Spatial distribution and seasonal variation of phthalate esters in the Jiulong River estuary, Southeast China

Marine Pollution Bulletin xxx (xxxx) xxx–xxx

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Spatial distribution and seasonal variation of phthalate esters in the Jiulong River estuary, Southeast China Rongli Lia,b, Jing Lianga,c, Hualing Duana, Zhenbin Gonga,b,c,⁎ a b c

State key Laboratory of Marine Environment Science, Xiamen University, Xiamen 361102, China Center for Marine Environmental Chemistry and Toxicology, College of the Environment & Ecology, Xiamen University, Xiamen 361102, China Fujian Collaborative Innovation Center for Exploitation and Utilization of Marine Biological Resources, Xiamen University, Xiamen 361102, China

A R T I C L E I N F O

A B S T R A C T

Keywords: Phthalate esters (PAEs) Spatial distribution Seasonal variation Jiulong River estuary

The spatial distribution and seasonal variation of 16 phthalate esters (PAEs) in water, suspended particulate matter (SPM) and sediment were investigated in the Jiulong River estuary, Fujian, Southeast China. Of the 16 PAE congeners analyzed, only six PAEs, including dimethyl phthalate (DMP), diethyl phthalate (DEP), diisobutyl phthalate (DIBP), di-n-butyl phthalate (DBP), di(2-ethylhexyl) phthalate (DEHP) and diisononyl phthalate (DINP), were identified and quantified. The total concentrations of the six PAEs (∑6PAEs) detected for all seasons ranged from 3.01 to 26.4 μg/L in water, 1.56 to 48.7 mg/kg in SPM, and 0.037 to 0.443 μg/kg in sediment. DEHP, DIBP and DBP were the most abundant PAE congeners in all of the water, SPM and sediment phases. The spatial distributions of PAEs in the estuary were controlled not only by the riverine runoff, seasons, hydrodynamic condition and human activities but also the physicochemical properties of PAEs.

1. Introduction Phthalate esters (PAEs) are widely used in plastic products, pesticides, cosmetics and personal care products (Gomez-Hens and AguilarCaballos, 2003; Shea, 2003) and may be easily re-leached into the environment by aging and decomposition procedures because of their physical bonding to polymer chains. Because of their widespread usage and physicochemical properties, PAEs are ubiquitous in the environment and have been detected in various matrices, such as air (Wang et al., 2008b), surface water (Zeng et al., 2009; Li et al., 2015; Selvaraj et al., 2015), sediment (Sha et al., 2007; Zeng et al., 2009), and soil (Pei et al., 2013; Niu et al., 2014), as well as the tissues and fluids of wildlife and humans (Kim et al., 2011; Liu et al., 2012; Cheng et al., 2013). Studies on toxicology and environmental toxicology have shown that some PAE congeners, such as di-n-butyl phthalate (DBP), butyl benzyl phthalate (BBP), di(2-ethylhexyl) phthalate (DEHP) and their metabolites, are endocrine disrupting compounds (Kavlock, et al., 2002a, 2002b, 2002c; Gomez-Hens and Aguilar-Caballos, 2003). Six PAEs, i.e., dimethyl phthalate (DMP), diethyl phthalate(DEP), DBP, BBP, DEHP and di-n-octyl phthalate (DnOP), have been listed as priority pollutants by the United States Environmental Protection Agency (USEPA, 2014). The European Union (EU) has recommended that the use of several PAEs in children's toys should be lower than 0.1% (EU/2005/84/EC, 2005), and the World Health Organization (WHO) has recommended

⁎

the concentration of DEHP in drinking water be below 8 μg/L (WHO, 2004). Recently, PAE contamination has been an increasingly hot issue. Numerous studies have been performed on the occurrence, distribution (Bartolomé et al., 2006; Sha et al., 2007; Teil et al., 2007; Wang et al., 2008a; Wang et al., 2008b; Zeng et al., 2009; Dargnat et al., 2009; Li et al., 2015; Selvaraj et al., 2015; Gao and Wen, 2016), environmental behavior (Staples, et al., 1997; Turner and Rawling, 2000; Net et al., 2015) and potential risk (Li et al., 2015; Net et al., 2015; Zhang et al., 2015) in different kinds of environmental matrices. Previous research has largely focused on PAE distribution in aquatic environment such as some rivers and lakes of the world (Sha et al., 2007; Teil et al., 2007; Wang et al., 2008a; Zeng et al., 2009; Li et al., 2015; Selvaraj et al., 2015; Zhang et al., 2015). However, there have been few studies on estuaries, let alone comprehensively investigating the seasonal distribution and environmental chemical behavior of PAEs in water, suspended particulate matter (SPM) and sediment in a subtropical estuary. Jiulong River, located in the southeast of Fujian Province and transporting a total runoff of approximately 1.24 × 1010 m3/a, is a shallow estuary connecting to the Xiamen Bay and the Taiwan Strait. The river catchment covers an area of 14,740 km2 and includes 8 cities or counties with a population of over 3.5 million (Fujian Provincial Bureau of Statistics, 2015). This estuary has been subjected to frequent human activity in recent decades. In addition, an abundance of

