{"paper_id":"45031912-117b-4bfb-abda-aee957d02385","body_text":"Ecological Risk Assessment of Five Endocrine-Disrupting Compounds in Wastewater Treatment Plants from Monterrey, Mexico | 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 Ecological Risk Assessment of Five Endocrine-Disrupting Compounds in Wastewater Treatment Plants from Monterrey, Mexico Khirbet López-Velázquez, Jorge L. Guzmán-Mar, Hugo A. Saldarriaga-Noreña, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-708615/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 5 You are reading this latest preprint version Abstract The potential ecological risk of five residual endocrine-disrupting compounds (EDCs) in four wastewater treatment plants (WWTPs) was studied. The wastewater samples were collected in WWTPs of the Metropolitan Area of Monterrey, Mexico (designed as Monterrey City hereinafter) and 17β-estradiol (E2), 17α-ethinylestradiol (EE2), bisphenol A (BPA), 4-nonylphenol (4NP), and 4-tert-octylphenol (4TOP) were studied by SPE/GC-MS method. Results showed that all EDCs are widely distributed in WWTPs, finding high concentrations of BPA (450 ng/L) and EE2 (407.5 ng/L) in influents, while EE2 and 4TOP were the most abundant in effluents at levels from 1.6–26.8 ng/L (EE2) and < LOQ – 5.0 ng/L (4TOP), which corroborate that the wastewater discharges represent critical sources of EDCs to the aquatic environments. The potential ecological risk of residual EDCs was evaluated through risk quotients (RQs), and results indicated that the effluents of the WWTPs represent a high risk to exposed aquatic species, mainly due to the effect of residual estrogens E2 and EE2 which were considered as the most hazardous compounds among the studied EDCs, with RQ values up to 49.1 and 1165.2, respectively. Environmental Chemistry Toxicology health risk environmental pollution emerging contaminants quotient risk water pollution WWTP. Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction Endocrine-disrupting compounds (EDCs) belong to a subclass of so-called emerging organic pollutants and their presence in the environment represents a potential risk to public health (Sauvé and Desrosiers 2014 ). According to the United States Environmental Protection Agency (USEPA) and the European Chemicals Agency (ECHA), EDCs are exogenous substances or a mixture of substances that alter the structure or function(s) of the endocrine system and cause adverse effects at the level of the organism, its progeny, populations or subpopulations of organisms (EPA 1998 ; ECHA and EFSA 2018). These compounds are widely distributed in the environment, mainly in aquatic ecosystems, and have attracted special attention due to their potential risk to the health of aquatic organisms and humans, even at very low concentrations such as ng/L (Adeel et al. 2017 ). Several studies have reported that EDCs may generate different adverse effects on exposed organisms, including feminization and masculinization, deficiencies in the sexual, prostate, brain, and immune development, gonadal atrophy, infertility, precocious puberty, and different types of cancer (prostate, testicles, breast, ovaries, among others) (Roby 2013 ; Kabir et al. 2015 ; Wang et al. 2019 ; Jackson and Klerks 2020 ). Moreover, it has been reported that EDCs may be associated with a high incidence of obesity and the development of diseases such as diabetes in humans (Hatch et al. 2010 ). Among the different EDCs, the estrogens E2 and EE2, the alkylphenols 4NP and 4TOP, as well as the plasticizer BPA, are the most frequently EDCs detected in various aquatic environments such as rivers, lakes, and coastal areas (Ronderos-Lara et al. 2018 ; Calderón-Moreno et al. 2019 ; Inam et al. 2019 ; Salgueiro-González et al. 2019 ; Jiang et al. 2020 ; Čelić et al. 2020 ); due to their high estrogenic potential, these substances are being regulated by the European legislation through the European Water Framework Directive (2000/60/EC). In this sense, 2.0 µg/L has been defined as the maximum admissible concentration for 4NP and 4TOP in surface water (European Parliament 2008). In addition, BPA and E2 were recently proposed for inclusion as priority hazardous substances, recommending 0.01 µg/L and 0.001 µg/L as the maximum allowable concentration in surface water, respectively (European Parliament 2018 ). Regarding EE2, has been included in the watch list to monitor it and evaluate its possible incorporation as a priority hazardous substance for human health (European Parliament 2013). In another way, it is known that effluents from WWTPs are one of the main sources of EDCs emissions to aquatic environments, and several studies have reported the detection of EDCs in WWTP effluents around the world, revealing that these substances are partially removed during wastewater treatment processes (Manickum and John 2014 ; Wee et al. 2019 ; Jiang et al. 2020 ; Čelić et al. 2020 ). For example, Jiang et al. ( 2020 ) detected E2 (< LOQ − 50.03 ng/L) and EE2 (4.72–35.03 ng/L) in effluents from 38 WWTPs in China. Similarly, Manickum and John ( 2014 ) reported the detection of E2 (4.0–107.0 ng/L) and EE2 (1.0–8.0 ng/L) in the effluent of a WWTP in South Africa. On the other hand, BPA (3.31 ng/L), 4NP (4.62 ng/L), and 4TOP (4.44 ng/L) were detected in a WWTP effluent in Portugal (Carvalho et al. 2016 ). Furthermore, 4NP (420–2120 ng/L) and 4TOP (5.3–54.8 ng/L) were detected in effluents of nine WWTPs in Iran (Bina et al. 2018 ). Therefore, the incomplete removal of EDCs in WWTPs contributes to their frequent detection in surface water, which may subsequently impact on the essential activities such as agriculture, livestock, fisheries, drinking water, and domestic and recreational activities (Čelić et al. 2020 ). In Mexico, some studies have reported the detection of E2, EE2, and BPA in several WWTPs in a wide concentration range from < LOD – 16,600 ng/L (Díaz-Torres et al. 2013 ; Estrada-Arriaga et al. 2016 ; López-Velázquez et al. 2020 ; Villarreal-Morales et al. 2020 ). Likewise, other authors such as Calderón-Moreno et al. ( 2019 ), and Ronderos-Lara et al. ( 2018 ) detected E2, EE2, BPA, 4NP and 4TOP in river water (Morelos, Mexico) at levels from < LOD – 624.3 ng/L, emphasizing EE2 and BPA as the most abundant EDCs. In particular, the study of EDCs in Monterrey city is of great interest due to it is the second most populated region in Mexico (5,341,171 inhabitants; INEGI 2021 ), and stands out as one of the most industrialized zone in the country (SEDATU 2015 ) contributing with the emission of a large number of pollutants into the environment, including some EDCs as was informed by Cruz-López et al. ( 2020 ), and Villarreal-Morales et al. ( 2020 ). Moreover, is of great interest to evaluate the ecological risk on the aquatic systems due to their high estrogenic potential and the continuous emission of EDCs towards the environment, which may impact directly on the ecosystems of the receiving water bodies such as the urban rivers Pesqueria, Santa Catarina, La Silla, Sabinal, and Topo Chico (Fig. 1 ),which are tributaries to the Rio San Juan that flows into the Rio Bravo (natural border between Mexico and United States) and the Gulf of Mexico. Recently, some studies have been focused on evaluating the potential environmental risk through hazard index associated with E2, EE2, BPA, 4NP, and 4TOP in the dissolved phase of surface water (Stasinakis et al. 2012 ; Peng et al. 2017 ; Calderón-Moreno et al. 2019 ) as well as influents and effluents of WWTPs (Yu et al. 2013 ; Manickum and John 2014 ; Patrolecco et al. 2015 ; Ben et al. 2018 ; Jiang et al. 2020 ). In these studies, the risk quotients (RQ) have been calculated for several aquatic organisms (i.e. algae, crustaceans, and fish), and it is considered a useful strategy for the evaluation of water resources, which could contribute to improve the wastewater treatment processess, implementing effective strategies of management and control of wastewater discharges, surface, and drinking water, for the health protection of human and aquatic organisms (Xu et al. 2016). Therefore, this study aims to determine the potential environmental risks associated with five dissolved EDCs in four WWTPs from Monterrey City, which to our knowledge, constitutes the first report of this type in WWTPs from Mexico. Materials And Methods Chemical and reagents 17β-estradiol (≥ 98.0%), 17α-ethinylestradiol (≥ 98.0%), bisphenol A (≥ 99.0%), 4-nonylphenol (≥ 99.0%), 4-tert-octylphenol (≥ 99.0%), chrysene-d12 (≥ 99.0%), N,O-bis(trimethylsilyl)trifluoroacetamide + trimethylchlorosilane (BSTFA + TMCS, 99:1), pyridine (≥ 99.0%), hexane, methanol and dichloromethane HPLC grade were purchased from Sigma-Aldrich (St. Louis, MO, USA). Water HPLC grade was acquired from Tedia Company, and acetone HPLC grade was acquired from Meyer. The Oasis HLB solid-phase extraction cartridges (500 mg, 6 mL) were purchased from Waters (Milford, USA). Standard stock solutions (1000 µg/mL) of individual EDCs and Chrysene-d12 used as internal standard (1500 µg/mL) were prepared in acetone. These solutions were stored in amber vials at 4°C until use. Sample collection and instrumental analysis In this work, four WWTPs that receive urban and industrial wastewater were studied, the geographical location of WWTPs is shown in Fig. 1 , and detailed information of each WWTP and the main quality parameters of the wastewater samples were included in Table 1 . Table 1 Main characteristics of the studied WWTPs and wastewater samples. WWTP Capacity (m 3 /day) Population served Average discharge (m 3 /day) Physicochemical characteristics of the wastewater samples Stage T (°C) pH DO (mg/L) TSS (mg/L) COD (mg/L) BOD 5 (mg/L) A 17280 377480 15322.5 I 24.3 7.4 1.9 267.7 593.7 218.9 E 24.1 7.1 7.2 17.3 57.5 13.9 B 345600 1931229 232465.6 I 22.9 7.2 3.0 385.3 660.7 255.6 E 25.9 7.2 6.0 21.3 54.0 14.3 C 162000 444006 97436.5 I 23.6 7.1 1.7 257.7 607.2 209.9 E 24.4 7.3 6.0 17.0 62.3 8.2 D 648000 796337 589671.4 I 22.8 7.4 1.9 286.4 726.2 230.2 E 24.2 7.2 6.6 23.2 57.1 12.4 I, influent: E, effluent; DO, dissolved oxygen; TSS, total suspended solids; COD, chemical oxygen demand; BOD 5 , biological oxygen demand at the five days. Two sampling campaings were carried out in January and August 2019, and composite wastewater samples were collected in influents and disinfected effluents of each WWTP (2 L, made up of three simple samples). The samples were stored in amber glass bottles, transported at 4°C, and preserved at -20°C until their analysis, according to Method 1698 from the USEPA ( 2007 ). Subsequently, the solid-phase extraction and gas chromatography coupled to the mass spectrometer (SPE/GC-MS) were employed for the EDCs analysis as was described in previous work (López-Velázquez et al. 2021 ) and strict quality control procedures were adopted. Briefly, based on the internal standard method, good correlation coefficients (R 2 > 0.982) were obtained for all EDCs; limits of detection (LOD) ranged from 0.21 ng/L (E2) to 1.1 ng/L (EE2) and limits of quantification (LOQ) ranged from 0.71 ng/L (E2) to 3.01 ng/L (EE2). The precision of the method (expressed as relative standard deviation) was < 4.9% at 25 ng/L, and < 6.4% at 230 ng/L for each EDC in both concentration levels. Moreover, recoveries of EDCs ranged from 74.6% (EE2) to 103.4% (BPA), and all instrumental and procedural blanks were below LOD. Data analysis Daily mass Using data of EDCs levels detected in the WWTPs, the daily mass of each EDC in the influents and effluents (Mass inf or eff ) was calculated by Eq. 1. Where C inf and C eff are the concentrations of the selected EDCs in the influents and effluents of the WWTPs (mg/m 3 ). Q water is the daily wastewater flow in each WWTP (m 3 /day) which were considered equals in influents and effluents since the loss of wastewater during the treatments and the effect of the dilution by rainfall was considered small and negligible in the sampling dates (20–30 mm/month; CONAGUA 2019 ). Moreover, the approximate remotion (AR) for each EDC were estimated following Eq. 2: Ecological risk assessment In this study, the potential environmental risk of the EDCs detected in the WWTPs was assessed employing the risk quotients (RQ), which is an internationally accepted parameter for environmental risk assessment (European Commission 2003 ; EMEA 2006 ). RQ values were calculated as follows (Eq. 3): Where MEC is the measured concentration in influents and effluents of WWTPs (ng/L), and PNEC is the predicted no-effect concentration. PNEC values for each EDCs in wastewater were calculated by Eq. 4: Where HC5 is the hazardous concentration for 5% of the exposed species, and AF is the assessment factor which was set to 3 in order to protect other more sensitive organisms no considered in the toxicological studies (Tamis and Jongbloed 2019 ). HC5 values for E2, EE2, BPA, 4NP, and 4TOP were taken from scientific literature and are shown in Table 5 . Further, the criteria for establishing the potential ecological risk were the following: RQ ≥ 1, high risk; 0.1 ≤ RQ ≤ 1, medium risk, and RQ < 0.1, low risk (Huang et al. 2018 ). In addition, regarding RQs for surface water, a dilution factor of 10 was used for MEC values (Jiang et al. 2020 ), assuming that effluents of WWTP would be diluted after being discharged. Results And Discussion Concentrations of EDCs in influents The frequency of detection of the five EDCs in the influents was variable, ranging from 62.5% (4NP) to 100% (EE2) as shown in Table 2 . Notably, EE2 was detected in all samples collected during the two sampling campaigns reaching high levels up to 407.5 ng/L (Fig. 2 ). These EE2 levels were higher than those detected in 38 WWTPs in China, ranging from 4.96 to 51.06 ng/L (Jiang et al. 2020 ), and those detected in South Africa (one WWTP) ranging from 10 to 95 ng/L (Manickum and John 2014 ). However, EE2 concentrations are comparable to that reported by Belhaj et al. ( 2016 ), who detected concentrations between 199 and 600 ng/L in the influent of one WWTP (Tunisian). Furthermore, E2 levels in influents ranged from < LOD – 15.1 ng/L (frequency of 75%) and were lower than those detected in 38 WWTPs from China (< LOQ – 62.92 ng/L) (Jiang et al. 2020 ), and those detected in one urban WWTP from Tunisian, between 45.0–75.0 ng/L (Belhaj et al. 2016 ). According to previous studies, it is