This is the accepted version of the journal article: Hernandez del Amo, Elena; Poblete, Rodrigo; Sánchez Martínez, M. Olga; [et al.]. «Biological treatment and microbial composition of landfill leachate using a compost process in an airlift bioreactor». Journal of cleaner production, Vol. 415 (August 2023), art. 137748. DOI 10.1016/j.jclepro.2023.137748 This version is available at https://ddd.uab.cat/record/275850 under the terms of the license 1 Biological treatment and microbial composition of landfill leachate using a 2 compost process in an airlift bioreactor 3 4 Elena H. del Amoa,d, Rodrigo Pobleteb,*, Olga Sáncheza, Manuel I. Maldonadoc,e 5 a 6 Departament de Genètica i Microbiologia. Universitat Autònoma de Barcelona, 7 08193 Bellaterra, Spain b 8 Universidad Católica del Norte, Facultad de Ciencias del Mar, Escuela de 9 Prevención de Riesgos y Medioambiente, 1780000 Coquimbo, Chile. c 10 CIEMAT-Plataforma Solar de Almería, Ctra. De Senés s/n, 04200 Tabernas, 11 Almería, Spain. d 12 Institut d’Ecologia Aquàtica. Universitat de Girona, 17003 Girona, Spain e 13 CIESOL, Joint Centre University of Almería-CIEMAT, 04120 Almería, Spain 14 15 *Corresponding author 16 17 Abstract 18 Landfill leachate (LL) contains a large amount of toxic compounds and its treatment 19 is currently a matter of concern. In this work, an adapted compost in different airlift 20 bioreactors was used to depurate a complex, toxic and old landfill leachate without 21 treatment (raw leachate) and after pretreatments (coagulation/flocculation; 22 coagulation/flocculation and filtration; coagulation/flocculation, filtration and photo- 23 Fenton process). After the complete pretreatments, a high removal of organic matter 24 was achieved, with a global removal of chemical oxygen demand (COD) and humic 25 acids of 72.4% and 83.4%, respectively; besides, copper and iron in the landfill 26 leachate presented a total removal of 91.1% and 65.8%, respectively. On the other 27 hand, after the contact of raw leachate with compost in the airlift, there was a 28 decrease of COD, copper and iron, while for humic acids there was a slight increase. 29 The same trend was observed when the leachate was submitted to the different 30 pretreatments and subsequently subjected to the biologic process with compost. The 31 respirometric analyses showed that the raw leachate was toxic, although this 32 tendency decreased along the treatments, with inhibition values of 41.8%, 27.5%, 33 22.0% and 12.1% for raw and pretreated leachate (by coagulation/flocculation, 34 filtration and photo-Fenton processes), respectively. Also, in order to improve our 35 knowledge about the composition of the microbial assemblages in compost samples 36 and their possible role in pollutants removal from LL, we analysed samples from both 37 an adapted and a non-adapted compost before and after being in contact with the 38 raw leachate by applying Illumina sequencing of the 16S rRNA gene. Bacteroidota, 39 Proteobacteria, Firmicutes, Spirochaetota and Deinococcota were the most 40 abundant phyla in all samples, being present in the 50 most abundant Amplified 41 Sequence Variants (ASVs) of the study, which represented 56.5% of the total 42 analysed sequences and were considered as our core community. Chryseolinea, 43 Herbinix, Proteiniphilum, Pseudomonas and Sphaerochaeta seemed to be the most 44 resilient genera when the compost was in contact to LL. Moreover, our results 45 showed that the metabolisms related to chemoheterotrophy, fermentation and the 46 nitrogen cycle were the most relevant in all samples. In general, the microbial 47 community was able to adapt to adverse conditions and remove pollutants, as heavy 48 metals. 49 Keywords: Landfill leachate treatment; organic matter; heavy metals; compost, 50 microbial community. 51 52 1. Introduction 53 Currently, with the rapid growth of population, urbanization, industrialization and 54 development of technology, the annual production of municipal solid waste is 55 increasing year after year. The main practice for disposing these wastes is landfill 56 (Miao et al., 2019), but one of the problems of this method is the production of 57 leachates, that is, the percolation of water in the waste layers and the in situ 58 occurrence of biological and chemical reactions. The landfill leachate (LL) contains 59 a large amount of refractory organic products, heavy metals, high ammonia and 60 several toxic contaminants (Hassan et al., 2016), as xenobiotic compounds like 61 aromatic hydrocarbons, pesticides, phenols, aliphatic chlorinated and plasticizers. 62 As a consequence, an inadequate disposal or treatment of LL may cause long-term 63 potential harm to the environment (Zhang et al., 2019). 64 At present, LL is mainly treated by biological and physicochemical processes. 65 Physicochemical processes can remove most of the contaminants, although they 66 are expensive and susceptible to produce secondary pollution (Miao et al., 2019). In 67 contrast, biological methods are the common technique for treating LL due to their 68 simplicity and cost-effectiveness (Bu et al., 2016), and they are applicable when the 69 ratio of biochemical oxygen demand (BOD) to chemical oxygen demand (COD) in 70 LL is higher than 0.4 (De et al., 2019). However, the high concentrations of pollutants 71 present in an old LL may reduce the activity of microorganisms and the efficacy of 72 biological treatment (Liu et al., 2015) due to the presence of nitrogen (Klein et al., 73 2017) and organic refractories with high molecular weight and complex structures 74 (Di Iaconi et al., 2006). In this context, it is important to promote an adaptation of the 75 biological system to obtain the depuration of the wastewater that presents problems 76 caused by the low biodegradability and acute toxicity of those pollutants (Bai et al., 77 2020). 78 Alternatively, the composting process is a technology for the transformation of 79 organic waste into stable and high-quality agricultural by-products via biochemical 80 reactions, reducing their environmental risk (Li et al., 2012). Besides, the application 81 of composting allows the valorisation of waste. The composting process is driven by 82 the microbial metabolism, and the duration of the composting period depends on 83 factors such as temperature, pH, compost mass bulk density, porosity and aeration, 84 among others (Ren et al., 2018). Furthermore, composting constitutes a 85 bioaugmentation method where thermophilic bacteria participate in the 86 biodegradation of polluting materials (Yanto and Tachibana, 2013), resulting in a 87 feasible bioremediation alternative. Compost has been studied for soil remediation 88 and has been considered a suitable material for in situ heavy metal removal (Zhou 89 et al., 2017) and elimination of emerging pollutants (Kuppusamy et al., 2017). The 90 effectiveness of compost use in the treatment of pollutants is either dependent on 91 the adsorption by organic matter or on the degradation by microorganisms and 92 present enzymes (Kuppusamy et al., 2017; Zhou et al., 2017). In general, the 93 compost quality has an impact on the bioavailability and biodegradation of organic 94 pollutants (Cerda et al., 2018; Luo et al., 2018). Unlike conventional biological 95 treatments, this kind of processes are easy and reliable methods for wastewater 96 treatment using very small spaces (Gholami et al., 2020). 