Modelling and optimization of hexavalent chromium removal from aqueous solution by adsorption on low-cost agricultural waste biomass using response surface methodological approach

Wastewater pollution by chromium is of major concern due to the excessive amount generated by various industries using processes that retain a chromium finish treatment, which is destructive to the environment and human health (Jobby et al. 2018). In fact, chromium is the 7th most abundant element on Earth (Ponnusamy & Yashwanthraj 2017), and is dispersed to groundwater and surface water due to its extensive use in various industrial sectors such as metallurgy, tanning industries, painting, ceramics and the production of steel and alloys owing to its various qualities such as hardness, solubility and corrosion resistance (Hamilton et al. 2018). Chromium has different oxidation states, the most stable of which are trivalent chromium Cr(III) and hexavalent chromium Cr(VI) (Mahmoud et al. 2020). Studies have revealed that Cr(VI) is among the 14 most toxic chemicals posing a threat to humans even at ppb concentrations (Pradhan et al. 2017). It can easily penetrate into the body through the skin, digestion, the respiratory tract and mucous membranes (Li et al. 2021). Moreover, the International Agency for Research on Cancer (IARC) classified Cr(VI) compounds as carcinogenic to humans (Moffat et al. 2018). The World Health Organization (WHO) recommended a maximum allowed concentration of Cr(VI) to 0.05 and 0.5 mg/L respectively in drinking water and industrial wastewater (Aigbe & Osibote 2020).

Several techniques have been used for the uptake of this pollutant from aqueous systems including precipitation (Sun et al. 2007), electrocoagulation (Hamdan & El-Naas 2014), reverse osmosis (Mnif et al. 2017), ion exchange (Harbi et al. 2016) and adsorption (Jain et al. 2018), but these methods have several disadvantages such as high operational cost, high reagent and energy consumption, low selectivity, higher quantities of sludge generation, and are time consuming and labor-intensive (Iftekhar et al. 2017). Recently, the adsorption process, as an alternative treatments, has attracted intensive attention to find low-cost adsorbents with high chromium removal capacities (Pakade et al. 2019). A large range of adsorbents has been studied, including carbon-based materials, mineral, organic or biological origin, biosorbents, agricultural wastes. The low cost of agricultural wastes sorbents contrasted with conventional adsorbents has inspired researchers to exploit these as competent sorbents for hexavalent chromium ions removal (Mondal et al. 2017). The agricultural products enclose some compounds, including lignin, pectin, cellulose, hemicellulose, which possess effective functional groups with great affinity to Cr(VI) ions (Ali et al. 2016). In addition, they have been used owing to their low cost, renewability, sustainability, rich surface with functional groups and biodegradability (Dai et al. 2018). Several studies have focused on the efficiency of various biosorbents for Cr(VI) removal such as potato peels (Mutongo et al. 2014), peapod (Sharma et al. 2016), rice straw (Gao et al. 2008), barks of Acacia albida (Gebrehawaria et al. 2015), and teff straw (Tadesse et al. 2014). Recently, agricultural waste such as pineapple core (Rosales et al. 2019), tea (Çelebi 2020), sugarcane bagasse (Karri et al. 2020), mango kernel (Akram et al. 2017), Phragmites australis and Ziziphus spin-christi (Mahmoud et al. 2020), fruit peel (Ben Khalifa et al. 2019; Wang et al. 2020) has shown good results in the adsorption of Cr(VI) ions. Nag et al. studied the efficiency of diverse natural biomaterials including mango, jackfruit, bamboo leaves, onion and garlic peel, coconut shell and acid-treated rubber leaf for Cr(VI) removal from aqueous solution. Their results showed maximum capacity of 35.7 mg/g for mango leaf and the sequence of adsorption capacity was found to be mango leaf > jackfruit leaf > acid-treated rubber leaf > onion peel > bamboo leaf > garlic peel > coconut shell, in a lower pH solution (Nag et al. 2020). Another study performed by Rambabu et al. showed a Cr(VI) removal efficiency of 58.02% using date palm empty fruit bunch wastes (Rambabu et al. 2020).

