Mechanism of interaction and removal of zinc with lignocellulosic adsorbents, closing the cycle with a soil conditioner

2.1 Materials and chemicals

Local dried nut manufactory provided pistachio, peanut, and almonds hells. Previous to the ground and sieved, all shells were cleaned with deionized water and then dried out in the oven (Memmert Universal UN750, Germany) at 105 °C for >24 h. The particle size of 0,5–1,2 mm was used as the adsorbents for further studies.

The chemicals, ZnCl₂ (96% purity), HCl, and NH₄OH, are of analytical grade and were provided from Merck Chemistry, Turkey. Deionized water (resistivity = 18.2 MΩ cm⁻¹) was produced from a Merck KGaA, Darmstadt, Millipore, Sigma system and used throughout the further study. Zn stock solution (1000 mg/L) was prepared with the help of exactly 2.09 g ZnCl₂ dissolved into 1 L pure water and the desired concentration of Zn²⁺ was diluted for the study. The value of pH measured using a pH 510 Eutec pH-meter in solution (100 mg/L) was adjusted to 6 by using 0.1 mol/L HCl or 0.1 mol/L NH₄OH.

2.2 FTIR measurements

The surface chemistry was studied with the help of FTIR spectroscopy. FTIR spectra were recorded using a Perkin Elmer 400 FTIR/FT-FIR) with a spectral resolution of 4 cm⁻¹. FTIR spectra for three adsorbents is demonstrated in Fig. 1

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Fig. 1

Three adsorbent FTIR spectra and functional groups.

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2.3 SEM analyses

Scanning electron microscopy using a Zeiss Gemini 500–71-08 was used for the surface properties of the shell samples. The Origin® software was used to smooth the data. SEM images (magnification of 20,000) of the almond, peanut, and pistachio shells were taken with raw, and 10-minute intervals during removal of Zn²⁺. SEM images is presented in (Fig. 2).

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Fig. 2

SEM images of three adsorbent (Fresh, 10, 20 and 30 min).

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2.4 Analytical methods

Perkin Elmer Optima 2100 DV model inductively coupled plasma optical emission spectrometry (ICP-OES) was used to calculate the final Zn²⁺ concentrations after the designated contact time.

2.5 Batch studies

Adsorbent, 1.0 g for three shells in a 100 mL-glass conical flask under initial Zn²⁺ concentration of 5, 10, 25, 50, and 100 mg/L, at an average 24 °C temperature, was used for the batch studies (in Erlenmeyer flasks), for 45 min of contact time. The flask was shaken by a d ZHICHENG analytical model thermal shaker at 150 rpm with pre-fixed time, ranged from 5 to 45 min. 2 mL supernatants for each including the initial solution were used at pre-fixed time intervals before the Zn²⁺ concentration determination. The amount of Zn²⁺ ions in solutions (qe) were calculated by using equations (1):

The studies were carried out in duplicate to ensure reproducibility, reliability, and accuracy of the data and the Origin 9.0 program (Origin Lab, USA) was also used for all data.

2.6 Error function analyses

In this study, the average relative error, normalized standard deviation and marquardt‘s percent standard deviation was also applied experimental data to confirm the best fitting. The equations are given below;

The MPSD, NSD and ARE shows more correct estimation of qe value (Kayranli, 2011).

3.1 Characterization of adsorbents

The FTIR spectrums, scanned in the range of 450–4000 cm⁻¹, are demonstrated in Fig. 1. The spectra revealed many absorption peaks, indicating the complexity of the adsorbents. As seen in Fig. 1, the band at 3276 cm⁻¹ is indicating some hydroxyl groups (–OH) resulted from lignin, cellulose, hemicellulose in/on pistachio shell. The band near 2843 and 2150 cm⁻¹ is the stretching vibration of C–H in alkanes, aldehydes and a carboxylic acid, and C≡C bond. The peak near 1722 cm⁻¹ is the stretching vibration of C=O in aldehydes, and ketones. There is a complex set of absorptions unique to each compound in the fingerprint region (1500 cm⁻¹ to 500 cm⁻¹) of the spectrum. It is described with the help of references instead of interpreting the peaks visually. The band around 1423, 1251, and 1148 cm⁻¹ represents C=C alkanes, –NO₂ asymmetric nitro compound, and –CH₃, −CH₂ from alkanes, respectively. The peak 1026 cm⁻¹ represents the C–O bond in cellulose. Peanut and almond shell also includes cellulose, hemicellulose and lining compounds, so similar spectra peaks came out as can be seen in Fig. 1. The adsorbent peak gives valuable information concerning the bond –OH groups, C=O stretching, secondary amino group, carbonyl/carboxyl group –C–C– functional group were mostly taken part in the adsorption process.