known that the occurrence of estrogens such as E2 and EE2 is related to the extensive use of these substances as therapeutic or contraceptive agents, and their subsequent excretion mainly in urine, which is considered one of the main sources of estrogens to the environment (Manickum and John 2014 ). Table 2 Concentrations (ng/L) of selected EDCs in four WWTPs. Influents Effluents Range mean median DF a (%) Range mean median DF (%) E2 <LOQ b – 15.1 4.3 2.9 75.0 <LOQ – 9.5 1.5 <LOQ 37.5 EE2 <LOQ c – 407.5 73.2 14.2 100 1.6–26.8 9.7 7.4 100 BPA <LOQ d – 450 72.1 7.1 87.5 <LOQ – 3.0 0.43 <LOQ 25.0 4NP <LOQ e – 18.9 3.3 0.5 62.5 <LOQ – 2.3 0.35 <LOQ 37.5 4TOP <LOQ f – 58.8 8.8 1.2 87.5 <LOQ – 5.0 1.2 0.5 62.5 a DF = detection frequency; LOQ = b 0.71 ng/L, c 3.0 ng/L, d 1.7 ng/L, e 0.86 ng/L, f 0.91 ng/L. The frequency of detection of BPA and 4TOP in the influents was also high (87.5% for each one) and the range of concentration was < LOQ – 450 ng/L for BPA and < LOQ – 58.8 ng/L for 4TOP in the four WWTPs. These concentrations of BPA and 4TOP are lower than those detected in five WWTPs from the USA, between 60–600 ng/L for BPA, and 80–3900 ng/L for 4TOP (Yu et al. 2013 ), and to those reported in six WWTPs from Mexico-USA, ranging between 175.5–1476.8 ng/L for BPA, and 259.3–3693.7 ng/L for 4TOP (De la Torre 2011 ). Similarly, 4NP was detected in the influents of the four WWTPs but with lower frequency (62.5%) at levels from < LOQ – 18.9 ng/L, much lower than reported by Bina et al. ( 2018 ) in nine WWTPs of Iran (ranging from 1250 to 17020 ng/L) and Jiang et al. ( 2020 ) in 38 WWTPs from China (ranging between 1519.5 and 27736.7 ng/L). As shown in Fig. 2 , EE2 as well as BPA, were the most abundant EDCs in the influents of WWTPs, and its wide concentration range reflects the high consumption rates and its constant emission in urban and industrial wastewater discharges from Monterrey City. Furthermore, in this study, low levels of 4NP and 4TOP compared to those detected levels in other research suggests a moderate use of these alkylphenols contained in surfactants and detergents, mainly used in domestic and commercial activities (Bina et al. 2018 ). In addition, Table 3 shows a summarized comparison between EDC levels detected in this research and those reported in other regions, where the EDCs amounts are often widely detected of the order of ng/L. Table 3 Comparisons of EDCs levels detected in WWTPs from other countries. EDC Country Nº of studied WWTP Influents (ng/L) Effluents (ng/L) References E2 Mexico 4 <LOQ – 15.1 <LOQ – 9.5 This study China 38 <LOQ – 62.92 <LOQ – 50.03 (Jiang et al. 2020 ) South Africa 1 20–199 4–107 (Manickum and John 2014 ) USA 6 <LOD – 106.5 <LOD – 42.2 (De La Torre 2011 ) Mexico 2 ND <LOD – 0.7 (Díaz-Torres et al. 2013 ) Mexico 2 20–31.5 ND (Estrada-Arriaga et al. 2016 ) Tunisian 1 45–78 10.0–46.0 (Belhaj et al. 2016 ) EE2 Mexico 4 <LOQ – 407.5 1.6–26.8 This study China 38 4.96–51.06 4.72–35.03 (Jiang et al. 2020 ) South Africa 1 10–95 1–8 (Manickum and John 2014 ) Tunisian 1 199–600 179–294 (Belhaj et al. 2016 ) BPA Mexico 4 <LOQ – 450 <LOQ – 3.0 This study Greece 1 ND 151–790 (Stasinakis et al. 2012 ) USA 5 60–600 <LOQ – 44 (Yu et al. 2013 ) USA 6 175.5–1,476.8 11.1–685.6 (De La Torre 2011 ) México 1 5,900–16,600 ND (Villarreal-Morales et al. 2020 ) Mexico 2 ND <LOD – 30 (Díaz-Torres et al. 2013 ) Portugal 1 10.01 ± 1.89 3.31 ± 0.09 (Carvalho et al. 2016 ) 4NP Mexico 4 <LOQ – 18.9 <LOQ – 2.3 This study China 38 1,519.51–27,736.71 1,346.75–7,513.57 (Jiang et al. 2020 ) Greece 1 ND 2,581–4,552 (Stasinakis et al. 2012 ) USA 5 220–870 <LOQ – 50 (Yu et al. 2013 ) USA 6 2,412.8–66,457.7 71.6–7,899.5 (De La Torre 2011 ) Iran 9 1,250–17,020 420–2,120 (Bina et al. 2018 ) Portugal 1 4.62 ± 0.32 4.44 ± 0.19 (Carvalho et al. 2016 ) 4TOP Mexico 4 <LOQ – 58.8 <LOQ – 5.0 This study USA 5 80–3,900 <LOQ – 100 (Yu et al. 2013 ) USA 6 259.3–3,693.7 7.2–416.1 (De La Torre 2011 ) Iran 9 35–718 5.3–54.8 (Bina et al. 2018 ) Portugal 1 ND ND (Carvalho et al. 2016 ) ND = not detected, LOQ = limit of quantification, LOD = limit of detection. Concentrations of EDCs in effluents The detection frequency and concentrations of the five selected EDCs in the effluents were lower than those detected in the influents (Table 2 and Fig. 2 ), indicating that the treatment processes in WWTPs have a notable effect on the remotion of these substances. In effluents, levels of estrogens E2 and EE2 ranged from < LOQ – 9.5 and 1.6–26.8 ng/L, respectively. The synthetic estrogen EE2 standing out for its frequent detection (100%) in all WWTPs effluents, which reveal its high persistence to treatment processes, which is associated with the ethinyl functional group that makes it highly resistant to biodegradation (Ting and Praveena 2017 ), this characteristic could also explain its frequent detection in the effluents of WWTPs around the world (Manickum and John 2014 ; Belhaj et al. 2016 ; Jiang et al. 2020 ; López-Velázquez et al. 2020 ). BPA was detected in only 25% of the samples collected in effluents, ranging in low levels from < LOQ to 3.0 ng/L; these results suggest that the conditions of all WWTPs allowed the high removal of BPA (> 96.9%). This is consistent with those reported by Villarreal-Morales et al. ( 2020 ), who reported high BPA concentrations in the influent of one WWTP in Monterrey City (5,900–16,600 ng/L), and not detected levels in the effluent; however, it is worth note that they used SPE/LC-UV technique, and likely levels of BPA in the effluents could be underestimated. For 4NP and 4TOP, the detected concentrations in the effluents ranged from < LOQ to 2.3 ng/L and < LOQ to 5.0 ng/L, respectively, and were considered low compared with those quantified in other WWTPs effluents in ranges from 1,346.7 to 7,513.5 ng/L, and 420 to 2,120 ng/L for 4NP (Bina et al. 2018 ; Jiang et al. 2020 ); and from 7.2 to 416.1 ng/L for 4TOP (De la Torre 2011 ). These authors related the levels of 4NP and 4TOP in WWTPs with the extensive use of polyethoxylated alkylphenols (active substances of detergents and surfactants) in domestic, urban and hospital clean activities. Moreover, the detected levels of these alkylphenols in the wastewater may be regulated to some extent by microbial activity in the environment by degrading the polyethoxylated alkylphenols to give rise to large amounts of 4NP and 4TOP (Lee et al. 2013 ; Santhi et al. 2015 ). Mass balance of EDCs dissolved in WWTPs The mass balance for the five EDCs in the soluble phase was determined based on the concentrations detected in the WWTPs and the volume of water treated per day (Table 1 ). The results are shown in Table 4 and it was observed that the total loading mass of the EDCs in the influents of WWTPs equals 118,687.0 mg/day and are distributed as follows: BPA (61,282.6 mg/day) > EE2 (43,559.5 mg/day) > 4TOP (8,751.4 mg/day) > E2 (3,411.2 mg/day) > 4NP (1,682.3 mg/day). In the WWTPs, 93.4% of the total mass of the EDCs was removed by treatment processes, and the remaining mass in effluents was 7,792.9 mg/day distributed as follows: EE2 (5,741.3 mg/day) > 4TOP (905.7 mg/day) > E2 (658.1 mg/day) > 4NP (283.5 mg/day) > BPA (204.3 mg/day); these results are similar to estimates by Ashfaq et al. ( 2018 ) who reported 951 mg/day of 4NP, 669 mg/day of E2, and 127 mg/day of 4NP in the effluents from nine WWTPs (China). However, the emission rate for 4NP and BPA were much lower than those estimated by Stasinakis et al. ( 2012 ) in a WWTP in Greece (~ 5×10 4 mg/day for 4NP and ~ 5×10 3 mg/day for BPA), which was associated with intense urban and industrial activities. Additionally, Fig. 3 shows the daily mass of EDCs in the effluents of the WWTPs, and it was observed that the emission rate of EDCs is directly related to the number of the population served and the volume of wastewater treated (see Table 1 ). Also, it is observed that EE2 is the major constituent (73.7%) of the dissolved EDCs in the four effluents, which are directly discharged to La Silla, Sabinal, Santa Catarina, and Pesquería rivers (Fig. 1 ), suggesting a potential health risk to exposed aquatic ecosystems and human health. Table 4 Daily mass load (mg/day) and approximate remotion of EDCs in the WWTPs. WWTP A WWTP B WWTP C WWTP D Σmass load (mg/day) E2 mass inf 3.1 685.8 1130.3 1592.1 3411.3 mass eff 18.4 0 462.8 176.9 658.1 AR (%) -493.5 100.0 59.0 88.9 EE2 mass inf 37.6 14680.2 20822.2 8019.5 43559.5 mass eff 211.5 2301.4 1135.1 2093.3 5741.3 AR (%) -462.5 84.3 94.5 73.9 BPA mass inf 90.4 52816.2 4808.5 3567.5 61282.6 mass eff 0 58.1 146.2 ND 204.3 AR (%) 100.0 99.9 96.9 100.0 4NP mass inf 4.6 674.2 1003.6 ND 1682.4 mass eff 1.5 267.3 14.6 ND 283.4 AR (%) 67.4 60.3 98.5 – 4TOP mass inf 14.6 7287.8 63.3 1385.7 8751.4 mass eff 38.3 116.2 73.1 678.1 905.7 AR (%) -162.3 98.4 -15.5 51.0 ΣEDCs in influents (mg/day) 118687.2 ΣEDCs in effluents (mg/day) 7792.8 AR = approximate remotion, ND = not detected. Based on the mass balance of EDCs in influents and effluents of the WWTPs, the approximate remotion of EDCs were estimated, and results are shown in Table 4 . The remotion values for E2 and EE2 in WWTP B, C, and D, ranged between 59–100% (E2), and 73.9–94.5% (EE2), these values were higher than those reported by Jiang et al. ( 2020 ) from 6.3 to 29.64% for E2, and from − 57.6 to 18.51% for EE2. In the case of BPA, the four WWTPs showed high remotion values, between 96.9 and 100% (Table 4 ), which agrees well with those observed by Ben et al. ( 2018 ) in 14 WWTPs from China. In addition, the remotion of 4NP ranged from 60.3 to 98.5% in WWTP A, B, and C; and for 4TOP, the remotion was 98.4 and 51.0% in WWTP B and D, respectively. These results agree with those reported by Bina et al. ( 2018 ) who studied 9 WWTPs and estimated remotion values between 61.9 and 93.1% for 4NP, and between 71.5 and 99.2% for 4TOP; also, similar values were reported by Ben et al. ( 2018 ) and Jiang et al. ( 2020 ). It is worth noting that some negative values were observed for E2, EE2, and 4TOP in WWTP A (-493.5, -462.5, and − 162.3%, respectively), and this phenomenon was also observed for 4TOP in WWTP C (-15.5%). These negative values indicate that levels of these EDCs were higher in effluents than influents, and can be attributed to the likely transformation of conjugated estrogens to their active forms, and the biodegradation of polyethoxylated alkylphenols to give rise to metabolites such as 4TOP by the action of the microbial consortia in the WWTPs, which increase their concentration in the effluents, and it is consistent with that described by Yu et al. ( 2013 ) and Zuo et al. ( 2006 ). Risk assessment The occurrence of EDCs caused for the discharge of treated and untreated wastewater may represent a potential ecological risk to both aquatic species and humans. Therefore, the risk quotients (RQ) were calculated from the influent and effluent data of the four WWTPs using the MEC values, and the PNEC values for each EDC were taken from the scientific literature. The results are shown in Table 5 and Fig. 4 , and it is observed that the highest RQ values for E2, EE2, and BPA were 78.1, 17,442.8 and 10.4, indicating that the untreated wastewater represent a high risk for aquatic species. While, the highest RQ values for 4NP and 4TOP in untreated wastewater were 0.2 and 0.5, suggesting a medium risk for exposed species. Likewise, the treated water in WWTPs effluents were also considered as a high risk for aquatic organisms, mainly attributed to the abundance of E2 (RQ = 49.1) and EE2 (RQ = 1,165.2), which are considered as potent endocrine disruptors due to their high estrogenic potential, even at trace levels such as pg/L (European Commission 2012; Brion et al. 2019 ). In addition, as can be seen in Fig. 4 , BPA, 4NP, and 4TOP represent a low risk in WWTPs effluents (RQs < 0.1 for each); however, this was not significant because they constitute a minimal part of the remaining EDCs in the effluents (Fig. 3 ). Finally, the possible ecological risk was estimated for the receiving waterbodies impacted by the effluents of WWTPs (Fig. 4 ), and results suggest that the organisms in these aquatic ecosystems may be exposed to high risk, attributed to the abundance of remaining E2 (RQ = 4.9) and EE2 (RQ = 116.5) in the effluents of WWTPs (Fig. 3 ). Table 5 HC5 values for the protection of 95% of the species, risk quotient (RQ) calculated from maximum EDCs levels detected in the four WWTPs. EDCs HC5 (ng/L) PNEC (ng/L) RQ = MEC/PNEC Influents Effluents Surface water d E2 0.58 a 0.19 78.1 High risk 49.1 High risk 4.9 High risk EE2 0.07 b 0.023 17442.8 High risk 1165.2 High risk 116.5 High risk BPA 129 a 43.00 10.4 High risk 0.07 Low risk 0.007 Low risk 4NP 280 a 93.33 0.2 Medium risk 0.02 Low risk 0.002 Low risk 4TOP 360 c 120.00 0.5 Medium risk 0.04 Low risk 0.004 Low risk a (Huang et al. 2019 ), b (Brion et al. 2019 ), c (Tamis and Jongbloed 2019 ), d Dilution of 10 times was assumed in receiving waterbody. Additionally, in the worst-case scenario, the results obtained in this study could underestimate the potential ecological risk related to EDCs since in this study only two sampling campaigns were carried out. Moreover, the suspended phase of EDCs in the WWTPs and the fraction of untreated wastewater directly discharged to the environment were not considered. In addition, the emission of pollutants such as EDCs may be a function of population consumption and excretion rates, as well as urban and industrial activities which vary over time. Also, in the environment, EDCs are regulated to some extent by environmental factors such as temperature, precipitation, solar radiation, microbial activity, among others. Conclusions This study revealed that EE2 and BPA were the most frequently detected EDCs in the influents of WWTPs, likely associated to the extensive use of EE2 as a contraceptive method and the use of BPA as a plasticizer in industrial activities. In addition, the detected levels of 4NP and 4TOP suggest their moderate use in urban activities in Monterrey City. Furthermore, EE2 was detected in all WWTP effluents ranging from 1.6 to 26.8 ng/L being the most recalcitrant compound in the treatment processes. Also, the mass balance in the dissolved phase revealed that the WWTP effluents constitute critical sources of EDCs emission to the environment, despite that these compounds present high remotion percentages in some WWTPs. Moreover, through the RQ values, it was estimated that the wastewater in influents and effluents of the studied WWTPs represent a high risk to exposed aquatic species, due to the abundance of dissolved E2 and EE2. Also, a preliminary assessment of the risk quotient in receiving water bodies indicated a potential environmental risk for La Silla, Santa Catarina, Sabinal, Topo Chico, and Pesqueria rivers. However, ecotoxicological studies and extensive monitoring are needed to protect the biodiversity of these aquatic environments. Additionally, it is necessary pay more attention to the possible public health risk associated with the occurrence of EDCs in WWTPs in densely populated and industrialized zones such as Monterrey City. Declarations Acknowledgements The authors thanks to Facultad de Ciencias Químicas, Universidad Autónoma de Nuevo León; Centro de Investigaciones Químicas, Universidad Autónoma del Estado de Morelos, and Servicios de Agua y Drenaje de Monterrey. López-Velázquez acknowledges the scholarship from Consejo Nacional de Ciencia y Tecnología (CONACyT-México, 736037). Special thanks to Ph.D. Yunuén Canedo López and MSc. David Herrera López for their valuable comments on the manuscript. Funding This work was supported by the Facultad de Ciencias Químicas, Universidad Autónoma de Nuevo León and PAICyT-UANL (CE868- 19). Ethics approval and consent to participate Not applicable. Consent for publication Not applicable. Availability of data and materials Not applicable Competing interests The authors declare no competing interests Author contribution KLV: Investigation, conceptualization, writing and original draft. JLGM: Supervision, resources, writing-review and editing. 