Distribution, sources and composition of antibiotics in sediment, overlying water and pore water from Taihu Lake, China

Distribution, sources and composition of antibiotics in sediment, overlying water and pore water from Taihu Lake, China

Science of the Total Environment 497–498 (2014) 267–273 Contents lists available at ScienceDirect Science of the Total Environment journal homepage:...

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Science of the Total Environment 497–498 (2014) 267–273

Contents lists available at ScienceDirect

Science of the Total Environment journal homepage: www.elsevier.com/locate/scitotenv

Distribution, sources and composition of antibiotics in sediment, overlying water and pore water from Taihu Lake, China Jian Xu a,b, Yuan Zhang a,b,⁎, Changbo Zhou a, Changsheng Guo a,b, Dingming Wang a,b, Ping Du a, Yi Luo c, Jun Wan a,b, Wei Meng a,b a b c

State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China Laboratory of Riverine Ecological Conservation and Technology, Chinese Research Academy of Environmental Sciences, Beijing 100012, China College of Environmental Sciences and Engineering, Ministry of Education Key Laboratory of Pollution Processes and Environmental Criteria, Nankai University, Tianjin 300071, China

H I G H L I G H T S • Antibiotics are ubiquitous in sediment, overlying water and pore water in Taihu Lake. • Antibiotics in Taihu Lake originated from human and nonhuman activities. • Ksp is higher than Ksw, indicating the continuous antibiotics input to lake water.

a r t i c l e

i n f o

Article history: Received 27 May 2014 Received in revised form 28 July 2014 Accepted 29 July 2014 Available online xxxx Editor: Thomas Kevin V Keywords: Antibiotics Sources Composition Porewater Taihu Lake

a b s t r a c t The occurrence of 15 antibiotics classified as sulphonamides, fluoroquinolones, macrolides, tetracyclines and trimethoprim in sediment, overlying water, and pore water matrices in Taihu Lake, China was studied. The total concentrations were from 4.1 μg/kg to 731 μg/kg, from 127 ng/L to 1210 ng/L, and from 1.5 ng/L to 216 ng/L in sediment, overlying water and pore water, respectively. Antibiotics in different locations originated from various sources, depending on human, agricultural and aquacultural activities. Composition analysis indicated that human-derived and animal-derived drugs significantly contributed to the total contamination of antibiotics in the lake, indicating the high complexity of contamination sources in Taihu Lake Basin. The in situ sediment–pore water partitioning coefficients were generally greater than sediment–overlying water partitioning coefficients, suggesting continuous inputs into the lake water. This study shows that antibiotics are ubiquitous in all compartments in Taihu Lake, and their potential hazards to the aquatic ecosystem need further investigation. © 2014 Elsevier B.V. All rights reserved.

1. Introduction Antibiotics represent a class of pharmaceuticals that have been used for several decades in human and veterinary medicine for the therapeutic treatment of infectious diseases in humans and for treating and protecting the health of animals, as well as in the animal industry as growth promoters. Recently, antibiotics have been the subject of numerous discussions on the spread and maintenance of bacterial resistance (Pruden et al., 2006). The consumption of antibiotics has been increasing in industrialized and developing countries, resulting

⁎ Corresponding author at: State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China. Tel.: +86 10 84915237; fax: +86 10 84926073. E-mail address: [email protected] (Y. Zhang).

http://dx.doi.org/10.1016/j.scitotenv.2014.07.114 0048-9697/© 2014 Elsevier B.V. All rights reserved.

in their detection in surface water, sediments and biota around the world. Antibiotics in the aquatic environment originate mainly from several sources. Most antibiotics are sewage derived, which are partly eliminated in wastewater treatment processes, present in effluents, and finally reach the ambient surface waters. Antibiotics used for animals enter the environment via manure and wastewater lagoon application to fields as fertilizer. Accidental overflow or leakage from storage lagoons or tanks also likely contributes to the release of these compounds to the environment (Kim and Carlson, 2007). The input of antibiotics could be via surface runoff from agricultural fields, which was confirmed by evidence that sediment concentrations of antibiotics in agriculture-influenced rivers were greater than those in the overlying water matrix (Kümmerer, 2009). Aquacultural activities are another source of antibiotics in the aquatic environment. Drugs used in aquaculture can be transported directly into surface water or accumulate in the sediment (Kim and Carlson, 2006).

