Occurrence, spatial and seasonal variation, and environmental risk of pharmaceutically active compounds in the Pearl River basin, South China

Haojun Lei, Kaisheng Yao, Bin Yang, Lingtian Xie, Guangguo Ying

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Front. Environ. Sci. Eng. ›› 2023, Vol. 17 ›› Issue (4) : 46. DOI: 10.1007/s11783-023-1646-8
RESEARCH ARTICLE
RESEARCH ARTICLE

Occurrence, spatial and seasonal variation, and environmental risk of pharmaceutically active compounds in the Pearl River basin, South China

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Highlights

● 38 PhACs and 2 pesticides were detected in the three rivers of the Pearl River basin.

● Anti-inflammatory/analgesics drugs were the predominant PhACs.

● The concentrations of PhACs showed seasonal and spatial variation.

● Diazepam and ibuprofen were the two PhACs with a moderate environmental risk.

Abstract

The occurrence, fate, and environmental risk of 40 pharmaceutically active compounds (PhACs) from surface waters and sediments were comprehensively investigated in the Beijiang River, Xijiang River, and Maozhou River of the Pearl River basin, South China. Salicylic acid and diclofenac (anti-inflammatory drugs), gemfibrozil (a lipid regulator), carbamazepine (an antiepileptic drug), diazepam (a psychoactive drug), and 2-methyl-4-chloro-phenoxyacetic acid (MCPA, a pesticide) were the most ubiquitous compounds in the studied region. The average concentrations of detected PhACs in surface waters and sediments ranged from 0.17 to 19.1 ng/L and 0.10 to 10.4 ng/g, respectively. Meanwhile, PhACs concentration in surface waters and sediments varied greatly among and within the Beijiang River, Xijiang River, and Maozhou River. The largest annual flux of PhACs of the Xijiang River and Beijiang River was more than 11 000 kg per annum, whereas only 25.7 kg/a in the Maozhou River. In addition, the estimated emissions of PhACs in the Beijiang River, Xijiang River, and Maozhou River ranged respectively from 0.28 to 4.22 kg/a, 0.12 to 6.72 kg/a, and 6.66 to 91.0 kg/a, and the back-estimated usage varied with a range from 12.0 to 293 kg/a, 6.79 to 944 kg/a, 368 to 17 459 kg/a. Moreover, the emissions of PhACs showed a close relationship with the gross domestic product (GDP) of each city along the Pearl River. The environmental risk assessment suggested that diazepam and ibuprofen had a moderate risk in this region.

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Keywords

Pharmaceutically active compounds / Occurrence / Spatiotemporal variations / Pearl River / Environmental risk assessment

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Haojun Lei, Kaisheng Yao, Bin Yang, Lingtian Xie, Guangguo Ying. Occurrence, spatial and seasonal variation, and environmental risk of pharmaceutically active compounds in the Pearl River basin, South China. Front. Environ. Sci. Eng., 2023, 17(4): 46 https://doi.org/10.1007/s11783-023-1646-8