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Occurrence and photochemical degradation of 17 a -ethinylestradiol in Acushnet River Estuary. 63:1583–1590. doi:10.1016/j.chemosphere.2005.08.063. Cite Share Download PDF Status: Under Review Version 1 posted Reviews received at journal 20 Sep, 2021 Reviewers invited by journal 03 Aug, 2021 Editor invited by journal 30 Jul, 2021 Editor assigned by journal 16 Jul, 2021 First submitted to journal 11 Jul, 2021 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. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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-708615\",\"acceptedTermsAndConditions\":true,\"allowDirectSubmit\":false,\"archivedVersions\":[],\"articleType\":\"Research Article\",\"associatedPublications\":[],\"authors\":[{\"id\":43823319,\"identity\":\"20babc5e-967e-4087-bcf3-763f396a4e54\",\"order_by\":0,\"name\":\"Khirbet López-Velázquez\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Universidad Autonoma de Nuevo Leon\",\"correspondingAuthor\":false,\"submittingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Khirbet\",\"middleName\":\"\",\"lastName\":\"López-Velázquez\",\"suffix\":\"\"},{\"id\":43823320,\"identity\":\"6244a53d-793a-4046-96a9-f9b93b27a367\",\"order_by\":1,\"name\":\"Jorge L. 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Murillo-Tovar\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Universidad Autonoma del Estado de Morelos\",\"correspondingAuthor\":false,\"submittingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Mario\",\"middleName\":\"A.\",\"lastName\":\"Murillo-Tovar\",\"suffix\":\"\"},{\"id\":43823323,\"identity\":\"e82f9efe-9c11-4437-9bb5-d07f0e64de31\",\"order_by\":4,\"name\":\"Minerva Villanueva-Rodríguez\",\"email\":\"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABPUlEQVRIie2RPUvDQBjHn+MgXVqzJojtJxASAimlvnwQF0ugmbpKi0KvBM5JMgeqnyFT0a3hAbMkdhYXi9DJgo5FBC/Fal9iZ4f7wR0P3P2eP/ccgETyH6E/Be0NF7UGbbEXxCpuVQhbUpLvozzll2WF8L+V/ctS9NLhR2DEQpndYtmI0/FT5wYrVQrkecrhxBiuKDbuOGbKHTCQsOgqQctIXKuWDtC884Ca1xxaAVtTirbOEgq6J1JKHBsBayp6b4AkRFB2S0LxYV2pzljSnSvRJ8du4E+E0sdjoRQ+MoVvKDZhbQRVTAxFyqmqZSkMG1kKzU+xdNaOi3Nlj7umr01ojd27TojE0/sP2sZbRon5zozzsqJiNJ7yekVRm+SRXdQPw9iL3l7PDlrh6sQW5H4ZydprufclEolEspUv/9tzeuF2w4kAAAAASUVORK5CYII=\",\"orcid\":\"https://orcid.org/0000-0001-7481-2499\",\"institution\":\"Universidad Autonoma de Nuevo Leon\",\"correspondingAuthor\":true,\"submittingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Minerva\",\"middleName\":\"\",\"lastName\":\"Villanueva-Rodríguez\",\"suffix\":\"\"}],\"badges\":[],\"createdAt\":\"2021-07-11 23:22:42\",\"currentVersionCode\":1,\"declarations\":\"\",\"doi\":\"10.21203/rs.3.rs-708615/v1\",\"doiUrl\":\"https://doi.org/10.21203/rs.3.rs-708615/v1\",\"draftVersion\":[],\"editorialEvents\":[],\"editorialNote\":\"\",\"failedWorkflow\":false,\"files\":[{\"id\":12190694,\"identity\":\"f2dbd273-aa6e-47d3-9954-412ec0528fa5\",\"added_by\":\"auto\",\"created_at\":\"2021-08-06 19:14:40\",\"extension\":\"jpeg\",\"order_by\":1,\"title\":\"Figure 1\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":274135,\"visible\":true,\"origin\":\"\",\"legend\":\"Map showing the location of the Monterrey City, and the four studied WWTPs, as well as the main receiving waterbodies.\",\"description\":\"\",\"filename\":\"floatimage1.jpeg\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-708615/v1/23b2b21858ab2d1dc613deac.jpeg\"},{\"id\":12190696,\"identity\":\"0d3cd790-15db-4638-b47e-dc1c735717e7\",\"added_by\":\"auto\",\"created_at\":\"2021-08-06 19:14:40\",\"extension\":\"jpeg\",\"order_by\":2,\"title\":\"Figure 2\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":77686,\"visible\":true,\"origin\":\"\",\"legend\":\"Concentration ranges of five EDCs detected in four WWTPs of Monterrey City.\",\"description\":\"\",\"filename\":\"floatimage2.jpeg\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-708615/v1/bfe7effa7eeec5921e61039d.jpeg\"},{\"id\":12190697,\"identity\":\"9fa3e783-ba43-46c2-9760-451b4803aa91\",\"added_by\":\"auto\",\"created_at\":\"2021-08-06 19:14:41\",\"extension\":\"jpeg\",\"order_by\":3,\"title\":\"Figure 3\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":105515,\"visible\":true,\"origin\":\"\",\"legend\":\"Daily mass load of selected EDCs in effluents of four WWTPs in Monterrey City.\",\"description\":\"\",\"filename\":\"floatimage3.jpeg\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-708615/v1/0d0598dd6b0cb4bb08012041.jpeg\"},{\"id\":12190825,\"identity\":\"4488ce5b-6c2c-4d32-afa9-cb2da951cb9b\",\"added_by\":\"auto\",\"created_at\":\"2021-08-06 19:17:41\",\"extension\":\"jpeg\",\"order_by\":4,\"title\":\"Figure 4\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":104164,\"visible\":true,\"origin\":\"\",\"legend\":\"Risk quotient values calculated from EDCs levels detected in four WWTPs. *Dilution of 10 times was assumed for surface water.\",\"description\":\"\",\"filename\":\"floatimage4.jpeg\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-708615/v1/49622d693b33024da906947f.jpeg\"},{\"id\":13707800,\"identity\":\"20c16a57-0990-458c-8995-d39a0c529043\",\"added_by\":\"auto\",\"created_at\":\"2021-09-17 14:04:48\",\"extension\":\"pdf\",\"order_by\":0,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"manuscript-pdf\",\"size\":703921,\"visible\":true,\"origin\":\"\",\"legend\":\"\",\"description\":\"\",\"filename\":\"manuscript.pdf\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-708615/v1/92a8a23a-6e7d-458a-bfe9-4afd6a95888a.pdf\"}],\"financialInterests\":\"\",\"formattedTitle\":\"\\u003cp\\u003eEcological Risk Assessment of Five Endocrine-Disrupting Compounds in Wastewater Treatment Plants from Monterrey, Mexico\\u003c/p\\u003e\",\"fulltext\":[{\"header\":\"Introduction\",\"content\":\"\\u003cp\\u003eEndocrine-disrupting compounds (EDCs) belong to a subclass of so-called emerging organic pollutants and their presence in the environment represents a potential risk to public health (Sauv\\u0026eacute; and Desrosiers \\u003cspan citationid=\\\"CR42\\\" class=\\\"CitationRef\\\"\\u003e2014\\u003c/span\\u003e). According to the United States Environmental Protection Agency (USEPA) and the European Chemicals Agency (ECHA), EDCs are exogenous substances or a mixture of substances that alter the structure or function(s) of the endocrine system and cause adverse effects at the level of the organism, its progeny, populations or subpopulations of organisms (EPA \\u003cspan citationid=\\\"CR15\\\" class=\\\"CitationRef\\\"\\u003e1998\\u003c/span\\u003e; ECHA and EFSA 2018). These compounds are widely distributed in the environment, mainly in aquatic ecosystems, and have attracted special attention due to their potential risk to the health of aquatic organisms and humans, even at very low concentrations such as ng/L (Adeel et al. \\u003cspan citationid=\\\"CR1\\\" class=\\\"CitationRef\\\"\\u003e2017\\u003c/span\\u003e). Several studies have reported that EDCs may generate different adverse effects on exposed organisms, including feminization and masculinization, deficiencies in the sexual, prostate, brain, and immune development, gonadal atrophy, infertility, precocious puberty, and different types of cancer (prostate, testicles, breast, ovaries, among others) (Roby \\u003cspan citationid=\\\"CR38\\\" class=\\\"CitationRef\\\"\\u003e2013\\u003c/span\\u003e; Kabir et al. \\u003cspan citationid=\\\"CR30\\\" class=\\\"CitationRef\\\"\\u003e2015\\u003c/span\\u003e; Wang et al. \\u003cspan citationid=\\\"CR48\\\" class=\\\"CitationRef\\\"\\u003e2019\\u003c/span\\u003e; Jackson and Klerks \\u003cspan citationid=\\\"CR28\\\" class=\\\"CitationRef\\\"\\u003e2020\\u003c/span\\u003e). Moreover, it has been reported that EDCs may be associated with a high incidence of obesity and the development of diseases such as diabetes in humans (Hatch et al. \\u003cspan citationid=\\\"CR23\\\" class=\\\"CitationRef\\\"\\u003e2010\\u003c/span\\u003e).\\u003c/p\\u003e \\u003cp\\u003eAmong the different EDCs, the estrogens E2 and EE2, the alkylphenols 4NP and 4TOP, as well as the plasticizer BPA, are the most frequently EDCs detected in various aquatic environments such as rivers, lakes, and coastal areas (Ronderos-Lara et al. \\u003cspan citationid=\\\"CR39\\\" class=\\\"CitationRef\\\"\\u003e2018\\u003c/span\\u003e; Calder\\u0026oacute;n-Moreno et al. \\u003cspan citationid=\\\"CR7\\\" class=\\\"CitationRef\\\"\\u003e2019\\u003c/span\\u003e; Inam et al. \\u003cspan citationid=\\\"CR26\\\" class=\\\"CitationRef\\\"\\u003e2019\\u003c/span\\u003e; Salgueiro-Gonz\\u0026aacute;lez et al. \\u003cspan citationid=\\\"CR40\\\" class=\\\"CitationRef\\\"\\u003e2019\\u003c/span\\u003e; Jiang et al. \\u003cspan citationid=\\\"CR29\\\" class=\\\"CitationRef\\\"\\u003e2020\\u003c/span\\u003e; Čelić et al. \\u003cspan citationid=\\\"CR9\\\" class=\\\"CitationRef\\\"\\u003e2020\\u003c/span\\u003e); due to their high estrogenic potential, these substances are being regulated by the European legislation through the European Water Framework Directive (2000/60/EC). In this sense, 2.0 \\u0026micro;g/L has been defined as the maximum admissible concentration for 4NP and 4TOP in surface water (European Parliament 2008). In addition, BPA and E2 were recently proposed for inclusion as priority hazardous substances, recommending 0.01 \\u0026micro;g/L and 0.001 \\u0026micro;g/L as the maximum allowable concentration in surface water, respectively (European Parliament \\u003cspan citationid=\\\"CR22\\\" class=\\\"CitationRef\\\"\\u003e2018\\u003c/span\\u003e). Regarding EE2, has been included in the watch list to monitor it and evaluate its possible incorporation as a priority hazardous substance for human health (European Parliament 2013).\\u003c/p\\u003e \\u003cp\\u003eIn another way, it is known that effluents from WWTPs are one of the main sources of EDCs emissions to aquatic environments, and several studies have reported the detection of EDCs in WWTP effluents around the world, revealing that these substances are partially removed during wastewater treatment processes (Manickum and John \\u003cspan citationid=\\\"CR35\\\" class=\\\"CitationRef\\\"\\u003e2014\\u003c/span\\u003e; Wee et al. \\u003cspan citationid=\\\"CR49\\\" class=\\\"CitationRef\\\"\\u003e2019\\u003c/span\\u003e; Jiang et al. \\u003cspan citationid=\\\"CR29\\\" class=\\\"CitationRef\\\"\\u003e2020\\u003c/span\\u003e; Čelić et al. \\u003cspan citationid=\\\"CR9\\\" class=\\\"CitationRef\\\"\\u003e2020\\u003c/span\\u003e). For example, Jiang et al. (\\u003cspan citationid=\\\"CR29\\\" class=\\\"CitationRef\\\"\\u003e2020\\u003c/span\\u003e) detected E2 (\\u0026lt;\\u0026thinsp;LOQ \\u0026minus;\\u0026thinsp;50.03 ng/L) and EE2 (4.72\\u0026ndash;35.03 ng/L) in effluents from 38 WWTPs in China. Similarly, Manickum and John (\\u003cspan citationid=\\\"CR35\\\" class=\\\"CitationRef\\\"\\u003e2014\\u003c/span\\u003e) reported the detection of E2 (4.0\\u0026ndash;107.0 ng/L) and EE2 (1.0\\u0026ndash;8.0 ng/L) in the effluent of a WWTP in South Africa. On the other hand, BPA (3.31 ng/L), 4NP (4.62 ng/L), and 4TOP (4.44 ng/L) were detected in a WWTP effluent in Portugal (Carvalho et al. \\u003cspan citationid=\\\"CR8\\\" class=\\\"CitationRef\\\"\\u003e2016\\u003c/span\\u003e). Furthermore, 4NP (420\\u0026ndash;2120 ng/L) and 4TOP (5.3\\u0026ndash;54.8 ng/L) were detected in effluents of nine WWTPs in Iran (Bina et al. \\u003cspan citationid=\\\"CR5\\\" class=\\\"CitationRef\\\"\\u003e2018\\u003c/span\\u003e). Therefore, the incomplete removal of EDCs in WWTPs contributes to their frequent detection in surface water, which may subsequently impact on the essential activities such as agriculture, livestock, fisheries, drinking water, and domestic and recreational activities (Čelić et al. \\u003cspan citationid=\\\"CR9\\\" class=\\\"CitationRef\\\"\\u003e2020\\u003c/span\\u003e).\\u003c/p\\u003e \\u003cp\\u003eIn Mexico, some studies have reported the detection of E2, EE2, and BPA in several WWTPs in a wide concentration range from \\u0026lt;\\u0026thinsp;LOD \\u0026ndash; 16,600 ng/L (D\\u0026iacute;az-Torres et al. \\u003cspan citationid=\\\"CR12\\\" class=\\\"CitationRef\\\"\\u003e2013\\u003c/span\\u003e; Estrada-Arriaga et al. \\u003cspan citationid=\\\"CR17\\\" class=\\\"CitationRef\\\"\\u003e2016\\u003c/span\\u003e; L\\u0026oacute;pez-Vel\\u0026aacute;zquez et al. \\u003cspan citationid=\\\"CR34\\\" class=\\\"CitationRef\\\"\\u003e2020\\u003c/span\\u003e; Villarreal-Morales et al. \\u003cspan citationid=\\\"CR47\\\" class=\\\"CitationRef\\\"\\u003e2020\\u003c/span\\u003e). Likewise, other authors such as Calder\\u0026oacute;n-Moreno et al. (\\u003cspan citationid=\\\"CR7\\\" class=\\\"CitationRef\\\"\\u003e2019\\u003c/span\\u003e), and Ronderos-Lara et al. (\\u003cspan citationid=\\\"CR39\\\" class=\\\"CitationRef\\\"\\u003e2018\\u003c/span\\u003e) detected E2, EE2, BPA, 4NP and 4TOP in river water (Morelos, Mexico) at levels from \\u0026lt;\\u0026thinsp;LOD \\u0026ndash; 624.3 ng/L, emphasizing EE2 and BPA as the most abundant EDCs.