Treatment and reuse of a pesticide-containing wastewater by a combination of physicochemical, biological and membrane processes

Treatment and reuse of a pesticide-containing wastewater by a combination of physicochemical, biological and membrane processes | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Treatment and reuse of a pesticide-containing wastewater by a combination of physicochemical, biological and membrane processes Fernanda Cazelato Gaioto, Maurício Matheus, Bianca Miguel de Souza Chaves, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-2804636/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 11 Sep, 2023 Read the published version in Brazilian Journal of Chemical Engineering → Version 1 posted 5 You are reading this latest preprint version Abstract Proper treatment and reuse of industrial wastewaters are efficient ways to mitigate their environmental impacts. In this work, a pesticide formulation wastewater pretreated by activated carbon was combined with sewage (4:96) and subjected to biotreatment in a lab-scale moving-bed biofilm reactor (MBBR) with 50% media filling ratio and 6h HRT. Throughout 180 days, efficient removal was achieved for organic matter (86%, tCOD) and ammonium (88%). Additionally, the MBBR effluent exhibited higher quality than the water of the river used by the pesticide industry. For evaluating the possibility of wastewater reuse, the effluents from the MBBR (M) and a lubricant industry (L, from the same industrial site) were combined with the river water (R) that feeds the industrial water treatment plant (WTP) and submitted to a lab-scale reproduced WTP: coagulation/flocculation, sedimentation, sand filtration and microfiltration. River water and two combinations (RM: 85:15 and RML: 80:15:5) were assessed. The mixtures improved the efficiency of the lab-reproduced WTP; however, the fouling potential was high (SDI 15 >5) for reverse osmosis at the end of the WTP. Thus, after microfiltration, two ultrafiltration (UF) membranes (10 and 50 kDa) were tested, producing similar quality water (0.02 NTU, low SDI and color). After UF, the total turbidity and color removals for R, RM and RML were, respectively, 99.87%, 99.84% and 99.81%, and 96.2%, 87.3% and 93.1%. The UF implementation produced stable high-quality water, implying a reduction of RO membrane costs and cleaning frequency, while increasing the permeate flux. Ultimately, complete wastewater reuse was enabled by the proposed chain. moving bed biofilm reactor pesticide wastewater treatment ultrafiltration zero disposal industrial wastewater Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 1 Introduction Pesticides are chemical or biological substances used in agriculture to control insects, weeds, and other pests. However, the release of pesticide-contaminated water poses a serious threat to the environment and human health, even at trace concentrations (Li et al. 2018 ; Plakas and Karabelas 2012). Thereby, the proper treatment of pesticide industry wastewater is of paramount importance to avoid water pollution. The main source of wastewater from pesticide formulation industries is the periodic cleaning of equipment and production lines between batches of different pesticide products (Matheus et al. 2020 ). Thus, this wastewater usually contains different pesticide ingredients, which are commonly toxic and persistent (Bachmann Pinto, Miguel de Souza, and Dezotti 2018). Previous studies have shown that the chemical oxygen demand (COD) and biological oxygen demand (BOD) of pesticide production wastewaters are within the range of 150–33750 mg/L and 30–11590 mg/L, respectively (Lindsey Goodwin et al. 2018 ). Matheus et al. ( 2020 ) reported values of total ammoniacal nitrogen, total and soluble COD of 150 mg/L, 16900 mg/L and 12300 mg/L, respectively, for a wastewater from a pesticide formulation industry resulting from various washing operations. The concentration of pesticide substances varies substantially, with some ingredients being detected at concentrations of up to 2500 mg/L (Lindsey Goodwin et al. 2018 ). Biological treatment has been widely used to remove organic compounds in WWTPs due to its cost-benefit relationship and flexibility. Advances in biological technologies have led to the development of more robust systems to remove agro-industrial contaminants, such as the moving bed biofilm reactor (MBBR) (Bachmann Pinto, Miguel de Souza, and Dezotti 2018; Cao et al. 2016 ; Chen, Sun, and Chung 2007). MBBR is a flexible and compact system, in which biomass grows adhered to carriers, making it more specialized. In addition, like other biofilm processes, the MBBR is more resistant to toxic and organic shock loads. Unlike conventional activated sludge systems, the MBBR does not require sludge recycle, and the maintenance of solids inside the reactor makes the cell residence time longer than the hydraulic retention time (Bassin, Dezotti, and Rosado 2018). Industries have been investing in alternatives for water and wastewater reuse to comply with regulations and reduce legal sanctions, water consumption, and production costs. Industrial water reuse usually requires advanced treatments in the polishing stage to remove residual organic matter, nutrients and microorganisms (M. Racar et al. 2019 ). Membrane technologies have received considerable attention for water reuse applications. Reverse osmosis (RO) is a pressure-driven membrane technology widely applied for water and wastewater reuse. RO usually requires pretreatment processes that provide high-quality feed water to minimize fouling formation (Kucera 2010 ; Pearce 2008 ). The use of low-pressure membrane technologies prior to RO, such as microfiltration (MF) and ultrafiltration (UF) membranes, is an attractive option in that sense (Kucera 2010 ; Pearce 2008 ). The UF membrane rejects suspended and dissolved organic carbon, high molecular weight (MW) substances, and microorganisms. Therefore, UF pretreatment can reduce the RO membrane fouling and improve the RO system performance by increasing the permeate flux and membrane lifespan, while reducing the cleaning frequency and energy and chemicals consumption (Kucera 2010 ; Marko Racar et al. 2017 ; Vedavyasan 2007 ). Coagulation and sand filter are cost-effective pretreatments for UF. When applied together, the sand filter reduces turbidity by removing residual particles (M. Racar et al. 2019 ). However, in coagulation/flocculation treatments preceding depth filtration, the removal of polar micropollutants proved to be largely ineffective (Saraiva Soares et al. 2013 ). Generally, only hydrophobic organic micropollutants are removed by adsorbing onto the flocs that are retained in the sand filter (Li et al. 2018 ; Matsushita et al. 2018 ; Thuy et al. 2008 ). Conversely, membrane separation technologies are widely used to remove organic micropollutants, such as pesticides. RO has demonstrated removal efficiency greater than 90% for a broad spectrum of trace organic compounds, including low MW ( 200 g/mol (Goh et al. 2022 ; Plakas and Karabelas 2012). In the literature, studies can be found versing about individual treatment technologies applied to pesticide-containing wastewaters, whether focused on individual persistent substances or complex industrial wastewaters. Other works assess combinations of processes; however, only one was found evaluating the reuse potential of a pesticide-containing wastewater (Bachmann Pinto, Miguel de Souza, and Dezotti 2018). In this sense, this work aims to further evaluate such potential by analyzing a full treatment train that could end up with the total reuse of the pesticide-rich wastewater from a pesticide formulation industry. That industry mixes its pesticide formulation wastewater (pretreated with adsorption onto powdered activated carbon (PAC)) with the sanitary and utilities residuary water, taking it to local activated sludge secondary treatment. In parallel, water is caught from a river and treated in a water treatment plant (WTP) by a combination of coagulation/flocculation, sedimentation, sand filtration, cartridge microfiltration, and reverse osmosis, providing the water at required quality for industrial uses. This study was conducted in two phases (I and II). In phase I, an MBBR was evaluated on a lab scale as an alternative to the existing activated sludge reactor in the industry. The MBBR performance was evaluated in terms of organic and nitrogenous matter removal. A complementary evaluation of biodegradation of a highly water-soluble insecticide active ingredient, Imidacloprid (IMI), was carried out in another MBBR. In phase II, the possibility of total reuse of the treated (non-settled) effluent from the MBBR was evaluated, through the impact generated by its addition to the river water in the performance of the physicochemical processes of the WTP, reproduced at bench scale. There was an additional opportunity to evaluate the insertion of a third stream into the water treatment train: the wastewater from a local lubricants industry, low in organics, nitrogen, and turbidity. Finally, the inclusion of ultrafiltration treatment to further protect the RO modules of the WTP, ensuring a high-quality water feed, was proposed and tested at different pressures and membranes. 2 Materials And Methods 2.1 The Industrial Wastewater and Water Treatment Plants The industrial wastewater from a local plant in Rio de Janeiro, Brazil, is highly complex due to the variety of manufactured pesticide products. The biological treatment is currently performed by an activated sludge system, preceded by an equalization tank. As shown in Fig. 1 , the wastewater from the formulation plant initially passes through a PAC pre-treatment, and then proceeds to a filter press. The filtrate (named EPTAC) goes to the equalization tank, where it is mixed with the sewage and utilities wastewater (SE), in a 4:96 volumetric proportion. Then, this mixture is sent to the activated sludge reactor. Finally, the treated water is discharged into a local river after secondary settling. River water is collected downstream from the location where the treated pesticide effluent is discharged and forwarded to the WTP to be used in the industrial processes. The WTP consists of the following processes: coagulation/flocculation, lamellar decanter, rapid down-flow sand filter, microfiltration cartridge (1µm), and reverse osmosis. Currently, the effluent from a lubricant industry recently installed in the complex, pretreated in a water/oil separator, is also sent to the WTP due to its extremely low concentration of organic matter. 2.2 Phase I: Biological Treatment 2.2.1 MBBR Fed by Industrial Wastewater Two wastewater streams (EPTAC and SE, see Fig. 1 ) were periodically sampled from the pesticide industry. After collection, the samples were kept refrigerated at around 4°C. The average composition of each wastewater is displayed in Table 1 . Currently, these two streams are biologically treated in the industry in a proportion of 4% v/v EPTAC + 96% v/v SE, named as Mix w . This wastewater mixture was regularly prepared to feed the bench-scale MBBR at the same proportion used in the industry. Table 1 Average composition of pesticide industry wastewater samples. Parameter Unit EPTAC SE COD mg/L 4,778 160 sCOD mg/L 4,456 54 NH 4 + -N mg/L 22 44 TSS mg/L 47 155 VSS mg/L 47 96 Turbidity NTU 13.91 30.01 pH - 4.56 7.52 Biological treatment of the industrial effluent mixture was conducted in a laboratory-scale aerobic cylindrical glass MBBR with 6.6 cm diameter and useful volume of 500 mL. The reactor was filled with AnoxKaldnes® K1 carriers (500 m²/m³) made of high-density polyethylene (HDPE) at a filling fraction of 50%, resulting in 250 m 2 /m 3 effective specific surface area. The reactor was fed in upflow mode using a peristaltic pump to control the flow rate and to provide a hydraulic retention time (HRT) of 6 h, based on the previous studies of Matheus et al. ( 2020 ). A porous air diffuser stone was inserted at the bottom of the reactor to aerate the system and maintain good hydrodynamic conditions. The MBBR was inoculated with 25 mL of suspended biological sludge from a bench-scale activated sludge system, fed with 95% synthetic sanitary effluent and 5% leachate (COD ≈ 2400 mg/L), and 8 K1 carriers with established biofilm from a bench-scale MBBR reactor fed with similar wastewater to this work. Initially, over a period of 36 d (acclimation phase), the reactor was fed with synthetic wastewater composed of 0.375 g glucose/L, 0.27 g NaHCO 3 /L, 0.1146 g NH 4 Cl/L, 0.4 g NaCl/L, 0.025 g K 2 HPO 4 /L, 0.020 g KH 2 PO 4 /L, and 0.5 mL of trace metal solution/L, to provide biofilm development. The trace metal solution is described elsewhere (VISHNIAC and SANTER 1957). Then, Mix w was added gradually and slowly for 94 d (adaptation phase). After that, the MBBR was fed with 100% Mix w for 153 d. Finally, the reactor was operated only with SE for 20 d in order to compare the biological activity of the biofilm under different conditions, i.e., in the presence and absence of EPTAC. During the MBBR operation, the pH was kept near neutrality (6.0-7.6) and the temperature ranged from 21 to 26°C. 2.2.2 Maximum and Real Specific Ammonium Removal Rates A batch test was performed to obtain the maximum ammonium removal rate of the microbiota under reactor operating conditions. Batch experiments were conducted during MBBR operation with influent Mix w and SE, after outlet ammonium concentration of less than 5 mg/L was established during continuous operation. First, the reactor was emptied and then filled with the untreated influent (with ammonium concentration of 47 mgNH 4 + -N/L and 67 mgNH 4 + -N/L for Mix w and SE, respectively) was added to the closed reactor. 7 mL samples were collected and filtered through a 0.45 µm nitrate cellulose membrane at time zero and then at intervals of 15 min in the first hour, 30 min in the second hour and every 1 h thereafter, in a total of 5 h. The ammonium concentration was determined over time. Specific maximum ammonium removal rate was determined by linear regression of ammonium concentration over time, taking into account the concentration of volatile attached solids (VAS), and was expressed as mgNH 4 + -N/(gVAS·h). The real specific ammonium removal rate of the system was calculated considering the continuous influent and effluent ammonium concentration (i.e., the removed ammonium under normal operating conditions), the VAS concentration and the HRT applied. 2.2.3 Evaluation of Biodegradation of a Pesticide Active Ingredient in MBBR The active pesticide ingredient selected for biodegradation evaluation in an MBBR was Imidacloprid (purity 99.1%, CAS 138261-41-3), supplied by the industry that provided the wastewaters for this study. This compound was chosen due to its high water solubility (610 mg/L at 20°C), as this property is a cause of high bioaccumulation of compounds in water bodies (Khairkar et al. 2020 ). Imidacloprid (IMI) is a neonicotinoid insecticide with a molecular weight of 255.66 g/mol, molecular formula C 9 H 10 ClN 5 O 2 , and log K ow of 0.57 (at 21°C). IMI biodegradation was investigated in a bench-scale MBBR with a working volume of 315 mL and HRT of 6 h, filled with AnoxKaldnes® K1 carriers at 50% media filling ratio, operated at 23 ± 2°C, pH of 7.41 ± 0.34, and dissolved oxygen concentration of 7.1 ± 0.4 mg/L. The reactor was initially fed with synthetic sanitary wastewater composed of 0.19 g glucose/L (200 mg sCOD/L), 0.34 g NaHCO 3 /L, 0.115 g NH 4 Cl/L (30 mg NH 4 + -N/L), 0.02 g KH 2 PO 4 /L, 0.025 g K 2 HPO 4 /L, and 0.5 mL of trace metal solution/L during 133 d for biofilm formation and acclimation. After MBBR performance stabilization, 5 mg/L of IMI was added to the feed solution, representing around 11.26 mg/L of theoretical COD. The feed was kept in a refrigerator at around 4ºC to minimize biodegradation before the MBBR. 2.3 Phase II: Evaluation of the Possibility of Total Effluent Reuse In order to evaluate the reuse feasibility and the potential impact caused by the additional streams (MBBR effluent and lubricant industry effluent), the following physicochemical processes were analyzed at lab-scale (simulating the industrial WTP): coagulation-flocculation, sedimentation, rapid down-flow sand filter, and microfiltration cartridge. An ultrafiltration step was also analyzed in the pretreatment sequence. Table 2 describes the water matrices used to feed the reverse osmosis pretreatment system. The mixture proportions simulate the average discharge of the secondary effluent, the lubricants industry wastewater, and the water withdrawal from a local river. Table 3 shows the characterization of the river water and the lubricant industry wastewater before the WTP pretreatment steps. The lubricant industry effluent comes from the production process and rainwater collected on the industrial courtyards. This effluent is pretreated in a water/oil separator and then sent to the WTP, due to the low concentrations of organic matter, ammonium, TOC, and turbidity. Table 2 Mixture proportions of river water and effluents treated in MBBR and a lubricant industry, used in reverse osmosis pretreatments. Aqueous Matrix Surface Water (% v/v) Mix tw (% v/v) LI Effluent (% v/v) River 100 - - RM 85 15 - RML 80 15 5 Mix tw = treated effluent in the MBBR, without decantation; LI = Lubricant industry; River = surface water; RM = River + Mix tw ; RML = River + Mix tw + LI Table 3 Characterizations of the river water and the effluent from the lubricant industry. Parameter Unit River Lot 1 River Lot 2 River Lot 3 LI effluent COD mg/L 74 ± 1 47 ± 1 53 ± 8 6 ± 1 sCOD mg/L 72 ± 2 32 ± 2 28 ± 2 7 ± 2 TOC mg/L 15.1 7.6 7.7 3.2 NH 4 + -N mg/L 31 26 24 2 TSS mg/L 35 60 28 10 VSS mg/L 27 37 10 0 Turbidity NTU 15.5 10.8 11.8 0.8 Color uH 158 87 69 7 pH - 7.6 7.5 7.4 7.6 Condutivity µS/cm 622.3 653.3 616.5 143.3 2.3.1 Coagulation-Flocculation and Sedimentation The coagulation-flocculation process was the first pretreatment step performed in the aqueous matrices. Jar test (Digimed MF-01 flocculation module) was used to determine the optimal dosage of chemical agents for the three aqueous matrices. The conditions applied in this test were the same as in the previous study conducted by Bachmann Pinto et al. (2018). The coagulation-flocculation agents used in this study were the same ones used in the pesticide industry: Panfloc AP ® Polyaluminum chloride (PACl) (16.0–18.5% w/w Al 2 O 3, Pan-Americana S.A.) was used as a coagulant; and Flonex® 905 SH, SNF Floerger, was used as anionic flocculant. After the flocculation process, the mixture was left for settling for about 30 minutes, and the supernatant was taken for water quality analysis and proceeding with the downstream processes. In a constant pressure in-line coagulation/UF process, alum and PACl can increase the natural organic matter removal and considerably reduce membrane fouling (Kabsch-Korbutowicz 2006 ). Furthermore, aluminum residuals from coagulation with alum cause colloidal fouling in RO membranes. Thus, PACl becomes an alternative as it minimizes this fouling and allows the reduction of aluminum-antiscalant interactions (Gabelich et al. 2006 ). In addition, using polyelectrolytes at low concentrations, from 0.1 to 1 mg/L, preceding the granular media filtration, can help produce better quality water (Amirtharajah 1988 ). 2.3.2 Rapid Down-Flow Sand Filter The clarified effluents obtained in the coagulation-flocculation and sedimentation processes were sent to a rapid down-flow sand filter with a constant filtration rate of 120 m 3 /(m 2 ·d). The filtration was performed in a cylindrical glass column with 3.7 cm of internal diameter filled with a 40 cm quartz sand bed. The sand is suitable for filtration with a particular size 12/20, uniformity coefficient of 1.42, and effective size of 1.0 mm. The storage of the filtered matrices started after 3 h of continuous filtration, as it is assumed filter maturation and, consequently, a satisfactory and stable quality in terms of turbidity. River matrix filtration was completed after 8 h, while RM and RML matrices were completed after 9 h. 2.3.3 Microfiltration Cartridge Filter After the rapid sand filter, the aqueous matrices followed for filtration in Eaton’s LOFTREX filter cartridge manufactured from polypropylene microfibers, with nominal particle retention of 1 µm and 80% retention efficiency. 