In this study, the occurrence and environmental risks related to triclosan (TCS) in the two wastewater treatment plants (WWTPs) were investigated in Isfahan, Iran. Influent and effluent samples were collected and analyzed by dispersive liquid–liquid microextraction (DLLME)–GC–MS method with derivatization. Moreover, the risk of TCS exposure was conducted for aquatic organisms (algae, crustaceans, and fishes) and humans (males and females). TCS mean concentrations in influent and effluent of WWTPs were in the range of 3.70–52.99 and 0.83–1.09 μg/L, respectively. There were also no differences in the quantity of TCS and physicochemical parameters among the two WWTPs. The mean risk quotient (RQ) for TCS was higher than 1 (in algae) with dilution factors (DFs) equal to 1 in WWTP1. Moreover, the RQ value was higher than 1 for humans based on the reference dose of MDH (RFDMDH) in WWTP1. Furthermore, TCS concentration in wastewater effluent was the influential factor in varying the risk of TCS exposure. The results of the present study showed the risk of TCS exposure from the discharge of effluent of WWTP1 was higher than WWTP2. Moreover, the results of this study may be suitable for promoting WWTP processes to completely remove micropollutants.

  • WWTP1 was at risk of TCS exposure for aquatic and human life.

  • Algae was highly vulnerable to TCS exposure among aquatic organisms.

  • The concentration of TCS was the significant effective factor in the risk of TCS.

Triclosan (5-chloro-2-(2,4-dichlorophenoxy) phenol, TCS) is an antibacterial agent and emerging organic contaminant (Chen et al. 2019; Lee et al. 2019) with low water solubility (10 mg/L at 20 °C), lipophilicity (log Kow = 4.8 at 25 °C, pH 7), low volatility (boiling and melting points between 280–290 °C and 56–60 °C, respectively), and ionizable (pKa = 7.9–8.1) characteristics (Kantiani et al. 2008; Lee 2015; Olaniyan et al. 2016; Sarkar et al. 2020; Liu et al. 2022; Wang et al. 2022). It is applied in pharmaceutical and personal care products (PPCPs) (e.g., soap, mouthwashes, toothpaste, deodorants, and cosmetics), toys, shoes, and building materials (USFDA 2008; CIR 2010; Chen et al. 2019). TCS is listed among the top contaminants in the world and its use has been restricted by the US FDA and EU due to risks to humans, animals, and aquatic organisms (COM 2014; USFDA 2015; Healy et al. 2017).

TCS has half-lives of 60 days in water (Clarke et al. 2016); thus, it is considered bio-persistent and bioaccumulative in aquatic organisms and it can make antibiotics resistant (Yazdankhah et al. 2006; Higgins et al. 2011; Oggioni et al. 2013; Ebele et al. 2017), cause alterations in the microbial community (Carey & McNamara 2015; Carey et al. 2016), and diverse toxic effects on aquatic organisms in comparison with other antimicrobial agents (Brausch & Rand 2011). Some researchers reported toxic effects of TCS on aquatic organisms, such as increased oxidative stress (Riva et al. 2012), enzymatic toxicity, reproductive toxicity, thyroid toxicity, lethal toxicity, and genotoxicity (Yaqi et al. 2019; Zheng et al. 2019). In addition, studies indicated that TCS had endocrine disruption effects (Lee et al. 2014; Pollock et al. 2014), increased risk of obesity (Lankester et al. 2013), inhibition of muscle function (Cherednichenko et al. 2012), quality reduction of sperm (Zhu et al. 2016), skin irritation, increased the risk of asthma and spontaneous abortion rates, altered the activity of endogenous hormones, and decreased fecundity and body growth (Kantiani et al. 2008; Olaniyan et al. 2016; Tan et al. 2021a) in humans.

The products containing TCS are released into wastewater and conveyed to wastewater treatment plants (WWTPs). WWTPs cannot completely remove TCS from wastewater, therefore, the residual TCS would enter the water and sediments (Crawford & Decatanzaro 2012; Liu et al. 2022; Du et al. 2023). TCS is frequently detected in wastewater (McClellan & Halden 2010; Zhao et al. 2010; Kookana et al. 2011; Yu et al. 2011; Jabłońska-Trypuć 2023), surface water (Loos et al. 2007; Kantiani et al. 2008; Kookana et al. 2011; Wang et al. 2022), sediments (Wang et al. 2022; de Rezende & Mounteer 2023), groundwater (Sorensen et al. 2015), and drinking water (Li et al. 2010; Moazeni et al. 2023) all over the world due to the its widespread usage.