\\u003c/p\\u003e \\u003cp\\u003eIn particular, the study of EDCs in Monterrey city is of great interest due to it is the second most populated region in Mexico (5,341,171 inhabitants; INEGI \\u003cspan citationid=\\\"CR27\\\" class=\\\"CitationRef\\\"\\u003e2021\\u003c/span\\u003e), and stands out as one of the most industrialized zone in the country (SEDATU \\u003cspan citationid=\\\"CR43\\\" class=\\\"CitationRef\\\"\\u003e2015\\u003c/span\\u003e) contributing with the emission of a large number of pollutants into the environment, including some EDCs as was informed by Cruz-L\\u0026oacute;pez et al. (\\u003cspan citationid=\\\"CR11\\\" class=\\\"CitationRef\\\"\\u003e2020\\u003c/span\\u003e), and Villarreal-Morales et al. (\\u003cspan citationid=\\\"CR47\\\" class=\\\"CitationRef\\\"\\u003e2020\\u003c/span\\u003e). Moreover, is of great interest to evaluate the ecological risk on the aquatic systems due to their high estrogenic potential and the continuous emission of EDCs towards the environment, which may impact directly on the ecosystems of the receiving water bodies such as the urban rivers Pesqueria, Santa Catarina, La Silla, Sabinal, and Topo Chico (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e),which are tributaries to the Rio San Juan that flows into the Rio Bravo (natural border between Mexico and United States) and the Gulf of Mexico.\\u003c/p\\u003e \\u003cp\\u003eRecently, some studies have been focused on evaluating the potential environmental risk through hazard index associated with E2, EE2, BPA, 4NP, and 4TOP in the dissolved phase of surface water (Stasinakis et al. \\u003cspan citationid=\\\"CR44\\\" class=\\\"CitationRef\\\"\\u003e2012\\u003c/span\\u003e; Peng et al. \\u003cspan citationid=\\\"CR37\\\" class=\\\"CitationRef\\\"\\u003e2017\\u003c/span\\u003e; Calder\\u0026oacute;n-Moreno et al. \\u003cspan citationid=\\\"CR7\\\" class=\\\"CitationRef\\\"\\u003e2019\\u003c/span\\u003e) as well as influents and effluents of WWTPs (Yu et al. \\u003cspan citationid=\\\"CR50\\\" class=\\\"CitationRef\\\"\\u003e2013\\u003c/span\\u003e; Manickum and John \\u003cspan citationid=\\\"CR35\\\" class=\\\"CitationRef\\\"\\u003e2014\\u003c/span\\u003e; Patrolecco et al. \\u003cspan citationid=\\\"CR36\\\" class=\\\"CitationRef\\\"\\u003e2015\\u003c/span\\u003e; Ben et al. \\u003cspan citationid=\\\"CR4\\\" class=\\\"CitationRef\\\"\\u003e2018\\u003c/span\\u003e; Jiang et al. \\u003cspan citationid=\\\"CR29\\\" class=\\\"CitationRef\\\"\\u003e2020\\u003c/span\\u003e). In these studies, the risk quotients (RQ) have been calculated for several aquatic organisms (i.e. algae, crustaceans, and fish), and it is considered a useful strategy for the evaluation of water resources, which could contribute to improve the wastewater treatment processess, implementing effective strategies of management and control of wastewater discharges, surface, and drinking water, for the health protection of human and aquatic organisms (Xu et al. 2016). Therefore, this study aims to determine the potential environmental risks associated with five dissolved EDCs in four WWTPs from Monterrey City, which to our knowledge, constitutes the first report of this type in WWTPs from Mexico.\\u003c/p\\u003e\"},{\"header\":\"Materials And Methods\",\"content\":\"\\u003cdiv class=\\\"Section2\\\" id=\\\"Sec3\\\"\\u003e\\n \\u003ch2\\u003eChemical and reagents\\u003c/h2\\u003e\\n \\u003cp\\u003e17\\u0026beta;-estradiol (\\u0026ge;\\u0026thinsp;98.0%), 17\\u0026alpha;-ethinylestradiol (\\u0026ge;\\u0026thinsp;98.0%), bisphenol A (\\u0026ge;\\u0026thinsp;99.0%), 4-nonylphenol (\\u0026ge;\\u0026thinsp;99.0%), 4-tert-octylphenol (\\u0026ge;\\u0026thinsp;99.0%), chrysene-d12 (\\u0026ge;\\u0026thinsp;99.0%), N,O-bis(trimethylsilyl)trifluoroacetamide\\u0026thinsp;+\\u0026thinsp;trimethylchlorosilane (BSTFA\\u0026thinsp;+\\u0026thinsp;TMCS, 99:1), pyridine (\\u0026ge;\\u0026thinsp;99.0%), hexane, methanol and dichloromethane HPLC grade were purchased from Sigma-Aldrich (St. Louis, MO, USA). Water HPLC grade was acquired from Tedia Company, and acetone HPLC grade was acquired from Meyer. The Oasis HLB solid-phase extraction cartridges (500 mg, 6 mL) were purchased from Waters (Milford, USA).\\u003c/p\\u003e\\n \\u003cp\\u003eStandard stock solutions (1000 \\u0026micro;g/mL) of individual EDCs and Chrysene-d12 used as internal standard (1500 \\u0026micro;g/mL) were prepared in acetone. These solutions were stored in amber vials at 4\\u0026deg;C until use.\\u003c/p\\u003e\\n\\u003c/div\\u003e\\n\\u003cdiv class=\\\"Section2\\\" id=\\\"Sec4\\\"\\u003e\\n \\u003ch2\\u003eSample collection and instrumental analysis\\u003c/h2\\u003e\\n \\u003cp\\u003eIn this work, four WWTPs that receive urban and industrial wastewater were studied, the geographical location of WWTPs is shown in Fig. \\u003cspan class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e, and detailed information of each WWTP and the main quality parameters of the wastewater samples were included in Table \\u003cspan class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e.\\u003c/p\\u003e\\n \\u003cdiv class=\\\"gridtable\\\"\\u003e\\u0026nbsp;\\u003ctable border=\\\"1\\\" id=\\\"Tab1\\\"\\u003e\\n \\u003ccaption\\u003e\\n \\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 1\\u003c/div\\u003e\\n \\u003cdiv class=\\\"CaptionContent\\\"\\u003e\\n \\u003cp\\u003eMain characteristics of the studied WWTPs and wastewater samples.\\u003c/p\\u003e\\n \\u003c/div\\u003e\\n \\u003c/caption\\u003e\\n \\u003ctbody\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" rowspan=\\\"2\\\"\\u003e\\n \\u003cp\\u003eWWTP\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" rowspan=\\\"2\\\"\\u003e\\n \\u003cp\\u003eCapacity (m\\u003csup\\u003e3\\u003c/sup\\u003e/day)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" rowspan=\\\"2\\\"\\u003e\\n \\u003cp\\u003ePopulation served\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" rowspan=\\\"2\\\"\\u003e\\n \\u003cp\\u003eAverage discharge (m\\u003csup\\u003e3\\u003c/sup\\u003e/day)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colspan=\\\"7\\\"\\u003e\\n \\u003cp\\u003ePhysicochemical characteristics of the wastewater samples\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eStage\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eT (\\u0026deg;C)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003epH\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eDO (mg/L)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eTSS (mg/L)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eCOD (mg/L)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eBOD\\u003csub\\u003e5\\u003c/sub\\u003e (mg/L)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" rowspan=\\\"2\\\"\\u003e\\n \\u003cp\\u003eA\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" rowspan=\\\"2\\\"\\u003e\\n \\u003cp\\u003e17280\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" rowspan=\\\"2\\\"\\u003e\\n \\u003cp\\u003e377480\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" rowspan=\\\"2\\\"\\u003e\\n \\u003cp\\u003e15322.5\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eI\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e24.3\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e7.4\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e1.9\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e267.7\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e593.7\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e218.9\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eE\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e24.1\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e7.1\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e7.2\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e17.3\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e57.5\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e13.9\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" rowspan=\\\"2\\\"\\u003e\\n \\u003cp\\u003eB\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" rowspan=\\\"2\\\"\\u003e\\n \\u003cp\\u003e345600\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" rowspan=\\\"2\\\"\\u003e\\n \\u003cp\\u003e1931229\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" rowspan=\\\"2\\\"\\u003e\\n \\u003cp\\u003e232465.6\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eI\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e22.9\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e7.2\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e3.0\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e385.3\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e660.7\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e255.6\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eE\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e25.9\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e7.2\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e6.0\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e21.3\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e54.0\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e14.3\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" rowspan=\\\"2\\\"\\u003e\\n \\u003cp\\u003eC\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" rowspan=\\\"2\\\"\\u003e\\n \\u003cp\\u003e162000\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" rowspan=\\\"2\\\"\\u003e\\n \\u003cp\\u003e444006\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" rowspan=\\\"2\\\"\\u003e\\n \\u003cp\\u003e97436.5\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eI\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e23.6\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e7.1\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e1.7\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e257.7\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e607.2\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e209.9\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eE\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e24.4\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e7.3\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e6.0\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e17.0\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e62.3\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e8.2\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" rowspan=\\\"2\\\"\\u003e\\n \\u003cp\\u003eD\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" rowspan=\\\"2\\\"\\u003e\\n \\u003cp\\u003e648000\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" rowspan=\\\"2\\\"\\u003e\\n \\u003cp\\u003e796337\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" rowspan=\\\"2\\\"\\u003e\\n \\u003cp\\u003e589671.4\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eI\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e22.8\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e7.4\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e1.9\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e286.4\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e726.2\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e230.2\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eE\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e24.2\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e7.2\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e6.6\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e23.2\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e57.1\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e12.4\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003c/tbody\\u003e\\n \\u003ctfoot\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd colspan=\\\"11\\\"\\u003eI, influent: E, effluent; DO, dissolved oxygen; TSS, total suspended solids; COD, chemical oxygen demand; BOD\\u003csub\\u003e5\\u003c/sub\\u003e, biological oxygen demand at the five days.\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003c/tfoot\\u003e\\n \\u003c/table\\u003e\\n \\u003c/div\\u003e\\n \\u003cp\\u003eTwo sampling campaings were carried out in January and August 2019, and composite wastewater samples were collected in influents and disinfected effluents of each WWTP (2 L, made up of three simple samples). The samples were stored in amber glass bottles, transported at 4\\u0026deg;C, and preserved at -20\\u0026deg;C until their analysis, according to Method 1698 from the USEPA (\\u003cspan class=\\\"CitationRef\\\"\\u003e2007\\u003c/span\\u003e). Subsequently, the solid-phase extraction and gas chromatography coupled to the mass spectrometer (SPE/GC-MS) were employed for the EDCs analysis as was described in previous work (L\\u0026oacute;pez-Vel\\u0026aacute;zquez et al. \\u003cspan class=\\\"CitationRef\\\"\\u003e2021\\u003c/span\\u003e) and strict quality control procedures were adopted. Briefly, based on the internal standard method, good correlation coefficients (R\\u003csup\\u003e2\\u003c/sup\\u003e\\u0026thinsp;\\u0026gt;\\u0026thinsp;0.982) were obtained for all EDCs; limits of detection (LOD) ranged from 0.21 ng/L (E2) to 1.1 ng/L (EE2) and limits of quantification (LOQ) ranged from 0.71 ng/L (E2) to 3.01 ng/L (EE2). The precision of the method (expressed as relative standard deviation) was \\u0026lt;\\u0026thinsp;4.9% at 25 ng/L, and \\u0026lt;\\u0026thinsp;6.4% at 230 ng/L for each EDC in both concentration levels. Moreover, recoveries of EDCs ranged from 74.6% (EE2) to 103.4% (BPA), and all instrumental and procedural blanks were below LOD.\\u003c/p\\u003e\\n\\u003c/div\\u003e\\n\\u003cdiv class=\\\"Section2\\\" id=\\\"Sec5\\\"\\u003e\\n \\u003ch2\\u003eData analysis\\u003c/h2\\u003e\\n \\u003cdiv class=\\\"Section3\\\" id=\\\"Sec6\\\"\\u003e\\n \\u003ch2\\u003eDaily mass\\u003c/h2\\u003e\\n \\u003cp\\u003eUsing data of EDCs levels detected in the WWTPs, the daily mass of each EDC in the influents and effluents (Mass\\u003csub\\u003einf or eff\\u003c/sub\\u003e) was calculated by Eq. 1.