97 Nowadays, several works have reported the use of compost for LL treatment. In the 98 research of Spiniello et al. (2023), the coupling of a hybrid constructed wetland to a 99 solar photo-Fenton process was studied, where the layers of the wetlands included 100 sand, solid compost and carriers, and the removals obtained ranged from 75 to 95% 101 for all the parameters evaluated after LL recirculation. In addition, published the use 102 of compost in the denitrification of LL, observing that it was unable to sustain the 103 denitrification process; a full denitrification was only achieved after the use of 104 augmented substrates. Besides, Liu et al. (2022) evaluated a coagulation and a 105 photo-Fenton process in the treatment of a mature LL using aluminium ions as 106 coagulant agent and, when the conditions were optimal, they obtained a removal 107 efficiency of colour and total organic carbon of 97.6% and 88.1%, respectively. 108 On the other hand, single bioreactors are often used in wastewater treatment 109 because they offer some benefits such as enhanced organic removal capacity, 110 smaller reactor volume, lower energy consumption, short hydraulic retention time 111 and high organic loading rate (Warmeling et al., 2016). Particularly, airlift bioreactors 112 are single devices that create different oxygen concentration zones (aerobic, 113 anaerobic and anoxic) by embedding the blade as a physical separation, providing 114 a more convenient operation in comparison to other single bioreactors (Asadi et al., 115 2017). This kind of bioreactor enhances the contact efficiency between gas–solid– 116 liquid phases due to fluid circulation (Mota et al., 2015), providing a very high mixing 117 inside the reactor without the need of a mechanical stirrer (Asadi et al., 2017). 118 Besides, it presents an increased microbial diversity and high removal efficiency of 119 recalcitrant pollutants (Xu et al., 2020). The oxygen bubbles circulate inside the 120 bioreactor thanks to the action of the airlift, increasing the efficiency of oxygen mass 121 transfer, and allowing the growth of microorganisms as well as the removal of 122 organic matter (Mendes and Badino, 2015). Due to all these advantages, in this 123 work, we have focused on the characterization of pollutants, such as COD, iron, 124 humic acids and copper, and heavy metal removal from a LL in an airlift bioreactor 125 packed with a LL preadapted compost. As far as we know, no studies have been 126 done using this kind of setup for LL treatment. Therefore, it is the first research 127 focused on the evaluation of the utilization of an adapted compost to remove 128 pollutants present in a landfill leachate. Microbial communities were further 129 investigated by applying Illumina sequencing of the 16S rRNA gene, a method able 130 to provide thousands of sequence reads. 131 132 2. Materials and methods 133 134 2.1. Sample collection 135 Samples (100 L) of LL were obtained from different places of the pond of landfill El 136 Panul, where the municipal solid waste from Coquimbo (Chile, Longitude: -71.3, 137 Latitude: -29.9) is disposed off. 138 139 140 2.2. Pretreatment of the landfill leachate 141 Due to the fact that it is the first study that considers the use of compost in the 142 depuration of a LL, there is no information available about the effect of the initial 143 characteristics of this wastewater in the biological process. Considering that it is 144 possible to obtain a different response in the removal of pollutants in the biological 145 process due the initial characteristics of the LL, several pre-treatments in the LL and 146 their impact in the final stage were evaluated. 147 Since the performance of the photocatalytic processes depends on the transparency 148 of water, and it is needed to avoid the presence of pollutants, such as humic acids, 149 which interfere with the UV transmittance and effectivity (Wang et al., 2023), we 150 carried out a coagulation/flocculation process, that is a physicochemical treatment 151 which allows the removal of organic matter and humic acids (Alfaia et al., 2019). 152 Also, the coagulation/flocculation makes an adequate combination with filtration, 153 since the first one allows to increase the size of the particles through the 154 destabilization and aggregation of colloids and particles, favouring the performance 155 of the second one. Filters reject particles with larger size than its pore diameter so, 156 these particles are retained in the membrane, enhancing the performance of the 157 filtration process (Lee et al., 2020). As a consequence, to improve the removal of 158 pollutants, the raw LL was submitted to a coagulation/flocculation process using 159 FeCl3 with a load of 1 g/L (Merck), stirred at 150 rpm for 2 h (Poblete et al., 2020), 160 then being left to rest for 12 hours. Then the supernatant was collected and 161 submitted to a 5 µm filtration. Subsequently, the filtered LL was treated by a photo- 162 Fenton process in a laboratory scale photoreactor of 1 L capacity, using UV 163 irradiation emitted by an immersion UV lamp of 36 W (Atman Unit) with a maximum 164 emission at a wavelength of 254 nm. The pH of the LL was adjusted to 3 using H2SO4 165 and the reagents used in the photo-Fenton reaction were FeSO4•7H2O and H2O2 in 166 concentrations of 0.3 g/L and 0.67 g/L, respectively. The reagent concentrations 167 were established according to previous results obtained by our research group, 168 aimed to achieve the higher removal of pollutants in a LL treated by a photo-Fenton 169 process (Poblete et al., 2019). The run lasted 1 h. A submerged pump (40 W) 170 recirculated the LL at a flow rate of 8 L/min from a recirculation tank of 5 L useful 171 capacity, which received LL from the photoreactor. Figure 1 shows a schematic 172 diagram of the pretreatments involved. UV lamp Stirrer Filter Photoreactor Recirculation tank Leachate 173 Raw Coag/floc process Filtration process Photo-Fenton process 174 Figure 1. Schematic diagram of the pretreatment of the raw landfill leachate (LL). 