Even low concentrations of TCS can create adverse effects on humans and aquatic life, therefore, it is essential to evaluate the risk of TCS related to wastewater applications in the environment to aquatic organisms and human health (EU 2016; USFDA 2016). It is reported that the use of TCS is not yet limited and it exists in disinfectant products in many developed and developing countries. Additionally, toxicological studies indicated that exposure to TCS can prevent the growth and mortality of algae, crustaceans, and fishes (Orvos et al. 2002; Oliveira et al. 2009). Moreover, some risk assessment studies have been carried out for human exposure to TCS via wastewater applications (Musee 2018; Mohan & Balakrishnan 2019; Ashfaq et al. 2023; Zhang & Lu 2023). Studies regarding assessment of TCS risks through wastewater in Iran are limited. Thus, the present study is the first one with the aim of investigating environmental risk of TCS through the application of effluent of WWTPs in Isfahan, Iran. The purposes of this study were to consider the occurrence of TCS, to estimate the ecotoxicological risk of TCS in three different aquatic organisms (algae, invertebrates, and fishes), and to human health risk due to the discharge of effluent of wastewater from two WWTPs into surface water bodies.

Chemicals

Analytical grades of methanol, 1,1,1-trichloroethane (CH3CCl3), and ethyl acetate were purchased from Merck Co (Darmstadt, Germany). Additionally, gas chromatography (GC) grade of Triclosan (TCS) and N-methyl-N-(tert-butyldimethylsilyl) trifluoroacetamide (MTBSTFA) as derivatization chemicals were obtained from Sigma–Aldrich Co (Milwaukee, WI, USA).

Sampling sites and sample collection

Isfahan is one of the biggest provinces in the central plateau of Iran, with a total area of 107,045 km2. The average annual rainfall in Isfahan is approximately 150 mm and its average ambient temperatures are about 36.4 and 10.8 °C, in summer and winter, respectively. It has an arid and semi-arid climate in the north and east regions and a Mediterranean climate in the south.

In this study, a total of 60 wastewater samples were taken from two WWTPs in Isfahan from July to October 2022. The relevant information on the two WWTPs is presented in Table 1.

Table 1

Information on wastewater treatment plants (WWTPs)

Types of WWTPWastewater treatment plant
WWTP1WWTP2
 Conventional activated sludge Conventional activated sludge/Two-stage activated sludge: A-B 
Capacity (m3/d) 130000 250000 
Disinfection process Bleach Bleach (sometimes) 
Final effluent receiving field River (Zayandehroud river) Land application/Agricultural use 
Types of WWTPWastewater treatment plant
WWTP1WWTP2
 Conventional activated sludge Conventional activated sludge/Two-stage activated sludge: A-B 
Capacity (m3/d) 130000 250000 
Disinfection process Bleach Bleach (sometimes) 
Final effluent receiving field River (Zayandehroud river) Land application/Agricultural use 

Influent and effluent samples of WWTPs were collected in the dark glass bottles in a cool box at 4 °C after grab sampling and transported to the laboratory immediately. Furthermore, all the samples were analyzed on-site for electrical conductivity (EC), temperature, and pH.

Sample preparation

50 mL of samples were centrifuged to separate the liquid and solid phases. The dispersive liquid–liquid microextraction (DLLME) method was performed for the TCS extraction from liquid phases, as reported by Montes et al. (2009). First, a sample volume of 5 mL was decanted into a 10-mL falcon. Then, 60 μL of 1,1,1-trichloroethane (extraction solvent) and 750 μL of methanol (dispersion solvent) were quickly added into the tube using a 1-mL Hamilton syringe. After that, the cloudy solution was centrifuged at 4,000 rpm for 5 min. Next, 30 μL of the sediment phase was taken and evaporated to dryness in a nitrogen stream at room temperature. Finally, the sample was derivatized by the MTBSTFA and kept in a laboratory bain-marie for 10 min at 65 °C and quickly injected into the gas chromatography–mass spectrometry (GC/MS) system. Furthermore, the solid phase was poured into a Petri dish and put in a 40 °C oven for 24 h. Afterwards, 5 mL of ethyl acetate was added to the sample and put into the ultrasonic bath for 2 h. After 10 min of shaking, the sample was centrifuged. Then, 2 mL of the prepared sample was evaporated with a nitrogen gas stream at room temperature. Next, the sample was derivatized by the MTBSTFA and maintained in a laboratory bain-marie for 10 min at 65 °C and rapidly injected into the GC–MS system. The concentration of TCS was reported as the sum of TCS concentration in liquid and solid phases.

GC–MS analysis

TCS concentration was analyzed by a GC–MS system (model 7890A Agilent Technologies, Palo Alto, CA, USA), interfaced with a mass selective detector (model 5975 Cinert). A fused silica capillary column (60 m × 0.25 mm i.d., 0.25 μm film thickness) was used and a carrier gas (helium ∼99.99%) was maintained at a flow rate of 1 mL/min and MS was run in a selected ion monitoring (SIM) mode (70 eV). Furthermore, the GC conditions were as follows: an injector temperature of 300 °C, an injection volume of 2 μL, and a split ratio of 5:1. The oven temperature was set at 80 °C for 1 min in the initial stage, to 270 °C at a rate of 10 °C/min; the final temperature was held at 270 °C for 2 min. In addition, the MS transfer line and ion source were kept at 300 and 230 °C, respectively. In the SIM mode for m/z 200, 345, and 347 for quantitative analysis.

