**Biomass Surface Area (m2/g) Total Pore Volume 3. Results and Discussion**

nomenon.

residues.

#### Pine sawdust 1.1 0.003 9.4 *3.1. Biomass Characterization*

Sunflower seed hulls 0.7 0.0009 4.9 Corn residues mix 1.5 0.006 14.9 The phenomena that occur in an adsorbent are related to its specific surface and, therefore, to the total volume of pores and their dimensions, that influence the interaction with the adsorbate and the obtained adsorption efficiency. Table 1 shows the results obtained from the BET analysis for pine sawdust, sunflower seed hulls and corn residues mix. All biomasses showed the presence of mesopores and the surface area values are in agreement with those reported in the literature for adsorbents of lignocellulosic origin [34,39]. Corn biomass presented a higher surface area, total pore volume, and mean pore size comparing with the other two biomass residues (pine sawdust and sunflower seed hulls). Bilal et al. [7] reported that the adsorption of contaminants increases with the increase in the surface area of the adsorbent, since the adsorption process is a surface phenomenon.

**(cm3/g) Mean Pore Size (nm)** 


SEM images allow to obtain information about the morphological characteristics (tex-

**Table 1.** BET analysis results of surface area, total pore volume and mean pore size for biomass residues.

SEM images allow to obtain information about the morphological characteristics (texture, topography and surface characteristics) of the adsorbents. So, the SEM images of the three studied agro-industrial wastes are presented in Figure 3. Biomass analyzed particles showed an elongated shape and a fibrous microstructure. An irregular and rough surface with cavities can be observed in all cases, which forms a network of holes and fibers. These characteristics can facilitate the adsorption of heavy metals [40]. No appreciable changes were detected in the morphology of the adsorbents related to the interaction with metal ions, as reported by Zhang et al. [33], after the adsorption of heavy metals. The combination of SEM with EDS detector and analyzer system allowed to obtain the distribution of heavy metals on the biomasses after adsorption by mapping. As shown in Figure 4, the distribution, and therefore adsorption, of nickel, zinc and cadmium in the adsorbents was across the entire surface. ture, topography and surface characteristics) of the adsorbents. So, the SEM images of the three studied agro-industrial wastes are presented in Figure 3. Biomass analyzed particles showed an elongated shape and a fibrous microstructure. An irregular and rough surface with cavities can be observed in all cases, which forms a network of holes and fibers. These characteristics can facilitate the adsorption of heavy metals [40]. No appreciable changes were detected in the morphology of the adsorbents related to the interaction with metal ions, as reported by Zhang et al. [33], after the adsorption of heavy metals. The combination of SEM with EDS detector and analyzer system allowed to obtain the distribution of heavy metals on the biomasses after adsorption by mapping. As shown in Figure 4, the distribution, and therefore adsorption, of nickel, zinc and cadmium in the adsorbents was across the entire surface.

**Figure 3.** SEM images of: (**A**) pine sawdust, (**B**) sunflower seed hulls, (**C**) corn residues mix. **Figure 3.** SEM images of: (**A**) pine sawdust, (**B**) sunflower seed hulls, (**C**) corn residues mix.

tively.

**Figure 4.** Elemental distribution obtained by SEM-EDS by mapping analysis for (**A**) pine sawdust, (**B**) sunflower seed hulls, (**C**) corn residues mix, after adsorption of Cd(II), Zn(II) and Ni(II), respec-**Figure 4.** Elemental distribution obtained by SEM-EDS by mapping analysis for (**A**) pine sawdust, (**B**) sunflower seed hulls, (**C**) corn residues mix, after adsorption of Cd(II), Zn(II) and Ni(II), respectively.

ATR-FTIR made it possible to determine the presence of functional groups in biomass responsible for the metal adsorption mechanism, for example, either by electrostatic forces or complexation. ATR-FTIR spectra for the biomass residues studied here are shown in Figure 5. The large number of IR bands was associated with the typical complex nature of agro-industrial biomasses [41–43]. The assignment of the main IR bands at the respective approximate wavelengths are summarized in Table 2. The great similarity be-ATR-FTIR made it possible to determine the presence of functional groups in biomass responsible for the metal adsorption mechanism, for example, either by electrostatic forces or complexation. ATR-FTIR spectra for the biomass residues studied here are shown in Figure 5. The large number of IR bands was associated with the typical complex nature of agro-industrial biomasses [41–43]. The assignment of the main IR bands at the respective approximate wavelengths are summarized in Table 2. The great similarity between the ATR-FTIR spectra of sawdust, sunflower and corn was due to the fact that the composition of these three biomasses is based on cellulose and lignin.