1 Introduction

Pharmaceutically active compounds (PhACs) are widely used in humans and veterinaries to prevent, diagnose, and treat diseases. Major groups of the PhACs include non-steroidal anti-inflammatory drugs (NSAIDs), antidepressants, anxiolytics, and hypertension medicines. Most of these drugs have been regarded as emerging organic contaminants in aquatic ecosystems (Daughton and Ternes, 1999; Silva et al., 2015). The PhACs have attracted massive attention due to their large quantity of consumption, continuous discharge, and ecological risk to aquatic organisms in the receiving aquatic environments (Hu et al., 2019; Fatima et al., 2020; Szabelak and Bownik, 2021). The PhACs have been frequently detected in surface waters throughout the world at concentrations range of ng/L to µg/L over the past decades (Zhao et al., 2016; Valdez-Carrillo et al., 2020). The primary sources of PhACs to aquatic environments are effluents from the wastewater treatment plants (WWTPs), wastewaters from livestock and poultry industries, and sewage wastewater containing optionally disposal of expired or unused drugs (Subedi et al., 2017; Thiebault et al., 2017; Lei et al., 2021).
Among the PhACs, NSAIDs are one of the most frequently used pharmaceuticals globally, and listed among the top 10 persistent pollutants (Green et al., 2001). Widely detected NSAIDs in aquatic environments include ibuprofen, diclofenac, naproxen, ketoprofen, and salicylic acid (Świacka et al., 2020). For instance, the most prominent NSAIDs in African surface waters are ibuprofen, diclofenac, and naproxen, with maximum concentrations of µg/L (Madikizela and Chimuka, 2017; Madikizela et al., 2017; Sibeko et al., 2019). Meanwhile, psychotropic pharmaceuticals (PPhs) are widely consumed in the developed countries (Brauer et al., 2021). Antidepressants and anxiolytics are the most widely detected PPhs in aquatic environments (Mompelat et al., 2009; Schlüsener et al., 2015; Grabicová et al., 2020; Branchet et al., 2021). The presence of some PPhs in aquatic environments has been implicated a pollution source from the wastewater. For example, the presence of carbamazepine (an antiepileptic drug) has been deemed a ubiquitous indicator of wastewater pollution (Glassmeyer et al., 2005). Other PPhs, such as benzodiazepines (BZDs) and its various transformed products (i.e., diazepam and 6-chloro-4-phenyl-2(1H)-quinazolinone (6-CPQ), are frequently detected at a few ng/L to hundreds ng/L in different waters (Calamari et al., 2003; Calisto and Esteves, 2009; Hass et al., 2012; Lei et al., 2021).
Numerous studies have shown that many PhACs are toxic to aquatic organisms. For example, NSAIDs decrease the chlorophyll and carotenoid content for the green algae Scenedesmus obliquus, resulting in a reduced photosynthetic efficiency and growth (Wang et al., 2020). Psychoactive compounds such as diazepam at environmental concentrations can alter the transcriptional expression of genes and behavior of zebrafish (Oggier et al., 2010). In addition, exposure to sertraline disturbs the balance of microbial communities (Yang et al., 2019). Therefore, the environmental risk of PhACs cannot be simply ignored.
The Pearl River basin serves as an important source of drinking water for many cities in southern China. Previous research on the pollution of PhACs in the Pearl River basin has been conducted with one or two sampling campaigns along one main stream with recognized sources of PhACs contamination (Yang et al., 2017). This approach could not provide a complete understanding on variations in the frequency of occurrence and the environmental risk of PhACs. Moreover, data on PhACs for multiple rivers in the Pearl River basin by one sampling campaign in each of two seasons in a year are of relatively paucity. The main objective of this study was to evaluate the occurrence of PhACs in the Beijiang River, Xijiang River, and Maozhou River of the Pearl River basin. Major classes of PhACs in this study included NSAIDs, antidepressants, anxiolytics, and anti-hypertension drugs. In addition, the seasonal and temporal variations in the concentrations of these PhACs among and between different rivers, along with the environmental risk were evaluated. This study can provide important data on the fate and environmental assessment of the PhACs in the Pearl River basin.

2 Materials and methods

2.1 Chemicals

Standards (total number of 40) of 11 non-steroidal anti-inflammatory drugs (NSAIDs), 2 antiepileptic drugs (primidone and carbamazepine), 2 lipid regulators (gemfibrozil and clofibric acid), 1 antineoplastic drug (cyclophosphamide), 22 psychoactive drugs (fluoxetine, sertraline, 17 benzodiazepines and their 3 transformed products), 2 pesticides (bentazone and 2-methyl-4-chloro-phenoxyacetic acid (MCPA)), and 13 internal standards were obtained from Sigma-Aldrich (USA), Cerilliant Corporation (USA), Dr. Ehrenstorfer GmbH (Germany), and Riedel-de Haen (Germany). Chemical information of these pharmaceutically active compounds (PhACs) is provided in Table S1, Supplementary Information. The HPLC-grade organic solvents used were all purchased from the Merck Corporation (Shanghai, China).