Peanut shells (PSh) are low-cost, abundant, inexpensive and available in huge quantities. According to the Food and Agriculture Organization of the United Nations, 46 million tons of peanut were produced worldwide in September 2019 (Sorita et al. 2020). Approximately, 1 kg of peanut generated about 230–300 g of shells and it has been predicted that 10.7–14.0 million tons of peanut shell waste were generated worldwide in the years 2017 and 2018 (Ge et al. 2020). In addition, the Tunisian Ministry of Agriculture announced that the production of peanuts increased from 5,060 to 6,495 tons from the years 2015 to 2019.

There are many ways and procedures to optimize the adsorption process. The traditional single-variation method is not a reliable method of finding optimal conditions. Currently, response surface methodology with central composite design (RSM-CCD) has been widely used in environmental study modeling and optimization processes (Badr et al. 2020). RSM-CCD is an empirical statistical technique that contributes to development, improvement and optimization processes and can simultaneously resolve the optimum of several variables with the least number of experiments providing an appropriate experimental design (Mondal et al. 2017). Numerous applications of RSM have been successfully conducted to optimize the hexavalent chromium removal using biomaterials (Ben Khalifa et al. 2019; Afshin et al. 2021; Bian et al., 2021; Guo et al. 2021).

To the best of our knowledge, there have been few studies relating to the biosorption of Cr(VI) onto PSh using RSM-CCD. The main novelty of the reported study is to evaluate the biosorption capacity of PSh biomass owing to the diverse functional groups present in it. Additionally, the work intends to expose the performance of CCD to model and optimize hexavalent chromium removal from aqueous solution by adsorption on PSh, which has not been established until now. Consequently, PSh is considered as a low-cost, effectual and sustainable biosorbent for effective treatment of Cr(VI) ions polluted water.

The aims of this study were to recuperate the PSh wastes and reuse them for Cr(VI) removal from wastewater. The produced biosorption was characterized by scanning electron microscopy (SEM), energy-dispersive X-ray (EDX) spectroscopy, Fourier transform infrared (FTIR) spectroscopy, Brunauer-Emmett-Teller (BET) theory, and X-ray diffraction (XRD) and also by using Boehm and pH zero charge methods. The significant variables (pH, adsorbent amount (g), and temperature (°C)) affecting Cr(VI) biosorption were studied and optimized using RSM with CCD according to the desirability function (DF). In addition, adsorption isotherms, kinetics and thermodynamic studies were processed in order to understand the adsorption mechanism. This work also reports recovery of Cr(VI) after the adsorption process, which is necessary for sustainable application of peanut shells in wastewater treatment.

A stock solution of hexavalent chromium (1,000 mg/L) was prepared by dissolving 2.828 g of potassium dichromate (K₂Cr₂O₇) of 99% purity obtained from Merck in 1 L distilled water. The complexing agent 1,5-diphenycarbazide (98%) was supplied by Sigma Aldrich. Hydrochloric acid (37%), sulphuric acid (95–98%) and ethanol (95%) were purchased from Acros. Sodium chloride and sodium hydroxide were obtained from Shamlab. All the solutions were prepared with distilled water.

The peanut shells (PSh) were collected from a local center of preparation of shell-removed peanut in Kelibia, Tunisia. The raw feed stocks were washed three times with tap water to remove all the adhering dirt. Then, they were washed three times with distilled water. The wet material was dried in the oven at 80 °C for 24 hours and was ground using a mortar. The resulting powdered PSh was sieved to obtain a particle size less than 250 μm. Table 1 shows some physical and chemical proprieties of peanut shells powder.

