Purification of Pesticide-Contaminated Water Using Activated Carbon from Prickly Pear Seeds for Environmentally Friendly Reuse in a Circular Economy

Abstract

This study proposes an innovative approach based on the concept of the circular economy. It involves treating deltamethrin-contaminated water using an activated carbon (AC) adsorption technique based on a highly adsorbent plant waste derived from prickly pear seeds (PPSs). Activated carbon was prepared from PPS via a simple pyrolysis process preceded by chemical impregnation with phosphoric acid. Thus, a whole range of physicochemical tests were carried out, including iodine number (${\mathrm{Q}}_{{\mathrm{I}}_2}$), methylene blue number (Q_MB), Bohem dosage, pH_ZC, Brunauer–Emmett–Teller analysis (BET), and scanning electron microscopy (SEM). The ${\mathrm{Q}}_{{\mathrm{I}}_2}$ and Q_MB were, respectively, 963.5 (mg g⁻¹) and 8.3 (mg g⁻¹). The pH_zc of activated carbon was 2.5, and the surface area BET was 1161.3 m² g⁻¹. Adsorption kinetics, isotherms, and thermodynamic studies of pesticides using activated carbon were established. The obtained results revealed that the adsorption of the pesticide by the activated carbon appeared to be chemisorption with an adsorption capacity of 1.13 mg g⁻¹. The adsorption capacity increased with increasing temperature, which explains an endothermic adsorption interaction. These results are in agreement with the results found using the density functional theory (DFT) and showed that activated carbon has an interesting adsorption power, which makes it as efficient as commercial activated carbon and predisposes it to the depollution of aqueous solutions contaminated with pesticides.

1. Introduction

The circular economy is currently one of today’s most significant challenges. It has developed in response to the growing consumption of depleted natural resources. Indeed, the unsustainable exploitation of resources has led to an inherent degradation of the environment, an imbalance in biodiversity, and the pollution of water bodies [1,2,3]. Hence, there is growing interest in transitioning to a circular economy, which aims to limit the consumption and wastage of natural resources and the production of waste. It goes beyond the linear economic model of extracting, manufacturing, consuming, and disposing by calling for rational and responsible use of natural resources and primary raw materials, as well as, in order of priority, the prevention of waste production. This includes the reuse and recycling of products, or, if that is not possible, the recovery of waste [1,2,3]. On the other hand, the global contamination of surface and groundwater by pesticides has become a major concern worldwide. As a result, these environmental issues have caught the attention of researchers, and the whole world is now determined to take action to restore water to good ecological status [4]. Pesticides are now the source of diffuse pollution that contaminates all continental waters in the world, including rivers, groundwater, and coastal areas. This contamination affects water quality, and, as a result, further treatment is required [5,6,7]. Pesticides may at first have seemed beneficial, but their harmful side-effects have now come to light. They are highly harmful to human health, being toxic [8], allergenic [9], carcinogenic [10], and mutagenic [11]. Their toxicity is linked to their molecular structure [12]. The main pesticides in use today belong to several major chemical families: organochlorines, organophosphates, pyrethroids, carbamates, phytosanitary products, and others [13]. Deltamethrin is a synthetic pyrethroid pesticide. It is mainly used as an active ingredient in certain insecticides. It is widely used in agriculture for its efficacy and potency against various ectoparasites (flies, lice, and ticks) and snakes due to its neurotoxic properties [14]. Deltamethrin is also frequently used in preserving and protecting stored grains and cereals from insects [14,15]. This substance is classified as highly toxic to aquatic life, with long-term effects. Its residues are often found in fruit, vegetables, cereals, and dairy products, as well as in drinking water [16,17,18,19]. Currently, there are several methods for treating pesticide-contaminated water, including ozonation [20,21], reverse osmosis [21], photocatalytic degradation [22] using various nanomaterials [23], the advanced oxidative process [24,25], photo-Fenton processes [26,27], anaerobic–aerobic biological treatment [28], etc. AC adsorption is a highly successful technique used for the removal of pesticides from contaminated water [29]. AC is characterized by its porous structure, large specific surface area, high adsorption capacity, and excellent mechanical stability, which probably make it a highly effective adsorbent for the removal of pollutants and the treatment of water [30,31]. However, commercial activated carbon is a relatively expensive product, and its regeneration is not always evident. As a result, in recent years, researchers have been searching for eco-responsible solutions to produce cheaper activated carbon from renewable materials [32]. On the other hand, the growing global interest in protecting the environment from solid waste generated by various human activities has prompted researchers to find ways of recovering this waste and encouraging the transition to a circular economy in which the objectives are energy, ecology, and a commitment to sustainable development [1,2,3]. In this context, several studies have been carried out in the framework of recovering agricultural waste in the production of activated charcoal. These coals are derived from lignocellulosic residues, such as olive kernels [33], apricot kernel shell [34], apricot stones [35], almond shells [36], pistachio shells [37], walnut shells [38], date kernels [39], banana stalks [9], rambutan peels [40], mangosteen peels [41], corncob [42], grape marks [43], coconut shells [44], peanut shells [45], etc. They are used, in turn, in water treatment [36,38,39,43], product purification [30,42], and gas adsorption systems [40,41]. In this context, this work proposes the valorization of PPS. This biomass, recovered from a food processing company, was first used in the extraction of residual fixed fatty oils using an ecological supercritical fluid extraction method. The waste regenerated from this operation was then reused for the elaboration of activated carbon. This study contributes to exploring eco-design strategies aimed at extending the life of a product by sharing, repairing, and reusing or recycling the materials that make them up at the end of their life, in a never-ending cycle. This contribution therefore allows for the management of PPS waste in line with the principles of the circular economy. In particular, it involves studying and validating a chemical treatment process for PPS that is inexpensive, effective, and perfectly suited to Tunisia’s socio-economic context. The main objective of this study is to prepare AC from the PPS to obtain an adsorbent that can be used for water treatment, particularly for pesticide removal. The PPS waste was transformed into activated carbon through chemical activation with phosphoric acid. Likewise, a physicochemical characterization of the biochar was carried out using different analysis techniques, including, in particular, Iodine (${\mathrm{Q}}_{{\mathrm{I}}_2}$) and Methylene Blue (Q_MB) numbers, pH of zero charge value (pH_ZC), Boehm dosage, scanning electron microscope (SEM), and Brunauer–Emmett–Teller (BET). In addition, kinetic modeling was carried out to establish the adsorption mechanism. In this study, isothermal models (Langmuir and Freundlich) were used to determine the equilibrium pesticide saturation rate. The thermodynamic parameters were also investigated to better understand the adsorption mechanisms. Importantly, this work is novel in its use of a modern scientific tool to establish the theoretical retention mechanism between the pesticide and activated carbon from PPS. This tool is known as the density functional theory (DFT), which is increasingly used in predicting reaction mechanisms between various systems consisting of adsorbent and adsorbate [46,47,48,49,50,51].