Quality assurance/control

Quantitative analysis was directed via standard calibration. The concentration ranges of TCS were in the ranges of 0.1, 0.5, 1, 5, and 10 μg/L under the DLLME conditions for the liquid phase. In addition, the TCS concentration ranges of 1, 10, 50, and 100 μg/L were prepared in ethyl acetate for the solid phase. Linear regression analysis was applied and high correlation coefficients were attained (R2 ≥ 0.99) for all experiments. Recoveries were obtained by spiking 0.5, 1, and 10 μg/L of natural standards into randomly selected samples and three replicates were ready at each spiking level based on the guidelines developed by the International Conference on Harmonization (ICH 2005). The recovery of TCS was an average amount of 100% ± 6.5. The detection limit (LOD) and quantification limit (LOQ) were calculated according to the United States Geological Survey (USGS) and the United States Environmental Protection Agency (USEPA) guidelines. The LOD and LOQ of TCS were 0.04 and 0.11 μg/L, respectively. The relative standard deviations (RSDs) were used for precision expressions inter and intra-days, and were determined by examining the standard solution of 10 μg/L for 8 sequential days and 8 repeats in one day, respectively. The RSD amounts of inter and intra-days were 4.30 ≤ 8% and 5.30 ≤ 12%, respectively. According to the suggestion of Li et al. (2019), TCS concentrations below the LOD were kept in the record as one-half of LOD.

Risk assessment

The environmental risk assessment (ERA) method is an advantageous method to assess the potential risk of a chemical contaminant for aquatic organisms and humans by determining the risk quotient (RQ) (Kosma et al. 2014; Mohan & Balakrishnan 2019). In this study, ecotoxicological and human health risks were estimated according to the scenario of the potential of discharging secondary wastewater effluent into water resources.

Ecotoxicological risk assessment

The predicted TCS environmental concentration in surface water (PECwater) (μg/L) was calculated in accordance with Kosma et al. (2014) and Mohan & Balakrishnan (2019):
formula
(1)
Here, MECeff is expressed as wastewater effluent TCS environmental concentration (μg/L), SUSPwater is the river concentration of suspended solids (μg/L), DF is the factor of dilution, and Kpsusp is the coefficient of solids-water partitioning of suspended solids (L/Kg) which was calculated by Equation (2) (Mohan & Balakrishnan 2019):
formula
(2)

where Focsusp states the weight fraction of organic carbon in the suspended solids (kg/kg), and KOC denotes the coefficient of partition of organic carbon in water (L/kg).

The predicted no-effect concentration (PNEC) (μg/L) was estimated based on Equation (3) (Kosma et al. 2014; Mohan & Balakrishnan 2019):
formula
(3)
here, EC50 is the half maximum of effective concentration, LC50 is the 50% lethal concentration, NOEC is the no-observed-effect concentration, and AF is the assessment factor.
The risk quotient (RQ) was determined by Equation (4) (Kosma et al. 2014; Mohan & Balakrishnan 2019):
formula
(4)

Human health risk assessment

The estimated daily intake (EDI, μg/kg.day) of TCS for fish consumption is earned by Equation (5) (Mohan & Balakrishnan 2019):
formula
(5)
Here, ED refers to exposure duration, EF is exposure frequency, FIR is the rate of TCS ingestion via the consumption of fish, Cf refers to a factor for the conversion of fresh weight to dry weight as the 79% moisture content of the fillet of fish, WAB is the average of body weight for Iranian adults, and AT is the average time of exposure.
PECfish is the TCS environmental concentration of fish predicted as μg/kg:
formula
(6)
where PECwater is the TCS environmental concentration measured in the WWTP effluent (μg/L), BCFfish is the fish bioconcentration factor assessed based on log Kow, for BCFfish calculation, the biotransformation in fish is considered, and BMF is biomagnification factor to evaluate secondary poisoning for the fish-eating predator.
The RQ is the EDI of the TCS to its reference dosage (RfD) and was used to assess the human health risk:
formula
(7)

All of the input information for the estimation of the ecotoxicological and human health risks of TCS is presented in Table 2.

