Equilibrium Biosorption of Zn²⁺ and Ni²⁺ Ions from Monometallic and Bimetallic Solutions by Crab Shell Biomass

Abstract

This work explored the technical feasibility of using crab shell (CS) as a promising, low-cost biosorbent to individually and simultaneously remove Zn²⁺ and Ni²⁺ from aqueous solutions. It was found that in both monometallic and bimetallic systems, Zn²⁺ and Ni²⁺ biosorption by CS was strongly dependent on the solution pH, with the optimum biosorption occurring at a pH of 6.0 for both heavy metals. The obtained isotherms for Zn²⁺ and Ni²⁺ biosorption onto CS in monometallic and bimetallic systems demonstrated that CS has a higher affinity for Zn²⁺ than for Ni²⁺. The experimental equilibrium data for the bimetallic system revealed that when one heavy metal is present in the system, there is a decrease in the equilibrium biosorption capacity for the other heavy metal; therefore, the combined action of Zn²⁺ and Ni²⁺ was antagonistic. The Sips and Redlich–Peterson isotherm models best fitted the equilibrium biosorption data for Zn²⁺ and Ni²⁺ in the monometallic systems, while the modified Sips model best fitted the binary biosorption equilibrium data. DRIFTS analyses indicated that carbonate ion, chitin, and proteins are mainly involved in the biosorption of Zn²⁺ and Ni²⁺ by CS from aqueous solutions, as confirmed using a range of analytical techniques.

1. Introduction

Divalent zinc (Zn²⁺) and nickel (Ni²⁺) are essential trace elements for many living organisms, and they play crucial roles in several biological metabolic processes; however, these heavy metals are also toxic at high levels [1]. Both Zn²⁺ and Ni²⁺ ions are commonly found in effluents discharged by anthropogenic activities and industry, including those based on mineral processing, the use of non-ferrous metals, galvanization, paint formulation, battery manufacture, and porcelain enameling, among others [2,3]. Due to the high Zn²⁺ and Ni²⁺ concentrations present in these effluents, they can impart deleterious effects on the environment and on living organisms [3,4,5]. More specifically, Ni²⁺ can produce a wide variety of acute and chronic health effects in humans, such as lung and kidney damage, skin dermatitis, nausea, vomiting, diarrhea, dizziness, cyanosis, rapid respiration, chest pain, and extreme weakness [6,7]. In addition, Ni²⁺ is an embryotoxic, teratogenic [6], carcinogenic, and nephrotoxic agent [8]. Although Zn²⁺ is comparatively less toxic than several other heavy metal ions, prolonged exposure to high Zn²⁺ concentrations can cause abdominal pain, nausea, vomiting, fatigue, lethargy, anemia, dizziness, focal neuronal deficits, diarrhea, and prostate cancer [9,10]. It has also been reported that binary mixtures of Zn²⁺ and Ni²⁺ ions can exhibit synergistic or additive adverse effects on biochemical and physiological processes in living organisms, and their toxic effects are therefore higher than anticipated based on the effect of single metal ions in a mixture [1]. Due to such toxic effects, the World Health Organization (WHO) has established allowable limits of 0.07 and 3 mg/L for Ni²⁺ and Zn²⁺ ions in drinking water, respectively [11,12].

To safeguard human health, as well as the terrestrial and aquatic environments and the living organisms that live in them, the removal of Zn²⁺ and Ni²⁺ ions from domestic and industrial wastewaters is of particular importance. For this purpose, several physico-chemical treatment methods are available for the removal of these ions from industrial wastewaters, including chemical coagulation–flocculation, chemical precipitation, ion exchange, ultrafiltration, reverse osmosis, and electrochemical methods [13]. However, these methods tend to suffer from a number of disadvantages, including high costs, complexity, and/or the generation of hazardous wastes [14]. In contrast, the biosorption approach appears to be a more attractive and viable treatment technology for removing heavy metals from industrial wastewaters because of its ease of operation, simplicity of design, adaptability, flexibility, effectiveness, efficacy, efficiency, biosorbent regeneration, eco-friendliness, and insensitivity to toxic pollutants [15,16]. Thus, a vast array of biomaterials have been studied in terms of their abilities to remove heavy metals from single metal aqueous solutions, with examples including nonliving filamentous fungi, bacteria, yeasts, microalgae, and seaweed, in addition to agro-industrial, fishery, and forestry biowastes [17]. In contrast, few studies have been published regarding the simultaneous biosorption of several heavy metal ions from multi-metal solutions, even though it is well known that some industrial wastewaters contain various heavy metals at high concentrations [18]. This is of particular importance, since the presence of more than one heavy metal in industrial wastewater may hamper the biosorption process due to the fact that the different heavy metals may interact both with each other in solution and may also compete for the biosorption binding sites present on the biosorbent surface [19,20]. Thus, to understand the behaviors of multicomponent biosorption systems and to design reliable processes and equipment for the biosorptive removal of heavy metals from industrial wastewater, it is essential to understand the equilibrium isotherms of multicomponent systems [19,21].

In the above context, crab shell (CS) is an abundant biowaste that originates from the seafood industry, and its disposal in large quantities remains a significant issue. The ability to recycle this biowaste into useful resources is therefore of particular interest to find potential alternative uses for the discarded CS. For example, CS has the potential to be used as a viable, readily available, and economically-feasible biosorbent due to its ability to remove heavy metals and other types of inorganic and organic contaminants from wastewater systems [22]. More specifically, CS has been found to exhibit a remarkable ability to biosorb heavy metal ions from single and multicomponent aqueous solutions, such as those containing Pb²⁺, Cd²⁺, Cr³⁺ [23], Ni²⁺ [24], V⁵⁺, Cr⁶⁺ [25], Cu²⁺ [26], Zn²⁺, and Mn²⁺ [27]. These efficient biosorbent properties of CS can be attributed to its mechanical resistance and its rigid structure [27], in addition to the fact that it possesses a wide variety of functional groups on its surface that are capable of biosorbing different heavy metals [22,28].

Thus, we herein report our investigation into the potential of CS to biosorb Zn²⁺ and Ni²⁺ ions from monometallic and bimetallic aqueous solutions. Furthermore, several isotherm models were studied in a comparative manner to evaluate their suitability for describing the CS biosorption behavior in both types of solution. Additionally, diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS), X-ray fluorescence spectroscopy (XRF), scanning electron microscopy coupled with energy dispersive X-ray spectroscopy (SEM-EDX), and confocal laser scanning microscopy (CLSM) studies were performed to confirm the biosorption of Zn²⁺ and Ni²⁺ ions onto CS.

2. Materials and Methods

2.1. The Biosorbent

Samples of Callinectes sapidus crab, commonly known as blue crab, were acquired at a local market in Mexico City, Mexico. To separate the crab shells from the crabmeat, the crab samples were boiled at 92 °C for 15 min, washed exhaustively with deionized water, and subsequently dried at 65 °C until reaching a constant mass. The dried samples were then milled, and the resulting particles were sifted through standard sieves to harvest the particle fraction with sizes ranging from 0.3 to 0.5 mm, which was used in the subsequent biosorption experiments.

