Competitive adsorption of tetracycline, oxytetracycline and chlortetracycline on soils with different pH value and organic matter content

Environmental Research 178 (2019) 108669

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Competitive adsorption of tetracycline, oxytetracycline and chlortetracycline on soils with different pH value and organic matter content

T

Manuel Conde-Cida, Gustavo Ferreira-Coelhob, Avelino Núñez-Delgadob,∗, David Fernández-Calviñoa, Manuel Arias-Estéveza, Esperanza Álvarez-Rodríguezb, María J. Fernández-Sanjurjob a b

Department of Plant Biology and Soil Science, Faculty of Sciences, Campus Univ. Ourense, 32004, Ourense, Universidade de Vigo, Spain Department of Soil Science and Agricultural Chemistry, Engineering Polytechnic School, Campus Univ. s/n, 27002, Universidade de Santiago de Compostela, Lugo, Spain

A R T I C LE I N FO

A B S T R A C T

Keywords: Adsorption-desorption Chlortetracycline Oxytetracycline Tetracycline Veterinary antibiotics

Antibiotics spread into the environment can cause soil and water degradation. Specifically, tetracycline antibiotics (TCs) are among those most consumed in veterinary medicine, and near 90% of the doses administered to animals are excreted as original compounds, due to poor absorption. In this study we investigated competitive soil adsorption/desorption for three tetracycline antibiotics (tetracycline: TC, oxytetracycline: OTC, and chlortetracycline: CTC), usually spread on soils by slurry fertilization, affecting to soil degradation due to chemical pollution. The study was carried out on six soils selected according to their pH values (4.49–7.06), and organic matter contents (1.07–10.92%). The competitive experiments were performed in ternary systems (adding all three TCs simultaneously, using five equal and increasing concentrations, from 17 to 200 μmol L−1). The results were compared with those obtained in simple systems (adding individual antibiotics separately), for the same final concentration (in this case, 200 μmol L−1) and for different concentrations (200 μmol L−1 in the simple systems, versus 600 μmol L−1 in the ternary systems, resulting from the sum of 200 μmol L−1 of each of the three antibiotics). In all cases, batch-type adsorption/desorption experiments were carried out, with 24 h as contact time. Those soils with higher organic matter content adsorbed 100% of the TCs, with desorption being always lower than 3%. In soils with less organic matter, adsorption decreased as the dose of added antibiotic increased, due to competition for adsorption sites. CTC was the most retained among the three TCs (up to 20% more than the other when high doses of antibiotic were added). In the simple systems, percentage adsorption was always high (> 85%) for the three TCs; however, percentage adsorption decreased in the ternary systems, reaching just 65% and 40% (for equal and different ionic strength, respectively) in soils with low organic matter contents. These results show the environmental and public health relevance of competition among the three TCs. In fact, the highest risk of entering the food chain takes place when these antibiotics are spread together on soils with low organic matter content, especially in the case of TC and CTC, which are the least adsorbed and the most desorbed molecules.

1. Introduction Among the various causes of soil degradation, chemical pollution is one of the most relevant (Bridges and Oldeman, 1999). It is the case for emerging pollutants, and specifically for antibiotics spread into the environment, which can cause soil and water degradation (Bastos et al., 2018). In fact, agricultural and livestock productions are continuously increasing (mainly in developed countries) due to the growing demand for food on a global scale. The spreading of organic and inorganic fertilizers (including organic waste and by-products) is a common

∗

practice in agriculture, as is the veterinary use of antibiotics for the treatment of diseases, but also to prevent it, and as animal growth promoters (Charuaud et al., 2019). Tetracycline antibiotics (TCs) are the most widely used in veterinary medicine, which is due to factors such as their low cost, broad spectrum and high antimicrobial activity (Daghrir and Drogui, 2013). In fact, the European Medicines Agency (2016) indicates that in 2014 the consumption of TCs represented as much as 33.4% of total antibiotics used in veterinary medicine. Due to their poor absorption when administered to animals, 80–90% of the doses of TCs are excreted as original (not metabolized) compounds in

Corresponding author. E-mail address: [email protected] (A. Núñez-Delgado).

https://doi.org/10.1016/j.envres.2019.108669 Received 4 June 2019; Received in revised form 12 August 2019; Accepted 14 August 2019 Available online 17 August 2019 0013-9351/ © 2019 Elsevier Inc. All rights reserved.

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feces and urine (Kumar et al., 2005), most of them passing to slurry tanks, and to soil when spread as organic fertilizers (Conde-Cid et al., 2018a; Kivits et al., 2018; Charuaud et al., 2019). Specifically, in a recent study carried out in Galicia (NW Spain) (Conde-Cid et al., 2018a) we found concentrations of 0.9, 4.0 and 35.0 mg kg−1 for the tetracycline antibiotics TC, CTC and OTC, respectively, in animal slurries, and up to 0.6 and 0.2 mg kg−1 for TC and CTC, respectively, in agricultural soils. Risks of environmental pollution due to the spreading of animal slurries have been a frequent concern (Núñez-Delgado et al., 2002), however, it is of specific growing relevance all that related to environmental pollution due to emerging pollutant, and specifically to antibiotics, with marked hazards for animal and human health (Kuppusamy et al., 2018; Peng et al., 2019). The persistence of these antibiotics in the environment is affected by degradation processes (Conde-Cid et al., 2018b), while transfer to water bodies and plant uptake is also dependent on adsorption/desorption and transport processes (Fernández-Calviño et al., 2015a; Conde-Cid et al., 2018a; Zhang et al., 2019). These processes are affected by physicochemical characteristics of antibiotics (such as molecular structure, size, solubility and hydrophobicity), and by soil characteristics, mainly pH and contents of components capable of retaining these pollutants (organic matter, clay, non-crystalline minerals) (Kemper, 2008). Specifically, the role of organic matter is of main importance, due to its large amount of pH-dependent functional groups, with the capability of having highly negative charge, allowing adsorption of positively charged antibiotics through electrostatic interactions. In addition, adsorption can also take place by means of hydrogen bonds or cationic bridges through metal ions (Wang and Wang, 2015; Okaikue-Woodi et al., 2018; Wang et al., 2018b; Zhang et al., 2019). The use of sorbent materials is being considered of great interest as a means to remove or retain pollutants (Xu et al., 2016; Anastopoulos et al., 2018; Anjum et al., 2019). Specifically, previous studies have been carried out focusing on antibiotics removal by means of sorbent materials (Chen et al., 2016; Li et al., 2019), even if, in most cases, antibiotics contained in animal slurries are directly spread on soils, using them as organic fertilizers. Some previous works dealt with TCs adsorption on soils, studying each antibiotic individually (simple systems) (Sassman and Lee, 2005; Jia et al., 2008; Figueroa-Diva et al., 2010; Wan et al., 2010; Zhang et al., 2010; Teixidó et al., 2012; Bao et al., 2013; Fernández-Calviño et al., 2015a, b; Li et al., 2015; Peng et al., 2019). However, there is a lack of studies focusing on competitive adsorption of antibiotics on soils, and specifically in cases where several TCs are incorporated simultaneously (multiple systems), which is common in real world when fertilizing with slurries (Conde-Cid et al., 2018a). Our research team used stirred flow chamber experiments to carry out preliminary studies on competitive adsorption for three TCs (TC, OTC, and CTC), although limited to two clearly acid soils (pH < 4.5) (Fernández-Calviño et al., 2015a, 2015b). In addition, we have also verified the frequent simultaneous presence of different TCs in slurries and soils (Conde-Cid et al., 2018a), which indicates the need of performing broader studies on competitive adsorption for TCs in a higher number of agricultural soils with contrasted chemical characteristics. In view of that, the objective of this work is to study the competitive adsorption/desorption of three TCs (TC, OTC, and CTC) in six soils with different characteristics (notably, pH and organic matter content), comparing the results from simple systems (with presence of a single antibiotic) and ternary systems (simultaneous presence of three antibiotics), with equal and different ionic strengths, which as far as we know supposes an original research not previously performed.

