The Development and Evaluation of Biosorbent Composite Spheres for the Adsorption and Quantification of Copper

Abstract

Separation techniques are employed to treat and preconcentrate samples. Preconcentration commonly employs adsorption due to the wide range of sorbents available. The biosorbent composite has emerged as a highly effective alternative, primarily due to its selectivity for active sites and its impressive adsorption capability. This study aimed to assess and create a spherical biosorbent composite using cellulose acetate and avocado seed. The purpose of this work was to use a biosorbent composite for copper adsorption by flame atomic absorption spectrometry. The copper adsorption follows the Langmuir isotherm, which indicates that it occurs in a monolayer and is homogeneous. Additionally, the adsorption nature is favorable according to the R_L factor. The highest capacity for copper adsorption is 0.121 mg g⁻¹. The report describes the methodology and validation process for quantifying copper. The findings demonstrate that the composite biosorbent enables accurate preconcentration and quantification of copper found in decongestants.

1. Introduction

Separation processes are used for the elimination of undesirable components (purification), the separation of different compounds from their initial solution, and the acquisition of a higher proportion of previously diluted compounds (preconcentration) [1].

Due to their low concentration and the presence of interferers in the sample, preconcentration can combine different methods for finding a wide range of analytes that are present in different matrices. These procedures have a relevant role in the sample treatment, since they allow for an increase in the detection and quantification limits (LOD and LOQ, respectively), precision, and accuracy [2]. Some of the methods used to separate and concentrate analytes before they are used are ion exchange, coprecipitation, cloud point extraction, electrodeposition, photodegradation, photocatalysis, solid-phase extraction, and adsorption [3,4].

Adsorption is a very popular technique because of its low cost, ease of operation, and versatility. Adsorption consists of connecting the fluid (analyte) with an adsorbent. Adsorbents can be natural, synthetic (such as carbon or minerals), chemically modified, agricultural waste, or biosorbent [5]. Applications for biosorbents, such as biomass, food, or biopolymers, are expanding due to their selective nature, non-toxicity, ease of modification, strength, chemical resistance, biodegradability, fast kinetics, and effective removal of heavy metals from complex solutions [6,7,8,9].

The use of several biosorbents has proven to be an effective method for adsorbing, preconcentrating, and quantifying diverse analytes. This is due to their selectivity in binding to specific chemical bonding sites, such as carboxylic, hydroxyl, amine, and other groups, as well as their capacity for absorption [10]. For example, Ozdemir et al. [4] developed an analytical method for immobilizing A. kestanboliensis on XAD-4 resin for the preconcentration of Co(II) and Hg(II), achieving an LOD of 0.04 ng·mL⁻¹. Moreover, Molaudzi [11] employed sugarcane bagasse and orange peels to detect lead with LODs of 0.109 and 0.287 mg·L⁻¹, respectively. On the contrary, Ribeiro et al. [12] used citrus reticulate for quantifying nickel obtained from an LOD of 3.2 µg·L⁻¹.

On the other hand, one of the most commonly used biopolymers is cellulose acetate (CA), which is the most abundant source of cellulose on earth. It is eco-friendly and easily modified by groups, such as amide and anionic ligands, that permit better adsorption capacity [13,14,15]. One application of CA is in composite material development. CA and lemongrass leaf prepared the adsorption of crystal violet, obtaining a capacity of 33.47 mg·g⁻¹ [16]; banana pseudo-stem fibers functionalized with iminodiacetic acid were employed for impregnated cellulose acetate beads for the removal of methylene blue with a maximum adsorption of 124.3 mg·g⁻¹ [17], while cellulose acetate/graphene oxide from sugarcane bagasse was applied for the adsorption of nickel with a capacity of 14.54 mg·g⁻¹ [18].

Considering this, this work involved the development of a spherical biosorbent composite with CA and avocado seed for the quantification of the amount of copper present in decongestant samples by flame atomic absorption spectrometry (FAAS) in a simple and green form. Copper is an essential element that is present in natural forms (food) or through pollution. It is an important component employed in the metabolism of glucose, cholesterol, and amino acids by enzymes [19]. However, in high amounts, it is very toxic when it accumulates in the brain, lungs, or liver, affecting the function of these organs. It can also contribute to different chronic diseases, gastrointestinal problems, cardiovascular collapse, tachycardia, and renal complications, amongst other health concerns [20]. For this reason, the WHO recommends an upper limit of 2–3 mg of copper daily for adults [19].