\\u003c/p\\u003e\\n \\u003cp\\u003e\\u003cimg src=\\\"data:image/png;base64,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\\\"\\u003e\\u003c/p\\u003e\\n \\u003cp\\u003eWhere C\\u003csub\\u003einf\\u003c/sub\\u003e and C\\u003csub\\u003eeff\\u003c/sub\\u003e are the concentrations of the selected EDCs in the influents and effluents of the WWTPs (mg/m\\u003csup\\u003e3\\u003c/sup\\u003e). Q\\u003csub\\u003ewater\\u003c/sub\\u003e is the daily wastewater flow in each WWTP (m\\u003csup\\u003e3\\u003c/sup\\u003e/day) which were considered equals in influents and effluents since the loss of wastewater during the treatments and the effect of the dilution by rainfall was considered small and negligible in the sampling dates (20\\u0026ndash;30 mm/month; CONAGUA \\u003cspan class=\\\"CitationRef\\\"\\u003e2019\\u003c/span\\u003e). Moreover, the approximate remotion (AR) for each EDC were estimated following Eq. 2:\\u003c/p\\u003e\\n \\u003cp\\u003e\\u003cimg src=\\\"data:image/png;base64,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\\\"\\u003e\\u003c/p\\u003e\\n \\u003cp\\u003e\\u003cbr\\u003e\\u003c/p\\u003e\\n \\u003c/div\\u003e\\n \\u003cdiv class=\\\"Section3\\\" id=\\\"Sec7\\\"\\u003e\\n \\u003ch2\\u003eEcological risk assessment\\u003c/h2\\u003e\\n \\u003cp\\u003eIn this study, the potential environmental risk of the EDCs detected in the WWTPs was assessed employing the risk quotients (RQ), which is an internationally accepted parameter for environmental risk assessment (European Commission \\u003cspan class=\\\"CitationRef\\\"\\u003e2003\\u003c/span\\u003e; EMEA \\u003cspan class=\\\"CitationRef\\\"\\u003e2006\\u003c/span\\u003e). RQ values were calculated as follows (Eq. 3):\\u003c/p\\u003e\\n \\u003cp\\u003e\\u003cimg src=\\\"data:image/png;base64,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\\\"\\u003e\\u003c/p\\u003e\\n \\u003cp\\u003eWhere MEC is the measured concentration in influents and effluents of WWTPs (ng/L), and PNEC is the predicted no-effect concentration. PNEC values for each EDCs in wastewater were calculated by Eq. 4:\\u0026nbsp;\\u003c/p\\u003e\\n \\u003cdiv class=\\\"gridtable\\\"\\u003e\\u0026nbsp;\\u003cimg src=\\\"data:image/png;base64,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\\\"\\u003e\\u003c/div\\u003e\\n \\u003cp\\u003eWhere HC5 is the hazardous concentration for 5% of the exposed species, and AF is the assessment factor which was set to 3 in order to protect other more sensitive organisms no considered in the toxicological studies (Tamis and Jongbloed \\u003cspan class=\\\"CitationRef\\\"\\u003e2019\\u003c/span\\u003e). HC5 values for E2, EE2, BPA, 4NP, and 4TOP were taken from scientific literature and are shown in Table\\u0026nbsp;\\u003cspan class=\\\"InternalRef\\\"\\u003e5\\u003c/span\\u003e. Further, the criteria for establishing the potential ecological risk were the following: RQ\\u0026thinsp;\\u0026ge;\\u0026thinsp;1, high risk; 0.1\\u0026thinsp;\\u0026le;\\u0026thinsp;RQ\\u0026thinsp;\\u0026le;\\u0026thinsp;1, medium risk, and RQ\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.1, low risk (Huang et al. \\u003cspan class=\\\"CitationRef\\\"\\u003e2018\\u003c/span\\u003e). In addition, regarding RQs for surface water, a dilution factor of 10 was used for MEC values (Jiang et al. \\u003cspan class=\\\"CitationRef\\\"\\u003e2020\\u003c/span\\u003e), assuming that effluents of WWTP would be diluted after being discharged.\\u003c/p\\u003e\\n \\u003c/div\\u003e\\n\\u003c/div\\u003e\"},{\"header\":\"Results And Discussion\",\"content\":\"\\u003cdiv id=\\\"Sec9\\\" class=\\\"Section2\\\"\\u003e\\n\\u003ch2\\u003eConcentrations of EDCs in influents\\u003c/h2\\u003e\\n\\u003cp\\u003eThe frequency of detection of the five EDCs in the influents was variable, ranging from 62.5% (4NP) to 100% (EE2) as shown in Table\\u0026nbsp;\\u003cspan class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003e. Notably, EE2 was detected in all samples collected during the two sampling campaigns reaching high levels up to 407.5 ng/L (Fig.\\u0026nbsp;\\u003cspan class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003e). These EE2 levels were higher than those detected in 38 WWTPs in China, ranging from 4.96 to 51.06 ng/L (Jiang et al. \\u003cspan class=\\\"CitationRef\\\"\\u003e2020\\u003c/span\\u003e), and those detected in South Africa (one WWTP) ranging from 10 to 95 ng/L (Manickum and John \\u003cspan class=\\\"CitationRef\\\"\\u003e2014\\u003c/span\\u003e). However, EE2 concentrations are comparable to that reported by Belhaj et al. (\\u003cspan class=\\\"CitationRef\\\"\\u003e2016\\u003c/span\\u003e), who detected concentrations between 199 and 600 ng/L in the influent of one WWTP (Tunisian). Furthermore, E2 levels in influents ranged from \\u0026lt;\\u0026thinsp;LOD \\u0026ndash; 15.1 ng/L (frequency of 75%) and were lower than those detected in 38 WWTPs from China (\\u0026lt;\\u0026thinsp;LOQ \\u0026ndash; 62.92 ng/L) (Jiang et al. \\u003cspan class=\\\"CitationRef\\\"\\u003e2020\\u003c/span\\u003e), and those detected in one urban WWTP from Tunisian, between 45.0\\u0026ndash;75.0 ng/L (Belhaj et al. \\u003cspan class=\\\"CitationRef\\\"\\u003e2016\\u003c/span\\u003e). According to previous studies, it is known that the occurrence of estrogens such as E2 and EE2 is related to the extensive use of these substances as therapeutic or contraceptive agents, and their subsequent excretion mainly in urine, which is considered one of the main sources of estrogens to the environment (Manickum and John \\u003cspan class=\\\"CitationRef\\\"\\u003e2014\\u003c/span\\u003e).\\u003c/p\\u003e\\n\\u003cdiv class=\\\"gridtable\\\"\\u003e\\n\\u003ctable id=\\\"Tab2\\\" border=\\\"1\\\"\\u003e\\u003ccaption\\u003e\\n\\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 2\\u003c/div\\u003e\\n\\u003cdiv class=\\\"CaptionContent\\\"\\u003e\\n\\u003cp\\u003eConcentrations (ng/L) of selected EDCs in four WWTPs.\\u003c/p\\u003e\\n\\u003c/div\\u003e\\n\\u003c/caption\\u003e\\n\\u003cthead\\u003e\\n\\u003ctr\\u003e\\n\\u003cth align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/th\\u003e\\n\\u003cth colspan=\\\"4\\\" align=\\\"left\\\"\\u003e\\n\\u003cp\\u003eInfluents\\u003c/p\\u003e\\n\\u003c/th\\u003e\\n\\u003cth colspan=\\\"4\\\" align=\\\"left\\\"\\u003e\\n\\u003cp\\u003eEffluents\\u003c/p\\u003e\\n\\u003c/th\\u003e\\n\\u003c/tr\\u003e\\n\\u003c/thead\\u003e\\n\\u003ctbody\\u003e\\n\\u003ctr\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003eRange\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003emean\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003emedian\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003eDF\\u003csup\\u003ea\\u003c/sup\\u003e (%)\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003eRange\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003emean\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003emedian\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003eDF (%)\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003c/tr\\u003e\\n\\u003ctr\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003eE2\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e\\u0026lt;LOQ\\u003csup\\u003eb\\u003c/sup\\u003e \\u0026ndash; 15.1\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e4.3\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e2.9\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e75.0\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e\\u0026lt;LOQ \\u0026ndash; 9.5\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e1.5\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e\\u0026lt;LOQ\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e37.5\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003c/tr\\u003e\\n\\u003ctr\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003eEE2\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e\\u0026lt;LOQ\\u003csup\\u003ec\\u003c/sup\\u003e \\u0026ndash; 407.5\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e73.2\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e14.2\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e100\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e1.6\\u0026ndash;26.8\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e9.7\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e7.4\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e100\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003c/tr\\u003e\\n\\u003ctr\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003eBPA\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e\\u0026lt;LOQ\\u003csup\\u003ed\\u003c/sup\\u003e \\u0026ndash; 450\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e72.1\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e7.1\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e87.5\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e\\u0026lt;LOQ \\u0026ndash; 3.0\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e0.43\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e\\u0026lt;LOQ\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e25.0\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003c/tr\\u003e\\n\\u003ctr\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e4NP\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e\\u0026lt;LOQ\\u003csup\\u003ee\\u003c/sup\\u003e \\u0026ndash; 18.9\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e3.3\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e0.5\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e62.5\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e\\u0026lt;LOQ \\u0026ndash; 2.3\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e0.35\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e\\u0026lt;LOQ\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e37.5\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003c/tr\\u003e\\n\\u003ctr\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e4TOP\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e\\u0026lt;LOQ\\u003csup\\u003ef\\u003c/sup\\u003e \\u0026ndash; 58.8\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e8.8\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e1.2\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e87.5\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e\\u0026lt;LOQ \\u0026ndash; 5.0\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e1.2\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e0.5\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e62.5\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003c/tr\\u003e\\n\\u003c/tbody\\u003e\\n\\u003ctfoot\\u003e\\n\\u003ctr\\u003e\\n\\u003ctd colspan=\\\"9\\\"\\u003e\\u003csup\\u003ea\\u003c/sup\\u003eDF = detection frequency; LOQ\\u0026thinsp;=\\u0026thinsp;\\u003csup\\u003eb\\u003c/sup\\u003e 0.71 ng/L, \\u003csup\\u003ec\\u003c/sup\\u003e 3.0 ng/L, \\u003csup\\u003ed\\u003c/sup\\u003e1.7 ng/L, \\u003csup\\u003ee\\u003c/sup\\u003e0.86 ng/L, \\u003csup\\u003ef\\u003c/sup\\u003e0.91 ng/L.\\u003c/td\\u003e\\n\\u003c/tr\\u003e\\n\\u003c/tfoot\\u003e\\n\\u003c/table\\u003e\\n\\u003c/div\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003eThe frequency of detection of BPA and 4TOP in the influents was also high (87.5% for each one) and the range of concentration was \\u0026lt;\\u0026thinsp;LOQ \\u0026ndash; 450 ng/L for BPA and \\u0026lt;\\u0026thinsp;LOQ \\u0026ndash; 58.8 ng/L for 4TOP in the four WWTPs. These concentrations of BPA and 4TOP are lower than those detected in five WWTPs from the USA, between 60\\u0026ndash;600 ng/L for BPA, and 80\\u0026ndash;3900 ng/L for 4TOP (Yu et al. \\u003cspan class=\\\"CitationRef\\\"\\u003e2013\\u003c/span\\u003e), and to those reported in six WWTPs from Mexico-USA, ranging between 175.5\\u0026ndash;1476.8 ng/L for BPA, and 259.3\\u0026ndash;3693.7 ng/L for 4TOP (De la Torre \\u003cspan class=\\\"CitationRef\\\"\\u003e2011\\u003c/span\\u003e). Similarly, 4NP was detected in the influents of the four WWTPs but with lower frequency (62.5%) at levels from \\u0026lt;\\u0026thinsp;LOQ \\u0026ndash; 18.9 ng/L, much lower than reported by Bina et al. (\\u003cspan class=\\\"CitationRef\\\"\\u003e2018\\u003c/span\\u003e) in nine WWTPs of Iran (ranging from 1250 to 17020 ng/L) and Jiang et al. (\\u003cspan class=\\\"CitationRef\\\"\\u003e2020\\u003c/span\\u003e) in 38 WWTPs from China (ranging between 1519.5 and 27736.7 ng/L).\\u003c/p\\u003e\\n\\u003cp\\u003eAs shown in Fig.\\u0026nbsp;\\u003cspan class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003e, EE2 as well as BPA, were the most abundant EDCs in the influents of WWTPs, and its wide concentration range reflects the high consumption rates and its constant emission in urban and industrial wastewater discharges from Monterrey City. Furthermore, in this study, low levels of 4NP and 4TOP compared to those detected levels in other research suggests a moderate use of these alkylphenols contained in surfactants and detergents, mainly used in domestic and commercial activities (Bina et al. \\u003cspan class=\\\"CitationRef\\\"\\u003e2018\\u003c/span\\u003e). In addition, Table\\u0026nbsp;\\u003cspan class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003e shows a summarized comparison between EDC levels detected in this research and those reported in other regions, where the EDCs amounts are often widely detected of the order of ng/L.\\u003c/p\\u003e\\n\\u003cdiv class=\\\"gridtable\\\"\\u003e\\n\\u003ctable id=\\\"Tab3\\\" border=\\\"1\\\"\\u003e\\u003ccaption\\u003e\\n\\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 3\\u003c/div\\u003e\\n\\u003cdiv class=\\\"CaptionContent\\\"\\u003e\\n\\u003cp\\u003eComparisons of EDCs levels detected in WWTPs from other countries.