Occurrence of quinotone antibiotics and their impacts on aquatic environment in typical river-estuary system of Jiaozhou Bay, China

Ecotoxicology and Environmental Safety 190 (2020) 109993

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Occurrence of quinotone antibiotics and their impacts on aquatic environment in typical river-estuary system of Jiaozhou Bay, China

T

Ke Liua,b,c, Daolai Zhangb,c,∗, Xiaotong Xiaoa,c,∗∗, Lijuan Cuid, Hailong Zhanga,c a

Key Laboratory of Marine Chemistry Theory and Technology, Ministry of Education /Institute for Advanced Ocean Study, Ocean University of China, Qingdao, 266100, China b Qingdao Institute of Marine Geology, Qingdao, 266071, China c Laboratory for Marine Ecology and Environmental Science, Qingdao National Laboratory for Marine Science and Technology, Qingdao, 266237, China d Institute of Wetland Research, Chinese Academy of Forestry, Beijing, 100091, China

A R T I C LE I N FO

A B S T R A C T

Keywords: Quinotone antibiotics Surface sediments Risk quotients River-estuary system Jiaozhou Bay

There is a data gap on occurrence and transport of antibiotics in river-estuary system, with limited understanding of their impact on aquatic environment. To gain insight into the antibiotic pollution in river-estuary system, 22 surface sediments and 5 wetland plants from Yang River and its estuary in Jiaozhou Bay were selected to explore the occurrence and transport of eight quinotone antibiotics (QNs), and their impacts on aquatic environment. Our results indicated that QNs were widely present in the sediments from Yang River and its estuary, with a range of 1.34–8.69 ng/g (average 4.46 ng/g) in Yang River and 0.99–10.86 ng/g (average 3.92 ng/g) in its estuary, respectively. No obvious correlations were observed between QNs values and TOC contents in sediments from our study area, due to low detective concentrations and frequencies of QNs. The mass loading of individual antibiotic from Yang River to its estuary was from 11.73 to 391.59 g/year, far below those from the other estuarine regions all over the world. QNs were observed in all five wetland plants, demonstrating that QNs contaminants could be taken up by wetland plants and providing the evidence that phytoremediation could be a feasible way to remove contaminants. Negative partial coefficients between individual antibiotic and brassicasterol biomarker suggested the presence of QNs inhibited the phytoplankton growth. Evaluation of ecological risk based on the values of risk quotients (RQs) showed that OFL in Yang River displayed medium risk for algae, and CIP and OFL in its estuary also displayed medium risk value for plant and algae. The results could provide powerful basis on controlling river antibiotics pollution to enhance rivers-estuary security in similar regions.

1. Introduction In the past several decades, antibiotics has been widely used in medicine and aquaculture husbandry to prevent or treat human and animal diseases, and to promote animal growth (Ginebreda et al., 2010; Lindberg et al., 2014; Phillips et al., 2015; Rehman et al., 2015; Kafaei et al., 2018). Numerous studies showed that some of the administered antibiotics were metabolized in the body, and almost 90% of them could be excreted via feces or urine (Klaus, 2009; Kümmerer, 2009; Carvalho and Santos, 2016). These molecules were released into environment via municipal wastewater effluents, agricultural activities, or the direct discharge of untreated waste. However, a significant amount of antibiotics could not be eliminated from the wastewater due to

limited removal efficiencies of typical wastewater treatment processes, so that most antibiotics residues were discharged into the environment (Ternes et al., 2004; Rico et al., 2013). As a result, considerable amounts of antibiotics have been detected in varying environments. Although antibiotic residues are lower than inhibitory level, continual inputs of antibiotics could cause their accumulations in the environment even to cause antibiotics resistance genes in some bacteria or microorganisms (Ruoting et al., 2006; Tao et al., 2010; Zhang et al., 2013; Xiong et al., 2015;Awasthi et al., 2019). Additionally, widespread antibiotics could also generate a potential risk on ecosystems and even human health (Kümmerer, 2009). For example, Song et al. (2017) have demonstrated that antibiotics residues around Tai Lake posed the highest dietary risk in all aquatic species. Besides, the presence of

∗

Corresponding author. Qingdao Institute of Marine Geology, Qingdao, 266071, China. Corresponding author. Key Laboratory of Marine Chemistry Theory and Technology, Ministry of Education /Institute for Advanced Ocean Study, Ocean University of China, Qingdao, 266100, China. E-mail addresses: [email protected] (D. Zhang), [email protected] (X. Xiao). ∗∗

https://doi.org/10.1016/j.ecoenv.2019.109993 Received 24 August 2019; Received in revised form 17 November 2019; Accepted 20 November 2019 0147-6513/ © 2019 Elsevier Inc. All rights reserved.

