Abstract

Freshwater contaminants tend to precipitate into intertidal surface sediments, particularly in the estuary and intertidal zones during freshwater–seawater mixing. Quinolone-type antibiotics are such contaminants, and their concentrations in the intertidal sediments are important indicators for the whole spectrum of antibiotics used in the estuary and adjacent areas. The impacts of sediment types and environmental factors on the distribution of 16 quinolones were probed based on nine Bohai and 42 Yellow Sea intertidal sediment samples. The samples were collected from locations along the coastal areas in China. Quinolones were detected in all samples, while moxifloxacin, ciprofloxacin, and ofloxacin were detected at a frequency >50%. Sediment types, pH, organic carbon content, K, Na and Fe concentrations had little correlation with quinolone distributions in intertidal sediments. However, combined concentrations of Ca + Mg (46.7 g/kg in Bohai and 13.7 g/kg in Yellow Sea samples) appeared to correlate with oxolinic acid detecting frequencies (88.9% and 4.8%, respectively) and concentrations (2.0–10.1 μg/g and up to 3.09 μg/g, respectively). Different detection frequencies of the quinolones could be attributed to the formation of cation bridges between oxolinic acid and Ca + Mg, which results in dominant sorption of oxolinic acid at different locations and sediment matrices.

INTRODUCTION

The widespread use of antibiotics has resulted in increased frequencies of their release into the environment. Antibiotic production in China reached 248,000 metric tons in 2013, and total antibiotic usage reached near 162,000 metric tons (Ying et al. 2017). Antibiotics have been detected in different waste streams and environmental matrices that include municipal wastewater (Wu et al. 2016; Subedi et al. 2017), landfills (Song et al. 2016), rivers (Johnson et al. 2015; Zhang et al. 2015; Zou et al. 2018), lakes (Tang et al. 2015), ocean (Lunestad et al. 1995), soil (Chen et al. 2014), sediments (Shi et al. 2014), and groundwater (Paiga & Delerue-Matos 2016; Chen et al. 2017; Yao et al. 2017). And antibiotics have been detected in water supplies, as evidenced by their reported presence in drinking water (Simazaki et al. 2015). Specifically in China, antibiotics have frequently been detected at high concentrations in the Yangtze River (Yan et al. 2013), Pearl River (Xu et al. 2007), Haihe River (Luo et al. 2011), Huangpu River (Jiang et al. 2011), coastal seawater (Nie et al. 2009) and sediments (Lei et al. 2015; Dong et al. 2016), which have caused wide public concern.

The distribution of antibiotics between surface water (i.e., river, lake, ocean) sediments and overlying water is affected by sediment types and environmental factors, including temperature, pH, organic carbon (OC) content, and cation concentrations (Vasudevan et al. 2009; Feng et al. 2016). Li & Zhang (2016) reported substantially different oxytetracycline (OTC) adsorption capacities for sediments from Bohai Bay and Laizhou Bay (5.03 and 0.602 mg/g, respectively; both locations are in China), where silt/clay ratios were 0.995 and 0.528 for sediments from Bohai Bay and Laizhou Bay, respectively. Studies conducted by Luo et al. (2011) and Shi et al. (2014) showed that season temperatures affected the aqueous concentrations of antibiotics in the Haihe River and Yangtze Estuary (China), with higher concentrations during the winter than in the summer. Notably, the difference in concentration of ofloxacin (OFL) in November over May was 397 ng/L. Wang et al. (2017) observed that the OFL adsorption capacity decreased from 25.6 to 8.0 mg/g with increasing pH from 6.1 to 7.5 in marine sediments. However, Zhao et al. (2011) observed no difference in tetracycline (TC) adsorption on kaolin at pH from 6 to 8. Researchers have also reported negative OC content on the adsorption of antibiotics on sediment. Cao et al. (2015) investigated an 80% decrease of the Freundlich constant (Kf) after removing OC from sediments by hydrogen peroxide oxidation. Xu & Li (2010) reported that oxidized sediments resulted in a substantial decrease in TC adsorption. Furthermore, different cations also affect the adsorption of antibiotic, including heavy metals (Yang et al. 2017), calcium ions (Qin et al. 2014), and iron manganese composite oxide (Yan et al. 2017). Cation bridging with antibiotics is known to occur with clay particles, where Figueroa et al. (2004) reported that calcium promotes the adsorption of OTC on montmorillonite through an ion bridge at pH > 7.