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The extensive use of antibiotics has resulted in increasing interest in their fate after consumption and excretion. Given the variability of the physicochemical properties of these chemicals, such as water solubility, octanol/water partitioning coefficient, and acid dissociation constant, antibiotics may be introduced into different environmental compartments. A number of studies reported the occurrence of antibiotics in different environmental matrices. Kümmerer (2009) concluded that the concentrations of antibiotics in different countries were in the same range in aqueous compartments, such as sewage and surface water. Generally, concentrations were in the higher μg/L range in hospital effluent, in the lower μg/L range in municipal wastewater, and in the higher and lower μg/L ranges in different surface waters, groundwater and seawater (Kümmerer, 2009). Antibiotics in sediments in aquaculture waters have been well documented because the substances used in fish farming can enter the sediments directly from the water (Kümmerer, 2009). Understanding antibiotic occurrence in different environmental compartments (e.g., surface water, sediments) could be used to evaluate the transport and ultimate fate of antibiotics in the aquatic environment. Pseudo-partitioning coefficient (P-PC), the ratio of the measured concentration in sediment to the concentration in overlying water, was adopted to describe the dynamics of antibiotics between sediment and surface river waters (Kim and Carlson, 2006; Massey et al., 2010; Zhang et al., 2013). However, limited information is available on the distribution of these compounds between sediments and pore water. The bioavailable fraction of contaminants in sediments is “freely dissolved”, which is present in sediment interstitial water or pore water (Hawthorne et al., 2005; Ter Laak et al., 2006). Sediment–pore water partitioning is an important process that controls the transport, fate, and ecotoxicological risk of the microlevels of organic contaminants in aquatic environments (Yu et al., 2009). Partitioning of organic compounds such as polycyclic aromatic hydrocarbons (PAHs), polychlorinated biphenyls (PCBs), hexachlorobenzene (HCB), and nonylphenol polyethoxylates, between sediments and pore water has been investigated in river, harbor, and bay sediments (Chin and Gschwend, 1992; McGroddy et al., 1996; Maskaoui et al., 2002; Booij et al., 2003; Hawthorne et al., 2005; Yu et al., 2008; Yu et al., 2009). Determining antibiotic concentrations in the pore water phase is necessary to fully understand the fate of chemicals in sediment. Taihu Lake is the third largest freshwater lake in China. It covers an area of 2338 km2 and is a typical shallow lake with an average water depth of approximately 2 m. The lake is surrounded by highly developed cities and towns, which account for more than 14% of gross domestic product of China (Qiao et al., 2006). Numerous wastes from industrial and agricultural activities and municipal sewage from small towns enter the lake, causing severe environmental problems, such as

water eutrophication (Hu et al., 1998; Zuo et al., 2003; Guo, 2007; Duan et al., 2009). Apart from providing drinking water to more than two million people, the lake also sustains one of the most important fisheries for crabs, carp, and eels in China (Guo, 2007). Anthropogenic activities have significantly influenced the lake aquatic environment. Organic contaminants, including PAHs, PCBs, organochlorine pesticides, polychlorinated dibenzodioxins, and polybrominated diphenyl ethers, in Taihu Lake have been studied (Zhang and Jiang, 2005; Liu et al., 2009; Zhang et al., 2011; Wang et al., 2012; Zhang et al., 2012). However, limited information is available on the spatial distribution of antibiotics. The occurrence of antibiotics in Taihu Lake is the general expectation due to the intensive inputs of antibiotics via sewage, livestock and aquaculture. The main objective of this study is to monitor the residues of commonly used human and animal antibiotics in sediment, pore water, and overlying water matrices in Taihu Lake. Specifically, concentrations of sulphonamides (SAs), fluoroquinolones (FQs), macrolides (MLs), tetracyclines (TCs) and trimethoprim (TMP) were investigated (Table 1). Spatial trends were examined to determine the differences in locations. The partitioning behavior of antibiotics between sediment and pore water and between sediment and overlying water was also determined. The results are expected to help better understand the fate, sources and bioavailability of antibiotics in the lake aquatic environment.