In this study, the morphology and structure of PSh were carefully investigated through various measurements. The surface functional groups of PSh were estimated by the Boehm method (Valentín-Reyes et al. 2019). This method is based on the neutralization of oxygenated functions by three bases having different strengths, sodium carbonate (Na₂CO₃), sodium bicarbonate (NaHCO₃) and sodium hydroxide (NaOH) in order to determine the nature and amounts of surface functionalities among carboxylic, phenolic and lactonic groups (Kim et al. 2012). Here, 0.5 g of PSh was added to 50 mL of the three mentioned basis and HCl (0.1 mol/L). After 24 h, the basic functions were titrated with HCl (0.1 mol/L) and the acidic with NaOH (0.1 mol/L).

The pH of zero charge (pH_pzc) was determined by mixing 0.15 g of PSh with a solution 0.01 mol/L NaCl. The pH of each sample was adjusted to different values from 2 to 12 (2 units increment) using HCl (1 and 0.1 mol/L) and NaOH (1 and 0.1 mol/L). After 24 h the final pH of solutions was measured and the point of intersection of pH_final versus pH_initial was noted as pH_pzc of PSh. The pH_pzc of a material refers to the pH value for which the net charge on the surface of the material is zero (Norouzi et al. 2018).

Fourier transform infrared (FTIR) spectroscopy of the PSh was conducted by Bruker Vertex 70 model, in a spectral range of 400–4,000 cm⁻¹. The PSh was also characterized by X-ray diffraction (XRD model: PANalytical X-ray diffractometer) to identify the surface groups and phase identification. Microstructure and morphology of the native PSh was carried out using Hitachi S-4800 scanning electron microscope (SEM) operating at 20 kV. The elemental composition of PSh was determined using an Energy Dispersive X-ray (EDX) Spectrometer. The surface area and pore size of the biosorbent were determined using nitrogen adsorption isotherms at 77 K recorded with a Micrometrics Surface Area Analyzer (ASAP 2020, Micrometrics Inc, USA) after degassing at 100 °C overnight.

Reusability of the biosorbent is a very essential factor that influences the process economics of the biosorption system, precisely towards the operational costs of the process (Bharath et al. 2020). Here, 0.73 g of PSh was treated with 100 mg/L of Cr(VI) solution for 45 min at the optimum conditions (pH (2.11) and temperature (37.2 °C)). Cr(VI) loaded adsorbent was filtered, dried overnight at 80 °C and transferred into a series of flasks containing 0.1 M of sodium hydroxide, 0.1 M of sodium chloride and distilled water. Saturated adsorbent was then agitated at 125 rot/min for 45 min with all desorption solutions. The temperature of 25 °C was chosen for desorption experiments. The regenerated PSh was washed several times with distilled water, dried and applied for more Cr(VI) ions sequestration experiments.

The intersection of the curve final pH = f (initial pH) with the bisector corresponds to the pH_pzc of PSh as shown in Figure 1 was equal to 4.6. Therefore, when the pH of the solution is lower than 4.6, the adsorbent surface is charged positively. By contrast, for pH values above 4.6, the surface is charged negatively (Raza et al. 2015).

The amounts of basic and acidic groups found in PSh are presented in Table 3. Obtained results proved that the adsorbent had more acidic functional groups at the surface. The distribution of the acidic functional groups differs: the carboxylic functions represent 31.03%, the phenolic functions 6.90% and the lactones 62.07%. These results are perfectly consistent with the pH of zero charge found previously (4.6). Omorogie et al. was found to have a quite similar value for Nauclea Diderrichii seed biomass waste equal to 4.9 (Omorogie et al. 2016).