175 2.3. Biological treatment in an airlift packing bioreactor 176 The removal efficiency of different pollutants present in the LL was evaluated using 177 an airlift packing bioreactor (APBR) at a prototype scale in batch condition. The 178 APBR was inoculated with immature compost that was obtained using organic 179 wastes constituted by 10 kg of granulated solid coffee waste and 10 kg of sawdust, 180 that were placed in a 50-litre cylindrical container. The solid coffee waste used to 181 compost was obtained from a local shop in Coquimbo (Chile). Sawdust was obtained 182 from carpentry stores also in Coquimbo. 183 With the aim of adapting the microorganisms present in the compost to the complex 184 content of the LL, it was wetted with a 10% concentration of the raw leachate for one 185 week. The following week, the concentration of the leachate was increased again by 186 10%, and this rise in concentration was maintained until week 10, to finally use a 187 leachate without dilution (pure raw leachate) and maintain the periodically wetted 188 compost with pure raw landfill leachate for a duration of 6 months, in order to allow 189 the microorganisms present in the compost to gradually adapt to the complex and 190 toxic substances of the leachate (Yadav et al., 2020; Tombola et al., 2019). 191 In the APBR with adapted compost, 1 kg of material was placed inside the reactor 192 as a packed tower of 1 L of volume. A diffusor and a tube of air connected to a 10 193 W-power air pump were positioned at the bottom of the tower (Figure 2). The air 194 pump provided aeration to allow the oxygenation of the packed tower and the 195 recirculation of the LL. 196 In the bottom and in the upper parts of the packed tower there was a geotextile 197 membrane to avoid leakage of the compost. The system was filled with 2 L of LL and 198 the air pump was turned on to produce the effect of airlift and the recirculation of the 199 LL in the system with a flow of 0.5 L/min. The packed tower of the APBR was 50 cm 200 high, with an external diameter of 5 cm, connected to a recirculation tube with the 201 same dimensions (Figure 2). In the upper zone of the packed tower a 10 cm 202 extension of the tube was maintained free of LL and compost, which allowed sample 203 collection and the retention of the foam generated during the process. Air pump Aeration Sampling point Packed tower Compost Recirculation tube Bubbles Difusser Membrane 204 205 Figure 2. Schematic diagram of the airlift packing bioreactor (APBR). 206 207 To evaluate the effect of the pretreatments above described on the biological 208 process, the LL submitted to the different pretreatment stages was treated in the 209 APBRs (Figure 3). The system operated continuously for 10 days for each LL. Thus, 210 the LL added into the bioreactors was: a) raw LL; b) LL submitted to 211 coagulation/flocculation; c) LL submitted to coagulation/flocculation and filtration; 212 and d) LL submitted to coagulation/flocculation, filtration and photo-Fenton process. 213 UV lamp Raw LL Coag/floc Filtration Photo-Fenton process Stirrer Photoreactor Recirculation tank LL a) b) c) d) Bioreactor Bioreactor Bioreactor Bioreactor 214 215 Figure 3. Schematic diagram of the pretreatment processes and final airlift 216 packing bioreactors. 217 218 2.4. Determination of pretreatment parameters 219 The removal efficiency of the pollutants was determined by taking samples of LL in 220 the recirculating system on the sample points and measuring the changes in 221 chemical oxygen demand (COD), humic acids, heavy metals, faecal coliforms and 222 toxicity. These parameters were determined along the different stages of the 223 pretreatment in order to characterize the increase in biodegradability before and after 224 the biological treatment. All the samples were taken by triplicate. The COD of the LL 225 was measured according to the EPA 410.4 methodology and Colorimetric Method, 226 pH was measured using a pH meter (WTW 3150i unit), and humic acids were 227 determined spectrophotometrically in an Optizen Pop spectrophotometer at 254 nm 228 (ABS254). Iron was analysed with the EPA phenantroline method 315B, while total 229 copper was determined using the Bicichoninate Acid Method (HI-93702-01). The 230 Total Organic Carbon (TOC) analysis, was carried out with 50 µL of samples injected 231 in a Shimadzu TOC-L, with an acid-catalysed combustion at 650 °C, using a non- 232 dispersive infrared (NDIR) detector. Faecal coliforms were determined using the 233 NCh 2313/23 method. Heterotrophic plate counts (HPC) microorganisms were 234 measured according to the spread plate method, in terms of Colony-Forming Units 235 (CFU). 236 To determine the microbial compost stability and activity (Villaseñor et al., 2011), 237 which depends on the biodegradability and toxicity of the mixture of LL+compost in 238 the different APBRs, a respirometric test was carried out based on the oxygen 239 uptake rate (OUR) of a mixture of liquid medium containing nutrients. The aeration 240 and stirring of the suspension allowed oxygen to be adequately dispersed (Scaglia 241 et al., 2011). The test was performed using a BM-T respirometer (Surcis S.L.), 242 constituted by a 1 L capacity vessel, equipped with a thermometer and an oxygen 243 probe (Protos 3400, Knick Elektronische Messgeräte GmbH & v Co. KG). Fifty grams 244 of LL + compost collected from the top of the APBR were shredded and 245 homogenized in a stirrer and then placed in the vessel of the respirometer; 1 L of 246 distilled water was added and the mix was homogenized, the temperature was set 247 at 20°C and the system was continuously aerated and stirred (Scaglia et al., 2007). 248 The reference sample was made up with 50 mL of distilled water with 0.5 g of sodium 249 acetate per gram of volatile suspended solid (as a highly biodegradable compound). 250 Fifty mL of the different samples were added to obtain the OUR. The pH of each 251 sample was previously adjusted to 7 (Lo, 2010). Each assay continued until a 252 plateau in the respiration of the sludge (Rs, mg/L·h) was obtained and the maximum 253 respiration rate (Rsmax, mg/L·h) was achieved. The inhibition percentages (%I) were 254 calculated using the following equation: !" 255 %𝐼 = $1 − !" ' ∗ 100 (1) !"# 256 Anova and Tukey HSD post hoc tests were done to evaluate significant differences 257 between the different treatments, with a p-value of 0.05. 