\\u003c/p\\u003e\\n\\u003c/div\\u003e\\n\\u003c/caption\\u003e\\n\\u003cthead\\u003e\\n\\u003ctr\\u003e\\n\\u003cth align=\\\"left\\\"\\u003e\\n\\u003cp\\u003eEDC\\u003c/p\\u003e\\n\\u003c/th\\u003e\\n\\u003cth align=\\\"left\\\"\\u003e\\n\\u003cp\\u003eCountry\\u003c/p\\u003e\\n\\u003c/th\\u003e\\n\\u003cth align=\\\"left\\\"\\u003e\\n\\u003cp\\u003eN\\u0026ordm; of studied WWTP\\u003c/p\\u003e\\n\\u003c/th\\u003e\\n\\u003cth colspan=\\\"2\\\" align=\\\"left\\\"\\u003e\\n\\u003cp\\u003eInfluents (ng/L)\\u003c/p\\u003e\\n\\u003c/th\\u003e\\n\\u003cth align=\\\"left\\\"\\u003e\\n\\u003cp\\u003eEffluents (ng/L)\\u003c/p\\u003e\\n\\u003c/th\\u003e\\n\\u003cth align=\\\"left\\\"\\u003e\\n\\u003cp\\u003eReferences\\u003c/p\\u003e\\n\\u003c/th\\u003e\\n\\u003c/tr\\u003e\\n\\u003c/thead\\u003e\\n\\u003ctbody\\u003e\\n\\u003ctr\\u003e\\n\\u003ctd rowspan=\\\"7\\\" align=\\\"left\\\"\\u003e\\n\\u003cp\\u003eE2\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003eMexico\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e4\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd colspan=\\\"2\\\" align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e\\u0026lt;LOQ \\u0026ndash; 15.1\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e\\u0026lt;LOQ \\u0026ndash; 9.5\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003eThis study\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003c/tr\\u003e\\n\\u003ctr\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003eChina\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e38\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd colspan=\\\"2\\\" align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e\\u0026lt;LOQ \\u0026ndash; 62.92\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e\\u0026lt;LOQ \\u0026ndash; 50.03\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e(Jiang et al. \\u003cspan class=\\\"CitationRef\\\"\\u003e2020\\u003c/span\\u003e)\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003c/tr\\u003e\\n\\u003ctr\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003eSouth Africa\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e1\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd colspan=\\\"2\\\" align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e20\\u0026ndash;199\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e4\\u0026ndash;107\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e(Manickum and John \\u003cspan class=\\\"CitationRef\\\"\\u003e2014\\u003c/span\\u003e)\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003c/tr\\u003e\\n\\u003ctr\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003eUSA\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e6\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd colspan=\\\"2\\\" align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e\\u0026lt;LOD \\u0026ndash; 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18.9\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e\\u0026lt;LOQ \\u0026ndash; 2.3\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003eThis study\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003c/tr\\u003e\\n\\u003ctr\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003eChina\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e38\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd colspan=\\\"2\\\" align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e1,519.51\\u0026ndash;27,736.71\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e1,346.75\\u0026ndash;7,513.57\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e(Jiang et al. \\u003cspan class=\\\"CitationRef\\\"\\u003e2020\\u003c/span\\u003e)\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003c/tr\\u003e\\n\\u003ctr\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003eGreece\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e1\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd colspan=\\\"2\\\" align=\\\"left\\\"\\u003e\\n\\u003cp\\u003eND\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e2,581\\u0026ndash;4,552\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e(Stasinakis et al. \\u003cspan class=\\\"CitationRef\\\"\\u003e2012\\u003c/span\\u003e)\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003c/tr\\u003e\\n\\u003ctr\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003eUSA\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e5\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd colspan=\\\"2\\\" align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e220\\u0026ndash;870\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e\\u0026lt;LOQ \\u0026ndash; 50\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e(Yu et al. \\u003cspan class=\\\"CitationRef\\\"\\u003e2013\\u003c/span\\u003e)\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003c/tr\\u003e\\n\\u003ctr\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003eUSA\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e6\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd colspan=\\\"2\\\" align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e2,412.8\\u0026ndash;66,457.7\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e71.6\\u0026ndash;7,899.5\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e(De La Torre \\u003cspan class=\\\"CitationRef\\\"\\u003e2011\\u003c/span\\u003e)\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003c/tr\\u003e\\n\\u003ctr\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003eIran\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e9\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd colspan=\\\"2\\\" align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e1,250\\u0026ndash;17,020\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e420\\u0026ndash;2,120\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e(Bina et al. \\u003cspan class=\\\"CitationRef\\\"\\u003e2018\\u003c/span\\u003e)\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003c/tr\\u003e\\n\\u003ctr\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003ePortugal\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e1\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd colspan=\\\"2\\\" align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e4.62\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;0.32\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e4.44\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;0.19\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e(Carvalho et al. \\u003cspan class=\\\"CitationRef\\\"\\u003e2016\\u003c/span\\u003e)\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003c/tr\\u003e\\n\\u003ctr\\u003e\\n\\u003ctd rowspan=\\\"5\\\" align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e4TOP\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003eMexico\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e4\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd colspan=\\\"2\\\" align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e\\u0026lt;LOQ \\u0026ndash; 58.8\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e\\u0026lt;LOQ \\u0026ndash; 5.0\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003eThis study\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003c/tr\\u003e\\n\\u003ctr\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003eUSA\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e5\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd colspan=\\\"2\\\" align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e80\\u0026ndash;3,900\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e\\u0026lt;LOQ \\u0026ndash; 100\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e(Yu et al. \\u003cspan class=\\\"CitationRef\\\"\\u003e2013\\u003c/span\\u003e)\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003c/tr\\u003e\\n\\u003ctr\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003eUSA\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e6\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd colspan=\\\"2\\\" align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e259.3\\u0026ndash;3,693.7\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e7.2\\u0026ndash;416.1\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e(De La Torre \\u003cspan class=\\\"CitationRef\\\"\\u003e2011\\u003c/span\\u003e)\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003c/tr\\u003e\\n\\u003ctr\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003eIran\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e9\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd colspan=\\\"2\\\" align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e35\\u0026ndash;718\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e5.3\\u0026ndash;54.8\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e(Bina et al. \\u003cspan class=\\\"CitationRef\\\"\\u003e2018\\u003c/span\\u003e)\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003c/tr\\u003e\\n\\u003ctr\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003ePortugal\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e1\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd colspan=\\\"2\\\" align=\\\"left\\\"\\u003e\\n\\u003cp\\u003eND\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003eND\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e(Carvalho et al. \\u003cspan class=\\\"CitationRef\\\"\\u003e2016\\u003c/span\\u003e)\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003c/tr\\u003e\\n\\u003c/tbody\\u003e\\n\\u003ctfoot\\u003e\\n\\u003ctr\\u003e\\n\\u003ctd colspan=\\\"7\\\"\\u003eND\\u0026thinsp;=\\u0026thinsp;not detected, LOQ\\u0026thinsp;=\\u0026thinsp;limit of quantification, LOD\\u0026thinsp;=\\u0026thinsp;limit of detection.\\u003c/td\\u003e\\n\\u003c/tr\\u003e\\n\\u003c/tfoot\\u003e\\n\\u003c/table\\u003e\\n\\u003c/div\\u003e\\n\\u003c/div\\u003e\\n\\u003cdiv id=\\\"Sec10\\\" class=\\\"Section2\\\"\\u003e\\n\\u003ch2\\u003eConcentrations of EDCs in effluents\\u003c/h2\\u003e\\n\\u003cp\\u003eThe detection frequency and concentrations of the five selected EDCs in the effluents were lower than those detected in the influents (Table\\u0026nbsp;\\u003cspan class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003e and Fig.\\u0026nbsp;\\u003cspan class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003e), indicating that the treatment processes in WWTPs have a notable effect on the remotion of these substances. In effluents, levels of estrogens E2 and EE2 ranged from \\u0026lt;\\u0026thinsp;LOQ \\u0026ndash; 9.5 and 1.6\\u0026ndash;26.8 ng/L, respectively. The synthetic estrogen EE2 standing out for its frequent detection (100%) in all WWTPs effluents, which reveal its high persistence to treatment processes, which is associated with the ethinyl functional group that makes it highly resistant to biodegradation (Ting and Praveena \\u003cspan class=\\\"CitationRef\\\"\\u003e2017\\u003c/span\\u003e), this characteristic could also explain its frequent detection in the effluents of WWTPs around the world (Manickum and John \\u003cspan class=\\\"CitationRef\\\"\\u003e2014\\u003c/span\\u003e; Belhaj et al. \\u003cspan class=\\\"CitationRef\\\"\\u003e2016\\u003c/span\\u003e; Jiang et al. \\u003cspan class=\\\"CitationRef\\\"\\u003e2020\\u003c/span\\u003e; L\\u0026oacute;pez-Vel\\u0026aacute;zquez et al. \\u003cspan class=\\\"CitationRef\\\"\\u003e2020\\u003c/span\\u003e).\\u003c/p\\u003e\\n\\u003cp\\u003eBPA was detected in only 25% of the samples collected in effluents, ranging in low levels from \\u0026lt;\\u0026thinsp;LOQ to 3.0 ng/L; these results suggest that the conditions of all WWTPs allowed the high removal of BPA (\\u0026gt;\\u0026thinsp;96.9%). This is consistent with those reported by Villarreal-Morales et al. (\\u003cspan class=\\\"CitationRef\\\"\\u003e2020\\u003c/span\\u003e), who reported high BPA concentrations in the influent of one WWTP in Monterrey City (5,900\\u0026ndash;16,600 ng/L), and not detected levels in the effluent; however, it is worth note that they used SPE/LC-UV technique, and likely levels of BPA in the effluents could be underestimated.\\u003c/p\\u003e\\n\\u003cp\\u003eFor 4NP and 4TOP, the detected concentrations in the effluents ranged from \\u0026lt;\\u0026thinsp;LOQ to 2.3 ng/L and \\u0026lt;\\u0026thinsp;LOQ to 5.0 ng/L, respectively, and were considered low compared with those quantified in other WWTPs effluents in ranges from 1,346.7 to 7,513.5 ng/L, and 420 to 2,120 ng/L for 4NP (Bina et al. \\u003cspan class=\\\"CitationRef\\\"\\u003e2018\\u003c/span\\u003e; Jiang et al. \\u003cspan class=\\\"CitationRef\\\"\\u003e2020\\u003c/span\\u003e); and from 7.2 to 416.1 ng/L for 4TOP (De la Torre \\u003cspan class=\\\"CitationRef\\\"\\u003e2011\\u003c/span\\u003e). These authors related the levels of 4NP and 4TOP in WWTPs with the extensive use of polyethoxylated alkylphenols (active substances of detergents and surfactants) in domestic, urban and hospital clean activities. Moreover, the detected levels of these alkylphenols in the wastewater may be regulated to some extent by microbial activity in the environment by degrading the polyethoxylated alkylphenols to give rise to large amounts of 4NP and 4TOP (Lee et al. \\u003cspan class=\\\"CitationRef\\\"\\u003e2013\\u003c/span\\u003e; Santhi et al. \\u003cspan class=\\\"CitationRef\\\"\\u003e2015\\u003c/span\\u003e).\\u003c/p\\u003e\\n\\u003c/div\\u003e\\n\\u003cdiv id=\\\"Sec11\\\" class=\\\"Section2\\\"\\u003e\\n\\u003ch2\\u003eMass balance of EDCs dissolved in WWTPs\\u003c/h2\\u003e\\n\\u003cp\\u003eThe mass balance for the five EDCs in the soluble phase was determined based on the concentrations detected in the WWTPs and the volume of water treated per day (Table\\u0026nbsp;\\u003cspan class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e). The results are shown in Table\\u0026nbsp;\\u003cspan class=\\\"InternalRef\\\"\\u003e4\\u003c/span\\u003e and it was observed that the total loading mass of the EDCs in the influents of WWTPs equals 118,687.0 mg/day and are distributed as follows: BPA (61,282.6 mg/day)\\u0026thinsp;\\u0026gt;\\u0026thinsp;EE2 (43,559.5 mg/day)\\u0026thinsp;\\u0026gt;\\u0026thinsp;4TOP (8,751.4 mg/day)\\u0026thinsp;\\u0026gt;\\u0026thinsp;E2 (3,411.2 mg/day)\\u0026thinsp;\\u0026gt;\\u0026thinsp;4NP (1,682.3 mg/day). In the WWTPs, 93.4% of the total mass of the EDCs was removed by treatment processes, and the remaining mass in effluents was 7,792.9 mg/day distributed as follows: EE2 (5,741.3 mg/day)\\u0026thinsp;\\u0026gt;\\u0026thinsp;4TOP (905.7 mg/day)\\u0026thinsp;\\u0026gt;\\u0026thinsp;E2 (658.1 mg/day)\\u0026thinsp;\\u0026gt;\\u0026thinsp;4NP (283.5 mg/day)\\u0026thinsp;\\u0026gt;\\u0026thinsp;BPA (204.3 mg/day); these results are similar to estimates by Ashfaq et al. (\\u003cspan class=\\\"CitationRef\\\"\\u003e2018\\u003c/span\\u003e) who reported 951 mg/day of 4NP, 669 mg/day of E2, and 127 mg/day of 4NP in the effluents from nine WWTPs (China). However, the emission rate for 4NP and BPA were much lower than those estimated by Stasinakis et al. (\\u003cspan class=\\\"CitationRef\\\"\\u003e2012\\u003c/span\\u003e) in a WWTP in Greece (~\\u0026thinsp;5\\u0026times;10\\u003csup\\u003e4\\u003c/sup\\u003e mg/day for 4NP and ~\\u0026thinsp;5\\u0026times;10\\u003csup\\u003e3\\u003c/sup\\u003e mg/day for BPA), which was associated with intense urban and industrial activities. Additionally, Fig.