Characterization of the Adsorption of Cu (II) from Aqueous Solutions onto Pyrolytic Sludge-Derived Adsorbents

Abstract

The adsorption of Cu (II) onto two typical types of pyrolytic sludge was investigated in this study. The examined conditions include pH, adsorption time, and temperature, as well as the dosage of adsorbents. Results show that the adsorbents removed the Cu (II) effectively. The adsorbent made from pyrolyzed paper mill sludge (Cu_MS) exhibited exceptional performance, with a removal efficiency of around 100%. Moreover, the adsorption of Cu (II) onto Cu_MS was not affected by pH in the range of 3–9. The kinetic data showed better conformation with the pseudo-second-order kinetic model, and the adsorption processes of the Cu_MS fit well to the Langmuir isotherm model. The adsorption capacity reached 4.90 mg·g⁻¹ under appropriate conditions. Microscopic analysis and FT-IR analysis revealed that the adsorbent with porous structure and high monosilicate content was beneficial to Cu (II) adsorption. Thus, the Cu_MS is a potentially promising candidate for retaining Cu (II) in aqueous environments.

1. Introduction

There is steady concern about the pervasive detection of heavy metals in aquatic environments, as heavy metals are increasingly discharged into the drainage systems by the electroplating, metallurgical, paper manufacturing, and tannery industries. These elements are generally known to exhibit acute toxicity and inflict permanent damage on living organisms even at extremely low concentrations [1,2,3]. Hence, their sufficient removal and reclamation is pressing. Treatment technologies for water remediation, such as physical–chemical precipitation, membrane filtration, ion exchange, nanotechnology, and adsorption, have been well developed to eliminate the pollutants over the years [4]. Among these techniques, adsorption has been extensively used due to its unique properties, such as efficient performance, operational simplicity and economic feasibility [5,6]. In detail, the developed adsorbents have a relatively extraordinary capacity and large surface area, such that they can decrease the heavy metal concentrations to an acceptable level [7,8]. In view of the intended applications, the fabrication of adsorbent materials involves severe technological requirement limitations with respect to cost effectiveness, available precursors, applicable functions, and corrosion resistance. Therefore, the feasibility of this work has to be taken into account [9,10,11]. Sewage sludge, generated as a by-product of the wastewater treatment process, can be converted to an attractive adsorbent [12]. The general adsorption performances of pyrolytic sludge are definitely far from meeting the needs of commercial applications. Pyrolytic sludge usually suffers from slow adsorption or limited adsorption capacity, probably due to the high ash content, which is inevitably produced during the pyrolytic process. However, resource utilization for sewage sludge will be a preferred and attractive application option in coming years [9]. In other words, it is imperative to redefine a sustainable destination for these engineered materials [6,13,14]. As confirmed in the literature, through oxygen-limited pyrolysis and chemical treatment, sewage sludge can be converted into cost-effective and eco-friendly adsorbents [15,16]. Compared to untreated sewage sludge, the leaching efficiency and mobility of heavy metals present in the pyrolytic sludge were dramatically reduced [17]. These innovative and promising adsorbent materials, featuring double benefits of favorable adsorption properties and renewable sources, were used as substitutes for activated carbon. Indeed, their particular properties are superior to those of activated carbon [18].

Herein, the straightforward objective of the present study was to describe the adsorption characteristics of pyrolytic sludge-based adsorbents with respect to Cu (II)-containing aqueous solutions. For comparison, two typical low-cost adsorbents derived from excess domestic sewage sludge (SS) and paper mill sludge (MS) were prepared by pyrolysis technology under laboratory conditions, and their underlying discrepancies in adsorption characterizations were fully revealed. To this end, simulated batch experiments at environmentally relevant concentrations were conducted to symmetrically investigate the effects of variable conditions on their removal efficiency and adsorption performance. Subsequently, the dominant mechanism for the adsorption was elucidated in detail based on the gathered results with high accuracy and reliability. Similar to qualitative indications reported previously, this study documents a favorable strategy bridging the gap between undesired waste utilization and intractable environmental repercussions.