Table 1 Main chemical characteristics of the A Limia (AL) and Sarria (S) soils studied (average of N = 3 replicates, with coefficients of variation < 5%). Parameter

Unit

Sand Silt Clay Al C N C/N pH(H2O) pH(KCl) eCEC Ca Mg Na K Al P Alox Alpir Feox Fepir

% % % % % %

cmol(+) kgˉ1 cmol(+) kgˉ1 cmol(+) kgˉ1 cmol(+) kgˉ1 cmol(+) kgˉ1 cmol(+) kgˉ1 mg kg−1 mg kg−1 mg kg−1 mg kg−1 mg kg−1

Soil 3AL 54.7 26.0 19.3 28.4 3.4 0.3 10.9 4.7 4.3 5.9 2.2 0.6 0.4 1.0 1.7 117.9 5040 3342 2585 1652

19AL 64.7 14.0 21.3 15.0 1.1 0.1 11.9 4.8 4.3 4.1 1.5 0.4 0.3 1.3 0.6 225.4 855 614 1150 946

50AL 58.7 16.0 25.3 22.8 10.9 0.8 13.0 4.5 4.0 11.6 5.9 1.5 0.4 1.1 2.7 135.9 2995 2460 1430 2842

6S 29.3 49.3 21.4 n.d. 2.0 0.2 8.4 6.3 5.9 15.0 12.9 1.1 0.4 0.6 n.d. 71.4 18377.5 9125.3 56423.8 21192.8

51S 27.3 51.3 21.4 0.05 1.8 0.2 9.05 7.1 6.4 12.5 9.9 1.0 0.3 1.4 0.01 120.0 15755.7 7902.0 42377.4 11196.1

71S 61.3 23.3 15.4 0.06 6.9 0.5 14.2 6.2 5.4 17.4 12.8 2.9 0.4 1.2 0.1 96.8 50593.5 44980.3 73095.9 39370.1

Alox, Feox, Alpir, Fepir: Al and Fe extracted with ammonium oxalate and sodium pyrophosphate, respectively; n.d.: not detected.

(NW Spain) with intensive farming activities: A Limia (Ourense province) (AL samples), and Sarria (Lugo province) (S samples). In the S zone, granite rocks and acid schists are dominant as lithology, while quaternary deposits dominate in the AL zone. Further details on both zones were provided in a previous work (Conde-Cid et al., 2018a), which focused on the content of veterinary antibiotics (TCs and sulfonamides) in animal slurries, soils and crops in these two areas. In fact, six crop soils (of the total of the 65 analyzed in the mentioned previous work) were selected for the present study (three soils from AL, and three from S), which differ in pH (AL soils with pH between 4.5 and 4.8, and S soils with pH between 6.2 and 7.0), in organic matter content (three soils with less than 2% organic carbon, and three with 3.4%, 6.9% and 10.9%, respectively), and also differ in other parameters relevant in adsorption, as the non-crystalline Al and Fe contents (Table 1). To get each of the six soil samples (one per sampling zone), 15 subsamples were taken in each sampling point. The sampling depth was 0–20 cm, restricted to the surface layer of the soil. Sampling was carried out in a zigzag manner, by means of an Edelman probe. For each sampling point, subsamples were mixed to obtain a single (≈2 kg) representative sample. In the laboratory, soil samples were air dried (at ≈20 °C for 7 days), sieved by 2 mm, homogenized and stored in polyethylene bottles till analyses. Triplicate determinations were carried out in all cases. 2.2. Characterization of soil samples All soil analyses were performed as per standard methods (Tan, 1996; Conde-Cid et al., 2018a). Sand (2–0.05 mm), silt (0.05–0.002 mm) and clay (< 0.002 mm) fractions were quantified by means of the international method of the Robinson pipette. The pH of the soil was determined in water and in 0.1 M KCl (soil: solution = 1 : 5 ratio), using a pH-meter model 2001 (Crison, Spain). Organic carbon and total N contents were determined by elemental analysis, using a ThermoFinnigan 1112 Series NC instrument (ThermoFinnigan, The Netherlands). Exchangeable cations were extracted using 1 M NH4Cl and quantified by absorption/emission atomic spectrometry (AAnalyst 200, PerkinElmer, USA). The effective cation exchange capacity (eCEC) was calculated as the sum of exchangeable Ca, Mg, Na, K and Al. The non-crystalline Al and Fe (Alox, Feox) were extracted with a solution of ammonium oxalate, acidified at pH 3 with oxalic acid, while the Al and

2. Materials and methods 2.1. Study area Soil sampling was carried out in two agricultural areas in Galicia 2

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2.5. Data analysis and statistical treatment

Fe bound to organic matter (Alpir, Fepir) were extracted with sodium pyrophosphate at pH 10; the determination of Al and Fe was made in both cases by atomic absorption spectrophotometry. Available P was determined by UV spectrophotometry (model UV-1201, Shimadzu, Japan) after applying the Olsen method. All determinations were made in triplicate.