2. Materials and methods 2.1. Sample collection and preparation The study area and sampling locations are shown in Supplementary Materials Figure S1. Thirty samples covering the entire lake were collected in Taihu Lake in May 2010, representing areas affected by human- (urban and rural) and animal-raising activities. Four liters of overlying water samples at a depth of 1.0 m was collected using a transparent organic glass water sampler and placed in prerinsed brown glass bottles. Surface sediments (0 cm to 5 cm) were collected using a grab sampler. The water and sediment samples were transported to the laboratory in an ice box. Sediments were stored at − 20 °C. The primary physicochemical properties of water and sediments are shown in Supplementary Materials Table S1. Approximately 200 mL of pore water from the sediment was obtained by centrifugation at 8000 rpm. Overlying water and pore water were treated within 12 h after collection. The analysis of sediments was completed within 7 d.

Table 1 Primary usage of studied compounds. Compounds

Acronym

CAS number

pKaa

logKowb

Primary usagec

Sulphathiazole Sulphachloropyridazine Sulphamethoxazole Sulphisoxazole Sulphadimethoxine Sulphamethazine Norfloxacin Ofloxacin Ciprofloxacin Enrofloxacin Oxytetracycline Tetracycline Chlortetracycline Erythromycin-H2O Roxithromycin Trimethoprim

STZ SCP SMX SIA SDX SMT NOR OFL CIP ENR OTC TC CTC ERM-H2O ROM TMP

72-14-0 80-32-0 723-46-6 127-69-5 122-11-2 57-68-1 70458-96-7 82419-36-1 85721-33-1 93106-60-6 79-57-2 60-54-8 57-62-5 114-07-8 80214-83-1 738-70-5

7.1 – 5.81 4.8 5.98 7.49 6.3 6.05 6.09 6.12 3.3 3.3 3.3 8.9 9.17 7.13

0.05 −1.09 0.89 1.01 1.63

Livestock, aquaculture Livestock Human Human Poultry, livestock Human, livestock Human, poultry, livestock Human, poultry, livestock Human Human, poultry, livestock Human, livestock Human, livestock Livestock Human, poultry, livestock Human Human

a b c

From reference: Qiang and Adams (2004). Values calculated by EPI Suite (USEPA) From references: Kim and Carlson (2007), Managaki et al. (2007), and Luo et al. (2011).