2. Materials and Methods

2.1. Sludge Collection and Preparation

The original types of sewage sludge used in the carbonaceous absorbent preparation were respectively collected from a sewage treatment plant and a paper mill sewage treatment plant located in Guangzhou, South China. Sludge was immediately stored in a refrigerator (4 °C) before use. The sludge was air-dried at room temperature, ground into powder, and then sieved with the desired particle diameter ranging from 0.15 mm to 0.25 mm. The sludge was transported to porcelain crucibles and then pyrolyzed using a muffle furnace at 800 °C for 3 h (heating rate of 10 °C/min) under an inert atmosphere. Afterwards, the pyrolyzed sludge was naturally cooled to room temperature. The obtained samples were abbreviated as Cu_SS and Cu_MS, respectively, for sludge collected from the sewage treatment plant and the paper mill sewage treatment plant. After conversion, samples were repeatedly washed with distilled water to remove chemical residues remaining in the resultant product.

2.2. Batch Adsorption Experiments

The Cu (II) standard stock solutions were freshly prepared using CuCl₂, and the working solutions were obtained by successively diluting the stock solutions with distilled water. Simulated batch absorption experiments were performed in 250 mL Erlenmeyer flasks with stoppers. The pH of Cu (II)-bearing solutions was adjusted by adding 0.1 mol·L⁻¹ HCl or NaOH solutions. A specific amount of the solid adsorbents was initially dispersed into 100 mL of a simulated solution of Cu (II) at defined concentrations. The homogeneous mixtures were then intensively shaken in the reciprocating water-bath oscillator operated at 220 rpm and three controlled temperatures (20, 30, and 40 °C). The suspension solution was collected for analysis at prescribed time intervals. Samples were centrifuged at 4000 rpm for 20 min, and then filtered with 0.45-μm membranes before analysis. The percentage removal efficiency (RE) of the experiments was estimated according to Equation (1). In addition, the amount of Cu (II) adsorbed per unit mass of adsorbent (q_t, mg·g⁻¹) at time t (min) was calculated using Equation (2).

$$\mathrm{RE}(\%)=\frac{C_i-C_t}{C_i}\times 100\%$$

(1)

$$q_t=\frac{\left(C_i-C_t\right)\times V}{M}$$

(2)

where C_i (mg·L⁻¹) and C_t (mg·L⁻¹) are the initial concentration and the residual concentration of Cu (II), respectively; V (L) is the volume of Cu (II) solution; and M (g) represents the mass weight of adsorbents.

2.3. Analytical Methods and Characterization

Concentrations of metals were determined by flame atomic absorption spectrometry (AAS, ZA-3000, Hitachi, Toyota, Japan). The metal-leaching characteristics were obtained according to the Chinese standard method (HJ/T299-2007). The chemical composition was determined by X-ray fluorescence spectroscopy (XRF1800, Shimadzu, Kyoto, Japan). All solution pH values were monitored using a digital pH meter (pH-3C, Leici, Shanghai, China). The surface morphology was examined by scanning electron microscopy (SEM, S-4800, Hitachi, Toyota, Japan). The surface area and porosity were measured using an ASAP 2020 Surface Area and Porosity Analyzer (Micromeritics, Washington, WA, USA). Fourier Transform infrared spectroscopy (FT-IR) was obtained using a Bruker VERTEX 70 Fourier transform infrared spectrometer (Bruker, Billerica, German) with the KBr pressed pellet method.

3. Results and Analysis

3.1. Physical and Chemical Properties and Leaching Toxicity Characteristics of Adsorbents

The chemical compositions were summarized in

Table 1. Chemical composition of the Cu_SS and Cu_MS used in the present study. Cu_SS: the adsorbent made from the sewage sludge; Cu_MS, the adsorbent made from pyrolyzed paper mill sludge.

Chemical Composition	Al2O3	CaO	Fe2O3	K2O	MgO	MnO	Na2O	P2O5	SiO2	TiO2
CuSS (wt %)	18.41	3.59	7.97	3.93	2.72	0.06	0.78	10.42	51.22	0.92
CuMS (wt %)	15.95	50.34	0.84	0.35	2.17	0.03	0.42	0.96	28.41	1.03

. The chemical compositions in Cu_SS were mainly Al₂O₃, P₂O₅ and SiO₂, while the major chemical constituents in Cu_MS were Al₂O₃, CaO, and SiO₂.

The total and leaching concentrations of heavy metals in Cu_SS and Cu_MS are presented in

Table 2. Total and leaching concentrations of heavy metals in Cu_SS and Cu_MS.