The Freundlich (Eq. (1)), Langmuir (Eq. (2)), and Temkin (Eq. (3)) equations were used to describe data obtained in the adsorption experiments: n qa = KF Ceq

(1)

2.3. Adsorption and desorption experiments

qa =

Batch-type experiments were carried out. For the adsorption trials, 1 g of each soil was stirred for 24 h with 40 mL of 0.005 M CaCl2 solutions containing specific concentrations of the antibiotics. In the ternary system experiments (performed to study competitive adsorption), total antibiotic concentrations of 50, 100, 200, 400, and 600 μmol L−1 were used, with each of the three TCs (TC, CTC, and OTC) added to constitute 1/3 of each total concentration. In the simple system experiments (performed to study individual adsorption of each antibiotic), a concentration of 200 μmol L−1 was used for each antibiotic, separately. With these two kinds of experiments, it will be possible to compare the following: a) on the one hand, under conditions of equal ionic strength, adsorption in the simple systems (concentration of individual antibiotic added separately being 200 μmol L−1) versus the ternary systems (in that case where the total concentration added resulting from the sum of the three antibiotics is also 200 μmol L−1); and b), on the other hand, adsorption when the ionic strength of both kinds of systems is different (with concentration being 200 μmol L−1 in the simple systems, compared to the situation in which the concentration is 600 μmol L−1 in the ternary systems, resulting from the sum of concentrations of 200 μmol L−1 for each of the three TCs). After the stirring phase, all samples were centrifuged at 4000 rpm (6167×g) for 15 min. In all equilibrium solutions, pH values were measured using a glass electrode (Crison, Spain), dissolved organic carbon (DOC) was determined by spectrophotometry (model UV-1201, Shimadzu, Japan), and the concentration of the three TCs was quantified as indicated in section 2.4 (see below). The amount of antibiotic adsorbed was calculated as the difference between the concentration added and that remaining in the equilibrium solution after centrifugation. All trials were performed in triplicate. Regarding desorption, 40 mL of 0.005 M CaCl2 were added to each of the samples used in the previous adsorption phase, then these samples were stirred for 24 h and centrifuged at 4000 rpm (6167×g) for 15 min. Subsequently, antibiotics released to the solution were determined. All trials were performed in triplicate.

KL Ceq qm 1 + KL Ceq

(2)

qa = β ln KT + β ln Ce

(3)

where qa (μmol kg−1) is the amount of each of the three TCs adsorbed onto the soil at equilibrium; Ceq (μmol L−1) is the concentration of each antibiotic present in the solution at equilibrium; KF (Ln μmol1−n kg−1) is the Freundlich affinity coefficient; n (dimensionless) is the Freundlich linearity index. In addition, KL (L μmol−1) is a Langmuir parameter related to the adsorption energy, and qm (μmol kg−1) is the Langmuir's maximum adsorption capacity of the soil. Finally, β = RT/bt with bt being the Temkin isotherm constant; Kt is the Temkin isotherm equilibrium binding constant (L g−1); T is Temperature (25 °C) (K = 298°), and R is the universal gas constant (8314 Pa m3/mol K). Furthermore, bearing in mind competition for adsorption sites, adsorption models could be modified, and an initial approach could take into account the total amount of antibiotics adsorbed (Eq. (4)) 1

TC OTC CTC TC OTC CTC (Qeq + Qeq + Qeq ) = KF (Ceq + Ceq + Ceq ) OTC TC , Qeq where Qeq OTC TC sorbed; Ceq , Ceq

n

(4)

CTC and Qeq CTC and Ceq

are the amounts of TC, OTC and CTC adare the concentration of TC, OTC and CTC remaining in solution at equilibrium; and KF and n are Freundlich's parameters. In a previous study, Arias et al. (2006) worked with the Murali–Aylmore model to examine adsorption in multiadsorbate solutions where all individual adsorbates comply with Freundlich's equation in the absence of competitors. Arias et al. (2006) studied competition between Zn and Cu, while in the current work, focused on three tetracycline antibiotics, the best fit corresponded to the following equations derived from the Murali–Aylmore model: nTC + 1 KFTC × CTC + aTC × (COTC + CCTC )

(5)

QeqOTC =

nOTC + 1 KFOTC × COTC COTC + aOTC × (CTC + CCTC )

(6)

QeqCTC =

nCTC + 1 KFCTC × CCTC + aCTC × (COTC + CTC )

(7)

QeqTC =

2.4. Quantification of the three tetracycline antibiotics The procedure previously described by López-Peñalver et al. (2010) and Fernández-Calviño et al. (2015a, b) was used to quantify TCs, after slight modification. Briefly, all suspensions resulting from the adsorption and desorption experiments were subjected to HPLC liquid chromatography, by means of a Dionex apparatus (Dionex Corporation, Sunnyvale, USA), complemented with a P680 quaternary pump, an ASI100 auto-sampler, a TCC-100 thermostatized column compartment, and a UVD170U detector. Also, a Luna C18 column (150 mm long; 4.6 mm internal diameter; 5 μm particle size), from Phenomenex (Madrid, Spain), and a guard column (4 mm long; 2 mm i. d.; 5 μm particle size), packed with the same material as the column, were used to carry out chromatographic separations. The injection volume was 50 μL, and the flow rate was 1.5 mL min−1, with a mobile phase integrated by acetonitrile (phase A) and 0.02 mol L−1 oxalic acid/0.01 mol L−1 triethylamine (phase B). A linear gradient elution program was run from 5 to 32% of phase A (and 95 to 68% of phase B) within 10.5 min. The initial conditions were re-established in 2 min and held for 2.5 min. The total analysis time was 15 min, with a retention time of 8.0 min. The wavelength used for TCs detection was 360 nm. More details can be seen in Fernández-Calviño et al. (2015a, b).

CTC

CCTC

where CTC, COTC and CCTC are concentrations of each antibiotic remaining in solution at the equilibrium, KFTC , KFOTC and KFCTC , nTC , nOTC and nCTC are Freundlich's parameters (see Table 4 below), and aTC , aOTC and aCTC are additional parameters related to competence among the three tetracycline antibiotics. Due to the fact that a is situated in the denominator of the quotients, higher a values will give lower Qeq scores, resulting in lower adsorption for the tetracycline antibiotics. Desorption was expressed as the amount of each of the three TCs desorbed (μmol kg−1), and also as the percentage of each of the TCs desorbed with respect to the amount previously adsorbed. The statistical software R version 3.1.3 (R Core Team, 2015) and the nlstools package for R (Baty et al., 2015) were used to perform the adjustments of the experimental data to both adsorption models. In addition, the SPSS 15.0 software was used to perform bivariate Pearson correlations (considered significant at p < 0.01 and p < 0.05) between adsorption and desorption data and soil variables. 3