2.2. Preparation of the Zn²⁺ and Ni²⁺ Aqueous Solutions

Stock solutions of 40 mM Zn²⁺ and 40 mM Ni²⁺ ions were prepared by weighing the appropriate quantity of ZnSO₄·7H₂O (>99.9%, JT Baker, Monterrey, Mexico) or NiSO₄·6H₂O (>99.1%, JT Baker, Monterrey, Mexico) and making up the volume to 1 L using deionized water. The stock Zn²⁺ and Ni²⁺ solutions were then appropriately diluted with deionized water to produce test solutions of the desired concentrations, which were used in the individual and simultaneous Zn²⁺ and Ni²⁺ biosorption experiments.

2.3. Biosorbent Characterization

We have characterized CS in terms of average specific surface area, total pore volume, and average pore diameter. These characteristics were determined from nitrogen adsorption–desorption isotherms at 77.35 K using a Quantachrome NovaWin gas sorption analyzer (Quantachrome Instruments, Boynton Beach, FL, USA). The CS particles were degassed with nitrogen at 373 K. Then, we determined the specific surface area of the CS using the Brunauer, Emmett, and Teller (BET) multipoint method, and the total pore volume and pore diameter by applying the Barrett, Joyner, and Halenda (BJH) method [16].

2.4. Single and Binary Metal Biosorption Studies

Previous kinetic studies performed using metal solutions of different pH values, with different initial Zn²⁺ and Ni²⁺ concentrations, and using CS as a biosorbent, showed that the biosorption times to reach equilibrium were less than 24 h [29]. Therefore, a CS/solution contact time of 24 h was employed for the equilibrium biosorption studies using the single or binary metal ion solutions. These studies were conducted using a 50 mL volume of the desired metal solution and a 1 g/L concentration of CS in a 250 mL Erlenmeyer flask under 180 rpm constant agitation at 25 °C. The pH values of the metal solutions were calibrated to the desired values using 0.1 M NaOH or HCl solutions.

To assess the effect of the solution pH on the individual biosorption of Zn²⁺ and Ni²⁺ by CS, solutions with initial metal concentrations of 2 mM and pH values ranging from 1.0 to 6.0 were used. The same pH range was also employed for the binary metal biosorption experiments, using equimolar initial concentrations of Zn²⁺ and Ni²⁺ (i.e., 2 mM). It should be noted that pH values > 6.0 were not examined to prevent Zn(OH)₂ and Ni(OH)₂ precipitation.

To examine the effects of the initial Zn²⁺ and Ni²⁺ concentrations on the equilibrium biosorption process for the two monometallic systems, the initial concentrations of the metal ions were varied within the range of 0.2–40 mM. For the binary metal system, an array of assays was performed by maintaining the initial concentration of one heavy metal constant within the 0.2–40 mM range, while varying the initial concentration of the other heavy metal within the same range.

Upon completion of the single and binary biosorption experiments, the Erlenmeyer flasks were removed from the water bath shaker, and the biosorbent and metal solution were separated by filtration through Whatman No. 42 filter paper. The residual Zn²⁺ and/or Ni²⁺ concentrations of the filtrates were measured according to the Zincon Method 8009 and the Dimethylglyoxime Method 10220, respectively, following the instructions outlined in the Hach Water Analysis Handbook [30].

Additionally, CS-free controls were also assayed at identical experimental conditions as those used for the Zn²⁺ and/or Ni²⁺ biosorption trials to ascertain the degree of Zn²⁺ and/or Ni²⁺ ion loss by adsorption onto the glass and/or by means of precipitation. It should be noted that no significant differences were detected in the Zn²⁺ and/or Ni²⁺ concentrations for the CS-free control experiments, thereby indicating that the removal of these metal ions could be attributed to the action of the CS biosorbent.

The biosorption capacities of the Zn²⁺ and Ni²⁺ ions at equilibrium (q_e, mmol/g) were estimated according to Equation (1):

$$q_e=\frac{C_i-C_e}{C_b}$$

(1)

where C_e and C_i are the equilibrium and initial concentrations of Zn²⁺ or Ni²⁺ in the aqueous solution (mmol/L), respectively, and C_b is the CS concentration (g/L).

2.5. Biosorption Equilibrium Modeling of Zn²⁺ and/or Ni²⁺ Ions onto CS

To gain a suitable understanding of the monometallic and bimetallic biosorption systems, the derivation of an accurate mathematical representation of the equilibrium biosorption isotherm is of paramount importance. More specifically, modeling of the equilibrium biosorption isotherm is necessary to derive design parameters that can be used for optimization and scaleup purposes, as well as to allow comparisons between the biosorption performances of different biosorption systems [31]. Additionally, these isotherm model parameters frequently provide valuable information regarding the interactions between the adsorbate and the biosorbent, the affinity of the biosorbent toward the adsorbate, and the surface characteristics of the biosorbent [32]. It is therefore crucial to identify the most suitable mathematical models to describe the equilibrium isotherms for the single and binary biosorption of Zn²⁺ and Ni²⁺ ions onto CS.

The equilibrium data for single Zn²⁺ and Ni²⁺ biosorption systems were analyzed using the Langmuir, Freundlich, Sips, and Redlich–Peterson isotherm models (

Table 1. Biosorption isotherm models for the single heavy metal systems.

Model	Equation	Nomenclature		Reference
Langmuir	$q_e=\frac{q_m{b}_L{C}_e}{1+b_L{C}_e}$	qe qm Ce bL	Equilibrium biosorption capacity (mmol/g) Maximum biosorption capacity (mmol/g) Equilibrium heavy metal concentration in the aqueous phase (mM) Langmuir constant (L/mmol)	[33]
Freundlich	$q_e=k_F{C}_F{}^{\frac{1}{n_F}}$	1/nF kF	Relative indicator of the biosorption intensity Indicator of the capacity of biosorption (mmol/g) (mmol/L)−1/nF	[33]
Redlich–Peterson	$q_e=\frac{k_{RP}{C}_e}{1+(a_{RP}{C}_e{}^{b_{RP}})}$	kRP aRP bRP	Model parameter (L/g) Model parameter (mmol/L)−BRP Model parameter	[17]
Sips	$q_e=\frac{q_m{b}_S{C}_e{}^{n_S}}{1+(b_S{C}_e{}^{n_S})}$	qm bs ns	Maximum biosorption capacity (mmol/g) Model parameter (mmol/L)−nS Sips parameter	[34]

), which have been extensively used to examine equilibrium data for wastewater treatment applications [17,33,34].

Likewise, the nonmodified competitive Langmuir, uncompetitive Langmuir, partial competitive Langmuir, extended Freundlich, modified Sips, and modified Redlich–Peterson isotherm models were used in this work to fit the experimental data obtained for the simultaneous biosorption of Zn²⁺ and Ni²⁺ from bimetallic systems (

Table 2. Isotherm models used in this work for the binary biosorption of Zn²⁺ and Ni²⁺ by CS.

