In recent decades, increasing attention has been directed toward the effects of alkylphenols and bisphenols due to their demonstrated endocrine-disruptive effects. This study investigated the occurrence and potential risk assessment of two alkylphenols and seven bisphenols in surface water collected from rivers (Cau River, Duong River, and Thai Binh River) flowing through Bac Ninh province, one of the pivotal economic regions in the North of Vietnam. The results demonstrated that these compounds were widely distributed in the rivers. The average concentrations were ranked as follows: 4-tert-octylphenol (4-t-OP) (91.2 ng/L) > 4-nonylphenol (4-NP) (78.9 ng/L) > bisphenol S (BPS) (72.4 ng/L) > bisphenol A (BPA) (5.6 ng/L) > bisphenol F (BPF) (below method detection limit) with detection frequencies of 100% (except for BPF of 23%). The presence of alkylphenols and bisphenols in aquatic environments closely correlates with anthropogenic activity. The environmental risk assessment was carried out based on the Risk Quotient (RQ) evaluation, indicating that 4-NP poses medium risk in all three rivers. In addition, 4-t-OP, which is more toxic than 4-NP, poses high risk to aquatic organisms in the Duong River (RQ = 1.1), while BPA and BPS show low risk to aquatic organisms in three rivers (RQ < 0).

  • Validation of an LLE-UPLC-MS/MS method for determination of EDCs compounds in surface water.

  • APs were found at higher concentration than BPs.

  • A significant correlation was observed between contamination concentration and industrial activities.

  • The Cau River and the Duong River have found higher concentration of APs and BPs than the Thai Binh River.

Over the past two decades, there has been a significant surge in industrial production in Vietnam, necessitating the utilization of a large quantity of chemical substances and cutting-edge technology. A prime illustration of this phenomenon is the widespread use of plasticizers, which are additives incorporated into plastic manufacturing processes to enhance characteristics like flexibility, stability, and durability. These additives, such as bisphenol A (BPA) and alkylphenols (APs), are considered endocrine-disrupting chemicals (EDCs) (Salgueiro-González et al. 2017) that interfere with the biosynthesis, metabolism, or hormone system (Lu et al. 2013). Therefore, in Directive 2013/39/EU, 4-tert-octylphenol (4-t-OP), and 4-nonylphenol (4-NP) have been included in the list of 45 priority substances set in the new European water legislation (Kern 2014). However, these compounds are still found in the environment, especially in industrial wastewater (0.5–1.1 μg/L for NP, Japan), rivers (0.029–2.591 μg/L for NP, 0.011–0.35591 μg/L for OP, Hong Kong), and sediments (16.6–203.8 μg/L for NP, not detected (ND)–2.6 for OP, China) (Chokwe et al. 2017). According to the guidelines set by the European Food Safety Authority (50 μg/kg (body weight)/day for BPA) and the Danish Institute of Safety and Toxicology (5 μg/kg (body weight)/day for NP) and OP is unavailable (Ademollo et al. 2008). The levels of intake and concentrations of grains, livestock, and seafood play a crucial role in determining the overall risk associated with NP and BPA (Ademollo et al. 2008).

APs are a group of organic compounds obtained by the alkylation of phenols. Among them, 4-t-OP and 4-NP are the most used in industrial and household applications, with more than 80% of the total APs production used in applications for both industrial and commercial production of textiles, paper, food, or beverage packaging (Ying et al. 2002). Furthermore, APs are also the main degradation product of alkylphenol ethoxylates (APEO), one of the most widely used classes of surfactants as detergents, dispersants, emulsifiers, solubilizers, and foaming agents (Salgueiro-González et al. 2017). These compounds are less degraded in water and can be easily accumulated in biological tissues because of their lipophilicity (Selvaraj et al. 2014). Significantly, both 4-NP and 4-t-OP have been categorized as definitely endocrine disrupting, particularly in aquatic organisms. These chemical substances are capable of causing adverse effects on the reproductive system of aquatic organisms such as fish (Yusoff et al. 2017). They could affect the organism via binding receptors or hormone-binding proteins in the body by mimicking the effects of endogenous hormones (Beek 2000).

Furthermore, bisphenols (BPs) with two benzyl rings in the structure have many analogs, connected by a differently substituted bridging atom, mainly a carbon atom, with the exceptions of bisphenol P (BPP) and bisphenol S (BPS). BPA was used as a monomer to produce epoxy resins, phenolic resins, polycarbonate resins, polyester, and lacquer coatings for food cans (Salgueiro-González et al. 2012). BPA has received great attention due to its potential association with adverse health effects such as prostate cancer, breast cancer, obesity, and neurological and reproductive problems (Fu & Kawamura 2010). As a result, other compounds such as bisphenol B (BPB), BPS, bisphenol F (BPF), bisphenol AF (BPAF), bisphenol P (BPP), and bisphenol AP (BPAP), which were used to replace BPA in plastic production, have been also found in water and sediment, providing evidence for their widespread use (Gao et al. 2023). Recent studies indicate that these alternative compounds also show some negative effects on androgen receptor (AR) and estrogen receptor (ER) activity as well as synthetic steroid hormones, in the delayed hatching of zebrafish (Shi et al. 2015).

Various chromatography techniques have been employed to analyze APs and BPs on a global scale (Xie et al. 2006; Shao et al. 2007; Zhao et al. 2009; Yang et al. 2014). Gas chromatography (GC) is currently recognized as a suitable method for identifying diverse organic contaminants in different environmental matrices, as evidenced by the research studies of Duong et al. (2010) and the study of Česen et al. (2019). This technique usually requires an additional derivatization step, which is time-consuming, loss of analytes, and contamination from materials and the environment. Nowadays, liquid chromatography is considered a powerful technique for APs and BPs analysis (Shao et al. 2007; Jin & Zhu 2016; Liu et al. 2016; Salgueiro-González et al. 2017). Liquid chromatography combined with ultraviolet/fluorescence (UV/FLD) detectors is not recommended to quantify APs and BPs in the environmental sample due to the overlapping of analytes with similar properties, poor sensitivity of UV detector, or matrix effect to the emission of analytes with FLD detector (Zhao et al. 2009). Therefore, liquid chromatography coupled with mass spectrometry (LC-MS/MS) is currently the most powerful technique for analyzing APs and BPA in environmental matrices (Shao et al. 2007; Pérez-Palacios et al. 2012; Salgueiro-González et al. 2012). Effective sample preparation to remove possible interferences and pre-concentration of analytes are also mandatory to achieve the required levels. Techniques such as liquid phase extraction (LLE) (Xie et al. 2006), solid phase extraction (SPE) (Liu et al. 2016), ultrasonic extraction (USE) (Pérez-Palacios et al. 2012), and accelerated solvent extraction (ASE) (Shao et al. 2007) are usually applied to enrich these analytes in different matrices.