\\u0026nbsp;\\u003cspan class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003e shows the daily mass of EDCs in the effluents of the WWTPs, and it was observed that the emission rate of EDCs is directly related to the number of the population served and the volume of wastewater treated (see Table\\u0026nbsp;\\u003cspan class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e). Also, it is observed that EE2 is the major constituent (73.7%) of the dissolved EDCs in the four effluents, which are directly discharged to La Silla, Sabinal, Santa Catarina, and Pesquer\\u0026iacute;a rivers (Fig.\\u0026nbsp;\\u003cspan class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e), suggesting a potential health risk to exposed aquatic ecosystems and human health.\\u003c/p\\u003e\\n\\u003cdiv class=\\\"gridtable\\\"\\u003e\\n\\u003ctable id=\\\"Tab4\\\" border=\\\"1\\\"\\u003e\\u003ccaption\\u003e\\n\\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 4\\u003c/div\\u003e\\n\\u003cdiv class=\\\"CaptionContent\\\"\\u003e\\n\\u003cp\\u003eDaily mass load (mg/day) and approximate remotion of EDCs in the WWTPs.\\u003c/p\\u003e\\n\\u003c/div\\u003e\\n\\u003c/caption\\u003e\\n\\u003cthead\\u003e\\n\\u003ctr\\u003e\\n\\u003cth align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/th\\u003e\\n\\u003cth align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/th\\u003e\\n\\u003cth align=\\\"left\\\"\\u003e\\n\\u003cp\\u003eWWTP A\\u003c/p\\u003e\\n\\u003c/th\\u003e\\n\\u003cth align=\\\"left\\\"\\u003e\\n\\u003cp\\u003eWWTP B\\u003c/p\\u003e\\n\\u003c/th\\u003e\\n\\u003cth align=\\\"left\\\"\\u003e\\n\\u003cp\\u003eWWTP C\\u003c/p\\u003e\\n\\u003c/th\\u003e\\n\\u003cth align=\\\"left\\\"\\u003e\\n\\u003cp\\u003eWWTP D\\u003c/p\\u003e\\n\\u003c/th\\u003e\\n\\u003cth align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e\\u0026Sigma;mass load (mg/day)\\u003c/p\\u003e\\n\\u003c/th\\u003e\\n\\u003c/tr\\u003e\\n\\u003c/thead\\u003e\\n\\u003ctbody\\u003e\\n\\u003ctr\\u003e\\n\\u003ctd rowspan=\\\"2\\\" align=\\\"left\\\"\\u003e\\n\\u003cp\\u003eE2\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003emass\\u003csub\\u003einf\\u003c/sub\\u003e\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e3.1\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e685.8\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e1130.3\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e1592.1\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e3411.3\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003c/tr\\u003e\\n\\u003ctr\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003emass\\u003csub\\u003eeff\\u003c/sub\\u003e\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e18.4\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e0\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e462.8\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e176.9\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e658.1\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003c/tr\\u003e\\n\\u003ctr\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003eAR (%)\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e-493.5\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e100.0\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e59.0\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e88.9\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n\\u003c/tr\\u003e\\n\\u003ctr\\u003e\\n\\u003ctd rowspan=\\\"3\\\" align=\\\"left\\\"\\u003e\\n\\u003cp\\u003eEE2\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n\\u003c/tr\\u003e\\n\\u003ctr\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003emass\\u003csub\\u003einf\\u003c/sub\\u003e\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e37.6\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e14680.2\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e20822.2\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e8019.5\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e43559.5\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003c/tr\\u003e\\n\\u003ctr\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003emass\\u003csub\\u003eeff\\u003c/sub\\u003e\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e211.5\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e2301.4\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e1135.1\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e2093.3\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e5741.3\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003c/tr\\u003e\\n\\u003ctr\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003eAR (%)\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e-462.5\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e84.3\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e94.5\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e73.9\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n\\u003c/tr\\u003e\\n\\u003ctr\\u003e\\n\\u003ctd rowspan=\\\"3\\\" align=\\\"left\\\"\\u003e\\n\\u003cp\\u003eBPA\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n\\u003c/tr\\u003e\\n\\u003ctr\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003emass\\u003csub\\u003einf\\u003c/sub\\u003e\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e90.4\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e52816.2\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e4808.5\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e3567.5\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e61282.6\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003c/tr\\u003e\\n\\u003ctr\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003emass\\u003csub\\u003eeff\\u003c/sub\\u003e\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e0\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e58.1\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e146.2\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003eND\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e204.3\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003c/tr\\u003e\\n\\u003ctr\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003eAR (%)\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e100.0\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e99.9\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e96.9\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e100.0\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n\\u003c/tr\\u003e\\n\\u003ctr\\u003e\\n\\u003ctd rowspan=\\\"3\\\" align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e4NP\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n\\u003c/tr\\u003e\\n\\u003ctr\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003emass\\u003csub\\u003einf\\u003c/sub\\u003e\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e4.6\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e674.2\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e1003.6\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003eND\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e1682.4\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003c/tr\\u003e\\n\\u003ctr\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003emass\\u003csub\\u003eeff\\u003c/sub\\u003e\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e1.5\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e267.3\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e14.6\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003eND\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e283.4\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003c/tr\\u003e\\n\\u003ctr\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003eAR (%)\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e67.4\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e60.3\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e98.5\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e\\u0026ndash;\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n\\u003c/tr\\u003e\\n\\u003ctr\\u003e\\n\\u003ctd rowspan=\\\"3\\\" align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e4TOP\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n\\u003c/tr\\u003e\\n\\u003ctr\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003emass\\u003csub\\u003einf\\u003c/sub\\u003e\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e14.6\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e7287.8\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e63.3\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e1385.7\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e8751.4\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003c/tr\\u003e\\n\\u003ctr\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003emass\\u003csub\\u003eeff\\u003c/sub\\u003e\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e38.3\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e116.2\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e73.1\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e678.1\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e905.7\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003c/tr\\u003e\\n\\u003ctr\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003eAR (%)\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e-162.3\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e98.4\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e-15.5\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e51.0\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n\\u003c/tr\\u003e\\n\\u003ctr\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n\\u003ctd colspan=\\\"3\\\" align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e\\u0026Sigma;EDCs in influents (mg/day)\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e118687.2\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003c/tr\\u003e\\n\\u003ctr\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n\\u003ctd colspan=\\\"3\\\" align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e\\u0026Sigma;EDCs in effluents (mg/day)\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e7792.8\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003c/tr\\u003e\\n\\u003ctr\\u003e\\n\\u003ctd colspan=\\\"7\\\" align=\\\"left\\\"\\u003e\\n\\u003cp\\u003eAR\\u0026thinsp;=\\u0026thinsp;approximate remotion, ND\\u0026thinsp;=\\u0026thinsp;not detected.\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003c/tr\\u003e\\n\\u003c/tbody\\u003e\\n\\u003c/table\\u003e\\n\\u003c/div\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003eBased on the mass balance of EDCs in influents and effluents of the WWTPs, the approximate remotion of EDCs were estimated, and results are shown in Table\\u0026nbsp;\\u003cspan class=\\\"InternalRef\\\"\\u003e4\\u003c/span\\u003e. The remotion values for E2 and EE2 in WWTP B, C, and D, ranged between 59\\u0026ndash;100% (E2), and 73.9\\u0026ndash;94.5% (EE2), these values were higher than those reported by Jiang et al. (\\u003cspan class=\\\"CitationRef\\\"\\u003e2020\\u003c/span\\u003e) from 6.3 to 29.64% for E2, and from \\u0026minus;\\u0026thinsp;57.6 to 18.51% for EE2. In the case of BPA, the four WWTPs showed high remotion values, between 96.9 and 100% (Table\\u0026nbsp;\\u003cspan class=\\\"InternalRef\\\"\\u003e4\\u003c/span\\u003e), which agrees well with those observed by Ben et al. (\\u003cspan class=\\\"CitationRef\\\"\\u003e2018\\u003c/span\\u003e) in 14 WWTPs from China. In addition, the remotion of 4NP ranged from 60.3 to 98.5% in WWTP A, B, and C; and for 4TOP, the remotion was 98.4 and 51.0% in WWTP B and D, respectively. These results agree with those reported by Bina et al. (\\u003cspan class=\\\"CitationRef\\\"\\u003e2018\\u003c/span\\u003e) who studied 9 WWTPs and estimated remotion values between 61.9 and 93.1% for 4NP, and between 71.5 and 99.2% for 4TOP; also, similar values were reported by Ben et al. (\\u003cspan class=\\\"CitationRef\\\"\\u003e2018\\u003c/span\\u003e) and Jiang et al. (\\u003cspan class=\\\"CitationRef\\\"\\u003e2020\\u003c/span\\u003e).\\u003c/p\\u003e\\n\\u003cp\\u003eIt is worth noting that some negative values were observed for E2, EE2, and 4TOP in WWTP A (-493.5, -462.5, and \\u0026minus;\\u0026thinsp;162.3%, respectively), and this phenomenon was also observed for 4TOP in WWTP C (-15.5%). These negative values indicate that levels of these EDCs were higher in effluents than influents, and can be attributed to the likely transformation of conjugated estrogens to their active forms, and the biodegradation of polyethoxylated alkylphenols to give rise to metabolites such as 4TOP by the action of the microbial consortia in the WWTPs, which increase their concentration in the effluents, and it is consistent with that described by Yu et al. (\\u003cspan class=\\\"CitationRef\\\"\\u003e2013\\u003c/span\\u003e) and Zuo et al. (\\u003cspan class=\\\"CitationRef\\\"\\u003e2006\\u003c/span\\u003e).\\u003c/p\\u003e\\n\\u003c/div\\u003e\\n\\u003cdiv id=\\\"Sec12\\\" class=\\\"Section2\\\"\\u003e\\n\\u003ch2\\u003eRisk assessment\\u003c/h2\\u003e\\n\\u003cp\\u003eThe occurrence of EDCs caused for the discharge of treated and untreated wastewater may represent a potential ecological risk to both aquatic species and humans. Therefore, the risk quotients (RQ) were calculated from the influent and effluent data of the four WWTPs using the MEC values, and the PNEC values for each EDC were taken from the scientific literature. The results are shown in Table\\u0026nbsp;\\u003cspan class=\\\"InternalRef\\\"\\u003e5\\u003c/span\\u003e and Fig.\\u0026nbsp;\\u003cspan class=\\\"InternalRef\\\"\\u003e4\\u003c/span\\u003e, and it is observed that the highest RQ values for E2, EE2, and BPA were 78.1, 17,442.8 and 10.4, indicating that the untreated wastewater represent a high risk for aquatic species. While, the highest RQ values for 4NP and 4TOP in untreated wastewater were 0.2 and 0.5, suggesting a medium risk for exposed species. Likewise, the treated water in WWTPs effluents were also considered as a high risk for aquatic organisms, mainly attributed to the abundance of E2 (RQ\\u0026thinsp;=\\u0026thinsp;49.1) and EE2 (RQ\\u0026thinsp;=\\u0026thinsp;1,165.2), which are considered as potent endocrine disruptors due to their high estrogenic potential, even at trace levels such as pg/L (European Commission 2012; Brion et al. \\u003cspan class=\\\"CitationRef\\\"\\u003e2019\\u003c/span\\u003e). In addition, as can be seen in Fig.