Cu and As(V) Adsorption and Desorption on/from Different Soils and Bio-Adsorbents

Citation: Cela-Dablanca, R.; Barreiro, A.; Ferreira-Coelho, G.; Campillo-Cora, C.; Pérez-Rodríguez, P.; Arias-Estévez, M.; Núñez-Delgado, A.; Álvarez-Rodríguez, E.; Fernández-Sanjurjo, M.J. Cu and As(V) Adsorption and Desorption on/from Different Soils and Bio-Adsorbents. Materials 2022,15, 5023. https://doi.org/10.3390/ ma15145023 Academic Editor: Teofil Jesionowski Received: 2 June 2022 Accepted: 18 July 2022 Published: 19 July 2022 Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. Copyright: © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/). materials Article Cu and As(V) Adsorption and Desorption on/from Different Soils and Bio-Adsorbents Raquel Cela-Dablanca 1,* , Ana Barreiro 1, Gustavo Ferreira-Coelho 1, Claudia Campillo-Cora 2, Paula Pérez-Rodríguez 2, Manuel Arias-Estévez 2, Avelino Núñez-Delgado 1, Esperanza Álvarez-Rodríguez 1 and María J. Fernández-Sanjurjo 1 1Department of Soil Science and Agricultural Chemistry, Engineering Polytechnic School, University of Santiago de Compostela, 27002 Lugo, Spain; ana.barreir[email protected] (A.B.); [email protected] (G.F.-C.); [email protected] (A.N.-D.); esperanza.alvar[email protected] (E.Á.-R.); [email protected] (M.J.F.-S.) 2Soil Science and Agricultural Chemistry, Faculty of Sciences, University of Vigo, 32004 Ourense, Spain; [email protected] (C.C.-C.); [email protected] (P.P.-R.); [email protected] (M.A.-E.) *Correspondence: [email protected] Abstract: This research is concerned with the adsorption and desorption of Cu and As(V) on/from different soils and by-products. Both contaminants may reach soils by the spreading of manure/slurries, wastewater, sewage sludge, or pesticides, and also due to pollution caused by mining and industrial activities. Different crop soils were sampled in A Limia (AL) and Sarria (S) (Galicia, NW Spain). Three low-cost by-products were selected to evaluate their bio-adsorbent potential: pine bark, oak ash, and mussel shell. The adsorption/desorption studies were carried out by means of batch-type experiments, adding increasing and individual concentrations of Cu and As(V). The fit of the adsorption data to the Langmuir, Freundlich, and Temkin models was assessed, with good results in some cases, but with high estimation errors in others. Cu retention was higher in soils with high organic matter and/or pH, reaching almost 100%, while the desorption was less than 15%. The As(V) adsorption percentage clearly decreased for higher As doses, especially in S soils, from 60–100% to 10–40%. The As(V) desorption was closely related to soil acidity, being higher for soils with higher pH values (S soils), in which up to 66% of the As(V) previously adsorbed can be desorbed. The three by-products showed high Cu adsorption, especially oak ash, which adsorbed all the Cu added in a rather irreversible manner. Oak ash also adsorbed a high amount of As(V) (>80%) in a rather non-reversible way, while mussel shell adsorbed between 7 and 33% of the added As(V), and pine bark adsorbed less than 12%, with both by-products reaching 35% desorption. Based on the adsorption and desorption data, oak ash performed as an excellent adsorbent for both Cu and As(V), a fact favored by its high pH and the presence of non-crystalline minerals and different oxides and carbonates. Overall, the results of this research can be relevant when designing strategies to prevent Cu and As(V) pollution affecting soils, waterbodies, and plants, and therefore have repercussions on public health and the environment. Keywords: bio-adsorbents; heavy metals; soil pollution; release; retention 1. Introduction The increasing spreading of metals and metalloids included in the group of the socalled “heavy metals” into the soil through fertilizers, manure/slurry, sewage sludge, irrigation with wastewater, pesticides, or mining and industrial activities has given rise to concerns about their impact on the environment in general and human health in particular [ 1 – 4 ]. These substances enter various environmental compartments (soil, water, and air), and affect different