258 259 2.5. DNA extraction 260 We extracted DNA from adapted and non-adapted compost samples, as well as from 261 samples from both types of compost which had been in contact with raw LL for 10 262 days in order to compare the composition of microbial communities before and after 263 being in contact with LL. DNA extraction was performed using the DNeasy Power 264 Soil Kit (Qiagen) according to the manufacturer’s instructions. DNA concentration 265 and purity were measured using a Nanodrop spectrophotometer (NanoDrop 266 Technologies, Inc., Wilmington, DE) at 260 nm and 260/280 nm respectively. DNA 267 extracts were conserved at -80ºC for further analyses. 268 269 2.6. Amplicon sequencing 270 DNA was sequenced by RTL Genomics (Lubbock, TX, USA; 271 https://rtlgenomics.com). Two primers were used to amplify bacterial and archaeal 272 16S rRNA gene: 515F-Y (GTGYCAGCMGCCGCGGTAA) and 926R: 273 (CCGYCAATTYMTTTRAGTTT) (Parada et al., 2016). Illumina MiSeq 2x300 flow 274 cells was used. Sequence data from the MiSeq platform were quality filtered, 275 trimmed, dereplicated, merged and, after a process of chimera removal, clustered 276 into amplicon sequence variants (ASVs) using the DADA2 Pipeline (Callahan et al., 277 2016). Afterwards, ASVs tabulation, and taxonomy assignment were performed 278 using the Silva taxonomic database (v132). Sequences with unclassified genera or 279 species with the Silva database were taxonomically identified by Blast (NCBI). 280 Finally, the Phyloseq package was used to tabulate relative abundances at various 281 taxonomic levels and to determine the microbial core community (McMurdie and 282 Holmes, 2013). DADA2 and Phyloseq have been run as an R script (in R v.4.2.1) 283 using R packages dada2 v.1.24.0, phyloseq v. 1.40.0 and ggplot2 v.3.3.6. 284 Taxonomic identification was carried out by means of the tool Faprotax (Louca et al., 285 2016) to predict the functional composition of the microbial communities based on 286 16S rRNA marker gene profiles. 287 Sequence statistical analyses were performed using the R statistical software (R 288 Core Team, 2021) and the vegan and venneuler packages. Alphadiversity analyses 289 were performed using a ASVs abundance table that was previously subsampled 290 down to the minimum number of reads in order to avoid artefacts due to an uneven 291 sequencing effort among samples. For alphadiversity analyses, we calculated the 292 Chao1 index as a measure of richness and the Shannon index as diversity metrics. 293 Sequence data has been deposited in GenBank database with BioProject accession 294 number PRJNA911052. 295 296 3. Results and discussion 297 298 3.1. Parameters after LL pretreatment 299 The raw LL was submitted to different pretreatment processes 300 (coagulation/flocculation, filtration and photo-Fenton process) and after each stage, 301 it was subject to a biological process in an APBR system. The main characteristics 302 of the LL samples in the different stages of the pretreatment are presented in Table 303 1. 304 305 Table 1. Landfill leachate (LL) characteristics. Stage treatment Coag/Flocc Filtration Photo- Raw Fenton Parameter Value COD (mg/L) 13780 11300 6890 3800 pH 8.85 8.82 8.83 2.95 Total Iron (mg/L) 82.3 94.1 43.5 28.1 Copper (mg/L) 180.6 60.9 17.1 16.8 Humic acids (abs 254 101.6 78.0 28.1 nm) 159.2 TOC (mg/L) 3845.4 3250.6 2801.5 1600.4 Faecal coliforms (MPN) nd nd nd nd HPC (CFU) nd nd nd nd 306 MPN: most probable number 307 nd: not detected 308 The non detection of faecal coliforms and HPC in the raw LL was probably due to the toxicity of this 309 kind of water (Wijekoon et al., 2022). 310 311 312 Figure 4 shows the changes in the concentration of copper, humic acids (ABS254) 313 and iron in the raw LL submitted to subsequent coagulation/flocculation, filtration and 314 photo-Fenton processes before the biological treatment. A high removal of organic 315 matter was observed in terms of COD and humic acids along the pretreatment 316 process, with COD decreasing from 13780 to 11300 mg/L after 317 coagulation/flocculation, from 11300 to 6890 mg/L after filtration, and from 6890 to 318 3800 mg/L due to photo-Fenton, achieving a global removal of a 72.4%. In the case 319 of humic acids, the trend was similar, going from 159.5 to 101.7 mg/L, from 101.7 to 320 78.0 mg/L and from 78.0 to 26.4 mg/L, due to coagulation/flocculation, filtration and 321 photo-Fenton processes respectively, reaching a global removal of 83.4%. 322 We have to take into consideration that the UV-quenching substances of LL are 323 constituted by a hydrophilic fraction and also hydrophobic humic substances such 324 as humic acids and fulvic acids, and each has distinct behaviours during its treatment 325 (Iskander et al., 2018). Since these kind of substances can attract heavy metals and 326 organic matter, allowing their transportation into surface water of groundwater 327 (Reshadi et al., 2020), their removal is crucial for environmental protection. 328 14000 200 Copper, Iron (mg/L) and ABS254 COD 12000 175 HA Copper 150 10000 COD (mg/L) Iron 125 8000 100 6000 75 4000 50 2000 25 0 0 Raw LL Coag/floc Filt photo-Fenton 329 Treatment of the landfill leachate 330 Figure 4. Change in the concentration of COD, copper, humic acids (ABS254) and 331 iron in the different stages of LL pretreatment. Error bars represent the standard 332 deviations for three replicated measures (n = 3). 333 The removal of organic matter due to coagulation/flocculation could be explained by 334 the agglomeration of particles in the LL suspension, including organic colloids 335 (Cheng et al., 2020; Ibrahim and Yaser, 2019). The suspension is destabilized by 336 the coagulant, and the flocculation occurs when compact flocs are formed and 337 settled (Zahrim et al., 2018). The flocs that do not settle can be trapped in the filter, 338 reducing the concentration of organic matter. On the other hand, the decrease of 339 organic matter in the photo-Fenton process can be due to the generation of the 340 highly reactive hydroxyl radicals, that are non-selectively oxidant (Espinoza- 341 Quiñones et al., 2019), as shown by equations 2 and 3 which allow the oxidation of 342 the organic matter present in the LL and enhance its biodegradability, as previously 343 reported (Poblete and Pérez, 2020). 344 Fe2+ + H2O2 è Fe3+ + OH- + ·OH (2) 345 Fe3+ + H2O + hvè Fe2+ + H++ ·OH (3) 346 Concerning the heavy metals analysed, the copper decreased from 180.3 to 60.5 347 mg/L after coagulation/flocculation, from 60.5 to 17.8 mg/L after filtration and from 348 17.5 to 16.8 mg/L due to the photo-Fenton process, obtaining a global removal of 349 91.1%. In the case of iron, its concentration changed from 82.0 to 94.1 mg/L, from 350 94.1 to 43.5 mg/L and from 43.5 to 28.1 mg/L, due to coagulation/flocculation, 351 filtration and photo-Fenton processes, achieving a global removal of 65.8%. The 352 increase of the concentration of iron after the coagulation/flocculation process is due 353 to the addition of this metal in the process, concentration that was reduced after the 354 filtration process. The removal of copper in the LL achieved by the 355 coagulation/flocculation process, that used Fe(III), demonstrated the high 356 performance of Fe(III), being in agreement with the data reported by Chu et al., 357 (2020), who published removal rates of dissolved organic carbon, Ni and As, of 358 84.1%, 73.1% and 96.9%, respectively. 