2.2 Sample collection

The Pearl River is a major river and main drinking water source in south China, which covers approximately 453,690 square kilometers. The Xijiang River, Beijiang River, and Maozhou River belong to the Pearl River basin. The Xijiang River and Beijiang River are the main tributaries of the Pearl River, crossing Guangxi and Guangdong in China, with a full-length of 2214 km and 573 km, respectively. The Maozhou River is a tributary crossing Shenzhen and Dongguan with a length of 41.6 km.
Twenty-two sampling sites in the Xijiang River, 13 in the Beijiang River, and 7 in the Maozhou River were respectively selected as representative sites. Table S2 provides detailed information about the sampling sites in this study. Sample collection of surface waters and sediments was conducted in July and December 2018 for the wet and dry seasons, respectively. Surface water samples were taken in 1 L amber bottles, followed by immediate field adjustment of the pH to 3.0 with 4 mol/L H2SO4, while sediment samples were collected in 200 mL glass bottles. Three replicate samples were collected for each sampling site. After collection, appropriate volume of methanol (final concentration: 5 % v/v) was immediately added to the surface water samples, and sodium azide (1 g/L each) was added to the sediment samples to suppress microbial activity. All the pre-treated samples were delivered to the lab in coolers. The surface water samples were kept at 4 °C and extracted within 24 h. Additionally, the sediment samples were freeze-dried, sieved by a standard 60-mesh sieve, and stored at –20 °C.

2.3 Sample preparation and chemical analysis

The extraction methods for the 40 PhACs in the surface water samples and sediment samples followed our previous study (Chen et al., 2010; Lei et al., 2021). Briefly, the solid-phase extraction (SPE) method was applied using Oasis HLB cartridges to extract the water samples. The sediment samples were extracted using SPE clean-up and ultrasonic-assisted extraction. Details of the extraction methods are provided in Text S1.
The target compounds were analyzed on an Agilent 1290 liquid chromatography with an Agilent 6495 triple quadrupole mass spectrometer (HPLC-MS/MS). The HPLC-MS/MS was conducted in both negative and positive ionization modes with an electrospray ionization (ESI) source. The operating conditions of LC and MS for analyzing the target compounds can be found in our recent papers (Yang et al., 2017; Lei et al., 2021).

2.4 Quality assurance and quality control

The internal standard method was used to determine the quality assurance and quality control (QA/QC) for chemical analysis. Table S3 shows the method quantitation limits (MQLs) for each target in the water and sediment samples. For the surface water and sediment samples, the MQLs ranged from 0.024 to 1.552 ng/L and 0.007 to 2.915 ng/g, respectively. The recoveries were between 80 % and 120 %, which were validated in our previous studies as well (Chen et al., 2010; Yang et al., 2017; Lei et al., 2021). Additionally, the mixture of standard samples, procedural blank samples, and instrumental blank samples were detected in each batch of ~ 10 samples. No target compounds were detected in the blank samples.

2.5 Calculation of contaminant flux, emission, and usage

Contaminant flux was used to evaluate the quantity, the rate, and the moving of a contaminant between two sites and calculated using Eq. (1). The estimated emission and the back-estimated usage of a detected compound in water samples were calculated using Eqs. (2)–(3).
Contaminant flux(kg/a)=Cwater×Qwet/dry season flow×3600×24×365×109
Emission(kg/a)=Cwater×Qcapacity×105
Usage(kg/a)=Cwater×Qdischarge×1051Removalrate%×100100+Stability×100Excretion
where Cwater (ng/L) represented the concentration of each detected compound in waters in the wet or dry season; Qwet/dry season flow (m3/s) referred to flow rate for the surface waters at each sampling time (shown in Table S2); Qcapacity and Qdischarge (10000 t/a) respectively designated the wastewater treatment capacity and wastewater discharge at each sampling site (listed in Table S4); Removal rate (%) was the percentage of the detected compound removed after sewage treatment, and stability was a measure of stability change (%) of each PhACs after 12 h, and excretion was the percentage of PhACs from human body after the relevant forms of administration (listed in Table S5).

2.6 Environmental risk assessment

The environmental risk of the detected PhACs was evaluated using Eqs. (4) and (5) based on European Union Technical Guidance Document (EU TGD, 2003).
RQ=MEC/PNEC
PNEC=EC50/AF
where RQ was the risk quotient; MEC was the measured concentration of each PhACs; PNEC was the predicted no-effect concentration; AF was the assessment factor and an AF of 1000 was used due to at least one short-term EC50 was available (Chen et al., 2015; Biel-Maeso et al., 2018).