The objective of this study was to validate a simple LLE combined with an LC-MS/MS method to determine two APs and seven BPs in surface water (Supplementary Figure S1). This research aimed to gain knowledge of the occurrence and level of these compounds in the environment and environmental risk assessment. The results from this study will be valuable to help the corresponding management and conservation policies in this area, which locates a huge number of industrial enterprises.

Targeted compounds, chemical reagents, and solvents

High purity standards (purity >98%) for nine targeted compounds (4-NP, 4-t-OP, BPA, BPS, BPF, BPB, BPP, BPAP, and BPAF) and internal standards (4-NP-D4, BPA-D8, and BPS-D8) were purchased from Cluzeau Info Labo (CIL, Sainte-Foy-La Grande, France). Organic solvents (acetonitrile, methanol, dichloromethane, and hexane) used for sample processing and LC-MS/MS analysis were purchased from Sigma-Aldrich (Singapore). Ultrapure water (18.2 MΩ cm−1) was produced from the Smart 2 pure 12 UV water purification system (Thermo, England) and was used throughout this study. Ammonium acetate used for the mobile phase was purchased from Merck (Germany).

Study sites and sample collection

Bac Ninh Province is one of the pivotal economic regions within the Hong River Delta, beside Hanoi. With three large river systems flowing through, namely the Cau River, spanning 70 km and having an annual water volume of approximately 5 billion m3; the Thai Binh River, stretching 17 km and having an annual water volume of approximately 35.95 billion m3; and the Duong River, with a length of 42 km and an average total water volume of 31.6 billion m3. This river system has an estimated overall surface water flow of about 177.5 billion m3, with 176 billion m3 of water contained within the rivers. This abundant water supply plays an important role in the province's irrigation, drainage, and water management.

Field cruises were performed from June to July 2021 aboard a fishing ship. Samples were taken only at the subsurface (20–50 cm depth) while in the three rivers. Twenty-six surface water samples (500–1,000 mL) were collected manually from the edge of the ship (Figure 1) including stations R1–R8 in the Cau River, R9–R20 in the Duong River, and R21–R26 in the Thai Binh River, which is the combination of the Cau River and the Duong River. All samples were kept in glass bottles pre-combusted at 450 °C for 6 h, rinsed several times with field samples, and stored at 4 °C in the dark until returned to the laboratory using cold boxes.
Figure 1

Sampling sites for three rivers flowing through Bac Ninh province (the balloons illustrate the sampling sites, Cau River in blue, Duong River in yellow, and Thai Binh River in green).

Figure 1

Sampling sites for three rivers flowing through Bac Ninh province (the balloons illustrate the sampling sites, Cau River in blue, Duong River in yellow, and Thai Binh River in green).

Close modal

Sample preparation and analysis

Sample preparation

At the laboratory, the samples were filtered using a GF/F filter (Whatman, Ø 47 mm, pore size < 0.7 μm, pre-combusted at 450 °C for 6 h) with the help of a vacuum pump. The filtered samples were stored at 4 °C and analyzed within 48 h or stored at −80 °C for further analysis.

A 200 mL filtered sample was spiked with a solution of internal standards (15 μL each of 1 mg/L 4-NP-D4, BPS-D8, and BPA-D8). This sample was then extracted by liquid–liquid extraction with 3 × 10 mL of dichloromethane, shaken vigorously for 10 min each time. Next step, the sample was allowed to stand until the aqueous phase and the organic phase completely separated. The organic phase was collected into a glass tube, evaporated under a gentle stream of nitrogen until dryness, and then reconstituted to 3 × 100 μL of H2O/acetonitrile (ACN) (30/70, v/v). Finally, the solutions were filtered using a syringe with a 0.2 μm pore size and subjected to the LC-MS/MS system under optimal operating conditions.

Instrumental analysis

Shimadzu Nexia (Shimadzu, Japan) was utilized for APs and BPs compound separation. The targeted compounds were separated by a reverse phase column (Waters BEH® C18, 100 mm × 2.1 mm, 1.7 μm particle size) with a guard column (20 mm × 2.1 mm, 0.22 μm filter). The mobile phase consisted of 2 mM ammonium acetate buffer (pH 6.90) (channel A) and 2 mM ammonium acetate in acetonitrile (channel B). The gradient was started with 50% channel B and kept at this proportion for 0.5 min, then the percentage of channel B was linearly increased to 95% in 6 min and kept at this condition for 2 min before returning to the initial condition and waiting for the next injection. The total running time was 12 min. The column chamber was constantly kept at 40 °C and the injected volume was 20 μL. The separation was adopted from Loos et al. (2007), with slight adjustments made to the LC conditions (column, mobile phase) and MS conditions. The tandem mass spectrometer (Shimadzu 8050) equipped with an electrospray ionization (ESI) source was set up at −3 kV for capillary voltage. The temperatures of the ion source, nebulizer gas, drying gas flow, and heating gas flow were all optimized and maintained at 300 °C, 3 L min−1, 10 L min−1, and 10 L min−1, respectively. The LC-MS/MS working conditions are detailed in Supplementary Table S1.

Target compounds were optimized to achieve the highest sensitivity via compound optimization function with flow injection experiments. Two transitions were selected and monitored using multiple reaction monitoring (MRM). All optimized parameters of the mass spectrometry, such as precursor ion, product ion, collision energy, and Q1 and Q3 bias for all analytes, are listed in Supplementary Table S2. The LC-MS LabSolution software (Shimadzu, Japan) was used for the acquisition and evaluation of data. Peak integration was based on the unit resolution for both precursor and product ions.

Methodology

Optimization of sample preparation

Solvents play important roles in extracting and separating specific matrix to determine the targeted compounds, which have been used in previous research, such as dichloromethane (DCM) (Amiridou & Voutsa 2011; Elobeid et al. 2012), n-Hexane (Xie et al. 2006), DCM: n-Hexane (2:1, v:v) (Oketola & Fagbemigun 2013) for the LLE of APs and BPs. Three types of solvents were employed to optimize extraction processes at the final spiking concentration of 50 ng/L. The recovery of all targeted compounds after LLE with 3 × 10 mL n-Hexane has shown high efficiency with BPS, BPF, and 4-NP; however, this method was not suitable for other compounds, especially BPA, with a recovery rate lower than 20% (Figure 2). The second method with 2 × 10 mL DCM and then 10 mL n-Hexane provided a stable recovery rate of more than 50% for all targeted compounds. According to AOAC (2016), the recovery rate must be no higher than 120%, so the solvent combination (2 × 10 mL DCM and 10 mL n-Hexane) is unacceptable for liquid–liquid extraction of BPA and BPAP. In contrast, the third extraction method with 3 × 10 mL DCM provided higher recovery rates, more than 70% and less than 120% (AOAC 2016). Thus, the DCM extraction method has been applied to this study.
Figure 2

Recoveries of alkylphenols and bisphenols at 50 ng/L with three different solvent proportions.