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which is located at the west coast of the Yellow Sea as a typical semienclosed bay with poor hydrodynamic environment. Over the past years, coastal populations have increased rapidly, causing elevated pollutant input to Jiaozhou Bay via rivers, such as dichlorodiphenyltrichloroethanes (DDTs) (Ma et al., 2001), polycyclic aromatic hydrocarbons (PAHs) (Yang et al., 2014; Lang et al., 2015) and trace metals (Xu et al., 2016). Besides dense population, there are emerging marine aquaculture industries around the Jiaozhou Bay. Qingdao gross output value of fishery increased from 0.98 to 203.01 million dollars during 1978–2017, with aquatic products output of 114 thousand tons in 2017 (Qingdao Statistical Yearbook data). In order to prevent diseases and promote rapid growth of aquatic product, antibiotics were often added directly into aquatic ponds by farmers (Dolliver and Gupta, 2008; Carvalho and Santos, 2016), resulting elevated antibiotic residues accompanying increased fishery output all over the world, the same in Jiaozhou Bay of China. To date, the study of loadings of pollutants from rivers into Jiaozhou Bay is rare. The knowledge gap of occurrence and transport of antibiotics and their impacts on aquatic environment in river-estuary system limits better understanding of the fate of antibiotics. The Yang River is one of the major rivers flowing into the Jiaozhou Bay with 574.6 million m3 discharge per year, which has been influenced by coastal anthropogenic activities such as wastewater discharge from industries, agriculture and aquaculture. In our previous study, the QNs have been detected in sediments from both the Dagu River and Yang River wetlands of Jiaozhou Bay, with higher QNs level found in Yang River wetland (Liu et al., 2018). Hence, we present distribution of the QNs concentrations in sediments from Yang river-estuary system in this study, to explore their impacts on aquatic environment and to assess the ecologic risk of QNs to the aquatic organisms.

antibiotics in environmental media has potential undesirable effect on organism, as the antibiotics have been detected in algae, plant, bile, muscle and liver of fish (Tang et al., 2015; Chen et al., 2018). Therefore, the residual, migration and degradation of antibiotics in environmental mediums have drawn the attention of the entire community. Antibiotics have been used as one class of novel proxies to assess the anthropogenic influence on environment. Several studies indicated that existence of antibiotics have been found in different countries all over the world, including rivers in American (Kolpin et al., 2002, 20–420 ng/L), wastewater treatment plant and rivers in Switzerland and Australia (Golet et al., 2003, 255–568 ng/L; Watkinson et al., 2009, 20–2800 ng/L), aquaculture water in Italy and Persian Gulf of Iran (Giorgia Mary et al., 2004, 0.1–578.8 ng/g; Kafaei et al., 2018, 7.89–149.63 ng/L), groundwater in Spain (López−Serna et al., 2013, 0.1–16.7 ng/L), and even fish in Puget Sound estuaries (Meador et al., 2016, 0.2–34 ng/g). In China, antibiotics residues were widely detected in soils (Li et al., 2015, 0.08–80 ng/g; Sun et al., 2017, 0.01–27.7 ng/g), rivers (Xu et al., 2013, 1.8–45.6 ng/L) and sediments (Liang et al., 2013, 0.9–13.5 ng/g; Chen and Zhou, 2014, 0.2–10.2 ng/g; Zhao et al., 2016, 0.87–104.75 ng/g). As reported, the amount of antibiotics consumption in China was on the top of the world, reaching up to 162000 tons in 2013, much higher than that in the USA (17900 tons, 2011/ 2012) and UK (1060 tons, 2013) (Zhang et al., 2015). Furthermore, the defined daily doses (DDDs) of antibiotics were 157 units per 1000 inhabitants in China, 5–8 times higher than those in the USA, UK, Canada and Europe (Zhang et al., 2015). These reports also pointed out that antibiotics excreted by human and animals in 2013 were 54000 tons, of which 53800 tons entered into environment via wastewater treatments. However, most of antibiotics in the wastewater treatment plants couldn't be completely removed, thus the residual antibiotics could be conserved in water bodies and even to be absorbed in the marine or river sediments (Conkle et al., 2010; Jia et al., 2012). Quinolone antibiotics (QNs), as a class of antibiotics, are widely used in hospitals, households, and veterinary medicine due to their broad spectrum, less negative effects, and low drug–resistance. Published studies revealed that QNs were determined with highest detection frequency and concentration in sediments than other antibiotics (such as tetracyclines, macrolides and sulfonamides) due to their high partitioning, low mobility, and low biodegradation rates (Golet et al., 2003; Li et al., 2012; Shi et al., 2014). Rivers play important roles in pollutants transport, in the term of an important path to deliver pollutants to estuaries (Wang et al., 2012, 2018a; Zhang et al., 2012; Liu et al., 2015; Keen et al., 2018). River runoff has been considered as the most important contributor and source of antibiotic contaminants (Shimizu et al., 2013). According to previous studies, large amounts of antibiotic contaminants were transported to estuary regions via river runoff, such as Yellow River (Zhang et al., 2012), Pearl River (Xu et al., 2013), Yangtze River (Qi et al., 2014), and Garonne River (Aminot et al., 2016) and so on. Estuaries, the linkage between land and ocean system, are important areas for the transport and storage of antibiotic pollutants driven by anthropogenic activities, including agricultural and urban runoff. For example, antibiotics has been found in UK estuaries, (Thomas and Hilton, 2004), in the Seine estuary and Gironde estuary, France (Togola and Budzinski, 2007; Aminot et al., 2016) and in the Pearl River estuary and Yangtze estuary, China (Xu et al., 2013; Yan et al., 2015). Hence, the transport mechanism of pollutants in the river-estuary system is essential to understand the fate of pollutants in the environment. Antibiotic pollutants poured into rivers are adsorbed onto particles in water column, and then are transported to the estuaries. Under the action of gravity, particles containing antibiotic pollutants settle and are finally buried in surface sediments of estuaries or futher transported to the adjacent sea (Luo et al., 2019). In China, there are far more small and medium rivers than large rivers, so the pollution of small and medium rivers should be carefully considered. Jiaozhou Bay of China is characterized with more than ten small rivers flowing into it every year,