Table 2

Input parameters in risk assessment

ParametersNotationUnitsValuesReferences
Ecotoxicological risk assessment 
TCS concentration in the effluent MECeff μg/L WWTP1: Weibull (σ = 1.079 μ = 1.092); WWTP2: normal (σ = 0.816 μ = 0.830) This study 
Suspended matter concentration in the river SUSPwater μg/L 15 × 10−3 TGD (2003)  
Dilution factor DF – 1, 2, 10, 100, 1,000 Mohan & Balakrishnan (2019)  
The weight fraction of organic carbon in suspended matter Focsusp Kg/Kg 0.1 EPA (2003)  
Organic carbon water coefficient KOC L/Kg 8,417 EPA (2003)  
Assessment factor AF – 10,000 This study 
Algae 
Scenedesmus subspicatus EC50 (1) μg/L 0.007 Mohan & Balakrishnan (2019)  
Scenedesmus subspicatus EC50 (2) μg/L 0.014 
Scenedesmus subspicatus EC50 (3) μg/L 0.0548 
Pseudokirchneriella subcapitata EC50 (4) μg/L 0.051 
Selenastrum capricortunum EC50 (5) μg/L 5.3 × 10−3 
Crustaceans 
Chironomus tentans LC50 (1) μg/L Mohan & Balakrishnan (2019)  
Hyalella azteca LC50 (2) μg/L 
Daphnia Magna LC50 (3) μg/L 2.9 
Fishes 
Pimephales promelas LC50 (1) μg/L 36 Mohan & Balakrishnan (2019)  
Oryzias latipes LC50 (2) μg/L 3.52 
Danio rerio LC50 (3) μg/L 4.20 
Danio rerio LC50 (4) μg/L 0.26 
Pimephales promelas NOEC (5) μg/L 2.70 
Human health risk assessment 
TCS concentration in the effluent PECwater μg/L WWTP1: normal (σ = 1.150 μ = 1.063); WWTP2: Weibull (α = 0.00308 β = 0.499) This study 
Exposure duration ED years 53 Li et al. (2019)  
Exposure frequency EF days/year 365 
Ingestion rate of fish FIR g/person/day 10.7 Ebrahimi et al. (2019)  
Conversion factor Cf – 0.208 Mohan & Balakrishnan (2019)  
Average body weight WAB Kg Males: Uniform (a = 32.759 b = 117.36); Females: Gamma (3P)(α = 90.165 β = 1.3017 γ = −52.678) This study 
Average exposure time AT  ED × EF Mohan & Balakrishnan (2019)  
Fish bioconcentration factor BCFfish L/kg wet-weight 1,127 
Biomagnification factor BMF – 2 for log Kow = 4.5–5 
Reference dose RfDEPA (RfD1) μg/kg.day 300 List (2008)  
RfDMDH (RfD2) 47 Yost et al. (2017)  
RfDRodrics (RfD3) 470 Rodricks et al. (2010)  
ParametersNotationUnitsValuesReferences
Ecotoxicological risk assessment 
TCS concentration in the effluent MECeff μg/L WWTP1: Weibull (σ = 1.079 μ = 1.092); WWTP2: normal (σ = 0.816 μ = 0.830) This study 
Suspended matter concentration in the river SUSPwater μg/L 15 × 10−3 TGD (2003)  
Dilution factor DF – 1, 2, 10, 100, 1,000 Mohan & Balakrishnan (2019)  
The weight fraction of organic carbon in suspended matter Focsusp Kg/Kg 0.1 EPA (2003)  
Organic carbon water coefficient KOC L/Kg 8,417 EPA (2003)  
Assessment factor AF – 10,000 This study 
Algae 
Scenedesmus subspicatus EC50 (1) μg/L 0.007 Mohan & Balakrishnan (2019)  
Scenedesmus subspicatus EC50 (2) μg/L 0.014 
Scenedesmus subspicatus EC50 (3) μg/L 0.0548 
Pseudokirchneriella subcapitata EC50 (4) μg/L 0.051 
Selenastrum capricortunum EC50 (5) μg/L 5.3 × 10−3 
Crustaceans 
Chironomus tentans LC50 (1) μg/L Mohan & Balakrishnan (2019)  
Hyalella azteca LC50 (2) μg/L 
Daphnia Magna LC50 (3) μg/L 2.9 
Fishes 
Pimephales promelas LC50 (1) μg/L 36 Mohan & Balakrishnan (2019)  
Oryzias latipes LC50 (2) μg/L 3.52 
Danio rerio LC50 (3) μg/L 4.20 
Danio rerio LC50 (4) μg/L 0.26 
Pimephales promelas NOEC (5) μg/L 2.70 
Human health risk assessment 
TCS concentration in the effluent PECwater μg/L WWTP1: normal (σ = 1.150 μ = 1.063); WWTP2: Weibull (α = 0.00308 β = 0.499) This study 
Exposure duration ED years 53 Li et al. (2019)  
Exposure frequency EF days/year 365 
Ingestion rate of fish FIR g/person/day 10.7 Ebrahimi et al. (2019)  
Conversion factor Cf – 0.208 Mohan & Balakrishnan (2019)  
Average body weight WAB Kg Males: Uniform (a = 32.759 b = 117.36); Females: Gamma (3P)(α = 90.165 β = 1.3017 γ = −52.678) This study 
Average exposure time AT  ED × EF Mohan & Balakrishnan (2019)  
Fish bioconcentration factor BCFfish L/kg wet-weight 1,127 
Biomagnification factor BMF – 2 for log Kow = 4.5–5 
Reference dose RfDEPA (RfD1) μg/kg.day 300 List (2008)  
RfDMDH (RfD2) 47 Yost et al. (2017)  
RfDRodrics (RfD3) 470 Rodricks et al. (2010)  

Data analysis

The statistical analyses were analyzed with SPSS 22.0. The correlations between TCS concentration, temperature, EC, and pH were determined by Pearson correlation analysis. The Independent Samples Test (t-test) was done to evaluate the difference in parameters between two WWTPs. A significant P-value <0.05 was considered.