−1.03 −0.39 −1.08 0.4 −1.6 −1.39 −0.62 2.54 2.75 0.91

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Water samples (1500 mL for overlying water and 200 mL for pore water) were filtered through glass microfiber filters (GF/B, Whatman, Sigma Aldrich, St. Louis, MO, USA). The pH value was adjusted to 3 using concentrated sulfuric acid. Na2EDTA (0.8 g) and 50 ng of surrogate standards (CIP-D8 , SAM-13 C6 , ERM-13 C, and TRM- 13C 3 ) were added to the solution. Samples were loaded at a flow rate of 10 mL/min on Waters Oasis HLB cartridges (500 mg, 6 mL), which were preconditioned sequentially with 5 mL of methanol, 5 mL of water and 5 mL of 10 mM/L Na2EDTA (pH 3.0) solution. The cartridges were rinsed with 5 mL of 5% methanol aqueous solution and 5 mL of ultrapure water, and dried under vacuum. Antibiotics were eluted with 10 mL of methanol, and the eluent was concentrated under a gentle stream of nitrogen to near dryness. The extract was brought to 1.0 mL with methanol and ready for analysis. Fifty nanograms of surrogate standards (CIP-D8, SAM-13C6, ERM-13C and TRM-13C3) was added to 2 g of freeze-dried sediment. Then 30 mL of extraction buffer (pH = 5) consisting of 15 mL of methanol, 5 mL of 0.1 M Na2EDTA, and 10 mL of citrate buffer was added. Each sample was vortexed at 300 rpm for 20 min, ultrasonically extracted for 15 min, and centrifuged at 4000 rpm for 5 min. The supernatant was decanted into a brown glass bottle. Extraction was repeated two more times and the supernatants were combined. Rotary evaporation was applied to remove the organic solvent from the supernatant, and the residue was brought to 500 mL with ultrapure water. The strong anion exchange (SAX) cartridge (3 mL, 200 mg, Thermo Fisher Scientific, Waltham, MA, USA) and Waters Oasis HLB cartridge were tandem connected to extract antibiotics from the solution. The SAX cartridge was used to reduce matrix interferences by adsorbing anionic humic particles from the sediment extracts, preventing contamination, blocking and overloading of the HLB cartridge (Jacobsen et al., 2004). The diluted extracted solution was passed through the cartridges at a flow rate of 10 mL/min. After sample loading, the SAX cartridge was discarded and the HLB cartridge was washed with 5 mL of deionized water, vacuum dried for 1.5 h, and eluted with 10 mL of methanol. The procedures were the same as that for water sample treatment. All overlying water, pore water and sediments were analyzed in duplicate, and the reported data were the average of the two analyses. 2.2. Quantification and method validation The target antibiotics were analyzed by high-performance liquid chromatography–tandem mass spectrometry (HPLC–MS/MS). The HPLC separation was conducted using an Agilent 1200 series (Palo Alto, CA, USA) equipped with an Agilent Zorbax Eclipse XDB-C18 column (4.6 × 150 mm, 5 μm). The column was maintained at 30 °C during sample analysis. The mobile phase consisted of eluent A (acetonitrile) and eluent B (0.1% formic acid in ultrapure water).

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The flow rate was kept at 0.3 mL/min, and the injection volume was 10 μL. The separation of antibiotics was achieved with the following gradient program: 0–8 min, 15% A; 8–16 min, 15%–50% A; 16–24 min, 50%–60% A; 24–26 min, 60%–15% A; and 26–28 min, 15% A. The system was reequilibrated for 10 min between runs. Mass spectrometric analyses were performed by an Agilent 6410 triple quadrupole mass spectrometer equipped with an electrospray ionization source that operated in the positive ionization mode. The nebulizer pressure was set to 40 psi and the flow rate of drying gas was set to 3 L/min. The capillary and nozzle voltages were 4000 and 0 V, respectively. The flow rate and temperature of the sheath gas were 8 L/min and 350 °C, respectively. Sample acquisition was performed in the multiple reaction monitoring (MRM) mode, by recording two MRM per compound. The detailed optimization parameters are shown in Table S2. The calibration curves for analyte detection were obtained by performing a linear regression analysis on spiked samples. The antibiotic concentrations in the samples were quantified using the internal standard method. The linearity obtained for all analytes was good in the investigated ranges for the sediment and water matrices, with correlation coefficients greater than 0.98. Recoveries of antibiotics in the water and sediment samples were tested, and the detailed results are shown in Table S3. The recoveries of antibiotics ranged from 82.7% to 114.3% in water and from 63.4% to 123.5% in sediment, respectively. The limit of quantification (LOQ) calculated with a signal/noise ratio of 10 was 0.1 ng/L to 3.6 ng/L for water and 0.3 μg/kg to 3.9 μg/kg for sediment. 3. Results and discussion 3.1. Antibiotic occurrence in Taihu Lake The concentrations of antibiotics in the three environmental compartments in Taihu Lake are summarized in Table 2, and their detection frequencies are shown in Table S4. The antibiotic concentrations in overlying water ranged from 127 ng/L to 1210 ng/L. The detection frequency of 6 SAs at levels over their LOQs in overlying water was from 17% to 97% among 30 measurements. Sulphamethoxazole (SMX) was detected most frequently (97%), with the average concentration of 48.4 ng/L. The highest average concentration was determined for sulphamethazine (SMT) at 252.7 ng/L, with a detection frequency of 87% in overlying water samples. Sulphisoxazole (SIA) and sulphachloropyridazine (SCP) were two SAs less frequently detected in overlying water from Taihu Lake, with detection frequencies of 17% and 23%, respectively. Among the four FQs, three were detected with detection frequencies greater than 63%, whereas enrofloxacin (ENR) was not detectable in all measurements. Ciprofloxacin (CIP)