2. Materials and methods 2.1. Sampling sites and sample collection 22 surface sediments and 5 wetland plants were collected from the downstream of Yang River and Estuary in Jiaozhou Bay, China (Fig. 1). Surface sediments (~5 cm) were obtained with a clean stainless steel shovel during 2016, and wetland plants were obtained in areas of homogeneous density during 2017. Each sample was wrapped in precleaned alumina foil and then immediately transferred to laboratory to store at −20 °C.

2.2. Chemicals and materials In this study, we choose eight QNs as target compounds, due to their board spectrum, less side effects, and low drug-resistance. Eight target antibiotics standards including pipemidic acid (PPA, 99.0%), ofloxacin (OFL, 99.0%), enrofloxacin (ENR, 99.0%), ciprofloxacin (CIP, 94.0%), sarafloxacin (SAL, 97.0%), lomefloxacin (LOM, 98.7%), flumequine (FLU, 98.5%), and oxolinic acid (OA, 94.0%), were purchased from Dr. Ehrenstorfer GmbH (Augsburg, Germany); HPLC-grade acetonitrile, phosphoric acid, and triethylamine were purchased from Merck (Darmstadt, Germany); Oasis HLB (6 mL, 500 mg) was purchased from Waters (Milford, MA, USA); ammonia solution and magnesium nitrate hexahydrate were purchased from the Chemical Reagent Factory (Shanghai and Tianjin, China). The ultrapure water was prepared with a Milli-Q water purification system (Millipore, Bedford, MA, USA). Stock solutions of the individual antibiotic compounds were dissolved in acetonitrile and stored in a freezer at −20 °C. Mixed standard working solutions were prepared by diluting them serially using acetonitrile containing 10% Milli-Q water. All of working solutions should be freshly prepared daily for analysis.

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Fig. 1. Map of sampling locations from Yang River and its estuary system, Jiaozhou Bay, China. Sites Y1–Y10 and E1–E12 are locations of surface sediments (red dots) obtained from the downstream of Yang River and its estuary, respectively. Sites P1–P5 are locations of wetland plants (yellow triangle) at the south of the estuary. Different colors represent different functional areas as marked in the study area. (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)

separation, the HLB cartridges were washed using 10 mL methanol and 10 mL Milli-Q water. The QNs was eluted with 15 mL of acidic acetonitrile (Vactonitrile/VH3PO4 = 5:1). The eluent of QNs fraction was concentrated to 0.5 mL under a gentle nitrogen stream at 40 °C, ready for analysis. The extraction and purification of biomarker sterols (including brassicasterol and dinosterol) follow the procedure of Zhao et al. (2006). Briefly, about 5 g sediment samples were freeze-dried and homogenized before any further treatment. Prior to the biomarker analyses, the internal standard C19 n-alkanol was added to the sediments for quantification. Subsequently, the sediments were solvent extracted ultrasonically four times using dichloromethane: methanol (V/V = 3:1) as solvent. Further separation of sterols from total extracts

2.3. Sample extraction The analytical methods of QNs follow the procedure of Turiel et al. (2006). Before extraction, about 5 g sediments were freeze-dried, homogenized and sieved using 100–mesh nylon sieve. Subsequently, the sediments were put into a 50 mL glass tube with 15 mL extract solution which was mixed by 50% Mg(NO3)2 and 5% NH3•H2O (V/ V = 92:8). The mixture was ultrasonically extracted for 30 min, and centrifuged for 10 min. The supernatant was poured into a clean tube. The same extraction process was repeated for four times and the supernatants were combined as total extracts. Further separation of the QNs from the total extracts was carried out on Oasis HLB cartridges (500 mg, 6 mL, Waters) for purification and condensation. Prior to 3

