This is the accepted version of the article: Beltrán-Flores, Eduardo; Torán, Josefina; Caminal i Saperas, Glòria; [et al.]. «The removal of diuron from agricultural wastewaters by Trametes versicolor im- mobilized on pinewood in simple channel reactors». Science of the Total Environ- ment, Vol. 728 (August 2020), art. 138414. DOI 10.1016/j.scitotenv.2020.138414 This version is available at https://ddd.uab.cat/record/238000 under the terms of the license 1 The removal of diuron from agricultural wastewaters 2 by Trametes versicolor immobilized on pinewood in 3 simple channel reactors 4 Eduardo Beltrán-Floresa, Josefina Torána, Glòria Caminalb, 5 Paqui Blánqueza, *, Montserrat Sarràa. 6 a Departament d’Enginyeria Química Biològica i Ambiental, Escola d’Enginyeria, 7 Universitat Autònoma de Barcelona, 08193 Bellaterra, Barcelona, Spain. 8 b Institut de Química Avançada de Catalunya (IQAC) CSIC, Jordi Girona 18-26, 9 08034 Barcelona, Spain. 10 11 12 13 14 15 16 * Corresponding author. E-mail address: Paqui.Blanquez@uab.cat (P. Blánquez) 17 Abstract 18 The presence of pesticides in agricultural wastewater entails harmful risks to both the 19 environment and public health. In this study, two channel-type bioreactors with 20 Trametes versicolor immobilized on pinewood chips were evaluated in terms of the 21 removal efficiency of diuron from agricultural wastewater under non-sterile conditions. 22 First, both single and successive sorption processes of diuron on pinewood chips were 23 evaluated. The Freundlich model showed the best correlation in the sorption isotherm 24 study (R2 = 0.993; Δq = 5.245), but according to repeated sorption experiments, the 25 Langmuir model (R2 = 0.993; Δq = 5.757) was considered more representative. 26 Equilibrium was reached after approximately 48 h, and the Elovich kinetic model gave 27 the best fit with the experimental data. A packed-bed channel bioreactor (PBCB) was 28 found to be a remarkable alternative able to remove up to 94 % diuron from agricultural 29 wastewater during 35 d. However, periodic manual mixing was required to guarantee 30 an aerobic process, and a rotating drum bioreactor (RDB) was subsequently proposed 31 as an enhanced version. The RDB removed up to 61 % diuron during 16 d using 32 almost 7 times lower wood dose (152 g wood·L-1) than in the PBCB (1000 g wood·L-1). 33 Keywords: 34 Bioreactor, pesticide, low-cost sorbent, organic contaminant, fungal treatment 35 1. Introduction 36 Diuron is the common name of N-(3,4-dichlorophenyl)-N,N-dimethyl-urea, which is a 37 phenyl urea herbicide extensively used to control germinating grass, broadleaf weeds 38 and mosses. This compound inhibits photosynthesis by blocking electron transfer in 39 photosystem II in a broad spectrum of plants and photosynthetic microorganisms. 40 Diuron is applied to many crops, especially cereals, but also in non-agricultural areas 41 for the maintenance of railways, gardens, roads, parks, etc. (Giacomazzi and Cochet, 42 2004; Tixier et al., 2001). 43 The use of diuron can lead to serious environmental and public health problems due to 44 its high persistence and toxic effects on living beings. Diuron has a recalcitrant 45 structure with a half-life of approximately 328 d in soil (Jury et al., 1983). Once applied 46 to the target field, rainfall can deliver diuron through runoff and leaching from the 47 ground to nearby water bodies (Langeron et al., 2014; Rupp et al., 2006). Aquatic 48 organisms are especially susceptible to diuron exposure, but studies on animals have 49 also revealed carcinogenic effects of diuron on rats and cytotoxic and potentially 50 genotoxic damage in human cells (Huovinen et al., 2015). 51 The United States Environmental Protection Agency has also identified diuron as a 52 “known/likely” human carcinogen considering several types of carcinomas developed in 53 rats (US EPA, 2003). Diuron has been included in the list of Priority Substances in the 54 Field of Water Policy of the European Commission Directive 2000/60/EC (European 55 Commission, 2000). This directive urges the Member States to progressively reduce 56 the emission and release of such substances. It also demands compliance with the 57 European Commission Directive 98/83/CE, which requires Member States to meet the 58 concentration limit of 100 ng·L-1 for individual species of pesticides in water intended 59 for human consumption (European Commission, 1998). Accordingly, declining trends in 60 diuron concentrations have been detected in some areas(Palma et al., 2014), probably 61 partly due to the EC decision (Commission Decision 2007/417/EC) not to include 62 diuron in Annex I of Directive 91/414/EEC for authorized phytosanitary products in the 63 EU (European Commission, 2007). However, high concentrations have been recently 64 detected in natural water resources (Lapworth and Gooddy, 2006), especially near crop 65 fields and after rainfall, reaching values up to 150 ng·L-1 (Ccanccapa et al., 2016). 