Enhanced Adsorption of Cu²⁺ from Aqueous Solution by Sludge Biochar Compounded with Attapulgite-Modified Fe

Abstract

Three types of modified sludge biochar were produced for the adsorption of copper in aqueous solutions via the calcium-based magnetic (CaCO₃, Feⁿ⁺) treatment (CA–BC), nanozero-valent iron (nZVI) treatment (nZVI–BC), and iron (Fe³⁺) treatment (FA–BC) of raw biochar. The results suggested that the adsorption capacity for Cu²⁺ of calcium-based magnetic attapulgite/sludge biochar (CA–BC) prepared from CaCO₃, FeCl₃, and FeSO₄ is 38.01% greater than that of unmodified biochar and 6.41% to 17.5% greater than that of the other biochar. The CA-BC contained a variety of ferrite-containing and hydroxide-functional groups, as well as a more developed pore structure. The existence of H⁺ reduced the adsorption capacity of the biochar for Cu²⁺. A high initial concentration of Cu²⁺ could increase Cu²⁺ adsorption on CA–BC. Combined with theoretical calculations, the adsorption efficiency of CA–BC in different systems was explored. The results revealed that CA–BC achieved a maximum removal rate of 92.644% at a pH of 6 with a reaction time of 157 min and an initial Cu²⁺ concentration of 2.813 mg/L. These results suggest that CA–BC shows great potential for removing Cu²⁺ from aqueous solutions.

1. Introduction

Cu is an important heavy metal element with various applications. As a nutrient element, Cu is often used in animal feed to promote growth [1]. Heavy metals are among the most critical pollutants owing to their toxicity, non-degradability, and bioaccumulation tendency. Even though Cu is an essential micronutrient for life, it can be a severe poisoning source [2]. Cu exacerbates several serious health problems, such as liver cell death, neurological damage, metabolic disorders, and cognitive deficits, due to its non-degradability [3,4]. In recent decades, researchers have proposed many techniques, such as adsorption, oxidation/electrochemical oxidation, chemical precipitation, membrane filtration, reverse osmosis, and coagulation/flocculation, to remove Cu²⁺ from wastewater [5]. Adsorption has unique advantages of high performance and cost effectiveness and hence has emerged as a widely employed method for addressing heavy-metal pollution [6]. Accordingly, numerous adsorbents, such as attapulgite, sludge biochar, and composite materials, have been developed and utilized [7].

Sludge biochar is manufactured in an anoxic environment through thermochemical biomass conversion via carbonization; it is highly porous and hence provides a large surface area for increased adsorption of harmful heavy metals [8,9]. Moreover, sludge biochar can alleviate the problems of nanozero-valent iron (nZVI), which is prone to corrosion and agglomeration [10]. Pan et al. indicated that nanoparticles can be loaded onto BC composites via modification, resulting in the dispersion and stabilization of the nanoparticles, which increase surface active sites, thereby improving the physicochemical properties of this material [11]. Fe-modified biochar has also been found to exhibit an excellent heavy-metal removal capacity in aqueous solutions [12]. Qian et al. indicated that nZVI exhibits great remediation potential in reducing heavy-metal ion concentrations in water [13]. Researchers have attempted to use different materials, such as attapulgite and sludge biochar, to solve the problem of the nZVI particles’ tendency to agglomerate easily [14,15].

Attapulgite is a clay mineral characterized by abundant silicate layers and a unique chained structure and has attracted attention as a promising support material due to its low cost, high yield, and large surface area, facilitating heavy-metal ion adsorption [16]. Natural attapulgite contains numerous impurities; therefore, modifying it to improve its properties is essential. Modified attapulgite used in heavy-metal-contaminated soils can effectively increase crop yields while reducing heavy-metal content in plants. CaCl₂-modified attapulgite exhibits an excellent phosphorus adsorption ability. When the initial phosphorus concentration in a synthesized wastewater sample was 2.0 mg/L, the adsorption capacity of CaCl₂-modified attapulgite increased from 0.074 to 0.891 mg/g, an increase of 12 times [17]. Sohrabi et al. indicated that combining attapulgite with Fe₃O₄ resulted in an increased adsorbent surface area, leading to an increase in the number of adsorption sites [18]. These results indicate that modified attapulgite and modified sludge biochar play a pivotal role in mitigating environmental pollution caused by heavy metal ions.

