Abstract

In the present study, copper tailings were treated at different temperatures (50–650 °C) and for various times (0.5–6 hours) and their phosphate adsorption capacity was investigated. The results showed that heating temperature significantly affected adsorption capacity. The highest capacity was observed in treatments at 310–350 °C. Heating time did not influence phosphate adsorption ability of copper tailings. Scanning electron microscopy, Barrett–Joyner–Halenda (BJH), and Fourier transform infrared spectroscopy (FTIR) were employed to characterize untreated copper tailings (raw CT) and copper tailings heated at 340 °C (CT340). The results showed that CT340 had a rougher surface, more and smaller pores, a larger surface area and higher FTIR transmittance than raw CT. These changes in texture might explain the increased phosphate adsorption of thermally modified copper tailings. Mathematical modeling showed that the Langmuir nonlinear model was the best fit to the current data. The maximum adsorption capacities of raw CT and CT340 were predicted as 2.08 mg/g and 14.25 mg/g at 298 K, pH 6.0, respectively.

INTRODUCTION

Water eutrophication facilitates algal growth and causes serious environmental and aesthetic problems (Kilpimaa et al. 2014). Discharge of phosphate from industrial and agricultural practices is one of the major factors causing water eutrophication. Hence, technologies for removing phosphate from water are in urgent demand (Wang et al. 2016a, 2016b).

Recently, numerous technologies have been developed to remove phosphate, such as physicochemical precipitation (Franco et al. 2017; Huang et al. 2017; Park et al. 2017), adsorption (Lv et al. 2013; Ashekuzzaman & Jiang 2014; Ren et al. 2015a, 2015b; Cui et al. 2016; Song et al. 2016; Jung et al. 2017; Koilraj & Sasaki 2017; Yang et al. 2018), ion exchange (Blaney et al. 2007; Zhang et al. 2017; Gan et al. 2018), membrane technology (Van Voorthuizen et al. 2005; Mouiya et al. 2018), and biological treatment (Debashan & Bashan 2004; Sevcenco et al. 2015). Among these methods, adsorption is the most promising because it has merits of low cost, simple operation, and potential regeneration (Jung et al. 2015; Park et al. 2015). Scientists have made many efforts to search for suitable adsorbents. Organic materials from municipal and agro-industrial wastes have been tried for phosphate removal (Bhatnagar & Sillanpää 2010). Inorganic adsorbents, such as steel slag (Barca et al. 2012; Claveau-Mallet et al. 2012; Yu et al. 2015; Wang et al. 2016a, 2016b), fly ash (Xu et al. 2010; Hermassi et al. 2017), red mud (Zhao et al. 2011; Yu et al. 2015; Ye et al. 2016), manganese, iron oxide and copper tailings (Zeng et al. 2004; Kong et al. 2008; Jiang et al. 2008; Zhang et al. 2010; Liu et al. 2012) have also been tested for phosphate removal. Tailings are by-products from mineral processing and generally contain high levels of heavy metals (e.g., Cu2+, Zn2+, Pb2+, Mn2+). Currently, tailings are landfilled directly, which is likely to pollute nearby environments.

Heavy metals can interact with inorganic anionic ligands (such as SO42−, PO43−, and SeO43−) through precipitation, cooperative electrostatics and surface complexation (Awual et al. 2011; Dai et al. 2011; Liu et al. 2011; Zhang et al. 2011a, 2011b; Ren et al. 2015a, 2015b). These interactions not only remove phosphate from solution, but also immobilize heavy metals and reduce their availability to organisms, overall decreasing the harmful effects of both phosphate and heavy metals to environments (Khan & Jones 2009; Mignardi et al. 2012; Li et al. 2016b). In addition, tailings adsorbing phosphate are potential fertilizers, since similar methods have been applied to remove phosphate using fly ash and other wastes, and then developed as fertilizers (Debashan & Bashan 2004; Hermassi et al. 2017).