tween the ATR-FTIR spectra of sawdust, sunflower and corn was due to the fact that the composition of these three biomasses is based on cellulose and lignin. The presence of numerous functional groups in biomass facilitates the adsorption of heavy metals [7]. A comparison of the ATR-FTIR spectra of the biomasses before and after the adsorption of the heavy metals is also shown in Figure 5, being both spectra were very similar in each biomass case. However, slight differences were observed, such as a shift of the band at 1603–1624 cm**−**1 in the three biomasses, and shift of the band at 1224–1238 cm**−**<sup>1</sup> in the pine sawdust and corn residues, after the contact with heavy metals. These results may be indicative that carboxyl, alcohol, phenol, amide, and other functional groups The presence of numerous functional groups in biomass facilitates the adsorption of heavy metals [7]. A comparison of the ATR-FTIR spectra of the biomasses before and after the adsorption of the heavy metals is also shown in Figure 5, being both spectra were very similar in each biomass case. However, slight differences were observed, such as a shift of the band at 1603–1624 cm−<sup>1</sup> in the three biomasses, and shift of the band at 1224–1238 cm−<sup>1</sup> in the pine sawdust and corn residues, after the contact with heavy metals. These results may be indicative that carboxyl, alcohol, phenol, amide, and other functional groups could provide possible adsorption sites for the retention of the studied heavy metals, and were similar to those found in previous works in the literature [44,45].

could provide possible adsorption sites for the retention of the studied heavy metals, and

were similar to those found in previous works in the literature [44,45].

**Figure 5.** ATR-FTIR spectra of: (**A**) pine sawdust, (**B**) sunflower seed hulls, (**C**) corn residues mix, before and after the adsorption process. **Figure 5.** ATR-FTIR spectra of: (**A**) pine sawdust, (**B**) sunflower seed hulls, (**C**) corn residues mix, before and after the adsorption process.


**Table 2.** Assignment of the main bands obtained by ATR-FTIR for biomass residues.

The XRF analysis for the biomasses before and after the adsorption of heavy metals is presented in Figure 6. The Cr peaks come from the tube used as the source of the equipment (anode). Signals corresponding to Cl, K, Ca, Mn and Fe were observed, although the intensities varied according to the residue. The presence in biomasses of Ni, Zn and Cd was observed after adsorption (Cd signals were detected in the Ca and K energy zone), associated with the decrease in the intensities of elements such as Ca and K, mainly. *Water* **2022**, *14*, x FOR PEER REVIEW 10 of 20

**Figure 6.** XRF of: (**A**) biomasses before the adsorption process, and after adsorption process with (**B**) pine sawdust, (**C**) sunflower seed hulls, (**D**) corn with adsorbed heavy metals. **Figure 6.** XRF of: (**A**) biomasses before the adsorption process, and after adsorption process with (**B**) pine sawdust, (**C**) sunflower seed hulls, (**D**) corn with adsorbed heavy metals.

Biomasses of plant origin are mainly composed of lignin and cellulose, as mentioned above, together with hemicellulose, low molecular weight compounds, lipids, proteins, starch, water, etc. [7]. The DTA-TGA profiles were obtained for the three biomasses here selected, and provided a description of the thermal behavior and an estimated percentage composition of biomasses, which was in agreement with the literature [47,48]. As seen in Figure 8, TGA analysis, the total weight loss was 96% for pine sawdust, 97% for sunflower

**Figure 7.** XRF of pine ashes, sunflower ashes and corn ashes.

The percentage of ash obtained was 0.2%, 2.0% and 10.2% for pine sawdust, sunflower seed hulls and corn residues mix, respectively. The XRD patterns of the biomasses (Figure S1 of the supplementary material) evidenced the presence of a significant amount of amorphous phase, in agreement with the mentioned results. The XRF equipment used does not allow the measurement of elements lighter than Na, and H, C and O are part of hemicellulose, cellulose and lignin as the main components of the biomasses. For that reason, the composition of the corresponding ashes was also analyzed by XRF (results collected in Figure 7). Differences in mineral content and composition were observed. Probably potassium, calcium, magnesium and phosphorus are involved in the adsorption of heavy metals through ion exchange mechanism, as reported previously [46]. **Figure 6.** XRF of: (**A**) biomasses before the adsorption process, and after adsorption process with (**B**) pine sawdust, (**C**) sunflower seed hulls, (**D**) corn with adsorbed heavy metals.