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3. Results and discussion

adsorption on soils are very complex, depending on physicochemical characteristics of the antibiotics (structure, solubility, hydrophobicity, etc.) and on soil characteristics (pH, organic matter, Fe and Al oxides contents, texture, etc.) (Kemper, 2008). A key aspect is the influence of pH on antibiotic/soil interactions, affecting to chemical speciation of antibiotics, and to the charge of soil components (Figueroa-Diva et al., 2010). Tetracycline antibiotics have various ionizable functional groups (such as hydroxyl, ketone and amino), subjected to protonation-deprotonation reactions, which give rise to different ionic species depending on the pH of the solution, thus presenting positive, neutral or negative charge (Sun et al., 2010). All these facts increase the variability of antibiotics adsorption on soils, which can take place through mechanisms of different nature: ion exchange, electrostatic attractions, H bonds, etc. To make it clear, in the present study the maximum adsorption values of each antibiotic and the characteristics of each soil were subjected to bivariate correlations analyses, finding significant (p < 0.01) positive correlations with Mg (r = 0.653), Na (r = 0.724), eCEC (r = 0.583), N (r = 0.726), C (r = 0.716), Alox (r = 0.430), and Alpir (r = 0.447). These high correlations corroborate the relevance of ion exchange processes in TCs adsorption. When pH has low values, as happens for three of the studied soils (3AL, 19AL, and 50AL), TCs are in cationic form, which allows interactions with negatively charged soil components. When pH value is higher, such as for soils 6S, 51S, and 70S, deprotonation of –OH and –CONH groups in the antibiotic molecules favors the presence of their anionic and/or zwitterionic forms. Therefore, adsorption can take place by means of cationic bridges with the negative charges of the soil colloids (negative charges also favored by the rise in pH). The participation of Mg2+ in these cationic bridges could explain its high and positive correlation with TCs adsorption. Within soil colloids, organic matter shows a great influence on TCs adsorption, in view of the significant and positive correlations with C and N contents. Previous studies showed the relevance of organic matter on TCs adsorption (Sun et al., 2010; Zhang et al., 2010; Zhao et al., 2011; Yao et al., 2016), attributed to the presence of different reactive functional groups, such as carboxyl, hydroxyl and carbonyls, which have amphoteric character (Wang and Wang, 2015). At pH > 4, the carboxylic groups in the organic matter are deprotonated, developing a negative charge. In this situation, the cationic forms of the TCs can be bound to these groups through electrostatic interactions, or by ion exchange (Figueroa et al., 2004). When pH value increases, more negative charges will be developed in soil organic molecules, and the negative charge is also favored in the TCs, thus facilitating adsorption through cation bridges, especially by means of multivalent metal ions (MacKay, 2005). Specifically, metal cations (M) such as Ca2+, Mg2+ or Al3+, can act as a bridges between organic matter (OM) and TCs, giving a ternary complex (MO-M-TC) (Gu et al., 2007; Zhang et al., 2010; Pikkemaat et al., 2016). In addition, other kinds of bonds have been also considered for TCs adsorption, such as H bonds, due to interactions between polar groups in the antibiotic and soil components (Gu et al., 2007). Therefore, high TCs adsorption capacity can be expected for soils containing high levels of organic matter, but also crystalline clays with high exchange capacity, non-crystalline minerals, and Fe and Al oxides (Yao et al., 2016). In the present work, the participation of non-crystalline minerals in TCs adsorption is corroborated by correlations with Alox and Alpir. In a previous study, Fernández-Calviño et al. (2015b) also found high TCs adsorption for soils with relevant contents in organic matter, clay and Fe and Al oxides. The results of bivariate correlations for TCs adsorption in each soil and the corresponding pH and DOC values in the equilibrium solution, for each of the TCs concentrations added are shown in Table 2. In AL soils, a significant and negative correlation was found among TCs adsorption for each of the three antibiotics and the pH values in the equilibrium solution. These soils have acidic pH (< 4.9), and additional pH decreases take place as TCs adsorption increases, which could indicate that positively charged groups in the TCs displace H+ from soil

3.1. Characteristics of the soils Table 1 shows the main characteristics of the six soils used in this study. In previous works (Fernández-Calviño et al., 2015a, 2015b) dealing with competitive and non-competitive adsorption of TC, OTC and CTC in two soils from the same origin as the six soil samples studied in the current work, the authors extensively commented about effects of soil characteristics such as soil organic carbon, clay, cationic exchange capacity, Al and Fe oxides contents, and pH values, on the retention of tetracycline antibiotics. In the current work, carbon contents varied from just 1.1% up to 10.9%, with the latter being also the soil showing the highest clay content and the most acidic pH (4.5) (Table 1). 3.2. Adsorption of the three TCs on soils in ternary systems (with all three antibiotics present simultaneously) Results corresponding to the adsorption of OTC, CTC and TC for each of the soils studied, when all three TCs are added simultaneously and in the same concentration (from 17 to 200 μmol L−1 each of the three) are shown in Fig. 1. Adsorption was higher for each of the three antibiotics as the added concentration increases, with the highest adsorption values corresponding to the highest doses of antibiotics added (Fig. 1). When these highest doses of antibiotics were added, the highest adsorption results were found in soil 50AL (7422.37 μmol kg−1 for OTC, 7285.27 μmol kg−1 for CTC, and 6457.48 μmol kg−1 for TC), and soil 71S (7376.96 μmol kg−1 for OTC, 6987.11 μmol kg−1 for CTC, and 6588.65 μmol kg−1 for TC), which are the soils with the highest organic matter contents (Table 1). The lowest adsorption corresponded to soil 19AL, especially when the highest dose of antibiotic was added (adsorption of 2959.46 μmol kg−1 for OTC, 3414.58 μmol kg−1 for CTC, and 2678.93 μmol kg−1 for TC), and this is the soil with the lowest organic matter content (Table 1). Expressing adsorption as percentage retention of the amount added, those two soils with more organic matter content adsorb near 100% of the three antibiotics, independently of the concentration added (Fig. 1). However, soil 19Al, which is the one with less organic matter, shows a clear decrease in the percentage of adsorption as the concentration of antibiotic added increases, going from 90% to 30–42%, suggesting a progressive saturation of the adsorption sites. Fig. 1 also shows that the adsorption of the three TCs is relatively similar in all soils when the antibiotics were added in low doses. But from a certain concentration added, the differences become evident, with TC being the least adsorbed. In addition, for soils with high organic matter content, OTC and CTC barely show differences regarding adsorption, but for those soils with low organic carbon content (19AL, 51S and 6S) CTC adsorbs preferentially when the added concentrations are high, with up to 20% more adsorption than the other two TCs. This would indicate that, at the TCs concentrations tested, those soils with higher organic matter contents did not suffer saturation of adsorption sites, and TCs do not show effects of competition with each other. However, when the organic matter content is low, there is a competition in favor of CTC (which could also be related to its greater persistence in soil, as per Pikkemaat et al., 2016). Therefore, under these conditions (low organic matter content in soils) the three TCs compete for the same adsorption sites, also favored by the fact of all three having very similar values for pKa1, pKa2 and pKa3 (Hamscher et al., 2005; López-Peñalver et al., 2010). The higher affinity of CTC for reactive surfaces in the soil can also be related to structural aspects, such as the ionization of the functional groups dimethylamine and phenolic b-diketone, which is considered a relevant factor in the adsorption of TCs (Pils and Laird, 2007; Chang et al., 2009a, b). In fact, it is well known that the processes leading to antibiotics 4

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Fig. 1. Adsorption results (in mg kg−1, and in percentage) for the three TCs (OTC, CTC, and TC) added simultaneously, in the six A Limia (AL) and Sarria (S) soils studied (from above, left to right: 19AL, 3AL, 50AL, 51S, 6S, 71S). Average values for three replicates, with error bars indicating that coefficients of variation were < 5%.