In the present study, the Monte Carlo (MC) simulation methods were employed by RStudio version 1.3.959 (Package ‘Monte Carlo’) and were run for 10,000 random values from the probability functions, and the probability distributions including normal, Weibull, Uniform, and Gamma were fitted to MECeff, PECwater, and WAB males and females, respectively. In addition, the Easyfit professional software Version 5.5 was applied for distribution fitting (Larionov et al. 2021). Moreover, the sensitivity analysis was completed based on Spearman's rank-order correlation to control the effect of the input variables on the calculated RQs (Al Garni & Awasthi 2020).

Occurrence of TCS in WWTPs

The presence of TCS in wastewater comes from the use of PPCPs, such as antibacterial products that are used in households and are washed away and end up in WWTPs through sewer networks. The resistance of TCS and other organic contaminants to microbial degradation and their low volatility properties make it harder for TCS to be removed through conventional wastewater treatment processes. In addition, the secondary treatment process in WWTPs consists of various methods, including an activated sludge reactor, a membrane bioreactor (anaerobic and aerobic), and a sequencing batch reactor. Research has shown that higher concentrations of triclosan (TCS) significantly hindered the acidification, methanogenesis, and solubilization steps in WWTPs. Moreover, the presence of TCS altered the microbial population in the activated sludge, leading to a decline in firmicutes and an increase in antibiotic-resistant and phenol-tolerant microbes. Consequently, these changes resulted in a decline in the removal of ammonia and also impacted the nitrification capacity (Yee & Gilbert 2016; Tan et al. 2021b). Furthermore, TCS comes out into surface waters due to the discharge of effluents of WWTPs. Therefore, regulatory monitoring of TCS in the environment, especially in the water and wastewater sources, is necessary (Kosma et al. 2014; Adhikari et al. 2022; Bakare & Adeyinka 2022). Results of the wastewater TCS concentration and physicochemical parameters of the influent and effluent samples are presented in Table 3. It was indicated that the concentration of TCS was 53.00 and 3.70 μg/L in the influent, whereas effluent samples had a concentration of 1.09 and 0.83 μg/L in WWTP1 and 2, respectively. The results showed that a substantial concentration of TCS is present in the wastewater samples of WWTP1. The WWTP1 probably received a higher volume of wastewater from some sources, such as industries, used detergents, several hospitals, medical clinics, and so on. Therefore, the consumption patterns of detergents by people who reside near the WWTP1 could be responsible for the increase in TCS concentration in this area (Bakare & Adeyinka 2022). In addition, differences in the consumption patterns, natures, volume and composition of influent flow being received, and type of treatment processes are other significant factors (Bester 2005; Lehutso et al. 2017). Some studies reported TCS concentration in the influent and effluent of WWTPs around the world (Table 4). According to Table 4, TCS concentration in WWTPs in Iran was higher than in most other countries.

Table 3

Mean ± standard deviation (SD) of TCS and physicochemical parameters in the WWTPs

PlantsParametersStreamMean ± SD
WWTP1 TCS Concentration (μg/L)a Ib 53.00 ± 73.08 
Ec 1.09 ± 1.25 
Temperature (̊C) Ic 26.18 ± 2.79 
Ed 26.62 ± 3.08 
EC (μs/cm) 1319.50 ± 65.37 
1295.25 ± 122.43 
pH 7.67 ± 0.19 
7.68 ± 0.34 
WWTP2 TCS Concentration (μg/L)b 3.70 ± 2.84 
0.83 ± 0.94 
Temperature (̊C) 26.93 ± 2.71 
27.30 ± 3.43 
EC (μs/cm) 1443.25 ± 101.36 
1438.25 ± 149.55 
pH 7.59 ± 0.14 
7.74 ± 0.04 
PlantsParametersStreamMean ± SD
WWTP1 TCS Concentration (μg/L)a Ib 53.00 ± 73.08 
Ec 1.09 ± 1.25 
Temperature (̊C) Ic 26.18 ± 2.79 
Ed 26.62 ± 3.08 
EC (μs/cm) 1319.50 ± 65.37 
1295.25 ± 122.43 
pH 7.67 ± 0.19 
7.68 ± 0.34 
WWTP2 TCS Concentration (μg/L)b 3.70 ± 2.84 
0.83 ± 0.94 
Temperature (̊C) 26.93 ± 2.71 
27.30 ± 3.43 
EC (μs/cm) 1443.25 ± 101.36 
1438.25 ± 149.55 
pH 7.59 ± 0.14 
7.74 ± 0.04 