This study examines the effect of three modified attapulgite/BC composite materials on Cu²⁺ removal. In particular, X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR), and scanning electron microscopy (SEM) were employed to analyze the surface characteristics of the materials. Further, Cu²⁺ removal efficacy was assessed with respect to varying pH values, material types, and initial Cu²⁺ concentrations. Finally, the adsorption efficacies of CA–BC, nZVI–BC, and FA–BC, which serve as functional adsorbents for Cu²⁺ removal, were evaluated. The results suggest that CA–BC demonstrated the highest removal efficiency, reaching approximately 92.644%, with a maximum theoretical adsorption of 3.98 at pH 6, a Cu²⁺ concentration of 2.813 mg/L, and a reaction time of 157 min. The CA–BC has great potential for removing Cu²⁺ from aqueous solutions.

2. Materials and Methods

2.1. Preparation of Sludge Biochar Composites

The solutions of Cu²⁺ with a concentration of 1000 mg/L were prepared by dissolving Cu²⁺ nitrate (Cu(NO₃)₂·3H₂O; purity: ≥99%) in distilled water. Ethanol, FeCl₃ (purity: ≥99%), FeSO₄ (purity: ≥99%), CaCO₃ (purity: ≥99%), Cu(NO₃)₂ (purity: ≥99%), NaOH (purity: ≥99%), HNO₃ (purity: ≥99%), and HCl (purity: ≥99%) were purchased from Damao Chemical Reagent Factory Co., Ltd. (Tianjin, China). Attapulgite was obtained from Banqiao, China. Sludge biochar was acquired from the Qilihe Wastewater Treatment Plant in Lanzhou City, Gansu Province.

In this study, four samples were studied, including sludge biochar (BC), calcium-based magnetic attapulgite/BC (CA–BC), iron-modified attapulgite/BC (FA–BC), and attapulgite-loaded nanozero-valent iron (nZVI)/BC (nZVI–BC).

For BC preparation, dried sludge was placed in a tube furnace under nitrogen atmosphere and slowly pyrolyzed at 350 °C for 2 h at a rate of 10 °C/min.

CA–BC was obtained by pyrolyzing a mixture of attapulgite, CaCO₃, dried sludge, and Feⁿ⁺. Details of the preparation process were presented in previous studies [19,20]. Further, attapulgite powder was added into a mixed solution containing 16.22 g/L of FeCl₃ and 30.40 g/L of FeSO₄. The pH of the solution was adjusted to 11 by adding 160 g/L of NaOH solution. Next, 3 wt% CaCO₃ was added to the suspension [21], which was vacuum-dried at 70 °C. The resulting solids were then mixed with dry sludge at a mass ratio of 3:1 in the liquid phase and co-pyrolyzed for 2 h in a tube furnace at 350 °C.

nZVI–BC was obtained by loading nZVI on attapulgite via liquid-phase synthesis. Attapulgite and FeSO₄·7H₂O were added to beakers containing deoxygenated deionized water at a ratio of 1:2 and stirred for 30 min under nitrogen atmosphere. Further, 7.56 g/L NaBH₄ (purity: ≥98%) solution was dropwise added to the beakers using burettes to induce a reduction reaction. After the reduction process, the supernatant was filtered. After being repeatedly washed four times with absolute ethyl alcohol, the resulting solid was placed in a vacuum-drying oven at 45 °C for 12 h [22]. The solid was mixed with dry sludge at a ratio of 1:2 in the liquid phase and co-pyrolyzed for 2 h in a tube furnace at 350 °C.

FA–BC was prepared by adding attapulgite to 37.83 g/L HCL solution, followed by stirring for 2 h, washing twice with deionized water, and thorough drying. The solid was mixed with BC at a ratio of 1:1, added to the 162.20 g/L FeCl₃ solution, and completely dried in a tube oven at 65 °C.

The surface functional groups of the absorbents, before and after modification, were analyzed via FTIR spectroscopy (Nicolet iS11, Thermo Fisher, Waltham, MA, USA). SEM was utilized to investigate the surface morphology of the prepared samples (JSM-6360, Jeol, Showa, Japan). In addition, chemical composition was analyzed via XRD, (JDX-3532, Jeol, Showa, Japan) [23].