Comparing the detection frequencies of norfloxacin (NOR), ciprofloxacin (CIP), and enrofloxacin (ENR) in seawater and sediment in the coastal Pearl River Delta, three antibiotics were only detected in sediment, with the highest concentrations being 13.28, 9.32, and 7.13 ng/g for NOR, CIP, and ENR, respectively (Nie et al. 2009). Liu et al. (2016) also reported that the concentrations of antibiotics in 35 estuarine sediments were higher than the concentrations of antibiotics in 104 marine sediments, where the concentration in the estuarine sediment could reach 4,695 μg/kg. Furthermore, antibiotics have been widely detected on the shore of the Bohai Sea and Yellow Sea (Zou et al. 2011; Li et al. 2012; Zhang et al. 2013; Liu et al. 2016). Intertidal surface sediment can absorb many antibiotics and cause the direct exposure of antibiotics to marine life (Maskaoui & Zhou 2010). Therefore, it is important to investigate the distribution of antibiotics in the intertidal surface sediment and its impacts. In this study, nine and 42 intertidal surface sediment samples from the Bohai Sea and Yellow Sea (China) respectively were collected. Quinolone concentrations, sediment types and environmental indicators in intertidal surface sediments were analyzed to investigate the distribution of quinolones and their potential environmental and health impacts.

MATERIALS AND METHODS

Study sites and sampling

As shown in Figure 1, nine of 51 intertidal surface sediment samples were collected from the Bohai Sea (Survey Region 1), China, and the others were sampled in the Yellow Sea (Survey Region 2). All samples were collected by China University of Geosciences (Beijing) (CUGB) personnel following standard sampling procedures (China Geological Survey 2008). The maximum sampling depth was 0.3 m or less from the surface of the sediment layer. All samples were sealed in seal bags and stored at 4°C in the dark and shipped via overnight express to CUGB laboratory.

Figure 1

Map of the survey regions and sampling sites.

Figure 1

Map of the survey regions and sampling sites.

Sample preparation and extraction

After being dried in the shade with shells and gravel removed, sediment samples were ground and screened through a 200-mesh sieve. Sediment samples were then weighed to 2 g and placed into 15 mL centrifuge tubes with 0.4 g Na2EDTA (China National Pharmaceutical Group Corporation, Beijing, PR China), 40 μL surrogate standards, and 10 mL acetonitrile phosphate buffer solution. Ten millilitres of acetonitrile phosphate buffer was added to each sample. The acetonitrile phosphate buffer was made by dissolving 0.0675 mL phosphoric acid and 15.6 g NaH2PO4·H2O in 500 mL water; then mixed with 500 mL acetonitrile, with a final pH at 3.0. The samples were mixed by shaking for 20 min, and then centrifuged at 3,500 rpm for 10 min. The supernatant was collected in a glass vial; and the above steps were repeated twice. The final supernatant was evaporated from about 30 mL to 15 mL by using an evapotranspirater before adding 15 mL of distilled water. Finally, an auto solid-phase extraction (SPE) (Auto SPE-06C, Reeko Instrument, TX, USA) with a tandem SAX-Oasis HLB SPE column (6 mL, 500 mg, Waters, MA, USA) was used to screen antibiotics at a speed of 6 mL/min. The surrogate standard mixtures contained ofloxacin-D3 and sulfadimethoxine-D6 (4 mg/L in methanol solution, Witega, Berlin, Germany).