2.7 Statistical analyses

Data were shown as mean with standard deviation. Spearman’s correlation analysis was used to analyze the relationship between the concentrations of the detected PhACs in the surface waters and sediments. To examine the variation in the concentrations of the target compounds among the sample sites and within each site, the data were analyzed using the principal coordinate analysis (PCoA) (Gower, 1966). Prior to PCoA analyses, Euclidean distance matrices were generated using the data on the standardized variables. The scatter of sites in the unconstrained ordination space was visualized since PCoA placed the sites onto Euclidean distance ordination axes using a matrix of inter-point dissimilarities (Anderson et al., 2008).

3 Results and discussion

A cross-basin and cross-season monitoring program was implemented to evaluate the usage and emissions of 40 PhACs and their environmental risk in Pearl River basin, South China. The detection concentrations and frequencies of PhACs determined in Beijiang River, Xijiang River, and Maozhou River are shown in Fig.1 and summarized in Tab.1. The PhACs were ubiquitously present in all samples at the 42 sampling sites. Out of the 40 compounds, 18 targets were detected in surface water samples and 7 in sediment samples.
Fig.1 Box-and-whisker plots showing the concentrations of the detected PhACs compounds in surface waters (Panel a) and sediments (Panel b) of the Beijiang River, Xijiang River, and Maozhou River in the wet and dry seasons. The whiskers indicate the maximum and minimum concentrations. The boxes stretch from 25th to 75th percentiles. The solid and dotted horizontal lines in the boxes respectively indicate the median and average concentrations. The number at the bottom of each box is the detection frequency of the corresponding compound.

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Tab.1 Detected PhACs and their concentration ranges (ng/L for surface water, ng/g for sediments) and detection frequencies (Freq., %) in surface waters and sediments of the Beijiang River, Xijiang River, and Maozhou River
CompoundsSurface waterSediment
RangeMeanMedianFreq.RangeMeanMedianFreq.
Salicylic acid6.04–16019.112.31001.87–63.210.437.93100
Diclofenac< MQL–53.96.782.8297.6ND0
Gemfibrozil< MQL–12.42.071.6396.4< MQL–19.21.801.1992.9
Naproxen< MQL–28.52.211.3471.4< MQL–8.581.701.5577.4
Ibuprofen< MQL–28925.14.6539.3ND0
Clofibric acid0.43–2.741.030.8215.5ND0
Mefenamic acid1.02–4.562.262.0814.3ND0
Indomethacin< MQL–4.681.371.2410.7ND0
MCPA< MQL–86.76.892.5389.3ND0
Bentazone< MQL–8.651.930.749.52ND0
Carbamazepine< MQL–19.62.430.4997.6< MQL–0.610.100.0532.1
Sertraline< MQL–0.710.290.2810.70.08–0.230.160.1714.3
Paracetamol< MQL–62.55.340.6484.5ND0
Cyclophosphamide< MQL–0.370.170.1826.2ND0
Diazepam0.03–25.02.351.2591.7< MQL–2.460.340.0742.9
Clozapine< MQL–5.830.940.1163.1< MQL–3.280.280.0444.0
Nordiazepam0.24–0.980.480.3816.7ND0
6-CPQ< MQL–4.570.560.2139.3ND0

ND: not detected.