2.2. Batch Sorption Experiments

Cu²⁺ adsorption efficiency was evaluated using four materials (BC, CA–BC, nZVI–BC, and FA–BC), which were introduced into the Cu²⁺ solution with a concentration of 4 mg/L, and pH was adjusted to 2–8 using NaOH or HCl. In particular, 9 mg of each material was weighed in 50 mL centrifuge tubes and mixed with 45 mL of the 4 mg/L Cu²⁺ solution to perform adsorption kinetics studies. Then, the tubes were shaken in a constant-temperature water bath vibrator (180 rpm; 25 ± 1 °C) for 1, 3, 6, 10, 15, 21, 28, 36, 45, 66, 91, 120, 136, 153, 190, 240, 300, 360, 420, and 480 min; thus, adsorption isotherms of the adsorbates were obtained. Further, 45 mL of the Cu²⁺ solution (concentrations of 0.5, 1, 2, 3, and 4 mg/L) was added to the tubes, and they were shaken for 3 h (180 rpm; 25 ± 1 °C).

The Cu²⁺ concentration in the solutions was measured via atomic adsorption spectroscopy (AAS; PEAA700). Each experiment was conducted thrice, ensuring the reproducibility of the findings. The data presented were derived from averaging the results of the three experiments, with error bars signifying the standard deviation determined from the mean.

2.3. Data Analysis

Adsorption efficiency η (%) and adsorption capacity q_e (mg/g) were calculated using Equations (1) and (2), respectively [24].

$$\mathsf{\eta }=\frac{C_0-C_e}{C_0}\times 100\%$$

(1)

$$q_e=\frac{\left(C_0-C_e\right)V}{m}$$

(2)

Here, V (L) denotes the solution volume, C₀ and C_e (mg/L) represent the Cu concentration before and after the reaction, and m (g) indicates the adsorbent mass.

Adsorption kinetics can be controlled via several independent processes conducted in parallel or in series. Pseudo-first-order kinetic models assume that adsorption is controlled by a diffusion step. Pseudo-second-order models are based on the assumption that the adsorption rate is controlled by a chemical adsorption mechanism, including the contribution of electrons and electron transfer between the adsorbate and adsorbent. Different kinetic models can be used to determine solute uptake rates and explore adsorption pathways [25].

In the pseudo-first-order kinetic model, the relation is expressed as follows:

$$\ln \left(q_e-q_t\right)={\mathrm{lnq}}_{\mathrm{e},\mathrm{c}}-{\mathrm{k}}_1\mathrm{t}$$

(3)

The pseudo-second-order kinetic model is expressed as follows:

$$\mathrm{t}/{\mathrm{q}}_{\mathrm{t}}=\frac{1}{{\mathrm{k}}_2{\mathrm{q}}_{\mathrm{e}}^2}+\frac{\mathrm{t}}{{\mathrm{q}}_{\mathrm{e}}}$$

(4)

where q_e (mg/g) signifies the equilibrium adsorption amount, t (min) represents the adsorption time, q_t (mg/g) refers to the amount adsorbed at time t, q_e (mg/g) denotes the calculated equilibrium adsorption amount, and k₁ and k₂ are the proposed primary and secondary adsorption rate constants, respectively.

An adsorption isotherm is a mathematical model that describes the distribution of an adsorbate on a solid surface based on assumptions about the surface homogeneity or heterogeneity and the likelihood of interaction between the surface coverage and adsorbate [26].

Isothermal adsorption experiments were performed at 25 °C.

The Langmuir isothermal adsorption model equation is expressed as follows:

$${\mathrm{q}}_{\mathrm{e}}=\frac{q_e{K}_L{C}_e}{1+{\mathrm{K}}_{\mathrm{L}}{\mathrm{C}}_{\mathrm{e}}}$$

(5)

The Freundlich isothermal adsorption model is expressed as follows:

$$q_e=K_F{C}_e^{1/n}$$

(6)

where q_e and q_m (mg/g) describe the equilibrium and maximum adsorption amount of the adsorbent, respectively; K_L and K_F represent the Langmuir and Freundlich adsorption equilibrium constants, respectively; and 1/n is the nonlinear index [27]. Statistical analyses, predicated on p values, were performed to elucidate significant disparities in the results.