2. Materials and Methods

2.1. Adsorbate

Deltamethrin (DLT) (99%) was obtained from Sigma Aldrich (Switzerland) and used as a standard to identify the presence of the pesticide.

Pure deltamethrin has low water solubility (0.2 µg L⁻¹ at 25 °C), but it is soluble in some organic solvents. All experiments were conducted in ultra-pure water using a water-soluble form of the commercial pesticide (DECIS EXPERT, BAYER^®) to ensure realistic results. Different concentrations from 2 to 15 mg L⁻¹ were prepared from commercial DLT and used as adsorbates during all experiments. The molecular structure of DLT is shown in Figure 1.

2.2. Synthesis of Activated Carbon (AC)

Prickly pear seeds were obtained as waste from a PPS oil extraction manufacturing industry (Sufetula, CRS NATURAL^®, Tunisia). It is a dry residue from the fruit seeds. The seed waste was used as raw material for activated carbon elaboration after a second lab oil extraction using supercritical CO₂ at 30 MPa and 50 °C. This biomass was first crushed using a grinder to obtain a particle mean size of 500 µm and then sieved before the chemical activation stage. The process parameters for thermo-chemical activation were set to their optimal values after a parametric study using a surface response experimental design with the Minitab 21.1.1 software. The chemical activation was performed with 1 L of H₃PO₄ [52] solution with a concentration of 3 M. The experimental protocol was carried out in two stages: impregnation and pyrolysis. The first step consisted of impregnating 200 g of PPS_s in a solution of phosphoric acid under reflux conditions at 80 °C for 4 h. The mixture was then stirred at room temperature for 24 h, filtered, and dried in an oven at 80° C for 5 h [53]. In the second step, the impregnated and dried material was subjected to pyrolysis. The process took place in an oven heated at a rate of 20 °C per minute for 40 min, reaching a target temperature of 800 °C. Once the target temperature was reached, it was maintained for 135 min. Subsequently, the sample was cooled for nearly two and a half hours [54,55]. All of the aforementioned steps were performed under a 3 L per minute flow of nitrogen (N₂) gas. The sample was then washed with demineralized water until it reached a constant pH, and then finally dried in an oven at 80 °C for 5 h. The resulting product is activated carbon, which is used as an adsorbent in this study.

2.3. Characterization of Activated Carbon

The obtained activated carbon was characterized through a variety of methods, including iodine number, methylene blue number, pH_zc, BET analysis, SEM imaging, and determination of surface functionality through the Boehm titration method [56].

2.3.1. Microporosity Approximated According to the Iodine Number and the Methylene Blue Number

The AC was characterized by quantifying the milligrams of iodine and methylene blue adsorbed per gram of AC in an aqueous solution. These tests provide insights into the porosity of activated carbon and its ability to adsorb molecules of different sizes.