3.1 Occurrence and seasonal distribution of PhACs in surface waters

The concentrations of the 40 PhACs ranged from ND to 289 ng/L (Tab.1). Fourteen, 14, and 16 PhACs were found in the surface waters of the Beijiang River, Xijiang River, and Maozhou River, respectively. Among them, the detection frequency and concentrations of anti-inflammatory/analgesics drugs were higher than those of others. In the Beijiang River, salicylic acid (32.0 ng/L), diclofenac (15.0 ng/L), MCPA (13.2 ng/L), and gemfibrozil (9.04 ng/L) were the compound detected at the highest concentrations (Fig. S1(a)). Salicylic acid (160 ng/L), MCPA (86.7 ng/L), diclofenac (53.9 ng/L), and ibuprofen (48.1 ng/L) showed the largest concentrations in the Xijiang River (Fig S1(c)), whereas ibuprofen (289.0 ng/L), salicylic acid (60.3 ng/L), paracetamol (62.5 ng/L) and diclofenac (47.3 ng/L) were detected with maximum concentrations in the Maozhou river (Fig S1(e)). Compared with their concentrations in the wet and dry seasons, the summed detected concentrations of PhACs were higher in the wet season than in dry season at most sampling sites and maintained roughly the same among sites across each river. The concentrations of the PhACs observed at the estuarine sampling sites of NR13, WR22, and MZR6 were not the highest, possibly due to the high dilution effect by tidal intrusion (Mijangos et al., 2018).
Most of the PhACs were detected at concentration levels similar to the previously reported concentrations in the Chinese streams (Bu et al., 2013). For instance, the concentrations of diclofenac acid, gemfibrozil, carbamazepine, and ibuprofen are close to those reported in the Liuxi, Zhujiang, and Dongjiang River, which are also part of the Pearl River basin (Peng et al., 2008; Yang et al., 2017; Yang et al., 2018). In contrast, in this study, naproxen, clofibric acid, and salicylic acid had relatively low concentrations (with a range from < MQL–28.5, 0.43–2.74, and 6.04–160 ng/L, respectively). Interestingly, diazepam, nordiazepam, and 6-CPQ (the transformed product of oxazepam) were found in the surface water samples, with a detection frequency of up to 91.7 %. It is known that diazepam is poorly removed by the WWTPs in Guangdong Province, China (Lei et al., 2021), which could account for its high detection frequency in this region. Meanwhile, the highest detected concentration of diclofenac (53.9 ng/L) was comparable with that in the Yangtze River in Jiangsu Province (58 ng/L) (Duan et al., 2021), Xiangjiang River in Hunan Province (32 ng/L) (Lin et al., 2018), and Jiulong River in Fujian Province (11 ng/L) (Sun et al., 2016), but approximately half of that in the Beiyun River in Beijing city (121.6 ng/L) (Ma et al., 2017). Similarly, the concentrations of gemfibrozil and carbamazepine were similar to those in the above-mentioned rivers, with a high detection frequency of 96.4 % and 97.6 %, respectively.
However, the concentrations of the detected PhACs in this study were different from those reported in other countries, especially in Europe and South Africa. For example, the highest detected concentration of diclofenac acid (53.9 ng/L in this study) is up to 18740 ng/L in Spain (Muñoz et al., 2009; Osorio et al., 2012; 2016; Mijangos et al., 2018), 568 ng/L in UK (Ashton et al., 2004; Kasprzyk-Hordern et al., 2008a; 2008b; 2009), 675 ng/L in Italy (Mandaric et al., 2017), and 11400 ng/L in South Africa (Madikizela and Chimuka, 2016). Similarly, the concentrations of ibuprofen, naproxen, carbamazepine, and mefenamic acid are relatively low compared with those from those rivers. Moreover, clozapine is detected in concentrations of 2180–8890 ng/L in the KwaZulu-Natal River, South Africa (Matongo et al., 2015), which is much larger than the concentrations of clozapine (< MQL–5.83 ng/L) in this study. The differences in these detected PhACs concentrations in the rivers are possibly due to the usages of these PhACs in different countries (Waleng and Nomngongo, 2022).

3.2 Occurrence and distribution of PhACs in the sediments

For the sediment samples, 7 PhACs were detected, with concentrations in the range of MQL–63.2 ng/g, MQL–31.3 ng/g, and MQL–28.3 ng/g for the Beijiang River, Xijiang River, and Maozhou River, respectively (Figs. S1(b), S1(d), S1(f)). Similar to the water samples, the predominant PhACs was the analgesics/anti-inflammatory, with salicylic acid being found in all the sediment samples. In the three rivers, among the 7 detected PhACs, salicylic acid and gemfibrozil showed the highest detection frequencies (100 % and 92.9 %), followed by naproxen (77.4 %), clozapine (44.0 %), and diazepam (42.9 %). On the other hand, diclofenac, ibuprofen, MCPA, and paracetamol were not detected in any sediments though they had relatively elevated concentrations in the surface waters samples. This could be due to the physicochemical properties of these four compounds. These compounds are not readily distributed into the sediments since they have relatively Log Kow values (0.70, 3.97, 2.53 and 0.46). Nonetheless, diclofenac, ibuprofen, and paracetamol are detected in the Spanish sediments at levels up to 11.0 ng/g, 24.9 ng/g and 222 ng/g, respectively (Biel-Maeso et al., 2017; Silva et al., 2011). Meanwhile, in South Africa, the concentration of ibuprofen in the sediments is up to 659 ng/g (Matongo et al., 2015).
There were large differences in the concentrations of PhACs in the sediments between the dry and wet seasons in most sampling sites. The concentrations of PhACs in the wet season were generally lower than those in the dry season, especially in the Maozhou River. The summed concentrations of determined PhACs in the Maozhou River ranged from 11.6 to 36.8 ng/g in the dry season, and from 3.68 to 7.46 ng/g in the wet season. Similar to these results, the detected PPCPs concentrations in the summer (wet season) are lower than in the winter (dry season) period for the Alpine River sediments (Mandaric et al., 2017). The differences of PhACs in the sediments between the dry and wet seasons could be due to the elevated water flow in wet season and small adsorption of these compounds on sediments. Overall, the concentrations of some detected PhACs in surface waters and sediments were highly correlated, including clozapine (p < 0.01), diazepam (p < 0.01), carbamazepine (p < 0.01), and salicylic acid (p < 0.05) (Table S9).