66 Conventional activate sludge process in wastewater treatment plants (WWTPs) is not 67 specifically designed to completely remove most pesticides [14]. In fact, poor removal 68 efficiencies (46.0 ± 16.3 %) have been typically obtained for diuron in WWTPs. Several 69 alternative treatments have been proposed to address these kinds of recalcitrant 70 compounds. They are commonly classified into physical, chemical and biological 71 treatments according to their elimination strategy. The first two groups of treatments 72 are frequently presented together as physico-chemical treatments due to the strong 73 relationship between these phenomena. Physico-chemical treatments mainly include 74 adsorption, advanced oxidation processes (ozonation, photocatalysis, etc.) and 75 membrane filtration (Marican and Durán-Lara, 2018). However, these technologies can 76 be unfeasible for treating micropollutants from wastewater since they can require 77 expensive regeneration processes, high energy or catalyst consumption, and additional 78 post-treatments of the rejected streams (Prieto-Rodriguez et al., 2012; Taheran et al., 79 2016) . 80 Among biological treatments, bioremediation using white-rot fungi (WRF) has been 81 proposed as a promising alternative to degrade a wide range of xenobiotics, such as 82 pharmaceutically active compounds (Haroune et al., 2014), polycyclic aromatic 83 hydrocarbons (Ding et al., 2013), personal care products (Rodarte-Morales et al., 84 2011), endocrine-disrupting chemicals (Cabana et al., 2007) and pesticides (Mir- 85 Tutusaus et al., 2014). In particular, Trametes versicolor is a fungus of special interest 86 for bioremediation purposes since it has an unspecific enzymatic system composed of 87 a family of ligninolytic extracellular enzymes (laccase and lignin, manganese and 88 versatile peroxidases) and the intracellular enzymatic system known as cytochrome 89 P450 (Asgher et al., 2008). 90 Despite the great potential of WRF, there is a critical drawback that can complicate its 91 implementation on an industrial scale. Treating real wastewater matrices under 92 nonsterile conditions negatively influences the enzymatic activity and survival of the 93 fungus due to pressure exerted by other microorganisms, mainly bacteria. Operating 94 under nonsterile conditions normally leads to shorter operation times and declines in 95 degradation performance (Mir-Tutusaus et al., 2016). 96 Different strategies have been adopted to favour the predominance of fungi against 97 bacteria, such as biomass renovation (Blánquez et al., 2006), adjustment of the C/N 98 ratio and pH (Badia-Fabregat et al., 2016), and fungus immobilization (Li et al., 2015), 99 among others. There are two types of immobilization strategies: autoimmobilization 100 (fungal pellets) and immobilization onto supports (Mir-Tutusaus et al., 2018). In 101 particular, immobilization on natural substrates, such as wood from timber industry 102 wastes, presents outstanding possibilities since such substrates can be used as low- 103 cost supports without adding any other source of nutrients. Wood substrates have a 104 complex structure that is highly resistant to bacterial attack. This structure is especially 105 convenient for the treatment of wastewater with a low organic content, such as 106 agricultural wastewaters, in which the addition of external nutrients is typically 107 mandatory (Torán et al., 2017). 108 The aim of this work was to study different channel-type bioreactors with pinewood 109 chips colonized by T. versicolor designed to remove diuron from real wastewater under 110 non-sterile conditions. For that purpose, sorption onto pinewood was first analysed by 111 both isotherm models and kinetics studies in batch mode and successive batch 112 sorption experiments. Then, wastewater spiked with diuron was treated in a simple 113 packed-bed channel bioreactor (PBCB) under non-sterile conditions. Finally, a rotating 114 drum bioreactor (RDB) incorporating automatic agitation was studied as an enhanced 115 version of the PBCB. 116 2. Materials and methods 117 2.1. Lignocellulosic material 118 Pinewood pallets were kindly provided by Timgad S.A. (Barcelona, Spain). The 119 pinewood pallets were fragmented into small pieces using a STERWINS Esh1-40.3 120 2500 W crushing machine. The obtained wood chips were sieved through two 121 standardized meshes of 16 and 7.10 mm, selecting the middle fraction. The resulting 122 wood chips were completely submerged in tap water and autoclaved at 120 ºC for 30 123 min, to later discard the free water. 124 The bulk density of the wood (ρb) was calculated according to the standardized method 125 ASTM D7481 – 18 (ASTM, 2018). The volume occupied by 50 g of wood chips (ms) 126 was measured in a 500 mL graduated cylinder. Then, the bulk density was obtained 127 using Eq. (1). 𝑚𝑠 128 𝜌𝑏 = 𝑉𝑏 (1) 129 To calculate the bed porosity of the wood chips, a defined mass of tap water (mw), 130 which was converted into volumetric units (Vw), was poured into the graduated cylinder 131 until the wood chips were completely submerged. The bed porosity was calculated by 132 Eq. (2). 𝑉𝑤 133 𝜙= 𝑉𝑏 (2) 134 2.2. Agricultural wastewater 135 Wastewater samples were collected from an agricultural drainage channel in the 136 Llobregat River Basin (Catalonia, Spain). These samples were collected in two different 137 periods of time, for the PBCB experiments in June 2017, and for the sorption and the 138 RDB experiments in September 2018. The agricultural wastewater was spiked with 6 139 ppm, 8 ppm and 10 ppm diuron for the single batch, successive sorption and 140 bioremediation experiments, respectively. The wastewater was stored at 4 ºC. 141 2.3. Chemicals and reagents 142 Diuron was purchased from Sigma Aldrich (Barcelona, Spain). Malt extract was 143 acquired from Scharlau (Barcelona, Spain). High-performance liquid chromatography 144 (HPLC) grade acetonitrile was supplied by Merck (Darmstadt, Germany). All chemical 145 used were of high purity grade. 