living beings (microbial, plant, and animal communities) and may have adverse effects on individual biological receptors and populations [ 5 ]. Their toxicity is affected by the difficulties of organisms to achieve their excretion, with a tendency to Materials 2022,15, 5023. https://doi.org/10.3390/ma15145023 https://www.mdpi.com/journal/materials Materials 2022,15, 5023 2 of 21 bio-accumulate, and, even in cases where they do not have high concentrations in specific environments, they can reach harmful levels after passing through the food chain [6,7]. Arsenic is naturally present in certain minerals, but its presence as a pollutant in the environment can also be caused by certain human activities, such as mining, use of fossil fuels, pesticides, and herbicides. It is a semimetal or metalloid that can occur in inorganic form, with the As(III) species being the most frequent in reducing conditions, and As(V) in well-aerated media, while the organic forms (with As included in organic molecules) are quantitatively less important [ 8 ]. This element causes special concern due to its high toxicity, and it can be mobilized in the most frequent groundwater pH values, thus threatening drinking water resources [ 9 ]. It has associated chronic toxic effects, increasing the risks of developing cancers affecting the skin, lung, kidney, and liver [ 10 , 11 ]. Details regarding the effects of arsenic on toxicity and human health have been extensively documented in previous papers [12–16]. As regards Cu, it is an essential micronutrient for human beings and for plant development, but it is toxic when present at high concentrations [ 17 , 18 ]. It is less mobile than As, but high Cu concentrations can alter cell division in some plants, affect microbial activity, microorganism diversity, and soil ecosystem services [ 19 – 22 ], and cause damage to detritivore populations [ 23 ]. As regards the effects of Cu on human health, extensive reviews have been carried out in previous publications [24–27]. Soils can act as a sink for these pollutants and reduce their toxicity through adsorption, precipitation, or occlusion processes, mainly affected by soil organic matter, low crystallinity minerals, and acid–base and redox conditions [28,29]. The retention capacity of the soil can be an important factor in mitigating the toxic effects of these metals/metalloids, but, in the long term, soil adsorbent surfaces could be saturated, increasing the risk of passage to plants, water, and the food chain. To minimize this problem, different remediation strategies have been developed, mainly aimed at acting on the mobility of the pollutants [ 30 ], including the use of bio-adsorbent materials. In this regard, studies focusing on bio-adsorbents are of growing interest, as an efficient and low-cost alternative to retain the different contaminants present in soils and water. Generally, materials that are low cost and locally available in large quantities are considered a good choice to be assessed regarding their effectivity [ 31 ]. The food and agroforestry industries produce large amounts of waste and by-products, such as mussel shell, biomass combustion ash, and pine bark, which could be used for this purpose. Specifically, previous studies on pollutant retention onto biomass ash showed promising results in investigations focused on As [32,33] as well as on Cu [34,35]. In this view, the objective of this work is to study the retention of Cu and As(V) in cultivated soils with different characteristics, as well as the capacity of different by-products (oak ash, pine bark, and mussel shell) to immobilize these contaminants. The results of the research could be useful in program-appropriate practices to manage soils and low-cost by-products in order to reduce the risks of environmental contamination associated with the spreading of materials that contain both pollutants. 