359 As can be observed in Table 1, TOC underwent a high removal, especially in the 360 photo-Fenton process, where an elimination of 42.8% was achieved, mostly caused 361 by the removal of organic carbon as aromatic compounds, leading to the generation 362 of hydroxyl radicals in the oxidation process (Welter et al., 2018). Nonetheless, the 363 subtraction of TOC was lower than that obtained by Liu et al., (2022) who reached a 364 76.4% removal of this parameter, probably due to the fact that they spent longer time 365 in the photocatalytic process. On the other hand, we did not detect the presence of 366 faecal coliforms nor heterotrophic plate counts, probably due to the toxicity of this 367 kind of water. 368 3.2. Parameters during LL biological treatment 369 The raw LL and the LL submitted to different pretreatments were placed in four 370 different APBR with the aim of promoting their contact with the compost throughout 371 the 10 day experiment, and to evaluate the removal of pollutants as well as the effect 372 of the different pretreatment stages. As can be observed in Figure 5, there is a 373 difference in the removal of the pollutants due to the biological process in the APBR, 374 depending on the stage of the pretreatments carried out. When LL without any 375 pretreatment (raw LL) was fed to the biological process (Figure 5a), the change in 376 COD varied from 13780 to 11870 mg/L, while copper decreased from 180.6 to 100 377 mg/L, and iron from 82.3 to 32 mg/L; in the case of humic acids, there was a slight 378 increase from 159.5 to 163 ABS254. When the LL was subjected to 379 coagulation/flocculation and to the biologic process (Figure 5b), the COD diminished 380 from 11300 to 9500 mg/L, while copper declined from 60.9 to 20.4 mg/L, and iron 381 varied from 94.1 to 75.6 mg/L; humic acids increased again from 101.6 to 162.0 382 ABS254. When the LL was submitted to coagulation/flocculation and filtration 383 processes in the bioreactor (Figure 5c), the change in COD was from 6890 to 4800 384 mg/L, for copper from 17.1 to 8.3 mg/L, for iron from 43.5 to 35.4 mg/L and, in the 385 case of humic acids from 78.8 to 205.6 ABS254. When the LL was submitted to the 386 whole pretreatment (coagulation/flocculation, filtration plus photo-Fenton), 387 decreases in COD from 3800 to 1520 mg/L, for copper from 16.8 to 8.37 mg/L, and 388 for iron from 28.1 to 15.4 mg/L were obtained in the biological process (Figure 5d), 389 while for humic acids the value increased from 26.1 to 35.5 ABS254. 200 16000 200 14000 Raw Coag/floc (mg/L) and ABS254 (mg/L) and ABS254 a) 14000 b) Iron and copper 12000 COD (mg/L) 150 12000 150 10000 HA Copper 10000 8000 100 Iron COD 8000 100 6000 6000 50 4000 50 4000 2000 2000 0 0 0 0 250 8000 40 5000 Coag/floc+Filt c) 7000 Coag/floc+Filt+photo-Fenton 35 Iron and copper 200 4000 COD (mg/L) 6000 30 d) 150 5000 25 3000 4000 20 100 3000 15 2000 2000 10 50 1000 1000 5 0 0 0 0 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 390 Time of biológical treatment (days) Time of biológical treatment (days) 391 Figure 5. Change in the concentration of different pollutants present in the LL 392 submitted to the biological process without pretreatment (a) or after the different 393 pretreatments (b: coagulation/flocculation, c: coagulation/flocculation + filtration, d: 394 coagulation/flocculation + filtration + photo-Fenton). Error bars represent the 395 standard deviation of the results (n = 3). 396 In general, there was an enhancement in the concentration of humic acids 397 throughout time in the different bioreactors due to the action of the compost. Humic 398 acids are organic substances rich in amino, hydroxyl and carboxyl groups, present 399 in the compost due to the high concentration of lignin (Wang et al., 2022). They 400 participate in the control of nutrients for microbial consortia and they protect 401 microorganisms from the action of hazardous compounds (Sun et al., 2022), being 402 also their presence an indicator of fertility in soils (Liu et al., 2023). Therefore, their 403 presence in the compost promotes the removal of toxic material from the LL. 404 Concerning the removal of COD, the results showed significant differences, with F 405 values higher than the tabulated number (440.3>0.005) (Table 2). A Tukey test 406 (Table 3) indicated that there were significant differences between all the treatments 407 evaluated. Also, significant differences were observed in the removal of humic acids, 408 with F values higher than the tabulated result (36.9>0.00004). The Tukey test 409 showed that there were significant differences between the photo-Fenton treatment 410 and all the rest of the treatments, including raw LL. 411 412 413 Table 2. Analysis of variance (ANOVA) for COD removal DF Sum of Squares Mean Square F Value Prob>F Model 3 6.78E+08 2.26E+08 440.30 0.005 Error 36 1.85E+07 513510.6 Total 39 6.97E+08 414 415 Table 3. Tukey tests for COD removal. Mean Diff SEM q Value Prob Alpha Sig Coag/floc Raw -2696 320.4 11.89721 0 0.05 1 Filt Raw -7317 320.4 32.28928 0 0.05 1 Filt Coag/floc -4621 320.4 20.39207 0 0.05 1 Photo-Fenton Raw -10681 320.4 47.13432 0 0.05 1 Photo-Fenton Coag/floc -7985 320.4 35.23711 0 0.05 1 Photo-Fenton Filt -3364 320.4 14.84504 2.55E-07 0.05 1 416 Sig equal 1 indicates that the means difference is significant at the 0.05 level. 417 418 In the case of the variation of cooper in the bioreactor after the different treatments, 419 significant differences were obtained in this parameter, with F values higher than the 420 tabulated number (154.6>2.86). The Tukey test showed that there were meaningful 421 differences between all the treatments except for the photo-Fenton and filtration 422 process. 423 Taking into consideration the change on the concentration of iron in the LL, the 424 anova test shows that there were significant differences in this parameter, with F 425 values higher than the tabulated number (59.8>4.64*10-14). The Tukey test showed 426 that there were meaningful differences between all the treatments evaluated. 