3.3 Seasonal variation in concentrations of PhACs

The relationship among different PhACs in waters and sediments in the dry and wet seasons was revealed by the heatmap - hierarchical cluster analysis (HM-HCA) (Fig.2 and Fig. S2). Among these PhACs, salicylic acid was classified as a unique class, while the rests were grouped into a class, regardless of the wet or dry season, because salicylic acid maintained a high concentration in surface waters from most sites with high detection frequency. Meanwhile, the sampling sites of the Maozhou River differed from those of the Beijiang River and Xijiang River in the concentrations of PhACs, except for the MZR0 site in the wet season (Fig.2). The Maozhou River could be more polluted than the other rivers since it flows through Shenzhen and Dongguan city. These two cities have more than 4.17 million residents and highly developed industry, therefore potentially contributing more PhACs into this river. However, the concentrations of PhACs in the sediments did not show much differences among the sites from different rivers in this study (Fig. S2).
Fig.2 The heatmap-hierarchical cluster analysis for detected PhACs in surface waters in the wet (Panel a) and dry (Panel b) seasons.

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The concentrations of PhACs in surface waters and sediments varied among and within the sampling sites of the Beijiang River, Xijiang River, and Maozhou River (Fig.3). A significant difference can be found in concentrations of PhACs in both the surface waters (PERMANOVA; pseudo–F = 23.874, p < 0.001) and sediments (PERMANOVA; pseudo–F = 7.489, p < 0.001) among the Beijiang River, Xijiang River, and Maozhou River (Fig.3). In the PCoAs, 3 principal components (PCOs) could account for up to 69.0 % of the variance, with 45.2 % of the variance by the first PCO (PCO1), 14.5 % by PCO2, and 9.25 % by the PCO3. Similarly, these 3 PCOs could explain 66.8 % of the variance of the PhACs concentrations in sediments among the Beijiang River, Xijiang River, and Maozhou River, with 28.6 % by PCO1, 22.8 % by PCO2, and 15.3 % by PCO3 (Fig.3).
Fig.3 PCoA analysis of the detected PhACs concentrations between and within the Beijiang River, Xijiang River, and Maozhou River basins. Panel a and Panel b display the PCoA analysis of the detected PhACs concentrations in surface waters and sediments. Panel c, Panel e, and Panel g display the PCoA analysis of the detected PhACs concentrations in surface waters between the wet and dry season. Panel d, Panel f, and Panel h displays the PCoA analysis of the detected PhACs concentrations in sediment between the wet and dry season.

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For each river, the PCoA analysis showed that the PhACs concentrations in the waters and sediments varied between the wet and dry seasons, which was obvious in the two-dimensional ordination plots (Fig.3). In surface waters, approximately 59.2 %, 69.5 % and 80.1 % of the variance in the PhACs concentrations in the waters between wet and dry season in the Beijiang River, Xijiang River, and Maozhou River was respectively explained by 3 PCOs (PERMANOVA; pseudo–F = 6.663, p < 0.001; pseudo–F = 3.5502, p < 0.001; pseudo–F = 1.3523, p = 0.2667, respectively). Similarly, 70.0 %, 63.3 % and 90.4 % of the variance in those of the sediments of the Beijiang River, Xijiang River, and Maozhou River was accounted by the 3 PCOs, respectively (PERMANOVA; pseudo–F = 1.3099, p = 0.2482; pseudo–F = 0.98594, p = 0.4353; pseudo–F = 6.1122, p < 0.001, respectively).