2. Materials and Methods 2.1. Soils and By-Products For this research, six crop soils were selected, which were previously sampled at two areas of Galicia (NW Spain) subjected to intensive farming: S soils (sampled at Sarria, Lugo province) and AL soils (sampled at A-Limia, Ourense province). The samples were taken from the surface layer (0–20 cm), with each one being the result of combining 10 sub-samples collected in a zig-zag manner for each soil. These soils have been previously studied and described [36]. The forest by-products used in this study were oak ash from a local boiler at Lugo (Spain), pine bark (fraction less than 0.63 mm), a commercial product provided by Geolia (Madrid, Spain), and un-calcined mussel shell (<1 mm in diameter), supplied by Abonomar Materials 2022,15, 5023 3 of 21 S.L. (Illa de Arousa, Pontevedra province, Spain). A more complete description was previously published [37]. The methods used for the characterization of soils and by-products were the following: pH in water and 0.1 M KCl (soil:solution ratio 1:2.5), using a pH-meter (pH-model 2001 Crison, Spain); C and N by elemental analysis (CHNS Truspec, Leco, St. Joseph, MI, USA); available P by the Olsen method [ 38 ]; exchangeable cations, extracted with 1 M NH 4 Cl [ 39 ] and quantified by atomic absorption/emission spectrometry; the effective cation exchange capacity (eCEC) was calculated as the sum of exchangeable Ca, Mg, Na, K, and Al; noncrystalline Al and Fe (Al o , Fe o ) were extracted with ammonium oxalate acidified at pH 3. All determinations were performed in triplicate. Tables 1and 2show the main characteristics of the soils and the three by-products used, respectively. Table 1. Main characteristics of the six soils studied. Average values (n= 3) with coefficients of variation always lower than 5%. Parameter Units Soil 3AL 19AL 50AL 6S 51S 71S pHH2O 4.74 4.80 4.49 6.33 7.06 6.24 pHKCl 4.30 4.25 4.00 5.86 6.39 5.44 Caecmolckg−12.24 1.53 5.94 12.86 9.89 12.79 Mgecmolckg−10.64 0.41 1.48 1.13 0.97 2.88 Naecmolckg−10.35 0.25 0.42 0.36 0.28 0.41 Kecmolckg−11.00 1.27 1.14 0.61 1.40 1.20 Alecmolckg−11.68 0.61 2.66 0.00 0.01 0.11 eCEC cmolckg−15.92 4.08 11.64 14.96 12.54 17.38 Al saturation % 28.43 15.00 22.83 0.00 0.05 0.06 Pmg kg−1117.90 225.43 135.90 71.42 120.03 96.77 N % 0.31 0.09 0.84 0.23 0.19 0.48 C % 3.39 1.07 10.92 1.98 1.75 6.88 OM % 5.84 1.84 18.83 3.41 3.02 11.86 C/N 10.94 11.89 13.00 8.44 9.05 14.21 Sand % 54.72 64.72 58.72 29.28 27.28 61.28 Silt % 26.00 14.00 16.00 49.28 51.28 23.28 Clay % 19.28 21.28 25.28 21.44 21.44 15.44 Alomg kg−15040.0 855.0 2995.0 18,377.5 15,755.7 50,593.5 Feomg kg−12585.0 1150.0 1430.0 56,423.8 42377.4 73,095.9 Ca e , Mg e , Na e , K e , and Al e = exchangeable concentrations of the elements; Al o and Fe o = Al and Fe concentration after extraction with ammonium oxalate. Table 2. Main characteristics of the three by-products used. Average values (n= 3) with coefficients of variation always lower than 5%. Parameter Unit Oak Ash Pine Bark Mussel Shell C % 13.23 48.70 11.43 N % 0.22 0.08 0.21 C/N 60.13 608.75 55.65 pHH2O 11.31 3.99 9.39 pHKCl 13.48 3.42 9.04 Caecmolckg−195.00 5.38 24.75 Mgecmolckg−13.26 2.70 0.72 Naecmolckg−112.17 0.46 4.37 Kecmolckg−1250.65 4.60 0.38 Alecmolckg−10.07 1.78 0.03 Al saturation % 0.02 11.91 0.11 eCEC cmolckg−1361.17 14.92 30.25 P-Olsen mg kg−1462.83 70.45 54.17 Alomg kg−18323.00 315.00 178.33 Feomg kg−14233.00 74.00 171.00 Ca e , Mg e , Na e , K e , and Al e = exchangeable concentrations of the elements; Al o and Fe o = Al and Fe concentration after extraction with ammonium oxalate. Materials 2022,15, 5023 4 of 21 Table S1 (Supplementary Materials) shows data on BET surface areas for the six soils studied, evidencing that the values were higher for S soils. Of note, although higher surface area facilitates achieving higher adsorption of a variety of substances onto soils, other factors could be of even higher relevance, as previously stated for different pollutants [ 40 ]. In addition, Table S2 (Supplementary Materials) shows data on BET surface areas for the three by-products, evidencing that the highest value corresponded to oak ash (1.3336 m 2 g −1 ), followed by mussel shell (1.1318 m 2 g −1 ), and being much lower for pine bark (0.3320 m2g−1). 