Copper is utilized in medical applications because it tends to form stable complexes with coordination numbers 4, 5, or 6 [20]. The oxidation state of copper also favors different geometries (square pyramidal, trigonal pyramidal, or octahedral), their affinity for N- and O- donors, and the formation of ionophores with dithiocarbamates, thiosemicarbazones, hydroxyquinolines, and hydroxyflavones that facilitate the transport of ions and increase their activity in the complex [19,21]. Copper can be found in anti-inflammatory, antimicrobial, and polyherbal formulations, as well as isotopes for radioimmunotherapy (around 0.03 mg·L⁻¹) [22,23]. For this reason, different techniques have been used to quantify copper in low concentrations, such as high-performance liquid chromatography, fluorescence, inductively coupled plasma mass spectrometry, and graphite furnace atomic absorption spectrometry [24]. However, these techniques are more expensive compared with FAAS, so, the use of the composite biosorbent proposal in this work is a good alternative for the quantification of copper in low concentrations. The composite biosorbent was characterized by Fourier transform infrared (FTIR) and scanning electron microscopy (SEM). Diverse parameters affect the biosorption; for instance, the pH, contact time, amount of avocado seed, and mass. Volume and elution time were evaluated.

2. Materials and Methods

2.1. Preparation of Biocomposite Cellulose Acetate Spheres

The initial step in the elaboration of composite cellulose acetate spheres involves activating the avocado seed. The avocado seed was washed and homogenously pulverized to a powdered form. This powder was dried at 65 °C for 8 h. Five grams of dry powder of avocado seed (HA) was shaken in 25 mL of a 0.5 mol·L⁻¹ solution of citric acid (J.T. Baker, ACS, 100.5%, Xalostoc, Edo. de Mexico, Mexico) for two hours. After that, it was filtered, washed, and dried for 24 h to obtain activated avocado seed (HAA) [25].

A 7% m/v cellulose acetate (CA, Mn = 50,000, Aldrich, Milwaukee, WI, USA) polymer solution in dimethylformamide (J.T. Baker, ACS, 99.9%, Xalostoc, Edo. de Mexico, Mexico) was prepared with different amounts of HAA. The polymer solution was dropped with a syringe into a 25 mL ethanol–water (1:4) solidification bath with 0.5 g sodium dodecyl sulfate (J.T. Baker, 95%, Phillipsburg, Germany) to obtain the composite cellulose acetate spheres (EAc/HAA). The EAc/HAA were rinsed with deionized water and allowed to dry at room temperature for 24 h for later use [26].

The EAc/HAA were characterized by scanning electron microscopy using a microscope JEOL JSM-6300 (Tokyo, Japan) to 10 Kv and 500×. The spheres were coated while being analyzed with gold sputtering. The images of the cross section of EAc/HAA were obtained with an optical microscope, ProScope HR. With regard to infrared analyses, an IR spectroscopy was performed with a Perkin Elmer System 2000 with Fourier transform.

2.2. Adsorption Experiments

Different parameters for copper adsorption were evaluated, including pH, amount of HAA, and sphere size. A total of 0.2 g of EAc/HAA was in contact with 10 mL of a solution of 5 mg·L⁻¹ of Cu(II) prepared from a CuCl₂·2H₂O salt. (J.T. Baker, 99%). Equation (1) was used to obtain the adsorption percentage ($\%{\mathrm{A}}_{\mathrm{Cu}}$), where C₀ and C_f are the initial and final concentrations, respectively.

$$\%{\mathrm{A}}_{\mathrm{Cu}}=\left({\displaystyle \frac{{\mathrm{C}}_0-{\mathrm{C}}_{\mathrm{f}}}{{\mathrm{C}}_0}}\right)100$$

(1)

