was 123.79 mg/g. Compared with normal calcium carbonate, NSC can achieve adsorption equilibrium faster, but the adsorption capacity is not changed significantly.
Different from the general adsorption kinetics, the curve of adsorption rate with the change of time showed a type of ‘S’ which fitted with a logistic growth model. It is presumed that the adsorption is divided into two steps: the precipitation of CaHPO4 is formed first, and with the increase of pH, the precipitation finally turns to Ca10(PO4)6CO3.
Langmuir isotherm showed better agreement with the adsorption than Freundlich isotherm. The thermodynamic studies proved that phosphorus removal by nano spherical CaCO3 was a spontaneous, endothermic, random and mainly chemical adsorption process.
ACKNOWLEDGEMENT
This work was supported by the National Science Foundation of China (51425802).
CONFLICT OF INTEREST
The authors declare that they have no conflict of interest.