The FTIR spectrum of peanut shells is shown in Figure 2(a). The broad peak at 3,313 cm⁻¹ is an indicator of O–H group suggesting the presence of phenols and alcohols which proves the presence of cellulose and lignin in the PSh sample (Taşar et al. 2014). The peak observed at 2,922 cm⁻¹ was attributed to C–H stretching vibration of lignocellulosic components proving the presence of methyl and methylene groups (Ding et al. 2012). The peak situated at 1,724 cm⁻¹ was ascribable to carbonyl group C = O stretching vibrations of hemicelluloses. The absorbance peak at 1,627 cm⁻¹ is characteristics of aromatic C = O stretching vibrations in associated carbonyl of lignin. The peak around 1,509 cm⁻¹ may be attributed to C = C vibration of an aromatic cycle of lignin (Bayuo et al. 2019). The peak appearing in 1,030 cm⁻¹ indicates the presence of C─O bonds. The phenol (OH), carbonyl (C = O) and carboxylic (COOH) groups are essential sorption sites (Lugo-Lugo et al. 2012). The existence of an –OH group coupled to carbonyl group confirms the presence of carboxylic acid groups in the biomass (Chigondo et al. 2013). The slight shifting of bands after adsorption of Cr(VI) ions is due to a chemical interaction confirming the sorption of PSh to chromium ions from wastewater (Banerjee et al. 2019). Zhao et al. (2020) reported a FTIR spectrum of peanut shells presenting similar bands.

XRD patterns of the material were determined by XRD using a PANalytical X- ray diffractometer applying CoKα irradiation (λ = 1.79 Å) operated at 40 kV and 30 mA. The scanning scope and scanning speed were 10°–120°. The XRD pattern (Figure 2(b)) of peanut shells showed the typical spectrum of cellulosic material having main and secondary peaks at 2θ of 24° and 16°, respectively. The major peak is an indicator of the presence of highly organized crystalline cellulose, while the minor rather weak peak is an indicator of a less organized polysaccharide structure (Zhu et al. 2009). The intensity of these peaks depends on the amount of cellulose present in the biomaterials (Prithivirajan et al. 2016). The conclusion is accordant with that of the FT-IR analysis.

The SEM micrographs of peanut shells at different magnifications are shown in Figure 3. As presented in Figure 3(a), the surface of PSh is porous, irregular and has different shapes. Inside the peanut shells matrix, great numbers of pores were observed at higher magnification (Figure 3(c)). Various shapes were also observed, for example spiral tubes shapes (Figure 3(b-1)) and cavities (Figure 3(b-2)). These biomasses formed a unique and natural porous arrangement during plant growth. The surface of the PSh after the adsorption of Cr(VI) (Figure 3(d)) was less porous on the PSh surface, indicating successful loading of Cr(VI) molecules on the PSh surface (Jawad et al. 2020a).

The EDX spectra results and the weight percentages (wt. %) of PSh are given in Figure 2(c). The amounts of C and O loaded on the surface with weight percentages of 68.68% and 30.01% respectively are rather high compared to Na, Mg, Cl and Ca loading. The nitrogen adsorption–desorption isotherms of PSh were also obtained and shown in Figure 2(d), The isotherm is type-IV with a broad H3 hysteresis loop as defined by the International Union of Pure and Applied Chemistry (IUPAC) classification (Thommes et al. 2015), which is characteristic of mesoporous materials. The specific surface areas pore volume and pore size of PSh were calculated to be 0.8126 m²/g, 0.0020 cm³/g and 8.9339 nm, respectively. Taşar et al. studied the removal of lead (II) on peanut shells and a similar surface area of 0.8444 m²/g, and average pore diameter of 20.72 Å were found using a Micromeritics ASAP 2020 apparatus. The pore volume was calculated as 0.000471 cm³/g (Taşar et al. 2014).

Contact time was evaluated as one of the most essential factors affecting the biosorption efficiency. Figure 4(a) showed that the Cr(VI) adsorption increased over time until reaching equilibrium after 45 minutes. The fast adsorption in the beginning is due to the availability of a high number of empty sites, and then the saturation is due to the saturation of adsorbent sites. Therefore, the optimum contact time was chosen as 45 min for further experiments. Taşar et al. evaluated the removal of Pb (II) on peanut shells and found the same optimum contact time (Taşar et al. 2014).