was found among adsorption of each antibiotic and organic matter (in form of DOC) in the equilibrium solution (Table 2). For those soils with pH < 4.9, this could be related to a solubilization of organic matter as TCs adsorption increases. For soils with pH > 6.2, an exchange among negatively charged TCs and organic anions can also occur. Fig. S1

adsorption sites. This process does not occur in S soils, which have pH > 6.2, making more probable that TCs are in zwitterionic and/or anionic form, thus facilitating TCs adsorption by means of cationic bridges, without ion exchange. Also, in those four soils having less organic matter, a highly significant (p < 0.01) and positive correlation

Table 2 Correlations among adsorption of each antibiotic (OTC, CTC and TC), for each concentration added, and the pH and DOC values in the respective equilibrium solution, in the six A Limia (AL) and Sarria (S) soils studied. OTC Soil 19AL 3AL 50AL 51S 6S 71S

CTC pH −0.964** −0.904* −0.939** −0.590ns 0.225ns −0.586ns

DOC 0.939** 0.987** 0.790ns 0.987** 0.980** 0.335ns

Soil 19AL 3AL 50AL 51S 6S 71S

TC pH −0.978** −0.902* −0.948** −0.599ns 0.184ns −0.594ns

Significant at (*): p < 0.05; (**): p < 0.01; ns: not significant difference found. 5

DOC 0.943** 0.982** 0.818* 0.994** 0.991** 0.343ns

Soil 19AL 3AL 50AL 51S 6S 71S

pH −0.939** −0.874* −0.922** −0.532ns 0.273ns −0.555ns

DOC 0.923** 0.977** 0.770ns 0.977** 0.977** 0.312ns

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0.726 and 0.998 for Freundlich. Other authors have previously reported that TCs adsorption fits well with the Freundlich model (Zhang et al., 2010; Teixidó et al., 2012; Fernández-Calviño et al., 2015a, b; Li et al., 2015). Regarding the Langmuir model, the Qm parameter is clearly lower in soil 19AL (with low pH and low organic matter content) and, in general, higher in soils with higher organic C content and/or high pH values (soils 71S and 51S), indicating low probability of saturating TCs adsorption capacity for the latter (Febrianto et al., 2009). The Qm value follows the sequence TC < OTC < CTC, indicating higher affinity of CTC for the adsorption sites. These Qm values are between 2680.51 and 10627.91 μmol kg−1 (Table 3), being much higher than those previously reported by Teixidó et al. (2012) (between 587 and 4458 μmol kg−1), and somewhat lower than those indicated by Li et al. (2010) (between 12310.25 and 21339.16 μmol kg−1). In the Langmuir model, the KL parameter (related to the strength of interaction adsorbent/adsorbate), ranged from 0.032 to 0.47 L μmol−1. In previous studies, reported KL values were between 0.18 and 1.67 L μmol−1 (Teixidó et al., 2012), and between 0.038 and 0.067 L μmol−1 (Li et al., 2010). In the present study, KL values are 10 times higher in soil 71S (the one with the highest content in low crystallinity components, in addition to having a high organic matter content) than in the other five. Therefore, TCs bonds are stronger in soils with high contents in components with variable charge, which can be negatively charged, interacting through cationic bridges with the anionic groups of the CTs. The relevance of organic matter in these strong bonds is supported by the significant correlations (p < 0.001) of the KL parameter with C (r = 0.907) for TC, as well as with C (r = 0.972) and N (r = 0.942) for OTC, and again with C (r = 0.975) and N (r = 0.941) for CTC. Other correlations were obtained with N (r = 0.865, p < 0.05) for TC. Finally, correlations were also found with the C/N ratio for all three TCs (r = 0.791, 0.793, and 0.768, p < 0.10, for TC, OTC and CTC respectively). In the Freundlich model, the n parameter indicates the reactivity of the active sites in the adsorbent. Table 4 shows that, for the present study, n values are lower in AL soils than in S soils, especially for CT. In all cases, n value is lower than 1 (between 0.14 and 0.58), coincident with results previously reported by Teixidó et al. (2012). This is related to non-linear and concave adsorption curves, and therefore to a decrease in adsorption sites as the concentration of TCs added increases, and could be associated to heterogeneous adsorption surfaces, with high-energy sites being occupied first (Sukul et al., 2008). Although not found in this study, values of n > 1 would correspond to high energy adsorption sites (Khezami and Capart, 2005; Foo and Hameed, 2010), with high accessibility of sorbates to the surface of the adsorbents (Skopp, 2009). In the present work, the n parameter was correlated with different soil characteristics for each antibiotic. In relation to CT, significant correlations were obtained with Feox and exchangeable Al (r = 0.846, and r = −0.813, respectively, p < 0.05). It also correlated with pH(H2O) and pH(KCL) (r = 0.791, and r = 0.787, respectively, p < 0.10), and with Alox and Fepir (r = 0.721, and r = 0.743, respectively, p < 0.10). With respect to CTC, the n parameter also correlated significantly (p < 0.05) with pH(H2O) (r = 0.896), pH(KCL) (r = 0.898) and exchangeable Al (r = −0.816). Finally, for OTC, correlations were found with pH(H2O), pH(KCL) and exchangeable Al (r = 0.748, r = 0.779 and r = −0.782, respectively, p < 0.10). Thus, those soil parameters having the highest relation with the n value are pH and non-crystalline Fe and Al contents. The Freundlich KF parameter, related to the capacity of adsorption in multilayers, showed a wide range of variation (between 494 and 4420 Ln μmol1−n kg−1), much higher than that previously reported by Teixidó et al. (2012) (KF between 240 and 1601 Ln μmol1−n kg−1). These values are higher in those soils showing higher organic matter contents (50AL and 71S); in fact, a significant correlation (p < 0.01) was found between C and KF (r = 0.984, r = 0.989, and r = 0.983, for TC, OTC and CTC, respectively). In addition, Table 4 shows that KF values in competition (obtained from Eq. (4)) are always higher than

Table 3 Parameters of the Langmuir model relating to adsorption process for the three TCs (TC, OTC, and CTC) and the A Limia (AL) and Sarria (S) soils studied. Soil

Antibiotic

19AL

TC OTC CTC TC OTC CTC TC OTC CTC TC OTC CTC TC OTC CTC TC OTC CTC

3AL

50AL

51S

6S

71S

Langmuir parameters Qm (μmol kg−1) Error 2412.33 246.67 3016.21 284.45 3572.10 443.77 6187.22 1163.39 8784.94 1465.22 7266.55 1332.28 6821.05 1765.99 7921.75 1756.07 8322.30 2131.18 6094.51 583.70 9602.68 1189.57 10627.91 1064.82 6283.88 1991.41 8571.64 1609.59 6178.86 799.17 8175.84 589.99 8588.18 1108.38 9217.52 2314.47

KL (L μmol−1) 0.27 0.07 0.07 0.08 0.04 0.07 0.78 0.68 0.69 0.08 0.04 0.06 0.03 0.03 0.03 0.44 0.43 0.47

Error 0.15 0.03 0.04 0.05 0.02 0.04 1.12 0.76 0.70 0.02 0.01 0.01 0.02 0.01 0.01 0.09 0.18 0.32

R2 0.894 0.953 0.936 0.991 0.968 0.946 0.726 0.813 0.825 0.974 0.983 0.991 0.901 0.970 0.972 0.989 0.966 0.935

Qm: maximum adsorption capacity; KL: parameter related to the strength of interaction adsorbent/adsorbate; R2: coefficient of determination.