Model	Equation	Nomenclature	Reference
Non-modified competitive Langmuir	$q_{eZn}=\frac{q_{mZn}\prime b_{LZn}\prime C_{eZn}}{1+b_{LNi}\prime C_{eNi}+b_{LZn}\prime C_{eZn}}$ $q_{eNi}=\frac{q_{mNi}\prime b_{LNi}\prime C_{eNi}}{1+b_{LNi}\prime C_{eNi}+b_{LZn}\prime C_{eZn}}$	qmZn’, qmNi’: Maximum Zn2+ and Ni2+ biosorption capacity (mmol/g). bLZn′, bLNi′: Langmuir constants for Zn2+ and Ni2+ biosorption (L/mmol) CeZn, CeNi: Equilibrium Zn2+ and Ni2+ concentrations (mM).	[35]
Uncompetitive Langmuir	$q_{eZn}=\frac{q_{mZn}{}^{\ast }(b_{LZn}{}^{\ast }{C}_{eZn}+b^{\ast } C_{eZn}{C}_{eNi})}{1+b_{LNi}{}^{\ast }{C}_{eNi}+b_{LZn}{}^{\ast }{C}_{eZn}+b^{\ast } C_{eZn}{C}_{eNi}}$ $q_{eNi}=\frac{q_{mNi}{}^{\ast }\left(b_{LNi}{}^{\ast } C_{eNi}+b^{\ast } C_{eZn}{C}_{eNi}\right)}{1+b_{LNi}{}^{\ast }{C}_{eNi}+b_{LZn}{}^{\ast }{C}_{eZn}+b^{\ast } C_{eZn}{C}_{eNi} }$	qmZn*, qmNi*: Maximum Zn2+ and Ni2+ biosorption capacity (mmol/g). bLZn*, bLNi*: Langmuir constants for Zn2+ and Ni2+ biosorption (L/mmol). b*: Langmuir parameter predicted by the uncompetitive model. CeZn, CeNi: Equilibrium Zn2+ and Ni2+ concentrations (mM).	[36]
Partial competitive Langmuir	$q_{eZn}=\frac{q_{mZn}\prime \prime C_{eZn}\left(b_{LZn}″+b_{LNi}″b_{NiZn}{C}_{eNi}\right)}{1+b_{LZn}\prime \prime C_{eZn}+b_{LNi}\prime \prime C_{eNi}+\left(b_{LZn}″b_{ZnNi}{C}_{eZn}{C}_{eNi}+b_{LNi}″b_{NiZn}{C}_{eZn}{C}_{eNi}\right)}$ $q_{eNi}=\frac{q_{mNi}\prime \prime C_{eNi}\left(b_{LNi}″+b_{LZn}″b_{ZnNi}{C}_{eZn}\right)}{1+b_{LZn}\prime \prime C_{eZn}+b_{LNi}\prime \prime C_{eNi}+\left(b_{LZn}″b_{ZnNi}{C}_{eZn}{C}_{eNi}+b_{LNi}″b_{NiZn}{C}_{eZn}{C}_{eNi}\right)}$	qmZn’’, qmNi’’: Maximum Zn2+ and Ni2+ biosorption capacity (mmol/g). bLZn’’, bLNi’’: Langmuir constants for Zn2+ and Ni2+ biosorption (L/mmol). bNiZn, bZnNi: Affinity constant for Ni2+ with the binding site already occupied by Zn2+, and affinity constant for Zn2+ with the binding site already occupied by Ni2+, respectively.	[36]
Extended Freundlich	$q_{eZn}=\frac{k_{FZn}{C}_{eZn}{}^{\frac{1}{n_{FZn}}+x_{Zn}}}{C_{eZn}{}^{x_{Zn}}+y_{Zn}{C}_{eNi}{}^{z_{Zn}}}$ $q_{eNi}=\frac{k_{FNi}{C}_{eNi}{}^{\frac{1}{n_{FNi}}+x_{Ni}}}{C_{eNi}{}^{x_{Ni}}+y_{Ni}{C}_{eZn}{}^{z_{Ni}}}$	kFZn, kFNi, nFZn, nFNi: Parameters derived from the corresponding single-component Freundlich isotherm. xZn, yZn, zZn, xNi, yNi, zNi: Freundlich parameters determined from the binary equilibrium data.	[37]
Modified Redlich–Peterson	$q_{eZn}=k_{RPZn}\frac{C_{eZn}}{{\eta }_{Zn}}/\left[1+a_{RPZn}{\left(\frac{C_{eZn}}{{\eta }_{Zn}}\right)}^{b_{RPZn}}+a_{RPNi}{\left(\frac{C_{eNi}}{{\eta }_{Ni}}\right)}^{b_{RPNi}}\right]$ $q_{eNi}=k_{RPNi}\frac{C_{eNi}}{{\eta }_{Ni}}/\left[1+a_{RPZn}{\left(\frac{C_{eZn}}{{\eta }_{Zn}}\right)}^{b_{RPZn}}+a_{RPNi}{\left(\frac{C_{eNi}}{{\eta }_{Ni}}\right)}^{b_{RPNi}}\right]$	ηZn, ηNi: Correction coefficients for Zn2+ and Ni2+ ions estimated from binary equilibrium data. KRPNi, KRPZn, ARPNi, ARPZn, bRPNi, bRPZN: Model parameters derived from the corresponding single-component biosorption data.	[38]
Modified Sips	$q_{eZn}=\frac{q_{msZn}\prime b_{sZn}\prime C_{eZn}{}^{n_{sZn}\prime }}{1+b_{sNi}\prime C_{eNi}{}^{n_{sNi}\prime }+b_{sZn}\prime C_{eZn}{}^{n_{sZn}\prime }}$ $q_{eNi}=\frac{q_{msNi}\prime b_{sNi}\prime C_{eNi}{}^{n_{sNi}\prime }}{1+b_{sNi}\prime C_{eNi}{}^{n_{sNi}\prime }+b_{sZn}{C}_{eZn}{}^{n_{sZn}\prime }}$	qmsZn’, qmsNi’: Maximum Zn2+ and Ni2+ biosorption capacity (mmol/g). bsZn’, bsNi’, nsZn’, nsNi’: Model parameters obtained from binary component biosorption data.	[20]

) [20,35,36,37,38].

2.6. Statistical Analyses and Determination of the Biosorption Isotherm Parameters

All batch equilibrium biosorption experiments were performed threefold to ensure the reproducibility and accuracy of the data. Mean values (calculated from triplicate experiments) ± standard deviations (SDs) are reported herein. The data obtained for the equilibrium biosorption of Zn²⁺ and/or Ni²⁺ were statistically examined by variance analysis with Tukey’s assay and with a 95% confidence interval using SigmaStat V3.5 software (Systat Software, San Jose, CA, USA).