2.2. Adsorption and Desorption Experiments To perform adsorption studies, batch-type experiments were carried out, stirring 1 g of each soil or by-product for 24 h with 40 mL of 0.005 M CaCl 2 and with different concentrations of Cu or As(V) (100, 200, 400, 800, and 1000 µ mol L −1 ), with each pollutant added individually. The solutions were prepared from analytical grade Cu(NO 3 ) 2 .3H 2 O and Na 2 HAsO 4 (Panreac, Barcelona, Spain). After 24 h of agitation, the samples were centrifuged (at 4000 rpm) and filtered. In the equilibrium solution, the dissolved organic carbon (DOC) was determined by means of UV-1201 spectroscopy (Shimadzu, Kyoto, Japan), the pH using a glass electrode (Crison, Madrid, Spain), and the concentrations of Cu or As using an ICP-MS equipment (Varian 820-NS, Palo Alto, CA, USA). The amount of Cu or As adsorbed was calculated by the difference between the added concentration and that remaining in the equilibrium solution. Regarding desorption experiments, 40 mL of 0.005 M CaCl 2 was added to each of the samples used in the previous adsorption tests, then stirring for 24 h, centrifuging, filtering and quantifying Cu or As(V) in the equilibrium solution, following the same methodology indicated above. 2.3. Data Analysis and Statistical Treatment The experimental adsorption data were checked as regards their fitting to the Freundlich (Equation (1)), Langmuir (Equation (2)), and Temkin (Equation (3)) models: qa=KFCn eq (1) qa=KFCn eq (2) qa=βln KT+βln Ceq (3) where q a is the amount of Cu or As(V) adsorbed in equilibrium ( µ mol kg −1 ); C eq is the concentration of Cu or As(V) present in the solution in the equilibrium ( µ mol L −1 ); K F is the Freundlich affinity parameter (L nµ mol 1−n kg −1 ); nis the Freundlich linearity parameter (dimensionless); K L is a Langmuir parameter related to the adsorption energy (L µ mol −1 ), and q m is the Langmuir’s maximum adsorption capacity ( µ mol kg −1 ). In addition, β is calculated as RT/bt;bt is the Temkin isotherm constant; Tis Temperature (K = 298 ◦ ) (25 ◦ C); Ris the universal gas constant (8314 Pa m 3 /mol K); and K T is the Temkin isotherm equilibrium binding constant (L g−1). Desorption was expressed as the amount of Cu or As(V) desorbed (in µ mol kg −1 , and also as percentage) with respect to the amount previously adsorbed. The statistical software R version 3.1.3 and the nlstools package for R [ 41 ] were used to check the fittings to the adsorption models. The SPSS 15.0 software was used to carry out bivariate Pearson correlations between adsorption and desorption data and characteristics of the sorbent materials, and multiple linear regression analyses. 3. Results 3.1. Cu and As(V) Adsorption onto Soils The adsorption curves for the soils and bio-adsorbents studied are shown in Figures 1and 2, respectively. Materials 2022,15, 5023 5 of 21 Figure 1. Cu and As(V) adsorption curves and selected graphical fittings to the various adsorption models for the six soils studied. Error bars represent twice the standard deviation of the mean (n= 3). When bars are not visible, they are smaller than the symbols. Materials 2022,15, 5023 6 of 21 Figure 2. Cu and As adsorption curves and selected graphical fittings to the various adsorption models for the three bio-adsorbents studied. Error bars represent twice the standard deviation of the mean (n= 3). When bars are not visible, they are smaller than the symbols. Figure 1shows a variety of shapes in the adsorption curves, with differences between the AL and S soils. In fact, these curves show that overall Cu adsorption was higher for S soils (which have higher surface area) than for AL soils, while As(V) adsorption was similar for both kinds of soils. Figure 2shows that Cu and As(V) adsorption results were clearly higher for oak ash as compared to pine bark and mussel shell. Figure 3shows the results corresponding to Cu and As(V) adsorption onto the different soils (both in absolute value and percentage) as a function of the concentration added. Considering the absolute values, it is clear that the higher the Cu or As(V) concentrations added, the higher the adsorption for all soils, while the adsorbed percentage shows a decreasing trend. Adsorption was generally higher for Cu than for As, especially in S