The SPE column was leached by 10 mL ultrapure water and dried for 30 min with N2, then eluted with a 6 mL ammonia/methanol (5/95, V/V) solution. The eluent was purged to <1 mL with N2 and methanol/water (1/1, V/V) was used to replenish the sample volume to 1 mL of analysis; internal standard mixtures of 10 μL were also added. The internal standard mixtures (4 mg/L in methanol solution) were composed of difloxacin-D3 (Witega, Berlin, Germany), sulfapyridine-13C6 (Witega, Berlin, Germany), sulfachloropryidazine-13C6 (Witega, Berlin, Germany), erythromycin-13C-D3 (TLC Pharmaceutical Standards, Ontario, Canada), and DMCT (Dr Ehrenstorfer, Augsburg, Germany). Methanol was purchased from Merck (Darmstadt, Germany) and phosphoric acid and NaH2PO4·H2O were purchased from Beijing Chemical Plan (Beijing, PR China).

Analyses for Ca, Mg, Fe, K, and Na were performed according to Standard Methods (APHA 2005). The PB-10 Precision pH meter measured pH (Sartorius, Göttingen. BRD) and TOC was measured by using a total organic carbon analyzer (TOC-V CPN, Shimadzu, Japan).

Antibiotics analysis

The antibiotic standards were purchased from Dr Ehrenstorfer (Augsburg, Germany) and Sigma-Aldrich (St Louis, MO, USA), as shown in Table 1. All solid standard quinolones were dissolved in formic acid before methanol was added to keep the volume constant at a concentration of 0.1 g/L.

Table 1

Summary of analytical results of target quinolones in 51 intertidal surface sediments

No.Cont.Abb.CAS no.MDLs (μg/g)Quinolone concentrations (μg/g)
Detection frequency (%)
No. > LOQMedianMaximum
Ofloxacin OFL 82419-36-1 0.1 51 7.6 16.0 100 
Moxifloxacin MOX 151096-09-2 0.1 43 1.8 3.5 84.3 
Ciprofloxacin CIP 85721-33-1 0.1 28 5.3 68.9 54.9 
Oxolinic acid OXA 14698-29-4 0.1 10 4.7 10.1 19.6 
Pipemidic acid PPA 51940-44-4 0.05 2.9 10.0 15.7 
Enoxacin ENO 74011-58-8 0.1 2.3 2.6 13.7 
Flumequine FLU 42835-25-6 0.05 4.9 18.1 7.8 
Norfloxacin NOR 70458-96-7 0.1 7.0 7.0 
Nalidixic acid NDA 389-08-2 0.1 1.4 1.4 
10 Lomefloxacin LQM 98079-52-8 0.1 ND ND 
11 Fleroxacin FLE 79660-72-3 0.25 ND ND 
12 Danofloxacin DAN 112398-08-0 0.1 ND ND 
13 Cinoxacin CIN 28657-80-9 0.1 ND ND 
14 Enrofloxacin ENR 93106-60-6 0.1 ND ND 
15 Sparfloxacin SPA 111542-93-9 0.05 ND ND 
16 Difloxacin DIF 91296-86-5 0.05 ND ND 
No.Cont.Abb.CAS no.MDLs (μg/g)Quinolone concentrations (μg/g)
Detection frequency (%)
No. > LOQMedianMaximum
Ofloxacin OFL 82419-36-1 0.1 51 7.6 16.0 100 
Moxifloxacin MOX 151096-09-2 0.1 43 1.8 3.5 84.3 
Ciprofloxacin CIP 85721-33-1 0.1 28 5.3 68.9 54.9 
Oxolinic acid OXA 14698-29-4 0.1 10 4.7 10.1 19.6 
Pipemidic acid PPA 51940-44-4 0.05 2.9 10.0 15.7 
Enoxacin ENO 74011-58-8 0.1 2.3 2.6 13.7 
Flumequine FLU 42835-25-6 0.05 4.9 18.1 7.8 
Norfloxacin NOR 70458-96-7 0.1 7.0 7.0 
Nalidixic acid NDA 389-08-2 0.1 1.4 1.4 
10 Lomefloxacin LQM 98079-52-8 0.1 ND ND 
11 Fleroxacin FLE 79660-72-3 0.25 ND ND 
12 Danofloxacin DAN 112398-08-0 0.1 ND ND 
13 Cinoxacin CIN 28657-80-9 0.1 ND ND 
14 Enrofloxacin ENR 93106-60-6 0.1 ND ND 
15 Sparfloxacin SPA 111542-93-9 0.05 ND ND 
16 Difloxacin DIF 91296-86-5 0.05 ND ND 

Note: ND means not detected.