Corresponding author at: State key Laboratory of Marine Environment Science, Xiamen University, Xiamen 361102, China. E-mail address: [email protected] (Z. Gong).

http://dx.doi.org/10.1016/j.marpolbul.2017.05.062 Received 17 October 2016; Received in revised form 22 May 2017; Accepted 27 May 2017 0025-326X/ © 2017 Published by Elsevier Ltd.

Please cite this article as: Li, R., Marine Pollution Bulletin (2017), http://dx.doi.org/10.1016/j.marpolbul.2017.05.062

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24.55°N

sampler (Van Veen bodemhappe, 2 L) and stored in a pre-cleaned brown glass jar at 4 °C on board. The sediment samples were then freeze-dried at − 20 °C for 72-h, ground with a mortar and sieved through a 100 mesh sieve, and finally stored in precleaned brown glass jar before pretreatment and analysis (GB 17378, 2007). To avoid possible contamination, no plastic equipment was used during all sampling and processing, and all glassware were previously soaked in a mixed K2CrO4/H2SO4 solution and then washed with a NaOH solution, tap water, ultrapure water, and acetone, sequentially.

N 24.50°N Haicang

S1

24.45°N S2

Zhangzhou

S4

Jiulong river estuary

S5 S6

Yellow River

Xiamen

S7 S8

S10 S11

S9

24.40°N

S13 S14

S3

S12

Changjiang River

S15

2.2. Chemicals and sample pretreatment

LEGEND

24.35°N

Water, SPM and sediment sampling

A mixed standard solution of 16 PAEs containing DMP, DEP, dipropyl phthalate (DPP), DBP, DIBP, dimethoxyethyl phthalate (DMEP), di-n-pentyl phthalate (DnPP), di-n-hexyl phthalate (DnHP), BBP, DEHP, di-n-heptyl phthalate (DHP), dicyclohexyl phthalate (DCHP), di-n-octyl phthalate (DnOP), DINP, di-iso-decyl phthalate (DIDP) and diundecyl phthalate (DUP) in n-hexane was prepared at 1000 mg/L for all PAE congeners. DMP-D4, DBP-D4 and DEHP-D4 in acetone (100 mg/L, Dr. Ehrenstorfer Gmbh, Germany) were mixed as a surrogate standard. Benzyl benzoate (BZB) in n-hexane (100 mg/L, Dr. Ehrenstorfer Gmbh, Germany) was used as an internal standard. Other chemicals used in this work are listed in Table S1. C18 sorbent (80–100 mesh) and neutral alumina (100–200 mesh) were cleaned with n-hexane using an ultrasonic extractor, baked at 60 °C to dry and stored in a sealed glass jar. Silica gel (100–200 mesh) and anhydrous sodium sulfate were baked at 180 °C and 420 °C for 12 h before use, respectively. Glass fiber filters (GF/F, Whatman) were carefully wrapped in pre-cleaned aluminum foil, and baked for 6 h at 400 °C prior to use. Prior to GC–MS analysis, the pretreatments of water, SPM and sediment samples were in accordance with previously established procedures in our laboratory (Liang et al., 2014; Li et al., 2017). The methods of sample pretreatment are also appended in the supporting information. A surrogate standard of 100 μL of 1.0 mg/L DMP-D4, DBPD4 and DEHP-D4 was spiked prior to pretreatment to further calibrate the analytical results and ensure the accuracy.