(Supplementary Material) shows infrared spectra for selected soils before and after adsorption of the three tetracycline antibiotics, evidencing modifications related to binding mechanisms after the adsorption process.

3.3. Adjustment of TCs adsorption to adsorption models The adsorption of the three antibiotics shows good adjustment to the Langmuir (Table 3) and Freundlich models (Table 4). Both equations satisfactorily explain TCs adsorption in five of the six soils studied, with R2 ranging between 0.726 and 0.991 for Langmuir, and between Table 4 Parameters of the Freundlich model relating to adsorption of the three TCs (TC, OTC, and CTC) in the A Limia (AL) and Sarria (S) soils studied. Soil

19AL

3AL

50AL

51S

6S

71S

Antibiotic

TC OTC CTC TC + TC OTC CTC TC + TC OTC CTC TC + TC OTC CTC TC + TC OTC CTC TC + TC OTC CTC TC +

OTC + CTC*

OTC + CTC*

OTC + CTC*

OTC + CTC*

OTC + CTC*

OTC + CTC*

Freundlich parameters KF (μmol kg−1)

Error

n

Error

R2

756.18 551.63 642.72 1334.64 1125.69 906.49 1081.75 1920.67 4088.29 4420.12 4050.86 10249.92 890.95 778.76 977.25 1425.08 494.00 593.83 541.83 880.25 2327.80 2560.60 2956.89 4596.01

45.94 29.78 40.75 66.86 110.78 143.84 189.83 271.37 1826.52 1712.49 1463.13 4462.77 35.37 147.03 81.09 167.99 228.01 180.54 175.57 387.49 142.39 172.08 480.47 198.83

0.26 0.34 0.36 0.33 0.38 0.48 0.43 0.44 0.146 0.17 0.25 0.18 0.44 0.54 0.59 0.52 0.49 0.56 0.48 0.52 0.51 0.45 0.49 0.48

0.01 0.01 0.02 0.01 0.03 0.04 0.05 0.03 0.17 0.15 0.18 0.13 0.01 0.05 0.03 0.03 0.12 0.08 0.08 0.09 0.03 0.03 0.11 0.02

0.994 0.997 0.997 0.999 0.991 0.987 0.983 0.997 0.726 0.813 0.825 0.951 0.987 0.983 0.996 0.998 0.925 0.967 0.960 0.983 0.990 0.992 0.955 0.999

KF: parameter related to the adsorption capacity; n: parameter related to the heterogeneity of the sorbent; Qd: maximum adsorption capacity; R2: coefficient of determination; * Obtained from Eq. 4. 6

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Table 5 Parameters of the Temkin model relating to adsorption of the three TCs (TC, OTC, and CTC) in the A Limia (AL) and Sarria (S) soils studied. Cases of poor fitting indicated by means of lowercase cursive figures. Soil

19AL

3AL

50AL

51S

6S

71S

Antibiotic

TC OTC CTC TC OTC CTC TC OTC CTC TC OTC CTC TC OTC CTC TC OTC CTC

Table 6 Fitting of adsorption results to Eqs. (5)–(7) (adapted from the Murali and Aylmore (1983) equation), using TC, OTC and CTC solutions in relations 1:1:1, with adsorbed antibiotic concentrations expressed in μmol kg−1 and antibiotic concentrations in the equilibrium solution expressed in μmol L−1.

Temkin parameters bt

Error

Kf (L/g)

Error

R2

6629.55 5234.53 5078.94 3518.43 2922.06 2610.27 3024.68 2336.28 1640.45 2527.06 2144.59 1768.32 2618.27 1800.48 2048.92 1582.58 1658.14 1349.50

39.91 49.48 74.93 133.69 193.26 188.91 941.73 915.51 550.79 124.68 236.85 228.58 242.78 246.10 166.20 111.43 183.50 379.86

6.82 2.34 4.50 10.73 7.14 4.44 116.54 50.12 12.20 2.13 2.21 2.34 0.74 0.71 0.45 6.63 9.07 6.34

3.53 0.98 2.97 8.86 6.58 3.39 934.52 264.05 18.26 0.84 1.40 1.00 0.57 0.32 0.16 1.14 3.46 3.57

0.988 0.986 0.970 0.954 0.931 0.962 0.884 0.922 0.985 0.978 0.942 0.961 0.945 0.968 0.982 0.992 0.984 0.975

Soil

Antibiotic

19 AL

TC (OTC + CTC); OTC (TC + CTC); CTC (TC + OTC); TC (OTC + CTC); OTC (TC + CTC); CTC (TC + OTC); TC (OTC + CTC), OTC (TC + CTC); CTC (TC + OTC); TC (OTC + CTC); OTC (TC + CTC); CTC (TC + OTC); TC (OTC + CTC); OTC (TC + CTC); CTC (TC + OTC); TC (OTC + CTC); OTC (TC + CTC); CTC (TC + OTC);

3 AL

50 AL

51 S

6S

71 S

Eq. Eq. Eq. Eq. Eq. Eq. Eq. Eq. Eq. Eq. Eq. Eq. Eq. Eq. Eq. Eq. Eq. Eq.

5 6 7 5 6 7 5 6 7 5 6 7 5 6 7 5 6 7

a

R2

3.55 0.25 −4.02 8.92 1.07 −7.68 36.75 −1.39 −75.41 28.25 0.86 −72.65 1.98 0.12 −1.13 81.35 6.23 −104.25

0.996* 0.997* 0.964* 0.996* 0.988* 0.984* 0.997* 0.999* 0.977* 0.992* 0.983* 0.976* 0.958* 0.971* 0.943* 0.978* 0.999* 0.969*

a: parameter related to competence among all three antibiotics; * Significant at p < 0.05.

bt: Temkin isotherm constant; Kt: Tempkin isotherm equilibrium binding constant (L/g); R2: coefficient of determination.