427 The percentage of removal of pollutants such as COD, copper and iron present in 428 the LL after the biological treatment is showed in Figure 6. The biological treatment 429 that reached the highest removal of COD was the one that underwent 430 coagulation/flocculation plus filtration plus photo-Fenton pretreatment processes, 431 with an elimination value of 60.0%. A similar trend was observed with iron, which 432 achieved a removal of 46.5%. In contrast, for copper, the highest elimination was 433 accomplished with LL pretreated with the coagulation/flocculation process, with a 434 value of 56.3%. 100 90 COD Copper Iron copper and iron (%) 80 Removal of COD, 70 60 50 40 30 20 10 0 a b c d 435 Experiment 436 Figure 6. Removal of pollutants (%) present in LL treated in the APBRs, using a) 437 raw LL, or different pretreatment processes: b) Coag/Floc, c) filtration and d) photo- 438 Fenton). 439 440 According to the respirometric tests carried out using sludges, the raw LL was toxic 441 and although toxicity decreased along the pretreatments of LL. Inhibition values of 442 41.8%, 27.5%, 22.0% and 12.1% were obtained for raw, coagulation/flocculation, 443 filtration and photo-Fenton processes respectively. These results agree with 444 previous findings from our research group (Poblete and Pérez, 2020), where a 445 decrease in the toxicity throughout the LL treatments was reported. This reduction 446 in the inhibition of sludge in the presence of the LL + compost mixture is due to the 447 pretreatment and the biological process, which promoted the removal of toxic 448 compounds from the wastewater, such as the adsorption of copper. Up to now, a 449 95% removal of this heavy metal has been previously reported (Pennanen et al., 450 2020), as well as the oxidation of complex organic matter by hydroxyl radicals, with 451 a removal of an 80% of COD of a LL using a photo-Fenton process (Carbajo et al., 452 2021). Additionally, the use of UV light and a photocatalyst, enhanced the 453 biodegradability of LL by 89% (da Costa et al., 2018). Table 4 shows a comparison 454 on the pollutants removal obtained in this work and in other ones where different 455 treatments were applied. 456 457 458 459 Table 4. Comparison on the pollutants removal obtained in this work and in other 460 ones where different treatments were applied. % of removal In this In other Reference Pollutant Treatment method manuscript works COD Coag/Flocc 14 35 (Reddy et al., 2022) Filtration 16 33 (Rohers et al., 2021) Photo-Fenton 60 43 (Ghanbarzadeh Lak et al., 2018) Biological process 60 60 (Tripathy and Kumar, 2022) Copper Coag/Flocc 67 87 (Ma et al., 2023) Filtration 53 28 (Bremner et al., 2020) Biological process 56 59 (Genethliou et al., 2023) Humic acids Coag/Flocc 36 20 (Kong et al., 2021) TOC Coag/Flocc 15 15 (Righetto et al., 2021) Filtration 14 24 (Agabo-García et al., 2023) Photo-Fenton 43 32 (Kanafin et al., 2023) 461 462 3.3. Operational costs 463 Table 5 shows the operational costs of the evaluated treatment, considering the 464 expenses of the reagents as well as the costs of the electric power consumption by 465 the equipment used in the different experiments. It should be highlighted that 466 experiment a (raw LL) corresponds to less reagent and total costs, as expected, 467 since there is not a pretreatment, which led to the lowest removal of pollutants 468 (Figure 6). In contrast, experiment d, which considers all the pretreatments, has the 469 highest values of operational costs, especially due to the use of reagents, although 470 it achieves the best levels of iron and copper removal, allowing less inhibition of the 471 sludge in the respirometric test. It is quite an interesting result, because copper 472 present in LL is considered an harmful substance, hazardous to the aquatic 473 environment (Wdowczyk and Szymańska-Pulikowska, 2021) and with negative 474 effects on microorganisms (Kwak et al., 2020). 475 Table 5. Operational costs of the different treatments carried out. Operational costs ($US/m3) Reagent Energy Total Exp a (raw LL and biologic) 3.8 22.2 26.0 b (coag/floc and biologic) 34.0 22.3 56.3 c (coag/floc, filtr and biologic) 34.0 22.3 56.3 d (coag/floc, filtr, photo-Fenton and biologic) 79.8 23.7 103.5 476 477 Also, it is possible to observe that operational costs associated to energy 478 consumption were similar for all the experiments, since these runs were carried out 479 in the APBR, that used aeration for 10 days. Although the power of the air pump was 480 small (10 W), its prolonged use over time, necessary to maintain a sufficient amount 481 of gas/liquid phases mass recirculation, implied a relatively high energy consumption 482 which generated higher operational costs (Chen et al., 2021; Yen and Liu, 2014). In 483 fact, the energy spent by the aeration process was more than 50% of the total energy 484 consumed in the biological treatment (McCarty et al., 2011), lower than that used by 485 Hu et al., (2020), who used an air compressor with a very high power. On the other 486 hand, Wei et al., (2023) published a cost of 113,9 €/m3 of oxypirolysis of LL using 487 Fe2O3@SiO2-Al2O3 as a catalyst. 488 489 The whole treatment, that includes coagulation-flocculation, filtration, photo-Fenton 490 reaction and biological process, has higher operational cost than others, as reported 491 by Turan et al., (2023) who published a cost of 50 $US/m3 using FeCl3 as coagulant 492 for LL treatment. However, it has to be taken into consideration that the non- 493 biodegradable and toxic behaviour of the mature LL studied in this work required 494 complex treatments (Yan et al., 2022; Gautam and Kumar, 2021). 495 496 It has been reported that aeration allows the enrichment of heterotrophic denitrifying 497 bacteria and the removal of nitrogen and organic matter (Song et al., 2020). Also, 498 the utilization of the APBR allows an effective suspension of solids, high mass 499 transfer, low shear stress to microorganisms suitable for biological processes, and 500 the absence of stagnant volumes into this reactor (Mirghorayshi et al., 2020). 501 3.4. Microbial community structure and predicted metabolisms in adapted and non- 502 adapted compost samples 503 In order to improve our knowledge about the composition of the microbial 504 assemblages in compost samples and their possible role in pollutants removal from 505 LL, we analysed samples from both an adapted and a non-adapted compost before 506 and after being in contact with the raw leachate on the basis of the 16S rRNA gene 507 sequence. After a rigorous quality control (see Materials and Methods), a total of 508 443,640 sequences passed quality filtering. On average, 73,940 sequences were 509 obtained per sample (ranging from 44,031 to 105,511). At this sequencing depth, 510 rarefaction curves revealed a reasonable coverage of bacterial richness (Figure S1). 