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**Figure 7.** XRF of pine ashes, sunflower ashes and corn ashes. **Figure 7.** XRF of pine ashes, sunflower ashes and corn ashes.

Biomasses of plant origin are mainly composed of lignin and cellulose, as mentioned above, together with hemicellulose, low molecular weight compounds, lipids, proteins, starch, water, etc. [7]. The DTA-TGA profiles were obtained for the three biomasses here selected, and provided a description of the thermal behavior and an estimated percentage composition of biomasses, which was in agreement with the literature [47,48]. As seen in Figure 8, TGA analysis, the total weight loss was 96% for pine sawdust, 97% for sunflower Biomasses of plant origin are mainly composed of lignin and cellulose, as mentioned above, together with hemicellulose, low molecular weight compounds, lipids, proteins, starch, water, etc. [7]. The DTA-TGA profiles were obtained for the three biomasses here selected, and provided a description of the thermal behavior and an estimated percentage composition of biomasses, which was in agreement with the literature [47,48]. As seen in Figure 8, TGA analysis, the total weight loss was 96% for pine sawdust, 97% for sunflower seed hulls, and 86% for corn residues mix, and was divided into three stages. The first weight loss stage (up to 230 ◦C) was 7% for pine sawdust, 12% for sunflower seed shells and 10% for corn residues mix. This stage was related to the loss of moisture, which was characterized by an endothermic peak at 52 ◦C in pine sawdust and at 60 ◦C in sunflower seed hulls. The degradation of low molecular weight compounds was identified with an exothermic peak at 263 ◦C, and was observed in sawdust. The second weight loss stage was 48% for sawdust (up to 311 ◦C), 56% for sunflower (up to 297 ◦C) and 50% for corn (up to 338 ◦C). This stage could be related to the degradation of hemicellulose and pectin into volatile compounds of lower molecular weight. Finally, the third weight loss stage was 41% (up to 500 ◦C), 29% (up to 460 ◦C) and 26% (up to 508 ◦C) for biomasses of pine sawdust, sunflower seed hulls and corn, respectively, and it could be related to the degradation of cellulose and lignin into CO2, H2O and ashes. From the TGA analysis, the final residue corresponds to the mineral content and was higher for corn than for sawdust and sunflower, in accordance with the results obtained following the guidelines of the ASTM E1755-01 standard. The two large exothermic peaks in the three DTA curves were assigned to the decomposition of the biopolymers present in the biomass: such as hemicellulose, cellulose and lignin. Since these biopolymers are closely related in the biomass structure, the thermal degradation of each biopolymer cannot be clearly defined independently, probably being

hemicellulose responsible of the first peak and cellulose and lignin together of the second peak [30]. *Water* **2022**, *14*, x FOR PEER REVIEW 12 of 20

**Figure 8.** DTA-TGA of: (**A**) pine sawdust, (**B**) sunflower seed hulls, (**C**) corn residues mix. **Figure 8.** DTA-TGA of: (**A**) pine sawdust, (**B**) sunflower seed hulls, (**C**) corn residues mix.

#### *3.2. Adsorption Process Characterization* Qu et al. [53], smaller ions are more hydrated than larger ones, which could hinder adsorption.

*3.2. Adsorption Process Characterization* 

sults obtained are shown in Figure 9.

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Biomasses of pine sawdust, sunflower seed hulls and corn residues mix were evaluated as adsorbents of mono-metal aqueous solutions of Ni(II), Zn(II) and Cd(II). The results obtained are shown in Figure 9. The higher surface area, pore volume and mineral fraction in corn residues could have positively contributed to the adsorption of heavy metals. However, the differences in the adsorption results are not too significant between the three biomasses.