3.4. Desorption of the three tetracycline antibiotics in a ternary system

those corresponding to individual antibiotics, and KF scores are once again higher for soil 50L, the one with the highest carbon content. In addition, results for the Temkin equation are shown in Table 5. In this model, adsorption is considered to be characterized by uniform distribution binding energies up to the maximum level (Ofomaja and Unuabonah, 2013). The Temkin equation considers adsorption heat, assuming a linear decrease in adsorption energy with surface occupation, which is related to adsorbent-adsorbate interactions. In this work, the Temkin model explains adsorption for all three tetracycline antibiotics in most cases, with R2 ranging from 0.884 to 0.992, even if fitting is not so good for soil 50AL. The Temkin model is considered appropriate for chemical adsorption based on strong electrostatic interactions between positive and negative charges, which makes clear the relevance of chemisorption processes in most of the soils here studied, also taking into account previous comments from Gao et al. (2012) and Rajapaksha et al. (2015). This fact complements the information derived from Freundlich's n values, which were always < 1, indicating a parallel relevance of physical adsorption in all cases. Thus, physical adsorption would be clearly dominant is soil 50AL (the one with the highest carbon content), while both physical and chemical adsorption would be relevant in the other soils here studied. Furthermore, Table 6 shows the good adjustment of CTC-OTC-TC adsorption data to the multiadsorbate model of Murali-Aylmore, taking into account that R2 values ranged from 0.943 to 0.999, with p < 0.05. Regarding Table 6, as previously commented, higher a values indicate that lower amounts of antibiotic are adsorbed in situations of competence. The highest a values (and thus the lowest adsorption) were those corresponding to TC (Eq. (5)) in all soils. These a values also indicate that TC adsorption in competition is lower in the two soils with the highest carbon contents (soils 50Al and 71S), which would be due to higher competition and higher adsorption of the other two antibiotics. In the opposite side, CTC (Eq. (7)) shows the lowest a values, indicative of the fact that CTC competes favorably with the other two antibiotics (and mainly with TC), thus adsorbing more intensively. Finally, OTC (Eq. (6)) is in intermediate situation compared to TC and CTC. All that is coherent with results shown in Fig. 1, making clear the relevance of soil organic matter on competitive adsorption of the three tetracycline antibiotics here studied.

For all soils, desorption values were always negligible for the two lowest TCs concentrations added, increasing as the concentration of added antibiotic increases. The maximum desorption value was 850 μmol kg−1, found for OTC when the highest dose of the antibiotic was added (Fig. 2). Expressing desorption in percentage of antibiotic released, compared to the amount previously adsorbed, values are low (generally less than 10%) for all three TCs in all soils, indicating that TCs adsorption is not easily reversible for the added concentrations. It should be noted that those soils with most organic matter (50AL and 71S) show high adsorption and low desorption, making clear the important role of the organic components in the strong retention affecting TCs, preventing their release to the soil solution, to water bodies, and plant uptake. Fernández Calviño et al. (2015a) also found low desorption (< 15%) for these antibiotics from two crop soils from A Limia. In the present study, desorption percentage tends to a slight increase when increasing the dose of antibiotic added. This could be due to the fact that highenergy sites are occupied first when low concentrations of antibiotics are added, so that the resistance to desorption is greater (Zhang et al., 2010). OTC and TC desorb more than CTC (Fig. 2), which is in agreement with previous findings by Fernández-Calviño et al. (2015a). Desorption values corresponding to the highest TCs concentrations added, in each soil, were subjected to an analysis of bivariate correlations with soil characteristics. The results showed a positive correlation (p < 0.01) with pH(KCl) (r = 0.677), and a negative correlation (p < 0.01) with available P (r = −0.62). Therefore, TCs desorption would be favored by higher pH values. The negative correlation with available P could indicate a competition for the adsorption sites positively charged between phosphate anions and negatively charged TCs.

3.5. Comparison of TCs adsorption results in simple and ternary systems Firstly, the adsorption of each of the three TCs was compared between an individual system (for a concentration of 200 μmol L−1 of a single antibiotic), and a ternary system (all three TCs together, at the same concentration of 200 μmol L−1 each, reaching a total sum of 600 μmol L−1). Since the final concentration in the ternary system is 7

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Fig. 2. Desorption results (in mg kg−1, and in percentage) for the three TCs (OTC, CTC, and TC) added simultaneously, in the six A Limia (AL) and Sarria (S) soils studied (from above, left to right: 19AL, 3AL, 50AL, 51S, 6S, 71S). Average values for three replicates, with error bars indicating that coefficients of variation were < 5%.

600 μmol L−1, there will be different ionic strength with respect to the simple systems (with only one antibiotic at 200 μmol L−1). In a second phase, the simple and ternary systems were compared in situations where the ionic strength was the same, so that in the simple systems each of the TCs was added separately in a concentration of 200 μmol L−1, and in the ternary systems each antibiotic was added in a concentration of 66.67 μmol L−1, giving a final concentration of 200 μmol L−1. Fig. 3 shows the adsorption results of these experiments for the six soils studied. Simple systems show higher adsorption than ternary systems, both for situations with equal and different ionic strength (Fig. 3). For each antibiotic, differences in adsorption between simple and ternary systems are more pronounced when ionic strength is different. In simple systems, 100% adsorption is always reached in those soils having the highest organic matter contents (50AL and 71S), being always > 85% for the other four soils (19AL, 51S, 3AL and 6S) (Fig. 3). In the ternary system, adsorption is close to 100% for soils with high organic matter

content, but it decreases for soils having lower organic matter, reaching 47% when the ionic strength is greater than that of the simple systems, and up to 65% when the ionic strength is the same. The decrease in the adsorption of one antibiotic in the presence of another can be due to a competition for adsorption sites (López-Peñalver et al., 2010), which is enhanced in situations where ionic strength is higher (Sun et al., 2010). This would be due to the decrease in the ratio cationic/zwitterionic species, with the latter having lower affinity for negatively charged soil surfaces (Figueroa et al., 2004). 3.6. Comparison of TCs desorption results in simple and ternary systems After studying adsorption, desorption experiments were carried out for the three TCs in the same simple and ternary systems, with equal and different ionic strength. The results are shown in Fig. 4. Desorption percentages were generally low, especially in simple systems (always lower than 5%) (Fig. 4). In ternary systems, desorption is higher in 8

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Fig. 3. Percentages of adsorption for the three TCs (TC, OTC and CTC) in the six A Limia (AL) and Sarria (S) soils studied (19AL, 3AL, 50AL, 51S, 6S, and 71S) in simple systems (each antibiotic added individually) and in ternary systems (the three antibiotics added simultaneously), with different ionic strength, and with the same ionic strength. Average values for three replicates, with error bars indicating that coefficients of variation were < 5%.

reported values < 1% for TC desorption from soils. Comparing with other antibiotics, Białk-Bielińska et al. (2012) reported clearly higher desorption results for sulfadimethoxine (from 13.4 to 96.8%), and for sulfaguanidine (14.3–71.6%); whereas Hu et al. (2019) found desorption ranging from 30.3 to 52.1% for sulfadiazine, and from 43.7 to 48.3% for sulfamethoxazole. In addition, Rabølle and Spliid (2000) reported desorption values from 26 to 69% for tylosin (a macrolide). Regarding norfloxacin, ciprofloxacin and enrofloxacin (fluoroquinolones), Leal et al. (2012) found high retention, associated to desorption results < 0.22%.