511 Observed richness (number of Amplicon Sequence Variants or ASVs) varied 512 between 749 and 1,901 (Table 6). These values were similar to those obtained from 513 the richness estimate index (Chao1), which ranged from 953 to 2072. Despite 514 variation in ASVs number, no significant differences were found between samples in 515 richness indices (Kruskal-Wallis and Wilcoxon’s test with Bonferroni correction, p > 516 0.05). Shannon’s diversity index varied from 3.33 to 5.95, showing usual diversity 517 values for microbial communities (Feranchuk et al., 2018). In this case, significant 518 differences were found between samples, showing lower diversity values without 519 preadaptation and without contact to the LL than those which were previously 520 adapted or exposed to the LL (one-way ANOVA and Tukey post-hoc test, p < 0.05). 521 Table 6. Alphadiversity from the microbial communities of the studied compost 522 samples. Sample Observed Chao1 Shannon Adapted & No LL 1647 1960.84 5.59 Adapted & LL 1327 1791.55 4.69 Non- adapted & No LL 749 952.55 3.33* Non-adapted & LL 1901 2072.23 5.95 523 * significant differences in Shannon index (p < 0.05) 524 Bacteroidota, Proteobacteria, Firmicutes, Spirochaetota and Deinococcota were the 525 most abundant phyla in the studied samples (Figure 7). These five phyla were found 526 in all samples, being present in the 50 most abundant ASVs of the study, which 527 represented 56.5% of the total analysed sequences and were considered as our 528 core community (Neu et al., 2021). 529 530 Figure 7. Relative abundance of each phylum in the microbial community from 531 adapted and non-adapted compost samples before (no LL) and after (LL) being 532 exposed to raw LL 533 Interestingly, the most representative phylum in samples which had been in contact 534 with leachate in some moment (i.e. preadaptation or treatment of LL) was 535 Bacteroidota (Figure 8). This phylum utilizes complex organic substrates in aquatic 536 environments, being able to degrade recalcitrant compounds, an activity previously 537 reported in studies from LL (Gabarró et al., 2013; Wang et al., 2022). Nevertheless, 538 in the compost sample not preadapted to leachate, Spirochaetota and Firmicutes 539 were more abundant than Bacteroidota. Both phyla, Spirochaetota and Firmicutes, 540 were previously described in microbial communities from compost of organic waste 541 or from rice straw (Tanahashi et al., 2005; Galitskaya et al., 2017). Recent studies 542 have shown the possible role of these phyla in decontaminating metals from different 543 environments. On the one hand, some genera from Bacteroidota, Spirochaetota, 544 and Firmicutes, are involved in the sulfur cycle and can use iron in their metabolisms 545 (Astorch-Cardona et al., 2023; Hashemi et al., 2022). Furthermore, these three phyla 546 have also been found in artificial copper-contaminated samples from MFCs and even 547 in gut microbiota (Gao et al., 2023; Wu et al., 2022). In this sense, it showed the 548 relevance of these phyla in the core community, taking into account that all of them 549 could contribute to the decontamination of LL. 550 551 552 553 Figure 8. Taxonomy of the core community. Data refer to the different microbial 554 communities from adapted and non-adapted compost samples before (no LL) and 555 after (LL) being exposed to raw LL. a) Relative abundance of each phylum in the 556 most abundant 50 ASVs b) Relative abundance of genus belonging to different 557 phyla from the main 50 ASVs. Bold letters label the most representative genera 558 from the microbial community. 559 At genus level, the relative abundance of some ASVs presented differences between 560 samples, and the final composition of the microbial community appeared to depend 561 on the preadaptation or not of the compost samples. In the case of the preadapted 562 compost to LL, the main genus was Dysgomonas (34% of sequences of core 563 community). However, when the sample was exposed to raw LL, Dysgomonas 564 became less abundant (until 0.1% of sequences) and another genus that was not 565 predominant at the beginning turned into the representative bacteria of the 566 community. Other genera that underwent significant changes in abundance before 567 and after being exposed to LL were Herbinix (from < 0.1% of sequences before the 568 contact of raw LL to 21% of sequences after the treatment), Proteiniphilum and 569 Sphaerochaeta (Figure 8). Herbinix, and concretely Herbinix luporum was described 570 as a cellulose degrading bacterium able to metabolize lignocellulose to acetate, 571 ethanol, and propionic acid in different biogas reactors (Koeck et al., 2016; Liu et al., 572 2017). In these kind of reactors, previous to the digestion process of the substrate, 573 pollutants were frequently found (i.e. nitrogen compounds and heavy metals) 574 (Rahman et al., 2021). Moreover, Proteiniphilum sp. was also usually detected in 575 biogas reactors. This genus has been reported as strict anaerobes that use several 576 macromolecular organic molecules as carbon and energy sources and produce 577 acetic acid (Dang et al., 2013). Proteiniphilum sp. has been recently isolated from 578 anaerobic digesters treating brewery wastewater or maize silage and wheat straw, 579 as well as from municipal solid waste landfill (Orellana et al., 2022; Wang et al., 580 2022). Thus, the most representative genera of our microbial community after being 581 preadapted and exposed to raw LL, showed a tolerance to different complex 582 substrates, being involved in the decrease of COD and metals concentration of the 583 raw LL. 584 A similar trend in the core microbial community was observed between compost 585 samples without preadaptation before and after the contact to raw LL. In this case, 586 Sphaerochaeta (37% of sequences of core community) and Asteroleplasma (26% 587 of sequences) were the dominant genera in the microbial assemblage of the non- 588 adapted compost before being in contact with LL. After the treatment of compost 589 with landfill leachate, the genera Pseudomonas (from 0.3% of to 23%) and 590 Chryseolinea (from <0.1% of to 19%), underwent a substantial abundance increase. 591 Asteroleplasma almost disappeared after the treatment, while Sphaerochaeta, 592 though decreased its relative abundance, remained one of the 5 most abundant 593 genus of the community (Figure 8). Pseudomonas strains are frequently reported as 594 exhibiting a great metabolic versatility and could survive in different ecological niches 595 including contaminated environments (Rojo, 2010). Pseudomonas sp. is a 596 microorganism that can naturally produce extracellular polysaccharide (EPS). EPS 597 structures support the sequestration of metal ions and prevent them from penetrating 598 into the cell surface or from being released in the environment (Imron et al., 2021). 