The point of zero charge was determined by the drift method to put on 0.2 g EAc/HAA in 0.03 mol·L⁻¹ NaCl solution (J.T. Baker, 99%, Phillipsburg, NJ, USA) for 48 h at room temperature, modifying the pH of the solution between 2 and 10. ΔpHz was determined as the minimum change in pH (ΔpH) according to Equation (2) [27].

$$\Delta \mathrm{pH}={\mathrm{pH}}_{\mathrm{final}}-{\mathrm{pH}}_{\mathrm{inicial}}$$

(2)

Different adsorption isotherms were utilized to explain the interaction between the analyte and the sorbent. Isotherms were evaluated with solutions in the range of 0.5–35 mg L⁻¹. Langmuir and Freundlich’s linear forms were employed (Equations (3) and (4)) [28]. The Dubinin–Radushkevich isotherm (Equation (5)) was used to differentiate the adsorption type (chemical and physisorption) [29] while the Langmuir–Freundlich isotherm model permits the determination of heterogeneous surfaces (Equation (6)) [30].

$${\displaystyle \frac{{\mathrm{C}}_{\mathrm{e}}}{{\mathrm{q}}_{\mathrm{e}}}}={\displaystyle \frac{1}{{\mathrm{K}}_{\mathrm{L}}{\mathrm{q}}_{\max }}}+{\displaystyle \frac{{\mathrm{C}}_{\mathrm{e}}}{{\mathrm{q}}_{\max }}}$$

(3)

$${\mathrm{logq}}_{\mathrm{e}}={\mathrm{logK}}_{\mathrm{f}}+{\displaystyle \frac{1}{\mathrm{n}}}{\mathrm{logC}}_{\mathrm{e}}$$

(4)

$${\mathrm{In}\mathrm{q}}_{\mathrm{e}}={\mathrm{In}\mathrm{q}}_{\max }-{\mathsf{\beta }\mathsf{\epsilon }}^2$$

(5)

$${\mathrm{q}}_{\mathrm{e}}={\displaystyle \frac{{\mathrm{q}}_{\max }{\left({\mathrm{K}}_{\mathrm{LF}}{\mathrm{C}}_{\mathrm{e}}\right)}^{{\mathrm{M}}_{\mathrm{LF}}}}{1+{\left({\mathrm{K}}_{\mathrm{LF}}{\mathrm{C}}_{\mathrm{e}}\right)}^{{\mathrm{M}}_{\mathrm{LF}}}}}$$

(6)

where C_e = equilibrium concentration of adsorbate (mg·L⁻¹), q_e = amount of adsorbed (mg·g⁻¹), K_L = Langmuir constant of adsorption, q_max = maximum adsorption capacity (mg·g⁻¹), K_f = adsorption capacity (mg·g⁻¹) n = adsorption intensity, β = Dubinin–Radushkevich constant, (mol² J⁻²)|, ε = Polanyi potential (KJ mol⁻¹), K_LF = constant of heterogeneous surface at equilibrium, and M_LF = heterogeneity parameter.

The effect of temperature study was realized employing the Van’t Hoff Equation (7) [31]

$${\mathrm{lnK}}_{\mathrm{e}}={\displaystyle \frac{\Delta {\mathrm{S}}^0}{\mathrm{R}}}-{\displaystyle \frac{\Delta {\mathrm{H}}^0}{\mathrm{R}}}·{\displaystyle \frac{1}{\mathrm{T}}}$$

(7)

where ∆S⁰ = entropy (J·mol⁻¹·K⁻¹), R = gas ideal constant (8.314 J·mol·K⁻¹), ∆H⁰ = enthalpy (kJ·mol⁻¹), T = absolute temperature (K) and K_e = equilibrium constant obtained. ∆H⁰ and ∆S⁰ were obtained from the slope and intercept of the plot LnK vs. 1/T (K⁻¹). The standard Gibbs free energy ($\Delta {\mathrm{G}}^0)$ was evaluated by Equation (8)

$$\Delta {\mathrm{G}}^0=-{\mathrm{RTlnK}}_{\mathrm{e}}$$

(8)

where K_e was evaluated based on the relationship between the amount of metal on the adsorbent (C_a) and the amount of metal in solution (C_p) (Equation (9)) [32].