2.3.4 Ultrafiltration Experiments Ultrafiltration (UF) tests employed commercial flat sheet membranes NADIR® UP010 P and UH050 P, with respective molecular weight cut-offs of 10 and 50 kDa, indicated for industrial water purification. Table S1 shows further characteristics of the UF membranes. Ultrafiltration experiments were performed in a lab-scale module operating in crossflow mode, with an effective membrane area of 77.7 cm 2 . Fig. S1 shows the UF experimental setup. During the experiment, the concentrate, permeate and excess feed (by-pass) were recirculated into the feed tank and, when the flow stabilized, the permeate samples were collected. The permeate flux was calculated as usual (Eq. (S1), supplemental material). Initially, the virgin UF membranes were compacted with distilled water at a constant transmembrane pressure (TMP) of 2 bar for 2 hours (stabilization time) to determine the water permeability of the membranes. After compaction, the water matrices (River, RM and RML) were filtrated through the UF membrane. All filtration tests were performed at 22 ± 2°C. The UP010 P and UH050 P transmembrane pressures ranged between 2–3 bar and 1–3 bar, respectively. During the experiments, the pressure was kept constant and the permeate flux was measured at time zero (beginning of permeation) and then every 5 min until its stabilization. Then, the filtrate was collected and analyzed in terms of total dissolved solids (TDS), total organic carbon (TOC), color, and turbidity. 2.4 Analytical Procedures Chemical oxygen demand (COD) (5220 D), ammonium (Nesslerization), total suspended solids (TSS) (2540 D), volatile suspended solids (VSS) (2540 E), and TDS (2540 C) were determined following standard methods (APHA, AWWA, and WEF 2017 ; ASTM 2008 ). The concentration of total attached solids (TAS) in MBBR carriers was determined after complete removal of the biofilm from 3 supports with an interdental toothbrush and distilled water, following the total solids method (2540 B) and relating the mass obtained with the number of supports in the MBBR (Matheus et al. 2020 ). Nitrate and nitrite were quantified using Hach NitraVer 5 and NitraVer 2 reagent kits, respectively. pH was measured according to the electrometric method 4500-H + B (APHA, AWWA, and WEF 2017 ), with a Hanna HI2221 pH meter. Soluble COD (sCOD), ammonium, nitrite, and nitrate were determined after filtering the samples in 0.45 µm cellulose nitrate membranes. Turbidity was measured using PoliControl’s AP-2000 turbidimeter, and color was determined using a Hach DR 2800 spectrophotometer at 455 nm. IMI quantification was performed using the Hybrid Quadrupole Thermo QExactive Orbitrap mass spectrometer (Thermo Scientific), with an electrospray ionization source (ESI). It has high resolution and accuracy in masses. The ionization mode used was positive (ESI(+)-Orbitrap-HRMS), mass resolution of 140,000 (FWHM) at m/z 200, spray voltage of 3.6 kV, S-Lens voltage of 60, capillary temperature of 320°C, sheath gas in the ionization source 10u, infusion flow of 10 µL/min, and 50 scans acquired. 2.4.1 Silt Density Index (SDI 15 ) SDI after 15 min (SDI 15 ) was determined using the microfiltration cartridge outlet matrices, since in the current industrial process setup, cartridge filters precede the reverse osmosis modules. The tests followed the ASTM method D4189-07 (ASTM 2014), according to which dead-end filtration of the samples at 22°C was performed in cellulose nitrate microfiltration membrane with 0.45 µm pore size and 47 mm diameter at a constant pressure of 30 psi. 3 Results And Discussion 3.1 Phase I: MBBR Performance During the 153 d of operation with Mix w and 20 d with SE, the MBBR showed total COD removal ranging from 65 to 95% and 76 to 92%, respectively, with an average of around 86% COD removal in both cases. As shown in Fig. 2 , the COD in the influent streams Mix w and SE ranged between 72–557 mg/L and 81–340 mg/L, respectively, while effluent COD presented values below 70 mg/L and 30 mg/L, respectively, with averages of 26 mg/L and 21 mg/L. These values are below the local legislation requirements for chemical industries to discharge into water bodies (COD < 250 mg/L) (INEA 2007). These COD removal values are similar to the results obtained by Cao et al. ( 2016 ) in a two-stage anoxic-aerobic MBBR system (82–91%), and Bachmann Pinto et al. (2018) in an aerobic MBBR (64–89%). Figure 3 shows ammonium concentration fluctuations in the influent Mix w (3–64 mgNH 4 + -N/L) and SE (59–68 mgNH 4 + -N/L). During the reactor operation with Mix w and SE as feed, average ammonium removal efficiencies were 88% and 86%, while average effluent ammonium concentrations were 5 mgNH 4 + -N/L (ranging between 0–22 mgNH 4 + -N/L) and 9 mgNH 4 + -N/L (ranging between 5–12 mgNH 4 + -N/L), respectively. After the 75th day of operation, there was an abrupt increase in the influent ammonium concentration and, consequently, a decrease in removal efficiency. Thus, an adaptation period to the higher nitrogen load was necessary. As commonly known, autotrophic nitrifying bacteria exhibit low growth rates and are quite sensitive to sudden changes in influent conditions (Metcalf & Eddy et al. 2014 ). 48 d later (123rd day), ammonium levels dropped to below 1 mg/L, but they increased in the long-term operation, fluctuating between 3 and 10 mg/L. The biofilm formed in the MBBR carriers was thin and evenly distributed over the media (Fig. S2), regardless of the variations of influent characteristics. However, a lower thickness was observed when the MBBR was fed with SE, likely because the reduction of organic load during that period limited the growth of heterotrophic organisms, causing their detachment and decreasing the amount of adhered biomass. Under these conditions, the biofilm becomes thinner and enriched in nitrifying bacteria (Bassin et al. 2012 ). In fact, the specific maximum ammonium removal rate increased from 4.7 to 13.9 mgNH 4 + -N/(gVAS.h) when the reactor feed shifted from Mix w (47 mg NH 4 + -N/L; 78 mg sCOD/L) to SE (67 mgNH 4 + -N/L; 47 mg sCOD/L). In addition, the results show that after the day 119, the reactor operated at a real specific ammonium removal rate equal to the maximum one, i.e., at the reactor maximum capacity. Consequently, in this condition, residual ammonium was always found in the effluent. Therefore, when a higher ammonium load was fed to the system, a lower performance was attained, and the treated effluent did not comply with local legislation (< 5 mgNH 4 + -N/L) (Fig. 3 ) (INEA 1986). Regarding the nitrification products, nitrate prevailed in the effluent throughout the MBBR operation period (on average 90.5% of inorganic N for Mix wt ), evidencing the occurrence of complete nitrification, i.e., the conversion of ammonium to nitrate by the sequential action of ammonium-oxidizing bacteria (AOB) and nitrite-oxidizing bacteria (BON) (Metcalf & Eddy et al. 2014 ). The MBBR operating conditions are important for the development and maintenance of the microbial consortium within the biofilm. According to Metcalf & Eddy et al. ( 2014 ), optimal nitrification is favored at pH between 7.5–8.0. Within the MBBR, the pH ranged from 6.0 to 7.6 (6.9 on average), with changes linked to variations in the influent ammonium concentration, with the pH value decreasing with the higher amount of nitrified ammonium, associated with the release of H + ions. At the lowest values of pH, a decrease in ammonium removal was observed (Fig. 3 ) since pH values below 6.8 significantly decrease the nitrification rate (Metcalf & Eddy et al. 2014 ). Thus, pH control was performed to keep it at acceptable values. Furthermore, the pH values in the effluent met the requirements of the local legislation (5.0–9.0) (INEA 1986). Hydrolysis and further degradation of particulate organic compounds by the biofilm allowed wastewater clarification and consequently reduced turbidity. In fact, the treated effluent presented low content of total suspended solids (8–78 mgTSS/L Mix tw ; 41–48 mgTSS/L SE) and turbidity (0–12 NTU Mix tw ; 3–21 NTU SE). In addition, the suspended solids in the effluent were mostly volatile (VSS/TSS = 0.76 (Mix tw ); VSS/TSS = 0.80 (SE)), which can be attributed to suspended organic matter (Fig. S3). In contrast, the adhered biomass concentration presented higher values as expected, given the MBBR characteristics. The average TAS measured when the MBBR was fed with Mix w and SE were 2.1 gTAS/L and 1.0 gTAS/L, respectively. The typical attached biomass concentration range reported for MBBR systems is 2.0–8.0 kgTAS/m 3 , similar to the biomass concentration found in activated sludge systems. However, in the MBBR process, the microorganisms are more specific and active, improving treatment efficiency (Bassin, Dezotti, and Rosado 2018). The results showed that the replacement of the activated sludge system by an MBBR is an interesting alternative, given its inherent characteristics and the quality of the treated effluent, which presented quality superior than the water captured from the local river for industrial use (Table 3 and Table 4 ). In this context, in order to optimize the WTP, the possibility of reusing the biologically treated wastewater from the MBBR together with the water from the lubricants industry, and the impact on the reverse osmosis pretreatment process were evaluated. In addition, a complementary study was conducted with the insecticide active ingredient IMI, as a model pesticide, in order to determine whether its biodegradation occurs in an MBBR and whether the effluent carries active ingredients to the receiving water body. Table 4 Characteristics of the influent and treated effluent of the MBBR. Parameter Unit Influent Mix w Effluent Mix tw Influent SE Effluent SE COD mg/L 206 ± 103 26 ± 13 183 ± 113 21 ± 5 SCOD mg/L 102 ± 29 17 ± 9 39 ± 2 24 ± 6 NH 4 + -N mg/L 33 ± 20 5 ± 6 64 ± 4 9 ± 2 NO 3 − -N mg/L N/A 24 ± 16 N/A 36 ± 5 NO 2 − -N mg/L N/A 0.4 ± 0.1 N/A 0.5 ± 0 TSS mg/L 123 ± 92 41 ± 20 307 ± 143 45 ± 5 VSS mg/L 65 ± 28 30 ± 14 124 ± 90 36 ± 6 Turbidity NTU 48 ± 61 3 ± 3 160 ± 103 8 ± 6 pH - 7.2 ± 0.4 6.8 ± 0.4 7.9 ± 0.1 7.1 ± 0.3 N/A: not available. 3.2 Evaluation of Imidacloprid Biodegradation In parallel, another MBBR was used to evaluate the removal of a chosen active ingredient, as explained in section 2.2.3. After exposing the MBBR fed only with synthetic sewage to 5 mg/L of the IMI insecticide, the COD removal performance dropped from an average of 83.7 ± 8.2% (n = 17, 90 days) to 66.6 ± 6.2% (n = 5) during the first 10 days with IMI, representing a significant statistical difference (ANOVA p-value = 0.00037, F = 0.9996). Meanwhile, the performance of ammoniacal nitrogen removal never got affected, even when the biofilm was first exposed to IMI. One possible explanation is that nitrifying autotrophic organisms are mostly located in the inner part of the biofilm, so they are more protected from IMI exposure. On the other hand, the activity of heterotrophic bacteria, dominant on the outer surface, was affected. The ammoniacal nitrogen removal actually increased from 93.8 ± 3.8% (n = 16, 63 days) to 99.5 ± 0.8% (n = 59, 383 days) when comparing the period without IMI and the whole operation with IMI. This increase was probably due to the higher adaptation period of the nitrifying microorganisms. The effluent mean concentrations of ammoniacal nitrogen were 1.48 ± 0.92 mg/L (without IMI) and 0.13 ± 0.22 mg/L (with IMI). Figure 4 shows the average inlet and outlet COD and NH 4 + -N concentrations, as well as the correspondent removal percentages, after a stabilized performance with IMI (i.e., the whole period for NH 4 + -N and after the 10 first days for COD). It is noticeable that, after acclimation with IMI, the MBBR maintained a similar average (ANOVA p-value = 0.0228, F = 0.9772) organic matter removal (87.4 ± 5.3%, n = 43, 369 days) when compared to the operation without IMI. The respective average effluent COD was 29.5 ± 14.4 mg/L (without IMI) and 25.2 ± 11.5 mg/L (with IMI). Overall, the MBBR demonstrated the robustness to adapt to the pesticide tested and still provide good COD and ammonium removals, as one should expect when assessing the results with the industrial wastewater in the previous section (3.1). However, when analyzing the IMI concentrations, no removal was observed for this compound, as the mean effluent concentration was 5.8 ± 0.2 mgIMI/L (n = 5, 399 days), compatible with the influent concentration (5 mgIMI/L). Therefore, the non-removal of the active ingredient indicates that neonicotinoid pesticides may appear in effluents of aerobic MBBRs and evidences the need for efficient post-treatments, which guarantee that the treated effluent is not a source of contamination in the environment. Thus, the effluent treated in the MBBR should not be disposed of directly in the river, and should be directed to the industry WTP. 3.3 Phase II: Reuse Evaluation Once the effluent treated in the MBBR reached the discharge limits imposed by local legislation, the possibility of total reuse of the wastewater from the pesticide industry and lubricant industry was evaluated. Conventional RO pretreatments applied in WTP of the industrial complex were tested at lab-scale in the following order: coagulation/flocculation, sedimentation, sand filtration, and cartridge microfiltration. The treatment sequence was performed using the water withdrawn from the local river (River) - after screening, equalization and sieving in fine mesh - and the RM and RML mixtures, in the proportions shown in Table 2 , to determine the impact of the addition of these streams on the RO pretreatment processes. The aqueous matrices characterization is summarized in Table S2. 3.3.1 Coagulation-Flocculation In the first pretreatment stage, the optimal coagulant and flocculant concentrations were determined considering color and turbidity values, as they presented significant variations. The optimal coagulant and flocculant concentrations were 40 mg/L and 0.2 mg/L for river water, and 20 mg/L and 0.2 mg/L for both RM and RML aqueous matrices. The turbidity removal after the reproduction of the process corresponded to 54% (from 15.4 to 7.06 NTU), 77% (from 10.7 to 2.43 NTU), and 82% (from 12.5 to 2.23 NTU), while color removal was 70% (from 158 to 47 Pt-Co units), 67% (from 79 to 26 Pt-Co units), and 63% (from 73 to 27 Pt-Co units) for River, RM and RML samples, respectively. Regarding the removal of pesticides by coagulation, adsorption is the main mechanism responsible for removal. The greater the hydrophobicity of these compounds, the better the adsorption to the floc or sludge and removal efficiency (Li et al. 2018 ; Thuy et al. 2008 ). The study conducted by Thuy et al. ( 2008 ) indicated that the removal of pesticides (aldrin, dieldrin, atrazine, and bentazone) occurs more by adsorption onto organic matter than by the destabilization of colloids. Saraiva-Soares et al. (2013) have investigated the removal of pesticides/metabolites using conventional drinking water treatment processes. The results showed that the removal was low for all contaminants tested (ethylenethiourea median ≤ 11%, 1,2,4-triazole median ≤ 18% and endosulfan median ≤ 54%, all in decanted water), and that the removal decreased when the initial concentration increased. Endosulfan was better removed than the others due to its low water solubility and high log K ow (4.75) and molar mass (406.93 g/mol). Matsushita et al. ( 2018 ) observed that the concentration of most of studied compounds (28 pesticides transformation products and 15 parent pesticides) was not modified after coagulation-sedimentation, with PACl as coagulant. Only etofenprox, the most hydrophobic compound (log K ow = 6.3) tested, was removed. 3.3.2 Sand Filter The supernatant aqueous matrices treated by the coagulation/flocculation process were subsequently fed to the rapid sand filter, in which the turbidity removal was 42%, 54% and 57% for the River (4.1 NTU), RM (1.1 NTU) and RML (0.95 NTU) matrices, respectively. The apparent color values were 36 Pt-Co (River), 22 Pt-Co (RM) and 22 Pt-Co units (RML). In addition, it was noted that the characteristics of the mixtures were better than that of the raw river water, thus influencing the subsequent treatment steps. In fact, the main purpose of filtration is to remove the suspended particles from the influent, providing a high clarity of the filtrate (turbidity reduction) (Amirtharajah 1988 ; Howe et al. 2012 ). Coagulation-flocculation followed by a sand filter has been shown to be ineffective in removing polar micropollutants (Saraiva Soares et al. 2013 ). Research carried out by Li et al. ( 2018 ) analyzed the effect of recycling spent filter backwash water on the removal of 14 organic pesticides and simulated the conventional drinking water treatment process (coagulation, flocculation, sedimentation, and rapid sand filter) with a raw water from Heihe reservoir (China), enriched with pesticides. The results showed that the pesticide removal by these processes was very low. Removal of hydrophobic pesticides (log K ow <3.8, diazinon, tolclofos-methyl, profenofos and chlorpyrifos) ranged from 29.1–57.5%; of hydrophilic ones (log K ow < 2.6, cyanazine, pirimicarb, atrazine and carbaryl) was lower than 3%; and of the others much less hydrophobic was lower 21%. Furthermore, micropollutants with low hydrophobicity (log K ow < 5.0) had a limited removal. Thus, more effective pesticide removal treatments should be incorporated into treatment plants in order to mitigate possible environmental risks. For this reason, the RO separation process is essential in the WTP. 3.3.3 Microfiltration Cartridge Filter The main impact of the microfiltration cartridge was the reduction in color and turbidity, which were, respectively, 2.6 NTU and 28 Pt-Co units for River, 0.8 NTU and 20 Pt-Co units for RM, and 0.7 NTU and 18 Pt-Co units for RML. After such effluent qualities were reached, the aqueous matrices from the cartridge filter were submitted to SDI 15 tests, as this parameter is used to assess the fouling potential of reverse osmosis membranes and the efficiency of the clarification process (ASTM 2014). As the SDI 15 test is normally applied to waters with turbidity lower than 1 NTU, the test was performed using only RM and RML matrices (ASTM 2014; Baker 2004 ). However, RM and RML presented an SDI 15 of 5.5 and 5.7, respectively, which is considered impracticable for feeding RO modules, indicating the need for pretreatment (Mosset et al. 2008 ). In order to minimize RO fouling, an SDI 15 < 3 is desired. For effluents with higher SDI values, it is recommended to use additional pretreatment processes (Baker 2004 ; Mosset et al. 2008 ). The yellow/brown color films formed on the membrane surface during the SDI 15 tests indicate that the fouling was probably caused by organic compounds not removed in previous processes (Abuabdou et al. 2020 ). 