The effect of adsorbent amount was studied to obtain an idea about the range to use for the experimental design. It can be seen in Figure 4(b) that the % Cr(VI) removal increased gradually from 4.05 to 22.33% with the increase in the mass of the adsorbent from 0.05 to 0.7 g and remained practically constant at adsorbent quantities higher than 0.7 g. This was due to the increase in the contact area and the number of adsorption sites and thus making easier penetration of Cr(VI) to the adsorption sites. As the quantity of hexavalent chromium ion is stable, an increase in the amount of adsorbent over a quantity that can completely adsorb the available Cr(VI) had no clear effect on further enhancement of percent adsorption.

Response surface methodology was developed by taking into consideration all the significant interactions in the CCD to optimize the critical variables and clarify the response surface nature in the experiment. The results of analysis of variance (ANOVA) and regression coefficients suggest the significant nature of contribution of the quadratic model with a P-value less than 0.05.

A Pareto chart was used mainly to recognize the factors that have the most cumulative effect on the system and thus abandon the less significant factors (Figure 5(a)). The frequency or impact of parameter is indicated by the length of each bar in the diagram. The positive coefficients indicate a desirable effect on the efficiency of Cr(VI) removal, while the negative coefficients for the model indicate an undesirable effect. It can be seen from Figure 5(a) that the pH was the most influencing factor on the removal of chromium followed by the temperature and the adsorbent amount (Mahmoud et al. 2016). The signs of coefficients showed that the adsorbent amount and the temperature had positive effects, while the pH had a negative effect on the chromium removal.

The adequacy graph of the model (Figure 5(b)) proves that the experimental results (R %) are very close to the values calculated by the model, insuring an accuracy of the model for favorable and real prediction of the results. It is clear that there is no obvious pattern followed in the observed values versus the residuals (Figure 5(c)). Figure 5(d) presents the histogram of raw residual, in which the arbitrary template of the residuals as well, announces the adequacy of the model.

To make easy the determination of the interactions between the factors and the identification of the main factors influencing the response, we resorted to the use of 3D surface plots (Fakhri 2014). The factors were taken in our case two by two in each figure while the third variable is maintained at level zero (in coded term). These plots are presented in Figure 6. From these interaction plots, it was noticed that there were very slight curvatures between the factors studied (pH, adsorbent amount and temperature) which affirmed that there were very slight interactions between these factors, as had already been shown by the statistical analysis of Pareto. Figure 6(a) shows the interaction connecting pH and adsorbent amount in the adsorption process of chromium on PSh. As shown, the removal percentage of Cr(VI) sharply increases by decreasing pH (from 10.0 to 2.0). For pH less than 2.5 (Figure 6(a)), the adsorption efficiency was maximum. This can be explained by chromium species distribution and the pH of zero charge (pH_PZC) of the biomass. At lower pH (pH < pH_PZC)_, the HCrO₄⁻ and Cr₂O₇²⁻ ions are the predominant chromium species and the surface of biosorbent becomes positively charged (Haroon et al. 2016). Therefore, the improvement of the Cr(VI) uptake at lower pH could be due to the electrostatic attraction between the biosorbent surface and the chromium species in solution. By contrast at higher pH(pH > pH_PZC), there is an electrostatic repulsion between the CrO₄²⁻ ions present mainly in the solution and the surface of the adsorbent charged negatively.

Similarly, Figure 6(c) presents the effect of adsorbent amount and temperature on Cr(VI) removal while pH is constant. A growth in both adsorbent mass and temperature increased the percentage of Cr(VI) removal before the optimum conditions were reached. Indeed, the number of abundant bonding sites on the PSh surface increased when adsorbence was added which caused the improvement of the chromium adsorption efficiency. The removal yield was better for the higher temperatures (Figure 6(b) and 6(c)). This result indicates that the Cr(VI) uptake on PSh is endothermic in nature The increasing in removal yield of Cr(VI) at high temperature can be attributed to the effect of temperature on the internal structure of the PSh, thus facilitation the diffusion of Cr(VI) ions in the PSh interspaces structure (Jawad et al. 2020a). Ben Ali et al. (2017) outlined that the biosorption on pomegranate peels was endothermic. The increase in adsorption efficiency with temperature suggests that active sites at the surface of the adsorbent available for adsorption increased with temperature. This may possibly also lead to some changes in the pore size, which becomes larger, and to a relative increase in the diffusion of the chromium ions due to the solution viscosity decreasing.