Materials		Heavy Metals
		Cr	Ni	Cu	Pb	Mn	Zn
CuSS	total contents (mg kg−1)	49.6	74.0	190	82.4	214	909
	leaching concentration (mg L−1)	8.19	4.10	5.69	ND 1	10.1	1.27
CuMS	total contents (mg kg−1)	19.4	103	175	ND	161	717
	leaching concentration (mg L−1)	1.32	3.30	6.41	ND	7.40	3.89
Threshold values for total contents 2	pH ≥ 6.5 (mg kg−1)	1000	200	500	1000	NA	1000
	pH < 6.5 (mg kg−1)	600	100	250	300	NA	500
Permissible limits for leaching toxicity 3 (mg kg−1)		15.0	5.00	100	5.00	NA	100

¹ Not detected; ² The threshold values of the Chinese control standards for pollutants in sludge from agricultural use (GB4284-84); ³ The permissible limits of the Chinese control standards for identification standard of hazardous wastes-identification of extraction toxicity (GB5085.3-2007).

. In this study, the threshold values in the standards (GB4284-84 and GB5085.3-2007) promulgated by the Chinese Ministry of Ecology and Environment (CMEE) were adopted. The total and leaching metal concentrations were lower than the permissible limits. Accordingly, Cu_SS and Cu_MS could be further applied for the treatment of waste water.

3.2. Effect of pH on Adsorption

The pH of a solution plays an important role in the adsorption process and can radically change the existing speciation of an adsorbate and surface charge of an adsorbent [19]. In the present study, the effect of pH was tested under a temperature of 25 °C, an initial Cu(II) concentration of 25 mg·L⁻¹, a reaction time of 360 min, and dosages of Cu_SS and Cu_MS of 20 g·L⁻¹ and 5 g·L⁻¹ respectively, depending on their adsorption capacity.

According to Figure 1, by increasing the pH_initial from 3 to 7, the RE of Cu_SS sharply increased from 21.56 to 73.60%. When the pH_initial was 8, the RE and q_t reached the maximum values of 77.12% and 0.964 mg·g⁻¹, respectively. Interestingly, when the pH_initial increased from 6 to 7, the RE was drastically increased from 52.84% to 73.60%. It can be concluded that Cu (II) competed with H⁺ for the vacant binding sites in Cu_SS under acidic conditions. In contrast, Cu (II) adsorption of Cu_MS was less affected by pH, and its RE and q_t values were greater than 96.81% and 4.84 mg·g⁻¹, respectively.

As shown in Figure 1, the solution pH_final in mixtures with Cu_SS increased from 5.14 to 8.30. The reason behind this pattern was that the hydrolysis of Cu (II) varied dramatically from weak to strong with the solution pH ranging from acidic to alkaline conditions. Additionally, compared with Cu_SS, Cu_SS had notably stronger buffering ability by releasing reactive OH groups into mixtures, with the adsorption of Cu (II) by Cu_MS.

3.3. Effect of Constant Temperature on Adsorption

The effect of the temperature was also investigated, under conditions of pH = 7, Cu(II) concentration of 25 mg·L⁻¹, and dosages of Cu_SS and Cu_MS of 20 g·L⁻¹ and 5 g·L⁻¹, respectively. According to Figure 2, when the temperature increased from 20 to 40 °C, the RE and adsorption capacity of Cu_SS considerably increased. This implied that the adsorption behavior was an endothermic process in nature, showing an enhanced adsorption capacity at higher temperatures. And the higher of the temperature, the faster the equilibrium of adsorption reached. However, the adsorption process of Cu_MS was not affected by the temperature, especially when the temperature reached 30 °C.

3.4. Effect of Adsorption Dosage on Adsorption

As shown in Figure 3, when the dosages increased from 1 to 20 g·L⁻¹, the RE of Cu_SS almost reached a balance, increasing from 44.82 to 73.60%. The q_t decreased with the ascending dosage of the Cu_SS, and it was affected by the reaction time. The maximum q_t for Cu_SS was 2.02 mg·g⁻¹ when the dosage was 5 g·L⁻¹ after the 480-min adsorption process.

When the dosages of Cu_MS ranged from 1 to 5 g·L⁻¹, the RE of Cu_MS reached a balance, and it reached approximately 100%. Interestingly, the reaction time had little effect on RE and the q_t value. These results indicated that, in comparison with Cu_SS, Cu_MS showed a lower dosage and a higher adsorption capacity.