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was carried out via open-column chromatography with SiO2 as a stationary phase using 12 mL dichloromethane: methanol (V/V = 95:5) after the elution of hydrocarbons using 8 mL n-hexane. Sterols were silylated with 40 μL BSTFA (bis-trimethylsilyl-trifluoroacetamide; 70 °C, 1 h) before instrumental analysis. 2.4. Instrumental analysis The QNs were analyzed by Shimadzu LC-20AT High Performance Liquid Chromatography (HPLC) system (Kyoto, Japan), equipped with a fluorescence detector. The separation of target antibiotics was achieved on an Agilent ZORBAX Exclipse XDB-C18 (5 μm, 4.6 mm × 150 mm; Agilent Technologies, Palo Alto, CA, USA). The mobile phase used in HLPC contained acetonitrile (A phase) and 1% phosphoric acid (V/V, pH = 3) (B phase), with a constant flow rate of 0.8 mL/min kept with 20 μL injection. The gradient elution program follows the procedure of 0–8 min, 10% A; 8–10 min, 10%–12% A; 10–23 min, 12% A; 23–40 min, 80% A; 40–45 min, 80%–15% A. The excitation wavelength and emission wavelength of fluorescence detector were 285 nm and 460 nm during 0–33 min, respectively, increasing to 325 nm and 365 nm during 33–45 min, respectively. Sterols were detected on gas chromatography (Agilent 6890 N GC with a HP-1 capillary column 50 m, 0.32 mm i.d., 0.17 μm film thickness), coupled to FID detector. H2 was applied as the carrier gas at a constant flow rate of 1.3 mL/min. The oven temperature program started at 80 °C, held for 1 min, then increased at 25 °C/min to 200 °C, at 4 °C/min to 250 °C, at 1.8 °C/min to 300 °C, and held for 15 min at 300 °C. Every of biomarker was identified and verified by Thermo Gas Chromatograph-Mass spectrometer (GC/MS) by comparison with the retention times of the standard substances. The MS was operated in the electron ionization (EI) mode at 70 eV (m/z 50 and 650), and He was selected as the carrier gas.

Fig. 2. Concentrations of QNs residues in sediments from Yang River of Jiaozhou Bay, China. Eight QNs are showed by different colors. On the top are the sedimentary TOC contents from corresponding stations. (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)

Bay wetlands (Liu et al., 2018). As reported, OA was widely used in aquaculture industries due to its good clinical effects at low dosage rate and low bioavailability in aquatic animals (Le and Munekage, 2004; Sarmah et al., 2006; Lai and Lin, 2009). OFL displayed the highest mean concentration (1.77 ng/g), consistent with the monitoring results in other regions, such as Pearl River estuary, Chaohu Lake and Tai Lake (Liang et al., 2013; Tang et al., 2015; Song et al., 2017). According to Li et al. (2012), OFL exhibited the highest sediment-water distribution coefficient, indicating that it tends to accumulate in sediments than other antibiotics (Yang et al., 2010; Li et al., 2012). Furthermore, previous studies have revealed medical usage of OFL was relatively high as medicine to treat human diseases in China (Liang et al., 2013). Although OFL displayed highest concentration than other QNs in Yang River of Jiaozhou Bay, pollution of OFL was at low level compared to the large rivers, e.g., Yellow River (3.07 ng/g) and Liao River (3.56 ng/ g) in China (Zhou et al., 2011), and Marshlands (2.7 ng/g) in Spain (Vazquez-Roig et al., 2012). Besides OFL, CIP was the second highest medicine consumption while it was observed with lowest detection of frequency (10%) and concentration (ND–0.59 ng/g) in Yang River (Fig. 2), due to its higher photogradation rate with short half-life in water (Lam et al., 2003; Cardoza et al., 2005). PPA exhibited the second highest average values, but was only detected at two stations (Fig. 2). The high concentrations of PPA at the two stations could be consistent with the aquaculture area which was located on the south of Yang River (Fig. 1). Estuary has been a significant sink of contamination, receiving considerable amounts of organic pollutants from land (via rivers, runoff and deposition) and marine. The QNs concentrations in sediments from the Yang River estuary were from 0.99 to 10.86 ng/g (average 3.92 ng/ g), with TOC values from 0.13% to 1.08% (Fig. 3). The QNs concentrations were also far below the trigger value of 100 ng/g in soil (Le and Munekage, 2004; Karcı and Balcıoğlu, 2009). Highest QNs residue was found at E3 station in the north of Yang River estuary (Fig. 3). Generally, the QNs concentrations in sediments from the north of the estuary (E1–E4 stations) were all higher than those from the south of the estuary (E5–E12 stations) in the wetlands. This can be interpreted as that plant in wetlands has significant purifying efficiency on pollutants (Dettenmaier et al., 2009; Herklotz et al., 2010). Of all target antibiotics, OA was also the most frequently detected compound, found in all estuary stations (Fig. 3). This could be ascribed to the large-scale usage of OA in aquaculture and livestock (Le and Munekage, 2004;