Analysis of antibiotics in sediments was performed using a Waters ACQUITY UPLC H-Class system coupled with a Waters Xevo-TQ-S Triple Quadrupole MS/MS spectrometer equipped with electrospray ionization (ESI) source (Waters, Milford, MA, USA). A Waters ACQUITY UPLC BEH C18 (2.1 × 50 mm) at 40 °C was used. The mobile phase contained 0.1% aqueous formic acid (A) and methanol/acetonitrile (B, 1/1, V/V, with 0.1% formic acid) at a 0.2 mL/min flow rate under the following gradient program: 0 min, 10% B; 0–7.0 min, 10–60% B; 7.0–7.5 min, 60–100% B; 7.5–10.0 min, 10% B. Formic acid was purchased from Sigma-Aldrich (St Louis, MO, USA), and acetonitrile was purchased from Merck (Darmstadt, Germany). The MS/MS operated in positive ion mode with the source temperature and desolation temperature set at 120 °C and 500 °C, respectively. The cone gas flow and nebulization gas flow were set at 10 L/h and 600 L/h, respectively. Sample injection volume was 1 μL.

Quality assurance and quality control

Quality assurance (QA) and quality control (QC) measures for field sampling and laboratory analysis were implemented. QA/QC controls for laboratory analysis followed the US EPA methods 8270D and 8000B, in which the recovery of surrogates was kept in the range of 80–94%. For every 20 samples, one laboratory reagent blank, one field reagent blank, one laboratory duplicate, one laboratory spiked blank, and one laboratory spiked sample matrix were included. Another area duplicate was included for every 20 samples that were collected from various field locations. If there were fewer than 20 samples from a zone, one field duplicate was also included. The recovery range of all laboratory spiked blanks and the laboratory spiked sample matrices was 28–146%. The relative deviations (RDs) of the laboratory duplicates were 5–50%. The concentrations of target compounds in all laboratory and field reagent blanks were less than their respective minimum detection levels (MDLs). In this survey, the blanks and recoveries of surrogates and spiked samples with target compounds were in the satisfactory range.

RESULTS AND DISCUSSION

Occurrence of selected quinolones in the intertidal surface sediment of Bohai and Yellow Seas

In nine Bohai intertidal surface sediments, at least one quinolone was detected, with the maximum number of quinolones detected in each sediment being five (Figure 2). As shown in Figure 3, six out of 16 quinolones were detected (MOX, OXA, CIP, OFL, FLU, and PPA) and a >50% detection frequency of MOX, OXA, CIP, and OFL was observed with detection concentrations at 1.5–3.5, 2.6–10.1, 1.6–4.2, and 3.1–11.5 μg/g, respectively.

Figure 2

The numbers of detected quinolones in the intertidal surface sediments of Bohai and Yellow Seas.

Figure 2

The numbers of detected quinolones in the intertidal surface sediments of Bohai and Yellow Seas.

Figure 3

Detection frequency and the median concentration of quinolones in the intertidal surface sediments of Bohai and Yellow Seas.

Figure 3

Detection frequency and the median concentration of quinolones in the intertidal surface sediments of Bohai and Yellow Seas.