3.3.4 Ultrafiltration Ultrafiltration (UF) has been widely used for the removal of microorganisms and suspended solids, allowing the effluent to reach SDI and turbidity values below 2 and 0.02 NTU, respectively (Baker 2004 ). UF can be used to eliminate compounds with molecular weight (MW) that tend to clog the RO membrane (Wolf, Siverns, and Monti 2005 ). Besides providing excellent RO feed water quality at low pressure and ensuring a stable RO system performance, with a possible 20% increase of the permeate flux (Vedavyasan 2007 ), the UF pretreatment also reduces the frequency of RO membrane chemical cleaning. Given these characteristics and the challenge of obtaining an SDI 15 < 3 using conventional pretreatments, the use of UF as a pretreatment of RO systems has become an increasingly relevant option (Miyoshi et al. 2015 ; Vedavyasan 2007 ). Therefore, it was proposed to insert the UF process before RO in the WTP of the industrial complex. The water permeability of the UP010 P and UH050 P fresh membranes used in this work was measured by filtrating pure water at different pressures, and the results obtained were 34.9 L/(m 2 ·h·bar) and 227.9 L/(m 2 ·h·bar), respectively. These values are consistent with those provided by the manufacturer for the UH050 P membrane, and slightly lower for the UP010 P one (Table S1 ), probably due to impurities in the filtration module. It was found that the flux of pure water increased linearly as a function of the pressure applied to the UF system for both UF membranes. In addition, the selected membranes can be classified as hydrophilic, since the angle formed between the membrane-liquid boundary and liquid-gas tangent, i.e., the contact angle (CA), is less than 90°, as shown in Table S1 . However, UP010 P is less hydrophilic because the CA of the UH050 P membrane is smaller (Miyoshi et al. 2015 ; Otitoju, Ahmad, and Ooi 2018). Hydrophilic membranes are advantageous because, according to Wardani et al. ( 2020 ), these are less susceptible to organic fouling, which is responsible for decreasing productivity and increasing energy costs. Figure S4 and Fig. S5 illustrate the decrease in permeate flux of both UF membranes over time under different pressures for the aqueous matrices River, RM, and RML from the cartridge filter. The UH050 P membrane presented higher permeate flux at the evaluated pressures, which can be explained by its greater hydrophilic nature, permeability, and pore size compared to the UP010 P membrane (Luo 2014 ). As the UH050 P membrane has a larger pore size, the water permeation resistance is lower. The experiment with the UH050 P membrane initially showed a rapid and exponential water flux decline, while the UP010 P membrane flux decline occurred more smoothly. In both experiments, for all tested pressures, a constant water flux was reached after 100 min (for UP010 P) and 120 min (for UH050 P). A possible justification is that when the membrane has larger pores, the particles that cause fouling enter their pores more easily, causing their blockage (Wang et al. 2018 ). Besides, the higher permeability of the UH050 P membrane initially leads to an increase in particle concentration near its surface, concentration polarization, generating an increase in the thickness of the cake and, consequently, the flux decline (Baker 2004 ). Concentration polarization is unavoidable for any filtration, even for crossflow (tangential flow), in which shear force prevents the formation of a thick cake layer (Song and Elimelech 1995). Thus, there is a decrease in permeate flux at the beginning of permeation. According to Juang et al. ( 2007 ), the initial rapid drop in the flux is probably due to partial pore blockage. Then, an increase in the resistance generated by the formation of a cake layer on the surface of the membrane causes the flux to gradually decrease until it approaches a steady-state condition. Moreover, it was observed that in the permeations with the aqueous matrices, the increase in transmembrane pressure (TMP) caused an increase in permeate flux, similar to that observed by Huang et al. ( 2014 ). It was also observed that the greater the turbidity presented by the feed water of the UF module, the lower the permeate flux. So, the flux increased in the following order: River (2.61 NTU) < RM (0.84 NTU) < RML (0.69 NTU). Xia et al. ( 2004 ) observed that when the UF feed water had turbidity of 20 NTU and 450 NTU, it took 60 min and only 10 min for the permeate flux to decrease by 50%, respectively. However, the RM-fed UP010 P membrane did not exhibit this behaviour at 3 bar, with the permeate flux for the RM-fed experiment lower than that of the River-fed trial, despite the lower turbidity of RM. This is possibly due to some alteration in the pressurization of the permeation system when running with the River and/or the RM matrices. Pure water fluxes are used as reference to evaluate variations in flux throughout the permeation process (Huang et al. 2014 ). Figure 5 shows the normalized flux after its stabilization to the two membranes fed with River, RM and RML. The results presented by the UH050 P membrane show that at 2 and 3 bar, the decline of flux was similar and relatively smaller than that at 1 bar, and corresponded to 19% of the pure water flux. The UP010 P membrane, on the order hand, showed a smaller drop in the flux, reaching a minimum of 50% of the pure water flux. According to Habert et al. ( 2006 ), the flux of a UF membrane can decrease in such a way that it can reach 10% of permeate flux with pure water. This difference is due to phenomena such as concentration polarization and particle adsorption on the membrane. Overall, the addition of MBBR-treated effluent and the lubricant industry wastewater to the river water positively affected the usual RO pretreatments of the WTP and the performance of UF membranes. After the UF permeation experiments, it was observed a film on the surface of the membranes, which was more evident on the UH050 P membranes, corroborating the obtained results of lower permeate flux. In addition, the formed films color indicates that the possible cause of membrane fouling was organic compounds (Fig. S6), as shown in the SDI 15 test (Mosset et al. 2008 ). After permeation, the aqueous matrices presented turbidity below the detection limit (< 0.02 NTU). Color reduction was also observed, and slightly lower values were obtained for UP010 P. The same was observed for TOC removal, however, at 3 bar (Table 5 ). Considering the permeate water quality and permeation fluxes, the UH050 P was proposed for use in the industrial complex in the pressure range of 2–3 bar. The insertion of the UF process is a pretreatment for RO allowing obtaining high quality water, with turbidity < 0.02 NTU (SDI 15 < 3), and color of 6 Pt-Co units (River), 10 Pt-Co units (RM) and 5 (RML) Pt-Co units. Hence, the UF filtrate can proceed to the reverse osmosis module, allowing the complete reuse of MBBR-treated and lubricant industry effluents. Table 5 Quality of aqueous matrices fed to UF membranes (after cartridge microfiltration) and their permeates. Parameter Unit Feed Permeate (UP010 P) Permeate (UH050 P) Pressure bar - 2.0 3.0 1.0 2.0 3.0 River TDS mg/L 303 250 270 270 243 233 TOC mg/L 7.7 4.1 2.9 3.4 3.3 3.4 Color Pt-Co units 28 4 4 6 5 6 Turbidity NTU 2.61 0.02 0.02 0.02 0.02 0.02 RM TDS mg/L 406 310 389 385 380 345 TOC mg/L 5.0 3.4 2.9 4.6 4.7 5.6 Color Pt-Co units 20 5 6 9 10 10 Turbidity NTU 0.84 0.02 0.02 0.02 0.02 0.02 RML TDS mg/L 392 387 380 346 328 338 TOC mg/L 6.9 4.1 2.7 4.5 5.3 5.5 Color Pt-Co units 18 4 3 5 5 4 Turbidity NTU 0.69 0.02 0.02 0.02 0.02 0.02 Some studies showed the importance of pretreatments prior to UF and compared the quality of treated water. Racar et al. ( 2017 ) pointed out the efficiency of using the sand filter before the UF process, since the filter reduces suspended particles and organics, thus increasing the critical flux and decreasing the membrane fouling. Lorain et al. ( 2007 ) compared the conventional pretreatment of RO (coagulation/sand filtration) with coagulation/UF for the desalination of raw seawater (SDI 6.1–6.4) and obtained SDI of 5.8–5.9 and 1.2–2 after the sand filter and UF, respectively. Water pretreated in the sand filter caused a loss of 28% of the permeability of RO membranes after 30 days, while the loss with the UF-pretreated water was 0% for 20 days due to the high quality of the feed water (turbidity < 0.1 NTU). Increasingly, ultrafiltration is now recognized as the best pretreatment option for seawater desalination by RO due to water characteristics and limitations of the conventional pretreatment processes, such as coagulation, flocculation and sand filtration (Lorain et al. 2007 ). Racar et al. ( 2019 ) studied the reclamation of the rendering plant secondary effluent (SE) and observed that the fouling of the UF membranes decreased considerably (50–95%) when coagulation and sand filtration pretreatment was performed before UF. Furthermore, this sequence of treatment processes resulted in a permeate water that can be reused in the treatment plant and for irrigation. Regarding the pesticide industry wastewater, Bachmann Pinto et al. (2018) assessed biological treatment followed by conventional and membrane processes aiming at water reuse. Microfiltration (0.45 µm) and ultrafiltration (100 kDa) were tested, and, in both processes, the permeate waters showed turbidity of 0.02 NTU and color of 10 Pt-Co units, which are similar to the results obtained in this study. The high quality water produced by UF, with low SDI values, improves the hydraulic performance of the RO, increases the permeate flux and membrane lifespan, and reduces fouling, cleaning frequency, energy consumption, and process costs (Lorain et al. 2007 ; Vedavyasan 2007 ; Wolf, Siverns, and Monti 2005 ). In this way, UF generates high quality feed water for RO modules, which, besides being responsible for optimizing the use of water resources through the reuse of treated water, are an alternative for the removal of pesticides whose MW range from 200 to 400 g/mol (Kiso 2001 ). Therefore, RO membranes with a molecular weight cut off in this range may be suitable for pesticide removal. Although membrane separation processes depend on several parameters, there are indications that size exclusion is the main rejection mechanism (Plakas and Karabelas 2012). RO treatment may enable pesticide rejections greater than 90% (Chian, Bruce, and Fang 1975; Dražević et al. 2011 ; Khairkar et al. 2020 ; Mehta et al. 2015). Imidacloprid rejection by RO was studied by Genç et al. (2017), who established as optimized conditions the following: BW30 membrane, TPM 30 bar, volume reduction factor 3 and pH 11. The IMI rejection for these conditions was 97.80%. Khairkar et al. ( 2020 ) obtained IMI rejections during RO water purification greater than 90% when using PDMS-coated TFC membrane (10 ppm feed concentration). 3.3.5 Proposed Treatment Train Figure 6 summarizes the color and turbidity removal results of the proposed pretreatment train for the RO modules, stressing the quality of permeates and the importance of the UF process. The combined processes presented excellent performance, achieving total turbidity removal efficiency of 99.9%, 99.8%, and 99.8%, and color removal of 96.2%, 87.3% and 93.1% for River, RM and RML matrices, respectively. Therefore, the proposed configuration of the pretreatment system for the RO unit could be composed of: coagulation/flocculation, sedimentation, sand filtration, cartridge microfiltration, and ultrafiltration (UH050 P; 2–3 bar). The final proposal for WTP optimization of the industrial complex aiming at the total reuse of the biologically (MBBR) treated pesticide-containing effluent and the lubricants industry effluent is illustrated in Fig. 7 . The results obtained in this study show that implementing the UF process after the current conventional RO pretreatments can provide a high quality feed water, reduce the fouling of the RO membranes, and, consequently, minimize costs. The final water could be reused in industrial processes with compatible water demand, such as cooling towers, boilers, and/or fire suppression systems, as well in restrooms, to wash patios, etc. 4 Conclusions The biological treatment of an industrial pesticide-containing wastewater in an MBBR was efficient in terms of average organic matter (86%) and ammonium (88%) removal. The MBBR treated effluent met the standards for disposal in surface water bodies, besides presenting superior quality compared to the receiving river water. The inclusion of that and the lubricant effluent streams to the withdrawn river water, in addition to improving the water treatment plant feed water quality, positively affected the RO pretreatment processes efficiency. However, the high fouling potentials (SDI 15 > 5) after microfiltration exposed the need to insert a more selective treatment, such as ultrafiltration, to produce a better RO feed water quality. The two UF membranes evaluated (UP010 P and UH050 P) presented similar results of permeate water turbidity (0.02 NTU) and low color, with a slightly higher permeate flux achieved for the UH050 P membrane. Overall, the proposed treatment train offered exceptional performance, reaching removal efficiencies of total turbidity of 99.9%, 99.8%, and 99.8%; and color of 96.2%, 87.3% and 93.1%, for River, RM and RML matrices, respectively. Furthermore, the non-removal of Imidacloprid during the biological treatment in the MBBR highlights the need to send the treated effluent to the WTP, thereby ensuring that the RO removes the compounds that are not biodegraded and, consequently, do not make them a source of contamination of the environment. Therefore, the sequence of RO pretreatments proposed in this study allows producing high-quality water and enables the total reuse of wastewater streams in the industrial complex, minimizing the RO chemical cleaning frequency, operating costs, and increasing permeate flux and membrane lifespan. Declarations On behalf of all authors, the corresponding author states that there is no conflict of interest. The authors would like to thank the financial support of the Brazilian government agencies CAPES and CNPQ. Acknowledgments The authors would like to thank the financial support of the Brazilian government agencies CAPES (Coordenação de Aperfeiçoamento Pessoal de Nível Superior) and CNPQ (Conselho Nacional de Desenvolvimento Científico e Tecnológico). References Abuabdou, Salahaldin M.A., Waseem Ahmad, Ng Choon Aun, and Mohammed J.K. 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Racar, Marko, Davor Dolar, Ana Špehar, and Krešimir Košutić. 2017. “Application of UF/NF/RO Membranes for Treatment and Reuse of Rendering Plant Wastewater.” Process Safety and Environmental Protection 105: 386–92. https://linkinghub.elsevier.com/retrieve/pii/S0957582016302853. Saraiva Soares, A. F. et al. 2013. “Efficiency of Conventional Drinking Water Treatment Process in the Removal of Endosulfan, Ethylenethiourea, and 1,2,4-Triazole.” Journal of Water Supply: Research and Technology-Aqua 62(6): 367–76. https://iwaponline.com/aqua/article/62/6/367/29168/Efficiency-of-conventional-drinking-water. Song, Lianfa, and Menachem Elimelech. 1995. “Theory of Concentration Polarization in Crossflow Filtration.” Journal of the Chemical Society, Faraday Transactions 91(19): 3389. http://xlink.rsc.org/?DOI=ft9959103389. Thuy, Pham Thi et al. 2008. “To What Extent Are Pesticides Removed from Surface Water during Coagulation-Flocculation?” Water and Environment Journal 22(3): 217–23. https://onlinelibrary.wiley.com/doi/10.1111/j.1747-6593.2008.00128.x. Vedavyasan, C.V. 2007. “Pretreatment Trends — an Overview.” Desalination 203(1–3): 296–99. https://linkinghub.elsevier.com/retrieve/pii/S0011916406012781. VISHNIAC, W, and M SANTER. 1957. “The Thiobacilli.” Bacteriological reviews 21(3): 195–213. http://www.ncbi.nlm.nih.gov/pmc/articles/PMC180898/. Wang, Li et al. 2018. “Integrated Aerobic Granular Sludge and Membrane Process for Enabling Municipal Wastewater Treatment and Reuse Water Production.” Chemical Engineering Journal 337: 300–311. https://doi.org/10.1016/j.cej.2017.12.078. Wardani, A.K., D. Ariono, S. Subagjo, and IG. Wenten. 2020. “Fouling Tendency of PDA/PVP Surface Modified PP Membrane.” Surfaces and Interfaces 19(10): 100464. https://linkinghub.elsevier.com/retrieve/pii/S246802301930639X. Wolf, Peter H., Steve Siverns, and Sandro Monti. 2005. “UF Membranes for RO Desalination Pretreatment.” Desalination 182(1–3): 293–300. https://linkinghub.elsevier.com/retrieve/pii/S0011916405004431. Xia, Shengji, Jun Nan, Ruiping Liu, and Guibai Li. 2004. “Study of Drinking Water Treatment by Ultrafiltration of Surface Water and Its Application to China.” Desalination 170(1): 41–47. https://linkinghub.elsevier.com/retrieve/pii/S0011916404800171. Supplementary Files SupplementalMaterialC.pdf Cite Share Download PDF Status: Published Journal Publication published 11 Sep, 2023 Read the published version in Brazilian Journal of Chemical Engineering → Version 1 posted Reviewers agreed at journal 17 Apr, 2023 Reviewers invited by journal 17 Apr, 2023 Editor invited by journal 13 Apr, 2023 Editor assigned by journal 13 Apr, 2023 First submitted to journal 11 Apr, 2023 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-2804636","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":192625956,"identity":"eb62c668-369a-45a7-8638-1294a3c04eb2","order_by":0,"name":"Fernanda Cazelato Gaioto","email":"","orcid":"","institution":"Federal University of Rio de Janeiro: Universidade Federal do Rio de Janeiro","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Fernanda","middleName":"Cazelato","lastName":"Gaioto","suffix":""},{"id":192625957,"identity":"d064817a-6b24-4d34-afe1-bc8bc47be643","order_by":1,"name":"Maurício Matheus","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABDElEQVRIiWNgGAWjYLCCBAYJGPMAEDODCAkZIrUkgFSzJYC08BBrH0gLjwGIiVOLbvsZsw8PaizkGNgPsG74+eOOnMH5M59f3aix4GFgP3x0AxYtZmdyjGckHJMwZuBJYLvZk/DM2OBG7jbrnGNAh/Gkpd3ApuVAjjFDYoMEEDGw3eBJOJy44QbvNuMcNqAWCR4zrFrOv0Foufkn4XD9hvNnnhnn/MOj5QaSLbeBtiQYHMhhfpzbhk/Ls2IGkF/YeBLbbsukHTaceSPNjDm3T4KHDZdfzidvZvxRUyfHz3742M03Nofl+c4ffvw55xtEBJsWOGBjYGyAsyUgIiQA5g+kqB4Fo2AUjIJhDwD8F2MoMkA8FgAAAABJRU5ErkJggg==","orcid":"https://orcid.org/0000-0002-0638-0230","institution":"Federal University of Rio de Janeiro: Universidade Federal do Rio de Janeiro","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Maurício","middleName":"","lastName":"Matheus","suffix":""},{"id":192625958,"identity":"fa729f9e-68be-40fb-95ba-cb0af28ed862","order_by":2,"name":"Bianca Miguel de Souza Chaves","email":"","orcid":"","institution":"The University of Arizona","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Bianca","middleName":"Miguel de Souza","lastName":"Chaves","suffix":""},{"id":192625959,"identity":"633672ae-860d-4b28-bbbb-63cdf0bf1cc3","order_by":3,"name":"Juacyara Carbonelli Campos","email":"","orcid":"","institution":"Federal University of Rio de Janeiro: Universidade Federal do Rio de Janeiro","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Juacyara","middleName":"Carbonelli","lastName":"Campos","suffix":""},{"id":192625960,"identity":"1e6dbab8-5b15-47c7-8b12-3ada2c6d8497","order_by":4,"name":"Thamara Andrade Barra","email":"","orcid":"","institution":"Federal University of Rio de Janeiro: Universidade Federal do Rio de Janeiro","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Thamara","middleName":"Andrade","lastName":"Barra","suffix":""},{"id":192625961,"identity":"44253818-691b-48d4-8aad-5b702073100b","order_by":5,"name":"Débora de Almeida Azevedo","email":"","orcid":"","institution":"Federal University of Rio de Janeiro: Universidade Federal do Rio de Janeiro","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Débora","middleName":"de Almeida","lastName":"Azevedo","suffix":""},{"id":192625962,"identity":"3f801882-2877-4bca-875b-090cf47be342","order_by":6,"name":"João Paulo Bassin","email":"","orcid":"","institution":"Federal University of Rio de Janeiro: Universidade Federal do Rio de Janeiro","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"João","middleName":"Paulo","lastName":"Bassin","suffix":""},{"id":192625963,"identity":"1f6f1da6-85cc-4e6b-8352-efaa33de7dd0","order_by":7,"name":"Márcia Walquíria de Carvalho Dezotti","email":"","orcid":"","institution":"Federal University of Rio de Janeiro: Universidade Federal do Rio de Janeiro","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Márcia","middleName":"Walquíria de Carvalho","lastName":"Dezotti","suffix":""}],"badges":[],"createdAt":"2023-04-12 08:31:42","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-2804636/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-2804636/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s43153-023-00394-z","type":"published","date":"2023-09-11T15:02:36+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":36011082,"identity":"54eebd8c-642a-4abb-a8f0-4e41d7c75d0a","added_by":"auto","created_at":"2023-04-19 15:24:01","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":36567,"visible":true,"origin":"","legend":"\u003cp\u003eFlowchart of wastewater treatment of the industrial complex.