Table 2 Summary of measured concentration in overlying water, pore water and sediment from Taihu Lake. nd: not detected. Antibiotics

STZ SCP SMX SIA SDX SMT NOR OFL CIP OTC TC CTC ERM-H2O ROM TMP

Overlying water, ng/L

Sediment, μg/kg

Pore water, ng/L

Range

Mean

Range

Mean

Range

Mean

nd–134.5 nd–89.4 nd–114.7 nd–61.4 nd–43.3 nd–654.0 nd–6.5 nd–82.8 nd–43.6 nd–72.8 nd–87.9 nd–142.5 nd–624.8 nd–218.3 nd–40.8

45.9 27.1 48.4 44.4 11.9 252.7 4.3 32.2 8.8 44.2 43.2 67.9 109.1 50.7 12.0

nd–31.0 nd–2.5 nd–15.7 nd–7.1 nd–18.5 nd–30.0 nd–25.6 nd–80.9 nd–7.4 nd–52.1 nd–35.6 nd–21.8 nd–25.0 nd–13.5 nd–7.3

15.4 1.7 5.1 4.8 5.3 12.6 18.6 33.6 5.0 47.8 11.7 18.5 12.6 4.0 2.9

nd–51.7 nd–15.8 nd–49.3 nd–22.6 nd–15.7 nd–99.8 nd–28.4 nd–52.8 nd–25.3 nd–196.7 nd–112.2 nd–48.5 nd–120.3 nd–45.2 nd–39.3

17.8 7.3 16.1 11.0 6.9 39.8 9.9 16.5 9.8 52.8 47.9 19.0 27.7 16.9 9.3

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showed the highest detection frequency of 93%, followed by 80% and 63% for norfloxacin (NOR) and ofloxacin (OFL), respectively. Among the three TCs (oxytetracycline [OTC], tetracycline [TC], and chlortetracycline [CTC]) and two MLs (erythromycin-H 2 O [ERM-H2O] and roxithromycin [ROM]), ERM-H2 O was the most frequently (83%) detected antibiotic in overlying water, with the highest concentration of 624.8 ng/L at site 27 and an average concentration of 109.1 ng/L. The other four antibiotics have detection frequencies greater than 70% for all measurements. The detection frequency of TMP, one of the most frequently prescribed antibiotics for use in humans, was 63% with the average concentration of 12.0 ng/L in water samples. For sediments, all studied antibiotics have detection frequencies greater than 70%, except for SIA and sulphadimethoxine (SDX), with detection frequencies of 33% and 57%, respectively (Table S4). The highest average concentration was determined for OTC at 52.8 μg/kg, followed by TC at 47.9 μg/kg. TCs have a strong adsorption capacity, and they tend to adsorb onto suspended particles and sediments (Tolls, 2001; Yang et al., 2010). In all sediment samples except for Site 12, TCs were detected with average concentrations ranging from 19.0 μg/kg to 52.8 μg/kg in this study. SDX and SCP have the lowest average concentrations of 6.9 and 7.3 μg/kg, respectively, which is possibly due to the lowest koc values for SAs (Tolls, 2001; Thiele-Bruhn, 2003). The highest average concentration of FQs was determined for OFL at 16.5 μg/kg.