Figure 2

Recoveries of alkylphenols and bisphenols at 50 ng/L with three different solvent proportions.

Close modal

Matrix effect and recovery of sample preparation

Ionization suppression/enhancement is a typical phenomenon in tandem mass spectrometry procedures utilizing soft ionization techniques such as electrospray ionization and atmospheric pressure chemical ionization. Ionization suppression/enhancement can have an impact on targeted compound recovery as well as the method's robustness and ruggedness (Furey et al. 2013). In this study, ionization suppression and enhancement were assessed by using a total of 15 pooled samples that were produced and divided into three subsamples. The first subsample contained only spiked internal standards (the concentration of all internal standards in the final solution was 50 ng/L), and the second subsample contained both spiked internal standards and standards before extraction (concentration of all internal standards and native standard in the final solution was 50 and 50 ng/L, respectively), and the third subsample contained both spiked internal standards and standard before extraction. All samples were extracted by LLE with 3 × 10 mL DCM and measured under the optimal experimental/instrumental conditions outlined above. The recovery was estimated by comparing the difference between the extraction spiking experiment and the theoretical value. The total recovery (R%), matrix effect (ME%), and extraction efficiency (RE%) were evaluated and computed according to Vu-Duc et al. (2019). Figure 3 illustrates that ME%, RE%, and R% of all targeted compounds were in the range of 92.4–115.3%, 77.8–110.4%, and 80.2–105.7%, respectively. The matrix effect of these compounds (ME% = 92.4–115.3%) was still in an acceptable range (from 80 to 120%), according to Vu-Duc et al. (2019). The experimental results indicated that ionization suppression/enhancement had no significant impact on the total recoveries of practically all analytes (Vu-Duc et al. 2019). Consequently, the developed method was utilized to quantify APs and BPs in water samples.
Figure 3

Overall recovery (R), extraction efficiency (RE), and matrix effect (ME) of all targeted compounds,.

Figure 3

Overall recovery (R), extraction efficiency (RE), and matrix effect (ME) of all targeted compounds,.

Close modal

Method validation and quality control

Methods were validated according to the AOAC International guidelines (AOAC 2016) using linearity, method detection limit (MDL), instrumental detection limit (IDL), correlation, and recovery tests. Linearity was studied using a mixture of standard solutions. The calibration curves were prepared based on the response (ratio between the peak area of investigated APs, BPs, and their corresponding internal standards) and working solution concentration. The linear range was investigated over a six-point calibration ranging from 1 to 500 μg/L. The IDL was based on a signal-to-noise (S/N) ratio of samples with a low concentration of each AP and BP and the establishment of the minimum concentration at which the analyte could be reliably detected or quantified. IDL values were calculated using the equation (Rao 2018):
formula

Recoveries were validated at three concentration levels (low, medium, and high). The MDL and MQL were determined using a signal-to-noise ratio of 3 and 10, respectively, and on a real sample matrix. If any compound was not detected in the real sample, the MDL and MQL were then calculated based on the spiked sample.

Potential risk assessment

The environmental risk assessment was conducted using a risk quotient (RQ) methodology, as recommended by the European Commission's Risk Assessment Guidelines from 2004 (Janssen et al. 2004). RQ serves as a valuable tool for evaluating the potential ecological risks posed by contaminants in aquatic ecosystems (Hong et al. 2022).

The calculation of the RQ involves the following equation:
formula
(1)
where RQ represents the risk quotient, MEC stands for the measured environmental concentration, and PNEC corresponds to the predicted no-effect concentration. To categorize the level of risk, the RQ values are divided into three distinct categories (Zhao et al. 2019):
  • RQ < 0.1 indicates a negligible risk,

  • 0.1 ≤ RQ ≤ 1.0 suggests a moderate risk, and

  • RQ > 1.0 signifies a high risk to aquatic species.

Method validation

Calibration curves and linearity

During the investigation of the linear range, a calibration curve was established using seven different concentration levels ranging from 1 to 500 μg/L. The analyte concentrations were evaluated using corresponding internal standards 4-NP-D4, BPA-D8, and BPS-D8, and each calibration point was fixed at the concentration of 50 μg/L. An eight-point calibration was prepared daily in ultrapure water and injected three times into the LC-MS/MS system under optimal conditions. The standard curve demonstrated the relationship between the peak area ratio and the concentration of analytes, and it was found to be a linear function. The peak area ratio was calculated by dividing the peak area of compounds by the peak area of the appropriate isotopic labeled internal standard. The results, as shown in Supplementary Table S3, indicate a rather strong correlation coefficient R2, which falls within the range of 0.99 < R2 < 1.

Instrument detection limit and method detection limit

Supplementary Table S3 shows the results of calculating the instrument detection limit (IDL) and MDL. IDL values are computed by measuring the noise-to-signal ratio of the lowest/known concentration of linearity samples, whereas MDLs were estimated from actual or spiked samples and both were expressed as concentrations (ng/L) (Rao 2018). The analytes demonstrated good sensitivity to MDL in the region of 0.02–0.88 ng/L. The new method's sensitivity was equivalent to those in recent studies and adequate for the analysis of these APs and BPs in surface water (Loos et al. 2007; Yang et al. 2014).

Recoveries

To validate the method recovery (%), a mixed standard (APs, BPs, and their corresponding internal standard) was spiked into the ultrapure water. The extraction process was performed as mentioned above. Table 1 illustrates the recoveries for spiked analytes at different concentrations (5, 50, and 100 ng/L).

Table 1

Recovery of targeted compounds at different concentration levels

CompoundRecoveries
5 ng/L50 ng/L100 ng/L
BPS 103.9 ± 4.2 104.9 ± 14.0 109.8 ± 11.0 
BPF 60.7 ± 14.4 70.1 ± 15 75.2 ± 6.4 
BPA 96.3 ± 11.2 105.9 ± 2.7 110.5 ± 14.2 
BPAF 53.5 ± 14.0 87.3 ± 6.6 73.4 ± 6.3 
BPB 94.6 ± 14 107.5 ± 5.1 99.8 ± 11.0 
BPAP 50.4 ± 3.4 88.5 ± 10.5 79.0 ± 5.6 
BPP 84.44 ± 8.6 84.7 ± 0.66 50.5 ± 13.3 
4-NP 79.5 ± 13.6 88.7 ± 4.0 61.5 ± 0.2 
4-t-OP 83.7 ± 3.7 90 ± 7.2 76.3 ± 2.8 
CompoundRecoveries
5 ng/L50 ng/L100 ng/L
BPS 103.9 ± 4.2 104.9 ± 14.0 109.8 ± 11.0 
BPF 60.7 ± 14.4 70.1 ± 15 75.2 ± 6.4 
BPA 96.3 ± 11.2 105.9 ± 2.7 110.5 ± 14.2 
BPAF 53.5 ± 14.0 87.3 ± 6.6 73.4 ± 6.3 
BPB 94.6 ± 14 107.5 ± 5.1 99.8 ± 11.0 
BPAP 50.4 ± 3.4 88.5 ± 10.5 79.0 ± 5.6 
BPP 84.44 ± 8.6 84.7 ± 0.66 50.5 ± 13.3 
4-NP 79.5 ± 13.6 88.7 ± 4.0 61.5 ± 0.2 
4-t-OP 83.7 ± 3.7 90 ± 7.2 76.3 ± 2.8 

The recoveries for APs and BPs range from 50.4 to 110.5% with low relative standard deviations (RSDs) (<20%). The recovery in this study to the confidence intervals of AOAC standards was equivalent to those in recent studies for the analysis of these APs and BPs in surface water (Zheng et al. 2019). Besides, lower RSD (<20%) demonstrates good reproducibility and consistency (AOAC 2016). Therefore, the proposed method is accepted for the analysis of real water samples.