The SEM images of pistachio, peanut, and almond shell are also demonstrated in Fig. 2. It can be seen from the SEM images; shells consist of the number of heterogeneous pore layers.

3.2 Contact time effect

Fig. 3 demonstrates the effect of time on Zn removal by shells. In the first 30 min, the removal rate increases quickly reaching a minimum of 83% for all adsorbents, and then increases in contact time have no critical effect on the rate and equilibrium was reached in about 45 min. Initial Zn²⁺ removal was rapid due to the large availability of functional groups on the adsorbent surface brought about the binding of metal ions on the adsorbent. The filling of functional groups on shells resulted in a decrease of Zn ions in the solution in the final stage (30–45 min) (see Fig. 3).

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Fig. 3

Effect of contact time, pH and Adsorbent dosage on removal of zinc.

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3.3 Effect of the pH

The adsorption capacity is, similarly, affected by pH due to the ability of hydrogen ions to change the adsorbent surface properties (Liu et al., 2017). Fig. 3 shows the effects of pH on the removal of Zn²⁺. The removal efficiency of Zn²⁺ sharply changed for all adsorbents when the pH was increased from 3 to 6 and however, the removal rate fluctuated or decrease with an increased in pH values (pH = 9.0). The maximum removal rate was obtained at pH 6.0.

3.4 Effect of adsorbent dose

Adsorbent dose effect on the removal of metal ions is given in Fig. 3. The removal rate of Zn²⁺ increased significantly from 68% to 82% for Peanut due to the adsorbent dosage increase number of functional and active sites that resulted in removal efficiency. A similar trend is also valid for the peanut and almond (see Fig. 3). The adsorbent dose increase from 0.25 to 8.0 g increases the removal efficiency first and then continues steadily. It can be explained by the relatively more existing reaction and binding sites in the surface area at lower adsorbent doses. The adsorbent dosage was selected as 1.0 g for the further batch experiments.

3.5 Adsorption isotherm

Freundlich (1906), Langmuir (1918), Temkin and Pyzhev (1940), Dubinin and Radushkevich (1947) isotherm models applied data obtained from the batch experiment, performed with altering initial Zn²⁺ concentrations ranging from 5 to 100 mg/L, to express the interactions. Isotherm linearized form of equations, parameters, and correlation coefficients is given in Table 1.

3.5.2

3.5.2 Langmuir isotherm;

The Langmuir constant (RL) gives information about the affinity of the sorbent for the binding ions. If RL > 1, the adsorption is undesirable; RL = 1, it is linear; 0 < RL < 1 it is desirable; RL = 0, it is irreversible (Langmuir, 1918). Values of 1/n for adsorption on the shells were calculated as 0.912 for pistachio, 0.988 for peanut, and 0.943 for almond. These values confirmed that desirable adsorption occurs for the removal of metal ions by the organic adsorbents.

Fig. 4 presents the comparison of the experimental values,i and the predicted amount of equilibrium for pistachio, peanut and almond shell. As demonstrated in Fig. 4, the data calculated values by Langmuir isotherm are close to the experimental data and the best isotherm for predicting the amount of Zn²⁺ adsorbed on the shells at equilibrium. Furthermore, the values of ARE, NSD, and MPSD error analysis are well fit to Langmuir isotherms provides a better model for the reduction of Zn²⁺ (see Table 1). The correlation coefficient (R²), however, shown that Temkin and Dubinin–Radushkevich models application for three adsorbents in this study is limited.

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Fig. 4

The predicted amount of adsorbents at equilibrium by different isotherm models and the experimental values.

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3.6 Kinetic studies

To analyse the adsorption process, diffusion rate and mechanism of Zn²⁺ the Elovich (Kayranli, 2011), Lagergren pseudo-first-order (Lagergren, 1898), and the pseudo-second order model (Ho and McKay, 2003), and the intra-particle diffusion model (Weber and Morris, 1963) were applied, and the linearized equations are given in Table 2. The coefficients (R²) of Zn²⁺ on the shells were calculated>0.99 for pseudo-second order. So, the pseudo-second order is well described in comparison to the pseudo first order in the adsorption process of Zn²⁺. Previous researchers (Lee and Choi, 2018) pointed out that pseudo-second order is more applicable than pseudo-first order to analyse the sorption rate of most sorbents in the aqueous medium. Similar results were found to remove Zn²⁺ by using shells and our results are in line with previous studies.