situations of higher ionic strength, reaching up to 20% of the amount of antibiotic previously adsorbed. Desorption is favored in soils with less organic matter content and higher pH (soils 6S and 51S). Also, in ternary systems CTC desorption increases in lower degree than that of TC and OTC, confirming the lower affinity of these two antibiotics for adsorption sites. Fernández-Calviño et al. (2015b) compared results corresponding to competitive desorption of the same three tetracycline antibiotics from two A Limia soils with non-competitive experiments previously reported in Fernández-Calviño et al. (2015a), finding that desorption percentages were higher in competitive trials, as in the current work, making clear that competition among TCs affects to bindings onto high energy adsorption sites, favoring desorption and increasing hysteresis. Conde-Cid et al. (2019) found that desorption results for the same three tetracycline antibiotics from soils of the same geographical origin as those here studied were also very low. These authors compared their desorption results with previous studied, such as those performed by Pils and Laird (2007), and by Munira and Farenhorst (2017), who

3.7. Slurries, agricultural impacts and territorial management regarding TCs pollution Animal slurries spread on agricultural lands have been for decades a matter of concern regarding diffuse source pollution, mainly as regards some heavy metals, excess of nutrients favoring eutrophication, and pathogenic microorganisms, causing risks of soil and water pollution 9

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Fig. 4. Percentages of desorption for the three TCs (TC, OTC and CTC) in the six A Limia (AL) and Sarria (S) soils studied (19AL, 3AL, 50AL, 51S, 6S, and 71S) in simple systems (each antibiotic added individually), and in ternary systems (the three antibiotics added simultaneously), with different ionic strength, and with the same ionic strength. Average values for three replicates, with error bars indicating that coefficients of variation were < 5%.

(and low-cost, when possible) measures to fight this kind of high risk pollution.

(López-PeriagoNúñez-DelgadoDiaz-Fierros, 2000, 2002; NúñezDelgado et al., 1997, 2002). In fact, legislative regulations have been implemented at different scales (see for example USEPA, 2019; EU, 2019), and even some controversy is taking place at Spanish and Galician levels (Esperante-Paramos, 2019). Recently, hazards related to emerging pollutants (including antibiotics) have been considered increasingly relevant, and some legislation has been developed (Official Journal of the European Union, 2013, 2015; Geissen et al., 2015; Núñez-Delgado et al., 2019). Within antibiotics, tetracyclines are among the most used in veterinary medicine, and some of them are within the ten antibiotic compounds also approved for use as growth promoters (in addition to therapeutic utilization) in the USA (Daghrir and Drogui, 2013). Other large livestock producing and exporting countries where antibiotics are not prohibited for growth promotion are China and Brazil. However, antibiotics are banned for that use in the European Union (Lekagul et al., 2019). Any case, taking into account that antibiotics reach environmental compartments, thus supposing environmental and public health concerns, their fate should be further investigated at local and global levels, as well as scientifically sound

4. Conclusions The adsorption and desorption of the three tetracycline antibiotics studied (TC, OTC, and CTC) depends on the pH, but mainly on the soil organic matter content. As a result, TCs adsorption was close to 100%, and desorption very low, in soils where organic matter is abundant, both in simple systems (with a single antibiotic present), and in ternary systems (with all three antibiotics present simultaneously). In ternary systems, TCs adsorption and desorption is very similar for low doses of antibiotics added, while at high doses added a competition for adsorption sites takes place, favorable for CTC, which is the most adsorbed and the less desorbed compound. The results indicate an increased risk of TCs entering the food chain when high doses of the three antibiotics are incorporated simultaneously into soils, especially for those with low organic matter content, with CTC being the TC showing the lowest risk among the three studied. These results should be taken 10

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into account when managing and spreading animal slurries containing antibiotics as organic fertilizers.

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Declarations of interest None. Funding sources supporting the work described in the manuscript Funding This work was supported by the Spanish Ministry of Economy and Competitiveness [grant numbers CGL2015-67333-C2-1-R and CGL2015-67333-C2-2-R]. It also received funds from the European Regional Development Fund (ERDF) (FEDER in Spain), being a complement to the previous grants, without additional grant number. M. Conde-Cid holds a pre-doctoral contract (FPU15/0280, Spanish Government). The research of Dr. Gustavo F. Coelho was also supported by the Improving Coordination of Senior Staff (CAPES), Post-Doctoral Program Abroad (PDE)/Process number {88881.172297/2018-01} of the Brazilian Government. CRediT authorship contribution statement Manuel Conde-Cid: Investigation, Formal analysis, Methodology. Gustavo Ferreira-Coelho: Investigation, Formal analysis, Methodology. Avelino Núñez-Delgado: Supervision, Writing - review & editing. David Fernández-Calviño: Formal analysis, Methodology, Validation. Manuel Arias-Estévez: Funding acquisition, Project administration, Supervision, Validation, Writing - review & editing. Esperanza Álvarez-Rodríguez: Funding acquisition, Methodology, Project administration, Resources, Supervision, Validation, Writing original draft, Writing - review & editing. María J. FernándezSanjurjo: Supervision, Validation, Writing - original draft, Writing review & editing. Acknowledgements Funding This work was supported by the Spanish Ministry of Economy and Competitiveness [grant numbers CGL2015-67333-C2-1-R and CGL2015-67333-C2-2-R]. It also received funds from the European Regional Development Fund (ERDF) (FEDER in Spain), being a complement to the previous grants, without additional grant number. M. Conde-Cid holds a pre-doctoral contract (FPU15/0280, Spanish Government). The research of Dr. Gustavo F. Coelho was also supported by the Improving Coordination of Senior Staff (CAPES), Post-Doctoral Program Abroad (PDE)/Process number {88881.172297/2018-01} of the Brazilian Government. The sponsors had not involvement in study design; in the collection, analysis and interpretation of data; in the writing of the report, and in the decision to submit the article for publication. Appendix A. Supplementary data Supplementary data to this article can be found online at https:// doi.org/10.1016/j.envres.2019.108669. References Anastopoulos, I., Mittal, A., Usman, M., Mittal, J., Yu, G., Núñez-Delgado, A., Kornaros, M., 2018. A review on halloysite-based adsorbents to remove pollutants in water and wastewater. J. Mol. Liq. 269, 855–868. https://doi.org/10.1016/j.molliq.2018.08. 104. Anjum, H., Johari, K., Gnanasundaram, N., Ganesapillai, M., Arunagiri, A., Regupathi, I., Thanabalan, M., 2019. A review on adsorptive removal of oil pollutants (BTEX) from wastewater using carbon nanotubes. J. Mol. Liq. 277, 1005–1025. https://doi.org/ 10.1016/j.molliq.2018.10.105.

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