Simultaneous adsorption of amoxicillin and ciprofloxacin on agricultural soils and by-products used as bio-adsorbents: unraveling the interactions in complex systems

1 Simultaneous Adsorption of Amoxicillin and Ciprofloxacin on Agricultural Soils 1 and By-products Used as Bio-adsorbents: Unraveling the Interactions in Complex 2 Systems 3 4 Raquel Cela-Dablanca1, Ainoa Míguez-González1, Ana Barreiro1, Lucia Rodríguez-López2, 5 Manuel Arias-Estévez2, Avelino Núñez-Delgado1, María J. Fernández-Sanjurjo1, Ventura 6 Castillo-Ramos3,*, Esperanza Álvarez-Rodríguez1 7 1Dept. Soil Science and Agricultural Chemistry, Engineering Polytechnic School, Univ. Santiago 8 de Compostela, 27002 Lugo, Spain 9 2Soil Science and Agricultural Chemistry, Fac. Sciences, Univ. Vigo, 32004 Ourense, Spain 10 3Department of Inorganic Chemistry, Faculty of Science, University of Granada, 18071, Granada, 11 Spain 12 *Corresponding author email: [email protected] 13 14 Abstract 15 The presence of pharmaceuticals in agricultural soils, like amoxicillin (AMX) and 16 ciprofloxacin (CIP), poses a significant environmental challenge with potential 17 implications for ecosystems and human well-being. This study explores the simultaneous 18 adsorption of AMX and CIP on crop soils and bio-adsorbents, focusing on competitive 19 adsorption dynamics. Tests were conducted with varying pharmaceutical concentrations 20 in six soils and three bio-adsorbents. CIP consistently exhibited higher adsorption than 21 AMX, particularly at higher concentrations. In the binary system, AMX's adsorption 22 exceeded the individual system at higher concentrations, implying a synergistic effect. 23 Bio-adsorbents, especially pine bark and oak ash, displayed superior adsorption capacities 24 compared to soils. Some soils exhibited enhanced adsorption and retention of both 25 antibiotics simultaneously, aligning with the cooperative adsorption model. Freundlich's 26 adsorption model described the competitive adsorption systems well. These findings have 27 implications for addressing antibiotic contamination in agricultural ecosystems, offering 28 insights into complex interactions in soil environments amid rising pharmaceutical 29 concerns. 30 31 Keywords: Antibiotics pollution; crop soils; emerging pollutants; release; retention; 32 synergistic adsorption 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 2 1. Introduction 48 The extensive utilization of antibiotics in recent years has resulted in their dissemination 49 and subsequent detection in water bodies and cultivated soils, posing a significant threat 50 to both human health and ecosystems [1]. Given that up to 90% of these biocides are 51 excreted from the body through feces and urine (due to not complete absorption in the 52 intestine), they accumulate in farm solid excreta and effluents or get released into 53 wastewaters and sludge generated from wastewater treatment plants (WWTP) after their 54 use in human medicine [2]–[4]. Regrettably, most WWTPs are not adequately equipped 55 to inactivate or remove antibiotics effectively, leading to their substantial release in 56 effluents and accumulation in sludge [5], [6]. 57 The incorporation of WWTP sludge and/or wastewater effluents into soil to enhance 58 fertility can inadvertently introduce these pollutants into crop soils. This may result in the 59 emergence of resistant bacteria, ecotoxicity, and the potential entry of antibiotics into the 60 food chain through water and crops, classifying these compounds as emerging pollutants 61 with adverse effects on human and animal health [7]–[9]. 62 Adsorption processes stand out as simple, cost-effective, highly efficient, eco-friendly, 63 and renewable approaches to improve the retention of antibiotics in soils [10]–[13]. 64 Employing adsorption to retain antibiotics in soils could present a viable and affordable 65 solution to control the dispersion of these pollutants into the food chain. Other methods 66 like advanced oxidation, hydrolysis, photodegradation and biodegradation have been 67 explored as alternatives to adsorption. However, most of these processes generate toxic 68 by-products, and lack sufficient reliability for antibiotic removal [14], [15]. 69 The concurrent presence of amoxicillin and ciprofloxacin in crop soils holds considerable 70 scientific importance due to its potential environmental ramifications and impact on 71 agricultural systems. Once introduced into the soil, these antibiotics may exhibit 72 prolonged persistence and interact with soil components, thereby exerting long-term 73 effects on soil quality, microbial communities, and nutrient cycling processes [16], [17]. 