\u003c/p\u003e","description":"","filename":"1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-2804636/v1/5f6726be5791c0a519fc921b.jpg"},{"id":36009836,"identity":"cb796f12-1936-4e5e-b762-dd2607c74afc","added_by":"auto","created_at":"2023-04-19 15:08:01","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":81040,"visible":true,"origin":"","legend":"\u003cp\u003eInfluent and effluent COD (bars) and COD removal efficiency (●) during the MBBR operation with Mix\u003csub\u003ew\u003c/sub\u003e and SE.\u003c/p\u003e","description":"","filename":"2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-2804636/v1/96eca0084929a9b64445a35c.jpg"},{"id":36009835,"identity":"f708e0cc-abfd-4e14-81b6-702be66465df","added_by":"auto","created_at":"2023-04-19 15:08:00","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":87352,"visible":true,"origin":"","legend":"\u003cp\u003eInfluent and effluent NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e-N concentration and removal efficiency (●) during the MBBR operation with Mix\u003csub\u003ew\u003c/sub\u003e and SE as feeding stream.\u003c/p\u003e","description":"","filename":"3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-2804636/v1/2e03a8b111f8eedf90862643.jpg"},{"id":36010691,"identity":"e1741a9e-ef32-4441-9882-c3796a032b44","added_by":"auto","created_at":"2023-04-19 15:16:01","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":49406,"visible":true,"origin":"","legend":"\u003cp\u003eMean influent and effluent concentrations of sCOD and NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e-N, and removal efficiencies (●), during the biological treatment in the MBBR fed with synthetic influent without and with Imidacloprid.\u003c/p\u003e","description":"","filename":"4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-2804636/v1/8f064e7aee2fce1d5e2a84d2.jpg"},{"id":36009838,"identity":"1aef350b-5928-4a5d-9ff5-03f724c86995","added_by":"auto","created_at":"2023-04-19 15:08:01","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":38965,"visible":true,"origin":"","legend":"\u003cp\u003eNormalized flux of the permeates analyzed after flux stabilization for UF membranes.\u003c/p\u003e","description":"","filename":"5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-2804636/v1/f3ed8085fcc654591a00e96d.jpg"},{"id":36009841,"identity":"675a96a5-9492-4430-a831-1708b11d655a","added_by":"auto","created_at":"2023-04-19 15:08:01","extension":"jpg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":51194,"visible":true,"origin":"","legend":"\u003cp\u003eColor and turbidity values (columns) and their removal percentage from different aqueous matrices: River (■), RM (●), and RML (▲) before (NT – no treatment) and after coagulation/flocculation/sedimentation (C/F/S), sand filter (SF), microfiltration cartridge (MF), and ultrafiltration (UF) pretreatments for RO feed water.\u003c/p\u003e","description":"","filename":"6.jpg","url":"https://assets-eu.researchsquare.com/files/rs-2804636/v1/8de1c554cc5ff4a4d8ded1e1.jpg"},{"id":36010688,"identity":"968cc2df-0fba-4e84-a8e8-c8bab2ea1220","added_by":"auto","created_at":"2023-04-19 15:16:01","extension":"jpg","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":71145,"visible":true,"origin":"","legend":"\u003cp\u003eFlowchart of wastewater treatment proposed in this study for the industrial complex. MBBR = Moving Bed Biofilm Reactor, EPTAC = Effluent Pretreated by PAC\u003cem\u003e.\u003c/em\u003e\u003c/p\u003e","description":"","filename":"7.jpg","url":"https://assets-eu.researchsquare.com/files/rs-2804636/v1/3efd877c50a3b7b43074fa14.jpg"},{"id":43301352,"identity":"bb62ffdb-a1f8-4ee0-9ae7-c17ec7dc6d69","added_by":"auto","created_at":"2023-09-18 15:10:10","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":838593,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-2804636/v1/a4cdec73-0143-40b9-b003-ed3b01c33650.pdf"},{"id":36011083,"identity":"296cf2b9-a8e5-4a0c-a296-17bd2dd7e3b2","added_by":"auto","created_at":"2023-04-19 15:24:01","extension":"pdf","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":306337,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementalMaterialC.pdf","url":"https://assets-eu.researchsquare.com/files/rs-2804636/v1/9bc2948f72a489639269d864.pdf"}],"financialInterests":"","formattedTitle":"Treatment and reuse of a pesticide-containing wastewater by a combination of physicochemical, biological and membrane processes","fulltext":[{"header":"1 Introduction","content":"\u003cp\u003ePesticides are chemical or biological substances used in agriculture to control insects, weeds, and other pests. However, the release of pesticide-contaminated water poses a serious threat to the environment and human health, even at trace concentrations (Li et al. \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Plakas and Karabelas 2012). Thereby, the proper treatment of pesticide industry wastewater is of paramount importance to avoid water pollution.\u003c/p\u003e \u003cp\u003eThe main source of wastewater from pesticide formulation industries is the periodic cleaning of equipment and production lines between batches of different pesticide products (Matheus et al. \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Thus, this wastewater usually contains different pesticide ingredients, which are commonly toxic and persistent (Bachmann Pinto, Miguel de Souza, and Dezotti 2018). Previous studies have shown that the chemical oxygen demand (COD) and biological oxygen demand (BOD) of pesticide production wastewaters are within the range of 150\u0026ndash;33750 mg/L and 30\u0026ndash;11590 mg/L, respectively (Lindsey Goodwin et al. \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Matheus et al. (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) reported values of total ammoniacal nitrogen, total and soluble COD of 150 mg/L, 16900 mg/L and 12300 mg/L, respectively, for a wastewater from a pesticide formulation industry resulting from various washing operations. The concentration of pesticide substances varies substantially, with some ingredients being detected at concentrations of up to 2500 mg/L (Lindsey Goodwin et al. \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eBiological treatment has been widely used to remove organic compounds in WWTPs due to its cost-benefit relationship and flexibility. Advances in biological technologies have led to the development of more robust systems to remove agro-industrial contaminants, such as the moving bed biofilm reactor (MBBR) (Bachmann Pinto, Miguel de Souza, and Dezotti 2018; Cao et al. \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Chen, Sun, and Chung 2007). MBBR is a flexible and compact system, in which biomass grows adhered to carriers, making it more specialized. In addition, like other biofilm processes, the MBBR is more resistant to toxic and organic shock loads. Unlike conventional activated sludge systems, the MBBR does not require sludge recycle, and the maintenance of solids inside the reactor makes the cell residence time longer than the hydraulic retention time (Bassin, Dezotti, and Rosado 2018).\u003c/p\u003e \u003cp\u003eIndustries have been investing in alternatives for water and wastewater reuse to comply with regulations and reduce legal sanctions, water consumption, and production costs. Industrial water reuse usually requires advanced treatments in the polishing stage to remove residual organic matter, nutrients and microorganisms (M. Racar et al. \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Membrane technologies have received considerable attention for water reuse applications. Reverse osmosis (RO) is a pressure-driven membrane technology widely applied for water and wastewater reuse. RO usually requires pretreatment processes that provide high-quality feed water to minimize fouling formation (Kucera \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Pearce \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). The use of low-pressure membrane technologies prior to RO, such as microfiltration (MF) and ultrafiltration (UF) membranes, is an attractive option in that sense (Kucera \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Pearce \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). The UF membrane rejects suspended and dissolved organic carbon, high molecular weight (MW) substances, and microorganisms. Therefore, UF pretreatment can reduce the RO membrane fouling and improve the RO system performance by increasing the permeate flux and membrane lifespan, while reducing the cleaning frequency and energy and chemicals consumption (Kucera \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Marko Racar et al. \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Vedavyasan \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2007\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eCoagulation and sand filter are cost-effective pretreatments for UF. When applied together, the sand filter reduces turbidity by removing residual particles (M. Racar et al. \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). However, in coagulation/flocculation treatments preceding depth filtration, the removal of polar micropollutants proved to be largely ineffective (Saraiva Soares et al. \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). Generally, only hydrophobic organic micropollutants are removed by adsorbing onto the flocs that are retained in the sand filter (Li et al. \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Matsushita et al. \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Thuy et al. \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2008\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eConversely, membrane separation technologies are widely used to remove organic micropollutants, such as pesticides. RO has demonstrated removal efficiency greater than 90% for a broad spectrum of trace organic compounds, including low MW (\u0026lt;\u0026thinsp;200 Da) ones. Therefore, RO is an alternative for the treatment of pesticide-contaminated waters, since most have MW\u0026thinsp;\u0026gt;\u0026thinsp;200 g/mol (Goh et al. \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Plakas and Karabelas 2012).\u003c/p\u003e \u003cp\u003eIn the literature, studies can be found versing about individual treatment technologies applied to pesticide-containing wastewaters, whether focused on individual persistent substances or complex industrial wastewaters. Other works assess combinations of processes; however, only one was found evaluating the reuse potential of a pesticide-containing wastewater (Bachmann Pinto, Miguel de Souza, and Dezotti 2018). In this sense, this work aims to further evaluate such potential by analyzing a full treatment train that could end up with the total reuse of the pesticide-rich wastewater from a pesticide formulation industry. That industry mixes its pesticide formulation wastewater (pretreated with adsorption onto powdered activated carbon (PAC)) with the sanitary and utilities residuary water, taking it to local activated sludge secondary treatment. In parallel, water is caught from a river and treated in a water treatment plant (WTP) by a combination of coagulation/flocculation, sedimentation, sand filtration, cartridge microfiltration, and reverse osmosis, providing the water at required quality for industrial uses.\u003c/p\u003e \u003cp\u003eThis study was conducted in two phases (I and II). In phase I, an MBBR was evaluated on a lab scale as an alternative to the existing activated sludge reactor in the industry. The MBBR performance was evaluated in terms of organic and nitrogenous matter removal. A complementary evaluation of biodegradation of a highly water-soluble insecticide active ingredient, Imidacloprid (IMI), was carried out in another MBBR. In phase II, the possibility of total reuse of the treated (non-settled) effluent from the MBBR was evaluated, through the impact generated by its addition to the river water in the performance of the physicochemical processes of the WTP, reproduced at bench scale. There was an additional opportunity to evaluate the insertion of a third stream into the water treatment train: the wastewater from a local lubricants industry, low in organics, nitrogen, and turbidity. Finally, the inclusion of ultrafiltration treatment to further protect the RO modules of the WTP, ensuring a high-quality water feed, was proposed and tested at different pressures and membranes.\u003c/p\u003e"},{"header":"2 Materials And Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 The Industrial Wastewater and Water Treatment Plants\u003c/h2\u003e \u003cp\u003eThe industrial wastewater from a local plant in Rio de Janeiro, Brazil, is highly complex due to the variety of manufactured pesticide products. The biological treatment is currently performed by an activated sludge system, preceded by an equalization tank. As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, the wastewater from the formulation plant initially passes through a PAC pre-treatment, and then proceeds to a filter press. The filtrate (named EPTAC) goes to the equalization tank, where it is mixed with the sewage and utilities wastewater (SE), in a 4:96 volumetric proportion. Then, this mixture is sent to the activated sludge reactor. Finally, the treated water is discharged into a local river after secondary settling.\u003c/p\u003e \u003cp\u003eRiver water is collected downstream from the location where the treated pesticide effluent is discharged and forwarded to the WTP to be used in the industrial processes. The WTP consists of the following processes: coagulation/flocculation, lamellar decanter, rapid down-flow sand filter, microfiltration cartridge (1\u0026micro;m), and reverse osmosis. Currently, the effluent from a lubricant industry recently installed in the complex, pretreated in a water/oil separator, is also sent to the WTP due to its extremely low concentration of organic matter.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Phase I: Biological Treatment\u003c/h2\u003e \u003cdiv id=\"Sec5\" class=\"Section3\"\u003e \u003ch2\u003e2.2.1 MBBR Fed by Industrial Wastewater\u003c/h2\u003e \u003cp\u003eTwo wastewater streams (EPTAC and SE, see Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) were periodically sampled from the pesticide industry. After collection, the samples were kept refrigerated at around 4\u0026deg;C. The average composition of each wastewater is displayed in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. Currently, these two streams are biologically treated in the industry in a proportion of 4% v/v EPTAC\u0026thinsp;+\u0026thinsp;96% v/v SE, named as Mix\u003csub\u003ew\u003c/sub\u003e. This wastewater mixture was regularly prepared to feed the bench-scale MBBR at the same proportion used in the industry.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAverage composition of pesticide industry wastewater samples.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eParameter\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUnit\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eEPTAC\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSE\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCOD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003emg/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4,778\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e160\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003esCOD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003emg/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4,456\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e54\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e-N\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003emg/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e44\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTSS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003emg/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e155\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVSS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003emg/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e96\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTurbidity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNTU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e30.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003epH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.52\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eBiological treatment of the industrial effluent mixture was conducted in a laboratory-scale aerobic cylindrical glass MBBR with 6.6 cm diameter and useful volume of 500 mL. The reactor was filled with AnoxKaldnes\u0026reg; K1 carriers (500 m\u0026sup2;/m\u0026sup3;) made of high-density polyethylene (HDPE) at a filling fraction of 50%, resulting in 250 m\u003csup\u003e2\u003c/sup\u003e/m\u003csup\u003e3\u003c/sup\u003e effective specific surface area. The reactor was fed in upflow mode using a peristaltic pump to control the flow rate and to provide a hydraulic retention time (HRT) of 6 h, based on the previous studies of Matheus et al. (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). A porous air diffuser stone was inserted at the bottom of the reactor to aerate the system and maintain good hydrodynamic conditions. The MBBR was inoculated with 25 mL of suspended biological sludge from a bench-scale activated sludge system, fed with 95% synthetic sanitary effluent and 5% leachate (COD\u0026thinsp;\u0026asymp;\u0026thinsp;2400 mg/L), and 8 K1 carriers with established biofilm from a bench-scale MBBR reactor fed with similar wastewater to this work.\u003c/p\u003e \u003cp\u003eInitially, over a period of 36 d (acclimation phase), the reactor was fed with synthetic wastewater composed of 0.375 g glucose/L, 0.27 g NaHCO\u003csub\u003e3\u003c/sub\u003e/L, 0.1146 g NH\u003csub\u003e4\u003c/sub\u003eCl/L, 0.4 g NaCl/L, 0.025 g K\u003csub\u003e2\u003c/sub\u003eHPO\u003csub\u003e4\u003c/sub\u003e/L, 0.020 g KH\u003csub\u003e2\u003c/sub\u003ePO\u003csub\u003e4\u003c/sub\u003e/L, and 0.5 mL of trace metal solution/L, to provide biofilm development. The trace metal solution is described elsewhere (VISHNIAC and SANTER 1957). Then, Mix\u003csub\u003ew\u003c/sub\u003e was added gradually and slowly for 94 d (adaptation phase). After that, the MBBR was fed with 100% Mix\u003csub\u003ew\u003c/sub\u003e for 153 d. Finally, the reactor was operated only with SE for 20 d in order to compare the biological activity of the biofilm under different conditions, i.e., in the presence and absence of EPTAC. During the MBBR operation, the pH was kept near neutrality (6.0-7.6) and the temperature ranged from 21 to 26\u0026deg;C.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section3\"\u003e \u003ch2\u003e2.2.2 Maximum and Real Specific Ammonium Removal Rates\u003c/h2\u003e \u003cp\u003eA batch test was performed to obtain the maximum ammonium removal rate of the microbiota under reactor operating conditions. Batch experiments were conducted during MBBR operation with influent Mix\u003csub\u003ew\u003c/sub\u003e and SE, after outlet ammonium concentration of less than 5 mg/L was established during continuous operation. First, the reactor was emptied and then filled with the untreated influent (with ammonium concentration of 47 mgNH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e-N/L and 67 mgNH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e-N/L for Mix\u003csub\u003ew\u003c/sub\u003e and SE, respectively) was added to the closed reactor. 