Microsoft Office Excel (2010) was used for data processing. Origin 9.0 (OriginLab, Northampton, MA, USA) was used to analyze the data and create graphs. The experimental data were analyzed using SPSS 20 (SPSS Inc., Chicago, IL, USA). The relationships between the process parameters regarding Cu⁺ adsorption efficiency were analyzed using Design Expert 10 software.

3. Results and Discussion

3.1. Characterization of Modified BC

FTIR analysis of the attapulgite revealed stretching vibrations of surface ligand water and zeolite water molecules, exhibiting peaks corresponding to –OH at 3439 and 3622 cm⁻¹. The characteristic peak of attapulgite, indicating the presence of Si–O–Si and Si–O bonds, was observed at 1025.17 cm⁻¹ [28,29] (Figure 1). Distinctive biochar peaks (–C=C– and –C=O) were observed at 1100 and 1630 cm⁻¹; FTIR analysis of sewage sludge prepared by Wang et al. also showed the presence of -C=C- and -C=O bonds [30]. CA–BC exhibited an additional characteristic peak at 468.58 cm⁻¹ unlike BC, attributable to the telescopic vibration of Fe–O in the high-spin state of Fe₃O₄. This suggests that Fe₃O₄ integration introduced numerous hydroxyl groups onto the material surface; this was accompanied by a slight shift in the vibrational peak of attapulgite, primarily due to Fe–O–Fe vibrations. The FTIR spectrum of nZVI–BC exhibited an –OH vibrational peak at 3613.08 cm⁻¹, indicating the formation of iron oxides during its preparation. The –OH vibrational peak of attapulgite diminished after loading it with nZVI. This is attributable to the acid treatment of attapulgite, which removed adsorbed water, zeolite water, and some crystallization water. The absorption peak of FA–BC at 558 cm⁻¹ indicates Fe–O accumulation in the biochar during pyrolysis, thus confirming that iron oxide precipitation occurred on the biochar’s surface.

The SEM images showed that the morphology of the biochar samples was characterized by rugged terrain with abundant pores and diminutive particles (Figure 2). This result agrees with observations noted during pig manure pyrolysis [31]. After being mixed with attapulgite, CA–BC, nZVI–BC, and FA–BC exhibited clustering of crystal bundles, forming cohered clay particles that generated pore-like structures on the surface [32]. The SEM images of sludge and calcium sulfate co-pyrolysis biochar prepared by Liu et al. also showed the same surface characteristics. Their adsorption of heavy metals is also effective, and the above studies have fully demonstrated that load-modified biochar with different elements has excellent adsorption performance for heavy metals [33]. The SEM image of CA–BC showed that iron oxides coalesced on the attapulgite surface, where single crystals were noticeably dispersed and independently arranged, forming a surface that was loose and porous. This is attributable to acid treatment and the simultaneous removal of impurities, such as dolomite, which weakened bonds between pristine molecules, opened pore channels, minimized the agglomeration of crystal bundles under surfactant action, and caused noticeable alterations in physical and chemical properties [34]. The SEM images of nZVI–BC and FA–BC show fibrous and earthy aggregates. The fine particles on the BC surface, resulting from iron oxide formation during pyrolysis, adhered to said surface, while a significant number of surface defects subsequently evolved into pores. This phenomenon likely stemmed from the pyrolytic decomposition of the organic content of the sludge, thereby enriching the microporous structure of the BC and resulting in a rod crystal structure that merged with the agglomerated structure. This indicated the successful surface adhesion of the modified attapulgite to the modified sludge biochar [35].

XRD analysis revealed that attapulgite primarily comprised dolomite, quartz, feldspar, calcite, sepiolite, mica, and certain accessory minerals (Figure 3). The iron oxide generated from CA–BC pyrolyzed at 150 °C was primarily Fe₂O₃, as evidenced by the characteristic peaks at 2θ = 35.5° and 29.80°, corresponding to Fe₂O₃ and CaCO₃, respectively. This iron oxide peak was more intense than that in the BC, indicating the significant presence of iron oxide. Fe₃O₄ was also detected, indicating the occurrence of oxidation during the preparation of the calcium-based magnetic attapulgite. This observation confirms the successful formation of the material. For nZVI–BC, the characteristic peak at 2θ = 44.71° indicated the efficient attachment of nZVI to BC. Other diffraction peaks at 2θ = 64.2°, 35.59°, and 35.4° corresponded to FeO, Fe₂O₃, and Fe₃O₄, respectively. FA–BC exhibited prominent characteristic peaks of C and SiO₂ at 2θ = 26.3° and of hematite (Fe₂O₃) at 36.1°, 42.3°, 44.8°, 58.2°, and 63.8°, indicating the successful loading of Fe³⁺ onto the material. The magnetic biochar prepared by Wu et al. also showed the presence of FeO, Fe₂O₃, and Fe₃O₄, and this study pointed out that positively charged surface functional groups and iron oxides in magnetic biochar can both serve as sorption sites for ions in a soil solution [36].