A 100 mL solution containing 18.17 µmol L⁻¹ (6 mg L⁻¹) of methylene blue, 0.25 mmolL⁻¹ of iodine, and 0.07 g of activated carbon was prepared. The mixture was stirred for 3 h, and then the absorbance was measured using a UV-visible spectrophotometer (6705 UV/VIS JENWAY, Vernon Hills, IL, USA) at wavelengths equal to 665 nm and 353 nm for the methylene blue and iodine assays, respectively [57,58]. Finally, the adsorption capacities, noted as Q (mg g⁻¹), were determined using Equation (1).

$$\mathrm{Q}=\frac{({\mathrm{C}}_0-{\mathrm{C}}_{\mathrm{f}})\mathrm{V}}{{\mathrm{m}}_{\mathrm{A}\mathrm{C}}}$$

(1)

• ${\mathrm{C}}_0$: Initial concentration of iodine (molL⁻¹) or methylene blue (mg L⁻¹).
• ${\mathrm{C}}_{\mathrm{f}}$: Final concentration of iodine (mol L⁻¹) or methylene blue (mg L⁻¹).
• $\mathrm{V}$: Volume of solution of iodine or methylene blue (mL).
• ${\mathrm{m}}_{\mathrm{A}\mathrm{C}}$: Mass of activated carbon (g).

2.3.2. Acidic and Basic Surface: Boehm Method

The neutralization method was adopted to determine the acidic and basic functions of the activated carbon surface involved in pollutant retention (the Boehm method). Four 0.02 M solutions of sodium bicarbonate (NaHCO₃), sodium carbonate (Na₂CO₃), sodium hydroxide NaOH, and hydrochloric acid HCl were prepared separately. A quantity of 500 mg of AC was introduced into each solution, which was stirred at 150 rpm (Vibramax 100, Gatersleben, Germany) for 48 h until reaching equilibrium [59,60]. Perkin Elmer (Waltham, MA, USA) FTIR-ATR Spectrum Two was used for infrared (IR) analysis of the AC.

2.3.3. pH of Zero Charge of Surface (pH_ZC)

The pH of zero charge pH_ZC is the pH at which the net surface charge is zero [61]. The measurements were conducted in the presence of NaCl (0.1 M) at different pH values ranging from 1 to 12 adjusted using HCl (0.1 M) or NaOH (0.1 M). For each starting pH value, 500 mg of the activated carbon was mixed with 50 mL of electrolyte solution. The equilibrium pH, corresponding to the pH_ZC point, was measured after 48 h [62].

2.3.4. Brunauer–Emmett–Teller BET Analysis

In order to determine the specific surface of the elaborated AC, the BET (Brunauer–Emmett–Teller) method was applied using a Micromeritics ASAP2020 (Norcross, GA, USA) analyzer in which liquid nitrogen was adsorbed at a temperature of 77 K. This method involves quantifying the amount of nitrogen required to create a monolayer of nitrogen molecules on the sample surface [63].

2.3.5. Scanning Electron Microscopy (SEM) Analysis

The AC surface morphology was assessed through scanning electron microscopy (SEM) analysis using a JSM-7000F JEOL Microscope (Kyoto, Japan). The primary components of the raw activated carbon, including carbon, hydrogen, nitrogen, and sulfur, were identified through elemental analysis using SEM energy dispersive X-ray spectroscopy EDS (EVO AZtec, OXFORD instruments, UK).

2.4. Adsorption Experiments

2.4.1. Determination of Pesticide Elimination Rate R (%)

Different samples were prepared by mixing 20 mL of deltamethrin (with a concentration of 15 mg L⁻¹) with different quantities of activated carbon between 0.03 mg and 0.5 mg. The contact time and temperature were 3 h and 27 °C ± 2, respectively. After stirring, the solution was filtered, and the filtrate was analyzed through High-Performance Liquid Chromatography HPLC at 230 nm. The pesticide elimination rate R (%) was calculated using the following equation [64]:

$$\mathrm{R}\left(\mathrm{\%}\right)=\frac{{(\mathrm{C}}_0-{\mathrm{C}}_{\mathrm{e}})}{{\mathrm{C}}_0}100$$

(2)

• ${\mathrm{C}}_0$: Initial concentration of deltamethrin (mg L⁻¹).
• ${\mathrm{C}}_{\mathrm{e}}$: Equilibrium concentration of deltamethrin (mg L⁻¹).