The Matlab V7.9 (The MathWorks Inc., Nattick, MA, USA) and SigmaStat V3.5 software programs were used to obtain the parameters for the monometallic and bimetallic isotherm models, respectively, through application of nonlinear regression analysis to the experimental equilibrium biosorption data. The goodness-of-fit of each isotherm model was evaluated using the determination coefficient (R²), the root mean squared error (RMSE), and the sum of the squared errors (SSE). An R² value close to unity in addition to smaller RMSE and SSE values indicate a better description of the experimental biosorption data by an individual isotherm model.

2.7. Diffuse Reflectance Infrared Fourier Transform Spectroscopy (DRIFTS)

DRIFTS analysis was used to determine the CS surface functional groups responsible for the biosorption of Zn²⁺ and/or Ni²⁺ ions from aqueous solutions. More specifically, samples of CS (1 g/L) were added to monometallic solutions containing 20 mM Zn²⁺ or Ni²⁺, and to bimetallic solutions containing 20 mM of both Zn²⁺ and Ni²⁺. All solutions were at pH 6.0 and the CS/solution mixtures were agitated at 180 rpm for 24 h to saturate the biosorbent binding sites with the metal ions. Subsequently, the resulting suspensions were subjected to centrifugation at 4000 rpm for 4 min, and the CS pellets were washed exhaustively with deionized water to eliminate the unbound Zn²⁺ and/or Ni²⁺ ions. Centrifugation was then repeated (4000 rpm, 4 min) using the suspensions of CS pellets in deionized water to obtain pellets of the heavy metal-loaded CS, which were oven-dried to a constant weight at 105 °C.

Dried samples of the native CS (i.e., not loaded with heavy metal ions) and of the CS samples loaded with Zn²⁺, Ni²⁺, and Zn²⁺+Ni²⁺ ions were ground into fine powders using a mortar and pestle, mixed with KBr in a 1:5 ratio, and then analyzed by DRIFTS using a Perkin-Elmer diffuse reflectance device on a Perkin-Elmer Spectrum 2000 FTIR spectrometer (Perkin-Elmer, Inc., Waltham, MA, USA). DRIFTS spectra were collected over 64 scans in the wavenumber range of 4000–400 cm⁻¹ with a resolution of 4 cm⁻¹.

2.8. Scanning Electron Microscopy Combined with Energy Dispersive X-ray Spectroscopy (SEM-EDX)

SEM-EDX analysis was used to examine any changes in the elemental composition of the CS surface resulting from the biosorption of Zn²⁺ and/or Ni²⁺ ions. For this purpose, dried samples of the native CS, Zn²⁺-loaded CS, Ni²⁺-loaded CS, and Zn²⁺+Ni²⁺-loaded CS were coated with graphite and then observed under a scanning electron microscope (SEM, JEOL, JSM-6300, Jeol Ltd., Tokyo, Japan) operating at 15 kV and equipped with an energy dispersive X-ray (EDX) detection system.

2.9. X-ray Fluorescence (XRF) Spectroscopy

The elemental analyses of the native CS, Zn²⁺-loaded CS, Ni²⁺-loaded CS, and Zn²⁺+Ni²⁺-loaded CS were carried out by XRF (Siemens SRS 3000 spectrometer, Siemens AG, Munich, Germany).

2.10. Confocal Laser Scanning Microscopy (CLSM)

Micrographs of the native CS, Zn²⁺-loaded CS, and Ni²⁺-loaded CS were obtained using a Zeiss LSM 710 NLO multiphoton laser scanning confocal microscope (Carl Zeiss Meditec AG, Jena, Germany). Measurements were carried out using Zeiss ZEN software, and a Zeiss EC Plan-Neofluar 10×/0.3 objective lens was used for scanning. The microscope possessed a fluorescence detection range of 417–729 nm.

3. Results and Discussion

3.1. Characterization of CS

The specific surface area, total pore volume, and pore diameter are important properties of biosorbents, considered to be indicative of biosorbent effectiveness. The CS average specific surface area, total pore volume, and average pore diameter were found to be 15 m²/g, 0.0326 cm³/g, and 3.209 nm, respectively. The average pore diameter of CS (3.209 nm) indicates that it is a mesoporous biomaterial.

3.2. Effect of the Metal Solution pH on the Single and Binary Biosorption of Zn²⁺ and Ni²⁺ Ions

The solution pH is among the foremost operational factors that affects the biosorption of heavy metal ions from aqueous solutions due to the fact that it affects the biosorbent surface charge, the water solubility, and the degree of ionization and speciation of the heavy metal ions. Consequently, the solution pH alters the availability of metal biosorption sites on the biosorbent surface, in addition to influencing competition between the heavy metals present in solution for the biosorption sites [1,39].

Thus, to assess the effects of the solution pH and to determine the optimum pH values for the individual and simultaneous biosorption of Zn²⁺ and Ni²⁺ ions onto CS, equilibrium biosorption trials were performed using metal solutions with pH values ranging from 1.0 to 6.0 (see Figure 1). It is evident from the plots shown in Figure 1 that for both simple and binary metal systems, the biosorption of both Zn²⁺ and Ni²⁺ was negligible between pH 1.0 and 3.0. In contrast, at solution pH values > 3.0, the equilibrium biosorption capacities of both metal ions increased upon increasing the solution pH, thereby confirming that the biosorption of Zn²⁺ and Ni²⁺ ions onto CS is strongly dependent on the solution pH. It was therefore considered that the extremely low levels of biosorption exhibited by CS at lower pH values were due to high electrostatic repulsion between the positively charged metal ions and the positively charged biosorption sites, as well as competition between the metal ions and the high concentration of H₃O⁺ (which is present at low pH values) for the occupancy of the same biosorption sites. In contrast, at higher solution pH values, the increased Zn²⁺ and Ni²⁺ biosorption levels were attributed to the increasingly anionic character of the CS surface, which resulted in strong electrostatic attractions between the positively charged metals ions and the negatively charged CS surface. Moreover, a lower concentration of H₃O⁺ would be present at higher pH values, and so the competition between this species and the metal ions for the biosorption sites would also be reduced.

For the monometallic and bimetallic systems, the highest equilibrium biosorption capacities of Zn²⁺ were obtained at solution pH values of 5.0 and 6.0, while the highest equilibrium Ni²⁺ biosorption capacity was attained at a solution pH of 6.0 in the single metal system and at solution pH values of 5.0 and 6.0 in the binary metal system (p < 0.05). These results indicate that a pH of 6.0 is optimal for both the individual and simultaneous biosorption of Zn²⁺ and Ni²⁺ ions onto CS biomass, and consequently, this solution pH value was used for all subsequent biosorption experiments. Indeed, previous studies have also reported an optimal solution pH of 6.0 for Zn²⁺ and Ni²⁺ biosorption in monometallic systems [40,41,42]. Furthermore, Morales-Barrera et al. [1] reported an optimal solution pH of 6.0 for the simultaneous biosorption of Zn²⁺ and Ni²⁺ onto Lemna gibba from binary metal solutions.