As seen in Fig. 5, the intra-particle diffusion plot can be separate a few linear regions, and the results demonstrated that not only intra-particle diffusion is the rate-limiting mechanism in the process, but also diffusion played an important role. The adsorption process was governed by more than one mechanism such as external mass transfer and internal particle diffusion.

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Fig. 5

Intra-particle diffusion plots of the pistachio, peanut, and almond for zinc.

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3.7 Removal mechanism of zinc

Heavy metals and functional groups interaction is complex and affected by adsorbent properties, porous structure, surface area, and functional groups, pH of the solution, metals chemistry in solution, binding characteristics that affects adsorption behaviours. The heavy metals adsorption process is mostly carried out by mechanism of ion exchange, electrostatic interaction, complex formation, surface complexation, physical adsorption, and/or precipitation (Kaur et al., 2020). Each mechanism specific role depends on functional groups of organic adsorbent, ionization of metals, and aqueous environment (Neris et al., 2019a). The main constituents of the three used organic residuals are lignin, cellulose, and hemicellulose, and also other components are, lipids, proteins, simple sugars, and ash, having a different ratio. Cellulose consists of 49.39% oxygen, 44.44% carbon, and 6.17% hydrogen with having a linear chain. There are many active sites on/in the shells, such as –COOH, –OH, –CH₃, –NO₂, –CH₂, –CH, amino acids, and so on, involving in the heavy metal removal process.

FTIR spectra of the shell at 10-minute intervals during Zn^{2 +} adsorption showed that functional groups of hydroxyl, carbonyl/carboxyl play important roles in the adsorption of heavy metals, and zinc adsorption by the shells increased over time. This adsorption resulted in changing the peaks and transmittances (see Table 3).

The spectroscopic analysis of the pistachio shell during the removal process demonstrated the peak transmittance shifted from 87.0 to 80.0 % (3276 cm⁻¹) for hydroxyl groups, and 94.0 to 87.0% for the peak of 2056 cm⁻¹ of alkanes, aldehydes, and carboxylic groups (C–H); 1722 cm⁻¹ assigned for aromatic C–C transmittance decrease 6.0%; 1148 cm⁻¹ assigned for C=O esther and carboxyl groups transmittance altered from 93.0 to 87.5%. The band at 3331 cm⁻¹ is indicating a number amount of hydroxyl (–OH) groups is produced from lignin, cellulose, hemicellulose, the transmittance decreased 11.0% for the almond shell. The peak near 2918 cm⁻¹ is the stretching vibration of C–H in alkanes, aldehydes and carboxylic acid, and changed to 16.5% % end of the process. Furthermore, the peak at 3272 cm⁻¹ refers to the hydroxyl groups (–OH) transmittance changed from 84.0 to 79% (30 min) for the peanut shell. It is most likely that surface adsorption through their complexation with the phenolic –OH group occurs. The bands at 1728–1606 cm⁻¹ for peanut were linked with the aromatic carbonyl/carboxyl C=O and the aromatic C=C stretching modes, and changes of these peaks after adsorption started surface complexation of Zn²⁺ by delocalized electrons. The peak near 1728 of transmittance changed 9.0% (30 min), is the vibration of C=O in aldehydes and ketones for almond. Similarly, the peaks at around 1597 and 1504 cm⁻¹ were assigned to C–O vibrations of hydroxyl groups or C–H stretching vibrations resulted from cellulose, hemicellulose and lignin and that of transmittance shifted 11.5% and 16.5 %, respectively. As seen in Table 3, the transmittance shifts informed that the bond –OH groups, C=O stretching, secondary amino group, carboxyl group –C–C– functional group were mostly taken part in the adsorption process. The –OH and –COOH groups were involved in the adsorption process due to C=O and –OH functional groups changed after zinc adsorption. These changes could be explained by the ion-exchange mechanism between adsorbent and adsorbate. The actives groups can cooperate with ions in many ways, as shown in Fig. 6. it can be concluded that the electrostatic interaction, ion exchange, diffusion, formation of complex, and Zn ions sorption by surface functional groups are the mechanism of the metal ions removal process.

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Fig. 6

Possible adsorption mechanisms of Zn^+2.