Biomasses of pine sawdust, sunflower seed hulls and corn residues mix were evaluated as adsorbents of mono-metal aqueous solutions of Ni(II), Zn(II) and Cd(II). The re-

According to the results of adsorption percentage (A%) and adsorption capacity (qe) obtained, Ni(II) presented a lower adsorption, compared to Zn(II) and Cd(II), in all the biomasses studied. The adsorption follows the order: Ni(II) < Zn(II) < Cd(II), as shown in Figure 9, for sawdust, sunflower and corn, as it was also reported for other waste of lignocellulosic origin, such as coffee residues, rice husks, cocoa husks, and paper manufacturing wastes [49,50]. This behavior is related to the different characteristics and affinity of the metal ions for adsorbent adsorption sites [51]. Comparing the values of the hydration energies (Ni(II): −2106 kJ/mol, Zn(II): −2044 kJ/mol and Cd(II): −1806 kJ/mol), related to hydrolysis of metal ions, the nickel ion has a higher hydration energy than the zinc and cadmium ions and, therefore, it is less easy to lose its water molecules from its coordination sphere, which would prevent it from being adsorbed by the adsorbent through complexation or ion-exchange mechanisms. According to Mahmood-ul-Hassan et al. [52] and

**Figure 9.** Comparison of the adsorption of mono-metal solutions of Ni(II), Zn(II) and Cd(II) on pine sawdust, sunflower seed hulls and corn residues mix. **Figure 9.** Comparison of the adsorption of mono-metal solutions of Ni(II), Zn(II) and Cd(II) on pine sawdust, sunflower seed hulls and corn residues mix.

The obtained results are of the same order as results reported in the literature for batch adsorption experiments of Ni(II), Zn(II) and Cd(II) using sawdust, sunflower and corn residues (Table S1, supplementary material). However, the differences between the results of adsorption percentage (A%) are not only due to the characteristics of the biomass adsorbent but were also due to the concentration of contaminant, dosage of the adsorbent, pH of the solution, temperature, contact time, among others, that are factors that can affect the adsorption process [7]. Some of these factors were evaluated by the authors in previous work on the adsorption of heavy metals on adsorbent materials of plant origin [26,46,54,55]. The determination of the adsorption of heavy metals of a mixing metal solutions represents a closer situation to a real effluent. The competition between the metal ions for the adsorption sites occurs due to the saturation of the adsorption sites of the adsorbent whose dosage remains fixed to that of the individual systems [7]. Figure 10 compares the results of A% for the adsorption of mono-metal aqueous solutions of Ni(II), Zn(II) and Cd(II), and the multi-metal aqueous solution made up of heavy metals mentioned above with a con-According to the results of adsorption percentage (A%) and adsorption capacity (qe) obtained, Ni(II) presented a lower adsorption, compared to Zn(II) and Cd(II), in all the biomasses studied. The adsorption follows the order: Ni(II) < Zn(II) < Cd(II), as shown in Figure 9, for sawdust, sunflower and corn, as it was also reported for other waste of lignocellulosic origin, such as coffee residues, rice husks, cocoa husks, and paper manufacturing wastes [49,50]. This behavior is related to the different characteristics and affinity of the metal ions for adsorbent adsorption sites [51]. Comparing the values of the hydration energies (Ni(II): −2106 kJ/mol, Zn(II): −2044 kJ/mol and Cd(II): −1806 kJ/mol), related to hydrolysis of metal ions, the nickel ion has a higher hydration energy than the zinc and cadmium ions and, therefore, it is less easy to lose its water molecules from its coordination sphere, which would prevent it from being adsorbed by the adsorbent through complexation or ion-exchange mechanisms. According to Mahmoodul-Hassan et al. [52] and Qu et al. [53], smaller ions are more hydrated than larger ones, which could hinder adsorption.

centration of 0.18 mmo/L of each of them. At this initial concentration, the results of A% The higher surface area, pore volume and mineral fraction in corn residues could have positively contributed to the adsorption of heavy metals. However, the differences in the adsorption results are not too significant between the three biomasses.

The obtained results are of the same order as results reported in the literature for batch adsorption experiments of Ni(II), Zn(II) and Cd(II) using sawdust, sunflower and corn residues (Table S1, supplementary material). However, the differences between the results of adsorption percentage (A%) are not only due to the characteristics of the biomass adsorbent but were also due to the concentration of contaminant, dosage of the adsorbent, pH of the solution, temperature, contact time, among others, that are factors that can affect the adsorption process [7]. Some of these factors were evaluated by the authors in previous work on the adsorption of heavy metals on adsorbent materials of plant origin [26,46,54,55].