2.4.2. Kinetics Adsorption

Adsorption kinetics experiments were carried out by mixing 10 mL of a solution at a constant concentration of pesticide (at 25 °C and pH = 6.4) with 0.2 g of activated carbon at a constant stirring speed of 150 rpm. For both kinetic and isothermal studies, a range of initial deltamethrin concentrations from 2 to 15 mg L⁻¹ were used. The equilibrium concentration of the pesticide was determined using High-Performance Liquid Chromatography (HPLC) with an Agilent (Santa Clara, CA, USA) 1200 instrument. An analytical column with a C18 phase (150 mm × 4.6 mm ID) was used. The mobile phase consisted of acetonitrile and water in an 80:20 ratio, respectively. The injection volume was set at 20 µL, with a flow rate of 0.5 mL min⁻¹, and detection occurred at a wavelength of 230 nm. In order to evaluate the effectiveness of an adsorbate through adsorption equilibrium kinetics studies, two kinetics models, namely, pseudo-first-order (PFO) and pseudo-second-order (PSO) models, were applied to examine the mechanism of the adsorption process. The equations for these two models are presented in

Table 1. Models of adsorption kinetics and isotherms.

Adsorption Models	Used Models	Modeling Equation
Kinetics	Pseudo-first-order	${\mathrm{q}}_{\mathrm{t}}={\mathrm{q}}_{\mathrm{e}}\times \left[1-{\mathrm{e}}^{\left(-{\mathrm{K}}_1\mathrm{t}\right)}\right]$
	Pseudo-second-order	${\mathrm{q}}_{\mathrm{t}}=\frac{{\mathrm{K}}_2{{\mathrm{t}\mathrm{q}}_{\mathrm{e}}}^2}{1+{\mathrm{K}}_2\mathrm{t}{\mathrm{q}}_{\mathrm{e}}}$
Isotherms	Langmuir	${\mathrm{q}}_{\mathrm{e}}=\frac{{\mathrm{q}}_{\mathrm{m}\mathrm{a}\mathrm{x}}{{{\mathrm{K}}_{\mathrm{L}}\mathrm{C}}_{\mathrm{e}}}^{}}{1+{\mathrm{K}}_{\mathrm{L}}{\mathrm{C}}_{\mathrm{e}}}$
	Freundlich	${\mathrm{q}}_{\mathrm{e}}={\mathrm{K}}_{\mathrm{F}}{{\mathrm{C}}_{\mathrm{e}}}^{1/\mathrm{n}}$

Where q_e, q_t, and q_max are the quantities of pesticides adsorbed (mg g⁻¹), respectively, at equilibrium time, time (t), and maximum quantity of the species fixed. K₁ (min⁻¹) is the constant rate for first-order kinetics, K₂ (g mg⁻¹ min⁻¹) is the adsorption rate constant, C_e is the residual concentration at equilibrium (mg L⁻¹), K_L is the Langmuir constant (L mg⁻¹), K_F is the Freundlich constant (mg^1−1/n L^1/n g⁻¹), and 1/n is the adsorption intensity.

[65].

2.4.3. Adsorption Equilibrium Models

For the adsorption isotherms analyses, several models, the Freundlich and Langmuir models, were used [66,67]. These models were applied to establish a correlation equation between the adsorption isotherms and the characteristic properties of the adsorbent and the adsorbate. The corresponding equations are summarized in Table 1.

2.4.4. Thermodynamic Study

The thermodynamic study was carried out to determine the influence of temperature on the adsorption of deltamethrin with the elaborated activated carbon. The experiments were established at 303, 313, and 323 K. The thermodynamic parameters for the adsorption processes were calculated using this equation [68]:

$$\mathrm{L}\mathrm{n}{\mathrm{K}}_{\mathrm{i}}=\frac{∆\mathrm{S}°}{\mathrm{R}}-\frac{∆\mathrm{H}°}{\mathrm{R}\mathrm{T}}$$

(3)

where K_i is the constant of the adsorption equilibrium of the initial step, ∆S⁰ (kJ mol⁻¹ K⁻¹) is the standard entropy, ∆H⁰ (kJ mol⁻¹) is the standard enthalpy, T is the absolute temperature (K), and R is the gas constant (8.314 J mol⁻¹ K⁻¹). The values of enthalpy (∆H⁰) and entropy (∆S⁰) were calculated from the linear regression intercept slope of Ln (K_i) = f (1/T). The standard Gibbs free energy change for the initial adsorption step ∆G⁰ (kJ mol⁻¹) was determined according to the following equation [69]:

∆G⁰ = ∆H⁰ − T∆S⁰

(4)

2.5. Density Functional Theory (DFT)

To determine the retention mechanism of DLT by activated carbon, we employed the density functional theory (DFT), which, through quantum chemistry calculations, allows for the determination of the molecular properties of the lowest energy configuration. Molecular descriptors based on the evaluation of HOMO/LUMO (Highest Occupied Molecular Orbitals/Lowest Unoccupied Molecular Orbitals) from these quantum chemistry calculations provide insights into the reactivity and stability of molecules. The main descriptors are the chemical potential, the hardness, and the global electrophilic index. The chemical potential, $\mathsf{\mu }=-\frac{\left(\mathrm{H}\mathrm{O}\mathrm{M}\mathrm{O}+\mathrm{L}\mathrm{U}\mathrm{M}\mathrm{O}\right)}{2}$, measures the tendency of electron release. A higher value of this parameter implies a lower capacity for retaining electrons. The molecule’s stability and resistance to deformation are characterized by its hardness, $\mathsf{\eta }=\frac{\left(-\mathrm{H}\mathrm{O}\mathrm{M}\mathrm{O}+\mathrm{L}\mathrm{U}\mathrm{M}\mathrm{O}\right)}{2}$. A decrease in this parameter corresponds to a lower excitation energy requirement for electron transition from HOMO to LUMO. The ability of the molecule to accept an electron is indicated by the global electrophilicity index, $\mathsf{\omega }=\frac{{\mathsf{\mu }}^2}{2\mathsf{\eta }}$. It quantifies the decrease in ligand energy caused by electrons transfer.