74 Moreover, the coexistence of both antibiotics could give rise to synergistic or antagonistic 75 effects, altering their adsorption behavior and mobility, and consequently influencing 76 their bioavailability to plants and potential uptake by crops [18]. Understanding the 77 simultaneous adsorption of amoxicillin and ciprofloxacin in crop soils is pivotal in 78 comprehending their environmental fate and the associated risks of entering the food 79 chain. This underscores the significance of employing sustainable agricultural practices 80 to mitigate potential adverse effects on human and ecosystem health. 81 Drawing from this context and our prior research works [19]–[22], the primary aim of 82 this study is to investigate the retention capacity of six crop soils, namely VO5, M1, FC, 83 VP1, VP6, and VP7, along with three distinct bio-adsorbents materials (pine bark, mussel 84 shell, and oak ash), concerning amoxicillin and ciprofloxacin adsorption. Additionally, 85 we seek to explore the simultaneous adsorption behavior of both antibiotics within these 86 systems. This comprehensive approach ensures a realistic representation of real-world 87 scenarios, enabling an in-depth analysis of the intricate interactions among the 88 pharmaceuticals, soils, and bio-adsorbents. Through elucidating the underlying 89 mechanisms, this study significantly could contribute to the understanding of the 90 functioning of such real systems and their potential implications. 91 92 2. Materials and methods 93 2.1.Screening and selection of soils samples and bio-adsorbents 94 The soil sampling procedure encompassed the collection of 60 distinct soil samples 95 distributed across Galicia, a geographic area in northwestern Spain. Among these, 27 96 samples were derived from corn crops, and 33 samples originated from vineyard soils. 97 3 Additionally, three samples were acquired from forest soils due to their differential 98 organic matter content and pH values compared to crop soils, both of which play pivotal 99 roles in adsorption/desorption processes (as depicted in Table S1, Supplementary 100 Material). 101 The sampling process involved obtaining ten sub-samples from each plot within the 102 topsoil layer (0-20 cm) using an Edelman probe in a zig-zag pattern. These ten sub-103 samples were combined to form a comprehensive and representative sample. 104 Subsequently, the collected samples were transported to the laboratory and subjected to 105 oven drying (at a specific temperature) until a constant weight was achieved. Following 106 this, the samples were sieved to a 2-mm size and properly stored. 107 From the initial pool of 60 soil samples, a subset of six soils was selected based on their 108 respective pH and organic matter contents. These soils were designated as M1, VO5, VP1, 109 VP6, VP7, and FC. 110 The study also employed biosorbents sourced from the forestry and agro-food industry. 111 Specifically, phyto mass ash was obtained from oak log combustion at a combustion 112 boiler in Lugo, Spain. The uncalcined mussel shell, with a particle size smaller than 1 113 millimeter, was provided by Abonomar S.L. on Isla de Arousa, Pontevedra, Spain. Lastly, 114 the Geolia trademark pine bark from Madrid, Spain, was crushed and sieved to a particle 115 size of 0.63 mm. 116 117 2.2.Chemicals and reagents 118 The antibiotic ciprofloxacin (CIP) was of 98% purity while amoxicillin trihydrate (AMX) 119 was of >95% purity, all of them supplied by Sigma-Aldrich (Madrid, Spain). All the 120 reagents needed for the quantification of the antibiotics were of HPLC grade, provided 121 by Sigma-Aldrich (Madrid, Spain). A Millipore system (Madrid, Spain) was used to 122 provide ultrapure water. 123 124 2.3.Characterizations of soils and bio-adsorbents 125 The granulometry of the soils was determined following the Robinson International 126 Pipette Method [23], which allowed for the separation of sand, silt, and clay fractions. 127 The soil textures were then classified using the Soil Taxonomy approach [24]. 