A pseudo-second-order model is commonly employed for the adsorption mechanism, where the main interaction involved in adsorption was adsorbent-adsorbate affinities in an aqueous solution. In an attempt to discriminate the adsorption behavior, the kinetics data were fitted to a pseudo-second-order model, as empirically expressed mathematically in Equation (3) [3,20,21].

$$\frac{t}{q_t}=\frac{1}{k_2\times q_e^2}+\frac{t}{q_e}=\frac{1}{h_0}+\frac{t}{q_e}$$

(3)

where k₂ is the second-order rate constants for the adsorption process, g·mg⁻¹·min⁻¹; t is the reaction time, min; q_e is the equilibrium adsorption capacity amount of the adsorbent, mg·g⁻¹; and h_o represents the initial adsorption rate, mg·g⁻¹·min⁻¹.

The fitted curves of the pseudo-second-order kinetic model for Cu (II) onto Cu_SS and Cu_MS at different doses and constant temperatures are depicted in Figure 4. Obviously, the model for the modified adsorbents at different doses were well fitted, the R² were higher than 0.99.

The slope (1/q_e) and intercept (h_o, 1/(k₂ × q_e²)), referring to the fitting values of the corresponding parameters, were determined by the linear plots t/q_t against t for the experimental data (

Table 3. Adsorption kinetics parameters for Cu (II) adsorption at different dosages.

	Dosage	Temperature	Pseudo-Second-Order Model	R2	1/qe	qe	1/(k2 × qe2)	k2
CuSS	1 g·L−1	30 °C	y = 0.6267x + 4.2587	0.9964	0.6032	1.6578	2.4939	0.1459
	2.5 g·L−1	30 °C	y = 0.6032x + 2.4939	0.9992	0.6032	1.6578	2.4939	0.1459
	5 g·L−1	30 °C	Y = 0.4787x + 11.448	0.9929	0.4787	2.0890	11.4480	0.0200
	10 g·L−1	30 °C	Y = 0.7584x + 10.749	0.9954	0.7584	1.3186	10.7490	0.0535
	20 g·L−1	30 °C	y = 1.0694x + 14.01	0.9968	1.0694	0.9351	14.0100	0.0816
	30 g·L−1	30 °C	y = 1.6519x + 3.6656	1.0000	1.6519	0.6054	3.6656	0.7444
CuMS	1 g·L−1	30 °C	y = 0.2054x + 0.6007	0.9999	0.2054	4.8685	0.6007	0.0702
	2.5 g·L−1	30 °C	y = 0.1973x + 0.4399	1.0000	0.1973	5.0684	0.4399	0.0885
	5 g·L−1	30 °C	y = 0.2021x + 0.0228	1.0000	0.2021	4.9480	0.0228	1.7914
	10 g·L−1	30 °C	y = 0.4016x + 0.0116	1.0000	0.4016	2.4900	0.0116	13.9037
	20 g·L−1	30 °C	y = 0.7999x + 0.0403	1.0000	0.7999	1.2502	0.0403	15.8769

). The second-order rate constants (k₂) and the initial adsorption rate (h₀) increased with increased adsorbent dosages. At the given experimental conditions, Cu_MS required less time to reach equilibrium than Cu_SS, likely because the q_e for Cu_MS was 2.5 times that for Cu_SS.

The Langmuir and Freundlich isotherm models were used to analyze the adsorption isotherms according to the data from Figure 3. The Langmuir isotherm model is expressed as Equation (4), and its linear form is expressed as Equation (5) [12].

$$q_t=\frac{K_L\times q_{max}\times C_e}{1+K_L\times C_e}$$

(4)

$$\frac{C_e}{q_t}=\frac{1}{K_L\times q_{max}}+\frac{C_e}{q_{max}}$$

(5)

where $K_L$ is the Langmuir adsorption constant related to adsorption energy and the affinity of binding sites; $C_e$ is the equilibrium concentration in the solution, mg L⁻¹; and $q_{max}$ is the maximum adsorption capacity of MS_x, mg g⁻¹.

The Freundlich isotherm model assumes that all adsorption sites in the MS_x are heterogeneous and that the adsorption mechanism is multilayer adsorption. The Freundlich isotherm model is expressed as Equation (6):

$$q_t=K_F\times C_e^{1/n}$$

(6)

where n is the heterogeneity factor and $K_F$ is the Freundlich constant (mg g⁻¹). The linear form of the Freundlich equation is expressed as Equation (7):

$$\ln q_t=\ln K_F+\frac{1}{n}\ln C_e$$

(7)

The n is related to the adsorption intensity or surface heterogeneity. A lower value of n indicates a lesser heterogeneity. All of the thermodynamic parameters for the Langmuir model and Freundlich model are shown in

Table 4. Thermodynamic parameters for the Langmuir and Freundlich models.