All of the abovementioned parameters can help predict, in an adsorption process, the mechanisms of adsorbent/adsorbate interaction.

All calculations were performed on molecular structures of the lowest energy determined with the model B3LYP/6-31G(d,p) at the ground state, which is often used for medium-sized molecular structures, using ORCA 5.0 and GAUSSIAN 09 software for calculations and Avogadro 1.2.0 and GaussView 6 for visualization.

For the molecular energy calculations, the total enthalpy (H) and the free Gibbs energy (G°) were calculated for the optimized geometry corresponding to the lowest energy level. The free Gibbs energy G° was calculated as:

G° = H − T × S

(5)

where T is the standard temperature and the entropy term S is the sum of the electronic, vibrational, rotational, and translational ones.

The adsorption energy E_ads and the standard free Gibbs energy variation $∆\mathrm{G}°$ are calculated as a function of the adsorbent adsorbate dimer (DLT-CXP), adsorbate (DLT), and adsorbent (CXP) enthalpies and free Gibbs energies as follows:

E_ads = H_DLT-CXP − H_DLT − H_CXP

(6)

$${∆\mathrm{G}}_{\mathrm{ads}}^{°}={\mathrm{G}}_{\mathrm{DLT}-\mathrm{CXP}}^{°}-{\mathrm{G}}_{\mathrm{DLT}}^{°}-{\mathrm{G}}_{\mathrm{CXP}}^{°}$$

(7)

3. Results and Discussion

3.1. Characterization of Activated Carbon

3.1.1. Iodine and Methylene Blue Indices (${\mathrm{Q}}_{{\mathrm{I}}_2}$, Q_MB)

The ${\mathrm{Q}}_{{\mathrm{I}}_2}$ and Q_MB indices are used for evaluating the pore characteristics of the synthesized carbon material. The measured methylene blue indices value was 8.3 mg g⁻¹, which validates the carbon’s capacity to adsorb large- and medium-sized molecules. On the other hand, the measured iodine index value in this study was 963.5 mg g⁻¹, indicating that this activated carbon can effectively adsorb medium and small molecules.

3.1.2. Boehm Titration

Boehm’s method was used to calculate the functional groups on the surface of an activated carbon that are involved in adsorption. According to this analysis, the surface of activated carbon, as presented in

Table 2. Amounts of acidic–basic functional groups of activated carbon.

Adsorbent	Acidity Functions (meq g−1)				Basicity
Activated carbon	Carboxylic	Lactonic	Phenolic	Total	Total
	0.688	0.128	0.08	0.896	0.160

, had predominantly acidic characteristics. The acidity of the AC is mainly due to the abundance of carboxylic groups, which make up approximately 77% of the total groups, with a quantity equal to 0.688 meq g⁻¹. Similarly, the amount of lactonic groups was equal to 0.128 meq g⁻¹, followed by phenolic groups with 0.08 meq g⁻¹. However, the overall basicity was lower (0.16 meq g⁻¹) than the total acidity (0.896 meq g⁻¹). It should be noted that the development of these acidic and basic functions on the surface of activated carbons varied according to the activating agent used. Acidic functional groups can also be revealed using FTIR and XPS techniques [70,71].

The FTIR-ATR spectrum demonstrated a relatively strong band (green background in Figure 2) in the range of 1650–1350 cm⁻¹ and approximately centered at 1570 cm⁻¹. This band is attributed to the combined stretching vibrations of conjugated C=O groups and aromatic rings in functionalized AC [72]. A slightly lower intensity broad band was observed in the region of 1310–890 cm⁻¹, considered the main spectra fingerprint (grey background), with maxima at 1146 and 1075 cm⁻¹. The existence of phenols was supported by O-H bending (1390 cm⁻¹) and C-O stretching (1165 cm⁻¹) vibrations of phenols [72]. A typical nitrile vibration was also observed at 2165 cm⁻¹. The IR spectra after adsorption displayed slightly more intense vibrations in the fingerprint region compared to the one before the adsorption.