Furthermore, we found that at solution pH values > 3.0, the equilibrium biosorption capacities of Zn²⁺ were greater than those of Ni²⁺ for both the monometallic and the bimetallic systems. Likewise, at solution pH values > 4.0, the biosorption capacities of Zn²⁺ (Figure 1a) and Ni²⁺ (Figure 1b) in the monometallic systems were higher than those of the bimetallic systems, indicating that the biosorptive removal of one heavy metal was adversely affected by the presence of another heavy metal in the bimetallic solution. These results also indicate that Zn²⁺ ions interfered more strongly with Ni²⁺ biosorption onto CS (~50%) than vice versa (~21%), and that the affinity of CS for Ni²⁺ ions is substantially less than for Zn²⁺ ions.

3.3. Metal Biosorption Isotherms

3.3.1. Monometallic Systems

Equilibrium biosorption isotherms and their mathematical modeling are important tools that provide meaningful information on the adsorbate–biosorbent interactions and the biosorption mechanism, and so are required for the design and optimization of large-scale biosorption processes [43,44]. Thus, Figure 2 displays the experimental isotherms for the biosorption of Zn²⁺ (Figure 2a) and Ni²⁺ (Figure 2b) from monometallic systems onto CS at a solution pH of 6.0 and at 25 ± 1 °C. As indicated, the equilibrium metal biosorption capacities increased with increasing equilibrium concentrations of Zn²⁺ and Ni²⁺ in the aqueous solutions, and this was attributed to the initial metal concentration, which ultimately resulted in enhanced interactions with the CS biosorbent by increasing the probability of interactions between the heavy metal ions and the biosorbent binding sites. Additionally, a higher initial metal concentration leads to a higher metal concentration gradient, which is the thermodynamic driving force that overcomes the mass transfer resistance of the system to increase the equilibrium biosorption capacity [43,45].

As shown in Figure 2, the Zn²⁺ and Ni²⁺ biosorption isotherms are concave to the concentration axis (i.e., the x-axis), which indicates that, as the binding sites for the biosorption of Zn²⁺ and Ni²⁺ ions become occupied, it becomes increasingly more difficult for the remaining heavy metal ions to find vacant binding sites on the CS surface [46] due to the biosorbent surface becoming progressively saturated with metal ions [47]. Likewise, the initial slope and the concave shape of the Zn²⁺ and Ni²⁺ biosorption isotherms show a resemblance with the type L isotherm of the Giles’ classification of adsorption isotherms from solute solutions [46]. This isotherm type is generally associated with a high affinity of the biosorbent for the adsorbate, in addition to a minimum competence between the adsorbate and the solvent to occupy the biosorbent binding sites [46,47]. It is noteworthy, however, that the Zn²⁺ and Ni²⁺ biosorption isotherms do not present a plateau, which suggests that the biosorption binding sites of CS are not saturated in the heavy metal concentration range examined herein (i.e., 0–40 mM). We also observed that the Zn²⁺ biosorption isotherm (Figure 2a) shows a higher initial slope than that of the Ni²⁺ biosorption isotherm (Figure 2b), which suggests that CS has a higher preference for Zn²⁺ ions compared to Ni²⁺.

The Zn²⁺ and Ni²⁺ biosorption isotherms were also modeled mathematically using two-parameter (Freundlich and Langmuir) and three-parameter (Sips and Redlich–Peterson) isotherm models to determine the most satisfactory models for describing the equilibrium biosorption processes. Thus,

Table 3. Parameters of the mono-component isotherm models for Zn²⁺ and Ni²⁺ biosorption onto CS.

Langmuir
	qm	bL		R2	SSE	RMSE
Zn2+	2.827 ± 0.123	0.969 ± 0.244		0.963	0.489	0.211
Ni2+	3.664 ± 0.116	0.151 ± 0.014		0.994	0.085	0.088
Freundlich
	kF	nF		R2	SSE	RMSE
Zn2+	1.291 ± 0.072	3.979 ± 0.308		0.978	0.292	0.163
Ni2+	0.717 ± 0.055	2.304 ± 0.136		0.984	0.197	0.134
Redlich–Peterson
	kRP	aRP	bRP	R2	SSE	RMSE
Zn2+	10.82 ± 2.11	6.619 ± 1.485	0.824 ± 0.012	0.998	0.031	0.053
Ni2+	0.977 ± 0.108	0.611 ± 0.124	0.778 ± 0.026	0.999	0.014	0.035
Sips
	qm	bS	nS	R2	SSE	RMSE
Zn2+	4.011 ± 0.369	0.505 ± 0.080	0.491 ± 0.048	0.995	0.062	0.075
Ni2+	4.706 ± 0.242	0.147 ± 0.007	0.744 ± 0.030	0.999	0.011	0.032

shows the parameters of the Freundlich, Langmuir, Redlich–Peterson, and Sips isotherm models for the single metal biosorption of Zn²⁺ and Ni²⁺ ions onto CS, along with their R², SSE, and RMSE values. In addition, comparisons between the experimental and predicted equilibrium data are shown in Figure 2.

As indicated by these data, the highest values for the determination coefficient (R²) and the lowest values for the error functions (SSE and RMSE) were provided by the Redlich–Peterson and Sips models, and consequently, these isotherm models were considered to be the most suitable for representing the experimental Zn²⁺ and Ni²⁺ biosorption isotherms in monometallic systems. It should be noted here that both the Sips and Redlich–Peterson models are hybrid models that combine the features of the Langmuir and Freundlich isotherms [48,49]. Furthermore, it was found that the Redlich–Peterson (b_RP) and Sips (n_s) isotherm constants deviated from unity, which indicates that the CS surface is heterogeneous in nature [50]. Moreover, the Langmuir isotherm model predicted b_L values between 0 and 1, while the Freundlich isotherm model predicted n_F values between 1 and 10, which both indicate that the biosorptive removal of Zn²⁺ and Ni²⁺ ions by CS was favorable under the studied conditions [43,51]. Additionally, the b_L and n_F values for Zn²⁺ biosorption were greater than those for the biosorption of Ni²⁺, which again suggests that CS has a higher preference for Zn²⁺ [1].

3.3.2. Bimetallic Systems

Figure 3 shows the Zn²⁺ biosorption isotherms in the absence of Ni²⁺ and upon increasing the Ni²⁺ concentration (Figure 3a), in addition to the Ni²⁺ biosorption isotherms at various concentrations of Zn²⁺ ions (Figure 3b).

The results presented in Figure 3 show that the maximum equilibrium biosorption capacity of Zn²⁺ decreased from 3.08 to 2.12 mmol/g upon increasing the initial Ni²⁺ concentration from 0 to 40 mM, which corresponds to a ≤31.27% decrease in the equilibrium Zn²⁺ biosorption capacity. Similarly, upon increasing the initial concentration of Zn²⁺ ions from 0 to 40 mM, the maximum equilibrium biosorption capacity of Ni²⁺ ions decreased from 3.18 to 0.221 mmol/g, which represents a ≤93% decrease in the presence of Zn²⁺ ions. These results clearly indicate that the biosorption of Ni²⁺ by CS was more adversely affected by the presence of Zn²⁺ ions than vice versa, further confirming the greater affinity of CS toward Zn²⁺ ions.