soils. When the highest Cu or As(V) concentrations (1600 µ mol L −1 ) were added, Cu maximum adsorption values were reached in soils 51S and 71S (37,687 µ mol kg −1 and 44,019 µ mol kg −1 , respectively), while for As(V), the highest scores corresponded to soils 50AL and 71S (17,076 µ mol kg −1 and 22,980 µ mol kg −1 , respectively) (Figure 3). In contrast, the minimum Cu adsorption corresponded to soils 19AL and 3AL (5963 µ mol kg −1 and 12,523 µ mol kg −1 , respectively), while for As(V), the minima were for soils 19AL and 6S (6290 µmol kg−1and 5868 µmol kg−1, respectively). Regarding percentage adsorption, within AL soils, the one with the highest organic matter content (soil 50AL, Table 1) adsorbed about 90% of Cu for the three lowest doses added, while this percentage dropped to 57% for the highest dose; however, for soil 19AL Materials 2022,15, 5023 7 of 21 (the one with the lowest organic matter content), Cu adsorption never exceeded 56%, being less than 12% for the highest dose. The progressive decrease in the adsorption rate affecting these three AL soils could be related to a saturation of the adsorption sites, many of which would be functional groups in organic compounds, and that decrease would be more pronounced for those soils with a lower organic matter content. In S soils, the adsorption was close to 100% for the three lowest doses of Cu added, decreasing to 82% in the soil with the highest organic matter content (soil 71S) and to 56% in soil 6S when the maximum Cu dose was added, again due to the saturation of the functional groups involved in adsorption, many of which lie in organic matter. Figure 3. Cu and As (V) adsorption, expressed in µ mol kg −1 and as percentage, for the soils studied, as a function of the pollutant concentrations added. Error bars represent twice the standard deviation of the mean (n= 3). When bars are not visible, they are smaller than the symbols. Table 3shows data corresponding to Cu and As(V) adsorption for the various initial concentrations added of both pollutants to the soils studied, in parallel to data corresponding to pH and DOC values in the equilibrium solution. 3.2. Cu and As(V) Desorption from Soils Figure 4shows the amounts of Cu and As(V) desorbed from the soils as a function of the concentrations added. As the added dose of each element increased, both the amount Materials 2022,15, 5023 8 of 21 and the percentage desorbed were higher. All AL soils had a similar desorption of both elements, while S-zone soils (with higher pH) desorbed much more As than Cu (Figure 4). Table 3. Values of Cu and As(V) adsorption (Q) as well of pH and DOC in the equilibrium solution for the various Cu and As(V) initial concentrations (C0) added to the soils. Cu As(V) Soil C0µmol L−1Qµmol kg−1pH DOC mg L−1Qµmol kg−1pH DOC mg L−1 3AL 0.00 0.00 4.75 0.08 0.00 4.76 0.19 100 2127.04 4.64 0.20 2394.39 4.78 0.19 200 3225.97 4.46 0.13 3764.03 4.97 0.23 400 6951.04 4.43 0.13 6037.21 5.17 0.16 800 10,467.99 4.25 0.12 9344.48 5.37 0.17 1600 12,523.80 4.10 0.10 16,882.19 5.92 0.16 19AL 0.00 0.00 4.71 0.20 0.00 5.00 0.08 100 1433.70 4.57 0.13 888.39 5.19 0.14 200 2088.81 4.45 0.19 1153.99 5.33 0.21 400 3969.43 4.34 0.29 5778.18 5.74 0.09 800 6659.33 4.27 0.17 4126.55 6.11 0.12 1600 5963.30 4.07 0.28 6290.39 6.60 0.09 50AL 0.00 0.00 4.27 0.26 0.00 4.50 0.13 100 2524.26 4.24 0.19 2272.59 4.37 0.18 200 5106.61 4.13 0.26 3939.78 4.38 0.20 400 11,086.25 4.03 0.28 6058.32 4.45 0.28 800 20,244.49 3.79 0.34 10,856.87 4.66 0.23 1600 28,481.45 3.69 0.23 17,075.78 4.89 0.22 6S 0.00 0.00 5.61 0.20 0.00 5.88 0.19 100 2558.33 5.66 0.19 3048.25 5.87 0.12 200 5253.62 6.26 0.13 3015.26 6.33 0.08 400 12,030.50 5.57 0.15 4393.79 6.44 0.09 800 22,000.77 5.07 0.13 5849.58 6.73 0.09 1600 29,540.60 4.75 0.17 5866.52 6.88 0.06 51S 0.00 0.00 6.04 0.16 0.00 6.61 0.15 100 2615.99 6.09 0.18 2016.28 6.80 0.14 200 5202.90 6.06 0.19 3091.30 6.83 0.12 400 12,205.87 5.93 0.14 4485.69 6.85 0.09 800 24,061.91 5.55 0.13 6775.33 6.96 0.12 1600 37,687.91 5.09 0.11 10,962.17 7.18 0.08 71S 0.00 0.00 5.49 0.29 0.00 6.00 0.11 100 2618.82 5.53 0.20 2516.39 5.85 0.09 200 5282.88 5.49 0.19 4786.28 5.84 0.13 400 11,962.35 5.36 0.16 8174.64 5.84 0.14 800 25,655.79 5.13 0.18 14,047.81 5.92 0.13 1600 44,019.57 4.69 0.15 22,979.85 6.07 0.13 In relation to Cu, desorption was much higher from AL soils than from S soils (the latter having a higher surface area). The maximum percentage values for AL soils were between 39% of the soil with less organic matter (19AL) and 12% of the one containing most organic matter (soil 50AL), while the range for the S zone was narrower: between 15% (soil 6S) and 5% (soils 51S and 71S). In general, soils with low desorption values match those with high adsorption scores. 