146 2.4. Fungal strain and culture conditions 147 T. versicolor (ATCC 42530) was purchased from the American Type Culture Collection. 148 The fungus was maintained by subculturing in agar plates of malt extract (2 % w/v) at 149 25 °C every 30 d. A mycelial suspension of T. versicolor was prepared according to 150 Blánquez et al. (Blanquez et al., 2004). 151 The prepared mycelial suspension of T. versicolor was inoculated on the wood chips 152 (0.25 mL mycelial suspension·g wood-1) inside a polyvinyl chloride box covered with 153 aluminium foil. Cultures were incubated during 9 and 20 d at 25 ºC before the PBCB 154 and RDB treatments, respectively. 155 2.5. Sorption and kinetic studies 156 Various amounts of pinewood sorbent (5, 10, 20, 30, 40 and 60 g) were added to a 157 series of 1 L Erlenmeyer flasks that were previously filled with 200 mL spiked 158 wastewater. Spiked wastewater was initially adjusted to pH 4.5. A continuous orbital 159 agitation of 135 rpm and a constant temperature of 25 ºC were maintained for almost 3 160 d (70 h) until equilibrium was reached. The remaining pesticide concentrations were 161 analysed by HPLC in defined intervals of time. 162 Eq. (3) and Eq. (4) were used to calculate diuron sorption at any time t and at 163 equilibrium respectively: (𝐶0 −𝐶𝑡 ) 𝑉 164 𝑞𝑡 = 𝑚 (3) (𝐶0 −𝐶𝑒 ) 𝑉 165 𝑞𝑒 = 𝑚 (4) 166 where C0, Ct and Ce (mg·L-1) are the diuron concentrations at initial time, any specific 167 time t, and at equilibrium respectively, V (L) is the solution volume and m (g) is the 168 wood mass used in each experiment. 169 Successive sorption cycles were performed by repeating the batch mode experiment 170 for m = 20 g of wood. The wood chips were strained at the end of each cycle to be later 171 reused in the following batches. The same C0 and operating conditions were 172 maintained in all cycles. 173 2.6. Packed bed channel bioreactor 174 The PBCB was constructed with a polyvinylchloride gutter (length x diameter: 50.5 x 11 175 cm). Two channels were operated in parallel: the control one with pinewood, and the 176 inoculated one with pinewood colonized with T. versicolor. In both cases, 1 kg wood 177 and 1 L wastewater were used (dose of 1000 g·L-1). A hydraulic retention time (HRT) of 178 3 d was employed. 179 The PBCB inlet and outlet were located at each of the reactor sides. Two different 180 experiments were performed using the PBCB: one PBCB experiment with spiked tap 181 water (10 ppm) and another PBCB experiment with spiked wastewater (10 ppm). 182 Wastewater was continuously pumped from the influent tank, which was mixed by a 183 magnetic stirrer, to the reactor, and then pumped out to the effluent tank. Samples 184 were collected from the effluent tank, and filtered and analysed by HPLC as described 185 in Section 2.8. The pH was initially adjusted to 4.5 and monitored at different points of 186 the system. No additional substrate or nutrient was added to the reactor. 187 2.7. Rotating drum bioreactor 188 The RDB was constructed using the same polyvinylchloride channel presented in 189 Section 2.6. However, an additional inner tube of methacrylate was located in the 190 center of the longitudinal axis of the channel. The wood chips were placed inside the 191 internal tube, while the wastewater was contained inside the channel. The tube was 192 provided with multiple holes of 8 mm diameter to allow the contact between the wood 193 chips and the wastewater. Approximately 30 % of the internal tube volume was 194 submerged in the liquid phase, while the remaining volume was in direct contact with 195 the air. The inner tube was connected to a 12 V electric motor (Worm Gear Motor; 196 model: 4632-370) that was operated at a constant rotation speed of 6 rpm. The 197 wastewater was continuously pumped from the influent tank to one RDB side, and the 198 effluent stream was drained by overflow from the other RDB side. The RDB was 199 equipped with a pH controller to adjust the pH between 4.3 – 4.7 by adding either 1 M 200 HCl or 1 M NaOH when required. The system was continuously operated with an HRT 201 of 3 d. 202 2.8. Pesticide analysis from liquid phase 203 1 mL liquid samples were periodically taken from the effluent tanks, filtered through 204 Millipore Millex-GV PVDF filters of 0.22 µm and introduced in amber vials for HPLC 205 analysis. A Dionex Ultimate 3000 HPLC was used to determine diuron concentrations 206 of the liquid samples. The HPLC was equipped with a UV detector working at 254 nm. 207 The separation was performed in a C18 reversed-phase column (Phenomenex®, 208 Kinetex® EVO C18 100 Å, 4.6 mm × 150 mm, 5 μm) at constant 30 ºC. The initial 209 composition of the mobile phase was 35 % acetonitrile and 65 % solution of 0.1 % 210 formic acid in MilliQ water. Then, the acetonitrile composition raised in ramp to 45 % 211 during the first 15 min. A total sample volume of 40 µL was injected at a constant flow 212 rate of 0.8 mL·min-1. 