3.4 Contaminant flux, estimated emission, and usage

The contaminant flux of each site in the wet and dry seasons for different rivers was estimated (Fig.4). The contaminant flux of the detected PhACs compounds in the dry season was significantly lower than that in the wet season, probably due to the higher surface water flow in the wet season. 81.3 % (Fig. S3(b)), 76.6 % (Fig. S3(c)), and 93.7 % (Fig. S3(d)) of the variance of contaminant flux between the wet and dry season within the Beijiang River, Xijiang River, and Maozhou River was accounted for by the 3 PCOs in the PCoAs analysis. In addition, the contaminant flux at the sites near the estuaries was relatively higher than that of other sites. The Xijiang River and Beijiang River had the highest contaminant flux in both seasons, approximating more than 11 000 kg/a, whereas only 25.7 kg/a in the Maozhou River. The spatial variation of contaminant flux varied significantly (Fig. S3a, PERMANOVA; Pseudo–F = 6.7305, p < 0.001) among the Beijiang River, Xijiang River, and Maozhou River, with 38.0 % of the variance explained by PCO1, 16.6 % by PCO2, and 13.1 % by PCO3.
Fig.4 Contaminant flux (kg/a) of the detected PhACs in the Beijiang River (Panel a), Xijiang River (Panel b), and Maozhou River (Panel c).

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The estimated emission and back-estimated usage of detected PhACs compounds for each sampling site were calculated (Fig. S4). According to volume of the sewage discharge (Table S4) and the concentrations of the detected compounds (Fig.1), the PhACs emission at each sampling site was estimated. The estimated emission of the Maozhou River (6.66–91.0 kg/a) was higher than that of the Beijiang River (0.28–4.22 kg/a) and the Xijiang River (0.12–6.72 kg/a). The higher emission of Maozhou River is most likely due to that Maozhou River flows through Shenzhen city, which produces larger volume of municipal sewage from its larger population. In addition, the estimated emission of Maozhou River was mainly contributed by commonly used painkillers, such as ibuprofen (37.9 %), paracetamol (16.4 %), salicylic acid (13.5 %), and diclofenac (13.2 %), while the emission of Beijiang River and Xijiang River was mainly contributed by salicylic acid (51.1 % and 41.7 %), MCPA (14.1 % and 19.6 %) and diclofenac (7.0 % and 12.3 %). It should be noted that the dilution factor of the river was ignored in the estimation, which may lead to the underestimated emission.
The usage was back-estimated using Eq. (3) and the removal rate of each compound obtained from our early study (Yang et al., 2017, 2018; Lei et al., 2021) (Figs. S4(b), S4(d), S4(f)). Salicylic acid and paracetamol were the main compounds in the Beijiang River and Xijiang River by back estimation. The highest back-estimated usage of salicylic acid and paracetamol was respectively 161 and 754 kg/a for the WR20 site of the Xijiang River. In the Maozhou River, the back-estimated usage of paracetamol was the largest. The usage of paracetamol at the MZR5 site was estimated to be 16 584 kg/a.
The widespread distribution of PhACs in the Pearl River basin is mainly due to anthropogenic activities. In order to explore the relationship between the emission of PhACs and gross domestic product (GDP), the correlation between PhACs-related data and the GDP of the city was determined by linear regression analysis (Table S4). The correlation coefficient (R2) between the estimated emission and GDP was 0.895 (Fig. S5), implying a close relationship between the PhACs emissions and GDP of each city. However, the R2 between the average concentrations of PhACs in the surface waters in the dry and wet seasons and GDP was 0.137.