3.3. Cu and As(V) Adsorption onto the Three By-Products Figure 5shows Cu and As(V) adsorption onto the three by-products as a function of the concentration added. Adsorption was always much higher for Cu than for As(V), especially for pine bark and mussel shell, while for oak ash, the differences were clearly smaller, although becoming more evident as the added dose increased. Materials 2022,15, 5023 9 of 21 Figure 4. Cu and As (V) desorption, expressed in µ mol kg −1 and as percentage, for the soils studied, as a function of the pollutant concentrations added. Error bars represent twice the standard deviation of the mean (n= 3). When bars are not visible, they are smaller than the symbols. Figure 5. Cu and As (V) adsorption, expressed in µ mol kg −1 and as percentage, for the three bioadsorbents studied, as a function of the pollutant concentrations added. Error bars represent twice the standard deviation of the mean (n= 3). When bars are not visible, they are smaller than the symbols. Materials 2022,15, 5023 16 of 21 that the extent is metal(loid)-specific when amended to soils. Park et al. [ 74 ] studied fly and bottom ash from wood pellet thermal power plants, finding that these by-products have a high potential for heavy metal removal, although the authors focused specifically on Cd. In addition, the quality of the bio-adsorbents is relevant, as shown by Lucchini et al. [ 75 ] working with ash derived from Cu-based preservative-treated wood, where the authors reported that these by-products can lead to extremely high Cu concentrations in soil and negatively affect plant growth. In view of the layout of some of the isotherm graphs, it could be considered that the concentrations of some of the sorbents and/or the concentration range of the sorbates were not optimal, influencing the accuracy of the fitting of various models. In this regard, we have published previous papers dealing with these and other aspects related to Cu and As adsorption/desorption studies, using similar values to those of the current work for molar concentrations of these pollutants, which facilitates the easier comparison of retention efficacy, although other concentrations and ranges would be cleary interesting for future investigation, to shed further and more specific light on the overall processes. As examples, the references [76–78] correspond to some of these papers. 4.4. Cu and As(V) Desorption from the Three By-Products According to [ 79 ], Cu binds to OC occupying high-affinity sites when Cu activity is low, but if that activity increases, Cu would also occupy low-affinity sites, which would facilitate desorption, and this could explain the obvious increase in desorption taking place only in pine bark as the concentration of Cu added rises. In relation to the percentage desorbed (Figure 6), a gradual increase is observed for pine bark as the dose of Cu added rises, reaching a maximum value of 15%. For oak ash and mussel shell, desorption rates were very low, not exceeding 2% in any case. Regarding As(V), the desorption sequence was: mussel shell ≥ pine bark> oak ash. For mussel shell, As(V) desorption increases as the added concentration rises (Figure 6), ranging from 186.25 to 1556.26 µ mol kg −1 , which corresponds to a value of 34% as maximum desorption. For pine bark, desorption reaches 35%, while for oak ash As(V) desorption was practically zero, probably due to the strong adsorption taking place at its high pH values, especially adsorption on the Fe and Al oxy-hydroxides very abundant in this by-product (Table 2), as indicated above. This shows the excellent adsorption capacity of oak ash for both Cu and As(V). 