2.5. Quality control In this study, quantitative analysis of individual antibiotic was performed using external standard methods. The linear calibration curves were performed by different concentrations of external standard (1.00, 2.00, 5.00, 10.00, 50.00, 100.00, and 200.00 μg/L) and their correlation coefficients with individual antibiotic compounds were all higher than 0.999. The recoveries for target spiked antibiotics in surface samples ranged from 79% to 120% with relative standard deviations less than 20%. The detective limits of antibiotic compounds were from 0.010 to 0.370 ng/g dry weight in the sediments. Quantitative analysis of brassicasterol and dinosterol was performed using internal standard method. Each biomarker compound were quantified by calculating the ratios of target peak area to those of the internal standards and every sample was in triplicate to ensure precision with relative standard deviations of < 10%. 3. Results and discussion 3.1. Occurrence and distribution of QNs in the Yang River and estuary The detected QNs ranged from 1.34 to 8.69 ng/g (average 4.46 ng/ g), with a TOC value from 0.39% to 1.20% in the Yang River, showing contaminated level (Fig. 2). The QNs concentrations in the sediments from the Yang River were relatively low compared to the trigger value of 100 ng/g in soil (Le and Munekage, 2004; Karcı and Balcıoğlu, 2009), which was established by the Steering Committee of the Veterinary International Committee on Harmonization (VICH). The highest concentration of QNs was observed at sampling site of Y1 (8.69 ng/g), located at the west most station in Yang River. Among all analyzed target antibiotics, OA was the most frequently detected compound, with detection frequencies of 100 percent at all sampling sites in the river (Fig. 2), reflecting its extensive use in this region, similar to Jiaozhou 4

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antibiotics, however, showed less than 1 dilution factors with range of 0.4–0.6 (Table 1). The less than 1 dilution factors of targets could be explained as that target QNs have been widely used in agriculture in the coastal region of Jiaozhou Bay. That means the antibiotics residues in our study area were not from the point source pollution, but from various sources, including fluvial transport, aquaculture, offshore pollution and wastewater discharge (Lang et al., 2015; Wang et al., 2018b). The sedimentary organic contaminants are related to sediment physicochemical properties, such as pH, salinity and TOC (Nie et al., 2015; Liu et al., 2016b). Especially TOC, reflect the absorption of pollutants in sediments. Positive correlations have been found between QNs and TOC (Shi et al., 2014; Liu et al., 2016a), as well as between individual antibiotic CIP and TOC (Liu et al., 2016a). We performed Person's correlation analysis to compare the correlation between QNs and TOC (Table S1). Statistical analysis showed no obvious correlation between total QNs values and TOC contents in sediments from our study area. Furthermore, individual antibiotics were also not significantly correlated with TOC values (Table S1). The positive correlation coefficient between TOC and OA (r = 0.42, P > 0.05), was slightly higher than other antibiotics. Except OA and SAL with high detection frequencies (100% and 86%, respectively), the detection frequencies of other six antibiotics were all below 50% (Figs. 2 and 3). Simultaneously, SAL exhibited lower concentration than OA in the study area. Therefore, low detective concentrations and frequencies may be accountable for the poor correlation between QNs and TOC in our study.

Fig. 3. Concentrations of QNs residues in sediments from Yang River estuary of Jiaozhou Bay, China. Eight QNs are showed by different colors. On the top are the sedimentary TOC contents from corresponding stations. (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)

Sarmah et al., 2006). PPA and OFL showed the highest mean concentrations of 2.43 and 1.28 ng/g, respectively (Fig. 3). Obviously, the distributions of target compounds in estuary were similar to those in Yang River (Figs. 2 and 3). It is noteworthy that the mean concentrations of OFL, LOM and SAL in estuary were lower than that in Yang River, while the mean concentrations of another five antibiotics, PPA, CIP, ENR, OA and FLU were higher in estuary than those in Yang River (Figs. 2 and 3). Generally, QNs concentrations in sediments from the Yang River estuary were far below those from the large river estuaries, such as Pearl River estuary (13.7 ng/g) (Liang et al., 2013) and Yangtze estuary (458.2 ng/g) (Shi et al., 2014) in China. This is ascribed to the great difference of population, aquaculture industry densities between Jiaozhou Bay and large estuarine regions.