3.2. Cu²⁺ Removal

The dependence of the number of negative and positive surface charges on the pH level of an adsorbent material is pronounced. This renders the pH of a solution a crucial factor in controlling the adsorption efficiency of heavy metals. In scenarios where the pH exceeds 8.0, the Cu²⁺ tends to form a large amount of Cu(OH)₂, manifesting as a blue precipitate. Consequently, the main consideration is the adsorption effect under acidic and neutral conditions, for which different pH values were considered herein, i.e., 2, 3, 4, 5, 6, 7, and 8.

The adsorption capacities of the four materials rapidly increased when the pH was below 6 and remained practically unchanged when the pH exceeded 6 (Figure 4). Within the pH range of 2–8, an exponential surge in Cu²⁺ elimination (from 32.43% to 90.28%) was observed when using CA–BC. Similarly, BC, nZVI–BC, and FA–BC exhibited enhanced Cu²⁺ removal capabilities, increasing from 21.33% to 58.49%, 18.63% to 75.68%, and 25.59% to 79.35%, respectively (Figure 5). The removal of CA–BC was 31.79% higher than that of BC and 14.6% and 10.93% higher than that of nZVI-BC and FA-BC, respectively. This phenomenon suggests that at low pH, the presence of functional groups, such as carboxyl groups on the surface of the composite material and the protonation of Fe–O, renders the surface positively charged, impeding binding with Cu²⁺ [37]. As pH increases, the functional groups on the surface composites undergo deprotonation, enabling them to effectively bind to Cu²⁺, thereby enhancing the adsorption performance of the composites. Furthermore, under acidic conditions, excess H⁺ in the solution competes with Cu²⁺ for active sites on the material. The active sites of the adsorbent interact with H⁺ due to a reduction in the Cu²⁺ adsorption capacity of the adsorbents. However, competition for active sites of the material between H⁺ and Cu²⁺ attenuates under high-pH conditions. The binding between the Si(Al)–O– group and H⁺ weakens, enhancing the material’s affinity toward Cu²⁺. The lower adsorption capacity of nZVI–BC compared to CA–BC for Cu²⁺ may be because nZVI–BC does not completely prevent nZVI agglomeration on the surface of the adsorbent. The reason for the lower Cu²⁺ adsorption capacity of FA–BC compared to that of CA–BC may be that excess Fe³⁺ blocks the active sites of the adsorbent, resulting in a lower reduction capacity. These adsorption mechanisms involve the formation of chemical bonds and noncovalent interactions between the functional groups on the surfaces of the adsorbents and Cu²⁺. Thus, CA–BC, nZVI–BC, and FA–BC exhibited optimal adsorption capacity for Cu²⁺ at a pH of 6.

3.3. Sorption Models

The Cu²⁺ removal efficacy of BC, CA–BC, nZVI–BC, and FA–BC rapidly increased within the first 100 min of usage and then reached a saturation point, remaining constant beyond 190 min. This is attributed to the abundant adsorption sites of these materials, which facilitated a swift uptake during adsorption (Figure 5). However, as Cu²⁺ progressively occupied the active sites, the adsorption rate decelerated until equilibrium was attained. The lower adsorption capacity of nZVI–BC and FA–BC compared to CA–BC was attributed to the clogging of adsorbent pores due to iron deposition [38].

The four fitting results for the kinetic model parameters are provided in

Table 1. Parameters of the adsorption kinetic model in Cu²⁺ for CA–BC, nZVI–BC, FA–BC, and BC.