Maximum adsorption efficiency for Cr(VI) by PSh and the corresponding optimal experimental conditions were determined by the DF (Asfaram et al. 2017) (Figure 7). The profile for predicted values and DF developed by STATISTICA 10.0 software. The measure in the range of 0.0 (unpleasant) to 1.0 (very pleasant) was employed to obtain a global function (D) which must be maximized based on the efficient optimization and selection of the considered variables. As claimed by the results of the CCD design matrix in Table 2, the minimum and maximum Cr(VI) removal respectively are equal to 1.94% and 26.29%. In conformity with these values, DF settings for each removal percentage as dependent factor are shown on the right side of Figure 7. The optimal conditions for chromium removal are a pH equal to 2.11, an adsorbent mass of 0.73 g and temperature of 37.2 °C. The maximum chromium removal percentage obtained from DF is 30.28%.

To verify the results given by the model, the experiment was repeated three times using the optimal conditions given by the software. The results showed an average Cr(VI) adsorption efficiency of 29.49 ± 0.8% which is near to the predicted value as revealed in Figure 7.

The biosorption mechanism of Cr(VI) ions on PSh surface associated perplexing adsorption chemistry with coexistence of several interactions. Generally, four main steps explain the mechanism of the biosorption of Cr(VI) ions at the surface of biosorbents rich in lignocellulose and hemicellulose. These steps are: (1) adsorption coupled reduction, (2) an anionic adsorption, (3) reduction and cationic adsorption and (4) cationic and anionic adsorption (Fan et al. 2017). Based on the PSh characterizations and the biosorption experiments obtained, a possible biosorption mechanism for the Cr(VI) ions removal by PSh could be planned through the adsorption-coupled reduction pathway.

The strongly acidic medium provided an excess of H⁺ ions for the reduction of chromium from its Cr(VI) nature to the Cr(III) state. Lastly, the reduced Cr(III) was more efficiently attracted to functional sites by electrostatic attractions and surface complexation. The greater affinity of Cr(III) ions for active anionic sites on the surface of the PSh improved the anchoring of chromium ions on the PSh biosorbent (Islam et al. 2019).

Adsorption isotherms were employed using four different models in order to elucidate the biosorption performance. Generally, adsorption isotherms including Langmuir, Freundlich, Dubinin–Radushkevich and Temkin present precious information about adsorption process, surface properties and adsorbent tendency. The adsorption experiments were conducted at four temperatures 283, 298, 308 and 318 K and for chromium concentration in the range of 10–250 mg/L. The Cr(VI) adsorption isotherms on peanut shells provided by the origin Pro version 8 software are represented in Figure 9. The non-linearized equations with the corresponding constants presented in the literature (Surip et al. 2020) are summarized in Table 5.

According to the values of R² and χ² in Table 5, the Langmuir model was the model which had the highest values of correlation coefficients R² which represents an excellent regression; in addition it had the lowest values of the chi-square χ² at different temperatures. Therefore, the Langmuir model was the most suitable model to describe the bioadsorption phenomenon of hexavalent chromium on PSh. This proved that the biosorption of Cr(VI) on PSh involved monolayer adsorption on the active sites of the material (Khammour et al. 2021).

The R_L values allowed a prediction of the shape of the isotherm and the nature of the adsorption process. For a favorable adsorption (Mahmoud 2020), 0 < RL < 1, while RL > 1, RL = 1 and RL = 0 represent an unfavorable monolayer adsorption process, linear (Dim et al. 2021), and irreversible adsorption process, respectively (Ali et al. 2019). According to the calculated results of separation factor in Table 6, it can be seen that the values of R_L are between 0 and 1, which proved that the adsorption of chromium on the peanut shells was favorable. In addition, the R_L values decreased with the increase of the initial concentration, which showed that the adsorption was favorable for high initial concentrations.