Occurrence of APs and BPs in surface water

The concentrations of various APs and BPs are presented in Figure 4. Out of the nine target compounds, only five were detected (including 4-NP, 4-t-OP, BPA, BPS, and BPF). 4-NP, 4-t-OP, BPA, and BPS were consistently detected in all samples, while BPF was found in only 23% of the total samples. The average concentrations of the detected compounds were ranked as follows: 4-t-OP (91.2 ng/L) > 4-NP (78.9 ng/L) > BPS (72.4 ng/L) > BPA (5.6 ng/L) > BPF (<MDL). In this study, the presence of APs and BPs contamination in aquatic environments is a result of anthropogenic activity. Because APs and BPs are not naturally occurring and are solely a byproduct of human activity (Zhu & Zuo 2013; Zaborowska et al. 2023). The predominant sources of APs and BP contamination include manufacturing facilities, waste disposal sites, wastewater discharges, and sewage treatment plants (Zhu & Zuo 2013; Zaborowska et al. 2023).
Figure 4

Distribution of alkylphenol (AP) and bisphenol (BP) analogs in rivers passing through Bac Ninh province in Vietnam in different sample sites.

Figure 4

Distribution of alkylphenol (AP) and bisphenol (BP) analogs in rivers passing through Bac Ninh province in Vietnam in different sample sites.

Close modal

Interestingly, the distribution of these compounds' concentration follows an inverted ‘W’ shape (Figure 4), indicating complex influences on their occurrence (Wang et al. 2016). The total average concentrations of the Cau River (313.1 ng/L) and the Duong River (243.1 ng/L) are higher than that of the Thai Binh River (157.034 ng/L). Due to the primary sources of industrial activity (industrial production of textiles and paper, agriculture, metal, and plastic manufacturing) in the Bac Ninh province being located along the banks of the Duong River and the Cau River. On the banks of these rivers it was observed that there were many various residential areas, agricultural areas, discharge points, hospitals, factories, sewage plants, and craft villages.

Thuan Thanh District (TT) and Tien Du District (TD) have industrial areas located on both banks of the Duong River. The data indicates that the concentration of water pollution in Thuan Thanh is relatively lower than that in Tien Du. Specifically, the total average concentration in Thuan Thanh is recorded at 181.4 ng/L while that in Tien Du stands at 344.8 ng/L. The reason for this difference is Tien Du's strong industrial activities in producing consumer goods, garments, agricultural products, and food. These industries are sources of emissions that contribute to increased concentrations of AP and BP in water, harming the environment. On the other hand, in Thuan Thanh there are industries with high technology, clean production, and eco-friendliness, such as electronics, telecommunications, pharmaceuticals, supporting industries, new materials, and equipment manufacturing.

The progressive decrease in total average concentration from the Duong River's midstream to the Thai Binh River may be due to natural river mixing, pollution dispersion in the direction of water flow, and other causes (Bielski 2021). Other natural variables include (i) the high average temperature of the tropical monsoon climate of Vietnam can promote degradation of slowly biodegraded trace organics and (ii) high discharge of rivers may dilute these trace pollutants (Le Thi Minh et al. 2016).

4-Nonylphenol (4-NP) has been detected in a few studies on water environments in Vietnam, with concentrations ranging from 16.8 to 18.4 ng/L, which is located in the downstream sites of Sai Gon and Dong Nai Rivers (Duong et al. 2010). In this study, 4-NP has been quantified with average concentrations of 134.2, 59.7, and 40.0 ng/L corresponding to three rivers: Cau River, Duong River, and Thai Binh River, as shown in the 4-NP boxplot (Figure 5). The concentrations of 4-NP typically exhibit strong fluctuations, with the highest values recorded at point R2 (286.1 ng/L) at the Cau River.
Figure 5

Box-and-whisker plots of targeted compound concentrations (ng/L) in the Bac Ninh region.

Figure 5

Box-and-whisker plots of targeted compound concentrations (ng/L) in the Bac Ninh region.

Close modal

The concentration of 4-NP in the samples was observed to be lower than the maximum allowable concentration (MAC) and the annual average (AA) in seawater samples and other surface waters. According to the Environmental Quality Standards (EQS) for these compounds, the AA for 4-NP in seawater samples and other surface waters is 300 ng/L, while the MAC is 2 μg/L (EU Commission 2022).

The dynamic fluctuations in 4-NP concentrations observed underscore the intricate nature of 4-NP emissions within these aquatic ecosystems. 4-NP in surface waters consistently reveals close correlations between its presence and anthropogenic activities (Gałązka & Jankiewicz 2022), particularly emphasizing the pivotal role of industrial/urban areas. Furthermore, the influence of stormwater discharge and runoff emerge as notable contributing factors to the widespread occurrence of 4-NP (Chokwe et al. 2017). 4-NP is highly toxic to aquatic life, causing reproductive effects on aquatic organisms at concentrations ranging from 0.13 mg/L to higher (Naylor 1996). Among all samples collected, no samples had 4-NP concentrations exceeding 0.13 mg/L, indicating that 4-NP has no significant influence on the ecological environment in these locations.

Furthermore, regarding 4-t-OP, which is approximately 25% more potent as an endocrine disruptor than 4-NP (Oketola & Fagbemigun 2013), concentrations of 4-t-OP were also detected in water samples from three different rivers, with concentrations ranging from 74.1 to 36.1 ng/L (Cau River), 482.0–39.8 ng/L (Duong River), and 76.3–48.0 ng/L (Thai Binh River). In the case of 4-t-OP, the MAC is not applicable as the AA (10 ng/L) is intended to protect against short-term pollution peaks in continuous discharges. However, the concentration of 4-t-OP obtained in the study for all samples was higher than the AA value. This suggests that the discharges of 4-t-OP into the aquatic environment of the Bac Ninh province may harm the environment and require more stringent regulations and monitoring.