Cu2+ has a strong affinity with phosphate, and can adsorb phosphate effectively (Song et al. 2016). There have been several trials to evaluate phosphate adsorption capacity by copper tailings. The results showed effective adsorption of phosphate by copper tailings. The maximum adsorption capacity varied from 0.85 mg/g to 4.56 mg/g, depending on the source of materials and conditions (Kong et al. 2008; Zhang et al. 2010). The mixture of phosphate solution and copper tailings not only reduced the bioavailability of Cd, Cu, Pb, and Zn in sediments, but also minimized soil acidification and the potential risk of eutrophication caused by phosphate solution (Mignardi et al. 2012). These results highlight the potential to develop copper tailings as a phosphate adsorbent.

One factor affecting the phosphate adsorption ability of copper tailings was specific surface area (Jiang et al. 2008). Small and porous particles, especially nanostructured materials, showed better adsorption ability (Li et al. 2014). Thus, enlarging the specific surface area of copper tailings was a potential way to increase its phosphate adsorption ability. Treatment with heat cracked the surface and loosened the texture of steel slag, leading to better phosphate adsorption than untreated samples (Yu et al. 2015). To the best of our knowledge, whether thermal modification could improve the phosphate adsorption capacity of copper tailings has not been investigated. In the present study, the effects of heating temperature and heating time on the phosphate adsorption capacity of copper tailings were investigated. Next, the physical characteristics of thermally modified and unmodified copper tailings were compared. These results contribute to the future development of copper tailings as phosphate adsorbent and the understanding of the mechanisms of thermal modification underlying the improvement of phosphate adsorption of copper tailings.

MATERIALS AND METHODS

Materials

Copper tailings used in the present study were obtained from Tongling Copper Mines Plant, Anhui Province, China. All chemicals used were of analytical grade and purchased from Sinopharm Chemical Reagent Corporation. All solutions were prepared with ultrapure water. KH2PO4 was used to prepare the phosphate solution and the pH value was adjusted using NaOH or HCl solution.

Preparation of thermally modified copper tailings

Copper tailings were crushed and sieved using a 100-mesh net. Next, the copper tailings were placed in corundum crucibles and heated in a muffle furnace at 13 different temperatures (50, 100, 150, 200, 250, 300, 350, 400, 450, 500, 550, 600, and 650 °C), and six different heating time (0.5, 1, 2, 3, 4, 5, 6 hours). After naturally cooling to room temperature, the thermally modified copper tailings were stored in a desiccator.

Phosphate adsorption experiments

Copper tailings (1.5 g) were mixed with 100 mL of 50 mg/L phosphate solution in reaction vessels and the pH value was adjusted to 5.38 (equal to the pH of the 50 mg/L phosphate solution). Adsorption experiments were carried out at 25 ± 1 °C in shaker (150 rpm) for 3 hours. Next, samples were immediately filtered through a syringe filter (0.45 μm), and the residual phosphate content in solution was determined using the molybdenum blue spectrophotometric method (Wei & Qi 2009). Absorbance at 700 nm was determined using a UV-Vis spectrophotometer (U-3900, Hitachi). All experiments were repeated three times. The phosphate adsorption capacity of copper tailings qt, (mg/g) at time t and equilibrium qe (mg/g) were calculated using the following equations (Mitrogiannis et al. 2017):  
formula
 
formula
where m (g) is mass of adsorbent, V (L) is volume of phosphate solution. Ci, Ct and Ce (mg/L) represents phosphate concentration in solution at the start, time t, and equilibrium, respectively.

Adsorption isotherm experiments

Two groups of samples were prepared: raw copper tailings (raw CT) and copper tailings heated at 340 °C for 2 hours (CT340). Phosphate solutions with concentrations ranging from 0 to 300 mg/L (for raw CT) and from 0 to 500 mg/L (for CT340) were prepared. Phosphate adsorption isotherms were determined by adding 1.5 g of adsorbent to 300 mL glass vessels and mixing with 100 mL phosphate solution. The pH value of the mixture was adjusted to 6.0 ± 0.1, and the vessels were shaken at 150 rpm for 3 hours at 25 ± 1 °C.

Langmuir and Freundlich isotherms were applied to fit the experimental data. Both linear and nonlinear methods were tested. Mathematical models are listed below.