aRemoval efficiency of TCS (R%) = 97.94

bRemoval efficiency of TCS (R%) = 77.59

cInfluent

dEffluent

Table 4

TCS concentration in influent and effluent of WWTPs reported around the world

StudyInfluent (μg/L)Effluent (μg/L)
This study (Isfahan, Iran) 3.70 – 52.99 1.09 – 0.83 
Bakare et al. (2022) (Durban, South Africa) 1.91 – 73.46 1.73 – 6.98 
Bernauer et al. (2021) (Luxembourg, Germany) 0.02 – 86.16 0.02 – 5.37 
Guerra et al. (2019) (Canada) 0.29 – 33.50 0.03 – 1.39 
Lehutso et al. (2017) (South Africa) 2.10 – 17.60 0.99 – 13.00 
Waltman et al. (2006) (North Texas, USA) 26.8 0.25 
Tran et al. (2016) (Singapore) 0.34 – 0.74 0.029 – 0.05 
Zhang et al. (2021) (Northern China) 0.3 ± 0.004 0.04 ± 0.003 
Nakada et al. (2010) (Germany) 1.86 – 26.8 0.027 – 2.7 
Kosma et al. (2014) (Greece) 0.11 – 0.68 ND* – 0.14 
StudyInfluent (μg/L)Effluent (μg/L)
This study (Isfahan, Iran) 3.70 – 52.99 1.09 – 0.83 
Bakare et al. (2022) (Durban, South Africa) 1.91 – 73.46 1.73 – 6.98 
Bernauer et al. (2021) (Luxembourg, Germany) 0.02 – 86.16 0.02 – 5.37 
Guerra et al. (2019) (Canada) 0.29 – 33.50 0.03 – 1.39 
Lehutso et al. (2017) (South Africa) 2.10 – 17.60 0.99 – 13.00 
Waltman et al. (2006) (North Texas, USA) 26.8 0.25 
Tran et al. (2016) (Singapore) 0.34 – 0.74 0.029 – 0.05 
Zhang et al. (2021) (Northern China) 0.3 ± 0.004 0.04 ± 0.003 
Nakada et al. (2010) (Germany) 1.86 – 26.8 0.027 – 2.7 
Kosma et al. (2014) (Greece) 0.11 – 0.68 ND* – 0.14 

*Not detected

The physicochemical parameters of wastewater samples investigated in this study are reported in Table 3. Moreover, some studies proved that TCS in water and wastewater was significantly correlated with physicochemical parameters (Wang et al. 2022; Moazeni et al. 2023). Among these parameters, EC relates to other nutrients such as ammonia, phosphate, and chloride that are the result of the presence of organic materials and ions (Bakare & Adeyinka 2022). According to Table 3, the EC values in the effluent samples were 1,295.25 and 1,438.25 μs/cm in WWTP1 and 2, respectively, which were higher than the WHO recommended value of 400 μs/cm (Bakare & Adeyinka 2022). In addition, an increase in EC values causes an increase in the concentration of organic materials such as TCS. These results indicate the necessity of investigating the risks related to organic materials such as TCS in wastewater.

Table 3 also revealed that the removal efficiency of TCS was 97.94 and 77.59% in WWTP1 and 2, respectively. As can be seen, there was a considerable decline in the TCS concentration in the influent to effluent samples in both WWTPs similar to the study by Bakare & Adeyinka (2022). This could be a result of the substantial quantities of TCS load in the influent of WWTPs. Furthermore, the treatment processes used in these WWTPs can remove large amounts of TCS. Thus, the effluent has a low concentration of TCS. Moreover, WWTP1 is an ancient treatment plant, nonetheless, its processes have been upgraded in recent years. Some of these upgrades include reducing a significant part of its inlet hydraulic load owing to setting up a new treatment plant, using diffuser aerators in the aeration pond, covering the ponds with the help of fiberglass caps, and changing the sludge return ratio to the aeration pond. The results of the qualitative analysis of effluent also show that its quality is better than WWTP2. In contrast, the effluent of WWTP2 does not have a high quality due to the high volume of treatment, the wear and tear of the equipment, although it is newer, and the local officials also emphasize this low quality and are trying new application methods for improving it. This result is in agreement with some studies reported elsewhere such as in Kumar et al. (2010), who reported that the TCS concentration had an important decline from 5.213 μg/L in influent to 0.18 μg/L in effluent samples. Moreover, Archana et al. (2017) and Zhang et al. (2021) reported 55–62% and 87% removal efficiency of TCS in Nagpur, India and Northern China WWTPs, respectively.

Risk assessment of TCS

The present study was performed to evaluate the risk of TCS exposure via the secondary-treated wastewater effluent of conventional activated sludge WWTPs in the aquatic environment.