Among these samples, 4-t-OP consistently exhibited higher concentrations than the others, with a maximum concentration of 482.0 ng/L observed at location R14 in the Duong River, where the textile industry is strongly developed. The concentrations of 4-t-OP at sites in Bac Ninh province in this study were higher than those in another study conducted in Vietnam (Le Thi Minh et al. 2016). This suggests continuous effluent discharge from both residential and industrial activities, especially the textile industry, is polluting these areas.

BPA, which has water solubility (120–300 mg/L) (Oketola & Fagbemigun 2013), was detected in low concentrations ranging from 1.0 to 30.2 ng/L in all samples. This may be attributed to the tendency of the compound to adsorb to river sediments (Oketola & Fagbemigun 2013). The presence of BPA on the surface, even in trace amounts, poses a significant threat to our environment. Its residues in natural ecosystems not only harm the environment but also disrupt metabolism (Gałązka & Jankiewicz 2022). Like 4-NP, BPA is present in the aquatic environment closely correlated with anthropogenic activity (Gałązka & Jankiewicz 2022). The BPs are the main ones used in the production of epoxy resins and polycarbonate plastics (Oketola & Fagbemigun 2013; Yan et al. 2017). A few samples from the Duong River have shown the signal of BPF but the concentrations were lower than MDL; therefore, the concentration of BPF was not reported. In contrast, BPS was detected in all samples (ranging from 27.8 to 234.3 ng/L), indicating that the majority of manufacturers are using BPS as a substitute for BPA. However, it is noteworthy that BP has not yet been legislated in water. BPA has been included in Annex II of the Directive 2008/105/EC as a future regulated substance in the ‘list of 33 priority substances’ (Salgueiro-González et al. 2012).

The confluence of the Duong River and the Cau River with the Thai Binh River has a higher possibility of increasing contaminant levels in the Thai Binh River. Comparing the results obtained in this study with previous research indicated that the concentrations of APs and BPs fall within the range of values found in waters assessed from other rivers, as shown in Table 2. Besides, BPA concentrations closely resembled those in a prior study in Long Xuyen, Vietnam, where there are agricultural, livestock, and industrial activities. The lower 4-NP levels observed in the current research and the higher 4-t-OP levels are likely a result of the strong influence of the textile industry in Bac Ninh province. The concentration analysis performed in this study revealed a significant rise in the concentration of BPS when compared to previous research findings in Long Xuyen. The difference in compound concentrations highlights the dynamic nature of pollutant dispersal in aquatic environments. Seasonal differences, as well as human activities in each place, may be causes for these variances.

Table 2

Concentrations of alkylphenols and bisphenols detected in rivers from Bac Ninh province in comparison with rivers and lakes in other studies

CompoundIn this study (n = 21)
DF%In other studies
References
Range (ng/L)Mean (ng/L)Range (ng/L)Region
BPS 27.8–234.3 72.4 100 0.28–67 Taihu, China Jin & Zhu (2016)  
2.24–73.3 Nanjing, China Zheng et al. (2019)  
1.5–8.7 Tamagawa Rive Yamazaki et al. (2015)  
2.16–56.9 Zhujiang River Huang et al. (2020)  
BPF < MDL < MDL 23 ND–5.6 Taihu, China Jin & Zhu (2016)  
ND–4.76 Nanjing, China Zhao et al. (2019)  
ND Nadong River, Korea Yamazaki et al. (2015)  
2.16–16.2 Zhujiang River Huang et al. (2020)  
BPA 1.0–30.2 5.6 100 24.2 ± 5.2 Long Xuyen, Vietnam Duong et al. (2010)  
6–481 Guangzhou, China Peng et al. (2008)  
410–2,990 Henan, China Zhang et al. (2011)  
ND–649 Iberian rivers, Europe Gorga et al. (2015)  
BPAF ND ND 0.13–1.1 Taihu, China Jin & Zhu (2016)  
1.5–16.2 Nanjing, China Zheng et al. (2019)  
ND–0.96 Zhujiang River Huang et al. (2020)  
12–84 Luoma Lake Yan et al. (2017)  
BPB ND ND ND Taihu, China Jin & Zhu (2016)  
6.4–23 Luoma Lake Yan et al. (2017)  
ND Hangzhou, China Yang et al. (2014)  
0.17–13.1 Pearl River, South China Zhao et al. (2019)  
BPAP ND ND 4.3–56 Luoma Lake Yan et al. (2017)  
ND–0.39 Taihu Lake Jin & Zhu (2016)  
0.540–0.903 Slovenia–Croatia Česen et al. (2019)  
4.3–56 Luoma Lake Yan et al. (2017)  
BPP ND ND ND–0.89 Zhujiang River Huang et al. (2020)  
0.27–1.53 Pearl River, South China Zhao et al. (2019)  
6.45 Slovenia–Croatia Česen et al. (2019)  
ND–1.09 Surface water (China) Fabrello & Matozzo (2022)  
4-NP 12.4–286.1 78.9 100 1,761.9 ± 201.5 Long Xuyen, Vietnam Duong et al. (2010)  
36–33,231 Guangzhou, China Peng et al. (2008)  
75.2–1,520 Henan, China Zhang et al. (2011)  
ND–391 Iberian rivers, Europe Gorga et al. (2015)  
4-t-OP 36.1–482.0 91.2 100 4.4 ± 0.5 Long Xuyen, Vietnam Duong et al. (2010)  
ND–85 Iberian rivers, Europe Gorga et al. (2015)  
0.4–1.3 Elbe River, Germany Jin & Zhu (2016)  
20.9–63.2 Henan, China Zhang et al. (2011)  
CompoundIn this study (n = 21)
DF%In other studies
References
Range (ng/L)Mean (ng/L)Range (ng/L)Region
BPS 27.8–234.3 72.4 100 0.28–67 Taihu, China Jin & Zhu (2016)  
2.24–73.3 Nanjing, China Zheng et al. (2019)  
1.5–8.7 Tamagawa Rive Yamazaki et al. (2015)  
2.16–56.9 Zhujiang River Huang et al. (2020)  
BPF < MDL < MDL 23 ND–5.6 Taihu, China Jin & Zhu (2016)  
ND–4.76 Nanjing, China Zhao et al. (2019)  
ND Nadong River, Korea Yamazaki et al. (2015)  
2.16–16.2 Zhujiang River Huang et al. (2020)  
BPA 1.0–30.2 5.6 100 24.2 ± 5.2 Long Xuyen, Vietnam Duong et al. (2010)  
6–481 Guangzhou, China Peng et al. (2008)  
410–2,990 Henan, China Zhang et al. (2011)  
ND–649 Iberian rivers, Europe Gorga et al. (2015)  
BPAF ND ND 0.13–1.1 Taihu, China Jin & Zhu (2016)  
1.5–16.2 Nanjing, China Zheng et al. (2019)  
ND–0.96 Zhujiang River Huang et al. (2020)  
12–84 Luoma Lake Yan et al. (2017)  
BPB ND ND ND Taihu, China Jin & Zhu (2016)  
6.4–23 Luoma Lake Yan et al. (2017)  
ND Hangzhou, China Yang et al. (2014)  
0.17–13.1 Pearl River, South China Zhao et al. (2019)  
BPAP ND ND 4.3–56 Luoma Lake Yan et al. (2017)  
ND–0.39 Taihu Lake Jin & Zhu (2016)  
0.540–0.903 Slovenia–Croatia Česen et al. (2019)  
4.3–56 Luoma Lake Yan et al. (2017)  
BPP ND ND ND–0.89 Zhujiang River Huang et al. (2020)  
0.27–1.53 Pearl River, South China Zhao et al. (2019)  
6.45 Slovenia–Croatia Česen et al. (2019)  
ND–1.09 Surface water (China) Fabrello & Matozzo (2022)  
4-NP 12.4–286.1 78.9 100 1,761.9 ± 201.5 Long Xuyen, Vietnam Duong et al. (2010)  
36–33,231 Guangzhou, China Peng et al. (2008)  
75.2–1,520 Henan, China Zhang et al. (2011)  
ND–391 Iberian rivers, Europe Gorga et al. (2015)  
4-t-OP 36.1–482.0 91.2 100 4.4 ± 0.5 Long Xuyen, Vietnam Duong et al. (2010)  
ND–85 Iberian rivers, Europe Gorga et al. (2015)  
0.4–1.3 Elbe River, Germany Jin & Zhu (2016)  
20.9–63.2 Henan, China Zhang et al. (2011)  