3.1.3. pH of Zero Charge Value

The pH_ZC of a material is a crucial parameter in surface characterization. This parameter helps determine whether the adsorbent surface is acidic or basic compared to the pH of the solution. When the pH is lower than the pH_ZC, the surface charge is positive, indicating acidity. However, when the pH is higher than the pH_ZC, the surface charge is negative, signifying alkalinity. In this study, the pH_ZC of the activated carbon was equal to 2.5 (Figure 3), which is lower than the solution’s initial pH of 6.8 (pH_i). These results indicate that the surface charge of the sorbent was negative. This aligns with the conclusions from the Boehm assay, as the AC presents a surface with an acidic character [73].

3.1.4. Specific Surface Area: BET Method

The low-temperature (−196 °C) nitrogen adsorption–desorption isotherm is commonly used for physical property analysis. The specific surface area is calculated using the BET method. For our prepared AC, the BET surface was equal to 1161.3 m² g⁻¹. The Barrett–Joyner–Halenda (BJH) pore size distribution (Figure 4a) clearly indicated a majority of microporosity, with a mean pore width slightly less than 2 nm. This was corroborated by the shape of the type I adsorption–desorption isotherm and the absence of hysteresis (Figure 4b), which is expected in the case of microporous material.

3.1.5. Morphological Study: SEM-EDX Analysis

Scanning electron microscopy (SEM) was used to examine the surface morphology of the AC. Figure 5 illustrates the obtained images of the sample. Note the presence of openings and hollow structures.

The elemental composition of the activated carbon derived from prickly pear seeds is illustrated in

Table 3. Elemental composition analysis of activated carbon.

Compound	C	O	Mg	Al	Si	P	K	Ca	Na	Fe
Weight of compound (%)	80.77	15.77	0.04	0.05	0.15	3.54	0.03	0.23	0.02	0.06

. From the obtained results, it is clear that the predominant elements in the composition were carbon (80%), oxygen (16%), and phosphorus (3%). However, other elements, such as calcium (Ca), silicon (Si), magnesium (Mg), iron (Fe), potassium (K), and sodium (Na), were present in relatively small quantities ranging between 0.02% and 0.23%.

3.2. Adsorption Studies

3.2.1. Mass Effect

To determine the optimum adsorbent mass for reducing the maximum amount of pesticide, the variation in activated carbon mass as a function of the amount of pesticide adsorbed was studied. The results in Figure 6 show that the mass of AC increased with the rate of pesticide adsorption. From 0.2 g upwards, the value of adsorbed pesticide remained stable. Consequently, this value of 0.2 was considered the optimum activated carbon mass that allows for the reduction of the maximum amount of deltamethrin, and it was used throughout this study.

3.2.2. Contact Time Effect

To reach the maximum value of deltamethrin adsorption capacity and to ensure the saturation of all available active sites on the AC surface, the contact time effect using different initial deltamethrin concentrations was studied. The range of initial deltamethrin concentrations was considered to be 2, 4, 6, 8, 10, 12, and 15 mg L⁻¹. Adsorption kinetics were studied for each initial concentration at 360 min. The obtained results are shown in Figure 7. It should be noted that deltamethrin adsorption by activated carbon takes place in two phases. The first phase is considered rapid, occurring between 0 and 60 min, with a rapidly increasing elimination rate reaching 75%. During this phase, lower concentrations have a higher removal rate (Figure 7—zoom). The second, slower phase is characterized by slight variations in the amount adsorbed until reaching equilibrium. The rapid adsorption during the first few minutes of the process is attributed to the number of active sites available on the adsorbent surface, corresponding to the highest process driving force. The number of such sites decreases with time when approaching the equilibrium state, resulting in a deceleration of the adsorption process.

3.2.3. Adsorption Kinetics Results

The effect of adsorption duration was studied for different concentrations of deltamethrin (2, 4, 6, 8, 12, and 15 mg L⁻¹). Kinetic curves are illustrated in Figure 8. The optimal equilibrium time for all studied concentrations was found to be 90 min. However, to ensure that full equilibrium was reached, the experimental data were collected after 6 h. The obtained equilibrium quantity q_e (mg g⁻¹) varied between 0.09 and 0.65.

Two kinetic models, namely, the pseudo-first-order model (PFO) [74] and the pseudo-second-order (PSO) model [75], were used to model the kinetics of deltamethrin adsorption onto AC. The modelization curves are presented in Figure 9.

Table 4. PFO and PSO kinetic model parameters of DLT AC adsorption.

C (mgL−1)	Pseudo-First-Order			Pseudo-Second-Order
	qe (mg g−1)	K1 (min−1)	R2	qe (mg g−1)	K2 (g mg−1 min−1)	R2
2	0.089	0.091	0.99	0.095	1.58	0.99
4	0.17	0.078	0.97	0.19	0.63	0.97
6	0.27	0.039	0.95	0.31	0.14	0.91
8	0.36	0.038	0.97	0.40	0.11	0.95
10	0.44	0.045	0.95	0.5	0.11	0.93
12	0.55	0.028	0.97	0.64	0.05	0.94
15	0.64	0.057	0.99	0.70	0.11	0.99

summarizes the obtained adsorption constant values of each model and the corresponding correlation coefficients (R²). The obtained results showed that the correlation coefficients (R²) for the two models are almost similar, and they are statistically acceptable.