Langmuir isotherm linear model (Kostura et al. 2005):  
formula
Langmuir isotherm nonlinear model (Sun et al. 2018):  
formula
Freundlich isotherm linear model (Deliyanni et al. 2007):  
formula
Freundlich isotherm nonlinear model (Zhang et al. 2017):  
formula
where Ce (mg/L) is the solution's concentration of sorbent at equilibrium; b, Ka are the Langmuir linear and nonlinear constants, respectively. K and KF are the linear and nonlinear Freundlich constants, respectively, n (Freundlich exponent) is an indicator of intensity change during the adsorption process and also an index of deviation from linearity of adsorption. Q0 and Qm denote the linear and nonlinear Langmuir maximum capacity (mg/g), respectively. Qe is phosphate adsorption capacity at equilibrium (mg/g).

Physical characterization

Scanning electron microscopy (SEM) imaging was conducted using a Hitachi S-4800 scanning microscope (Hitachi, Japan) to examine the surface topography of the adsorbent. Specific surface area was determined using a NOVA 2000e analyzer, and Fourier transform infrared spectra (FTIR) were analyzed by an IRPrestige-21 transform infrared spectrometer (Shimadzu, Japan). The data were analyzed using OriginPro 2017.

RESULTS AND DISCUSSION

Effects of heating temperature on phosphate adsorption capacity of CT

Compared with raw CT, thermal modification significantly affected the phosphate adsorption capacity of CT. As the heating temperature increased from 50 °C to 350 °C, the phosphate adsorption capacity of the CT increased significantly. When the temperature exceeded 350 °C, the phosphate adsorption capacity dropped. At 600 °C and 650 °C, the phosphate adsorption capacity was lower than raw CT (Figure 1). The highest adsorption, 3.32 mg/g, was observed in treatments at 310 °C to 350 °C, significantly higher than at other temperatures. No significant differences in capacity were observed when the temperature ranged from 310 °C to 350 °C, suggesting that 310–350 °C might be the best temperature range for thermal modification of CT.

Figure 1

Effects of heating temperature on phosphate adsorption of copper tailings.

Figure 1

Effects of heating temperature on phosphate adsorption of copper tailings.

With increasing temperature, CT firstly lost surface and interlayer water, secondly lost bound water from its structural framework, and lastly organic impurities were burned. Therefore, heating modification reduced adsorption resistance derived from water, enhanced porosity and enlarged the surface area of CT, which together improved its phosphate adsorption capacity. When the temperature exceeded 600 °C, the structure of adsorbent was destroyed, leading to sintering and stacking, which finally reduced adsorption capacity (Kong et al. 2008).

Effects of heating time on phosphate adsorption of CT

Effects of heating time on the adsorption ability of CT heated to 350 °C are illustrated in Figure 2. No significant differences in adsorption capacity were observed among treatments with heating times ranging from 0.5 to 6 hours. The highest average value of phosphate adsorption capacity, 3.15 mg/g, was observed from treatment for 2 hours.

Figure 2

Effect of heating time on the phosphate adsorption capacity of CT.

Figure 2

Effect of heating time on the phosphate adsorption capacity of CT.

Characterization of CT340 and raw CT

SEM images of CT340 and raw CT were compared. Particles of raw CT were relatively larger than CT340, suggesting thermal modification cracked CT. The surface of raw CT particles was relatively smooth, but that of CT340 was rough (Figure 3). These results suggest that the surface area of CT might be enlarged by thermal modification.

Figure 3

Scanning electronic microscopy images of copper tailings treated at 340 °C (a1 and b1) and raw copper tailings (a2 and b2).

Figure 3

Scanning electronic microscopy images of copper tailings treated at 340 °C (a1 and b1) and raw copper tailings (a2 and b2).

The N2 adsorption-desorption isotherms of raw CT and CT340 and their corresponding Barrett–Joyner–Halenda (BJH) pore size distribution plots are shown in Figure 4. Holes with diameters of less than 2 nm, ranging from 2 nm to 50 nm, and greater than 50 nm are called micropores, mesopores (transition pores) and macropores, respectively (Zhang & Wang 2016). Analyses of pore volume pore size distribution showed that pore the size of CT340 and raw CT was mainly 3 nm (mesopore). Moreover, the ratio of mesopores was relatively higher, and that of macropores was lower in CT340 compared with raw CT (Figure 4), demonstrating that the pore size distribution shifted downwards in response to thermal modification.

Figure 4

Pore size–pore volume distribution of raw CT and CT340.