Ecological risk assessment

In this study, the RQ method was applied to determine ecotoxicological risk by assessing the PECwater and PNEC as the exposure to hazardous concentrations of TCS to the algae, crustaceans, and fishes for the effluent of WWTPs. For RQs calculation, acute toxicity (EC50/LC50) was used because of the lack of chronic toxicity (NOEC) data presented in a similar study. Moreover, DF has a crucial role in the calculation of RQ, therefore, the RQs were estimated based on each DF (Mohan & Balakrishnan 2019). The box plots of RQs values for TCS in algae, crustaceans, and fishes in WWTP1 and 2 are shown in Figure 1. According to the results of WWTP1, the highest RQ value is observed for algae with a mean of 1.1 (95% CI: 0.48–2.62) and 1.45 (95% CI: 0.64–3.46) for lower DF with EC50 (1) (R1(A1)) and EC50 (5) (R1(A5)), respectively. Furthermore, the highest RQ seen for crustaceans and fishes with lower DF was 0.0027 with LC50 (3) (R1(C3)) and 0.03 with NOEC (5) (R1(C3)), respectively. Besides, results of WWTP2 indicated that RQ values for lower DF had higher RQ than others. However, all of them had RQ values lower than 0.01 with minimal risk of TCS exposure from wastewater effluent. Based on the risk ranking criteria, an RQ value higher than 1 indicates high risk (Bakare & Adeyinka 2022). Results indicate that algae will be at risk of TCS exposure through effluent of WWTP2 among sensitive species which have been investigated in this study. Some studies such as Mohan & Balakrishnan (2019) and Thomaidi et al. (2017) reported similar results. The most sensitive species appeared to be algae, as TCS presented significant acute and chronic ecotoxicological risks to them.
Figure 1

The Box plots of estimated ecotoxicological risk (RQs) for WWTP1 and 2.

Figure 1

The Box plots of estimated ecotoxicological risk (RQs) for WWTP1 and 2.

Close modal
The sensitivity analysis was achieved by the Spearman rank correlation coefficient to define the contribution of input factors to the variability of RQ (Thomaidi et al. 2017). According to Figure 2, results revealed that for both WWTPs, PECwater, MECeff, and EC50/LC50 were the most influential factors for algae, crustaceans, and fishes. Furthermore, Thomaidi et al. (2017) reported that the MECeff and EC50/LC50 were the most important variables in the estimated RQ for Daphnia Magna and fish.
Figure 2

The Spearman's rank correlation between the input factors and ecotoxicological risk (RQs).

Figure 2

The Spearman's rank correlation between the input factors and ecotoxicological risk (RQs).

Close modal

Humans health risk assessment

Because of biomagnification, TCS bioaccumulates in the human body through fish consumption and poses a great concern about its effects on human health (Kosma et al. 2014; Mohan & Balakrishnan 2019). In this study, PECfish was calculated based on TCS concentration in wastewater effluent for both WWTPs. This amount was 2,887.34 μg/kg (95% CI: 1,252.87–8,732.99) and 169.59 μg/kg (95% CI: 106.45–340.28) for WWTP1 and 2, respectively.

In this study, the human RQ of TCS was estimated as a non-cancer risk because there is no evidence that TCS is carcinogenic in humans (Yost et al. 2017). Meanwhile, there is no RfD value available for TCS at the USEPA IRIS site and USEPA regional screening level tables. So, the human risk of TCS exposure via fish consumption was estimated by the RfDs amounts of USEPA (300 μg/kg-day) (RfD1), MDH (47 μg/kg-day) (RfD2), and Rodricks (470 μg/kg-day) (RfD3) (List 2008; Rodricks et al. 2010; Yost et al. 2017). Figure 3 shows box plots of RQs for males and females in both WWTPs. According to Figure 3, the mean of RQ1, RQ2, and RQ3 values for males were 0.33 (95% CI: 0.12–2.38), 2.07 (95% CI: 0.79–15.21), and 0.21 (95% CI: 0.08–1.52), respectively in WWTP1. Moreover, these amounts in WWTP2 were 0.02 (95% CI: 0.01–0.06), 0.12 (95% CI: 0.06–0.39), and 0.012 (95% CI: 0.012–0.06), respectively. Based on Figure 3, the mean of RQ1, RQ2, and RQ3 values for females from WWTP1 were 0.35 (95% CI: 0.15–1.65), 2.20 (95% CI: 0.93–10.50), and 0.22 (95% CI: 0.093–1.05), respectively. In addition, these values were 0.02 (95% CI: 0.01–0.06), 0.13 (95% CI: 0.08–0.39), and 0.013 (95% CI: 0.008–0.039), respectively. The results of this study indicate that the RQ value for males and females in WWTP1 was higher than 1 with consideration of RfDMDH (RfD2), so they will be at risk of non-carcinogenic effects of TCS. However, Mohan & Balakrishnan (2019) reported that human health risks through TCS accumulating in fish from wastewater effluent were not concerning.
Figure 3

The Box plots of estimated human health risk (RQs) for WWTP1 and 2.