3.5 Environmental risk assessment

For each individual compound, the MEC and PNEC were used to calculate risk quotients (RQs) for aquatic organisms (algae, daphnia, and fish) (Tab.2). The criteria for the RQs were as follows in order to define different levels of environmental risk: RQ < 0.01 (insignificant risk), 0.01 < RQ < 0.1 (low risk), 0.1 < RQ < 1 (moderate risk), and RQ > 1 (high risk) (Ågerstrand and Rudén, 2010; Hernando et al., 2006; Bu et al., 2020). Among all the detected compounds, diazepam and ibuprofen were shown to have a moderate risk, which is also supported by other studies (Cunha et al., 2019; Ashfaq et al., 2017). While diclofenac, naproxen, carbamazepine, and gemfibrozil were considered to have a relatively low risk. In addition, the maximum concentrations of other detected PhACs compounds were lower than their PNECs, implying their relatively low environmental risk.
Tab.2 Risk Quotients (RQs) of the target compounds
CompoundsTherapeutic classMEC (ng/L)PNEC (µg/L)RQRQmaxRisk
AlgaeDaphniaFishAlgaeDaphniaFish
DiazepamPsycholeptics25.04.20b0.10/7.00c0.010.250.25moderate
IbuprofenAnti-inflammatory drugs2892.60a25.4a3.20a0.110.010.090.11moderate
DiclofenacAnti-inflammatory and antirheumatic products53.91.94a11.3a0.70a0.0280.010.080.08low
NaproxenAnti-inflammatory and antirheumatic products28.52.31a10.4a1.10a0.010.0030.030.03low
CarbamazepineAntiepileptics19.62.13a5.57a1.10a0.0090.0040.0180.018low
GemfibrozilLipid modifying agents12.46.43a25.0a1.10a0.0020.0000.0110.011low
ParacetamolAnalgesics and antipyretics62.517.0a28.7a47.0a0.0040.0020.0010.004/
Mefenamic acidAnti-inflammatory and antirheumaticproducts4.561.25a8.53a1.40a0.0040.0010.0030.004/
ClozapinePsycholeptics5.832.23a6.09a1.70a0.0030.0010.0030.003/
Salicylic acidAnti-inflammatory drugs16060d6.16e0.0030.003/
Clofibric acidLipid-lowering drugs2.744.20.0010.001/
CyclophosphamideAntineoplastic agents0.371.38a166a140a0.0000.0000.0000.000/
SertralinePsychoanaleptics0.71
MCPAHerbicides86.7304f334f562f
6-CPQPsycholeptics4.57///////
BentazoneHerbicides8.65141f215f390f
IndomethacinNonsteroidal anti-inflammatory drugs4.683.57f2.05f2.94f
NordiazepamPsycholeptics0.9823.4f22.5f36.6f

Four levels of risk were considered: RQ < 0.01, insignificant risk; 0.01 < RQ < 0.1, low risk; 0.1 < RQ < 1, moderate risk; RQ > 1, high risk (Ågerstrand and Rudén, 2010; Bu et al., 2013). a) (Bu et al., 2020), b) (Stuer-Lauridsen et al., 2000), c) (Cunha et al., 2019), d) (You et al., 2015), e) (Szabelak and Bownik, 2021). f) EC50 values (mg/L) for Daphnia magna (48 h), algae (96 h) and fish (96 h) used to calculate PNEC based on QSAR models (The Ecological Structure Activity Relationships, ECOSAR Version 1.11).

4 Conclusions

This study has revealed that PhACs are ubiquitous in the surface waters and sediments of the three major rivers of the Pearl River basin. The concentrations of commonly detected PhACs are comparable to those detected in many other river basins in China, and lower than in other countries. Meanwhile, there is a distinctive spatial and seasonal variation in PhACs occurrence profiles within and among the three river basins. In addition, the estimated emissions and back-estimated usage of PhACs in the Beijiang River and Xijiang River are lower than the Maozhou River, a river running through Shenzhen and Dongguan cities with large volume of municipal sewage due to the large population size. Diazepam and ibuprofen are considered to have a moderate risk among these PhACs in the Pearl River basin. This study suggests that a multiple-year monitoring the pollution of PhACs is necessary for a complete understanding of the risk of PhACs in the Pearl River basin.

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Acknowledgements

This work was financially supported by the National Natural Science Foundation of China (Nos. 41877358 and U1701242), the Pearl River Talent Plan of Guangdong Province (No. 2017GC010244) and the Key R&D projects of Guangxi (No. 2018AB36018).

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Supplementary material is available in the online version of this article at https://doi.org/10.1007/s11783-023-1646-8 and is accessible for authorized users.

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