Ta iw

an S

tr a it

Jiulong River Estuary Pearl River

0km

7.5km

24.30°N

Fig. 1. Location of the Jiulong River and the sampling sites in the estuary.

pollutants has been introduced into the estuary by river runoff, sewage discharge, agriculture, the tourist industry and shipping. Therefore, it is of great significance to study the pollution level in the estuary. In this work, the concentration level, chemical composition, spatial distribution and seasonal variation of 16 PAEs in the estuary of Jiulong River were investigated through water, SPM and sediment samples collected from 15 sites in April 2014, August 2014 and January 2015, which represent typical normal, wet and dry seasons, respectively. To the best of our knowledge, this report describes the first time that the spatial distribution and seasonal variation of PAEs in this estuary have been comprehensively investigated, and the results may be of benefit to pollution control strategies for the river network. 2. Materials and methods 2.1. Sampling Water, SPM and sediment samples from 15 sites were collected along the salinity gradient in the Jiulong River estuary during the wet season (August 2014), normal season (April 2014) and dry season (January 2015), as shown in Fig. 1. The salinity of the water was directly measured on-board with a salimeter (RHS-10, Fuzhou Link Optical Instrument Co., LTD). Water samples taken from the top layer (0–20 cm) were collected with a 10 L precleaned stainless steel barrel and filtrated on-board through glass fiber filters (GF/F, 0.7 μm, Whatman, England) to separate SPM from water. Filtered water samples were stored in pre-cleaned 10 L brown glass jars at 4 °C on board. SPM samples were placed directly into pre-cleaned aluminum pots, stored at 4 °C on board, and finally transported to the laboratory for further pretreatment. The SPM samples were freeze-dried at −20 °C for 72 h and stored in aluminum foil in desiccators until the following extraction (GB 17378, 2007). The 0–10 cm top layer of sediment was collected with a grab

2.3. Instrumental analysis The qualitative and quantitative analyses of PAEs were carried out on an Agilent 7890 GC coupled 5975 MSD (Agilent Technologies, USA), operating with an electronic impact (EI) ionization source in full scan and selective ion monitoring (SIM) modes. The qualitative analysis was performed using the retention time of the characteristic ion in conjunction with the ratio of 2 characteristic ions of each PAE congener. The quantitative analysis was carried out using the standard calibration method with an internal standard for each individual PAE. Benzyl benzoate (BBZ) was selected as the internal standard in all PAE quantifications to improve the method precision. A DB-35MS gas chromatographic column (30 m × 250 μm i.d.,

Table 1 Concentration levels of PAEs in water-phase in the wet, medium and dry seasons (μg/L). PAEs

DMP DEP DIBP DBP DEHP DINP ∑ 6PAEs

Wet season

Normal season

Dry season

Range

mean

Median

DF(%, n = 15)

Range

Mean

Median

DF(%, n = 15)

Range

Mean

Median

DF(%, n = 15)

0.032–0.24 0.024–0.086 1.09–11.8 0.30–1.77 0.62–12.4 ND-0.39 3.01–26.4

0.12 0.058 4.48 0.67 3.66 0.15 9.10

0.099 0.058 3.57 0.56 2.18 0.092 6.09

100 100 100 100 100 80

0.034–0.15 0.014–0.091 2.46–5.71 0.31–0.51 0.12–1.76 ND 3.51–6.92

0.092 0.044 3.52 0.37 0.57 ND 4.58

0.093 0.046 3.27 0.33 0.40 ND 4.25

100 100 100 100 100 0

0.033–0.056 0.021–0.066 1.90–7.11 0.35–0.97 1.13–10.9 ND-0.52 3.58–17.7

0.039 0.033 3.08 0.54 3.99 0.32 7.81

0.038 0.028 2.95 0.53 3.00 ND 6.94

100 100 100 100 100 40

ND: not detected, the concentration was lower than that of the LOQ; DF: detectable frequency.

2

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Table 2 Concentration levels of PAEs in SPM in the wet, medium and dry seasons (mg/kg). PAEs

Wet season

DMP DEP DIBP DBP DEHP DINP ∑ 6PAEs

Normal season

Dry season

Range

Mean

Median

DF(%,n = 15)

Range

Mean

Median

DF(%, n = 15)

Range

Mean

Median

DF(%, n = 15)

ND-0.062 0.26–2.36 0.51–4.56 0.40–4.27 0.67–12.5 ND-0.29 2.03–22. 3

0.025 0.87 1.99 2.17 7.02 0.14 11.5

0.022 0.79 1.68 2.22 7.27 ND 12.0

73 100 100 100 100 40

0.066–0.37 0.028–0.22 1.04–9.21 0.13–1.31 0.29–8.42 ND-0.50 1.56–13.3

0.16 0.10 4.44 0.65 1.54 0.50 6.93

0.14 0.10 4.35 0.66 0.81 ND 6.57

100 100 100 100 100 7

0.015–0.033 ND-0.10 0.420–5.02 0.071–1.80 0.57–43.5 0.10–2.44 1.90–48.7

0.023 0.035 2.23 0.63 8.27 0.60 11.5

ND 0.018 2.06 0.72 5.69 0.18 8.82

27 80 100 100 100 67

ND: not detected, the concentration was lower than that of the LOQ; DF: detectable frequency. Table 3 Concentration levels of PAEs in sediment-phase in the wet, medium and dry seasons (μg/kg). PAEs