The biosorption equilibrium data for Zn²⁺ in the presence of Ni²⁺ ions and those of Ni²⁺ in the presence of Zn²⁺ ions were also represented in the form of three-dimensional (3D) biosorption surfaces (Figure 4). These 3D surface plots confirmed that the biosorption of a single heavy metal is affected, to some degree, by the presence of a second heavy metal in solution, and again indicates that the adverse effect of Ni²⁺ on the biosorption of Zn²⁺ was not as pronounced as the effect of Zn²⁺ ions on the biosorption of Ni²⁺.

In solution, different heavy metals tend to exhibit one of three different types of biosorption behavior: (1) Antagonism, where the effect of mixing the heavy metals is less than the effect achieved for each individual heavy metal; (2) synergism, where the effect of mixing the heavy metals is higher than the effect achieved for each individual heavy metal; and (3) noninteraction, wherein the mixing of heavy metals has no influence on the biosorption of the individual heavy metals present in the mixture (i.e., the effect is the same) [37].

Based on these results, it is apparent that an antagonistic interaction exists between the Zn²⁺ and Ni²⁺ ions during the biosorption process, and this was likely due to competition between the heavy metals for the same biosorption binding sites on the CS surface. The above results also indicate that the affinity of CS for Zn²⁺ ions is greater than that for Ni²⁺ ions, and this may be attributed to the higher atomic weight (65.38 g/mol) and ionic radius (74 pm) of Zn²⁺ compared to the corresponding values for Ni²⁺ (i.e., 58.70 g/mol and 69 pm, respectively). It has been argued that the higher the atomic weight and ionic radius of a heavy metal, the greater the probability that the heavy metal will interact with the biosorbent binding sites, and the greater the affinity of the biosorbent toward that particular heavy metal [1,52,53]. Based on this assumption, the competitive effects of Zn²⁺ and Ni²⁺ ions are primarily determined by the physicochemical properties of the heavy metals. However, it should be noted that, in a general case, the biosorption capacity is not only related to the properties of the heavy metals, but also the type of biomass employed [54]. Previous studies have shown that the green microalgae Chlorella kessleri [55] and the macrophyta Lemna gibba [1] also have a greater preference for the biosorption of Zn²⁺ over Ni²⁺.

The above results clearly indicate that the competitive effect is a key factor influencing heavy metal biosorption, and additionally, they highlight the importance of investigating the biosorption capacities of biosorbents in the presence of coexisting heavy metals.

The model bimetallic isotherm parameters were then obtained for the simultaneous biosorption of Zn²⁺ and Ni²⁺ ions by CS, and are listed in

Table 4. Parameters of the binary isotherm models for Zn²⁺ and Ni²⁺ biosorption onto CS.

Nonmodified Competitive Langmuir Isotherm
	qmZn′	qmNi′	bL Zn′			bL Ni′	R2	SSE	RMSE
Zn2+	2.522 ± 0.03		1.132 ± 0.095			0.176 ± 0.021	0.969	3.580	0.159
Ni2+		3.255 ± 0.084	3.108 ± 0.273			0.21 ± 0.019	0.972	2.469	0.132
Uncompetitive Langmuir isotherm
	qmZn*	qmNi*	bL Zn*		bL Ni*	b*	R2	SSE	RMSE
Zn2+	2.54 ± 0.03		1.565 ± 0.16		0.919 ± 0.21	0.153 ± 0.05	0.976	2.772	0.141
Ni2+		3.288 ± 0.09	3.396 ± 0.34		0.209 ± 0.02	0.003 ± 0.002	0.972	2.414	0.131
Partial competitive Langmuir isotherm
	qmaxZn″	qmaxNi″	bL Zn″	bL Ni″	bNiZn	bZnNi	R2	SSE	RMSE
Zn2+	2.73 ± 0.04		1.20 ± 0.1	0.89 ± 0.18	0.24 ± 0.02	0.044 ± 0.01	0.972	2.069	0.122
Ni2+		3.69 ± 0.08	0.97 ± 0.13	0.15 ± 0.01	0.67 ± 0.06	0.006 ± 0.001	0.979	2.975	0.84
Extended Freundlich isotherm
	xZn	yZn	zZn	xNi	yNi	zNi	R2	SSE	RMSE
Zn2+	0.25 ± 0.03	0.23 ± 0.03	0.43 ± 0.04				0.964	4.179	0.173
Ni2+				0.06 ± 0.04	0.88 ± 0.11	0.85 ± 0.03	0.977	2.001	0.120
Modified Redlich–Peterson isotherm
	ηZn			ηNi			R2	SSE	RMSE
Zn2+	1.678 ± 0.089			0.865 ± 0.142			0.966	3.940	0.167
Ni2+	1.097 ± 0.110			0.925 ± 0.046			0.965	3.046	0.146
Modified Sips isotherm
	qmsZn’	bS Zn’	nSZn’	qmsNi’	bS Ni’	nS Ni’	R2	SSE	RMSE
Zn2+	3.07 ± 0.06	0.96 ± 0.07	0.64 ± 0.02		0.65 ± 0.09	0.45 ± 0.03	0.992	0.986	0.084
Ni2+		1.54 ± 0.17	0.85 ± 0.03	3.37 ± 0.54	0.15 ± 0.02	0.65 ± 0.03	0.984	1.391	0.100

along with their corresponding error functions. More specifically, the binary biosorption of Zn²⁺ and Ni²⁺ onto CS was best described by the modified Sips isotherm model, which gave the highest R² and the lowest SSE and RMSE values. The goodness-of-fit between the experimental data and the data predicted by the modified Sips isotherm model is shown in Figure 3 and Figure 4. The maximum capacities for Zn²⁺ and Ni²⁺ biosorption predicted by the modified Sips isotherm model for the binary metal system were 3.07 and 3.37 mmol/g, respectively (Table 4). CS shows much higher biosorption capacities for Zn²⁺ and Ni²⁺ than those shown by wheat straw [4] and Lemna gibba [1].

3.4. DRIFTS Studies

The DRIFTS spectra of the native CS and the CS loaded with Zn²⁺, Ni²⁺, and Zn²⁺+Ni²⁺ ions were then compared to identify the binding sites that may be involved in the biosorption of the heavy metals (Figure 5), while the main infrared absorption bands observed in the DRIFTS spectra are listed in Table 5.

It has previously been reported that Callinectes sapidus crab shell is composed of ~30–50 w/w% CaCO₃ [56], 25 w/w% proteins [57], ≤30 w/w% chitin [56], and a low content of lipids [58,59]. Based on these reports and the obtained DRIFTS spectrum for the native CS, several absorption bands were identified relating to these components, including the C=O stretching vibration of CO₃²⁻ at 1791 cm⁻¹ [60], the C–O stretching vibration of the ring COH and of the COC and CH₂OH groups of chitin at 1077 cm⁻¹ [61], the C=O stretching vibrations of the chitin and protein amide I bands at 1680–1650 cm⁻¹ [62], the C-N stretching and N-H bending vibrations of the chitin and protein amide II bands at 1560–1530 cm⁻¹ [62], and the C=O stretching vibration of the fatty acid carboxylic and/or ester groups at 1732 cm⁻¹ [63].