Figure 3

The Box plots of estimated human health risk (RQs) for WWTP1 and 2.

Close modal
The sensitivity analysis based on Figure 4 indicates that for both WWTPs, TCS concentration in the effluent of wastewater was a more important parameter than WAB and RfD.
Figure 4

The Spearman's rank correlation between the input factors and human health risk (RQs).

Figure 4

The Spearman's rank correlation between the input factors and human health risk (RQs).

Close modal

The presence of TCS, its inclination to accumulate in living organisms (including human milk), and its dioxin-like transformation products raise significant worries regarding its potential effects on the health of both humans and the ecosystem (Kosma et al. 2014). Indirect entry into the body can occur through the consumption of fish, meat, and vegetables exposed to TCS. The human body possesses the ability to efficiently absorb, circulate, and metabolize TCS within its system (Ramirez-Vargas et al. 2017). In addition, under specific conditions, it has the ability to facilitate the generation of chloroform. Personal hygiene items like soaps and detergents have the potential to react with water containing chlorine, resulting in the excessive production of chloroform due to the presence of TCS. The unregulated formation of chloroform in this manner poses a carcinogenic risk to the human body (Ben et al. 2016). Moreover, the capability of TCS to bind to the specific receptors for the thyroid is due to its similar structure to that of the thyroid hormone. Consequently, this hinders the actual thyroid hormone from binding to the receptors (Braun et al. 2018).

Recommendations

According to the risk assessment results of the present study and other similar studies (Brausch & Rand 2011; von der Ohe et al. 2012), TCS was found to be the compound with the highest contribution and environmental risk. It was observed that TCS has the ability to enter and disperse in the environment, and it exhibits a higher level of persistence than originally anticipated. Furthermore, TCS poses the highest risk to aquatic environments among all the potential PPCPs. Therefore, TCS should be given serious consideration as a candidate for regulatory monitoring and prioritization at the world level, taking into account realistic Predicted No-Effect Concentrations (PNECs) (Brausch & Rand 2011; von der Ohe et al. 2012). In addition, based on the aforementioned findings, it is imperative to acknowledge that TCS could potentially present a significant ecological hazard to aquatic ecosystems. It is recommended that measures be taken to mitigate and decrease its concentration levels in both treated wastewater and the surrounding surface water. A thorough debate is suggested taking place within the scientific community regarding the necessity of upgrading WWTPs in order to achieve effective removal of micropollutants. In addition, analysis of the mass balance of TCS in both conventional and full-scale wastewater treatment systems is recommended (Thomaidi et al. 2017). It is suggested that forthcoming studies could focus on the detection and estimation of risk of the main intermediate products including methyl-triclosan (M-TCS), 2,4 dichlorophenol (2,4 DCP), and dioxins (e.g., 2,8-dichloro-dibenzo-p-dioxin). Additionally, the detection of TCS in the wastewater sludge of WWTP1 and 2 is recommended. Moreover, this study estimated the toxicity risk of TCS in the effluent of WWTP in four groups including algae, crustaceans, fishes, and humans (males and females) as bioindicators based on risk assessment formulas. Furthermore, the limitation of this study was the lack of access to determine risk assessment relationships for exposure to TCS in wastewater effluent through agricultural applications such as the consumption of vegetables irrigated with wastewater effluent. It is recommended that future studies focus on this issue, too.

This study has surveyed the occurrence of TCS in two WWTPs in Isfahan, Iran, using DLLME/GC/MS. Results showed that the TCS removal efficiency was 97.94 and 77.59% in WWTP1 and 2, respectively. Furthermore, ERA was conducted using the RQ procedure to assess the exposure to TCS associated with the effluent of WWTPs for algae, crustaceans, fishes, and humans (males and females). It is proved that the lower dilution factor (DF = 1) had a higher RQ value in ecotoxicological risk estimation. In addition, the algae had a risk higher than 1 in WWTP1, and others had a lower risk value of TCS exposure. Moreover, males and females will be at risk of TCS exposure when RfD considers 47 μg/kg.day in WWTP1. According to the results of the ERA, the concentration of TCS in the effluent of WWTPs was an effective factor in the change of risk value (RQ). Therefore, advanced treatment processes are required to completely remove TCS from wastewater.

This research was supported by grants from the Isfahan University of Medical Sciences (Grant No. 298027 and No. 1401267) and was approved by the Ethical Committee of Isfahan University of Medical Sciences (IR.MUI.RESEARCH.REC.1398.219 and IR.MUI.RESEARCH.REC.1401.061). The authors also would like to acknowledge the financial support of Iran's National Elites Foundation for the present project. Additionally, they would like to thank the Isfahan Water & Wastewater Company and the manager and staff of the WWTPs for their collaboration.

All relevant data are included in the paper or its Supplementary Information.

The authors declare there is no conflict.

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