7 mL samples were collected and filtered through a 0.45 \u0026micro;m nitrate cellulose membrane at time zero and then at intervals of 15 min in the first hour, 30 min in the second hour and every 1 h thereafter, in a total of 5 h. The ammonium concentration was determined over time. Specific maximum ammonium removal rate was determined by linear regression of ammonium concentration over time, taking into account the concentration of volatile attached solids (VAS), and was expressed as mgNH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e-N/(gVAS\u0026middot;h). The real specific ammonium removal rate of the system was calculated considering the continuous influent and effluent ammonium concentration (i.e., the removed ammonium under normal operating conditions), the VAS concentration and the HRT applied.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section3\"\u003e \u003ch2\u003e2.2.3 Evaluation of Biodegradation of a Pesticide Active Ingredient in MBBR\u003c/h2\u003e \u003cp\u003eThe active pesticide ingredient selected for biodegradation evaluation in an MBBR was Imidacloprid (purity 99.1%, CAS 138261-41-3), supplied by the industry that provided the wastewaters for this study. This compound was chosen due to its high water solubility (610 mg/L at 20\u0026deg;C), as this property is a cause of high bioaccumulation of compounds in water bodies (Khairkar et al. \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Imidacloprid (IMI) is a neonicotinoid insecticide with a molecular weight of 255.66 g/mol, molecular formula C\u003csub\u003e9\u003c/sub\u003eH\u003csub\u003e10\u003c/sub\u003eClN\u003csub\u003e5\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e, and log K\u003csub\u003eow\u003c/sub\u003e of 0.57 (at 21\u0026deg;C).\u003c/p\u003e \u003cp\u003eIMI biodegradation was investigated in a bench-scale MBBR with a working volume of 315 mL and HRT of 6 h, filled with AnoxKaldnes\u0026reg; K1 carriers at 50% media filling ratio, operated at 23\u0026thinsp;\u0026plusmn;\u0026thinsp;2\u0026deg;C, pH of 7.41\u0026thinsp;\u0026plusmn;\u0026thinsp;0.34, and dissolved oxygen concentration of 7.1\u0026thinsp;\u0026plusmn;\u0026thinsp;0.4 mg/L. The reactor was initially fed with synthetic sanitary wastewater composed of 0.19 g glucose/L (200 mg sCOD/L), 0.34 g NaHCO\u003csub\u003e3\u003c/sub\u003e/L, 0.115 g NH\u003csub\u003e4\u003c/sub\u003eCl/L (30 mg NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e-N/L), 0.02 g KH\u003csub\u003e2\u003c/sub\u003ePO\u003csub\u003e4\u003c/sub\u003e/L, 0.025 g K\u003csub\u003e2\u003c/sub\u003eHPO\u003csub\u003e4\u003c/sub\u003e/L, and 0.5 mL of trace metal solution/L during 133 d for biofilm formation and acclimation. After MBBR performance stabilization, 5 mg/L of IMI was added to the feed solution, representing around 11.26 mg/L of theoretical COD. The feed was kept in a refrigerator at around 4\u0026ordm;C to minimize biodegradation before the MBBR.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Phase II: Evaluation of the Possibility of Total Effluent Reuse\u003c/h2\u003e \u003cp\u003eIn order to evaluate the reuse feasibility and the potential impact caused by the additional streams (MBBR effluent and lubricant industry effluent), the following physicochemical processes were analyzed at lab-scale (simulating the industrial WTP): coagulation-flocculation, sedimentation, rapid down-flow sand filter, and microfiltration cartridge. An ultrafiltration step was also analyzed in the pretreatment sequence. Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e describes the water matrices used to feed the reverse osmosis pretreatment system. The mixture proportions simulate the average discharge of the secondary effluent, the lubricants industry wastewater, and the water withdrawal from a local river. Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e shows the characterization of the river water and the lubricant industry wastewater before the WTP pretreatment steps. The lubricant industry effluent comes from the production process and rainwater collected on the industrial courtyards. This effluent is pretreated in a water/oil separator and then sent to the WTP, due to the low concentrations of organic matter, ammonium, TOC, and turbidity.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMixture proportions of river water and effluents treated in MBBR and a lubricant industry, used in reverse osmosis pretreatments.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAqueous Matrix\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSurface Water\u003c/p\u003e \u003cp\u003e(% v/v)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMix\u003csub\u003etw\u003c/sub\u003e\u003c/p\u003e \u003cp\u003e(%\u0026nbsp;v/v)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLI Effluent\u003c/p\u003e \u003cp\u003e(% v/v)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRiver\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRML\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003eMix\u003csub\u003etw\u003c/sub\u003e= treated effluent in the MBBR, without decantation; LI\u0026thinsp;=\u0026thinsp;Lubricant industry; River\u0026thinsp;=\u0026thinsp;surface water; RM\u0026thinsp;=\u0026thinsp;River\u0026thinsp;+\u0026thinsp;Mix\u003csub\u003etw\u003c/sub\u003e; RML\u0026thinsp;=\u0026thinsp;River\u0026thinsp;+\u0026thinsp;Mix\u003csub\u003etw\u003c/sub\u003e + LI\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCharacterizations of the river water and the effluent from the lubricant industry.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eParameter\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUnit\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRiver\u003c/p\u003e \u003cp\u003eLot 1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRiver\u003c/p\u003e \u003cp\u003eLot 2\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRiver\u003c/p\u003e \u003cp\u003eLot 3\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eLI effluent\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCOD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003emg/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e74\u0026thinsp;\u0026plusmn;\u0026thinsp;1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e47\u0026thinsp;\u0026plusmn;\u0026thinsp;1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e53\u0026thinsp;\u0026plusmn;\u0026thinsp;8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6\u0026thinsp;\u0026plusmn;\u0026thinsp;1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003esCOD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003emg/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e72\u0026thinsp;\u0026plusmn;\u0026thinsp;2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e32\u0026thinsp;\u0026plusmn;\u0026thinsp;2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e28\u0026thinsp;\u0026plusmn;\u0026thinsp;2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7\u0026thinsp;\u0026plusmn;\u0026thinsp;2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTOC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003emg/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e-N\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003emg/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTSS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003emg/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVSS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003emg/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTurbidity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNTU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e11.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eColor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003euH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e158\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003epH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCondutivity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026micro;S/cm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e622.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e653.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e616.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e143.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cdiv id=\"Sec9\" class=\"Section3\"\u003e \u003ch2\u003e2.3.1 Coagulation-Flocculation and Sedimentation\u003c/h2\u003e \u003cp\u003eThe coagulation-flocculation process was the first pretreatment step performed in the aqueous matrices. Jar test (Digimed MF-01 flocculation module) was used to determine the optimal dosage of chemical agents for the three aqueous matrices. The conditions applied in this test were the same as in the previous study conducted by Bachmann Pinto et al. (2018). The coagulation-flocculation agents used in this study were the same ones used in the pesticide industry: Panfloc AP\u003csup\u003e\u0026reg;\u003c/sup\u003e Polyaluminum chloride (PACl) (16.0\u0026ndash;18.5% w/w Al\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e3,\u003c/sub\u003e Pan-Americana S.A.) was used as a coagulant; and Flonex\u0026reg; 905 SH, SNF Floerger, was used as anionic flocculant. After the flocculation process, the mixture was left for settling for about 30 minutes, and the supernatant was taken for water quality analysis and proceeding with the downstream processes.\u003c/p\u003e \u003cp\u003eIn a constant pressure in-line coagulation/UF process, alum and PACl can increase the natural organic matter removal and considerably reduce membrane fouling (Kabsch-Korbutowicz \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). Furthermore, aluminum residuals from coagulation with alum cause colloidal fouling in RO membranes. Thus, PACl becomes an alternative as it minimizes this fouling and allows the reduction of aluminum-antiscalant interactions (Gabelich et al. \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). In addition, using polyelectrolytes at low concentrations, from 0.1 to 1 mg/L, preceding the granular media filtration, can help produce better quality water (Amirtharajah \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e1988\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section3\"\u003e \u003ch2\u003e2.3.2 Rapid Down-Flow Sand Filter\u003c/h2\u003e \u003cp\u003eThe clarified effluents obtained in the coagulation-flocculation and sedimentation processes were sent to a rapid down-flow sand filter with a constant filtration rate of 120 m\u003csup\u003e3\u003c/sup\u003e/(m\u003csup\u003e2\u003c/sup\u003e\u0026middot;d). The filtration was performed in a cylindrical glass column with 3.7 cm of internal diameter filled with a 40 cm quartz sand bed. The sand is suitable for filtration with a particular size 12/20, uniformity coefficient of 1.42, and effective size of 1.0 mm. The storage of the filtered matrices started after 3 h of continuous filtration, as it is assumed filter maturation and, consequently, a satisfactory and stable quality in terms of turbidity. River matrix filtration was completed after 8 h, while RM and RML matrices were completed after 9 h.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section3\"\u003e \u003ch2\u003e2.3.3 Microfiltration Cartridge Filter\u003c/h2\u003e \u003cp\u003eAfter the rapid sand filter, the aqueous matrices followed for filtration in Eaton\u0026rsquo;s LOFTREX filter cartridge manufactured from polypropylene microfibers, with nominal particle retention of 1 \u0026micro;m and 80% retention efficiency.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section3\"\u003e \u003ch2\u003e2.3.4 Ultrafiltration Experiments\u003c/h2\u003e \u003cp\u003eUltrafiltration (UF) tests employed commercial flat sheet membranes NADIR\u0026reg; UP010 P and UH050 P, with respective molecular weight cut-offs of 10 and 50 kDa, indicated for industrial water purification. Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e shows further characteristics of the UF membranes.\u003c/p\u003e \u003cp\u003eUltrafiltration experiments were performed in a lab-scale module operating in crossflow mode, with an effective membrane area of 77.7 cm\u003csup\u003e2\u003c/sup\u003e. Fig. \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e shows the UF experimental setup. During the experiment, the concentrate, permeate and excess feed (by-pass) were recirculated into the feed tank and, when the flow stabilized, the permeate samples were collected. The permeate flux was calculated as usual (Eq. (S1), supplemental material).\u003c/p\u003e \u003cp\u003eInitially, the virgin UF membranes were compacted with distilled water at a constant transmembrane pressure (TMP) of 2 bar for 2 hours (stabilization time) to determine the water permeability of the membranes. After compaction, the water matrices (River, RM and RML) were filtrated through the UF membrane. All filtration tests were performed at 22\u0026thinsp;\u0026plusmn;\u0026thinsp;2\u0026deg;C. The UP010 P and UH050 P transmembrane pressures ranged between 2\u0026ndash;3 bar and 1\u0026ndash;3 bar, respectively. During the experiments, the pressure was kept constant and the permeate flux was measured at time zero (beginning of permeation) and then every 5 min until its stabilization. Then, the filtrate was collected and analyzed in terms of total dissolved solids (TDS), total organic carbon (TOC), color, and turbidity.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e2.4 Analytical Procedures\u003c/h2\u003e \u003cp\u003eChemical oxygen demand (COD) (5220 D), ammonium (Nesslerization), total suspended solids (TSS) (2540 D), volatile suspended solids (VSS) (2540 E), and TDS (2540 C) were determined following standard methods (APHA, AWWA, and WEF \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; ASTM \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). The concentration of total attached solids (TAS) in MBBR carriers was determined after complete removal of the biofilm from 3 supports with an interdental toothbrush and distilled water, following the total solids method (2540 B) and relating the mass obtained with the number of supports in the MBBR (Matheus et al. \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eNitrate and nitrite were quantified using Hach NitraVer 5 and NitraVer 2 reagent kits, respectively. pH was measured according to the electrometric method 4500-H\u003csup\u003e+\u003c/sup\u003eB (APHA, AWWA, and WEF \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2017\u003c/span\u003e), with a Hanna HI2221 pH meter. Soluble COD (sCOD), ammonium, nitrite, and nitrate were determined after filtering the samples in 0.45 \u0026micro;m cellulose nitrate membranes. Turbidity was measured using PoliControl\u0026rsquo;s AP-2000 turbidimeter, and color was determined using a Hach DR 2800 spectrophotometer at 455 nm.\u003c/p\u003e \u003cp\u003eIMI quantification was performed using the Hybrid Quadrupole Thermo QExactive Orbitrap mass spectrometer (Thermo Scientific), with an electrospray ionization source (ESI). It has high resolution and accuracy in masses. The ionization mode used was positive (ESI(+)-Orbitrap-HRMS), mass resolution of 140,000 (FWHM) at m/z 200, spray voltage of 3.6 kV, S-Lens voltage of 60, capillary temperature of 320\u0026deg;C, sheath gas in the ionization source 10u, infusion flow of 10 \u0026micro;L/min, and 50 scans acquired.\u003c/p\u003e \u003cdiv id=\"Sec14\" class=\"Section3\"\u003e \u003ch2\u003e2.4.1 Silt Density Index (SDI\u003csub\u003e15\u003c/sub\u003e)\u003c/h2\u003e \u003cp\u003eSDI after 15 min (SDI\u003csub\u003e15\u003c/sub\u003e) was determined using the microfiltration cartridge outlet matrices, since in the current industrial process setup, cartridge filters precede the reverse osmosis modules. The tests followed the ASTM method D4189-07 (ASTM 2014), according to which dead-end filtration of the samples at 22\u0026deg;C was performed in cellulose nitrate microfiltration membrane with 0.45 \u0026micro;m pore size and 47 mm diameter at a constant pressure of 30 psi.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"3 Results And Discussion","content":"\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003e3.1 Phase I: MBBR Performance\u003c/h2\u003e \u003cp\u003eDuring the 153 d of operation with Mix\u003csub\u003ew\u003c/sub\u003e and 20 d with SE, the MBBR showed total COD removal ranging from 65 to 95% and 76 to 92%, respectively, with an average of around 86% COD removal in both cases. As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, the COD in the influent streams Mix\u003csub\u003ew\u003c/sub\u003e and SE ranged between 72\u0026ndash;557 mg/L and 81\u0026ndash;340 mg/L, respectively, while effluent COD presented values below 70 mg/L and 30 mg/L, respectively, with averages of 26 mg/L and 21 mg/L. These values are below the local legislation requirements for chemical industries to discharge into water bodies (COD\u0026thinsp;\u0026lt;\u0026thinsp;250 mg/L) (INEA 2007). These COD removal values are similar to the results obtained by Cao et al. (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2016\u003c/span\u003e) in a two-stage anoxic-aerobic MBBR system (82\u0026ndash;91%), and Bachmann Pinto et al. (2018) in an aerobic MBBR (64\u0026ndash;89%).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFigure\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e shows ammonium concentration fluctuations in the influent Mix\u003csub\u003ew\u003c/sub\u003e (3\u0026ndash;64 mgNH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e-N/L) and SE (59\u0026ndash;68 mgNH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e-N/L). During the reactor operation with Mix\u003csub\u003ew\u003c/sub\u003e and SE as feed, average ammonium removal efficiencies were 88% and 86%, while average effluent ammonium concentrations were 5 mgNH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e-N/L (ranging between 0\u0026ndash;22 mgNH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e-N/L) and 9 mgNH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e-N/L (ranging between 5\u0026ndash;12 mgNH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e-N/L), respectively. After the 75th day of operation, there was an abrupt increase in the influent ammonium concentration and, consequently, a decrease in removal efficiency. Thus, an adaptation period to the higher nitrogen load was necessary. As commonly known, autotrophic nitrifying bacteria exhibit low growth rates and are quite sensitive to sudden changes in influent conditions (Metcalf \u0026amp; Eddy et al. \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). 48 d later (123rd day), ammonium levels dropped to below 1 mg/L, but they increased in the long-term operation, fluctuating between 3 and 10 mg/L.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe biofilm formed in the MBBR carriers was thin and evenly distributed over the media (Fig. S2), regardless of the variations of influent characteristics. However, a lower thickness was observed when the MBBR was fed with SE, likely because the reduction of organic load during that period limited the growth of heterotrophic organisms, causing their detachment and decreasing the amount of adhered biomass. Under these conditions, the biofilm becomes thinner and enriched in nitrifying bacteria (Bassin et al. \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). In fact, the specific maximum ammonium removal rate increased from 4.7 to 13.9 mgNH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e-N/(gVAS.h) when the reactor feed shifted from Mix\u003csub\u003ew\u003c/sub\u003e (47 mg NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e-N/L; 78 mg sCOD/L) to SE (67 mgNH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e-N/L; 47 mg sCOD/L). In addition, the results show that after the day 119, the reactor operated at a real specific ammonium removal rate equal to the maximum one, i.e., at the reactor maximum capacity. Consequently, in this condition, residual ammonium was always found in the effluent. Therefore, when a higher ammonium load was fed to the system, a lower performance was attained, and the treated effluent did not comply with local legislation (\u0026lt;\u0026thinsp;5 mgNH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e-N/L) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e) (INEA 1986).