In pore water samples, antibiotics in Taihu Lake are also ubiquitous (Table 2). Compared with the concentration in overlying water, the concentrations of NOR, OFL and OTC were higher in pore water, whereas the rest had higher concentrations in overlying water. Sulphathiazole (STZ), SMX, SMT and TC were most frequently detected (67%), with average concentrations of 15.4, 5.1, 12.6 and 11.7 ng/L, respectively. OTC is least detected (10%). However, OTC has the highest average concentration (47.8 ng/L) among all antibiotics. To our knowledge, only one study reported the occurrence of antibiotics in pore water from Baiyangdian Lake in North China, where the mean concentrations of four antibiotics, i.e., OTC, TC, NOR and OFL were 18.86, 24.54, 21.43 and 3.67 ng/L, respectively (Cheng et al., 2014). The mean levels of NOR and TC in Taihu Lake are comparable to those in Baiyangdian Lake, whereas the mean levels of OTC and OFL are higher. 3.2. Spatial distribution analysis Spatial distribution analysis was conducted to determine the origin of antibiotics that was primarily due to human, agricultural, animal husbandry, or aquacultural influences. Generally, antibiotics are categorized as originating from human and animal-derived sources. For instance, SMX, TMP, ROM, and CIP are assumed to be human-derived compounds, and SMT, CTC, SDX, and SCP are assumed to be animalderived compounds. By contrast, antibiotics such as TC, OTC, OFL, and

Fig. 1. Distribution of the total antibiotics in overlying water, pore water and sediment from Taihu Lake.

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ERM-H2O are assumed to be human- and animal-derived compounds (Kim and Carlson, 2007; Managaki et al., 2007; Luo et al., 2011). Primary usage of the measured antibiotics is summarized in Table 1. The distribution of the total antibiotics in Taihu Lake is shown in Fig. 1 and indicates that high levels of antibiotics occurred in the northern and southern parts of the lake. Human-derived antibiotics occurred mainly in the northern part of Taihu Lake. In overlying water, the highest concentrations of SMX, TMP, and ROM were observed at Zhushan Bay (S1–S5) and Meiliang Bay (S15–S19), and CIP was evenly distributed around the lake. In sediments, in addition to Zhushan Bay and Meiliang Bay, high levels of these compounds were also detected in the eastern part of the lake (S25–S27). Considering that two major developed cities, Changzhou City and Wuxi City, are near the northern part of Taihu Lake, we are not surprised to observe high levels of human-derived antibiotics in this region (Wang et al., 2011). SMX, together with many other antibiotics, such as ROM, CIP, and TMP, has been extensively detected in many wastewater treatment plants (WWTPs) around the world (McArdell et al., 2003; Chang et al., 2008; Batt et al., 2007; Behera et al., 2011; Li et al., 2013; Xu et al., 2014). The effluents from WWTPs in Changzhou and Wuxi cities may have contributed to the high levels of human-derived antibiotics in the two bays of Taihu Lake. SMT is a typical animal-derived antibiotic that has been used as an indicator to detect the contribution of livestock wastes and extensive inputs of veterinary medicine (Managaki et al., 2007). SCP is also used as a potential chemical marker for livestock source (Luo et al., 2011). In the Taihu Lake water and sediment samples, the animal-derived SMT, SCP, CTC, and SDX occurred at high concentrations in the northern and eastern parts of the lake. Around Taihu Lake, more than 2000 concentrated animal feeding operations (CAFOs) exist, many of which are located in the northern part and significantly contribute to the occurrence of antibiotics in the lake. The eastern part of Taihu Lake has an area of approximately 131 km2, 41% of which (54 km2) is used for aquaculture farms for crabs and eels (Lai and Huang, 2008). Direct input of veterinary medicines in aquaculture increased the animal-derived antibiotics in water and sediment (S25–S30). Human-derived and animal-derived antibiotics are ubiquitously detected in the entire lake, indicating the extensive use of antibiotics in the basin. By contrast, certain antibiotics, such as TC and OTC, were not detected in sediment in the central part of the lake. TCs are less soluble in natural water and tend to adhere to suspended particles, leading to active deposition and sedimentation near the sources (Managaki et al., 2007). Sorption is an important attenuation mechanism for TCs from water. 3.3. Composition of antibiotics in Taihu Lake The composition of antibiotics detected in Taihu Lake was compared with the reported data in other regions of the world (Table 3). The results showed that, in Taihu Lake, the numbers and concentrations of the detected antibiotics were relatively greater those in other regions of the world. For instance, in Cache la Poudre Watershed in the USA, 15 antibiotics classified as TCs, MLs, and SAs were derived from human and animal sources (Kim and Carlson, 2007), which agreed with the national survey of 139 rivers in the USA, that a total of 14