128 The pH measurement was conducted in water and KCl solutions using a soil-to-liquid 129 ratio of 1:2.5 [25]. The pH readings were performed using a CRISON model 2001 pH-130 meter (Spain), with a contact time of ten minutes for water and two hours for KCl. To 131 analyze organic matter (OM) and nitrogen contents, elemental analysis was employed, 132 utilizing a TRUSPEC CHNS equipment from LECO model (USA). For the determination 133 of exchange cations, a 1M NH4Cl extract was utilized, with a soil-to-solution ratio of 134 1:10, and the extraction process was conducted over 12 hours [26]. Atomic 135 adsorption/emission spectrophotometry was employed, with the addition of 1% LaCl3 to 136 prevent any potential interferences. The elements Al, Ca, Mg, Na, and K were quantified 137 through this method. To assess the effective cation exchange capacity (eECE), the sum of 138 the exchange cations was calculated [27]. For the non-crystalline iron (Feox) and 139 aluminum (Alox) fractions, an extraction procedure was carried out using an ammonium 140 oxalate buffered solution at pH=3 [28]. Additionally, the fractions bound to organic matter 141 (Fepir and Alpir) were obtained using a sodium pyrophosphate solution at pH=10 [29]. The 142 quantification of these fractions was performed using atomic absorption 143 spectrophotometry. Tables S1 and S2 (Supplementary Material) provide an overview of 144 the characteristic physicochemical parameters of the six soils and three bio-adsorbents 145 studied. 146 147 4 2.4.Simple and binary adsorption/desorption tests and antibiotics quantification 148 Batch experiments were conducted in simple and binary systems, each containing either 149 one of the antibiotics (amoxicillin/ciprofloxacin) or both and were exposed to five 150 different concentrations of the respective antibiotics (ranging from 0 to 400 μmol L-1). To 151 initiate the tests, 4 g of the soils (0.5 g in the case of bio-adsorbents) were mixed with 10 152 mL of a 0.005 M CaCl2 solution, which served as the background electrolyte to maintain 153 a constant ionic strength. The antibiotic concentrations were varied independently for 154 each individual antibiotic. The mixture was stirred for 48 hours, a duration determined 155 based on prior kinetics experiments, to ensure that equilibrium was reached [20], [22]. 156 Following the adsorption phase, the samples were subjected to centrifugation at 4000 rpm 157 for 15 minutes, and the resulting supernatants were filtered through 0.45 µm nylon-type 158 syringe filters. 159 The quantification of antibiotic concentrations was performed using High-Performance 160 Liquid Chromatography (HPLC) with a Thermo-Fisher Model LPG 3400 SD equipment 161 (USA) coupled with a HPG-3400 quaternary pump (USA), a WPS3000 autosampler 162 (USA), a thermostated compartment for the TM-120 column, and an ultraviolet-visible 163 detector of the UltiMate 3000 series (USA). Data processing was facilitated using the 164 Chromeleon software, and a Luna C18 column (150 mm long; 4.6 mm internal diameter; 165 5 µm particle size) provided by Phenomenenex (Madrid, Spain) was used, along with a 166 pre-column (4 mm long; 2 mm internal diameter; 5 µm particle size) packed with the 167 same material as the column. The injection volume was set at 50 µL, and the flow rate 168 was maintained at 1.5 mL min-1. Regarding the mobile phase, acetonitrile (phase A) and 169 0.01 M phosphoric acid at pH=2 (phase B) were used for amoxicillin, while for 170 ciprofloxacin, the phases remained the same, but with a different linear gradient, varying 171 from 5% to 32% of phase A and from 95% to 68% of phase B over 10.5 minutes. The 172 wavelengths used for quantification were 212 nm for CIP and 230 nm for AMX. 173 After the adsorption step, desorption tests were conducted. The remaining material post-174 adsorption was weighed, and 10 mL of 0.005 M CaCl2 was added. The samples were 175 stirred for 48 hours, followed by centrifugation and filtration using the same conditions 176 as in the adsorption process. The concentration of the corresponding antibiotic in the 177 equilibrium solution was then determined using a similar procedure as that used in the 178 adsorption tests. 179 180 2.5.Freundlich´s adsorption modelling for simple and binary systems 181 To describe the individual adsorption process of each antibiotic, the Freundlich model 182 was used (eq. 1). 183 184 𝑞𝑞𝑒𝑒=𝐾𝐾𝑓𝑓𝐶𝐶𝑒𝑒 𝑛𝑛 (1) 185 186 Where qe (μmol kg-1) is the amount of antibiotic adsorbed per unit mass of adsorbent 187 (difference between the added amount and the amount remaining at equilibrium); Ce 188 (μmol L-1) is the equilibrium concentration of the antibiotic in the solution, Kf (Ln kg-1 189 μmol1-n) is the Freundlich constant related to the adsorption capacity, and n 190 (dimensionless) is a Freundlich parameter related to the adsorption intensity [30]. 191 Furthermore, to study a possible competition between antibiotics for adsorption sites, the 192 Freundlich equation was adapted (eq. 2) following the literature [2], focusing on the total 193 amount adsorbed for both antibiotics (eq. 2). 