\u003c/p\u003e \u003cp\u003eRegarding the nitrification products, nitrate prevailed in the effluent throughout the MBBR operation period (on average 90.5% of inorganic N for Mix\u003csub\u003ewt\u003c/sub\u003e), evidencing the occurrence of complete nitrification, i.e., the conversion of ammonium to nitrate by the sequential action of ammonium-oxidizing bacteria (AOB) and nitrite-oxidizing bacteria (BON) (Metcalf \u0026amp; Eddy et al. \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2014\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe MBBR operating conditions are important for the development and maintenance of the microbial consortium within the biofilm. According to Metcalf \u0026amp; Eddy et al. (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2014\u003c/span\u003e), optimal nitrification is favored at pH between 7.5\u0026ndash;8.0. Within the MBBR, the pH ranged from 6.0 to 7.6 (6.9 on average), with changes linked to variations in the influent ammonium concentration, with the pH value decreasing with the higher amount of nitrified ammonium, associated with the release of H\u003csup\u003e+\u003c/sup\u003e ions. At the lowest values of pH, a decrease in ammonium removal was observed (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e) since pH values below 6.8 significantly decrease the nitrification rate (Metcalf \u0026amp; Eddy et al. \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Thus, pH control was performed to keep it at acceptable values. Furthermore, the pH values in the effluent met the requirements of the local legislation (5.0\u0026ndash;9.0) (INEA 1986).\u003c/p\u003e \u003cp\u003eHydrolysis and further degradation of particulate organic compounds by the biofilm allowed wastewater clarification and consequently reduced turbidity. In fact, the treated effluent presented low content of total suspended solids (8\u0026ndash;78 mgTSS/L Mix\u003csub\u003etw\u003c/sub\u003e; 41\u0026ndash;48 mgTSS/L SE) and turbidity (0\u0026ndash;12 NTU Mix\u003csub\u003etw\u003c/sub\u003e; 3\u0026ndash;21 NTU SE). In addition, the suspended solids in the effluent were mostly volatile (VSS/TSS\u0026thinsp;=\u0026thinsp;0.76 (Mix\u003csub\u003etw\u003c/sub\u003e); VSS/TSS\u0026thinsp;=\u0026thinsp;0.80 (SE)), which can be attributed to suspended organic matter (Fig. S3). In contrast, the adhered biomass concentration presented higher values as expected, given the MBBR characteristics. The average TAS measured when the MBBR was fed with Mix\u003csub\u003ew\u003c/sub\u003e and SE were 2.1 gTAS/L and 1.0 gTAS/L, respectively. The typical attached biomass concentration range reported for MBBR systems is 2.0\u0026ndash;8.0 kgTAS/m\u003csup\u003e3\u003c/sup\u003e, similar to the biomass concentration found in activated sludge systems. However, in the MBBR process, the microorganisms are more specific and active, improving treatment efficiency (Bassin, Dezotti, and Rosado 2018).\u003c/p\u003e \u003cp\u003eThe results showed that the replacement of the activated sludge system by an MBBR is an interesting alternative, given its inherent characteristics and the quality of the treated effluent, which presented quality superior than the water captured from the local river for industrial use (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e and Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). In this context, in order to optimize the WTP, the possibility of reusing the biologically treated wastewater from the MBBR together with the water from the lubricants industry, and the impact on the reverse osmosis pretreatment process were evaluated. In addition, a complementary study was conducted with the insecticide active ingredient IMI, as a model pesticide, in order to determine whether its biodegradation occurs in an MBBR and whether the effluent carries active ingredients to the receiving water body.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCharacteristics of the influent and treated effluent of the MBBR.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eParameter\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUnit\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eInfluent Mix\u003csub\u003ew\u003c/sub\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eEffluent Mix\u003csub\u003etw\u003c/sub\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eInfluent\u003c/p\u003e \u003cp\u003eSE\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eEffluent\u003c/p\u003e \u003cp\u003eSE\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCOD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003emg/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e206\u0026thinsp;\u0026plusmn;\u0026thinsp;103\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e26\u0026thinsp;\u0026plusmn;\u0026thinsp;13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e183\u0026thinsp;\u0026plusmn;\u0026thinsp;113\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e21\u0026thinsp;\u0026plusmn;\u0026thinsp;5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSCOD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003emg/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e102\u0026thinsp;\u0026plusmn;\u0026thinsp;29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e17\u0026thinsp;\u0026plusmn;\u0026thinsp;9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e39\u0026thinsp;\u0026plusmn;\u0026thinsp;2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e24\u0026thinsp;\u0026plusmn;\u0026thinsp;6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e-N\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003emg/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e33\u0026thinsp;\u0026plusmn;\u0026thinsp;20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e5\u0026thinsp;\u0026plusmn;\u0026thinsp;6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e64\u0026thinsp;\u0026plusmn;\u0026thinsp;4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e9\u0026thinsp;\u0026plusmn;\u0026thinsp;2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e-N\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003emg/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e24\u0026thinsp;\u0026plusmn;\u0026thinsp;16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e36\u0026thinsp;\u0026plusmn;\u0026thinsp;5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNO\u003csub\u003e2\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e-N\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003emg/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e0.4\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e0.5\u0026thinsp;\u0026plusmn;\u0026thinsp;0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTSS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003emg/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e123\u0026thinsp;\u0026plusmn;\u0026thinsp;92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e41\u0026thinsp;\u0026plusmn;\u0026thinsp;20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e307\u0026thinsp;\u0026plusmn;\u0026thinsp;143\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e45\u0026thinsp;\u0026plusmn;\u0026thinsp;5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVSS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003emg/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e65\u0026thinsp;\u0026plusmn;\u0026thinsp;28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e30\u0026thinsp;\u0026plusmn;\u0026thinsp;14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e124\u0026thinsp;\u0026plusmn;\u0026thinsp;90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e36\u0026thinsp;\u0026plusmn;\u0026thinsp;6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTurbidity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNTU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e48\u0026thinsp;\u0026plusmn;\u0026thinsp;61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e3\u0026thinsp;\u0026plusmn;\u0026thinsp;3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e160\u0026thinsp;\u0026plusmn;\u0026thinsp;103\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e8\u0026thinsp;\u0026plusmn;\u0026thinsp;6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003epH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e6.8\u0026thinsp;\u0026plusmn;\u0026thinsp;0.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7.9\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e7.1\u0026thinsp;\u0026plusmn;\u0026thinsp;0.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eN/A: not available.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003e3.2 Evaluation of Imidacloprid Biodegradation\u003c/h2\u003e \u003cp\u003eIn parallel, another MBBR was used to evaluate the removal of a chosen active ingredient, as explained in section 2.2.3. After exposing the MBBR fed only with synthetic sewage to 5 mg/L of the IMI insecticide, the COD removal performance dropped from an average of 83.7\u0026thinsp;\u0026plusmn;\u0026thinsp;8.2% (n\u0026thinsp;=\u0026thinsp;17, 90 days) to 66.6\u0026thinsp;\u0026plusmn;\u0026thinsp;6.2% (n\u0026thinsp;=\u0026thinsp;5) during the first 10 days with IMI, representing a significant statistical difference (ANOVA p-value\u0026thinsp;=\u0026thinsp;0.00037, F\u0026thinsp;=\u0026thinsp;0.9996). Meanwhile, the performance of ammoniacal nitrogen removal never got affected, even when the biofilm was first exposed to IMI. One possible explanation is that nitrifying autotrophic organisms are mostly located in the inner part of the biofilm, so they are more protected from IMI exposure. On the other hand, the activity of heterotrophic bacteria, dominant on the outer surface, was affected. The ammoniacal nitrogen removal actually increased from 93.8\u0026thinsp;\u0026plusmn;\u0026thinsp;3.8% (n\u0026thinsp;=\u0026thinsp;16, 63 days) to 99.5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.8% (n\u0026thinsp;=\u0026thinsp;59, 383 days) when comparing the period without IMI and the whole operation with IMI. This increase was probably due to the higher adaptation period of the nitrifying microorganisms. The effluent mean concentrations of ammoniacal nitrogen were 1.48\u0026thinsp;\u0026plusmn;\u0026thinsp;0.92 mg/L (without IMI) and 0.13\u0026thinsp;\u0026plusmn;\u0026thinsp;0.22 mg/L (with IMI).\u003c/p\u003e \u003cp\u003eFigure\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e shows the average inlet and outlet COD and NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e-N concentrations, as well as the correspondent removal percentages, after a stabilized performance with IMI (i.e., the whole period for NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e-N and after the 10 first days for COD). It is noticeable that, after acclimation with IMI, the MBBR maintained a similar average (ANOVA p-value\u0026thinsp;=\u0026thinsp;0.0228, F\u0026thinsp;=\u0026thinsp;0.9772) organic matter removal (87.4\u0026thinsp;\u0026plusmn;\u0026thinsp;5.3%, n\u0026thinsp;=\u0026thinsp;43, 369 days) when compared to the operation without IMI. The respective average effluent COD was 29.5\u0026thinsp;\u0026plusmn;\u0026thinsp;14.4 mg/L (without IMI) and 25.2\u0026thinsp;\u0026plusmn;\u0026thinsp;11.5 mg/L (with IMI). Overall, the MBBR demonstrated the robustness to adapt to the pesticide tested and still provide good COD and ammonium removals, as one should expect when assessing the results with the industrial wastewater in the previous section (3.1).\u003c/p\u003e \u003cp\u003eHowever, when analyzing the IMI concentrations, no removal was observed for this compound, as the mean effluent concentration was 5.8\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2 mgIMI/L (n\u0026thinsp;=\u0026thinsp;5, 399 days), compatible with the influent concentration (5 mgIMI/L).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eTherefore, the non-removal of the active ingredient indicates that neonicotinoid pesticides may appear in effluents of aerobic MBBRs and evidences the need for efficient post-treatments, which guarantee that the treated effluent is not a source of contamination in the environment. Thus, the effluent treated in the MBBR should not be disposed of directly in the river, and should be directed to the industry WTP.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003e3.3 Phase II: Reuse Evaluation\u003c/h2\u003e \u003cp\u003eOnce the effluent treated in the MBBR reached the discharge limits imposed by local legislation, the possibility of total reuse of the wastewater from the pesticide industry and lubricant industry was evaluated. Conventional RO pretreatments applied in WTP of the industrial complex were tested at lab-scale in the following order: coagulation/flocculation, sedimentation, sand filtration, and cartridge microfiltration. The treatment sequence was performed using the water withdrawn from the local river (River) - after screening, equalization and sieving in fine mesh - and the RM and RML mixtures, in the proportions shown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, to determine the impact of the addition of these streams on the RO pretreatment processes. The aqueous matrices characterization is summarized in Table S2.\u003c/p\u003e \u003cdiv id=\"Sec19\" class=\"Section3\"\u003e \u003ch2\u003e3.3.1 Coagulation-Flocculation\u003c/h2\u003e \u003cp\u003eIn the first pretreatment stage, the optimal coagulant and flocculant concentrations were determined considering color and turbidity values, as they presented significant variations. The optimal coagulant and flocculant concentrations were 40 mg/L and 0.2 mg/L for river water, and 20 mg/L and 0.2 mg/L for both RM and RML aqueous matrices. The turbidity removal after the reproduction of the process corresponded to 54% (from 15.4 to 7.06 NTU), 77% (from 10.7 to 2.43 NTU), and 82% (from 12.5 to 2.23 NTU), while color removal was 70% (from 158 to 47 Pt-Co units), 67% (from 79 to 26 Pt-Co units), and 63% (from 73 to 27 Pt-Co units) for River, RM and RML samples, respectively.\u003c/p\u003e \u003cp\u003eRegarding the removal of pesticides by coagulation, adsorption is the main mechanism responsible for removal. The greater the hydrophobicity of these compounds, the better the adsorption to the floc or sludge and removal efficiency (Li et al. \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Thuy et al. \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). The study conducted by Thuy et al. (\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2008\u003c/span\u003e) indicated that the removal of pesticides (aldrin, dieldrin, atrazine, and bentazone) occurs more by adsorption onto organic matter than by the destabilization of colloids. Saraiva-Soares et al. (2013) have investigated the removal of pesticides/metabolites using conventional drinking water treatment processes. The results showed that the removal was low for all contaminants tested (ethylenethiourea median\u0026thinsp;\u0026le;\u0026thinsp;11%, 1,2,4-triazole median\u0026thinsp;\u0026le;\u0026thinsp;18% and endosulfan median\u0026thinsp;\u0026le;\u0026thinsp;54%, all in decanted water), and that the removal decreased when the initial concentration increased. Endosulfan was better removed than the others due to its low water solubility and high log K\u003csub\u003eow\u003c/sub\u003e (4.75) and molar mass (406.93 g/mol). Matsushita et al. (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) observed that the concentration of most of studied compounds (28 pesticides transformation products and 15 parent pesticides) was not modified after coagulation-sedimentation, with PACl as coagulant. Only etofenprox, the most hydrophobic compound (log K\u003csub\u003eow\u003c/sub\u003e = 6.3) tested, was removed.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section3\"\u003e \u003ch2\u003e3.3.2 Sand Filter\u003c/h2\u003e \u003cp\u003eThe supernatant aqueous matrices treated by the coagulation/flocculation process were subsequently fed to the rapid sand filter, in which the turbidity removal was 42%, 54% and 57% for the River (4.1 NTU), RM (1.1 NTU) and RML (0.95 NTU) matrices, respectively. The apparent color values were 36 Pt-Co (River), 22 Pt-Co (RM) and 22 Pt-Co units (RML). In addition, it was noted that the characteristics of the mixtures were better than that of the raw river water, thus influencing the subsequent treatment steps. In fact, the main purpose of filtration is to remove the suspended particles from the influent, providing a high clarity of the filtrate (turbidity reduction) (Amirtharajah \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e1988\u003c/span\u003e; Howe et al. \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2012\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eCoagulation-flocculation followed by a sand filter has been shown to be ineffective in removing polar micropollutants (Saraiva Soares et al. \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). Research carried out by Li et al. (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) analyzed the effect of recycling spent filter backwash water on the removal of 14 organic pesticides and simulated the conventional drinking water treatment process (coagulation, flocculation, sedimentation, and rapid sand filter) with a raw water from Heihe reservoir (China), enriched with pesticides. The results showed that the pesticide removal by these processes was very low. Removal of hydrophobic pesticides (log K\u003csub\u003eow\u003c/sub\u003e \u0026lt;3.8, diazinon, tolclofos-methyl, profenofos and chlorpyrifos) ranged from 29.1\u0026ndash;57.5%; of hydrophilic ones (log K\u003csub\u003eow\u003c/sub\u003e \u0026lt; 2.6, cyanazine, pirimicarb, atrazine and carbaryl) was lower than 3%; and of the others much less hydrophobic was lower 21%. Furthermore, micropollutants with low hydrophobicity (log K\u003csub\u003eow\u003c/sub\u003e \u0026lt; 5.0) had a limited removal.\u003c/p\u003e \u003cp\u003eThus, more effective pesticide removal treatments should be incorporated into treatment plants in order to mitigate possible environmental risks. For this reason, the RO separation process is essential in the WTP.