213 2.9. Routine analysis 214 Laccase activity was determined through the oxidation of 2.6-Dimethoxyphenol (DMP) 215 by laccase enzyme (Cruz-Morató et al., 2013). The absorbance was measured by a 216 UNICAM 8625 UV/VIS spectrometer at 650 nm, and the conductivity was analysed 217 using a CRISON MicroCM 2100 conductometer. The heterotrophic plate count (HPC) 218 was measured per triplicate according to the APHA standard (APHA, 1995). The 219 chemical oxygen demand (COD) and the ammonia concentration were determined 220 through commercial kits LCK114 or LCK314m and LCH303, respectively (Hach Lange, 221 Germany). 222 2.10. Isotherm and kinetic equations 223 The Langmuir, Freundlich and Temkin isotherm models are expressed by Eq. (5-8): 𝑞𝑚𝑎𝑥 𝐾𝐿 𝐶𝑒 224 Langmuir equation: 𝑞𝑒 = (5) 1+𝐾𝐿 𝐶𝑒 1/𝑛 225 Freundlich equation: 𝑞𝑒 = 𝐾𝐹 𝐶𝑒 (6) 𝑞𝑚𝑎𝑥 226 𝐾𝐹 = 1/𝑛 (7) 𝐶0 227 Temkin equation: 𝑞𝑒 = 𝐵 ln(𝐴𝐶𝑒 ) (8) 228 where qe is the sorbed diuron per gram of wood (mg·g-1) at equilibrium, qmax the 229 Langmuir maximum sorption capacity (mg·g-1), KL the sorption energy (L·mg-1), Ce the 230 diuron concentration at equilibrium (mg·L-1), KF the sorption capacity (units depend on 231 n), C0 the initial diuron concentration (mg·L-1), n the intensity of the sorption (unitless), 232 and B = RT/A, being R the ideal gas constant (8.314 J·mol−1·K−1), T the temperature 233 (K) and A is the Temkin equilibrium constant (L·mg-1). 234 Pseudo-first, pseudo-second, Elovich and intra-particle diffusion (IPD) kinetic equation 235 are shown in Eq. (9-12). 236 Pseudo-first order equation: 𝑞𝑡 = 𝑞𝑒 (1 − 𝑒 −𝑘1 𝑡 ) (9) 𝑘 𝑞𝑒2 𝑡 237 Pseudo-second order equation: 𝑞𝑡 = 1+𝑘2 (10) 2 𝑞𝑒 𝑡 238 Elovich equation: 𝑞𝑡 = 𝑏 ln(𝑎𝑏𝑡) (11) 239 Intra-particle diffusion equation: 𝑞𝑡 = 𝐾𝑖𝑑 𝑡1/2 + 𝐶 (12) 240 where qt is the diuron sorbed per gram of wood (mg·g-1) at any time t (h), k1 is the 241 pseudo-first rate constant (h-1), k2 the pseudo-second rate constant (g·mg-1·h-1), a the 242 sorption rate at the beginning of the process (mg·g-1·h-1), b is a coefficient related to the 243 surface coverage and activation energy (mg·g-1), Kid is the intra-particle diffusion rate 244 constant (mg·g-1·h-1/2) and C the intercept. 245 3. Results and discussion 246 3.1. Relation between contact time and diuron sorption 247 The apparent and true bulk densities were estimated to be 0.17 g·mL-1 ± 0.01 and 0.55 248 g·mL-1 ± 0.03, respectively, by Eq. (1). A pinewood porosity of 69.3 % ± 2.4 % was 249 obtained using Eq. (2). These results are consistent with previous works (Kim et al., 250 2016; Vo et al., 1995). 251 Fig. 1 shows the curves of diuron sorption on pinewood chips over time. The system 252 approached equilibrium in approximately 48 h for all sorbent amounts added (5, 10, 20, 253 30, 40, and 60 g). As expected, higher wood doses increased overall diuron elimination 254 but decreased the saturation rate per unit of wood. Diuron sorption onto pine chips was 255 mainly attributed to the chemical affinity that hydrophobic pesticides have for organic 256 components of wood, such as lignin (Rodríguez-Cruz et al., 2009). 257 258 Fig. 1. Effect of contact time on diuron sorption for several sorbent doses at 25 ºC (C0 = 259 6 mg·L-1) 260 Diuron was quickly sorbed onto external vacant sites at the beginning of the 261 experiment. Then, as the most superficial sites were filled, diuron molecules diffused 262 into the inner available sites of the chips, slowing the overall rate of sorption (Baccar et 263 al., 2012). 264 Table 1. Parameters, correlation coefficients and errors of Langmuir, Freundlich and 265 Temkin isotherm models for diuron sorption onto pinewood chips at 25 ºC Isotherms Parameters Langmuir KL (L·mg-1) qmax (mg·g-1) R2 Δq (%) Langmuir-1 0.057 0.548 0.993 5.782 Langmuir-2 0.046 0.677 0.423 5.758 Langmuir-3 0.112 0.305 0.387 7.200 Langmuir-4 0.043 0.711 0.387 5.789 Langmuir-5 0.051 0.610 0.993 5.757 Freundlich n qmax (mg·g-1) R2 Δq (%) 1.085 0.154 0.993 5.245 Temkin A B R2 Δq (%) 2.113 0.044 0.938 13.637 266 267 Significantly lower qt values were obtained compared to other studies using similar 268 carbon-based materials (De Gisi et al., 2016). However, this result was attributed to the 269 higher wood-wastewater mass ratio used in the present work. 270 3.2. Sorption isotherms 271 The experimental equilibrium data were fitted to several isotherm models, which 272 describe possible sorption mechanisms and facilitate the subsequent design of the 273 sorption process. The Langmuir, Freundlich and Temkin models were investigated. The 274 isotherm equations were also linearized and plotted to determine the most 275 representative model and its characteristic parameters from the slope and intercept. 276 Five different Langmuir linear forms were used since significant variations in their fits 277 and parameter values were previously reported (Baccar et al., 2013). The linear forms 278 of the isotherms are available in Table S1 of the Supplementary material. 279 The Langmuir model proposes sorption on finite sites and the formation of a single 280 monolayer without chemical interaction among sorbate molecules. Moreover, the 281 empirical Freundlich model considers sorption on heterogeneous surfaces and is more 282 suitable for low concentrations (Appel, 1973). Finally, the Temkin isotherm model 283 assumes chemical interactions among molecules and a linear decrease in binding 284 energy as vacant sites are filled. 