	Pseudo-First-Order Kinetic Model			Pseudo-Second-Order Kinetic Model
	k1	qm1	R2	k2	qm2	R2
CA–BC	0.0254	3.5174	0.9760	0.0082	3.9666	0.9940
nZVI–BC	0.0197	3.8460	0.9260	0.0050	4.5490	0.9790
FA–BC	0.0246	4.7535	0.8975	0.0061	4.7348	0.9875
BC	0.0936	2.4242	0.9523	0.0075	2.4456	0.9625

, where the R² values represent the model fitting coefficients. The R² correlation coefficients of the pseudo-first-order kinetic models for all four materials were lower than those of the pseudo-second-order kinetic models. The experimental values q_e were highly consistent with the theoretical adsorption capacities q_e derived from the pseudo-second-order kinetic models. This indicates that chemisorption is the rate-controlling step of Cu²⁺ adsorption onto the studied materials. Chemisorption is a process wherein adsorbate material molecules are attached to the adsorbent material surface through strong chemical bonds, particularly covalent bonds. This is not controlled by a single external factor but by many combined actions of multiple adsorption mechanisms [39].

The abovementioned fitting outcome was probably due to the abundance of active adsorption sites on the surfaces of the three composite materials. The adsorption process involves multiple mechanisms, including precipitation, electrostatic adsorption, and metal complexation. Because the actual measured values were relatively close to those of both kinetic models, BC, CA–BC, nZVI–BC, and FA–BC might exhibit more adsorption mechanisms for Cu²⁺ adsorption.

The pseudo-second-order kinetic model does not imply that the adsorption process only involves chemisorption. Therefore, the isothermal adsorption model was used to further identify the rate-controlling step [40].

Quantification and evaluation of the isothermal adsorption model related to Cu²⁺ were performed using a pH of 6, with pertinent model parameters determined at 25 °C (

Table 2. Parameters of the isothermal adsorption model in Cu²⁺ for CA–BC, nZVI–BC, FA–BC, and BC.

T/K (298)	Langmuir			Freundlich
	qmax	KL	R2	KF	nf	R2
CA–BC	3.988	0.0355	0.9922	3.907	3.2323	0.9839
nZVI–BC	3.226	0.0660	0.9360	2.408	3.7900	0.9780
FA–BC	3.070	0.0056	0.9892	3.037	3.2300	0.9830
BC	2.823	0.0203	0.9949	0.198	2.890	0.9726

).

The Langmuir model suggests competition and interaction between the adsorbent and active sites on the material surface, leading to changes in the adsorption extent [41] (Figure 6). Notably, the removal efficacy of CA–BC and BC improved during the pre-saturation phase, and the heavy-metal adsorption rate diminished after saturation. As evidenced by the correlation coefficients R² = 0.9922 and 0.9949 (Table 2), this result indicates that Cu²⁺ adsorption by BC and CA–BC was consistent with the Langmuir equation, indicating the competitive interaction between the adsorbent and active sites on the material surface, leading to enhanced stability. The removal rate depends on the square of the number of unoccupied adsorption vacancies on material surfaces. Thus, Cu²⁺ was immobilized on the CA–BC surface through monomolecular layer chemisorption [42].

The model-fitting coefficients for nZVI–BC and FA–BC were R² = 0.9780 and 0.9830, respectively. These values indicate that Cu²⁺ adsorption aligned more closely with the Freundlich model. The data fit implies the presence of multilayered nonhomogeneous surfaces on nZVI–BC, with Cu²⁺ predominantly immobilized through multimolecular layers. Chemisorption plays the key role in immobilizing Cu²⁺ onto the nZVI–BC surface. Regarding FA–BC, Cu²⁺ adsorption exhibited multilayer characteristics, possibly attributable to oxygen-containing functional groups, such as carboxyl (–COO–) and hydroxyl (–OH), on the surface of the modified BC. As per the assumptions of the proposed secondary kinetic model, adsorption rate control was predominantly governed by chemisorption. In the Freundlich isotherm adsorption model, the adsorption intensity constant is denoted as n_f. When n_f ranges between 2 and 10, the adsorption mechanisms of Cu²⁺ on nZVI–BC and FA–BC involve electrostatic attraction, co-precipitation, and complexation actions of surface functional groups and Feⁿ⁺ with Cu²⁺.

Furthermore, among the four analyzed materials, CA–BC emerged as the superior material, showcasing the most rapid adsorption process and optimal adsorption effect, thereby holding significant implications for modulating industrial wastewater treatment conditions.