In the Yellow Sea, 100% of quinolones were detected in 42 intertidal surface sediments, with up to six quinolones detected in each sediment sample (Figure 2). As shown in Figure 3, a total of nine out of 16 were detected (MOX, OXA, CIP, OFL, FLU, PPA, NDA, NOR, and ENO) and a >50% detection frequency of MOX, CIP, and OFL was observed with detection concentrations at 1.4–2.3, 1.1–68.9, and 2.4–16 μg/g, respectively. Compared with the quinolones detected in the intertidal surface sediments in the Bohai Sea, three multi-quinolones (including NDA, NOR, and ENO) were detected only in the Yellow Sea.

Effect of different sediment types on the distribution of quinolones in the Bohai and Yellow Seas intertidal surface sediments

The component of Bohai intertidal surface sediment was 67% sand and 33% silt-clay and 10% sand, 26% silt, and 64% silt-clay in Yellow Sea samples (Figure 4(a)). As shown in Figure 2, there was little significant difference in detection frequencies in the intertidal surface sediment samples from the Bohai and Yellow Seas (both detection frequencies are 100%). The maximum number of quinolones detected in each sediment were five and six respectively, and the detection concentration (mean detection concentrations were 1.9–9.3 μg/g and 0.5–7.5 μg/g, respectively) was observed for quinolones in the Bohai and Yellow Seas intertidal surface sediments. Considering the one-way analysis of variance (ANOVA) influencing sediment types regarding the distribution of the nine detected quinolones (Table 2, F < Fcrit), sediment type appeared to have no influence on quinolone distribution in intertidal surface sediments in the Bohai and Yellow Seas. Some researchers have reported that quinolone adsorption may be significantly affected by sediment (Xu & Li 2010; Githinji et al. 2011). Moreover, the concentration of OFL, which was detected in all sediments (Figures 2 and 4(a)) and ranged from 6 to 9 μg/g in three sediment types (Figure 4(b)), further supports the findings above.

Table 2

The one-way ANOVA of the influence of sediment types on the distribution of the nine detected quinolones

QuinolonesFFcrit
MOX 1.92 3.23 
OXA 0.07 4.74 
CIP 0.17 3.39 
OFL 0.26 3.19 
ENO 0.20 6.94 
FLU 0.06 199.5 
PPA 0.41 5.79 
QuinolonesFFcrit
MOX 1.92 3.23 
OXA 0.07 4.74 
CIP 0.17 3.39 
OFL 0.26 3.19 
ENO 0.20 6.94 
FLU 0.06 199.5 
PPA 0.41 5.79 

Note: NDA and NOR were only detected at one sample site and the value of Fcrit is not available.

Figure 4

(a) Distribution of detected quinolones in three typical sediments; (b) the boxplot of detected OFL in three typical sediments.

Figure 4

(a) Distribution of detected quinolones in three typical sediments; (b) the boxplot of detected OFL in three typical sediments.

Effects of environmental factors on the distribution of quinolones in the Bohai and Yellow Seas intertidal surface sediments

Neutral pH values at 7.0–7.5 and 6.5–7.3 were observed in intertidal surface sediments in the Bohai and Yellow Seas, respectively. Past studies have indicated that pH did not have a significant impact on the adsorption of TC and quinolones such as NDA, CIP, and NOR, nor on kaolin and anion-exchange polymers when pH is 6 to 8 (Robberson et al. 2006; Peng et al. 2011; Zhao et al. 2011). The electrostatic repulsion weakens the hydrophobic interaction between NDA and negatively charged mineral surfaces as the solution pH at 6 was above pKa, and thus reduced NDA adsorption and the uptake of NDA (Wu et al. 2013). Therefore, pH did not have a significant influence on quinolone distribution in the intertidal surface sediment of the Bohai and Yellow Seas. Similar results could also be summarized for OC content basis since it had a similar value that was detected in intertidal surface sediments of the Bohai and Yellow Seas (mean detection concentrations were 0.1 mg/kg and 0.43 mg/kg, respectively). The quinolones are not expected to leach, even in worst-case scenarios (soils rich in sand and poor in organic carbon) in 13 Brazilian soils (Leal et al. 2013) and Kim et al. (2012) found that OC content could affect the maximum adsorption quantity of OTC of sediment when increased from 0.82% to 1.83%.