In this case, a comparison of the results of these two models with the experimental results suggested that the PFO model fit the experimental data slightly better than the PSO model. The retention of the deltamethrin by the AC occurred proportionally to unoccupied, heterogeneous adsorbent sites. The adsorbent microporosity and DLT molecule size also suggest that the pesticide diffusion may be the limiting retention process.

3.2.4. Adsorption Isotherms and Modeling

The adsorption isotherms were assessed in order to evaluate the adsorption capacity of the AC. The experimental data were modeled using Langmuir and Freundlich adsorption models. Indeed, the Langmuir model is based on the hypothesis that the maximum adsorption occurs when all of the retention sites are occupied by a monolayer of adsorbate substance [76]. The Freundlich model is applied to multilayer adsorption on heterogeneous surfaces [77]. The adsorption isotherms are shown in Figure 10, and the parameters of each studied model are summarized in

Table 5. Parameters of isotherm of deltamethrin adsorption.

Models	Parameters of Isotherm		R2
Langmuir	qmax (mg g−1)	1.13	0.942
	KL (L mg−1)	0.676
Freundlich	1/n	0.639	0.926
	KF (mg1−1/n L1/n g−1)	0.437
	n	1.56

.

According to the results, we can deduce that the Langmuir model, which is illustrated in Figure 10, presents a good fit with the experimental data and a correlation coefficient R² > 0.94. However, by comparing the parameters appropriate to each model (

Table 6. The thermodynamic parameters.

Temperature (K)	ΔG° (kJ mol−1)	ΔH° (kJ mol−1)	ΔS° (kJ mol−1 K−1)
303	−29.89	87.92	0.389
313	−33.7
323	−37.66

), the Langmuir model is the most appropriate to describe the adsorption of deltamethrin by activated carbon. In this case, the adsorption was carried out on a monolayer surface of the adsorbent. Moreover, the Langmuir constant (K_L) value of about 0.7 L mg⁻¹ indicates that there was an interaction of weak binding between the adsorbent and the adsorbate. Thus, the adsorption was favorable, and desorption is possible in order to regenerate the adsorbent for further reuse.

3.2.5. Thermodynamics Study

To investigate the impact of temperature on the adsorption of the pesticide of activated carbon, a thermodynamic study was conducted. The obtained results are shown in Figure 11. From this figure, one can conclude that the increase in temperature had a significant effect on the equilibrium adsorbed quantity of pesticide q_e (mg g⁻¹).

The values of enthalpy (∆H⁰) and entropy (∆S⁰) of the adsorption, which are supposed to be temperature-independent in the range of 30–50 °C, were deduced from Figure 11b. According to the obtained results, it can be seen that the ∆H⁰ value was positive, which indicates that the adsorption process of the DLT is an endothermic reaction. The negative value of ∆G⁰ means that the adsorption of deltamethrin by the produced AC was spontaneous [78]. The classification of adsorption as either a physisorption or chemisorption process is based on the variation of enthalpy, which is a measure of the strength of the interaction between the adsorbent and the adsorbate. In our case, ∆H⁰ = 87.92 kJ mol⁻¹, which is greater than 40 kJ mol⁻¹ (Table 6). This indicates that the adsorption of deltamethrin by the activated carbon was a chemisorption process.

3.3. DFT and Retention Mechanism

To better understand the retention mechanism of DLT by the lab-prepared, activated carbon, we conducted DFT calculations on the adsorbate, adsorbent, and the adsorbate/adsorbent complex. Regarding the adsorbent, and based on a Boehm analysis, we chose to model our activated carbon with a pyrene molecule [79] functionalized with a carboxylic group, namely, carboxypyrene (CXP), which represents the major acidic functions of our adsorbent surface. The elucidation of adsorbate/adsorbent interactions was based on the evaluation of HOMO/LUMO energies of the optimized geometry (Figure 12).

HOMO represents the sites of high electron density, while LUMO represents sites of low electron density. Consequently, the HOMO/LUMO frontier orbitals determine the electron donor/acceptor character of the molecule. Thus, the higher the HOMO energy, the greater the molecule’s ability to donate electrons. Conversely, the lower the LUMO energy, the greater the molecule’s ability to accept electrons.

Table 7. HOMO, LUMO, and GAP energies of DLT, CXP, and DLT–CXP complex.

Compound	HOMO (eV)	LUMO (eV)	GAP (eV)
Deltamethrin	−6.57	−1.44	5.13
Carboxypyrene	−5.79	−2.30	3.50
Deltamethrin–Carboxypyrene	−7.48	1.16	8.65

illustrates all of the energy calculation results of the studied structures at the B3LYP/6-31G(d,p) level of theory. Figure 12 shows the DLT’s optimized structure at a minimum energy level. The same energy values and structure are found by both the Gaussian and ORCA software.