$${\mathrm{K}}_{\mathrm{c}}={\displaystyle \frac{{\mathrm{C}}_{\mathrm{a}}}{{\mathrm{C}}_{\mathrm{p}}}}$$

(9)

Evaluation of the rate adsorption was conducted using two kinetic models, namely pseudo-first-order and pseudo-second-order, as described by Equations (10) and (11) [33].

$$\ln \left({\mathrm{q}}_{\mathrm{e}}-{\mathrm{q}}_{\mathrm{t}}\right)={\mathrm{lnq}}_{\mathrm{e}}-{\mathrm{K}}_1\mathrm{t}$$

(10)

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

(11)

where K₁ = pseudo-first-order constant, (min⁻¹) and K₂ = pseudo-second-order constant (g mg⁻¹ min⁻¹).

2.3. Desorption Studies

A series of desorption studies were performed after copper adsorption. The EAc/HAA were rinsed with deionized water and then shaken with 10 mL of different amounts of eluent (HNO₃; J.T. Baker, ACS, 69–70%, Xalostoc, Edo. de Mexico, Mexico) for a duration of 90 min. The percentage of desorption ($\%D_{Cu}$) was determined with Equation (12), where C_D represents the final concentration of copper in the eluent.

$$\%D_{Cu}=\left({\displaystyle \frac{{\mathrm{C}}_{\mathrm{D}}}{{\mathrm{C}}_0-{\mathrm{C}}_{\mathrm{f}}}}\right)100$$

(12)

2.4. Preconcentration Experiments

The optimal conditions for Cu(II) preconcentration were determined using a Plackett–Burman experimental design (PBED). The variables evaluated were the mass (M, 0.2 and 1.0 g), sample volume (SV, 50 and 150 mL), desorption volume (DV, 5 and 10 mL), and adsorption and desorption time (AT and DT, 30 and 90 min). The data analysis was conducted using MINITAB 17 statistical software.

Optimal conditions were utilized to quantify copper in two distinct decongestant samples available from local pharmacies. All copper solutions were analyzed by the flame atomic absorption technique with a Varian SpectrAA 880 model. Each analysis was performed three times.

3. Results

3.1. Characterization of Spheres

3.1.1. Scanning Electron Microscopy

The formation of EAc/HAA involves a phase inversion. Varying miscibility between the polymeric solution and the coagulation bath might result in diverse morphologies due to the diffusion-based exchange between the two phases [34]. According to Figure 1, the EAc/HAA shows that an increase in HAA in the polymer solution decreases the porosity of the surface due to the amount of polymers employed [35]. Nevertheless, this polymer concentration permits a higher entanglement of polymer chains, allowing macrovoids inside the sphere [36].

3.1.2. FT-IR

Figure 2 shows the IR spectrum for the precursors (CA and HAA) and the EAc/HAA. Figure 2A presents the spectrum IR of avocado seed powder with a band around 3400 cm⁻¹ corresponding to the hydroxyl groups of the lignin, a 2926 cm⁻¹ band due to symmetric and asymmetric stretching of -CH of the cellulose, and a 1610 cm⁻¹ band of C-C and C-O of aromatic alkenes [37,38]. The HAA spectrum (Figure 2B) shows a decrease at 3400 and 1610 cm⁻¹ because of the condensation reactions, lignin division, and elimination of cellulose and hemicellulose. The 1736 cm⁻¹ band of C=O is characteristic of the activation with citric acid [39].

On the other hand, Figure 2C shows the characteristics of the bands of CA. At 3472 cm⁻¹, the stretching of OH groups is associated with 2940 and 2831 cm⁻¹ bands corresponding to CH and CH₂ vibration; at 1742 cm⁻¹, the C=O of the ester group shows a band of vibration, and a band is also observed at 1616 cm⁻¹ due to the water flexion of the adsorbed water, with a 1369 cm⁻¹ stretching band of CH₃. Meanwhile, 1235 and 1050 cm⁻¹ bands are observed for vibration of the C-O of ether [40,41]. The EAc/HAA spectrum (Figure 2D) demonstrates that the HAA immobilizes into the composite spheres.