As shown in Figure 5, the average concentrations of K, Na, and Fe in the intertidal surface sediment of the Bohai Sea were 22 g/kg, 20.6 g/kg, and 21 g/kg, and in the Yellow Sea were 24.8 g/kg, 22.7 g/kg, and 27.5 g/kg, respectively. No significant difference was observed; however, different concentrations of Ca + Mg in the Bohai Sea (46.7 g/kg) and Yellow Sea (13.7 g/kg) intertidal surface sediment were observed, which was consistent with the distribution of OXA in these two regions (the detection frequency was 88.9% and 4.8%, respectively, and the detection concentration was 2.6–10.1 μg/g and up to 3.09 μg/g, respectively; Figure 6). As shown in Figure 7, a regression equation was derived between Ca + Mg concentration and OXA to support the positive correlation; however, the R2 of the regression equation was not high, possibly due to the range of the concentrations for Ca + Mg from the same survey region being too small and the OXA detection concentration being too low. The formation of a cation bridge between OXA and Ca + Mg may be the key factor that increased the absorption of OXA in the sediment. Figueroa et al. (2004) observed that Ca + Mg could facilitate the absorption of quinolones in sediments by cation bridge when pH > 7.

Figure 5

Concentration of all inorganic ions in each sample.

Figure 5

Concentration of all inorganic ions in each sample.

Figure 6

Distribution of quinolones and cations in each sample and the relevant concentration map of Fe, Ca + Mg, and OXA.

Figure 6

Distribution of quinolones and cations in each sample and the relevant concentration map of Fe, Ca + Mg, and OXA.

Figure 7

The correlation between concentrations of Ca + Mg and OXA.

Figure 7

The correlation between concentrations of Ca + Mg and OXA.

CONCLUSION

Fifty-one intertidal surface sediment samples were collected in the Bohai and Yellow Seas (China). Quinolones, sediment types, and environmental indicators that included pH, OC content, and cations were monitored to investigate the quinolone antibiotics distribution in intertidal surface sediment and the potential impacts. The results indicated that the detection frequency of 16 quinolones in 51 intertidal surface sediments samples was 100%. Six quinolones were detected in nine Bohai intertidal surface sediment samples, and nine out of 42 Yellow Sea samples. Three quinolones, including MOX, CIP, and OFL were detected in all samples with a detection frequency of >50% with detection concentrations of 1.4–3.5, 1.1–68.9, and 2.4–16 μg/g, respectively. The components of the Bohai intertidal surface sediments were 67% sand and 33% silt-clay, and 10% sand, 26% silt, and 64% silt-clay in the Yellow Sea samples; however, there was no significant influence of sediment types on the distribution of quinolones that was observed through the use of one-way ANOVA due to FFcrit. The pH, OC content, K, Na, and Fe concentrations did not correlate with the distribution of quinolones, indicating that those factors had no significant influence on it. However, different concentrations of Ca + Mg in the Bohai (46.7 g/kg) and Yellow Sea (13.7 g/kg) intertidal surface sediments were consistent with the distribution of OXA, which were detected in 88.9% and 4.8% of the Bohai and Yellow Sea samples, respectively, and OXA concentration ranges were determined to be 2.0–10.1 μg/g and up to 3.09 μg/g, respectively. This indicates that some cations may have a substantial effect on the distribution of quinolones. As a result, the formation of a cation bridge between OXA and Ca + Mg may be the key factor that increases the sorption of OXA to the sediment.

ACKNOWLEDGEMENTS

The authors would like to acknowledge Dr Song Jin (University of Wyoming), Mr Paul Fallgren (Advanced Environmental Technologies LLC, Fort Collins, Colorado) and Ms Jadee Jin (Colorado State University) for data reviewing and editing the English writing of this manuscript. This research was financially supported by the National Natural Science Foundation of China (No. 41772245), the National Key Research and Development Program of China (No. 2017YFC0406104), and the Elite Scholar Program (Program E) of Tianjin University.

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