Figure 4

Pore size–pore volume distribution of raw CT and CT340.

Heating can increase surface area of products (Evita et al. 2013), and enlarged surface area promotes heating rate and reaction time (Schimmelpfenning & Glaser 2012), which further increases the surface area. In the present study, analysis of the surface area showed that the surface area of raw CT and CT340 was 2.994 m2/g and 6.934 m2/g, respectively. Clearly, thermal modification noticeably increased the surface area of CT, which should promote phosphate adsorption capacity (San & Tüzen 2013).

FTIR spectra of CT340 and raw CT are shown in Figure 5. The transmittance patterns of CT340 and raw CT are similar, showing peaks at 3,419 cm−1, 1,640 cm−1, 1,110 cm−1, which represent Si-OH stretching vibration, O-H bending vibration and Si-O-Si bending, respectively. Transmittance between 831 cm−1 and 433 cm−1 was attributed to the superposition of characteristic vibrations of aluminum and magnesium oxides (Cai et al. 2012).

Figure 5

FTIR spectra of raw CT and CT 340.

Figure 5

FTIR spectra of raw CT and CT 340.

The maximum adsorption capacities of CT340 and raw CT

Adsorption isotherms can be used to predict the maximum adsorption capacity of an adsorbent. Several mathematical formulas have been used to fit experimental data and to evaluate isotherm performance, such as Langmuir, Freundlich, Temkin, Redlich–Peterson, and Sips sorption isotherms (Rostamian et al. 2011). Among them, the characteristic feature of the Langmuir isotherm model is monolayer adsorption on a homogeneous surface with a finite number of adsorption sites and without any interaction between adsorbed molecules (Rout et al. 2014). The adsorption process of the Freundlich isotherm model is explained when a heterogeneous adsorbent surface is involved in multilayer distribution of adsorbate with interactions between the adsorbed molecules (Rout et al. 2014). Since Langmuir and Freundlich isotherms are commonly used (Li et al. 2014; Wan et al. 2017; Goscianska et al. 2018) in similar studies, these two isotherms were applied in the present study.

The fitting results, as summarized in Table 1 and Figure 6, elucidated that all four models showed high R2, suggesting these models fitted the present experimental data. These results could be interpreted by the complex mineralogical forms present in CT. Moreover, the Langmuir linear and nonlinear models showed better performance than the Freundlich linear and nonlinear models for both raw CT and CT340, since the former had higher R2. These results indicated that the monolayer adsorption process with intra-molecular interactions might be dominant during phosphate adsorption by CT. Based on the model's prediction, the maximum adsorption capacity of phosphate at 25 °C was 14.25 mg/g for CT340 and 2.08 mg/g for raw CT.

Figure 6

(a) Adsorption isotherms of phosphate adsorption by raw CT (experimental conditions: dosage of raw copper tailings = 1.5 g; initial phosphate concentration = 0–300 mg/L; temperature = 298 ± 1 K; pH 6.0 ± 0.1). (b) Adsorption isotherms of phosphate adsorption by CT340 (experimental conditions: dosage of raw copper tailings = 1.5 g; initial phosphate concentration = 0–500 mg/L; temperature = 298 ± 1 K; pH6.0 ± 0.1).

Figure 6

(a) Adsorption isotherms of phosphate adsorption by raw CT (experimental conditions: dosage of raw copper tailings = 1.5 g; initial phosphate concentration = 0–300 mg/L; temperature = 298 ± 1 K; pH 6.0 ± 0.1). (b) Adsorption isotherms of phosphate adsorption by CT340 (experimental conditions: dosage of raw copper tailings = 1.5 g; initial phosphate concentration = 0–500 mg/L; temperature = 298 ± 1 K; pH6.0 ± 0.1).