285 The linear correlation coefficient R2 and the normalized standard deviation Δq (%) were 286 used to evaluate the correlation between the experimental data and the sorption 287 isotherms. Δq is described by Eq. (13). 𝑞𝑒𝑥𝑝 −𝑞𝑐𝑎𝑙 2 ∑( ) √ 𝑞𝑒𝑥𝑝 288 ∆𝑞(%) = 100 𝑁−1 (13) 289 where qexp and qcal are the experimental and calculated amounts of diuron sorbed at 290 equilibrium, respectively, and N is the number of measurements. A higher R2 indicates 291 a better fit between the linear form and the experimental data. Furthermore, a lower Δq 292 represents a stronger correlation between the experimental and predicted data (Baccar 293 et al., 2013). 294 Table 1 summarizes the main parameters and fit coefficients of the isotherm models. 295 Although Langmuir-1, Langmuir-5 and Freundlich presented the highest R2 (0.993), the 296 Freundlich model exhibited a slightly lower Δq (5.245 %) and was thus considered to 297 be the best model describing the equilibrium data. The Freundlich isotherm has been 298 selected to represent pesticide sorption on carbon-based sorbents in previous studies 299 (Laohaprapanon et al., 2010; Rodriguez-Cruz et al., 2007). Regarding the Freundlich 300 parameters, a significantly low qmax of 0.154 mg·g-1 was estimated with Eq. (7), but this 301 value was in good agreement with those reported in the literature (Iqbal and Ashiq, 302 2007). Nevertheless, a further discussion of the resulting qmax is proposed in Section 303 3.4. The parameter 1/n is related to the sorption susceptibility of the system and can 304 indicate favourable (0 < 1/n <1), difficult (1/n > 1) or irreversible sorption (1/n = 0) 305 (Yang et al., 2017). In this case, 1/n revealed favourable sorption (1/n = 0.922) of 306 diuron onto pinewood chips. 307 3.3. Sorption kinetics 308 Sorption kinetics provide valuable information, such as the solute uptake rate and the 309 reaction pathway, which allows the subsequent design and scale-up of a sorption 310 system. The pseudo-first- and pseudo-second-order, intraparticle diffusion (IPD) and 311 Elovich models were tested. The kinetic linear and non-linear equations of these 312 models are shown in Table S2 of the Supplementary material. The pseudo-first and 313 pseudo-second-order models consider chemisorption to be the dominant mechanism. 314 In contrast, the IPD model identifies diffusion as the rate-limiting step. Between these 315 two opposing models, the Elovich model describes intermediate behaviour with no 316 clearly dominant mechanism (Wu et al., 2009). 317 The linear forms of these models were plotted to obtain the particular parameters of 318 each model from the slope and the intercept. The best correlation to the experimental 319 data was again selected according to R2 and Δq. The fitting results for the kinetic 320 models are presented in Table S3 of the Supplementary material. Although the 321 pseudo-second order model gave the highest R2 fits for all sorbent doses, the Elovich 322 model more accurately described the experimental data based on Δq. The sole 323 exception was for m = 5 g; in this case, the IPD model showed a better fit. 324 Nevertheless, this result could be because the system did not fully reach equilibrium for 325 m = 5 g in the period of time under study. It is probable that with a longer period of 326 time, the system would reach complete equilibrium, and the Elovich model would 327 provide the best fit. The Elovich model is appropriate for heterogeneous sorbents and 328 liquid-solid systems, and it recognizes the effect of surface coverage on the sorption 329 rate over time. Moreover, the values of the kinetic parameters are in agreement with 330 previous studies of micropollutant sorption on porous carbon-based materials (Emeniru 331 et al., 2017; Tseng et al., 2003). 332 3.4. Effect of successive sorption cycles on the sorption capacity 333 Successive sorption experiments were performed to verify the real sorption capacity of 334 pinewood and to compare it to the qmax predicted by the Freundlich model. In addition, 335 this system can represent real scenarios of sorption processes in continuous mode, 336 with low solute concentrations and high sorbent doses. In this study, seven cycles in 337 batch mode were completed by retaining the initial 20 g of pinewood chips and re- 338 suspending the chips in 0.2 L new spiked wastewater at 8 ppm. The cumulative 339 sorption of diuron is shown in Fig. 2. 340 341 Fig. 2. Effect of repetitive cycles in batch on diuron sorption over contact time 342 In this case, a higher concentration of 8 ppm instead of 6 ppm was used to guarantee 343 diuron detection in the HPLC (lower limit of detection of 0.5 ppm). As expected, 344 increasing the initial diuron concentration led to higher sorption on the wood chips 345 compared to that in the batch sorption process presented in Section 3.1 (0.05 instead 346 of 0.04 mg·g-1). Once equilibrium was reached in the first batch of the successive 347 sorption experiment, the treated wastewater was discarded, and a new 0.2 L sample of 348 wastewater spiked with 8 ppm diuron was poured inside the same Erlenmeyer flask to 349 start the second batch. In the second batch, the wood could sorb more diuron from the 350 wastewater. This result indicated that the wood had reached equilibrium in the first 351 batch but its sorption capacity was not exhausted. The same process was repeated for 352 7 cycles. Although the sorption capacity of the wood was reduced with each new cycle, 353 the wood was not completely saturated after 7 cycles. 