3.4. Optimal Process Optimization

The slope of the three-dimensional (3D) curve denotes the impact of primary factors on the relevant values; steeper slopes indicate heightened effects [43]. Response surface 3D plots were constructed based on the relationships between the material (A), pH (B), adsorption time (C), and initial Cu²⁺ concentration (D); the removal rate was the response value, which was fitted using multiple regression to acquire a regression equation:

$$\begin{array}{c}{Y}_{\eta }=92.03+2.29\times \mathrm{A}+1.43\times \mathrm{B}+2.01\times \mathrm{C}+1.13\times \mathrm{D}+6.04\times \mathrm{AB}-0.86\times \mathrm{AC}-6.67\times \mathrm{AD}-1.36\times \mathrm{BC}\\ -2.25\times \mathrm{BD}-3.32\times \mathrm{CD}-8.42\times A^2-5.9\times B^2-6.71\times C^2-5.59\times D^2\end{array}$$

Optimization specifically centered on the CA–BC, nZVI–BC, and FA–BC materials, with adsorption times ranging between 100 and 200 min. The pH interval of 5 to 7 yielded the highest adsorption rates, while the initial Cu²⁺ concentration was approximately between 2 and 4 mg/L. The response surface optimization analysis includes all possible extents of these factors and their interactions. For each variable, three levels were established. Based on the acquired experimental data, 3D modeling was subsequently conducted.

A comparison between different parameters revealed that the material type and adsorption time exerted the greatest significant influence on Cu²⁺ removal efficiency. In addition, the interaction between these two factors was notably impactful (Figure 7). The fitted surface suggested that the adsorption efficiency depended on pH and the initial Cu²⁺ concentration. At high pH and a high initial Cu²⁺ concentration, the Cu²⁺ removal efficiency of the materials (CA–BC, nZVI–BC, FA–BC, and BC) was high. The fitting data indicated a significant relationship between pH and the initial Cu²⁺ concentration (p < 0.05). Under neutral pH conditions, material-type variations led to notable fluctuations in the removal rate as the initial ion concentration increased. This indicates a significant relationship between the type of material and the initial ion concentration. Moreover, the magnitude of surface fluctuations as a function of the material type was considerable, indicating that the influence of the material type on the removal rate was more pronounced than that of the initial ion concentration. The p-value between adsorption time and pH was 0.1228, which is greater than 0.05, indicating a nonsignificant relationship between these two factors. However, the p-value for the relationship between the material and the initial ion concentration was lower than 0.0001, indicating a significant relationship between the composite materials and the Cu²⁺ concentration, a result that aligns with previous research findings [44].

The combination of preparation conditions was optimized using Design Expert 10.3 software. The results revealed that CA–BC reached a maximum removal rate of 92.644% at pH 6, with a reaction time of 157 min and an initial Cu²⁺ concentration of 2.813 mg/L. This result had higher accuracy and reproducibility compared to results derived from previous experiments and data.

4. Conclusions

This study investigated the feasibility of sludge biochar composites for Cu²⁺ removal, calcium-based magnetic attapulgite/BC outperformed the other materials. The following conclusions are drawn from a comprehensive analysis of material characterization, the adsorption kinetics model, and the isothermal adsorption model. The loaded material was uniformly distributed on the surface of three types of compound sludge biochar. The Cu²⁺ adsorption mechanism of calcium-based magnetic attapulgite/BC was perceived as a synergy of physical (pore deposition) and chemical (ionic bonding) interactions on the material surface. Attapulgite-loaded nanozero-valent iron (nZVI)/BC could not completely prevent the agglomeration of the nanozero-valent iron particles on the BC surface. Meanwhile, iron-modified attapulgite/BC blocked the active sites of BC, leading to decreased adsorption capacity. Cu²⁺ removal by calcium-based magnetic attapulgite/BC was dependent on pH, and a higher pH was favorable for Cu²⁺ removal. Through a systematic approach, subsequent optimization identified the most favorable preparation conditions for Cu²⁺ adsorption. calcium-based magnetic attapulgite/BC demonstrated the highest removal efficiency, reaching 92.644% with maximum theoretical adsorption of 3.98 at a pH of 6, Cu²⁺ concentration of 2.813 mg/L, and reaction time of 157 min. Considering that attapulgite and sludge BC are cost effective, readily available, and easy to prepare, calcium-based magnetic attapulgite/BC can be an efficient and promising remediation material for Cu²⁺ removal from wastewater.