Adsorbents	Langmuir Model			Freundlich Model
	R2	qmax	KL	R2	n	KF
CuSS	0.4796	3.179	0.052	0.6750	1.479	0.23
CuMS	0.9994	4.901	111.93	0.6749	5.963	3.48

. The adsorption of Cu_MS fitted well with the Langmuir isotherm model. The correlation coefficient values (R²) for the Langmuir model were greater than 0.99. However, the adsorption of Cu_SS fitted badly both with the Langmuir isotherm model and the Freundlich model. The maximum adsorption capacity (q_max) of Cu_MS was 4.90 mg g⁻¹, and K_L for Cu_MS was 111.93 L g⁻¹, indicating that the Cu_MS had a strong adsorption capacity.

4. Discussion

As the adsorption tests and the analysis show, the pseudo-second-order kinetic model for Cu (II) onto the two adsorbents at different doses and temperatures were well fitted, the R² were higher than 0.99. However, Cu_MS required less time to reach equilibrium compared to Cu_SS, and the q_e for Cu_MS was about 2.5 times that for Cu_SS. Furthermore, the adsorption of Cu_MS was fitted well by the Langmuir isotherm model. The maximum adsorption capacity (q_max) of Cu_MS was 4.90 mg g⁻¹. The value was competitive with some similar low-cost adsorbents, including sawdust [22], coal [23], and also modified waste [24], their adsorption capacity was between 1.62 and 2.10 mg g⁻¹.

The micro-structural properties of Cu_SS and Cu_MS are illustrated in Figure 5. Both Cu_SS and Cu_MS exhibited irregular particles. More specifically, Cu_SS bears clearly large irregular agglomerates (Figure 5), whereas Cu_MS showed porous surface features, which could be beneficial for increasing its specific surface area and providing available active adsorption sites.

With the characterization of surface area and porosity, it can be found that the BET-specific surface area of Cu_MS reached 386.22 m²·g⁻¹, which was approximately 2 times greater than that of Cu_SS (115.31 m²·g⁻¹). Furthermore, the micro-pore volume of Cu_MS reached 0.6893 cm³·g⁻¹, which was approximately 2 times higher than that of Cu_SS (0.2653 cm³·g⁻¹).

Additionally, compared with Cu_SS, Cu_MS had notably stronger buffering ability. With the chemical compositions analysis, we found that the major chemical constituents in Cu_SS were Al₂O₃, P₂O₅, and SiO₂, while the major chemical constituents in Cu_MS were Al₂O₃, CaO, and SiO₂. Thus, the mechanism for the adsorbents must be different.

FT-IR analysis of adsorbents after Cu(II) adsorption was conducted (Figure 6). The broad absorption band at 3423 cm⁻¹ present in Cu_SS is ascribed to the −OH stretching vibrations [25]. The absorption band at 1051 cm⁻¹ is ascribed to the stretching vibration of O-H. It can be deduced that the adsorption of Cu(II) on Cu_SS occurred and the H-bond and electrostatic interactions played an important role.

The absorption bands at 1090 and 1500 cm⁻¹ are related to the Si−O−Si stretching vibrations, while the absorption band at 468 cm⁻¹ is related to the Si−O bending vibrations [25], which is related to the disordering of SiO₄ [26], that is, a monosilicate is produced. The disordering of silicate in Cu_MS causes the overlap of the different absorption bands, which broaden the absorption band. Furthermore, the adsorption of the Cu would promote by the monosilicate [27].

5. Conclusions

Two types of pyrolytic sludge were studied for Cu(II) removal in this paper. Cu(II) adsorption by Cu_MS was not affected in the pH range of 3–9, whereas the pH values were narrow for Cu_SS adsorption of Cu(II). The adsorption residence time exerted insignificant impacts on the adsorption of Cu_MS, which was closely related to the dosage added. The maximum adsorption capacity of Cu_MS reached 4.90 mg/g. Moreover, the adsorption of the Cu_MS fitted well with the Langmuir isotherm model, and the pseudo-second-order kinetic model for Cu(II) onto the two adsorbents at different doses was also well fitted. Combining the surface area and porosity analysis and the FT-IR analysis, the higher adsorption capacity and the wider range of pH adaptation were due to its porous structure and higher monosilicate contents.