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3.8 Electrostatic interaction

The electrostatic interaction is created as a result of divalent metals and negatively charged functional groups on the adsorbent. However, this happens secondary and is very weak. The aqueous pH, and point of zero charges of the adsorbent are key for the frequency of electrostatic interaction(Yang et al., 2019). Therefore, the carboxyl groups were dissociated and associated with the Zn²⁺ ions due to the working pH value is 6.0. Three adsorbent shell is represented by S, and the protonation equilibria for the nitro, –NO₂ and the hydroxyl of C-6, –OH is as follows; S-O-NO₂ + H⁺→HO–S–NO₂(1) H_-1S + H → S S-HO-NO₂ + H⁺→ O–S–NO₃⁺ H₂O S + H → HS

3.9 Ion-exchange

The other main heavy metal removal process is that ion exchange takes place with the availability of carboxyl and hydroxyl functional groups include oxygen. The functional group chemistry and metal ion size are critical for process efficiency (Yang et al., 2019). Specifically, an acidic functional group plays a critical role in the removal of heavy metals by organic adsorbents. The zinc removal rate increased at pH 6.0 due to negatively adsorption surface increased. pH was adjusted by using NH₄OH in this study, resulting in hydroxide to form the Zn(HO)₂ salt. Based on the results, one of the adsorption mechanisms is cation exchange due to removal efficiency affected by pH (Ali et al., 2016). The ion exchange process is most likely defined by the following equations: RCOOH + NH₄OH → RCOONH₄ + H₂O, 2RCOONH₄ + ZnCl₂ → 2RCOOZn + NH₄Cl S-OH + Zn²⁺ → S-O-Zn⁺ +2H⁺ S-NO₂ + Zn²⁺ → S-NO-Zn⁺ +H₂O⁺ S-COOH + Zn²⁺ → S-COO-Zn⁺ +2H⁺

3.10 Surface complexations

Surface complexations occur with multi atom structures and metal-functional group interaction and important processes in adsorption. The carboxyl/carbonyl functional groups bind heavy metals, creating a complexation(Neris et al., 2019b). (Ali et al., 2016) pointed out that chemical adsorption may be the rate controlling step due to forming chemical bonds with exchange or sharing of electrons between sorbent and sorbate in process. The complex species associated with equilibrium can be defined by the following equations; S + Zn²⁺ →SZn²⁺ Zn²⁺ +S + H → SHZn²⁺ Zn²⁺+S + OH → Zn²⁺SOH

3.11 Diffusion

Fernández-López et al.(Fernández-López et al., 2019) pointed out that some information relating to the adsorbent surface, chemical/physical reaction, and diffusion, the relevant proper reaction rate is described by the sorption kinetic models. The adsorption-complexation interactions through electron exchange or sharing are the main sorption processes.

Therefore, an intra-particle diffusion model was applied to define the adsorption kinetics due to the porous structure of the shells. The first plot refers to the external surface adsorption in the intra-particle diffusion model. The First stage is the fastest adsorption process due to the presents of unbinding sites. The second part, the gradual adsorption stage, is defined with intra-particle diffusion of the metal ions through the pores of shell particles. The final equilibrium stage represents the intra-particle or both film and intra-particle diffusion due to the low metal ions remain in the solution. During the adsorption of Zn²⁺ onto the shells, sequencing steps take place and are represented in Fig. 6.

3.12 Use of end-product as a soil conditioner

Cultivation trends, currently, focus on using bio-organic fertilizer/conditioner instead of chemical fertilizers due to high costs, contamination, and inappropriate application causing soil quality degradation (Omoni et al., 2020). The world trend is to protect soil biodiversity while producing quality crops for sustainability. Organic fertilizers, produced organic wastes, are cheap nutrient sources and enhance crop production in low-input agriculture. Furthermore, organic waste increases soil organic carbon and microbial activity that helps provides nutrients and recycling them for plant growth (Hafez et al., 2021).

Zinc is an essential micronutrient and affects most of the physiological processes (Broadley et al., 2007). The presence of major nutrients concentrations and the microelements forms for plant usage is affected by soil pH, affecting also total Zn concentration and activity in soil solution, and high pH removes the total Zn concentration and activity (Bonten et al., 2008). Calcareous soil lacks nutrients, especially N, P, micro-nutrients, and soil organic matter, resulted in weak soil–plant productivity. Bio-organic conditioners decrease nutrient losses and enhance plant growth in calcareous soil (Hafez et al., 2021). Fresh shells contain organic materials, nutrients and mineral and then holding zinc with functional groups make it valuable soil conditioner/ amendments. The ideal soil pH for plant growth is between 6.0 and 8.0 called neutral soil. The end-product can also be used for reducing the pH of the alkaline and high alkaline soil (pH > 8).