DF = detection frequency.

Environmental risk assessment for APs and BPs

For all organic substances, PNEC water values were taken from the literature (Supplementary Table S4). The chart (Figure 6) illustrates the computed RQ values. Among the targeted compounds, 4-NP has been identified to pose a medium risk to aquatic organisms in all three rivers. However, based on the RQ values (RQCau River > RQDuong River > RQThai Binh River), it is evident that the highest risk to the organisms is present in the Cau River. Conversely, 4-t-OP, a substance with higher toxicity compared to 4-NP, was detected in 100% of the samples, and caused a high risk to aquatic organisms in the Duong River, along with a medium risk in the Cau and Thai Binh Rivers. This signals a concerning state of the aquatic ecosystem in these areas. Notably, the risk level of 4-t-OP in this study was higher than what was previously observed in the Chinese studies and vice versa for 4-NP (Liu et al. 2016).
Figure 6

Risk quotient of APs and BPs in surface water from Bac Ninh province.

Figure 6

Risk quotient of APs and BPs in surface water from Bac Ninh province.

Close modal

Among the seven BP substances studied, only BPA and BPS were detected in 100% of the samples. According to the RQ assessment, BPA did not pose harm to aquatic organisms in the Duong and Thai Binh Rivers but presented a low-risk level in the Cau River. On the other hand, BPS resulted in a low risk for all three rivers. The risk assessment results for BPA and BPS are both lower compared to previous studies conducted in China (Yan et al. 2017). This also serves as a warning for the aquatic ecosystems in these regions.

This study investigated the validation of an analytical method, the occurrence, and potential ecological risks of APs and BPs in surface water collected from rivers flowing through Bac Ninh province in Vietnam. The analytical method used in this study, involving liquid–liquid extraction and LC-ESI-MS/MS analysis, proved effective for quantifying APs and BPs in surface water. The method validation demonstrated good linearity, sensitivity, and reliability. The results showed the widespread presence of 4-NP, 4-t-OP, BPA, BPS, and BPF in the water samples. The concentrations varied among rivers, with the Cau and Duong rivers indicating greater pollution levels than the Thai Binh River. According to the environmental risk assessment based on RQ values, 4-NP poses a medium risk in all three rivers, but 4-t-OP poses a high ecological danger in the Duong River. BPS is detected with low risk in three rivers, while BPA and BPF showed low to negligible risks in all rivers. In summary, this research contributes valuable information on the environmental occurrence and risks associated with APs and BPs in rivers of Bac Ninh province, providing a foundation for future studies and environmental management initiatives in the region.

This paper is a contribution to the LOTUS International Joint Laboratory (http://lotus.usth.edu.vn) and the French National Research Institute for Sustainability Development (IRD). The paper was supported from BEAM research team supported by USTH funding. The authors would like to send special thanks to the anonymous reviewer. Your valuable comments help us to improve a lot for our paper.

This research was funded by the Vietnam Academy of Science and Technology (VAST) (Project code: QTFR02.03/24-25).

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

The authors declare there is no conflict.