3.2. Copper Adsorption

3.2.1. Influence of Characteristics of Biocomposite Spheres

The amount of HAA present in EAc/HAA was evaluated to be between 0 and 10% (w/v). According to Figure 3, an increase in HAA concentration to 2.5% w/v can be attributed to an extent in the active sites generated by the functional groups of citric acid during the activation process, considering that modified cellulose is better for adsorption of ions than unmodified cellulose [15]. It is significant to mention that the adsorption percentage is lower at concentrations higher than 2.5% w/v, probably due to the saturation of HAA decreasing the interaction between the analyte and the sorbent [42]. For further experiments, 2.5% w/v of HAA in the polymer solution was used.

One advantage of using EAc/HAA is the enhancement in the surface area. Based on this advantage, the influence of the EAc/HAA size on the adsorption percentage was evaluated, employing a 0.8 × 32 mm needle. This procedure allowed for an average sphere diameter of 2 mm, which is a decrease of approximately 40% of the initial size, making it possible to gain an extraction percentage of 46.08 ± 0.81%. The size has been utilized for the following experiments.

3.2.2. Influence of pH

The pH in the system can modify the species of metal ions and the material properties. Figure 4 shows that when the pH is low, the adsorption percentage goes down. This is probably because the high concentration of hydronium ions prevents the interaction between copper and the active sites of the EAc/HAA [42]. The decline observed at values over 6 can be ascribed to the generation of copper hydroxo complexes. This is because at pH levels ranging from 9 to 14 Cu(OH)₂ Cu(OH)₃⁻, and Cu(OH)₄²⁻ are the main species, with minor quantities of Cu(OH)⁺ (Figure 5) [15,43]. A pH of 6 will be used for the upcoming experiments.

On the other hand, the Cu(II) adsorption onto the EAc/HAA is completed by an ion exchange that involves an electrostatic interaction between the carboxylate groups (-COO-) and the metal ion. Because of this, the surface must not be positively charged [42]. Point zero charge (Figure 4) shows that to pHpzc < pH (~2.8), the net charge is globally adverse, increasing the electrostatic forces between the Cu(II) and the EAc/HAA [44].

3.2.3. Interference Study

This study assessed the impact of sodium chloride, the main ingredient in the decongestants, on the adsorption of copper. For this study, 5 mg L⁻¹ of Cu(II) was spiked with different ratios of NaCl 1:1, 1:10, and 1:100. The adsorption percentage obtained was 47.12 ± 3.92% indicating that there was no change in the adsorption percentage due to NaCl.

3.2.4. Adsorption Isotherm

Adsorption isotherms allow for a description of how the analyte (adsorbate) interacts with a solid phase (adsorbent) such as that shown in Figure 6 [45]. Langmuir and Freundlich evaluated two distinct isotherms in this context. According to the data shown in

Table 1. Isotherm model constants for adsorption of Cu(II) onto EAc/HAA.

Isotherm	Parameters 1
Langmuir	qmax 0.121 mg g−1
	KL 0.184 L mg−1
	R2 0.99
	SSE 9.1 × 10−3
Freundlich	KF 0.017 L g−1
	no 1.636
	R2 0.91
	SSE 2.3 × 10−3
Langmuir–Freundlich	qmax 0.201 mg·g−1
	KLF 0.041
	MLF 0.597
	R2 0.99
	SSE 3.2 × 10−4
Dubinin–Radushkevich	β 0.008 mol J−2
	E 7.54 KJ mol−1
	R2 0.99

¹ Maximum adsorption capacity—q_max (mg g⁻¹); Langmuir constant—K_L (L mg⁻¹); Freundlich constant—K_F (L g⁻¹); free strength of sorption—n_o; coefficient of correlation—R²; error sum of squires—SSE. Experimental conditions: Cu(II) in aqueous solution in pH = 6; 0.2 g of EAc/HAA prepared with 2.5% of HAA in polymeric solution.

, SSE values suit the Langmuir model for the Cu(II) adsorption results on the surface of the EAc/HAA. Therefore, the process was performed by monolayers with homogeneous and favorable adsorption (0.14 < R_L < 0.92) [28]. On the other hand, the Dubinin–Radushkevich isotherm indicates a physisorption due to E < 8 kJ/mol [46].