Table 1

Parameters of linear and nonlinear models of Langmuir and Freundlich

      Raw CT CT340 
Linear Langmuir Ka 0.427 0.243 
Qm 2.26 14.69 
R2 0.9992 0.9982 
Freundlich KF 0.6266 1.9302 
1/n 0.2803 0.4468 
R2 0.7724 0.7214 
Nonlinear Langmuir Ka 1.57 0.566 
Qm 2.08 14.25 
R2 0.9535 0.9802 
Freundlich KF 0.1870 4.2509 
1/n 0.8825 0.2380 
R2 0.8775 0.8749 
      Raw CT CT340 
Linear Langmuir Ka 0.427 0.243 
Qm 2.26 14.69 
R2 0.9992 0.9982 
Freundlich KF 0.6266 1.9302 
1/n 0.2803 0.4468 
R2 0.7724 0.7214 
Nonlinear Langmuir Ka 1.57 0.566 
Qm 2.08 14.25 
R2 0.9535 0.9802 
Freundlich KF 0.1870 4.2509 
1/n 0.8825 0.2380 
R2 0.8775 0.8749 

Comparison with other adsorbents

The phosphate adsorption capacity of adsorbents in previous literatures is summarized in Table 2. CT340 showed the highest adsorption capability among all listed adsorbents, which suggested that CT340 might have potential as a phosphate adsorbent for removing phosphate from aqueous solutions. However, CT might be harmful to the environment due to high levels of heavy metals. Whether heavy metals could be immobilized by phosphate in real situations and how to avoid environmental contamination with CT should be investigated in future.

Table 2

Comparison of phosphate adsorption capacity (qm) among CT340, raw CT with other reported adsorbents

Adsorbents qm (mg/g) pH Reference 
Thermally modified steel slag 13.62 7.0 Yu et al. (2015)  
Iron oxide tailings 8.21 6.6 Zeng et al. (2004)  
Mg-Al hydrotalcite-loaded kaolin clay 11.92 7.5 Lin & Zhou (2015)  
Acid-modified fly ash 13.3 7.5 Li et al. (2016a)  
Acid-modified palygorskite 10.5 7.5 Li et al. (2016a)  
Kanuma clay 4.39 7.0 Yang et al. (2013)  
Innovative modified bentonites 11.15 7.0 Zamparas et al. (2012)  
Ca(OH)2-modified natural clinoptilolite 7.57 7.0 Mitrogiannis et al. (2017)  
Granular boehmite 8.38 7.0 Ogata et al. (2012)  
Steel byproduct 3.70 7.0 Hua et al. (2016)  
Raw CT 2.08 6.0 This study 
CT340 14.25 6.0 This study 
Adsorbents qm (mg/g) pH Reference 
Thermally modified steel slag 13.62 7.0 Yu et al. (2015)  
Iron oxide tailings 8.21 6.6 Zeng et al. (2004)  
Mg-Al hydrotalcite-loaded kaolin clay 11.92 7.5 Lin & Zhou (2015)  
Acid-modified fly ash 13.3 7.5 Li et al. (2016a)  
Acid-modified palygorskite 10.5 7.5 Li et al. (2016a)  
Kanuma clay 4.39 7.0 Yang et al. (2013)  
Innovative modified bentonites 11.15 7.0 Zamparas et al. (2012)  
Ca(OH)2-modified natural clinoptilolite 7.57 7.0 Mitrogiannis et al. (2017)  
Granular boehmite 8.38 7.0 Ogata et al. (2012)  
Steel byproduct 3.70 7.0 Hua et al. (2016)  
Raw CT 2.08 6.0 This study 
CT340 14.25 6.0 This study 

CONCLUSION

Copper tailings were heated at different temperatures and for different times, and their phosphate adsorption capability was compared. The results showed that heating temperature had a significant effect but heating time did not influence the phosphate adsorption capacity of thermally modified copper tailings. The optimum temperature ranged from 310 to 350 °C. Thermally modified copper tailings showed higher porosity than raw copper tailings, and the BJH surface area was three times higher than that of raw copper tailings. These characteristics might explain the increased phosphate adsorption ability of copper tailings in response to heating.

ACKNOWLEDGEMENTS

This work was supported by the National Nature Science Foundation of China (No. 51409001), the Excellent Talents Supporting Program of Higher Education of Anhui (No. gxyqZD2016127), the College Natural Science Foundation of Major Project of Anhui, China (KJ2018ZD033), the Foundation of Anhui Provincial Key Laboratory of the Conservation and Exploitation of Biological Resources, and the Center of Analysis and Testing, Anhui Polytechnic University for the SEM, Brunauer–Emmett–Teller (BET), and FTIR analyses. We also express our thanks to reviewers, editors, and Dr Gen Zhang.

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