4.5. Fitting of Cu and As(V) Experimental Data to Different Adsorption Models Table 4shows that the Langmuir q m parameter, related to adsorption capacity, is generally higher for Cu than for As(V), and for soils and by-products having higher pH values. In addition, among the most acidic soils and sorbents, q m is higher for those with higher organic matter content, which will be the ones requiring higher concentrations of these elements to become saturated [ 80 ]. The q m values obtained for Cu are significantly correlated with the N content (r = 0.838, p< 0.01), N being related to organic matter, which corroborates the role of organic substances in Cu adsorption. Regarding As(V), q m values are significantly and positively correlated with the cation exchange capacity (r = 0.905), Ca (r = 0.864), K (r = 0.913), and pH KCl (r = 0.71), which could suggest that the As adsorbed is in anionic form, with adsorption taking place through a cationic bridge on the negatively charged components of variable charge (mainly organic matter and non-crystalline minerals). As regards the Langmuir K L parameter, its value was higher for Cu than for As(V), which suggests a higher adsorption energy for Cu [ 81 ]. K L is significantly and positively correlated with pH in water (r = 0.95, p< 0.01, for Cu, and r= 0.74, p< 0.05, for As), indicating an increase in the retention energy with increasing negative soil charge. The values of the Freundlich parameter K F parameter, related to the multilayer adsorption capacity of a given adsorbent [ 82 ], were also much higher for Cu than for As(V) (Table 5). In general, the highest K F values were found in those soils and by- Materials 2022,15, 5023 17 of 21 products having higher pH, with a significant correlation (p< 0.01) between K F and pH H2O (r = 0.941 and 0.85 for Cu and As, respectively) and also between K F and a parameter closely related to soil pH, especially in soils with variable charge, which is eCEC (r = 0.89 and 0.88 for Cu and As, respectively). The nFreundlich parameter indicates the reactivity and heterogeneity of the active sites of the adsorbent, with Table 5showing that the n value is always lower than 1 (specifically, it varies between 0.219 and 0.649), except for Cu adsorption on oak ash. This indicates the existence of non-linear and concave adsorption curves, with heterogeneous adsorption surfaces, which leads to a decrease in adsorption sites as the added metal/metalloid concentration increases [ 83 ], which coincides with the decrease in the adsorbed percentage as the dose of Cu and As added increases. Temkin’s model is related to the adsorption energy and is characterized by a uniform distribution of binding energies up to a maximum level [ 84 ]. It is also assumed that this energy decreases linearly with surface coverage due to adsorbent–adsorbate interactions. The Temkin parameters in the current study show R 2 values generally >0.80. According to [ 85 ], values of the Temkin constant (bt) lower than 20 KJ mol −1 would indicate the existence of physical adsorption processes. Table 4shows that, in general, bt values are always higher, which would justify the presence of chemisorption reactions [ 84 ]. According to [ 86 ], these high bt values would indicate a high degree of interaction between both pollutants (As and Cu) and the adsorbents used in the present study. 5. Conclusions In the soils and by-products used in this study, adsorption was higher for Cu than for As(V). In the soils, pH and organic matter content were the most influential factors as regards Cu adsorption, which increased with both parameters. In addition, Cu in cationic form would be adsorbed by binding to the negatively charged sites generated by raising the pH in the variable charge components (mainly organic matter and low-crystallinity minerals). Regarding As(V) adsorption, the influence of pH and organic matter was not so clear, since, at a low pH, As in anionic form binds to the positively charged colloids, while at higher pHs, other mechanisms intervene, such