354 Note that the Freundlich model estimated a qmax of 0.154 mg·g-1, but this level was 355 exceeded after 4 cycles. The Freundlich model was initially selected because it 356 provided the best fit based on the R (0.993) and Δq (5.757 %) values obtained in the 357 batch experiment. However, the results of the successive batch process revealed that 358 the Freundlich model could not accurately predict qmax. In fact, qmax is conventionally 359 determined from the Langmuir model instead of by applying Eq. (7) to the Freundlich 360 model (Baccar et al., 2013). In this study, the Langmuir model (Langmuir-5) obtained 361 the same R and a Δq (5.245 %) insignificantly higher than that in the Freundlich model 362 in the batch experiment. Since the Langmuir model showed a suitable fit, its estimated 363 qmax was also compared to the experimental data. Langmuir-5 provided a qmax of 0.610 364 mg·g-1, which was more consistent with the findings of the successive sorption 365 experiment. For that reason, the Langmuir and not the Freundlich model was selected 366 as the most representative isotherm for the sorption system. 367 3.5. Packed-bed channel bioreactor treating diuron in spiked tap water 368 The PBCB was proposed as an alternative technology to the trickling packed-bed 369 reactor used by Torán et al. (Torán et al., 2017) to facilitate future applications in crop 370 fields. Continuous long-term treatment was initially conducted with spiked tap water to 371 evaluate diuron removal under relatively aseptic conditions. Tap water was spiked with 372 10 ppm diuron to allow the detection of the remaining diuron by HPLC. Two channels 373 were operated in parallel with the same initial conditions. One channel was loaded with 374 wood chips to evaluate the contribution of the sorption process. The other channel was 375 filled with wood chips previously colonized by T. versicolor. The biodegradation effect 376 was deduced by comparing the control and the inoculated PBCBs. 377 Fig. 3 shows the diuron removals for both the control and inoculated PBCBs. White 378 columns represent the overall removals obtained in the control PBCB, while the sum of 379 the white and grey bars shows the overall removals in the inoculated PBCB. Grey 380 columns indicate biodegradation at each time. Biodegradation rates were calculated as 381 the differences between the overall removals of the control and the inoculated PBCBs. 382 383 Fig 3. Relative removal profiles of diuron in the PBCB for spiked tap water. In white, 384 diuron elimination in the control reactor. The entire columns (sum of the white and grey 385 columns) represent the overall removals of the inoculated bioreactor. In grey, the 386 biodegradation contribution obtained in the inoculated bioreactor. In all cases, errors of 387 less than 3 % diuron removal were obtained (standard deviation of triplicates). 388 The average diuron removals were 89 ± 4 % and 69 ± 11 % after 49 d for the 389 inoculated and control reactors, respectively (Fig. 3). There was overall 20 % higher 390 diuron removal in the inoculated channel, which was associated with fungal 391 bioremediation, as indicated by the grey column portions in Fig. 3. In addition, the 392 diuron removal trend showed a more pronounced decline in the case of the control 393 channel, which can be observed in the removal evolution over time in Fig. 3. In fact, an 394 even higher removal difference was observed at the end of the treatment, reaching up 395 to 30 % more elimination in the case of the inoculated channel. 396 In this experiment, the wood substrate served not only as a single source of nutrients 397 for T. versicolor but also as a support for fungus immobilization and as an effective 398 sorbent for diuron removal. In addition, the wood substrate provided enough nutrients 399 to ensure fungus survival and the co-metabolic biodegradation of diuron (Liang Jiwei 400 Wen Dawen Gao, 2011; Mir-Tutusaus et al., 2018). 401 3.6. Packed-bed channel bioreactor treating diuron in spiked real 402 wastewater 403 The same system used in Section 3.5 was employed to treat real wastewater spiked 404 with diuron (10 ppm) to evaluate the effect of a real matrix on the removal rate of the 405 inoculated system. No interference was observed between the HPLC chromatograms 406 of the spiked tap water and spiked real wastewater. No diuron (above 0.5 ppm) was 407 initially detected in the original wastewater matrix. Fig. 4 shows the evolution of the 408 diuron removal over time. An average diuron removal of 94 ± 5 % was obtained for the 409 inoculated reactor during 35 d of treatment. In this case, the same removal results 410 obtained for the control reactor in the tap water treatment were used to represent the 411 control contribution in the wastewater treatment (see Fig. 4), since negligible variations 412 were expected (Mahmoud et al., 2016). A significant difference in diuron removal was 413 detected between the inoculated and control reactors throughout the treatment, and it 414 was attributed to biodegradation by T. versicolor. Note that the maximum removal 415 divergence was obtained at the end of the process, when the sorption capacity was 416 considerably reduced for the control reactor but the elimination rate of the inoculated 417 reactor remained stable. 