3.3. Mass loadings of antibiotics Almost 20 billion metric tons of sediments are transported into ocean through rivers every year and most ultimately deposit in the estuary (Milliman and Syvitski, 1992). River-derived sediment is a major source of multiple contaminants from anthropogenic activities entering to Jiaozhou Bay. In our study area, although relatively low QNs concentrations were found in Yang River and its estuary sediments, the continuous input of contaminations could also induce environmental risks in Jiaozhou Bay. Sediment loading is a key parameter to assess the effect of river discharge on marine environment. Therefore, the annual inputs of antibiotics with sediment loadings from Yang River into the Jiaozhou Bay were calculated based on the measured concentrations in this study. According to sediment runoff from Qingdao Hydrographic Bureau, the sediment loading from Yang River to Jiaozhou Bay was 22150 tons (average of 1960–2008). We calculated mass loadings of every antibiotic from Yang River according to the following equation:

3.2. Environmental distribution Generally, if there was point source pollution in the Yang River, the targets in receiving water should be diluted by ten or dozen times (Minh et al., 2009). In this study, the dilution factor was used to evaluate the extent of attenuation of antibiotic compounds from river to estuary and it is calculated according to the average concentration of individual antibiotics in river and average concentration of individual antibiotics in estuary as following (Minh et al., 2009): Dilution factor = Mean concentration of QNs in the river / Mean concentration of QNs in the estuary. The results indicated that the dilution factor of OFL, SAL and LOM ranged from 1.4 to 1.6 (Table 1), similar to those in Jiaolai River of Laizhou Bay (1.2–3.3 times, Zhang et al., 2012). The other five

QN mass loadings (g/year) = QN concentration (ng/g) × sediment loadings (t/year) / 1000 The results indicated that the mass loadings of individual QNs ranged from 11.73 to 391.59 g/year (Table S2). OFL exhibited highest mass loading among the QNs in our study area (Fig. S2), similar to the highest OFL loading in Pearl River estuary (64.5 tons/2009, Xu et al., 2013), and consistent with the heavy usage of OFL in China (Zhang et al., 2015). Compared to other estuarine regions, the total mass loadings of QNs from Yang River to Jiaozhou Bay were still very lower (988.52 g), far below those from the Pearl River Delta into South China Sea (193 tons/2009–2010, Xu et al., 2013), the Yangtze River into the East China Sea (151.7 tons/2009–2010, Qi et al., 2014), Yellow River into Laizhou Bay of China (4.25 tons/2009, Zhang et al., 2012), and the Garonne River in France into the Atlantic Ocean (3.7 tons/2012, Aminot et al., 2016). This could be explained by much higher runoff volume of large rivers than Yang River (Zhang et al., 2012; Xu et al., 2013; Qi et al., 2014), resulting great difference in mass loading of QNs contaminants between them. Although the mass loadings from Yang

Table 1 Dilution factors of QNs in sediments from Yang River to estuary.

PPA OFL CIP LOM ENR SAL OA FLU

Mean concentration of QNs in theYang River (ng/g)

Mean concentration of QNs in the Yang River estuary (ng/g)

Dilution factor

1.51 1.77 0.11 0.17 0.08 0.09 0.12 0.06

2.43 1.28 0.30 0.11 0.14 0.06 0.21 0.10

0.6 1.4 0.4 1.6 0.6 1.4 0.6 0.6

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Fig. 5. The relative contributions of individual antibiotics to the growth of diatom. Numbers on each arrow indicate partial correlation coefficient values.

et al., 2019). Fig. 4. QNs concentrations in wetland plants from Yang River estuary of Jiaozhou Bay, China. Eight QNs are showed by different colors. (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)

3.5. Potential impact of QNs on phytoplankton Contaminants from anthropogenic activities have a potential threat to aquatic organisms. Without exception, antibiotics were detrimental to primary producers (Rico et al., 2018). Phytoplankton are dominant primary producers in aquatic ecosystems and are very sensitive to antibiotic contaminants (Rico et al., 2018). Brassicasterol and dinosterol, produced by diatom and dinoflagellate, have been used as indicators to reflect the biomass of phytoplankton (Volkman, 1986; Zhao et al., 2006). In Jiaozhou Bay, brassicasterol concentrations (average 460 ng/ g) were higher than dinosterol (average 74 ng/g) in sediments (our unpublished data). Similarly, diatom species make up 60–82% of phytoplankton and diatom cell abundance accounted for > 95% of phytoplankton biomass (Yao et al., 2010). Therefore, we constructed a partial correlation analysis between the level of individual antibiotic and brassicasterol, to explore the effects of QNs contaminants on diatom in our study area. Except OA, the partial correlation coefficients between brassicasterol and other seven antibiotics concentrations were all negative (Fig. 5), indicating that most QNs contaminants could be harmful to diatom growth because diatoms are sensitive to environmental condition and they response quickly to environmental changes. A strong negative relationship was also observed between heavy metals and diatom (Chu et al., 2019), and diatom variations have been used to reconstruct and monitor past and future metal contamination (Cunningham et al., 2005).