194 195 (𝑄𝑄𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎 +𝑄𝑄𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎)=𝐾𝐾𝐹𝐹�𝐶𝐶𝑒𝑒𝑒𝑒𝑎𝑎𝑎𝑎𝑎𝑎 +𝐶𝐶𝑒𝑒𝑒𝑒𝑎𝑎𝑎𝑎𝑎𝑎�𝑛𝑛 (2) 196 197 5 Where Qa is the individual amount adsorbed for each antibiotic; Ceq is the equilibrium 198 concentration of each antibiotic; KF and n are the parameters mentioned above. 199 200 3. Results and discussion 201 3.1. Adsorption of amoxicillin and ciprofloxacin in a binary system by different soils and 202 bio-adsorbents 203 Fig. S1 (Supplementary Material) depicts the adsorption capacity (in μmol kg-1) of AMX 204 and CIP in individual and binary systems of the six soils under investigation, while Fig. 205 S2 (Supplementary Material) represents the adsorbed amount as a percentage. 206 The addition of the two or even all three lower concentrations (25, 50, and 100 μmol L-1) 207 generally does not show significant differences in the adsorbed amount, neither between 208 the two antibiotics (AMX and CIP) nor between the two systems (individual and binary) 209 for each antibiotic (Fig. S1, Supplementary Material). This behavior changes for the two 210 higher concentrations added (200 and 400 μmol L-1), where generally a higher adsorption 211 of CIP than AMX is observed in both systems. Furthermore, in the case of AMX, there is 212 a higher retention in the binary compared to the individual system (Fig. S1, 213 Supplementary Material). 214 By expressing the data as a percentage of adsorption relative to the amount added, it is 215 generally observed that the adsorption rate of CIP is higher than that of AMX in both 216 systems, especially when the two higher concentrations are added. In the case of AMX, 217 the adsorption rate is higher in the binary than in the individual system, particularly at the 218 two higher concentrations. However, this rate decreases as the added concentrations 219 increase, particularly in the individual system. As for CIP, the behavior is less defined. 220 Some soils, such as M1, adsorb almost all of the added concentrations in both systems, 221 while others, as VO5, show an increasing adsorption percentage with the added 222 concentration. Soils such as FC and VP6 exhibit higher adsorption rates in the binary 223 system (between 80% and 100%) than in the individual system (between 40% and 100%), 224 with the percentage increasing as the added concentration increases. Finally, soils like 225 VP1 and VP7 show higher adsorption in the individual than in the binary system, with 226 the former adsorbing 100% of the added concentrations, while the latter shows an 227 increasing retention with concentration, reaching 100% for the two highest doses (Fig. 228 S2, Supplementary Material). 229 The higher adsorption of CIP compared to AMX in both the individual and binary systems 230 (Fig. S1, Supplementary Material) can be related to the fact that CIP has various 231 functional groups (hydroxyl, carboxyl, and fluoride) that play an important role in the 232 adsorption process [31]. These groups are found in cationic or zwitterionic form within 233 the pH range of the studied soils [32], electrostatically interacting with negatively charged 234 soil components. The non-crystalline components, which have a high presence in the 235 studied soils, contribute to the strong affinity of these substances. In contrast, AMX exists 236 in zwitterionic or anionic form [33], resulting in less favorable electrostatic interactions 237 with soil components. Several authors have also reported higher adsorption of CIP 238 compared to AMX [34], [35]. 239 The fact that AMX is generally more adsorbed in the presence of CIP becomes more 240 noticeable at higher concentrations, especially at 400 μmol L-1, where AMX adsorption 241 in the binary system can increase up to 2.7 times in soils M1 and VP7, and between 50% 242 and 75% in the rest of the soils, except for VP1. This synergistic relation in the binary 243 system, favoring AMX adsorption in the presence of CIP, is more significant in soils M1 244 and VP7, which have higher pH values (8.02 and 7.27, respectively). At these pH values, 245 AMX acts as an anionic species with deprotonated amino and carboxyl groups, while CIP 246 exists as a zwitterionic species, allowing for electrostatic attractions between the 247 6 positively charged groups of CIP and the anionic AMX. This suggests that the presence 248 of CIP adsorbed in the soils enhances the incorporation of AMX onto the adsorbent. Due 249 to the high amount of organic matter in both soils (8.58% for