418 419 Fig. 4. Relative removal profiles of diuron in the PBCB for spiked wastewater. In white 420 colour, diuron elimination in the control reactor. The entire columns (sum of the white 421 and grey columns) represent the overall removals of the inoculated bioreactor. In grey, 422 the biodegradation contribution obtained in the inoculated bioreactor. The pH and 423 laccase levels are indicated with triangles and circles, respectively. In all cases, errors 424 of less than 3 % diuron removal and 2 % laccase level were obtained (standard 425 deviation of triplicates). 426 Higher diuron degradation was obtained in the wastewater treatment compared to the 427 tap water experiment. This difference was attributed to synergistic cooperation between 428 autochthonous microorganisms in the wastewater and T. versicolor. Similarly, 429 Ellegaard-Jensen et al. (Ellegaard-Jensen et al., 2014) demonstrated that the 430 cooperative catabolism of certain fungal-bacterial consortia improved the degradation 431 efficiency of diuron. 432 In addition, the laccase level was monitored as an indicator of the enzymatic activity of 433 T. versicolor. A laccase peak of 62 AU·L-1 was detected on the 5th day and then 434 decayed to approximately 30 AU·L-1 and 4 AU·L-1 after 17 and 35 d, respectively. 435 However, the degradation profile of diuron did not follow the same negative trend, 436 indicating that laccase was probably not involved in the degradation of this pesticide 437 (Coelho-Moreira et al., 2013). 438 A pH of 7.9 was initially measured for the real wastewater. Since the optimal pH range 439 for T. versicolor is between 4.3 and 4.7, the pH of the influent tank was initially adjusted 440 to 4.5. However, T. versicolor progressively acidified the medium (Tavares et al., 2006) 441 to 3.8 at day 11. Consequently, the pH of the inlet was increased to 5.5 to maintain the 442 optimal pH range in the channel. However, the pH again decreased below the lower 443 limit of the optimal range for the fungus at day 21, and the pH of the influent was 444 readjusted to 6.5 until the end of the treatment to maintain a pH of approximately 4.5. 445 No significant differences in absorbance, CFU number, ammonia concentration, TSS or 446 COD were observed during the treatment (Table S4 of the Supplementary material). 447 The development of bacterial communities is considered a critical point in fungal 448 treatments (Yang et al., 2013), but fungal immobilization on pine chips proved to be an 449 excellent technique to deal with bacterial growth, preventing fungal inhibition. 450 The PBCB of pinewood colonized by T. versicolor showed high efficiency of diuron 451 removal in a continuous long-term treatment. Although manual mixing of inoculated 452 wood chips was a good strategy to preserve aerobic conditions and thus the enzymatic 453 activity and degradation capacity of T. versicolor, this step should be substituted by an 454 automated system. 455 3.7. Rotating drum bioreactor treating diuron in spiked real wastewater 456 Based on the excellent performance shown by the PBCB, an RDB was proposed to 457 automatize the treatment process. Manual mixing was replaced by continuous and 458 automatized rotation of the RDB internal tube, which was provided by an electric motor. 459 In addition, the output pumps were discarded, and the effluent left the reactor by 460 overflow. Fungal RDBs have been previously used for enzyme production (Colla et al., 461 2017; Domínguez et al., 2001) and biological desulfurization (Şener et al., 2018), and 462 a similar rotating drum biological contactor of white-rot fungus has been applied for 463 decolorization (Šíma et al., 2016). Recently, rotating biological contactors containing 464 immobilized T. versicolor were implemented to remove pharmaceutical micropollutants 465 from urban wastewaters (Cruz del Álamo et al., 2020). However, this is the first time 466 that a fungal RDB has been used for micropollutant treatment of real wastewaters. An 467 incubation time of 9 d was required to completely cover the wood surface with T. 468 versicolor before using the immobilized fungus in the PBCB. A higher incubation time 469 was used in the RDB (20 d) compared to the PBCB (9 d) to improve fungal 470 immobilization. 471 Continuous agitation at 6 rpm was initially employed to ensure enough oxygen diffusion 472 and perfect mixing inside the tube-shaped reactor. However, T. versicolor was 473 progressively detached from the wood surface during treatment, probably due to the 474 generation of significant shear forces that damaged the mycelial structure of the fungus 475 (Zhong, 2010). This fact indicated that the rotation speed was too high to maintain 476 fungal immobilization on the pinewood over time. The rotation speed also produced 477 foam inside the inoculated reactor, which has been identified as a major issue in fungal 478 treatments (Espinosa-Ortiz et al., 2016). 479 Nonetheless, the average diuron elimination was again slightly higher for the inoculated 480 reactor (61 % ± 3 %) than for the control reactor (55 % ± 7 %), as shown in Fig. 5. 