River inputs to Jiaozhou Bay were very low, the long-time scale inputs could lead to cumulative antibiotics in sediment of Jiaozhou Bay. It is the first time to estimate the mass loadings of QNs from river-estuary system in Jiaozhou Bay and the results could be as a reference for government regulators. 3.4. Uptake of QNs in wetland plants Previous studies have confirmed that plants like corn, lettuce, potato, onions and Chinese cabbage could take up antibiotics contaminants (Dolliver et al., 2007; Kumar et al., 2005). Further investigations revealed that the wetland plants have very high removal efficiency (98.4%) for sulfonamide antibiotics (Tai et al., 2019). In Jiaozhou Bay, Spartina alterniflora was the dominant wetland plant. In our study, QNs were found in all five Spartina alterniflora samples from wetland in the south of Yang River estuary (Fig. 1), ranging from 3.60 to 28.22 ng/g with a mean value of 14.06 ng/g (Fig. 4). Different levels of QNs in plants were observed at different sites (Fig. 4). As published, contaminants can be present in different environmental media, including soil, water and air. In this study, the phenomenon of different levels of QNs in the plants at different sites could be explained by different uptake processes of QNs in plants, such as uptake with transpiration water, diffusion from sediment into plants. And a significant uptake of QNs could occur in contaminated air when the QNs concentration was very low (Mikes et al., 2009; Trapp and Legind, 2011). To explore the correlation of QNs concentrations in plants and sediments, we compared QNs concentrations in plants to those in adjacent sediments. The plant sites P1, P3 and P4 were closed to the sediment sites E7, E11 and E8, respectively (Fig. S1). The comparison showed that QNs concentrations in plants were high at low QNs in sediments, and decrease for higher QNs in sediments content. This result was similar to the finding performed on DDT uptake by radishes. According to Mikes et al. (2009), when high contaminants occurred in the sediment, adjacent plant will have a limited sorption capacity for contaminants and it will be saturated quickly. Besides, other physical factors and environmental conditions, such as grain size, pH, salinity, temperature and humidity in sea water could also affect the uptake behavior of antibiotics from sediments to wetland plants (Azanu et al., 2016). Overall, our results confirm that wetland plants could take up contaminants from sediments as reported by previous studies (Wang

3.6. Ecological risk assessment Due to ubiquitous detection of QNs in different environmental compartments from all over the world, urgent concern has been paid on the influence of antibiotics residues on organisms and human health. Previous studies have revealed that antibiotics residues in environment compartments could induce the acute and chronic toxicity for aquatic and marine organisms, such as algae, plant invertebrate and fish (Isidori et al., 2005). To assess the risk of antibiotics on aquatic organisms, we performed the ecological risks using risk quotients (RQs) according to Hernando et al. (2006). RQs are calculated using the following formula: RQs = MEC / PNEC PNEC

wat

= LC50 or EC50 / AF

RQs are calculated through the measured environmental concentration (MEC) divided by the predicted no effect concentration (PNEC). Where MEC was maximum measured environmental concentration among each analyzed target antibiotic, while PNEC was 6

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Table 2 The risk quotients (RQs) for the aquatic organisms as calculated from the measured environmental concentration (MEC) and the predicted environmental concentration (PNEC) in Yang River and Estuary of Jiaozhou Bay. Targets

CIP LOM ENR

OFL

PPA SAL OA FLU

Taxonomic group

Algae Plant Algae Plant Algae Plant Invertebrate Fish Algae Plant Invertebrate – – Fish –

L(E)C50 (mg/L)

0.017 (24 h) 0.203 (7d) 0.186 (24 h) 0.106 (7d) 0.049 (5d) 0.114 (7d) 56.7 (48 h) > 100 (48 h) 0.021 (24 h) 0.126 (7d) 17.41 (48 h) – – 4000 500–1000

PNEC (ng/L)

17 203 186 106 49 114 56700 100000 21 126 17410 – – – –

Maximum MEC (ng/L)

Maximum RQs (MEC/PNEC)