Ademollo
N.
,
Ferrara
F.
,
Delise
M.
,
Fabietti
F.
,
Funari
E.
,
Ferrara
F.
,
Delise
M.
,
Fabietti
F.
&
Funari
E.
2008
Nonylphenol and octylphenol in human breast milk
.
Environment International
34
(
7
),
984
987
.
doi:10.1016/j.envint.2008.03.001
.
Amiridou
D.
&
Voutsa
D.
2011
Alkylphenols and phthalates in bottled waters
.
Journal of Hazardous Materials
185
(
1
),
281
286
.
doi:10.1016/j.jhazmat.2010.09.031
.
AOAC
2016
Guidelines for standard method performance requirements. Official Methods of Analysis of AOAC International [Preprint]. doi:10.1093/9780197610145.005.006
.
Beek
B.
2000
Bioaccumulation – New Aspects and Developments
.
Springer Berlin, Heidelberg. doi:10.1007/10503050
.
Bielski
A.
2021
Mixing effects in the river downstream from pollution discharge point
.
Technical Transactions
1
20
.
doi:10.37705/techtrans/e2021004
.
Česen
M.
,
Ahel
M.
,
Terzić
S.
,
Heath
D. J.
&
Heath
E.
2019
The occurrence of contaminants of emerging concern in Slovenian and Croatian wastewaters and receiving Sava river
.
Science of the Total Environment
650
,
2446
2453
.
doi:10.1016/j.scitotenv.2018.09.238
.
Chokwe
T. B.
,
Okonkwo
J. O.
&
Sibali
L. L.
2017
Distribution, exposure pathways, sources and toxicity of nonylphenol and nonylphenol ethoxylates in the environment
.
Water SA
43
(
4
),
529
542
.
doi:10.4314/wsa.v43i4.01
.
Duong
C. N.
,
Ra
J. S.
,
Cho
J.
,
Kim
S. D.
,
Choi
H. K.
,
Park
J. H.
,
Kim
K. W.
,
Inam
E.
&
Kim
S. D.
2010
Estrogenic chemicals and estrogenicity in river waters of South Korea and seven Asian countries
.
Chemosphere
78
(
3
),
286
293
.
doi:10.1016/j.chemosphere.2009.10.048
.
Elobeid
M. A.
,
Almarhoon
Z. M.
,
Virk
P.
,
Hassan
Z. K.
,
Omer
S. A.
,
ElAmin
M.
,
Daghestani
M. H.
&
AlOlayan
E. M.
2012
Bisphenol A detection in various brands of drinking bottled water in Riyadh, Saudi Arabia using gas chromatography/mass spectrometer
.
Tropical Journal of Pharmaceutical Research
11
(
3
),
455
459
.
doi:10.4314/tjpr.v11i3.15
.
EU Commission
2022
Proposal for a Directive amending WFD, GWD and EQSD, 0344
.
Fabrello
J.
&
Matozzo
V.
2022
Bisphenol analogs in aquatic environments and their effects on marine species – A review
.
Journal of Marine Science and Engineering
10
(
9
).
doi:10.3390/jmse10091271
.
Fu
P.
&
Kawamura
K.
2010
Ubiquity of bisphenol A in the atmosphere
.
Environmental Pollution
158
(
10
),
3138
3143
.
doi:10.1016/j.envpol.2010.06.040
.
Furey
A.
,
Moriarty
M.
,
Bane
V.
,
Kinsella
B.
&
Lehane
M.
2013
Ion suppression; A critical review on causes, evaluation, prevention and applications
.
Talanta
115
,
104
122
.
doi:10.1016/j.talanta.2013.03.048
.
Gao
Y.
,
Xiao
S. K.
,
Wu
Q.
&
Pan
C. G.
2023
Bisphenol analogues in water and sediment from the Beibu Gulf, South China Sea: Occurrence, partitioning and risk assessment
.
Science of The Total Environment
857
,
159445
.
doi:10.1016/J.SCITOTENV.2022.159445
.
Gorga
M.
,
Insa
S.
,
Petrovic
M.
&
Barceló
D.
2015
Occurrence and spatial distribution of EDCs and related compounds in waters and sediments of Iberian rivers
.
Science of the Total Environment
503–504
,
69
86
.
doi:10.1016/j.scitotenv.2014.06.037
.
Hong
Y.
,
Feng
C.
,
Jin
X.
,
Xie
H.
,
Liu
N.
,
Bai
Y.
,
Wu
F.
&
Raimondo
S.
2022
A QSAR–ICE–SSD model prediction of the PNECs for alkylphenol substances and application in ecological risk assessment for rivers of a megacity
.
Environment International
167
(
8
),
107367
.
doi:10.1016/j.envint.2022.107367
.
Huang
Z.
,
Zhao
J. L.
,
Yang
Y. Y.
,
Jia
Y. W.
,
Zhang
Q. Q.
,
Chen
C. E.
,
Liu
Y. S.
,
Yang
B.
,
Xie
L.
&
Ying
G. G.
2020
Occurrence, mass loads and risks of bisphenol analogues in the Pearl River Delta region, South China: Urban rainfall runoff as a potential source for receiving rivers
.
Environmental Pollution
263
,
114361
.
doi:10.1016/j.envpol.2020.114361
.
Janssen
M. P. M.
,
Traas
T. P.
,
Rila
J. P.
&
van Vlaardingen
P. L. A.
2004
Guidance for Deriving Dutch Environmental Risk Limits From EU-Risk Assessment Reports of Existing Substances. RIVM Report 601501020/2004
, pp.
1
35
.
Kern
K.
2014
New standards for the chemical quality of water in Europe under the new directive 2013/39/EU
.
Journal for European Environmental and Planning Law
11
(
1
),
31
48
.
doi:10.1163/18760104-01101002
.
Le Thi Minh
T.
,
Phuoc
D. N.
,
Quoc
T. D.
,
Ngo
H. H.
&
Lan
C. D. H.
2016
Presence of e-EDCs in surface water and effluents of pollution sources in Sai Gon and Dong Nai river basin
.
Sustainable Environment Research
26
(
1
),
20
27
.
doi:10.1016/j.serj.2015.09.001
.
Liu
D.
,
Liu
J.
,
Guo
M.
,
Xu
H.
,
Zhang
S.
,
Shi
L.
&
Yao
C.
2016
Occurrence, distribution, and risk assessment of alkylphenols, bisphenol A, and tetrabromobisphenol A in surface water, suspended particulate matter, and sediment in Taihu Lake and its tributaries
.
Marine Pollution Bulletin
112
(
1–2
),
142
150
.
doi:10.1016/j.marpolbul.2016.08.026
.
Lu
J.
,
Wu
J.
,
Stoffella
P. J.
&
Wilson
P. C.
2013
Analysis of bisphenol A, nonylphenol, and natural estrogens in vegetables and fruits using gas chromatography-tandem mass spectrometry
.
Journal of Agricultural and Food Chemistry
61
(
1
),
84
89
.
doi:10.1021/jf304971k
.
Naylor
C. G.
1996
The environmental fate and safety of nonylphenol ethoxylates
.
ASTM Special Technical Publication
1312
,
3
20
.
doi:10.1520/stp11336s
.
Oketola
A. A.
&
Fagbemigun
T. K.
2013
Determination of nonylphenol, octylphenol and bisphenol-A in water and sediments of two major rivers in Lagos, Nigeria
.
Journal of Environmental Protection
04
(
07
),
38
45
.
doi:10.4236/jep.2013.47a005
.
Peng
X.
,
Yu
Y.
,
Tang
C.
,
Tan
J.
,
Huang
Q.
&
Wang
Z.
2008
Occurrence of steroid estrogens, endocrine-disrupting phenols, and acid pharmaceutical residues in urban riverine water of the Pearl River Delta, South China
.
Science of the Total Environment
397
(
1–3
),
158
166
.
doi:10.1016/j.scitotenv.2008.02.059