The EAc/HAA has a maximum capacity of adsorption of 0.121 mg g⁻¹, while this is lower than that of other materials (

Table 2. Maximum adsorption capacity of Cu(II) of distinct biosorbents.

Material	Maximum Capacity (mg·g−1)	Reference
EAc/HAA	0.121	This work
Pseudomonas putida biomass trapped in agar beads	0.255	[47]
Spent Mushroom Compost	0.340	[48]
Venus shell	0.446	[49]
Olive stones	0.557	[50]

), it is sufficient for realizing the preconcentration of copper for this quantification.

The temperature studies determined the nature of adsorption.

Table 3. Thermodynamic parameters for adsorption of Cu(II) onto EAc/HAA.

Temperature (K)	∆G0 (KJ mol−1)	∆H0 (KJ mol−1)	∆S0 (KJ mol−1K−1)
291	−22.66
303	−25.13	32.23	0.19
308	−25.80

Gibbs free energy—∆G⁰ (KJ mol⁻¹); enthalpy—∆H⁰; entropy (KJ mol⁻¹)—∆S⁰ (KJ mol⁻¹K⁻¹). Experimental conditions: Cu(II) in aqueous solution in pH = 6; 0.2 g of EAc/HAA prepared with 2.5% of HAA in polymeric solution.

shows that ∆G⁰ was negative; this value corresponds to favorable and spontaneous adsorption, while a positive value of ∆H⁰ implies endothermic and monolayer adsorption [51]. This result corresponds with the Langmuir isotherm.

3.2.5. Kinetic Studies

The kinetic studies permit us to describe the interaction between the adsorbate and analyte with respect to time [52]. The results acquired for the two applied kinetic models are presented in

Table 4. Kinetic parameters for sorption of Cu(II) onto EAc/HAA.

Model	Estimated Kinetic Parameters 1
Pseudo-first-order	qe (mg·g−1)	0.21
	K1 (min−1)	9.44 × 10−3
	R2	0.91
Pseudo-second-order	qe (mg·g−1)	0.03
	K2 (g·mg−1·min−1)	2.03
	R2	0.96

¹ Copper extracted at equilibrium, q_e; constant of the pseudo-first-order, K₁ (min⁻¹); constant of the pseudo-second-order, K₂.

. The regression coefficient indicates that the strongest association is observed with the pseudo-second-order model, which proposes electrostatic interactions between Cu(II) and EAc/HAA [53].

3.3. Desorption Studies

The desorption of Cu(II) was realized with different amounts of HNO₃. The high concentration of H⁺ supposes positive charged sites on the surface; this does not permit the adsorption of cations such as copper [54]. In this case, the concentration of acid had no influence on the amount of Cu(II) desorbed (

Table 5. Influence of concentration of HNO₃ in the desorption of copper. Experimental conditions: 0.2 g of EAc/HAA prepared with 2.5% of HAA in polymeric solution; 5 mg·L^–1 of Cu(II) in aqueous solution pH = 6; desorption with 10 mL of HNO₃. The contact time was 90 min for each process (adsorption and desorption).

Concentration of HNO3 (mol L−1)	Desorption Percentage (%)
0.10	97.31 (2.84)
0.25	98.42 (1.85)
0.50	96.53 (4.99)
1.00	98.00 (3.93)

). For the next set of experiments, a concentration of 0.1 mol L⁻¹ was used.

3.4. Optimization of Preconcentration of Copper

Optimal conditions of preconcentration of copper employing EAc/HAA were obtained utilizing PBED. The main variables that permit a successful preconcentration method are the mass (M), sample volume (SV), desorption volume (DV), and adsorption and desorption time (AT and DT). The findings from these different experiments are shown in

Table 6. Level combination and results obtained of PBED for the preconcentration of copper.