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section3\"\u003e \u003ch2\u003e3.3.3 Microfiltration Cartridge Filter\u003c/h2\u003e \u003cp\u003eThe main impact of the microfiltration cartridge was the reduction in color and turbidity, which were, respectively, 2.6 NTU and 28 Pt-Co units for River, 0.8 NTU and 20 Pt-Co units for RM, and 0.7 NTU and 18 Pt-Co units for RML. After such effluent qualities were reached, the aqueous matrices from the cartridge filter were submitted to SDI\u003csub\u003e15\u003c/sub\u003e tests, as this parameter is used to assess the fouling potential of reverse osmosis membranes and the efficiency of the clarification process (ASTM 2014). As the SDI\u003csub\u003e15\u003c/sub\u003e test is normally applied to waters with turbidity lower than 1 NTU, the test was performed using only RM and RML matrices (ASTM 2014; Baker \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2004\u003c/span\u003e). However, RM and RML presented an SDI\u003csub\u003e15\u003c/sub\u003e of 5.5 and 5.7, respectively, which is considered impracticable for feeding RO modules, indicating the need for pretreatment (Mosset et al. \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). In order to minimize RO fouling, an SDI\u003csub\u003e15\u003c/sub\u003e\u0026thinsp;\u0026lt;\u0026thinsp;3 is desired. For effluents with higher SDI values, it is recommended to use additional pretreatment processes (Baker \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2004\u003c/span\u003e; Mosset et al. \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). The yellow/brown color films formed on the membrane surface during the SDI\u003csub\u003e15\u003c/sub\u003e tests indicate that the fouling was probably caused by organic compounds not removed in previous processes (Abuabdou et al. \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec22\" class=\"Section3\"\u003e \u003ch2\u003e3.3.4 Ultrafiltration\u003c/h2\u003e \u003cp\u003eUltrafiltration (UF) has been widely used for the removal of microorganisms and suspended solids, allowing the effluent to reach SDI and turbidity values below 2 and 0.02 NTU, respectively (Baker \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2004\u003c/span\u003e). UF can be used to eliminate compounds with molecular weight (MW) that tend to clog the RO membrane (Wolf, Siverns, and Monti \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2005\u003c/span\u003e). Besides providing excellent RO feed water quality at low pressure and ensuring a stable RO system performance, with a possible 20% increase of the permeate flux (Vedavyasan \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2007\u003c/span\u003e), the UF pretreatment also reduces the frequency of RO membrane chemical cleaning. Given these characteristics and the challenge of obtaining an SDI\u003csub\u003e15\u003c/sub\u003e\u0026thinsp;\u0026lt;\u0026thinsp;3 using conventional pretreatments, the use of UF as a pretreatment of RO systems has become an increasingly relevant option (Miyoshi et al. \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Vedavyasan \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2007\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eTherefore, it was proposed to insert the UF process before RO in the WTP of the industrial complex. The water permeability of the UP010 P and UH050 P fresh membranes used in this work was measured by filtrating pure water at different pressures, and the results obtained were 34.9 L/(m\u003csup\u003e2\u003c/sup\u003e\u0026middot;h\u0026middot;bar) and 227.9 L/(m\u003csup\u003e2\u003c/sup\u003e\u0026middot;h\u0026middot;bar), respectively. These values are consistent with those provided by the manufacturer for the UH050 P membrane, and slightly lower for the UP010 P one (Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e), probably due to impurities in the filtration module. It was found that the flux of pure water increased linearly as a function of the pressure applied to the UF system for both UF membranes. In addition, the selected membranes can be classified as hydrophilic, since the angle formed between the membrane-liquid boundary and liquid-gas tangent, i.e., the contact angle (CA), is less than 90\u0026deg;, as shown in Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e. However, UP010 P is less hydrophilic because the CA of the UH050 P membrane is smaller (Miyoshi et al. \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Otitoju, Ahmad, and Ooi 2018). Hydrophilic membranes are advantageous because, according to Wardani et al. (\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), these are less susceptible to organic fouling, which is responsible for decreasing productivity and increasing energy costs.\u003c/p\u003e \u003cp\u003eFigure S4 and Fig. S5 illustrate the decrease in permeate flux of both UF membranes over time under different pressures for the aqueous matrices River, RM, and RML from the cartridge filter. The UH050 P membrane presented higher permeate flux at the evaluated pressures, which can be explained by its greater hydrophilic nature, permeability, and pore size compared to the UP010 P membrane (Luo \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). As the UH050 P membrane has a larger pore size, the water permeation resistance is lower.\u003c/p\u003e \u003cp\u003eThe experiment with the UH050 P membrane initially showed a rapid and exponential water flux decline, while the UP010 P membrane flux decline occurred more smoothly. In both experiments, for all tested pressures, a constant water flux was reached after 100 min (for UP010 P) and 120 min (for UH050 P). A possible justification is that when the membrane has larger pores, the particles that cause fouling enter their pores more easily, causing their blockage (Wang et al. \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Besides, the higher permeability of the UH050 P membrane initially leads to an increase in particle concentration near its surface, concentration polarization, generating an increase in the thickness of the cake and, consequently, the flux decline (Baker \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2004\u003c/span\u003e). Concentration polarization is unavoidable for any filtration, even for crossflow (tangential flow), in which shear force prevents the formation of a thick cake layer (Song and Elimelech 1995). Thus, there is a decrease in permeate flux at the beginning of permeation. According to Juang et al. (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2007\u003c/span\u003e), the initial rapid drop in the flux is probably due to partial pore blockage. Then, an increase in the resistance generated by the formation of a cake layer on the surface of the membrane causes the flux to gradually decrease until it approaches a steady-state condition. Moreover, it was observed that in the permeations with the aqueous matrices, the increase in transmembrane pressure (TMP) caused an increase in permeate flux, similar to that observed by Huang et al. (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2014\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIt was also observed that the greater the turbidity presented by the feed water of the UF module, the lower the permeate flux. So, the flux increased in the following order: River (2.61 NTU)\u0026thinsp;\u0026lt;\u0026thinsp;RM (0.84 NTU)\u0026thinsp;\u0026lt;\u0026thinsp;RML (0.69 NTU). Xia et al. (\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2004\u003c/span\u003e) observed that when the UF feed water had turbidity of 20 NTU and 450 NTU, it took 60 min and only 10 min for the permeate flux to decrease by 50%, respectively. However, the RM-fed UP010 P membrane did not exhibit this behaviour at 3 bar, with the permeate flux for the RM-fed experiment lower than that of the River-fed trial, despite the lower turbidity of RM. This is possibly due to some alteration in the pressurization of the permeation system when running with the River and/or the RM matrices.\u003c/p\u003e \u003cp\u003ePure water fluxes are used as reference to evaluate variations in flux throughout the permeation process (Huang et al. \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Figure\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e shows the normalized flux after its stabilization to the two membranes fed with River, RM and RML. The results presented by the UH050 P membrane show that at 2 and 3 bar, the decline of flux was similar and relatively smaller than that at 1 bar, and corresponded to 19% of the pure water flux. The UP010 P membrane, on the order hand, showed a smaller drop in the flux, reaching a minimum of 50% of the pure water flux. According to Habert et al. (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2006\u003c/span\u003e), the flux of a UF membrane can decrease in such a way that it can reach 10% of permeate flux with pure water. This difference is due to phenomena such as concentration polarization and particle adsorption on the membrane. Overall, the addition of MBBR-treated effluent and the lubricant industry wastewater to the river water positively affected the usual RO pretreatments of the WTP and the performance of UF membranes.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eAfter the UF permeation experiments, it was observed a film on the surface of the membranes, which was more evident on the UH050 P membranes, corroborating the obtained results of lower permeate flux. In addition, the formed films color indicates that the possible cause of membrane fouling was organic compounds (Fig. S6), as shown in the SDI\u003csub\u003e15\u003c/sub\u003e test (Mosset et al. \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2008\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAfter permeation, the aqueous matrices presented turbidity below the detection limit (\u0026lt;\u0026thinsp;0.02 NTU). Color reduction was also observed, and slightly lower values were obtained for UP010 P. The same was observed for TOC removal, however, at 3 bar (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). Considering the permeate water quality and permeation fluxes, the UH050 P was proposed for use in the industrial complex in the pressure range of 2\u0026ndash;3 bar. The insertion of the UF process is a pretreatment for RO allowing obtaining high quality water, with turbidity\u0026thinsp;\u0026lt;\u0026thinsp;0.02 NTU (SDI\u003csub\u003e15\u003c/sub\u003e\u0026thinsp;\u0026lt;\u0026thinsp;3), and color of 6 Pt-Co units (River), 10 Pt-Co units (RM) and 5 (RML) Pt-Co units. Hence, the UF filtrate can proceed to the reverse osmosis module, allowing the complete reuse of MBBR-treated and lubricant industry effluents.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eQuality of aqueous matrices fed to UF membranes (after cartridge microfiltration) and their permeates.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eParameter\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUnit\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFeed\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003ePermeate\u003c/p\u003e \u003cp\u003e(UP010 P)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e \u003cp\u003ePermeate\u003c/p\u003e \u003cp\u003e(UH050 P)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePressure\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ebar\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"8\" nameend=\"c8\" namest=\"c1\"\u003e \u003cp\u003eRiver\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTDS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003emg/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e303\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e250\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e270\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e270\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e243\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e233\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTOC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003emg/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eColor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePt-Co units\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTurbidity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNTU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"8\" nameend=\"c8\" namest=\"c1\"\u003e \u003cp\u003eRM\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTDS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003emg/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e406\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e310\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e389\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e385\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e380\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e345\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTOC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003emg/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e5.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eColor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePt-Co units\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTurbidity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNTU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"8\" nameend=\"c8\" namest=\"c1\"\u003e \u003cp\u003eRML\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTDS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003emg/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e392\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e387\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e380\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e346\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e328\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e338\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTOC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003emg/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e5.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eColor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePt-Co units\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTurbidity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNTU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eSome studies showed the importance of pretreatments prior to UF and compared the quality of treated water. Racar et al. (\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) pointed out the efficiency of using the sand filter before the UF process, since the filter reduces suspended particles and organics, thus increasing the critical flux and decreasing the membrane fouling. Lorain et al. (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2007\u003c/span\u003e) compared the conventional pretreatment of RO (coagulation/sand filtration) with coagulation/UF for the desalination of raw seawater (SDI 6.1\u0026ndash;6.4) and obtained SDI of 5.8\u0026ndash;5.9 and 1.2\u0026ndash;2 after the sand filter and UF, respectively. Water pretreated in the sand filter caused a loss of 28% of the permeability of RO membranes after 30 days, while the loss with the UF-pretreated water was 0% for 20 days due to the high quality of the feed water (turbidity\u0026thinsp;\u0026lt;\u0026thinsp;0.1 NTU). Increasingly, ultrafiltration is now recognized as the best pretreatment option for seawater desalination by RO due to water characteristics and limitations of the conventional pretreatment processes, such as coagulation, flocculation and sand filtration (Lorain et al. \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). Racar et al. (\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) studied the reclamation of the rendering plant secondary effluent (SE) and observed that the fouling of the UF membranes decreased considerably (50\u0026ndash;95%) when coagulation and sand filtration pretreatment was performed before UF. Furthermore, this sequence of treatment processes resulted in a permeate water that can be reused in the treatment plant and for irrigation.\u003c/p\u003e \u003cp\u003eRegarding the pesticide industry wastewater, Bachmann Pinto et al. (2018) assessed biological treatment followed by conventional and membrane processes aiming at water reuse. Microfiltration (0.45 \u0026micro;m) and ultrafiltration (100 kDa) were tested, and, in both processes, the permeate waters showed turbidity of 0.02 NTU and color of 10 Pt-Co units, which are similar to the results obtained in this study. The high quality water produced by UF, with low SDI values, improves the hydraulic performance of the RO, increases the permeate flux and membrane lifespan, and reduces fouling, cleaning frequency, energy consumption, and process costs (Lorain et al. \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Vedavyasan \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Wolf, Siverns, and Monti \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2005\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn this way, UF generates high quality feed water for RO modules, which, besides being responsible for optimizing the use of water resources through the reuse of treated water, are an alternative for the removal of pesticides whose MW range from 200 to 400 g/mol (Kiso \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2001\u003c/span\u003e). Therefore, RO membranes with a molecular weight cut off in this range may be suitable for pesticide removal. Although membrane separation processes depend on several parameters, there are indications that size exclusion is the main rejection mechanism (Plakas and Karabelas 2012). RO treatment may enable pesticide rejections greater than 90% (Chian, Bruce, and Fang 1975; Dražević et al. \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Khairkar et al. \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Mehta et al. 2015). Imidacloprid rejection by RO was studied by Gen\u0026ccedil; et al. (2017), who established as optimized conditions the following: BW30 membrane, TPM 30 bar, volume reduction factor 3 and pH 11. The IMI rejection for these conditions was 97.80%. Khairkar et al. (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) obtained IMI rejections during RO water purification greater than 90% when using PDMS-coated TFC membrane (10 ppm feed concentration).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec23\" class=\"Section3\"\u003e \u003ch2\u003e3.3.5 Proposed Treatment Train\u003c/h2\u003e \u003cp\u003eFigure\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e summarizes the color and turbidity removal results of the proposed pretreatment train for the RO modules, stressing the quality of permeates and the importance of the UF process. The combined processes presented excellent performance, achieving total turbidity removal efficiency of 99.9%, 99.8%, and 99.8%, and color removal of 96.2%, 87.3% and 93.1% for River, RM and RML matrices, respectively. Therefore, the proposed configuration of the pretreatment system for the RO unit could be composed of: coagulation/flocculation, sedimentation, sand filtration, cartridge microfiltration, and ultrafiltration (UH050 P; 2\u0026ndash;3 bar).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe final proposal for WTP optimization of the industrial complex aiming at the total reuse of the biologically (MBBR) treated pesticide-containing effluent and the lubricants industry effluent is illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e. The results obtained in this study show that implementing the UF process after the current conventional RO pretreatments can provide a high quality feed water, reduce the fouling of the RO membranes, and, consequently, minimize costs. The final water could be reused in industrial processes with compatible water demand, such as cooling towers, boilers, and/or fire suppression systems, as well in restrooms, to wash patios, etc.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"4 Conclusions","content":"\u003cp\u003eThe biological treatment of an industrial pesticide-containing wastewater in an MBBR was efficient in terms of average organic matter (86%) and ammonium (88%) removal. The MBBR treated effluent met the standards for disposal in surface water bodies, besides presenting superior quality compared to the receiving river water. The inclusion of that and the lubricant effluent streams to the withdrawn river water, in addition to improving the water treatment plant feed water quality, positively affected the RO pretreatment processes efficiency. However, the high fouling potentials (SDI\u003csub\u003e15\u003c/sub\u003e\u0026thinsp;\u0026gt;\u0026thinsp;5) after microfiltration exposed the need to insert a more selective treatment, such as ultrafiltration, to produce a better RO feed water quality. The two UF membranes evaluated (UP010 P and UH050 P) presented similar results of permeate water turbidity (0.02 NTU) and low color, with a slightly higher permeate flux achieved for the UH050 P membrane.\u003c/p\u003e \u003cp\u003eOverall, the proposed treatment train offered exceptional performance, reaching removal efficiencies of total turbidity of 99.9%, 99.8%, and 99.8%; and color of 96.2%, 87.3% and 93.1%, for River, RM and RML matrices, respectively. Furthermore, the non-removal of Imidacloprid during the biological treatment in the MBBR highlights the need to send the treated effluent to the WTP, thereby ensuring that the RO removes the compounds that are not biodegraded and, consequently, do not make them a source of contamination of the environment.\u003c/p\u003e \u003cp\u003eTherefore, the sequence of RO pretreatments proposed in this study allows producing high-quality water and enables the total reuse of wastewater streams in the industrial complex, minimizing the RO chemical cleaning frequency, operating costs, and increasing permeate flux and membrane lifespan.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eOn behalf of all authors, the corresponding author states that there is no conflict of interest. The authors would like to thank the financial support of the Brazilian government agencies CAPES and CNPQ.