.
Rao
T. N.
2018
Validation of Analytical Methods
,
License IntechOpen. doi:10.5772/intechopen.72087
.
Salgueiro-González
N.
,
Concha-Graña
E.
,
Turnes-Carou
I.
,
Muniategui-Lorenzo
S.
,
López-Mahía
P.
&
Prada-Rodríguez
D.
2012
Determination of alkylphenols and bisphenol A in seawater samples by dispersive liquid-liquid microextraction and liquid chromatography tandem mass spectrometry for compliance with environmental quality standards (Directive 2008/105/EC)
.
Journal of Chromatography A
1223
,
1
8
.
doi:10.1016/j.chroma.2011.12.011
.
Salgueiro-González
N.
,
Muniategui-Lorenzo
S.
,
López-Mahía
P.
&
Prada-Rodríguez
D.
2017
Trends in analytical methodologies for the determination of alkylphenols and bisphenol A in water samples
.
Analytica Chimica Acta
962
,
1
14
.
doi:10.1016/j.aca.2017.01.035
.
Selvaraj
K. K.
,
Shanmugam
G.
,
Sampath
S.
,
Larsson
D. G. J.
&
Ramaswamy
B. R.
2014
GC-MS determination of bisphenol A and alkylphenol ethoxylates in river water from India and their ecotoxicological risk assessment
.
Ecotoxicology and Environmental Safety
99
,
13
20
.
doi:10.1016/j.ecoenv.2013.09.006
.
Shao
B.
,
Han
H.
,
Li
D.
,
Ma
Y.
,
Tu
X.
&
Wu
Y.
2007
Analysis of alkylphenol and bisphenol A in meat by accelerated solvent extraction and liquid chromatography with tandem mass spectrometry
.
Food Chemistry
105
(
3
),
1236
1241
.
doi:10.1016/j.foodchem.2007.02.040
.
Shi
J.
,
Jiao
Z.
,
Zheng
S.
,
Li
M.
,
Zhang
J.
,
Feng
Y.
,
Yin
J.
&
Shao
B.
2015
Long-term effects of bisphenol AF (BPAF) on hormonal balance and genes of hypothalamus-pituitary-gonad axis and liver of zebrafish (Danio rerio), and the impact on offspring
.
Chemosphere
128
,
252
257
.
doi:10.1016/j.chemosphere.2015.01.060
.
Vu-Duc
N.
,
Nguyen-Quang
T.
,
Le-Minh
T.
,
Nguyen-Thi
X.
,
Tran
T. M.
,
Vu
H. A.
,
Nguyen
L. A.
,
Doan-Duy
T.
,
Hoi
B. V.
,
Vu
C. T.
,
Le-Van
D.
,
Phung-Thi
L. A.
,
Vu-Thi
H. A.
,
Chu
D. B.
&
Plaza-Bolaños
P.
2019
Multiresidue pesticides analysis of vegetables in Vietnam by ultrahigh-performance liquid chromatography in combination with high-resolution mass spectrometry (UPLC-Orbitrap MS)
.
Journal of Analytical Methods in Chemistry
2019
.
doi:10.1155/2019/3489634
.
Wang
B.
,
Dong
F.
,
Chen
S.
,
Chen
M.
,
Bai
Y.
,
Tan
J.
,
Li
F.
&
Wang
Q.
2016
Phenolic endocrine disrupting chemicals in an urban receiving river (Panlong river) of Yunnan-Guizhou plateau: Occurrence, bioaccumulation and sources
.
Ecotoxicology and Environmental Safety
128
,
133
142
.
doi:10.1016/j.ecoenv.2016.02.018
.
Xie
Z.
,
Selzer
J.
,
Ebinghaus
R.
,
Caba
A.
&
Ruck
W.
2006
Development and validation of a method for the determination of trace alkylphenols and phthalates in sea water and air using GC-MS
.
Analytica Chimica Acta
565
(
2
),
198
207
.
doi:10.1016/j.aca.2006.02.027
.
Yamazaki
E.
,
Yamashita
N.
,
Taniyasu
S.
,
Lam
J.
,
Lam
P. K. S.
,
Moon
H. B.
,
Jeong
Y.
,
Kannan
P.
,
Achyuthan
H.
,
Munuswamy
N.
&
Kannan
K.
2015
Bisphenol A and other bisphenol analogues including BPS and BPF in surface water samples from Japan, China, Korea and India
.
Ecotoxicology and Environmental Safety
122
,
565
572
.
doi:10.1016/j.ecoenv.2015.09.029
.
Yan
Z.
,
Liu
Y.
,
Yan
K.
,
Wu
S.
,
Han
Z.
,
Guo
R.
,
Chen
M.
,
Yang
Q.
,
Zhang
S.
&
Chen
J.
2017
Bisphenol analogues in surface water and sediment from the shallow Chinese freshwater lakes: Occurrence, distribution, source apportionment, and ecological and human health risk
.
Chemosphere
184
,
318
328
.
doi:10.1016/j.chemosphere.2017.06.010
.
Yang
Y.
,
Lu
L.
,
Zhang
J.
,
Yang
Y.
,
Wu
Y.
&
Shao
B.
2014
Simultaneous determination of seven bisphenols in environmental water and solid samples by liquid chromatography-electrospray tandem mass spectrometry
.
Journal of Chromatography A
1328
,
26
34
.
doi:10.1016/j.chroma.2013.12.074
.
Yusoff
N. M.
,
Koyama
J.
&
Uno
S.
2017
Bioaccumulation of sedimentary endocrine disrupting chemicals (EDCs) by the benthic fish, Pleuronectes yokohamae
.
Malaysian Journal of Analytical Science
21
(
3
),
535
543
.
doi:10.17576/mjas-2017-2103-03
.
Ying
G. G.
,
Williams
B.
&
Kookana
R.
2002
Environmental fate of alkylphenols and alkylphenol ethoxylates – A review
.
Environment International
28
(
3
),
215
226
.
doi:10.1016/S0160-4120(02)00017-X
.
Zaborowska
M.
,
Wyszkowska
J.
,
Borowik
A.
&
Kucharski
J.
2023
Bisphenols – A threat to the natural environment
.
Materials
16
(
19
).
doi:10.3390/ma16196500
.
Zhao
R. S.
,
Wang
X.
,
Yuan
J. P.
&
Zhang
L. L.
2009
Solid-phase extraction of bisphenol A, nonylphenol and 4-octylphenol from environmental water samples using microporous bamboo charcoal, and their determination by HPLC
.
Microchimica Acta
165
(
3–4
),
443
447
.
doi:10.1007/s00604-009-0145-3
.
Zhao
X.
,
Qiu
W.
,
Zheng
Y.
,
Xiong
J.
,
Gao
C.
&
Hu
S.
2019
Occurrence, distribution, bioaccumulation, and ecological risk of bisphenol analogues, parabens and their metabolites in the Pearl River Estuary, South China
.
Ecotoxicology and Environmental Safety
180
(
March
),
43
52
.
doi:10.1016/j.ecoenv.2019.04.083
.
Zheng
C.
,
Liu
J.
,
Ren
J.
,
Shen
J.
,
Fan
J.
,
Xi
R.
,
Chen
W.
&
Chen
Q.
2019
Occurrence, distribution and ecological risk of bisphenol analogues in the surface water from a water diversion project in Nanjing, China
.
International Journal of Environmental Research and Public Health
16
(
18
).
doi:10.3390/ijerph16183296
.
Zhu
Z.
&
Zuo
Y.
2013
Bisphenol A and other alkylphenols in the environment – Occurrence, fate, health effects and analytical techniques
.
Advances in Environmental Research
2
(
3
),
179
202
.
doi:10.12989/aer.2013.2.3.179
.
This is an Open Access article distributed under the terms of the Creative Commons Attribution Licence (CC BY 4.0), which permits copying, adaptation and redistribution, provided the original work is properly cited (http://creativecommons.org/licenses/by/4.0/).

Supplementary data