Table 5. Main vibration frequencies found in the DRIFTS spectra of the native CS and the CS loaded with Zn²⁺, Ni²⁺, and Zn²⁺+Ni²⁺ ions.

Referenced Frequency (cm−1)	Functional Groups Involved	Native CS	Zn2+-Loaded CS	Ni2+-Loaded CS	Zn2++Ni2+-Loaded CS	Reference
		Frequency in This Work (cm−1)
3600–2600	OH, CH and NH stretching vibration	3600–2600	3600–2600	3600–2600	3600–2600	[62]
2877	CH stretching in chitin ring	ND	2874	2874	2874	[61]
1800	C=O stretching vibration of CO32-	1791	1792	1793	1794	[60]
1740	C=O stretching vibration of carboxylic or ester group of fatty acids	1732	1731	1733	ND	[63]
1680–1650	C=O stretching of amide I of chitin and proteins	1669	1669	1670	1669	[62]
1560–1530	N–H bending and C–N stretching of amide II of chitin and proteins	1557	1541	1541	1564	[62]
1383	CH deformation in amide II	ND	1374	1396	ND	[64]
1320	C-N stretching vibration of amide III	ND	1318	1339	ND	[65]
1260	C-O stretching of COOH	ND	1255	1275	1260	[52,65]
1074	Stretching vibrations of C–O on the structure of the chitin ring	1077	1115	1043	1116	[61]

ND = Not detected.

Table 5. Main vibration frequencies found in the DRIFTS spectra of the native CS and the CS loaded with Zn²⁺, Ni²⁺, and Zn²⁺+Ni²⁺ ions.

Referenced Frequency (cm−1)	Functional Groups Involved	Native CS	Zn2+-Loaded CS	Ni2+-Loaded CS	Zn2++Ni2+-Loaded CS	Reference
		Frequency in This Work (cm−1)
3600–2600	OH, CH and NH stretching vibration	3600–2600	3600–2600	3600–2600	3600–2600	[62]
2877	CH stretching in chitin ring	ND	2874	2874	2874	[61]
1800	C=O stretching vibration of CO32-	1791	1792	1793	1794	[60]
1740	C=O stretching vibration of carboxylic or ester group of fatty acids	1732	1731	1733	ND	[63]
1680–1650	C=O stretching of amide I of chitin and proteins	1669	1669	1670	1669	[62]
1560–1530	N–H bending and C–N stretching of amide II of chitin and proteins	1557	1541	1541	1564	[62]
1383	CH deformation in amide II	ND	1374	1396	ND	[64]
1320	C-N stretching vibration of amide III	ND	1318	1339	ND	[65]
1260	C-O stretching of COOH	ND	1255	1275	1260	[52,65]
1074	Stretching vibrations of C–O on the structure of the chitin ring	1077	1115	1043	1116	[61]

ND = Not detected.

The absorption spectra of the CS loaded with Zn²⁺, Ni²⁺ and Zn²⁺+Ni²⁺ ions showed several changes with respect to that of the native biosorbent, such as the appearance of new absorption bands, increases in the band amplitudes and intensities, and shifts in the band positions. These changes were suggestive of interactions between the heavy metals and the functional groups present on the CS surface. For example, one important change involved the absorption band corresponding to the C=O stretching vibration of CO₃²⁻, which was better defined in the spectra of the heavy metal-loaded biosorbent, which suggests that CaCO₃ is involved in the removal of Zn²⁺ and Ni²⁺ from both monometallic and bimetallic solutions by CS. Indeed, previous studies have reported that CaCO₃ plays a significant role in the adsorption of several heavy metals from aqueous solutions, such as lead, cadmium, copper, and chromium by crab shells [66,67].

Furthermore, a new absorption band appeared at 2874 cm⁻¹ in the DRIFS spectra of the CS loaded with Zn²⁺, Ni²⁺, and Zn²⁺+Ni²⁺ ions; this band was attributed to the stretching vibration of the chitin CH bonds, thereby suggesting that some of the CaCO₃ present in the crab shell dissolved in the aqueous solution to expose a number of chitin functional groups. It should also be noted here that during our study, before the solution pH reached a stable value of 6.0, an increase in pH was observed when CS particles were added to the single and binary metal solutions of Zn²⁺ and Ni²⁺; this increase was therefore attributed to the dissolution of CaCO₃ to produce CO₃²⁻ in solution. In this context, it has been previously proposed that the carbonate ions in solution (i.e., from the dissolved CaCO₃ present in the crab shell) can combine with divalent cationic heavy metals to form metal carbonates, which can then be biosorbed to chitin on the crab shell surface [27,66], and so it is possible that this reaction was also taking place in our system.

A change in the infrared band shape corresponding to the C=O stretching vibration (1669 cm⁻¹) of the amide I group [62], as well as a change in the amide II (C-N stretching and N-H bending) band width at 1564–1541 cm⁻¹ [62], were also observed in the DRIFTS spectra of the heavy metal-loaded biosorbent, which suggests the interaction of Zn²⁺ and Ni²⁺ with the amide functional groups of CS.

Moreover, new absorption bands appeared in the DRIFTS spectra of the heavy metal-loaded biosorbent at 1383 and 1320 cm⁻¹, which were assigned to the amide II C-H deformation vibration [64] and the amide III C-N stretching vibration [65], respectively. These findings strengthen the evidence for the involvement of amide functional groups in the biosorption of Zn²⁺ and Ni²⁺ ions by CS. Another important change was the appearance of an absorption band at 1260 cm⁻¹, which was assigned to the C-O stretching vibration of the COOH groups [52].

The above results therefore clearly indicate that the CO₃²⁻ ion, in addition to the amide and carboxylic functional groups present in the chitin and protein components of crab shell, play major roles in the CS biosorption of Zn²⁺ and Ni²⁺ from aqueous solutions.

3.5. EDX Analysis

The EDX spectra of the native, Zn²⁺-loaded, Ni²⁺-loaded, and Zn²⁺+Ni²⁺-loaded CS are shown in Figure 6. As indicated, strong calcium (Ca) peaks can be observed in the spectrum of the native CS (Figure 6a), which confirms the presence of CaCO₃ in this biosorbent. Peaks were also observed for carbon (C), oxygen (O), magnesium (Mg), sodium (Na), potassium (K), chlorine (Cl), and phosphorus (P), but no peaks were found for zinc and/or nickel on the surface of native CS. In contrast, strong peaks corresponding to zinc (Figure 6b), nickel (Figure 6c), and zinc + nickel (Figure 6d) were observed on the CS surface after biosorption from the corresponding aqueous solutions, thereby confirming the successful biosorption of these ions onto CS.