The determination of the adsorption of heavy metals of a mixing metal solutions represents a closer situation to a real effluent. The competition between the metal ions for the adsorption sites occurs due to the saturation of the adsorption sites of the adsorbent whose dosage remains fixed to that of the individual systems [7]. Figure 10 compares the results of A% for the adsorption of mono-metal aqueous solutions of Ni(II), Zn(II) and Cd(II), and the multi-metal aqueous solution made up of heavy metals mentioned above with a concentration of 0.18 mmo/L of each of them. At this initial concentration, the results of A% for each of the heavy metals were similar when the adsorption was carried out separately and when it was carried out within the mixture, on sunflower seed

hulls and corn residues mix. However, the adsorption of heavy metals in pine sawdust was lower for the multi-metal aqueous solution than for each metal separately, being the nickel ion the most affected by the competition with the other two heavy metals for the adsorption sites of the adsorbent, as expected (as Ni was the less adsorbed, as seen in Figure 9). Zhao et al. [46], also reported a lower performance of sawdust as an adsorbent when comparing the results of A% obtained for the adsorption of a mixture consisting of Cr(III), Cd(II), Cu(II) and Pb(II), on poplar sawdust and two other agricultural residues. mix. However, the adsorption of heavy metals in pine sawdust was lower for the multimetal aqueous solution than for each metal separately, being the nickel ion the most affected by the competition with the other two heavy metals for the adsorption sites of the adsorbent, as expected (as Ni was the less adsorbed, as seen in Figure 9). Zhao et al. [46], also reported a lower performance of sawdust as an adsorbent when comparing the results of A% obtained for the adsorption of a mixture consisting of Cr(III), Cd(II), Cu(II) and Pb(II), on poplar sawdust and two other agricultural residues.

for each of the heavy metals were similar when the adsorption was carried out separately and when it was carried out within the mixture, on sunflower seed hulls and corn residues

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#### *3.3. Spent Adsorbent Disposal 3.3. Spent Adsorbent Disposal*

There is limited information available in the literature on the toxic effects of spent adsorbents, and their regeneration decreases their performance and generate new contaminant materials. The safe disposal of used and/or spent adsorbents is nowadays raising as a need to consider it for a more sustainable processes that can help to preserve the environment [56]. Based on the previous experience of the authors [54,55], the local production of ceramics for bricks construction is presented as a possible alternative for the safe disposal of spent adsorbents that would contribute to the real applicability of them as metal adsorbents. There is limited information available in the literature on the toxic effects of spent adsorbents, and their regeneration decreases their performance and generate new contaminant materials. The safe disposal of used and/or spent adsorbents is nowadays raising as a need to consider it for a more sustainable processes that can help to preserve the environment [56]. Based on the previous experience of the authors [54,55], the local production of ceramics for bricks construction is presented as a possible alternative for the safe disposal of spent adsorbents that would contribute to the real applicability of them as metal adsorbents.

In Figure 11, the adsorption percentages obtained from the experiments using 0.1 g of adsorbent and 1.8 <sup>×</sup> <sup>10</sup>−<sup>6</sup> moles of each of the heavy metals in the multi-metal system are compared with those results obtained by increasing the residue mass by 20 times to 2 g and moles of adsorbate to 3.6 <sup>×</sup> <sup>10</sup>−<sup>5</sup> moles. As can be seen, by maintaining the adsorbent/adsorbate ratio constant, the adsorption percentage remained constant. These results were considered in the preparation of clay ceramics with 20% by volume of contaminated biomass with respect to the volume of clay. are compared with those results obtained by increasing the residue mass by 20 times to 2 g and moles of adsorbate to 3.6 × 10**−**5 moles. As can be seen, by maintaining the adsorbent/adsorbate ratio constant, the adsorption percentage remained constant. These results were considered in the preparation of clay ceramics with 20% by volume of contaminated biomass with respect to the volume of clay.

In Figure 11, the adsorption percentages obtained from the experiments using 0.1 g of adsorbent and 1.8 × 10**−**6 moles of each of the heavy metals in the multi-metal system

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**Figure 11.** Comparison of the percentage of adsorption (A%) when increasing 20 times the mass of adsorbent and moles of adsorbate in the multi-metal system of heavy metals for: (**A**) pine sawdust, (**B**) sunflower seed hulls, (**C**) corn residues mix. **Figure 11.** Comparison of the percentage of adsorption (A%) when increasing 20 times the mass of adsorbent and moles of adsorbate in the multi-metal system of heavy metals for: (**A**) pine sawdust, (**B**) sunflower seed hulls, (**C**) corn residues mix.