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors would like to thank the financial support of the Brazilian government agencies CAPES (Coordena\u0026ccedil;\u0026atilde;o de Aperfei\u0026ccedil;oamento Pessoal de N\u0026iacute;vel Superior) and CNPQ (Conselho Nacional de Desenvolvimento Cient\u0026iacute;fico e Tecnol\u0026oacute;gico).\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eAbuabdou, Salahaldin M.A., Waseem Ahmad, Ng Choon Aun, and Mohammed J.K. Bashir. 2020. \u0026ldquo;A Review of Anaerobic Membrane Bioreactors (AnMBR) for the Treatment of Highly Contaminated Landfill Leachate and Biogas Production: Effectiveness, Limitations and Future Perspectives.\u0026rdquo; \u003cem\u003eJournal of Cleaner Production\u003c/em\u003e 255: 120215. https://doi.org/10.1016/j.jclepro.2020.120215.\u003c/li\u003e\n \u003cli\u003eAmirtharajah, Appiah. 1988. \u0026ldquo;Some Theoretical and Conceptual Views of Filtration.\u0026rdquo; \u003cem\u003eJournal - American Water Works Association\u003c/em\u003e 80(12): 36\u0026ndash;46. https://onlinelibrary.wiley.com/doi/10.1002/j.1551-8833.1988.tb03147.x.\u003c/li\u003e\n \u003cli\u003eAPHA, AWWA, and WEF. 2017. \u003cem\u003eStandard Methods for the Examination of Water and Wastewater (23rd Edition)\u003c/em\u003e. 23rd ed. eds. Rodger B. Baird, Andrew D. Eaton, and Eugene W. Rice. USA: American Public Health Association; American Water Works Association; Water Environment Federation.\u003c/li\u003e\n \u003cli\u003eASTM. 2008. \u0026ldquo;ASTM D1426-08 - Standard Test Methods for Ammonia Nitrogen In Water.\u0026rdquo; (September).\u0026mdash;\u0026mdash;\u0026mdash;. 2014. \u0026ldquo;ASTM D4189-07 - Standard Method Test for Silt Density Index (SDI) of Water.\u0026rdquo;\u003c/li\u003e\n \u003cli\u003eBachmann Pinto, Haline, Bianca Miguel de Souza, and M\u0026aacute;rcia Dezotti. 2018. \u0026ldquo;Treatment of a Pesticide Industry Wastewater Mixture in a Moving Bed Biofilm Reactor Followed by Conventional and Membrane Processes for Water Reuse.\u0026rdquo; \u003cem\u003eJournal of Cleaner Production\u003c/em\u003e 201: 1061\u0026ndash;70. https://linkinghub.elsevier.com/retrieve/pii/S0959652618324557.\u003c/li\u003e\n \u003cli\u003eBaker, Richard W. 2004. Membrane Technology \u003cem\u003eMembrane Technology and Applications\u003c/em\u003e. 2nd ed. UK: John Wiley \u0026amp; Sons.\u003c/li\u003e\n \u003cli\u003eBassin, Jo\u0026atilde;o Paulo et al. 2012. \u0026ldquo;Effect of Different Operational Conditions on Biofilm Development, Nitrification, and Nitrifying Microbial Population in Moving-Bed Biofilm Reactors.\u0026rdquo; \u003cem\u003eEnvironmental Science \u0026amp; Technology\u003c/em\u003e 46(3): 1546\u0026ndash;55. http://pubs.acs.org/doi/abs/10.1021/es203356z.\u003c/li\u003e\n \u003cli\u003eBassin, Jo\u0026atilde;o Paulo, M\u0026aacute;rcia Dezotti, and Alexandre Rosado. 2018. \u0026ldquo;Molecular Biology Techniques Applied to the Study of Microbial Diversity of Wastewater Treatment Systems.\u0026rdquo; In \u003cem\u003eAdvanced Biological Processes for Wastewater Treatment - Emerging, Consolidated Technologies and Introduction to Molecular Techniques\u003c/em\u003e, Brazil: Springer, 205\u0026ndash;94.\u003c/li\u003e\n \u003cli\u003eCao, S. M. S., G. A. T. Fontoura, M\u0026aacute;rcia Dezotti, and J. P. Bassin. 2016. \u0026ldquo;Combined Organic Matter and Nitrogen Removal from a Chemical Industry Wastewater in a Two-Stage MBBR System.\u0026rdquo; \u003cem\u003eEnvironmental Technology\u003c/em\u003e 37(1): 96\u0026ndash;107. http://www.tandfonline.com/doi/full/10.1080/09593330.2015.1063708.\u003c/li\u003e\n \u003cli\u003eChen, Sheng, Dezhi Sun, and Jong-Shik Chung. 2007. \u0026ldquo;Treatment of Pesticide Wastewater by Moving-Bed Biofilm Reactor Combined with Fenton-Coagulation Pretreatment.\u0026rdquo; \u003cem\u003eJournal of Hazardous Materials\u003c/em\u003e 144(1\u0026ndash;2): 577\u0026ndash;84. https://linkinghub.elsevier.com/retrieve/pii/S0304389406012994.\u003c/li\u003e\n \u003cli\u003eChian, Edward S. K., Willis N Bruce, and Herbert H. P. Fang. 1975. \u0026ldquo;Removal of Pesticides by Reverse Osmosis.\u0026rdquo; \u003cem\u003eEnvironmental Science \u0026amp; Technology\u003c/em\u003e 9(1): 52\u0026ndash;59. https://pubs.acs.org/doi/abs/10.1021/es60099a009.\u003c/li\u003e\n \u003cli\u003eDražević, Emil, Kre\u0026scaron;imir Ko\u0026scaron;utić, Sanja Fingler, and Vlasta Drevenkar. 2011. \u0026ldquo;Removal of Pesticides from the Water and Their Adsorption on the Reverse Osmosis Membranes of Defined Porous Structure.\u0026rdquo; \u003cem\u003eDesalination and Water Treatment\u003c/em\u003e 30(1\u0026ndash;3): 161\u0026ndash;70. http://www.tandfonline.com/doi/abs/10.5004/dwt.2011.1959.\u003c/li\u003e\n \u003cli\u003eGabelich, Christopher J. et al. 2006. \u0026ldquo;Control of Residual Aluminum from Conventional Treatment to Improve Reverse Osmosis Performance.\u0026rdquo; \u003cem\u003eDesalination\u003c/em\u003e 190(1\u0026ndash;3): 147\u0026ndash;60. https://linkinghub.elsevier.com/retrieve/pii/S0011916406001329.\u003c/li\u003e\n \u003cli\u003eGen\u0026ccedil;, Nevim, Esra Can Doğan, Ali Oğuzhan Narcı, and Emine Bican. 2017. \u0026ldquo;Multi-Response Optimization of Process Parameters for Imidacloprid Removal by Reverse Osmosis Using Taguchi Design.\u0026rdquo; \u003cem\u003eWater Environment Research\u003c/em\u003e 89(5): 440\u0026ndash;50. http://doi.wiley.com/10.2175/106143017X14839994523460.\u003c/li\u003e\n \u003cli\u003eGoh, P.S. et al. 2022. \u0026ldquo;Membrane Technology for Pesticide Removal from Aquatic Environment: Status Quo and Way Forward.\u0026rdquo; \u003cem\u003eChemosphere\u003c/em\u003e 307: 136018. https://linkinghub.elsevier.com/retrieve/pii/S0045653522025115.\u003c/li\u003e\n \u003cli\u003eHabert, Alberto Cl\u0026aacute;udio, Cristiano Piacsek Borges, and Ronaldo Nobrega. 2006. \u003cem\u003eProcessos de Separa\u0026ccedil;\u0026atilde;o Por Membranas\u003c/em\u003e. Rio de Janeiro, RJ, Brazil: E-papers.\u003c/li\u003e\n \u003cli\u003eHowe, Kerry J. et al. 2012. \u003cem\u003ePrinciples of Water Treatment\u003c/em\u003e. 1st ed. USA: Wiley.\u003c/li\u003e\n \u003cli\u003eHuang, Jinhui et al. 2014. \u0026ldquo;Influence of Feed Concentration and Transmembrane Pressure on Membrane Fouling and Effect of Hydraulic Flushing on the Performance of Ultrafiltration.\u0026rdquo; \u003cem\u003eDesalination\u003c/em\u003e 335(1): 1\u0026ndash;8. https://linkinghub.elsevier.com/retrieve/pii/S0011916413005638.\u003c/li\u003e\n \u003cli\u003eINEA. 1986. \u0026ldquo;NT-202.R-10- Crit\u0026eacute;rios e Padr\u0026otilde;es Para Lan\u0026ccedil;amento de Efluentes L\u0026iacute;quidos.\u0026rdquo;\u003c/li\u003e\n \u003cli\u003e\u0026mdash;\u0026mdash;\u0026mdash;. 2007. \u0026ldquo;DZ-205.R-6 - Diretriz de Controle de Carga Org\u0026acirc;nica Em Efluentes L\u0026iacute;quidos de Origem Industrial.\u0026rdquo; : 2\u0026ndash;7.\u003c/li\u003e\n \u003cli\u003eJuang, Lain-Chuen, Dyi-Hwa Tseng, and He-Yin Lin. 2007. \u0026ldquo;Membrane Processes for Water Reuse from the Effluent of Industrial Park Wastewater Treatment Plant: A Study on Flux and Fouling of Membrane.\u0026rdquo; \u003cem\u003eDesalination\u003c/em\u003e 202(1\u0026ndash;3): 302\u0026ndash;9. https://linkinghub.elsevier.com/retrieve/pii/S0011916406012252.\u003c/li\u003e\n \u003cli\u003eKabsch-Korbutowicz, Malgorzata. 2006. \u0026ldquo;Removal of Natural Organic Matter from Water by In-Line Coagulation/Ultrafiltration Process.\u0026rdquo; \u003cem\u003eDesalination\u003c/em\u003e 200(1\u0026ndash;3): 421\u0026ndash;23. https://linkinghub.elsevier.com/retrieve/pii/S0011916406008381.\u003c/li\u003e\n \u003cli\u003eKhairkar, Shyam R. et al. 2020. \u0026ldquo;Hydrophobic Interpenetrating Polyamide-PDMS Membranes for Desalination, Pesticides Removal and Enhanced Chlorine Tolerance.\u0026rdquo; \u003cem\u003eChemosphere\u003c/em\u003e 258: 127179. https://doi.org/10.1016/j.chemosphere.2020.127179.\u003c/li\u003e\n \u003cli\u003eKiso, Yoshiaki. 2001. \u0026ldquo;Effects of Hydrophobicity and Molecular Size on Rejection of Aromatic Pesticides with Nanofiltration Membranes.\u0026rdquo; \u003cem\u003eJournal of Membrane Science\u003c/em\u003e 192(1\u0026ndash;2): 1\u0026ndash;10. https://linkinghub.elsevier.com/retrieve/pii/S0376738801004112.\u003c/li\u003e\n \u003cli\u003eKucera, Jane. 2010. \u003cem\u003eReverse Osmosis - Industrial Applications and Processes\u003c/em\u003e. 1st ed. 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Quantification in Terms of Capital Investment Cost and Operating Cost Reduction.\u0026rdquo; \u003cem\u003eDesalination\u003c/em\u003e 203(1\u0026ndash;3): 277\u0026ndash;85. https://linkinghub.elsevier.com/retrieve/pii/S0011916406012768.\u003c/li\u003e\n \u003cli\u003eLuo, Yunlong. 2014. \u0026ldquo;A Sponge - Based Moving Bed Bioreactor for Micropollutant Removal from Municipal Wastewater.\u0026rdquo; http://hdl.handle.net/10453/29223.\u003c/li\u003e\n \u003cli\u003eMatheus, Maur\u0026iacute;cio C. et al. 2020. \u0026ldquo;Assessing the Impact of Hydraulic Conditions and Absence of Pretreatment on the Treatability of Pesticide Formulation Plant Wastewater in a Moving Bed Biofilm Reactor.\u0026rdquo; \u003cem\u003eJournal of Water Process Engineering\u003c/em\u003e 36(February): 101243. https://doi.org/10.1016/j.jwpe.2020.101243.\u003c/li\u003e\n \u003cli\u003eMatsushita, Taku et al. 2018. \u0026ldquo;Removals of Pesticides and Pesticide Transformation Products during Drinking Water Treatment Processes and Their Impact on Mutagen Formation Potential after Chlorination.\u0026rdquo; \u003cem\u003eWater Research\u003c/em\u003e 138: 67\u0026ndash;76. https://doi.org/10.1016/j.watres.2018.01.028.\u003c/li\u003e\n \u003cli\u003eMehta, Romil, H. Brahmbhatt, N.K. Saha, and A. Bhattacharya. 2015. \u0026ldquo;Removal of Substituted Phenyl Urea Pesticides by Reverse Osmosis Membranes: Laboratory Scale Study for Field Water Application.\u0026rdquo; \u003cem\u003eDesalination\u003c/em\u003e 358: 69\u0026ndash;75. http://dx.doi.org/10.1016/j.desal.2014.12.019.\u003c/li\u003e\n \u003cli\u003eMetcalf \u0026amp; Eddy et al. 2014. \u003cem\u003eWastewater Engineering: Treatment and Resource Recovery\u003c/em\u003e. 5th ed. USA: McGraw-Hill.\u003c/li\u003e\n \u003cli\u003eMiyoshi, Taro et al. 2015. \u0026ldquo;Effect of Membrane Polymeric Materials on Relationship between Surface Pore Size and Membrane Fouling in Membrane Bioreactors.\u0026rdquo; \u003cem\u003eApplied Surface Science\u003c/em\u003e 330: 351\u0026ndash;57. http://dx.doi.org/10.1016/j.apsusc.2015.01.018.\u003c/li\u003e\n \u003cli\u003eMosset, Amandine, V\u0026eacute;ronique Bonnelye, Marc Petry, and Miguel Angel Sanz. 2008. \u0026ldquo;The Sensitivity of SDI Analysis: From RO Feed Water to Raw Water.\u0026rdquo; \u003cem\u003eDesalination\u003c/em\u003e 222(1\u0026ndash;3): 17\u0026ndash;23. https://linkinghub.elsevier.com/retrieve/pii/S0011916407007515.\u003c/li\u003e\n \u003cli\u003eOtitoju, Tunmise Ayode, Abdul Latif Ahmad, and Boon Seng Ooi. 2018. \u0026ldquo;Recent Advances in Hydrophilic Modification and Performance of Polyethersulfone (PES) Membrane via Additive Blending.\u0026rdquo; \u003cem\u003eRSC Advances\u003c/em\u003e 8(40): 22710\u0026ndash;28. http://xlink.rsc.org/?DOI=C8RA03296C.\u003c/li\u003e\n \u003cli\u003ePearce, G.K. 2008. \u0026ldquo;UF/MF Pre-Treatment to RO in Seawater and Wastewater Reuse Applications: A Comparison of Energy Costs.\u0026rdquo; \u003cem\u003eDesalination\u003c/em\u003e 222(1\u0026ndash;3): 66\u0026ndash;73. https://linkinghub.elsevier.com/retrieve/pii/S0011916407007564.\u003c/li\u003e\n \u003cli\u003ePlakas, Konstantinos V., and Anastasios J. Karabelas. 2012. \u0026ldquo;Removal of Pesticides from Water by NF and RO Membranes \u0026mdash; A Review.\u0026rdquo; \u003cem\u003eDesalination\u003c/em\u003e 287: 255\u0026ndash;65. https://linkinghub.elsevier.com/retrieve/pii/S0011916411006874.\u003c/li\u003e\n \u003cli\u003eRacar, M. et al. 2019. \u0026ldquo;Rendering Plant Wastewater Reclamation by Coagulation, Sand Filtration, and Ultrafiltration.\u0026rdquo; \u003cem\u003eChemosphere\u003c/em\u003e 227: 207\u0026ndash;15. https://linkinghub.elsevier.com/retrieve/pii/S0045653519306927.\u003c/li\u003e\n \u003cli\u003eRacar, Marko, Davor Dolar, Ana \u0026Scaron;pehar, and Kre\u0026scaron;imir Ko\u0026scaron;utić. 2017. \u0026ldquo;Application of UF/NF/RO Membranes for Treatment and Reuse of Rendering Plant Wastewater.\u0026rdquo; \u003cem\u003eProcess Safety and Environmental Protection\u003c/em\u003e 105: 386\u0026ndash;92. https://linkinghub.elsevier.com/retrieve/pii/S0957582016302853.\u003c/li\u003e\n \u003cli\u003eSaraiva Soares, A. F. et al. 2013. \u0026ldquo;Efficiency of Conventional Drinking Water Treatment Process in the Removal of Endosulfan, Ethylenethiourea, and 1,2,4-Triazole.\u0026rdquo; \u003cem\u003eJournal of Water Supply: Research and Technology-Aqua\u003c/em\u003e 62(6): 367\u0026ndash;76. https://iwaponline.com/aqua/article/62/6/367/29168/Efficiency-of-conventional-drinking-water.\u003c/li\u003e\n \u003cli\u003eSong, Lianfa, and Menachem Elimelech. 1995. \u0026ldquo;Theory of Concentration Polarization in Crossflow Filtration.\u0026rdquo; \u003cem\u003eJournal of the Chemical Society, Faraday Transactions\u003c/em\u003e 91(19): 3389. http://xlink.rsc.org/?DOI=ft9959103389.\u003c/li\u003e\n \u003cli\u003eThuy, Pham Thi et al. 2008. \u0026ldquo;To What Extent Are Pesticides Removed from Surface Water during Coagulation-Flocculation?\u0026rdquo; \u003cem\u003eWater and Environment Journal\u003c/em\u003e 22(3): 217\u0026ndash;23. https://onlinelibrary.wiley.com/doi/10.1111/j.1747-6593.2008.00128.x.\u003c/li\u003e\n \u003cli\u003eVedavyasan, C.V. 2007. \u0026ldquo;Pretreatment Trends \u0026mdash; an Overview.\u0026rdquo; \u003cem\u003eDesalination\u003c/em\u003e 203(1\u0026ndash;3): 296\u0026ndash;99. https://linkinghub.elsevier.com/retrieve/pii/S0011916406012781.\u003c/li\u003e\n \u003cli\u003eVISHNIAC, W, and M SANTER. 1957. \u0026ldquo;The Thiobacilli.\u0026rdquo; \u003cem\u003eBacteriological reviews\u003c/em\u003e 21(3): 195\u0026ndash;213. http://www.ncbi.nlm.nih.gov/pmc/articles/PMC180898/.\u003c/li\u003e\n \u003cli\u003eWang, Li et al. 2018. \u0026ldquo;Integrated Aerobic Granular Sludge and Membrane Process for Enabling Municipal Wastewater Treatment and Reuse Water Production.\u0026rdquo; \u003cem\u003eChemical Engineering Journal\u003c/em\u003e 337: 300\u0026ndash;311. https://doi.org/10.1016/j.cej.2017.12.078.\u003c/li\u003e\n \u003cli\u003eWardani, A.K., D. Ariono, S. Subagjo, and IG. Wenten. 2020. \u0026ldquo;Fouling Tendency of PDA/PVP Surface Modified PP Membrane.\u0026rdquo; \u003cem\u003eSurfaces and Interfaces\u003c/em\u003e 19(10): 100464. https://linkinghub.elsevier.com/retrieve/pii/S246802301930639X.\u003c/li\u003e\n \u003cli\u003eWolf, Peter H., Steve Siverns, and Sandro Monti. 2005. \u0026ldquo;UF Membranes for RO Desalination Pretreatment.\u0026rdquo; \u003cem\u003eDesalination\u003c/em\u003e 182(1\u0026ndash;3): 293\u0026ndash;300. https://linkinghub.elsevier.com/retrieve/pii/S0011916405004431.\u003c/li\u003e\n \u003cli\u003eXia, Shengji, Jun Nan, Ruiping Liu, and Guibai Li. 2004. \u0026ldquo;Study of Drinking Water Treatment by Ultrafiltration of Surface Water and Its Application to China.\u0026rdquo; \u003cem\u003eDesalination\u003c/em\u003e 170(1): 41\u0026ndash;47. https://linkinghub.elsevier.com/retrieve/pii/S0011916404800171.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":true,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"brazilian-journal-of-chemical-engineering","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bjce","sideBox":"Learn more about [Brazilian Journal of Chemical Engineering](http://link.springer.com/journal/43153)","snPcode":"43153","submissionUrl":"https://www.editorialmanager.com/bjce/default2.aspx","title":"Brazilian Journal of Chemical Engineering","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"moving bed biofilm reactor, pesticide wastewater treatment, ultrafiltration, zero disposal, industrial wastewater","lastPublishedDoi":"10.21203/rs.3.rs-2804636/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-2804636/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eProper treatment and reuse of industrial wastewaters are efficient ways to mitigate their environmental impacts. In this work, a pesticide formulation wastewater pretreated by activated carbon was combined with sewage (4:96) and subjected to biotreatment in a lab-scale moving-bed biofilm reactor (MBBR) with 50% media filling ratio and 6h HRT. Throughout 180 days, efficient removal was achieved for organic matter (86%, tCOD) and ammonium (88%). Additionally, the MBBR effluent exhibited higher quality than the water of the river used by the pesticide industry. For evaluating the possibility of wastewater reuse, the effluents from the MBBR (M) and a lubricant industry (L, from the same industrial site) were combined with the river water (R) that feeds the industrial water treatment plant (WTP) and submitted to a lab-scale reproduced WTP: coagulation/flocculation, sedimentation, sand filtration and microfiltration. River water and two combinations (RM: 85:15 and RML: 80:15:5) were assessed. The mixtures improved the efficiency of the lab-reproduced WTP; however, the fouling potential was high (SDI\u003csub\u003e15\u003c/sub\u003e\u0026gt;5) for reverse osmosis at the end of the WTP. Thus, after microfiltration, two ultrafiltration (UF) membranes (10 and 50 kDa) were tested, producing similar quality water (0.02 NTU, low SDI and color). After UF, the total turbidity and color removals for R, RM and RML were, respectively, 99.87%, 99.84% and 99.81%, and 96.2%, 87.3% and 93.1%. The UF implementation produced stable high-quality water, implying a reduction of RO membrane costs and cleaning frequency, while increasing the permeate flux. Ultimately, complete wastewater reuse was enabled by the proposed chain.\u003c/p\u003e","manuscriptTitle":"Treatment and reuse of a pesticide-containing wastewater by a combination of physicochemical, biological and membrane processes","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2023-04-19 15:07:56","doi":"10.21203/rs.3.rs-2804636/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewerAgreed","content":"","date":"2023-04-17T16:45:29+00:00","index":0,"fulltext":""},{"type":"reviewersInvited","content":"","date":"2023-04-17T14:52:41+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"Brazilian Journal of Chemical Engineering","date":"2023-04-13T05:28:02+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2023-04-13T04:03:52+00:00","index":"","fulltext":""},{"type":"submitted","content":"Brazilian Journal of Chemical Engineering","date":"2023-04-11T17:25:23+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"brazilian-journal-of-chemical-engineering","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bjce","sideBox":"Learn more about [Brazilian Journal of Chemical Engineering](http://link.springer.com/journal/43153)","snPcode":"43153","submissionUrl":"https://www.editorialmanager.com/bjce/default2.aspx","title":"Brazilian Journal of Chemical Engineering","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"fea21016-d93f-466e-9c4c-1ce170210729","owner":[],"postedDate":"April 19th, 2023","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2023-09-18T15:07:50+00:00","versionOfRecord":{"articleIdentity":"rs-2804636","link":"https://doi.org/10.1007/s43153-023-00394-z","journal":{"identity":"brazilian-journal-of-chemical-engineering","isVorOnly":false,"title":"Brazilian Journal of Chemical Engineering"},"publishedOn":"2023-09-11 15:02:36","publishedOnDateReadable":"September 11th, 2023"},"versionCreatedAt":"2023-04-19 15:07:56","video":"","vorDoi":"10.1007/s43153-023-00394-z","vorDoiUrl":"https://doi.org/10.1007/s43153-023-00394-z","workflowStages":[]},"version":"v1","identity":"rs-2804636","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-2804636","identity":"rs-2804636","version":["v1"]},"buildId":"WrCJVZZCHTDjtuVLN7oU0","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}