Physisorption occurs in the range 1–8 kJ/mol, while for values more than 8 kJ/mol, chemisorption is ruling (Touihri et al. 2021). The values of E in Table 5 indicated the physical adsorption of Cr(VI) on PSh. In addition, the values of the heterogeneity factors n_D were higher than 3, which proved the homogenization of the adsorbent sites. Conversely, as seen from Table 5, the adsorption heat b_T of the Temkin model increased with the increase in temperature from 283 to 318 K, proving that Cr(VI) adsorption on PSh was endothermic.

The performance of different adsorbents and their maximum Cr(VI) adsorption capacity is presented in Table 7. The Tunisian peanut shells have a relatively high adsorption capacity (3.489 mg/g) compared to other biomasses, confirming the suitability of the suggested use of PSh for the removal of Cr(VI). PSh proved a good adsorption capacity compared to some activated biomasses such as banana peel (Ali & Saeed 2015), barks of Acacia albida (Gebrehawaria et al. 2015) and leaves of Eucleas Chimperi (Gebrehawaria et al. 2015). The present biosorbent was able to remove 30.28 mg/L of Cr(VI) from wastewater, which is a high concentration removal compared to other biomasses.

Many connections for binding Cr(VI) to the surface of PSh might be explained by one or more of these bonds as follows: (I) electrostatic interaction of the chromium metal with charged surfaces on the PSh, (II) surface area, total pore volume and pore size obtained by such kind of biomass, and active sites including and –OH and –COOH groups in PSh play an important role in chromium removal process.

The kinetic experiments of Cr(VI) removal were analyzed using the non-linear form of the pseudo-first-order, pseudo-second-order and Elovich models (Huynh et al. 2020; Mohammed et al. 2020). The kinetics of PSh data obtained from the experiments of concentration of 100 mg/Lat various contact times, and optimum conditions obtained previously along with the equations and constants are shown in Table 8. In addition the non-linear plots of the three models are illustrated in Figure 10.

As shown in Table 8, the pseudo-second-order kinetic model has the lowest chi-square value χ² and the highest correlation coefficient R² compared with the other models (first order and Elovich). So the pseudo-second-order model indicated excellent applicability for describing the chromium (VI) adsorption process on peanut shells. In addition, the values of the calculated q_e from the pseudo-second-order model was close to the values of the experimental q_e,exp suggesting that the Cr(VI) adsorption may be due to electrostatic attraction between the positively charged group on the adsorbent surface and negatively charged CrO₄²⁻ group of the chromium at low pH (Jawad et al. 2020b). Thus, electrostatic attraction plays an important role in Cr(VI) biosorption by PSh. Yi et al. (2017) proved that the adsorption of chromium on litchi peels follows the pseudo second order.

The decrease in ΔG^o values with an increase in temperature proves that better biosorption occurred at high temperatures (Aditya et al. 2012). Moreover, the positive value of ΔH^o proved that the adsorption process was endothermic (Iftekhar et al. 2017). This conclusion is in agreement with the results proving the increase in Cr(VI) removal yield with temperature. In addition, the positive value of ΔS^○ indicated an increase in the disorder between the solid and solution interface during the adsorption process. Hlihor et al. (2017) have found similar results saying that the adsorption of Cr(VI) on dead and living Arthrobacter viscosus biomass is endothermic due to the positive value of ΔH^o. A positive value of ΔS^○ reflects the affinity of biomass towards chromium ions in aqueous solution.