\\u0026nbsp;\\u003cspan class=\\\"InternalRef\\\"\\u003e4\\u003c/span\\u003e, BPA, 4NP, and 4TOP represent a low risk in WWTPs effluents (RQs\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.1 for each); however, this was not significant because they constitute a minimal part of the remaining EDCs in the effluents (Fig.\\u0026nbsp;\\u003cspan class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003e). Finally, the possible ecological risk was estimated for the receiving waterbodies impacted by the effluents of WWTPs (Fig.\\u0026nbsp;\\u003cspan class=\\\"InternalRef\\\"\\u003e4\\u003c/span\\u003e), and results suggest that the organisms in these aquatic ecosystems may be exposed to high risk, attributed to the abundance of remaining E2 (RQ\\u0026thinsp;=\\u0026thinsp;4.9) and EE2 (RQ\\u0026thinsp;=\\u0026thinsp;116.5) in the effluents of WWTPs (Fig.\\u0026nbsp;\\u003cspan class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003e).\\u003c/p\\u003e\\n\\u003cdiv class=\\\"gridtable\\\"\\u003e\\n\\u003ctable id=\\\"Tab5\\\" border=\\\"1\\\"\\u003e\\u003ccaption\\u003e\\n\\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 5\\u003c/div\\u003e\\n\\u003cdiv class=\\\"CaptionContent\\\"\\u003e\\n\\u003cp\\u003eHC5 values for the protection of 95% of the species, risk quotient (RQ) calculated from maximum EDCs levels detected in the four WWTPs.\\u003c/p\\u003e\\n\\u003c/div\\u003e\\n\\u003c/caption\\u003e\\n\\u003cthead\\u003e\\n\\u003ctr\\u003e\\n\\u003cth rowspan=\\\"2\\\" align=\\\"left\\\"\\u003e\\n\\u003cp\\u003eEDCs\\u003c/p\\u003e\\n\\u003c/th\\u003e\\n\\u003cth rowspan=\\\"2\\\" align=\\\"left\\\"\\u003e\\n\\u003cp\\u003eHC5 (ng/L)\\u003c/p\\u003e\\n\\u003c/th\\u003e\\n\\u003cth rowspan=\\\"2\\\" align=\\\"left\\\"\\u003e\\n\\u003cp\\u003ePNEC (ng/L)\\u003c/p\\u003e\\n\\u003c/th\\u003e\\n\\u003cth colspan=\\\"6\\\" align=\\\"left\\\"\\u003e\\n\\u003cp\\u003eRQ\\u0026thinsp;=\\u0026thinsp;MEC/PNEC\\u003c/p\\u003e\\n\\u003c/th\\u003e\\n\\u003c/tr\\u003e\\n\\u003ctr\\u003e\\n\\u003cth colspan=\\\"2\\\" align=\\\"left\\\"\\u003e\\n\\u003cp\\u003eInfluents\\u003c/p\\u003e\\n\\u003c/th\\u003e\\n\\u003cth colspan=\\\"2\\\" align=\\\"left\\\"\\u003e\\n\\u003cp\\u003eEffluents\\u003c/p\\u003e\\n\\u003c/th\\u003e\\n\\u003cth colspan=\\\"2\\\" align=\\\"left\\\"\\u003e\\n\\u003cp\\u003eSurface water\\u003csup\\u003ed\\u003c/sup\\u003e\\u003c/p\\u003e\\n\\u003c/th\\u003e\\n\\u003c/tr\\u003e\\n\\u003c/thead\\u003e\\n\\u003ctbody\\u003e\\n\\u003ctr\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003eE2\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e0.58\\u003csup\\u003ea\\u003c/sup\\u003e\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e0.19\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e78.1\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003eHigh risk\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e49.1\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003eHigh risk\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e4.9\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003eHigh risk\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003c/tr\\u003e\\n\\u003ctr\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003eEE2\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e0.07\\u003csup\\u003eb\\u003c/sup\\u003e\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e0.023\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e17442.8\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003eHigh risk\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e1165.2\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003eHigh risk\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e116.5\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003eHigh risk\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003c/tr\\u003e\\n\\u003ctr\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003eBPA\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e129\\u003csup\\u003ea\\u003c/sup\\u003e\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e43.00\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e10.4\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003eHigh risk\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e0.07\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003eLow risk\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e0.007\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003eLow risk\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003c/tr\\u003e\\n\\u003ctr\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e4NP\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e280\\u003csup\\u003ea\\u003c/sup\\u003e\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e93.33\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e0.2\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003eMedium risk\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e0.02\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003eLow risk\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e0.002\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003eLow risk\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003c/tr\\u003e\\n\\u003ctr\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e4TOP\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e360\\u003csup\\u003ec\\u003c/sup\\u003e\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e120.00\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e0.5\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003eMedium risk\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e0.04\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003eLow risk\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003e0.004\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003eLow risk\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003c/tr\\u003e\\n\\u003c/tbody\\u003e\\n\\u003ctfoot\\u003e\\n\\u003ctr\\u003e\\n\\u003ctd colspan=\\\"9\\\"\\u003e\\u003csup\\u003ea\\u003c/sup\\u003e(Huang et al. \\u003cspan class=\\\"CitationRef\\\"\\u003e2019\\u003c/span\\u003e), \\u003csup\\u003eb\\u003c/sup\\u003e(Brion et al. \\u003cspan class=\\\"CitationRef\\\"\\u003e2019\\u003c/span\\u003e), \\u003csup\\u003ec\\u003c/sup\\u003e(Tamis and Jongbloed \\u003cspan class=\\\"CitationRef\\\"\\u003e2019\\u003c/span\\u003e), \\u003csup\\u003ed\\u003c/sup\\u003eDilution of 10 times was assumed in receiving waterbody.\\u003c/td\\u003e\\n\\u003c/tr\\u003e\\n\\u003c/tfoot\\u003e\\n\\u003c/table\\u003e\\n\\u003c/div\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003eAdditionally, in the worst-case scenario, the results obtained in this study could underestimate the potential ecological risk related to EDCs since in this study only two sampling campaigns were carried out. Moreover, the suspended phase of EDCs in the WWTPs and the fraction of untreated wastewater directly discharged to the environment were not considered. In addition, the emission of pollutants such as EDCs may be a function of population consumption and excretion rates, as well as urban and industrial activities which vary over time. Also, in the environment, EDCs are regulated to some extent by environmental factors such as temperature, precipitation, solar radiation, microbial activity, among others.\\u003c/p\\u003e\\n\\u003c/div\\u003e\"},{\"header\":\"Conclusions\",\"content\":\"\\u003cp\\u003eThis study revealed that EE2 and BPA were the most frequently detected EDCs in the influents of WWTPs, likely associated to the extensive use of EE2 as a contraceptive method and the use of BPA as a plasticizer in industrial activities. In addition, the detected levels of 4NP and 4TOP suggest their moderate use in urban activities in Monterrey City. Furthermore, EE2 was detected in all WWTP effluents ranging from 1.6 to 26.8 ng/L being the most recalcitrant compound in the treatment processes. Also, the mass balance in the dissolved phase revealed that the WWTP effluents constitute critical sources of EDCs emission to the environment, despite that these compounds present high remotion percentages in some WWTPs. Moreover, through the RQ values, it was estimated that the wastewater in influents and effluents of the studied WWTPs represent a high risk to exposed aquatic species, due to the abundance of dissolved E2 and EE2. Also, a preliminary assessment of the risk quotient in receiving water bodies indicated a potential environmental risk for La Silla, Santa Catarina, Sabinal, Topo Chico, and Pesqueria rivers. However, ecotoxicological studies and extensive monitoring are needed to protect the biodiversity of these aquatic environments. Additionally, it is necessary pay more attention to the possible public health risk associated with the occurrence of EDCs in WWTPs in densely populated and industrialized zones such as Monterrey City.\\u003c/p\\u003e\"},{\"header\":\"Declarations\",\"content\":\"\\u003cp\\u003e\\u003cstrong\\u003eAcknowledgements \\u003c/strong\\u003eThe authors thanks to Facultad de Ciencias Qu\\u0026iacute;micas, Universidad Aut\\u0026oacute;noma de Nuevo Le\\u0026oacute;n; Centro de Investigaciones Qu\\u0026iacute;micas, Universidad Aut\\u0026oacute;noma del Estado de Morelos, and Servicios de Agua y Drenaje de Monterrey. L\\u0026oacute;pez-Vel\\u0026aacute;zquez acknowledges the scholarship from Consejo Nacional de Ciencia y Tecnolog\\u0026iacute;a (CONACyT-M\\u0026eacute;xico, 736037). Special thanks to Ph.D. Yunu\\u0026eacute;n Canedo L\\u0026oacute;pez and MSc. David Herrera L\\u0026oacute;pez for their valuable comments on the manuscript.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eFunding \\u003c/strong\\u003eThis work was supported by the Facultad de Ciencias Químicas, Universidad Autónoma de Nuevo León and PAICyT-UANL (CE868- 19).\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eEthics approval and consent to participate\\u003c/strong\\u003e Not applicable.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eConsent for publication\\u003c/strong\\u003e Not applicable.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eAvailability of data and materials\\u003c/strong\\u003e Not applicable\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eCompeting interests\\u003c/strong\\u003e The authors declare no competing interests\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eAuthor contribution \\u003c/strong\\u003eKLV: Investigation, conceptualization, writing and original draft. JLGM: Supervision, resources, writing-review and editing. HASN and MAMT: Methodology, data curation, writing-review, and editing. MVR: Project administration, supervision, funding acquisition, conceptualization, writing-review, and editing.\\u003c/p\\u003e\"},{\"header\":\"References\",\"content\":\"\\u003col\\u003e\\n\\u003cli\\u003eAdeel M, Song X, Wang Y, Francis D, Yang Y. 2017. Environmental impact of estrogens on human, animal and plant life: A critical review. Environ. Int. 99:107\\u0026ndash;119. doi:10.1016/j.envint.2016.12.010.\\u003c/li\\u003e\\n\\u003cli\\u003eAshfaq M, Li Y, Wang Y, Qin D, Rehman MSU, Rashid A, Yu CP, Sun Q. 2018. Monitoring and mass balance analysis of endocrine disrupting compounds and their transformation products in an anaerobic-anoxic-oxic wastewater treatment system in Xiamen, China. Chemosphere. doi:10.1016/j.chemosphere.2018.04.028.\\u003c/li\\u003e\\n\\u003cli\\u003eBelhaj D, Athmouni K, Jerbi B, Kallel M, Ayadi H, Zhou JL. 2016. 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Occurrence and photochemical degradation of 17 a -ethinylestradiol in Acushnet River Estuary. 63:1583\\u0026ndash;1590. doi:10.1016/j.chemosphere.2005.08.063.\\u003c/li\\u003e\\n\\u003c/ol\\u003e\"}],\"fulltextSource\":\"\",\"fullText\":\"\",\"funders\":[],\"hasAdminPriorityOnWorkflow\":false,\"hasManuscriptDocX\":true,\"hasOptedInToPreprint\":true,\"hasPassedJournalQc\":\"\",\"hasAnyPriority\":false,\"hideJournal\":false,\"highlight\":\"\",\"institution\":\"\",\"isAcceptedByJournal\":false,\"isAuthorSuppliedPdf\":false,\"isDeskRejected\":\"\",\"isHiddenFromSearch\":false,\"isInQc\":false,\"isInWorkflow\":false,\"isPdf\":false,\"isPdfUpToDate\":true,\"isWithdrawnOrRetracted\":false,\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"identity\":\"environmental-science-and-pollution-research\",\"isNatureJournal\":false,\"hasQc\":true,\"allowDirectSubmit\":false,\"externalIdentity\":\"espr\",\"sideBox\":\"Learn more about [Environmental Science and Pollution Research](https://www.springer.com/journal/11356)\",\"snPcode\":\"11356\",\"submissionUrl\":\"https://submission.nature.com/new-submission/11356/3\",\"title\":\"Environmental Science and Pollution Research\",\"twitterHandle\":\"\",\"acdcEnabled\":true,\"dfaEnabled\":true,\"editorialSystem\":\"em\",\"reportingPortfolio\":\"Springer Hybrid\",\"inReviewEnabled\":true,\"inReviewRevisionsEnabled\":false},\"keywords\":\"health risk, environmental pollution, emerging contaminants, quotient risk, water pollution, WWTP. \",\"lastPublishedDoi\":\"10.21203/rs.3.rs-708615/v1\",\"lastPublishedDoiUrl\":\"https://doi.org/10.21203/rs.3.rs-708615/v1\",\"license\":{\"name\":\"CC BY 4.0\",\"url\":\"https://creativecommons.org/licenses/by/4.0/\"},\"manuscriptAbstract\":\"\\u003cp\\u003eThe potential ecological risk of five residual endocrine-disrupting compounds (EDCs) in four wastewater treatment plants (WWTPs) was studied. The wastewater samples were collected in WWTPs of the Metropolitan Area of Monterrey, Mexico (designed as Monterrey City hereinafter) and 17β-estradiol (E2), 17α-ethinylestradiol (EE2), bisphenol A (BPA), 4-nonylphenol (4NP), and 4-tert-octylphenol (4TOP) were studied by SPE/GC-MS method. Results showed that all EDCs are widely distributed in WWTPs, finding high concentrations of BPA (450 ng/L) and EE2 (407.5 ng/L) in influents, while EE2 and 4TOP were the most abundant in effluents at levels from 1.6\\u0026ndash;26.8 ng/L (EE2) and \\u0026lt;\\u0026thinsp;LOQ \\u0026ndash; 5.0 ng/L (4TOP), which corroborate that the wastewater discharges represent critical sources of EDCs to the aquatic environments. 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