Importantly, in the EDX spectra of the Zn²⁺-loaded, Ni²⁺-loaded, and Zn²⁺+Ni²⁺-loaded CS, the intensity of the calcium peak was significantly reduced compared with that observed in the native CS, which suggests that calcium ions were leached out from the CS, and that nickel and zinc carbonate species were present on the CS surface. Similar findings and conclusions were reported by Vijayaraghavan et al. [27] in their studies on the crab shell biosorption of Mn²⁺ and Zn²⁺ from aqueous solutions.

3.6. XRF Analysis

XRF studies were then conducted to assess the different chemical compositions of the native, Zn²⁺-loaded, Ni²⁺-loaded, and Zn²⁺+Ni²⁺-loaded CS, and results are listed in

Table 6. XRF analyses of the native, Zn²⁺-loaded, Ni²⁺-loaded, and Zn²⁺+Ni²⁺-loaded CS.

	%
Component	Native CS	Zn2+-Loaded CS	Ni2+-Loaded CS	Zn2++Ni2+-Loaded CS
ZnO	0.03	43.9	0.03	44.00
NiO	0.01	0.02	52.1	8.29
CaO	32.68	16.51	13.83	13.73
Trace metals	9.05	10.07	9.44	9.45
LOI	58.23	29.5	24.6	24.53

.

It is evident that the most abundant component of the native CS is calcium (i.e., CaO, 32.68%), which is present in the form of calcium carbonate in crab shells [56,68]. In addition, CS contains 9.05% trace elements, which mainly include phosphorus, magnesium, sodium, aluminum, and potassium. As indicated by the XRF results, its zinc and nickel contents are negligible. Furthermore, CS was found to contain an organic content of 58.23%, which was attributed to the chitin and protein components, and was determined based on the loss of ignition (LOI).

In contrast, following the biosorption of Zn²⁺ and Ni²⁺ from single metal systems, the zinc and nickel contents of the heavy metal-loaded CS increased to 43.9% (ZnO) and 52.1% (NiO), respectively. Similarly, for the binary metal system, the zinc and nickel contents in the Zn²⁺+Ni²⁺-loaded CS were determined to be 44% (ZnO) and 8.29% (NiO), respectively; this higher zinc content further confirms the greater affinity of CS toward Zn²⁺, as discussed above. Overall, these results clearly confirm the biosorption of Zn²⁺ and Ni²⁺ onto CS, both from single and the binary metal solution systems.

Notably, the calcium content (CaO) of Zn²⁺-loaded, Ni²⁺-loaded, and Zn²⁺+Ni²⁺-loaded CS was approximately half that of the native CS, which can be attributed to the dissolution of some of the CaCO₃ present in CS after coming into contact with Zn²⁺ and/or Ni²⁺ solutions. These findings corroborate the results obtained in the FTIR and SEM-EDX studies. Contrastingly, the trace element content of Zn²⁺-loaded, Ni²⁺-loaded, and Zn²⁺+Ni²⁺-loaded CS was similar to that of native CS, possibly due to the fact that these elements were not exchanged during the biosorption processes.

3.7. CLSM Studies

One of the advantages of CLSM is its ability to display autofluorescent components present in a sample that exhibit different emission wavelengths in different colors, without the need for staining. Thus, in the present work, this technique was used to demonstrate the presence of heavy metals on the surface of CS loaded with Zn²⁺ and Ni²⁺. Figure 7a, Figure 8a and Figure 9a display the optical micrographs recorded at a magnification of 20× for the native, Zn²⁺-loaded, and Ni²⁺-loaded CS, respectively. Likewise, Figure 7b–d, Figure 8b–e and Figure 9b–e correspond to the confocal micrographs of the above three CS systems, respectively. As indicated, the native CS exhibits two maximum emission wavelengths (E_m) in its emission spectrum, namely at 519 nm (in red, Figure 7b) and 461 nm (in blue, Figure 7c). To verify that this fluorescence originated from the biosorbent sample, the optical (Figure 7a) and confocal (Figure 7b–d) micrographs of the native CS were overlapped to generate the overlay image shown in Figure 7d.

In addition, as shown in Figure 8d and Figure 9d, both Zn²⁺ and Ni²⁺ exhibited autofluorescence at an E_m of 636 nm (in green), and consequently, the CLSM assays could only be performed using the samples loaded with a single heavy metal and not with both metals. Thus, Figure 8b–d show the confocal micrographs of CS loaded with Zn²⁺ at emission wavelengths of 519, 461, and 636 nm, respectively, while Figure 9b–d show the corresponding images for Ni²⁺ loading. The overlay images of the CS specimens loaded with Zn²⁺ and Ni²⁺ are shown in Figure 8e and Figure 9e, wherein it can be clearly observed that these metal ions were present on the CS surface.

4. Conclusions

The present work investigated the potential for using crab shell (CS) as a heavy metal biosorbent to individually and simultaneously remove Zn²⁺ and Ni²⁺ from aqueous solutions. Upon examination of the optimal conditions for the biosorption process, it was found that the solution pH had a significant effect in both the monometallic and bimetallic systems, and a pH of 6.0 was determined to be optimal for the individual and simultaneous removal of Zn²⁺ and Ni²⁺ ions. In addition, the single and binary biosorption equilibrium data obtained for the removal of Zn²⁺ and Ni²⁺ by CS indicated that the affinity of CS toward Zn²⁺ was higher than that toward Ni²⁺. Furthermore, the binary biosorption isotherms of Zn²⁺ and Ni²⁺ showed that the equilibrium biosorption capacity of one heavy metal decreased as the initial concentration of the other heavy metal increased, and this was attributed to competition between the two heavy metals for the CS biosorption binding sites. A high antagonistic effect of Zn²⁺ ions on the biosorption of Ni²⁺ was observed, although the biosorption of Zn²⁺ was affected to a considerably lesser extent by the presence of Ni²⁺ ions. The competitive effects between these two heavy metal ions were determined mainly by their physicochemical properties, and our results indicate that this competitive effect is a key factor influencing heavy metal biosorption, thereby highlighting the importance of investigating the biosorption capacities of biosorbents in the presence of coexisting heavy metals. Moreover, the individual biosorption of Zn²⁺ and Ni²⁺ ions from aqueous solutions by CS was best described by the Sips and Redlich–Peterson isotherm models, while the simultaneous biosorption of both heavy metals was best represented by the modified Sips isotherm model. Finally, the results of analysis by diffuse reflectance infrared Fourier transform spectroscopy indicated that the carbonate, carboxyl, and amide functional groups of CS were involved in the biosorption of Zn²⁺ and Ni²⁺ ions, and the biosorption of these ions on the CS surface was confirmed by X-ray fluorescence spectroscopy, scanning electron microscopy coupled with energy dispersive X-ray spectroscopy, and confocal laser scanning microscopy. These results are expected to contribute to the development of more efficient and effective biosorbents for the removal of heavy metal contamination from wastewater systems.