M1 and 6.14% for VP7), 250 which carries a negative charge at basic pH values, electrostatic repulsions between AMX 251 and the soils are expected in the individual system, leading to the adsorption of a certain 252 amount of the antibiotic possibly through cationic bridges due to the high amounts of 253 exchangeable calcium in these soils [36](39.44 μmol kg-1 for M1 and 10.53 μmol kg-1 for 254 VP7). The high affinity of soil M1 for adsorbing CIP at all concentrations promotes the 255 incorporation of AMX in the binary system, resulting in AMX adsorptions also 256 approaching 100%. Thus, a ternary complex of soil-CIP-AMX is formed, where CIP 257 provides positive charges for the binding of the anionic AMX. This synergistic 258 phenomenon between antibiotics has been described by other authors in the binary 259 adsorption of tetracycline and sulfadiazine [37]. 260 Regarding CIP, the adsorption in the binary system shows a different behavior compared 261 to the individual system, depending on the concentrations added. For the two highest 262 concentrations, no differences are observed between the two systems (Fig. S2, 263 Supplementary Material), indicating that AMX has no influence on the adsorption of CIP. 264 On the other hand, at the two lower concentrations, two different behaviors are observed. 265 In soils FC and VP6, there is higher adsorption of CIP in the binary system compared to 266 the individual system, and it is also higher than that of AMX. However, in soils VP1 and 267 VP7, the adsorption is higher in the individual system, and in the binary system, it is lower 268 than that of AMX (Fig. S2, Supplementary Material). Therefore, at low concentrations, 269 AMX sometimes has a synergistic effect on CIP adsorption, while in other cases, it has 270 an antagonistic effect. Some authors have found that at low concentrations, CIP is more 271 adsorbed in individual systems than in binary systems, indicating that it cannot efficiently 272 compete with AMX. Conversely, at high concentrations, greater adsorption in the binary 273 system than in the individual system has been observed, which is interpreted as a decrease 274 in mass transfer resistance for the adsorption of CIP species in this binary system [38]. 275 Fig. S3 (Supplementary Material) shows the adsorption of CIP and AMX by the bio-276 adsorbents in both the individual and binary systems, in terms of μmol kg-1 and as a 277 percentage. It is worth noting that all three bio-adsorbents used exhibit much higher 278 adsorption capacities than the soils in the present study (Figs. S1 and S3, Supplementary 279 Material). It can be observed that, generally, both in the individual and binary systems, 280 mussel shell and especially pine bark adsorb more CIP than AMX, while oak ash shows 281 the opposite trend (Fig. S3, Supplementary Material). Therefore, oak ash is an excellent 282 adsorbent for AMX, and pine bark is efficient for CIP in both systems. Expressing the 283 data as percentage values, it can be observed that the adsorption of CIP, both in binary 284 and single systems, is 100% onto pine bark. In mussel shell and oak ash, similar 285 adsorptions of CIP are obtained, while AMX is adsorbed more than CIP only onto oak 286 ash. 287 Comparing the single and binary systems, different behaviors are observed depending on 288 the antibiotic and bio-adsorbent used. In the case of AMX, it is found that in oak ash, at 289 low concentrations added, the adsorption is higher in the single than in the binary system, 290 indicating that CIP competes favorably with AMX under these conditions. However, at 291 higher concentrations, the adsorption is similar in both systems. In contrast, in pine bark 292 and especially in mussel shell, the effect of CIP on AMX is synergistic (Fig. S3, 293 Supplementary Material). 294 Chandrasekaran et al. [35] found that the adsorption of AMX by Prosopis juliflora, in a 295 binary system AMX + CIP, was lower than in the single system, indicating that CIP has 296 antagonistic/competitive effects on the adsorption of AMX, as observed in the case of the 297 7 oak ash used in the current research. This may be due to both antibiotics being negatively 298 charged at the pH of oak ash, leading to the most probable mechanism being cationic 299 bridges established by the abundant exchangeable calcium with the soil components, as 300 mentioned before. This suggests that CIP has a higher affinity than AMX for forming 301 cationic bridges. 