The HOMO–LUMO GAP energy is related to the stability of molecules, with larger gap energies indicating greater stability. The dimer DLT–CXP GAP energy of 8.65 eV indicates that the complex was more stable than the adsorbate (DLT) 5.13 eV and adsorbent (CXP) 3.50 eV ones. This is the first way DFT confirms the adsorption of DLT–CXP.

The adsorbate/adsorbent frontier orbitals HOMO/LUMO are represented in Figure 13. The derived chemical descriptor values are displayed in

Table 8. Chemical descriptors of DLT, CXP, and DLT–CXP complex.

Compound	µ (eV)	µ (eV)	µ (eV)
Deltamethrin	−4.01	2.57	3.13
Carboxypyrene	−4.04	1.75	4.68
Deltamethrin–Carboxypyrene	−3.16	4.32	1.16

.

The hardness of the dimer DLT–CXP, 4.32 eV, compared to the hardness of its constituents, 2.57 eV for DLT and 1.75 eV for CXP, also confirms the complex’s adsorbate/adsorbent stability and resistance to deformation. The decrease in the dimer energy is also confirmed by the lowest global electrophilicity index, 1.16 eV.

The Molecular Electrostatic Potential (MEP) can help to understand the retention mechanism. It is the electrostatic potential associated with the distribution of electrons and nuclear charges within a molecule. Typically, it is visualized by mapping its values onto the molecular surface using a color-coded scheme. The MEP calculation involves the optimization of molecular geometry, computation of electron density at various points surrounding the molecule, and subsequent determination of the interaction energy between a non-polarizing test charge at a specified point and the molecular charge distribution.

It serves as a condensed repository of information and a valuable tool for understanding the reactivity of molecules towards positively or negatively charged reactants.

The examination of DLT and CXP MEPs revealed excess electron densities around the nitrile group of DLT (red zone in Figure 14a) and a deficiency of the hydroxyl function of the carboxylic group of CXP (blue zone in Figure 14b). This behavior suggests a possible electrostatic interaction localized in those zones. On the other hand, the chemical potential of both DLT and CXP exhibited a high reactivity of both molecules. Their electronegativity, 4.01 and 4.04 eV, respectively, indicates their high reactivity. The reactivity of the dimer DLT–CXP is 3.16 eV, which shows relative stability compared to the reactivity of its constituents.

Based on the DFT calculation results presented in

Table 9. Energy and Gibbs free energy of DLT, CXP, and DLT–CXP complex.

Compound	H (A.U.)	G (A.U.)
Deltamethrin	−6277.069	−6277.154
Carboxypyrene	−803.693	−803.746
Deltamethrin–Carboxypyrene	−7081.2048	−7081.3127

, the adsorption energy ${\mathrm{E}}_{\mathrm{a}\mathrm{d}\mathrm{s}}=-0.44\mathrm{A}.\mathrm{U}$ (Equation (6)), and the standard free Gibbs energy ${∆\mathrm{G}}_{\mathrm{ads}}^{°}=-0.41\mathrm{eV}$ (Equation (7)). This is compatible, at a molecular scale, with a spontaneous exothermic chemisorption of DLT onto CPX, which is representative of the lab-prepared activated carbon.

Finally, according to the electronic energy stabilization process of the DLT–CXP complex (see animation: https://youtu.be/dLYqVwdQQxU), it appears that the retention of DLT by activated carbon occurs, in part, as follows: the labile hydrogen of the carboxylic acid functions on the surface of the adsorbent interacts electrostatically with the nitrile group of the DLT, which has a basic character. A hydrogen bond was established. This interaction was established by DFT and led to a complex adsorbent–adsorbate conformation of lower energy than each of its constituents.

4. Conclusions

This study describes the development of an unconventional activated carbon from agri-food waste PPS and is conceptualized within the framework of a circular economy.

Physico-chemical characterizations of the activated carbon derived from PPS were carried out. The obtained results are promising and affirm the great adsorption potential of the produced activated carbon. More importantly, the results show that the activated carbon has a microporous character, with a very high specific BET surface area (1161.31 m² g⁻¹). Moreover, the Boehm assay revealed that the synthesized activated carbon has functional groups that are predominantly acidic rather than basic, which is compatible with the obtained value of pHzc (2.5).

The kinetic models for the adsorption of deltamethrin with activated carbon were also studied. According to the obtained results, the pseudo-first-order model showed the best fit for the experimental data, with a high R². The equilibrium data were fitted to the Langmuir and Freundlich isothermal models. By comparing the parameters obtained with each model, it can be deduced that the Langmuir model fits very well with the experimental data.

More importantly, the originality of this work lies in the use of DFT to understand the theoretical adsorption mechanism and evaluate its similarity with the experimental results. The results can only further affirm the reliability of this interesting method.