599 Pseudomonas putida has been previously showed to have heavy metal resistance 600 genes and the ability to biodegrade phenolic LL (Paliwal et al., 2014; Michalska et 601 al., 2020). Pseudomonas parafulva and Pseudomonas putida, which are closely 602 related between them, were the main species in the compost sample in contact to 603 LL. On the other hand, Chryseolinea has been reported to be an aerobic 604 chemotrophic bacterium (Kim et al., 2013) that could remove nutrients from water. 605 Bacteria belonging to this genus were found in different reactors treating landfill 606 leachate and were mainly related to nitrogen and phosphorous cycles (Xu et al., 607 2018; Mu et al., 2022), suggesting a great ability to adapt to complex environments. 608 Finally, Sphaerochaeta was a genus present in all samples after the contact with raw 609 LL. Sphaerochaeta is a strictly fermentative genus which produces volatile fatty 610 acids, ethanol, hydrogen, and CO2 by fermenting complex organic compounds (Zhou 611 et al., 2017). Moreover, Sphaerochaeta has been previously reported as the 612 predominant bacteria in landfill leachate (Wong et al., 2019; Zhao et al., 2021; 613 Nimonkar et al., 2022), showing high resilience after the exposure to adverse 614 conditions. 615 On the other hand, on the basis of our 16S rRNA sequences, we utilized the Faprotax 616 tool in order to perforym a prediction of the main potential metabolisms ruling the 617 microbial communities of adapted and non-adapted compost samples before and 618 after their exposition to raw LL. Our results showed that the metabolisms related to 619 chemoheterotrophy, fermentation and the nitrogen cycle were the most relevant in 620 all samples (Table S2). Furthermore, in samples exposed to raw LL from adapted 621 and non-adapted composts, the most abundant metabolisms were related to 622 anaerobic pathways, which might play important roles in degrading complex organic 623 molecules into easily degradable substances (Zhao et al., 2021). Particularly, 624 samples from non-adapted composts were characterized by routes related to 625 nitrogen and methane metabolisms (Figure 9), a trend that has already been 626 observed in composting processes (Hoang et al., 2022). However, when these 627 samples were exposed to raw LL, those metabolisms were lost and enriched with 628 routes related to sulfur cycle, which has been previously associated to the presence 629 of iron (Long et al., 2016), as well as to plastic, hydrocarbon and aromatic 630 compounds degradation, and ligninolysis and cellullolysis metabolisms, implying 631 high activities of carbon-related metabolisms and the biotransformation of organic 632 substances (Toledo et al., 2017; Zhao et al., 2021). In contrast, in the preadapted 633 compost sample, all these last metabolisms were found from the very beginning and 634 once it was in contact with raw LL, the prevailing pathways related to hydrocarbon 635 degradation. In summary, both phylogenetic and metabolic results showed that, after 636 being exposed to raw LL, microbial communities were enriched with groups able to 637 use recalcitrant material indifferently if the biological sample was preadapted to LL 638 or not, thus the DOC removal and the degradation of complex compounds and heavy 639 metals were optimized with a minimal cost. The presence of Pseudomonas, 640 Chryseolinea, and Sphaerochaeta as the dominant genera in the microbial 641 community was found to have the best removal effect, considering the community 642 diversity and ability to recover after exposure to raw landfill leachate. When these 643 three genera were predominant, the most prevalent metabolisms in the microbial 644 community were related to the degradation of complex organic compounds found in 645 the LL. 646 647 648 Figure 9. Main representative metabolisms in microbial communities from adapted 649 and non-adapted compost samples before (no LL) and after (LL) being exposed to 650 raw LL. The diameter of the circles represents the prevalence of each metabolism in 651 the sample. 652 653 4. Conclusions 654 The different pretreatments carried out allowed a high removal of organic matter and 655 heavy metals in the LL. The removal of organic matter was observed along all the 656 pretreatments, although in the case of copper and iron, the removal was especially 657 due to the coagulation/flocculation and filtration processes. The contact of LL with 658 the compost produced an enhancement of humic acids throughout time in the 659 bioreactors, which stimulates the removal of toxic material in this polluted water. The 660 biological treatment with compost reached a higher removal of COD and iron when 661 coagulation/flocculation plus filtration plus photo-Fenton as pretreatment processes 662 were performed. On the other hand, the highest copper removal was obtained when 663 the LL was pretreated by coagulation/flocculation before the biological process. In 664 summary, the toxicity of the raw LL was reduced by the action of the pretreatments 665 and the biological treatment carried out, due to the removal of toxic compounds, 666 such as copper and recalcitrant organic matter. 667 The biological process applied to raw LL led to the lowest costs, but when this 668 process was applied to a LL submitted to all the pretreatments, the operational costs 669 raised due to the increase of reagents. Otherwise, the energy consumption was 670 similar for all the experiments, since all of them included an aerated bioreactor. 671 Concerning the microbial community, it was able to adapt to raw LL, showing a high 672 tolerance and resilience to toxic conditions, both in the compost previously in contact 673 with LL or not, though this item could affect the species composition of the 674 population. However, the genus Sphaerochaeta was able to hold up in all the studied 675 conditions. The prediction of microbial metabolisms also showed a remarkable ability 676 from microorganisms to remove and metabolize different complex and toxic 677 substances. 678 Thus, we can conclude that the application of this airlift bioreactor allows an effective 679 removal of pollutants in the LL with a minimal cost. 680 681 5. Acknowledgments 682 The authors wish to thank to the Chilean Ministry of Education and its Regular 683 Fondecyt N° 1210841, for the financial support and the Central Laboratory for Marine 684 Aquaculture of the Marine Sciences Department of the Universidad Católica del 685 Norte for equipment support. Elena H. del Amo is a Margarita Salas fellow from the 686 Spanish Government (REQ2021). 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