The macroscopic appearance of the clay ceramics is shown in Figure 12. All the samples presented a reddish color due to the Fe content of the natural clay and a porous surface according to the TGA and DTA results of the included lignocellulosic residues. As can be seen in Figure 8, at the ceramic firing temperature (950 °C), the added biomass burned out creating pores and releasing gases in the clay ceramics matrix. The macroscopic appearance of the clay ceramics is shown in Figure 12. All the samples presented a reddish color due to the Fe content of the natural clay and a porous surface according to the TGA and DTA results of the included lignocellulosic residues. As can be seen in Figure 8, at the ceramic firing temperature (950 ◦C), the added biomass burned out creating pores and releasing gases in the clay ceramics matrix.

Leaching tests based on EPA Method 1311 were performed to determine the possible leaching levels of Ni(II), Zn(II) and Cd(II) from the clay ceramics prepared with the addition of each of the spent adsorbents. Heavy metal concentrations were not detected in the TCLP extracts of the ceramic matrices because they were below the detection limits of the equipment used (Ni(II) < 0.05 mg/L, Zn(II) < 0.02 mg/L and Cd(II) < 0.05 mg/L, by AAS). For this reason, they were lower than the permissible limits of Argentina (nickel 5 mg/L and cadmium 1 mg/L, zinc not reported) [57].

**Figure 12.** Macroscopic appearance of clay ceramics including spent biomass of: (**A**) pine sawdust, (**B**) sunflower seed hulls, (**C**) corn residues mix, and comparison with a sample without residue addition. **Figure 12.** Macroscopic appearance of clay ceramics including spent biomass of: (**A**) pine sawdust, (**B**) sunflower seed hulls, (**C**) corn residues mix, and comparison with a sample withoutresidue addition.

Leaching tests based on EPA Method 1311 were performed to determine the possible leaching levels of Ni(II), Zn(II) and Cd(II) from the clay ceramics prepared with the addition of each of the spent adsorbents. Heavy metal concentrations were not detected in the TCLP extracts of the ceramic matrices because they were below the detection limits of the equipment used (Ni(II) < 0.05 mg/L, Zn(II) < 0.02 mg/L and Cd(II) < 0.05 mg/L, by AAS). For this reason, they were lower than the permissible limits of Argentina (nickel 5 mg/L and cadmium 1 mg/L, zinc not reported) [57]. Table 3 shows the retention efficiency calculated for each one clay ceramics matrices. It was calculated from the mass of each of the heavy metals added in the ceramic (included Table 3 shows the retention efficiency calculated for each one clay ceramics matrices. It was calculated from the mass of each of the heavy metals added in the ceramic (included in the spent adsorbent) and in the TCLP extract obtained for each tested ceramic. Based on these results, with heavy metal retentions above 88.5% in all cases, we can propose such clay ceramics prepared with added spent adsorbents with potential use in construction, and useful for the stabilization and immobilization of heavy metals together with the corresponding spent adsorbents. At firing temperatures in the followed leaching tests (EPA Method 1311), the organic residues can burn out and the heavy metals would be able to form stable phases with the clay minerals, which would decrease their bioavailability [58].

in the spent adsorbent) and in the TCLP extract obtained for each tested ceramic. Based on these results, with heavy metal retentions above 88.5% in all cases, we can propose such clay ceramics prepared with added spent adsorbents with potential use in construc-**Table 3.** Heavy metal retention efficiency for clay ceramics prepared from spent adsorbent with the mixture of heavy metals.


metals detected. This fact is important because in the leaching tests the clay ceramics were used crushed, but in practice the clay bricks will be used whole, so the leaching may be even lower, even there is still no legislation that imposes a test and limits on the leaching of heavy metals in construction materials [60]. **Table 3.** Heavy metal retention efficiency for clay ceramics prepared from spent adsorbent with the mixture of heavy metals. According to Mohajeran et al. [59], the particle size of the sample determines the contact surface with the leaching solution and therefore influences the concentration of heavy metals detected. This fact is important because in the leaching tests the clay ceramics were used crushed, but in practice the clay bricks will be used whole, so the leaching may be even lower, even there is still no legislation that imposes a test and limits on the leaching of heavy metals in construction materials [60].

tact surface with the leaching solution and therefore influences the concentration of heavy

#### **Clay Ceramics Retention Efficiency (%) 4. Conclusions**

**Ni(II) Zn(II) Cd(II)**  Pine sawdust >88.5 >98.2 >97.1 Sunflower seed hulls >95.9 >99.1 >98.5 Corn residues mix >93.4 >98.7 >97.9 One of the challenges of these times is the minimization of waste generated by agroindustrial activities and/or the reuse of this waste in applications that improve the quality of life. In this sense, considering that there is still no universal process to remove heavy metals from wastewater and effluents, adsorption from agroindustry residues is emerging as a simple, low-cost and efficient alternative.