302 Regarding the synergistic effect of CIP on AMX observed in pine bark and especially in 303 mussel shell, this can be related to the cooperative adsorption model proposed by several 304 authors [39], [40]. According to this model, when a solute is retained by a site on a 305 homogeneous adsorbent surface, it can influence the consecutive active sites of that 306 surface, promoting new adsorptions and stronger retentions. 307 As for CIP, the presence of AMX generally affects its adsorption very little in oak ash and 308 pine bark, while in mussel shell, it decreases the adsorption in the binary system (at high 309 concentrations), indicating that in this case, AMX competes with CIP (Fig. S3, 310 Supplementary Material). 311 312 3.2. Adsorption isotherms in the amoxicillin-ciprofloxacin binary system for soils and bio-313 adsorbents 314 Table 1 presents the values obtained after applying the Freundlich model for the binary 315 system of AMX with CIP for each soil. 316 317 318 8 Table 1. Freundlich´s model adsorption parameters for the binary system CIP+AMX and 319 simple systems in soils (KF, in Ln kg-1 μmol1-n, and n, dimensionless); -: error value too 320 high for fitting 321 Soil Antibiotic Freundlich KF Error n Error R2 CIP - - - - - VO5 AMX - - 0.629 0.199 0.868 CIP+AMX 8.777 5.046 0.658 0.112 0.975 CIP 0.00004 0 5.798 1.360 0.854 FC AMX 9.339 5.516 0.739 0.108 0.969 CIP+AMX 29.431 13.411 0.77 0.093 0.982 CIP - - - - - VP6 AMX 0.000004 0 3.274 1.869 0.862 CIP+AMX 4.564 3.335 1.042 0.138 0.979 CIP - - - - - M1 AMX - - 1.072 0.541 0.783 CIP+AMX 129.796 33.558 0.684 0.071 0.979 CIP - - - - - VP1 AMX - - 0.758 0.219 0.872 CIP+AMX 6.731 2.209 1.03 0.065 0.994 CIP - - - - - VP7 AMX 12.222 17.619 0.795 0.282 0.872 CIP+AMX 1.12 0.826 1.79 0.183 0.981 322 Fig. 1 shows the relation between equilibrium concentration (μmol L-1) and the adsorbed 323 amount of AMX and CIP (μmol kg-1) by the different soils used. The data is fitted to the 324 Freundlich model. 325 326 9 327 328 Fig. 1. Adsorption curves for AMX and CIP in the binary system onto the studied soils, 329 both real and according to the Freundlich model 330 331 As can be observed in Table 1, the Freundlich model for the binary system AMX+CIP fits 332 well, with high R2 values. Therefore, as mentioned earlier, the Freundlich model can be 333 satisfactorily adapted to describe these competitive adsorption systems. 334 The obtained KF values for the binary system AMX+CIP ranged from 1.12 to 129.80 Ln 335 kg-1 μmol1-n-n (Table 1), which are lower than those found in a previous study for the 336 binary adsorption of tetracycline+sulfonamide (ranging from 34.30 to 1130.45 Ln kg-1 337 μmol1-n-n) in six cultivation soils [41]. In the binary system of AMX+CIP, the KF values 338 were higher than for the individual systems of each antibiotic in FC, VP6, and M1 soils, 339 indicating that the simultaneous presence of both antibiotics favors their adsorption onto 340 these three soils, probably due to the previously described synergistic effects. 341 Regarding the parameter n for the binary system, the VP7 soil presents a value of 1.79 342 (the highest among all the studied soils), which indicates chemical adsorption between 343 the simultaneously present antibiotics and the soil. If we compare the value of n in the 344 AMX+CIP system for this soil with the respective values of the individual systems, it can 345 be appreciated that the presence of both antibiotics may cause modifications in the 346 adsorption mechanisms with the soil surface [41]. Other authors found values of n>1 for 347 binary adsorption systems of chlortetracycline+sulfonamide, suggesting strong 348 interactions between the antibiotics and the adsorption sites of the adsorbents [42]. For 349 the rest of the soils of the current research, the n values were close to 1 (linear adsorption, 350 Fig. 1) or less than 1, indicating the presence of heterogeneous adsorption surfaces, with 351 the highest energy sites being occupied first. 352 Regarding the bio-adsorbents, Table 2 presents the values obtained for each of them after 353 applying the Freundlich model for the binary system AMX-CIP. 354 355 356 16 Acknowledgements 483 The authors gratefully acknowledge the financial supports from the project “Problemas 484 ambientales del uso de antibióticos ionóforos en producción animal: Diagnóstico, 485 adsorción-desorción, efecto sobre los microorganismos y control con bioadsorbentes - 486 GENERACION DE CONOCIMIENTO 2021” (PID2021-1229200B-C21) of the 487 National Spanish Program. 488 489 490 17 References 491 492 [1] Y.-J. Zhang, H.-W. Hu, M. Gou, J.-T. Wang, D. Chen, and J.-Z. 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