481 Diuron removal decreased over time for the control reactor, which was probably due to 482 wood saturation (Torán et al., 2017). In contrast, the removal rate of the inoculated 483 reactor was more stable, remaining above 60 % after 16 d of treatment. A significant 484 difference of up to 20 % in diuron removal was achieved at the end of the process. The 485 process was stopped after 16 d because it seemed that T. versicolor had been 486 significantly removed from the substrate surface. 487 488 Figure 5. Diuron removal profiles for the inoculated (black dots) and the control (white 489 dots) RBDs, laccase activity (black rhombuses) and pH evolution (white squares) for 490 inoculated RDB. In all cases, errors of less than 3 % diuron removal and 2 % laccase 491 level were obtained (standard deviation of triplicates). 492 A lower mean removal was observed compared to that obtained with the PBCB, even 493 between the control reactors. This difference was mainly attributed to the different 494 wood/wastewater doses used between the PBCBs and the RBDs. For the RBDs, an 495 almost 7 times lower dose was used (152 g·L-1), but diuron removal did not decrease 496 proportionally, and only a mean reduction of 14 % was obtained between the control 497 reactors. This difference was probably due to the more efficient contact between the 498 wood chips and the wastewater driven by the continuous rotation. It has been 499 demonstrated that the agitation speed modifies not only the sorption kinetics but also 500 the sorption equilibrium of organic compounds on carbon-based materials (Kuśmierek 501 and Świątkowski, 2015). A higher removal efficiency was obtained by Torán et al. 502 (Torán et al., 2017) when working with immobilized T. versicolor on pine chips in a 503 packed bed reactor for ibuprofen (90 %) and ketoprofen (80 %) removals, but a similar 504 removal efficiency was obtained for naproxen (60 %). Nevertheless, in that case, a 505 higher dose of 240 g wood·L-1 wastewater was also employed. 506 Laccase was measured as an indicator of fungal activity, and it was reduced from 41 507 AU·L-1 to almost zero after 16 d. However, the lack of laccase was not accompanied by 508 lower elimination rates of diuron over time. This result is quite typical in fungal 509 treatments because cytochrome P450 generally plays a more important role in the 510 degradation of micropollutants (Marco-Urrea et al., 2009). Similar laccase levels and 511 evolution over time were also detected by Torán et al. when working with Trametes 512 versicolor immobilized on wood chips (Torán et al., 2017). 513 The initial pH of the wastewater was not adjusted for the RDB at the beginning of the 514 treatment. This decision was based on the natural ability of T. versicolor to acidify the 515 medium observed during the PBCB experiment. As shown in Fig. 5, the pH was 516 progressively reduced during the first days of the process. However, pH control was 517 established in the range of 4.3 to 4.7 on day 5 to ensure optimal operational conditions 518 for T. versicolor to reverse and attenuate the fungal losses derived from the high 519 rotation speed. 520 The HPC increase for the RDB was slightly higher than that for the PBCB; HPC rose 521 from an initial 4.8·104 ± 2.7·104 CFU·mL-1 to 5.4·105 ± 5.0·104 CFU·mL-1 after 16 d 522 (Table S5, Supplementary material). This greater bacterial proliferation was probably 523 associated with both the lower wood/wastewater dose employed in the RDB and the 524 superficial removal of T. versicolor from the pinewood chips. Mir-Tutusaus et al. (Mir- 525 Tutusaus et al., 2016) obtained a 100-fold increase in HPC after only 3 d of treating 526 non-sterile hospital wastewater with T. versicolor in a fluidized reactor. This notable 527 increase was promoted by the addition of glucose and NH4Cl as the main source of 528 nutrients for the fungus, since these compounds are easily assimilable by bacteria. A 529 more moderate increase in HPC was achieved in continuous mode with a preliminary 530 coagulation-flocculation step, which implies higher operational costs. In the present 531 study, the HPC increase was limited, and costs associated with nutrient supply and 532 pre-treatment were completely avoided. 533 4. Conclusions 534 Trametes versicolor immobilized on wood chips was used to treat agricultural 535 wastewaters in simple channel bioreactors. According to the sorption isotherm, the 536 Freundlich model gave the best fit for diuron sorption on the wood chips. However, 537 successive sorption experiments revealed inconsistencies between the qmax predicted 538 by the Freundlich model and the experimental results. In contrast, the experimental 539 data conformed to the qmax predicted by the Langmuir model, and thus, the Langmuir 540 model was selected as the most representative one. Regarding kinetics, the Elovich 541 model showed the best fit, suggesting that no sorption mechanism was predominant. 542 The PBCB showed high diuron removal from agricultural wastewater. Moreover, 543 synergistic interactions between T. versicolor and indigenous microorganisms were 544 proven. The automated RDB effectively removed diuron from spiked real wastewater 545 requiring 7 times lower wood amount than the PBCB. 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