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Table 4 Pseudo-partitioning coefficient of selected antibiotics. Compounds ksw, L/kg

STZ SCP SMX SIA SDX SMT NOR OFL CIP OTC TC CTC ERM-H2O ROM TMP a

Values in referencesa, L/kg

ksp, L/kg

Range

Mean Range

Mean

42–2978 105–1800 40–1690 167–254 90–1570 22–1094 652–6685 91–2592 145–5139 231–5409 185–7365 80–2430 4–8071 93–4438 183–4594

596 670 372 213 925 290 2239 843 1388 1462 1794 401 1049 698 1814

1688 5065 4816 3668 2997 5203 647 864 2310 1311 7537 999 3288 6352 6522

329–4792 4000–5667 1306–11615 950–14643 428–8291 1914–11605 130–1495 149–2993 598–4709 720–2465 799–22933 312–2765 1182–16040 2731–13824 1964–15720

3–378 1–97 20 402 1–3 4493–47093 310–12465 78–3020 290–31170 305 211

: From references: Tolls (2001), Kim and Carlson (2007), and Cheng et al. (2014).

antibiotics from human and animal origins were detected (Kolpin et al., 2002). In Tamagawa River in Japan, seven human-derived antibiotics were detected at significant concentrations, whereas animalderived antibiotics, such as SMT, were not detected because 60% of the river water was from sewage effluent and no CAFOs existed in the catchment (Managaki et al., 2007). In several European rivers, such as River Taff and River Ely in the UK (Kasprzyk-Hordern et al., 2009), and Seine River in France (Tamtam et al., 2008), human-derived antibiotics were the primary antibiotic pollutants. By contrast, in Mekong Delta in Vietnam, only four antibiotics were detected; these antibiotics were old and cheap, and most of them originated from nonhuman sources (Managaki et al., 2007). In this study, 15 target drugs, including sulfonamides, quinolones, macrolides, and tetracyclines were detected. Moreover, human- and animal-derived drugs significantly contributed to the total contamination of antibiotics in the lake, indicating the high complexity of contamination sources in Taihu Lake Basin. In developing countries, where agriculture and aquaculture are the dominant economic activities, potential inputs of antibiotics are from livestock and aquaculture waste as well as from sewage. This contrasts with industrialized countries, where antibiotics used for human medicine are the major sources of antibiotics in the aquatic environment (Managaki et al., 2007). China is a large country with high production and consumption of antibiotics (Liu and Wong, 2013). The inputs from adjacent sewage and agricultural activities, together with the direct usage in aquaculture, contributed to the severe antibiotic contamination in different environmental compartments in Taihu Lake. 3.4. Pseudo-partitioning coefficient calculation P-PC values were calculated to better understand the relationship of antibiotics between the solid and aqueous phases. P-PC was obtained using the ratio of the measured concentration in sediment to the concentration in aqueous phase (Kim and Carlson, 2007). The values of ksw (sediment to overlying water) and ksp (sediment to pore water) are summarized in Table 4. It shows that the P-PC values in Taihu Lake

Table 3 The number, classes and main origin of antibiotics in Taihu Lake and other water bodies around the world. Location

Number of antibiotics

Classes of antibiotics

Main origin

References

Cache la Poudre watershed, US 139 rivers, US Seine River, France River Taff and River Ely, UK Tamagawa River, Japan Mekong Delta, Vietnam Taihu Lake, China