Yang River

Estuary

Yang River

Estuary

1.198

2.284

2.368

0.996

0.606

0.138

12.945

2.364

14.812 0.665 2.095 0.393

3.254 0.109 1.476 0.427

0.07 0.006 0.013 0.022 0.012 0.005 0.000011 0.000006 0.616 0.103 0.001 – – – –

0.134 0.011 0.005 0.004 0.003 0.001 0.000002 0.000001 0.113 0.019 0.00014 – – – –

wat

= 1000 MEC

sed

Robinson et al. (2005) Robinson et al. (2005) Robinson et al. (2005) Robinson et al. (2005) Robinson et al. (2005) Robinson et al. (2005) Li et al. (2012) Li et al. (2012) Robinson et al. (2005) Robinson et al. (2005) Robinson et al. (2005)

Yu et al. (2005) Xu (1996)

4. Conclusion

obtained using the EC50 or LC50 divided by the assessment factor (AF). LC50 or EC50 is the lowest median effective concentration value obtained from the available literature (Table 2), and AF was chosen to be 1000 to represent chronic toxicity (Park and Choi, 2008). To date, there is rare information on risk assessment of antibiotics in sediments or soil compartments. Therefore, to better assess the environmental risk of antibiotics in sediments, we should determine MEC of antibiotics in water (MECwat) through MECsed using the following equation (Carlsson et al., 2006; Hernando et al., 2006): MEC

References

In this study, the occurrence and spatial characteristics of eight QNs were investigated in surface sediments and wetland plants from Yang River and Estuary of Jiaozhou Bay. The highest concentrations of QNs in sediments were observed at the west most station of river and north of Yang River estuary, respectively. Compared to other areas, the mass loadings of antibiotics contaminations in sediments from Yang River to estuary were relatively lower, but the continuous inputs could lead to cumulative antibiotics in sediments. QNs were found in all wetland plants and showed higher values than those in sediments, indicating that plants could take up contaminants from sediment and providing the possibility to remove the contaminants using phytoremediation technology. The results of Partial correlation analysis revealed that the growth of diatom could be affected by the QNs. The potential ecological risks of target antibiotics based on RQs suggested that OFL in Yang River, and CIP and OFL in estuary displayed medium environmental risk value for plant and algae, while other target antibiotics exhibited lower ecological risks to environment. Therefore, tight management measures should be urgently applied to control river contamination in Jiaozhou Bay and this investigation could be considered as a reference for other coastal zones with similar situations all over the world.

× %TOC / Koc

Where %TOC and Koc refer to total organic carbon and sediment–water partition coefficient, respectively. Koc was defined as a constant with the value of 407.38 according to Piao et al. (1999). Generally, the risk levels based on RQs were classified into three categories (de Souza et al., 2009) as high risk value (RQs > 1), medium risk value (0.1 < RQs < 1) and low risk value (RQs < 0.1). RQs for each target antibiotics in our study were shown in Table 2. Although most of target antibiotics posed lower risk values in surface sediments from Yang River, the RQs levels of OFL for algae (0.616) and plant (0.103) showed medium environmental risk (Table 2). In estuary, CIP and OFL exhibited medium environmental risk for algae with the RQs values of 0.134 and 0.113, respectively, while the RQs of other antibiotics showed low risks. All of target antibiotics presented low environmental risks for invertebrate and fish (Table 2), consistent with previous studies that invertebrate and fish were insensitive to antibiotics exposure compared to algae (Isidori et al., 2005; Kümmerer, 2009). Therefore, the antibiotics residues were at low to medium risk for algae and plant, and low risk for invertebrate and fish in the study regions. In recent years, pollutants have been observed in various small river-estuary systems all over the world. Quantities of measurements have been carried out to control the total mass loadings of pollutants entering marine system. Such as in Jiaozhou Bay, each river has been in charge of its own river director to control the pollutants. Furthermore, previous studies have demonstrated that constructed wetlands could remove the pollutants successfully and phytoremediation could be a feasible way to remove contaminants. According to Fernandes et al. (2015) and Santos et al. (2019), constructed wetlands have high removal efficiencies (above 85%) for antibiotics, such as ENR (Fernandes et al., 2015; Santos et al., 2019). Therefore, in the future, constructed wetlands could be applied in the river-estuary systems to remove the antibiotics pollutants from river transport in Jiaozhou Bay.

Author contribution section Ke Liu: Conceptualization, investigation, Writing–Original Draft, Daolai Zhang: Conceptualization, Resources, Formal analysis, Xiaotong Xiao: Conceptualization, Writing–Review & Editing. Lijuan Cui: Project administration. Hailong Zhang: Investigation, Resources.

Acknowledgments This work was supported by National Key R&D Program of China [Grant No. 2017YFC0506200]; the National Science Foundation of China [Grant No. 41306064, U1706219], and Key Science and Technology Innovation Program Supported by Shandong Province and Qingdao National Laboratory for Marine Science and Technology [2018SDKJ0504–1]. This is MCTL contribution #211.

Appendix A. Supplementary data Supplementary data to this article can be found online at https:// doi.org/10.1016/j.ecoenv.2019.109993. 7

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