as cationic bridges or ligand exchange. For As(V) and, to a lesser extent, for Cu, the percentage of adsorption decreases with increasing dose of the added pollutant, indicating the saturation of the adsorption sites. Regarding desorption, in soils with more acidic pH (AL soils), Cu and As desorption were similar, while in soils with higher pH (S soils), more As is desorbed. Overall, oak ash performed as an excellent Cu and As(V) adsorbent and could be used in soil and water decontamination processes, possibly due to its high pH and content of carbonates, oxides, and non-crystalline minerals. Mussel shell and pine bark could also be used to retain Cu, but its capacity to adsorb As was low and its desorption was high. The adsorption data for both elements can be partially fitted to the Langmuir, Freundlich, and Temkin models. The values of the different parameters of the equations indicate a higher adsorption energy for Cu onto the sorbent surfaces, compared to As(V), and the existence of heterogeneous adsorbent surfaces with the gradual saturation of the adsorption sites, as well as the predominance of chemisorption reactions. In addition, the high correlations obtained among the different parameters of the equations and parameters of the sorbents support the influence of pH, exchange cations, as well as organic matter and non-crystalline Fe and Al oxy-hydroxides in Cu and As(V) adsorption. These results can be considered relevant to program an appropriate management of soils affected by Cu and As(V) pollution, as well as the use of low-cost bio-adsorbents, such as those tested in this study. In future research, soils with different characteristics could be evaluated, as well as other bio-adsorbents and/or study conditions, and on the other hand, complementary studies could be designed in order to advance the elucidation of the mechanisms that intervene in the adsorption processes of both contaminants in the sorbent materials under consideration. Materials 2022,15, 5023 18 of 21 Supplementary Materials: The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/ma15145023/s1, Table S1: Data corresponding to the BET surface area results for the six soils studied. Mean values (n= 3) with coefficients of variation always <5%; Table S2. Data corresponding to the BET surface area results for the three bio-adsorbent materials studied. Mean values (n= 3) with coefficients of variation always <5%. Author Contributions: Conceptualization, M.J.F.-S., E.Á.-R., A.N.-D., M.A.-E. and P.P.-R.; methodology, M.J.F.-S., E.Á.-R., A.N.-D., M.A.-E. and P.P.-R.; software, R.C.-D., A.B., G.F.-C. and C.C.-C.; validation, M.A.-E., A.N.-D., E.Á.-R., A.N.-D. and M.J.F.-S.; formal analysis, R.C.-D.; investigation, R.C.-D., A.B., G.F.-C. and C.C.-C.; resources, E.Á.-R., M.J.F.-S. and M.A.-E.; data curation, R.C.-D., A.B., M.J.F.-S. and E.Á.-R.; writing—original draft preparation, R.C.-D., A.B., M.J.F.-S. and E.Á.-R.; writing—review and editing, A.N.-D.; visualization, R.C.-D., A.B., G.F.-C., C.C.-C., P.P.-R., M.A.-E., A.N.-D., E.Á.-R. and M.J.F.-S.; supervision, M.J.F.-S.; project administration, E.Á.-R., M.J.F.-S. and M.A.-E.; funding acquisition, E.Á.-R., M.J.F.-S. and M.A.-E. All authors have read and agreed to the published version of the manuscript. Funding: This work was supported by the Spanish Ministry of Economy and Competitiveness (grant numbers RTI2018-099574-B-C21 and RTI2018-099574-B-C22), with European Regional Development Funds (FEDER in Spain). Institutional Review Board Statement: Not applicable. Informed Consent Statement: Not applicable. Data Availability Statement: Not applicable. Conflicts of Interest: The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results. References 1. Coelho, G.F.; GonÇalves, A.C.; Nóvoa-Muñoz, J.C.; Fernández-Calviño, D.; Arias-Estévez, M.; Fernández-Sanjurjo, M.J.; Álvarez-Rodríguez, E.; Núñez-Delgado, A. Competitive and non-competitive cadmium, copper and lead sorption/desorption on wheat straw af-fecting sustainability in vineyards. J. Clean. Prod. 2016,139, 1496–1503. [CrossRef] 2. Qin, F.; Shan, X.; Wei, B. 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