15 14 17 5 7 4 15

Sulfonamides, macrolides, tetracyclines Sulfonamides, macrolides, tetracyclines, fluoroquinolones, TMP Quinolones, sulphonamides, nitro-imidazole Sulphonamides, macrolides, amide alcohols, nitro-imidazole, TMP Sulphonamides, macrolides, TMP Sulfonamides, macrolides, TMP Sulfonamides, macrolides, tetracyclines, fluoroquinolones, TMP

Human, animal Human, animal Human Human Human Animal Human; animal

Kim and Carlson (2007) Kolpin et al. (2002) Tamtam et al. (2008) Kasprzyk-Hordern et al. (2009) Managaki et al. (2007) Managaki et al. (2007) This study

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range from 22 L/kg to 14643 L/kg for SAs, from 91 L/kg to 6685 L/kg for FQs, from 80 L/kg to 22933 L/kg for TCs, from 4 L/kg to 16040 L/kg for MLs, and from 183 L/kg to 15720 L/kg for TMP. The results also indicate that the P-PC values of TCs agree with the reported data, but those of SAs are higher, and those of FQs are lower than the published values, which was associated with the different physicochemical properties of environmental matrices in different study areas. Table 4 also shows that ksp is generally greater than ksw, which may be attributed to the low antibiotic concentrations in pore water than in overlying water, because the new pollution input may directly increase antibiotic concentrations in overlying water. Cheng et al. (2014) suggested that ksp was a more desirable value for indicating the sorption characteristics in the aquatic environment, compared to ksw, because sediments were in closer contact with the pore water than overlying water and surface water. Moreover, ksp showed smaller fluctuations. In this study, the variation of ksp values was comparable to that of k sw values, suggesting that the specific sediments with different physicochemical properties played important roles in the partitioning of different antibiotics between sediment and aqueous compartments. One frequent observation is that the octanol–water partition coefficient is often not a good predictor of the sorption potential of pharmaceuticals and personal care products. Thus, koc may not be appropriate either. The P-PC values in this study did not exhibit any correlation with the corresponding sediment organic carbon content (statistical data not shown), indicating a complex partition mechanism of antibiotics with the lake sediments. The charged or amphoteric nature of these molecules means that they can bind to mineral surfaces and may do so more strongly than to organic matter (Xu et al., 2009). 4. Conclusions This study reported the occurrence of 15 individual antibiotics in the third largest freshwater lake in China. The results showed that antibiotic pollutants in Taihu Lake were ubiquitous in overlying water, sediment, and pore water compartments. In different locations, the origin of antibiotics varied depending on human, agricultural, and aquacultural activities. The composition of antibiotics suggested that human- and nonhuman-derived drugs significantly contributed to the total contamination of antibiotics in the lake, indicating the high complexity of contamination sources. The in situ sediment–pore water and sediment– overlying water partitioning coefficients were also calculated, which may be useful in predicting the fate of antibiotics in the aqueous environment. This study demonstrates the ubiquitous occurrence of antibiotics in Taihu Lake, which may pose potential hazards to the aquatic ecosystem. Further investigation is needed to address the antibioticassociated risks, such as the spread of antibiotics resistant bacteria and genes in the lake environment. Acknowledgments This study was financially supported by China's National Basic Research Program (2008CB418201) and the National Natural Science Foundation of China (51178438). References Batt AL, Kim S, Aga DS. Comparison of the occurrence of antibiotics in four full-scale wastewater treatment plants with varying designs and operations. Chemosphere 2007;68:428–35. Behera SK, Kim HW, Oh JE, Park HS. Occurrence and removal of antibiotics, hormones and several other pharmaceuticals in wastewater treatment plants of the largest industrial city of Korea. Sci Total Environ 2011;409:4351–60. Booij K, Hoedemaker JR, Bakker JF. Dissolved PCBs, PAHs, and HCB in pore waters and overlying waters of contaminated harbor sediments. Environ Sci Technol 2003;37: 4213–20. Chang H, Hu J, Wang L, Shao B. Occurrence of sulfonamide antibiotics in sewage treatment plants. Chin Sci Bull 2008;53:514–20.

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