Experiment	M	SV	DV	AT	DT	EF
1	+1	+1	−1	−1	+1	2.90
2	+1	−1	+1	−1	−1	1.20
3	−1	+1	−1	+1	+1	0.84
4	−1	+1	−1	−1	−1	0.81
5	−1	−1	+1	+1	+1	0.32
6	+1	−1	−1	+1	+1	2.29
7	−1	−1	+1	−1	+1	0.19
8	−1	+1	+1	+1	−1	0.36
9	+1	−1	−1	+1	−1	2.15
10	+1	+1	+1	−1	+1	1.91
11	−1	−1	−1	−1	−1	0.46
12	+1	+1	+1	+1	−1	2.29

M: mass (−1) 0.2 g (+1) 1.0 g; SV: sample volume (−1) 50 mL (+1) 150 mL; DV: desorption volume (−1) 5 mL (+1) 10 mL; AT: adsorption time (−1) 30 min (+1) 90 min; DT: desorption time (−1) 30 min (+1) 90 min; EF: enrichment factor.

of PBED.

In the analysis of PBDE, the variable that most influenced the preconcentration of Cu(II) was the sphere mass because of the number of active sites of the EAc/HAA available for adsorption [55]. Additionally, the active sites of the EAc/HAA could absorb a significant amount of Cu(II), thereby increasing the integrated amount of Cu(II).

On the contrary, the HNO₃ used for the desorption of Cu(II) permitted the protons (H⁺) of the solution to be adsorbed in the EAc/HAA instead of metallic ions [56].

On the other hand, high volumes of adsorption (150 mL) facilitated the determination of the low concentration of copper [57], while low desorption volumes led to an increase in the preconcentration factor. The preconcentration of copper did not significantly depend on adsorption and desorption times, but 90 min yielded the best results. Based on this, optimal conditions of analysis were gathered from the sample volume, 150 mL of Cu(II) pH = 6; desorption volume, 5 mL de HNO₃; adsorption and desorption time, 90 min and 1 g of EAc/HAA to 2.5% w/v.

3.5. Analytical Parameters

The analytical parameters and precision determined the optimum conditions for PBDE.

Table 7. Regression parameters obtained of the calibration plot absorbance (uA) vs. amount Cu(II) (mg L⁻¹).

Parameters	Value
Slope (uAL mg−1)	2.59 ± 0.14
Intercept (uA)	0.002 ± 0.008
Correlation coefficient (r)	0.998
Limit of detection (mg L−1)	0.007
Limit of quantification (mg L−1)	0.022
Intra-day repeatability
0.025 mg L−1	5.64%
0.050 mg L−1	5.42%
0.100 mg L−1	6.99%
Repeatability inter-day
0.025 mg L−1	3.54%
0.050 mg L−1	7.91%
0.100 mg L−1	4.54%

shows the calibration line’s regression parameters. The calibration line presents a linear dependence between the concentration of copper and the absorbance signal. According to IUPAC criteria [58], the detection limit was calculated by multiplying the value of the square root of the residual variance of the standard curve over the slope three times. The method’s accuracy was evaluated with the relative standard deviation (RSD) for three replicates in terms of intra-day repeatability and inter-day repeatability. According to EU guidelines, we conducted the experiments at 0.5×, 1.0×, and 2.0× of copper, ensuring acceptable levels of intra-day repeatability and inter-day repeatability, with calculated RSDs less than 10%.

Commercial decongestant samples were analyzed using the development method and by graphite furnace absorption atomic spectrometry (GFAAS). The results obtained by both methods (

Table 8. Cu(II) analysis in decongestant commercial samples by EAc/HAA and GFAAS.

Sample	Concentration (µg L−1)		tcalculated
	EAc/HAA	GFAAS
1	132.93 ± 9.79	121.72	1.98
2	168.79 ± 2.80	162.48	3.90

) were compared using a Student’s t-test. The values of t _calculated were compared with a t_tabulated (4.3) without significant differences found between the two methods. The results demonstrated the effectiveness of the EAc/HAA in preconcentration and determination of copper.

4. Conclusions

This study successfully developed and evaluated a spheric composite biosorbent with cellulose acetate and avocado seed (EAc/HAA) for copper adsorption and quantification. The negative charge of the surface of EAc/HAA due to the carboxylic groups of HAA permits the adsorption of Cu(II) at pH values more than 2.8. Favorable adsorption is achieved by monolayers that have a maximum adsorption capacity of 0.121 mg g⁻¹. The methodology described is effortless and eco-friendly because of the low consumption of solvents and the use of biodegradable materials.