Desorption is required to manage the biosorbent waste to avoid the generation of secondary waste and recovery of valuable materials. As low pH (pH = 2.0) was favorable for Cr(VI) uptake, recovery of consumed PSh was performed using 0.1 M NaOH solvent as a basic desorbent, 0.1 M NaCl and deionized water as a neutral desorbents. Figure 12 shows the outcomes of the PSh biosorbent reusability. From the different regenerants studied, it was detected that NaOH provided the best regenerability outcomes for the PSh biosorbent as shown in Figure 12. The biosorbent suffered a friendly loss of <5% in chromium ions recovery efficiency up to 3 recycle runs when washed with NaOH solvent. Desorption of Cr(VI) from the PSh biosorbent surface at strong basic pH environment can occur due to the exchange of CrO₄²⁻ (the dominant species of Cr(VI) in alkaline solution) with hydroxyl ions (Ye et al. 2019). Daneshvar et al. found similar results studying Cr(VI) desorption by NaOH solution at pH 12 (Daneshvar et al. 2019). They assured that attacking adsorption sites by OH⁻ ions led to Cr(VI) desorption. In another work, the maximum desorption efficiency of Cr(VI) was noted as 98.45% by 0.8 M NaOH solution (Akram et al. 2017). They explained that by electrostatic repulsion, due to negatively charged sites of sorbent, this increases Cr(VI) desorption from the adsorbent.

To make the desorption process more environmental friendly, desorption of Cr(VI) efficiency was also investigated using NaCl and deionized water. However, the loss in Cr(VI) removal efficiency by the regenerated biosorbent was >5% after the first recycle run.. In agreement with our results, Cheng et al. found extremely low Cr(VI) efficiency desorption using deionized water (>3%) and high desorption efficiency (<84%) using NaOH solution (Cheng et al. 2011). They concluded that desorption of Cr(VI) by chemical adsorption and ion exchange mechanisms is more efficient than desorption during washing by deionized water.

Hexavalent chromium removal from aqueous solution is a worldwide environmental concern. Studies have used diverse processes to attain a Cr(VI) free environment or achieve the stringent guidelines of governmental rules. In this study, an RSM-CCD was used to develop a mathematical model and optimize process conditions (pH, adsorbent amount and temperature) for Cr(VI) removal from wastewater by biosorption on PSh with a less number of experiments. The value of the adjusted coefficient of determination R² = 0.972 showed that the % removal of Cr(VI) predicted by the model was correlated with that found experimentally. ANOVA study showed the significance of generated models and depicted that pH has the most significant effect on response which had a substantial effect on the removal efficiency of Cr(VI). Temperature and adsorbent amount have comparatively less significant effects on the response of Cr(VI) removal yield. The optimal parameters to remove Cr(VI) from aqueous solution at constant short time of 45 min and constant initial Cr(VI) concentration of 100 mg/L using PSh were found to be pH 2.11, biosorbent amount 0.73 g and temperature of 37.2 °C. Under these conditions maximum chromium removal (29.49%) was achieved, which was rather near to the predicted value (30.28%) obtained from RSM model.

Peanut shells were characterized by SEM, EDX, FTIR, BET, XRD, Boehm method and pH zero charge analyses. The isotherm and kinetic data were described by Langmuir and the pseudo-second-order models, while maximum adsorption capacity attributed to Langmuir model was 3.49 mg/g for 0.73 g PSh at 318 K. This biosorbent was an efficient material despite its low specific area. The thermodynamic analysis also demonstrated that the biosorption process was endothermic as did the positive heat of enthalpy ΔH^o, accompanied by a positive value of entropy change ΔS^o. The PSh waste biomass proved good regeneration potential, precisely with NaOH washing, up to three successive biosorption runs. The results of this study proved that the reported material is efficient to remove 30.28% from 100 mg/L of Cr(VI) from aqueous solutions. The material has advantages such as shortest sorption time, was easy to use, economic, sensitive and selective for the removal of hexavalent chromium from wastewater samples.

The authors are thankful for the financial support received from Faculty of Sciences of Tunis, University of Tunis El Manar. Department of Separation Science, Lappeenranta-Lahti University of Technology (LUT) of Finland for hospitality received and for providing necessary instruments for the characterization of the material.

All relevant data are included in the paper or its Supplementary Information.