Agro-industrial residues such as pine sawdust, sunflower seed hulls and corn residues mix, without any additional treatment, are characterized. These results are correlated with the performance of these materials as adsorbents of heavy metals such as Ni(II), Zn(II) and Cd(II). In addition, SEM-EDS and XRF confirmed the presence of these heavy metals in the residues after the adsorption process.

Batch adsorption experiments from aqueous mono-metal solutions of nickel, zinc and cadmium ions, with concentrations of 0.18 mmol/L, with all three biomass residues selected showed promising results, with adsorption percentages greater than 50%. Ni(II) presented the lowest adsorption percentages and adsorption capacities compared to Zn(II) and Cd(II), possibly due to the higher hydration energy that could hinder its accessibility to the adsorbent. At this concentration, in a multi-metal solution, the decrease in adsorption due to the competition of heavy metals for the limited adsorption sites of pine sawdust determined that it is necessary to study multi-component systems to evaluate the actual performance of the adsorption process in practice.

Sawdust, sunflower and corn residues could be used as an alternative to traditional synthetic materials to remove heavy metals from wastewater given their properties, low cost and availability. However, more research is needed for the scale-up and possible commercial application of these agro-industrial residues as adsorbents of toxic metals from industrial wastewater.

Furthermore, a solution to the safe disposal of such biomass adsorbents after the adsorption process (containing heavy metals as pollutants) was proposed in this research work. The stabilization of these spent adsorbents in clay ceramics with possible use in construction is presented as an alternative for the immobilization of Ni(II), Zn(II), Cd(II) and their mixture. The heavy metal leaching tests of the ceramic matrices prepared with added spent adsorbents confirmed an effective immobilization for all heavy metals, whose concentrations were found to be below the permissible limits. The clay ceramics showed retention efficiencies over 88.5%.

**Supplementary Materials:** The following supporting information can be downloaded at: https:// www.mdpi.com/article/10.3390/w14203298/s1, Figure S1: XRD patterns of pine sawdust, sunflower seed hulls, and corn residues mix; Table S1: Main results of literature studies about the adsorption of Ni(II), Zn(II) and Cd(II) on sawdust, sunflower and corn. References [44,52,61–67] are cited in the "supplementary materials".

**Author Contributions:** Conceptualization, C.P. and A.C. (Adrián Cristóbal); methodology, D.S., C.P. and A.C. (Adrián Cristóbal); validation, D.S., A.C. (Agustín Costas) and A.C. (Adrián Cristóbal); investigation, D.S. and A.C. (Adrián Cristóbal); resources, C.P., A.C. (Agustín Costas) and A.C. (Adrián Cristóbal); writing—original draft preparation, D.S., C.P. and A.C. (Adrián Cristóbal); writing—review and editing, D.S., C.P. and A.C. (Adrián Cristóbal); project administration, C.P. and A.C. (Adrián Cristóbal); funding acquisition, C.P. and A.C. (Adrián Cristóbal). All authors have read and agreed to the published version of the manuscript.

**Funding:** This research was funded by grants from Spanish research projects (CTM2015-65414- C2-1-R and AGL2015-70393-R), National Scientific and Technical Research Council (PIP 2021-2023 GI 11220200100739CO), National University of Mar del Plata (UNMdP 15/G577, 2020-2021) and H2020-MSCA-RISE-2014 Research Executive Agency (UE) (GA645024 (NANOREMOVAS)).

**Institutional Review Board Statement:** Not applicable.

**Informed Consent Statement:** Not applicable.

**Data Availability Statement:** Not applicable.

**Acknowledgments:** All the authors are grateful to the UAB Microscopy Service (*Servei de Microscòpia Electrònica* from UAB, Catalunya, Spain) for the SEM analysis and the *Centro Biotecnológico Fares Taie* (Mar del Plata, Argentina) for the AAS analysis of the TCLP extracts.

**Conflicts of Interest:** The authors declare no conflict of interest.