Wet season

DMP DEP DIBP DBP DEHP DINP ∑ 6PAEs

Normal season

Dry season

Range

Mean

Median

DF(%,n = 15)

Range

Mean

Median

DF(%, n = 15)

Range

Mean

Median

DF(%, n = 15)

ND-1.0 ND-1.9 10.2–84.4 1.6–41.4 11.6–285.6 ND-67.3 38.9–443.2

1.0 1.3 41.7 19.2 93.6 26.0 166.1

ND 1.1 38.8 21.5 69.2 ND 148.5

13 87 100 100 100 40

ND-5.1 ND-3.5 31.3–116.8 6.1–19.3 4.3–148.1 ND-29.4 44.0–268.3

2.3 1.9 70.3 11.5 23.9 11.9 112.4

1.9 1.8 68.9 10.8 10.4 ND 94.1

80 87 100 100 100 27

ND-1.8 ND-5.8 16.3–50.6 3.3–92.8 7.2–394.7 ND-110.5 37.1–583.1

1.4 2.2 36.5 20.5 77.5 39.6 161.0

ND 1.1 40.4 14.7 36.7 21.5 107.6

23 85 100 100 100 62

ND: not detected, the concentration was lower than that of the LOQ; DF: detectable frequency. DINP DEHP DBP DIBP DEP DMP

Sediment

Normal season

SPM

Dry season

Wet season

Wet season

standard derivation obtained with 7 blank samples and were in the range of 7.1 ng/L (DMP) to 58.3 ng/L (DIBP) for water samples, 9.8 μg/ kg (DEP) to 29.5 μg/kg (DEHP) for SPM samples and 0.3 μg/kg (DBP) to 5.2 μg/kg (DINP) for sediment samples. The method precision was estimated by the relative standard derivation of 5 parallel water/SPM/ sediment samples including all the sample pretreatments and the GC–MS analysis and ranged from 6.9% (DMP) to 14.3% (DEP) for water, 6.3% (DEP) to 9.5% (DINP) for SPM and 5.1% (DIBP) to 11.4% (DINP) for sediment. The standard addition recoveries of 6 identified and quantified PAEs were between 77.1% (DMP) and 101.9% (DEHP) for water, 90.3% (DMP) and 101.4% (DIBP) for SPM and between 87.0% (DBP) and 101.7% (DMP) for sediment. All these data were calibrated by surrogate standards with recoveries of 79.2% ± 9.8% (DMP-D4), 80.5% ± 12.8% (DBP-D4) and 102.4% ± 5.9% (DEHPD4) in water, SPM and sediment samples. Only DBP, DIBP and DEHP were found and quantified in the procedural blank analysis for water, SPM and sediment samples, which might be from the laboratory environment and the organic solvents. The procedural blanks of DMP, DEP and DINP were all lower than that of their corresponding LOQs.

Dry season

Water

Normal season Dry season Wet season Normal season 0

20

40

(%)

60

80

100

Fig. 2. Proportion of PAE congeners to ∑ 6PAEs concentration in water, SPM and sediment, in wet season (Aug. 2014), normal season (Apr., 2014) and dry season (Jan. 2015).

0.25 μm film thickness) from Agilent Technologies was used for PAE separation. The temperature program for the GC oven was initiated at 60 °C, increased to 280 °C at a rate of 20 °C/min, then ramped at a rate of 10 °C/min to 320 °C, and finally held at 320 °C for 8 min. The injector port was operated at 300 °C in the splitless mode. The temperatures for the transfer line, ion source and quadrupole were maintained at 280 °C, 230 °C and 150 °C, respectively. The ionization energy of the EI was 70 eV. The flow rate of the carrier gas helium (> 99.999%) was constant at 2.0 mL/min. The injection volume of the sample solution was 1.0 μL.

3. Results and discussion 3.1. Concentration levels of PAEs in water, SPM and sediment Of the 16 PAEs analyzed with GC–MS, only 6 PAE congeners, i.e., DMP, DEP, DIBP, DBP, DEHP and DINP, were identified and quantified in all water, SPM, and sediment samples. A descriptive statistical summary of the concentration of individual PAEs and the sum of PAEs (∑6PAEs) found in water, SPM and sediment for the 3 seasons, are shown in Table 1, Table 2 and Table 3, respectively. The concentration levels of PAEs in the water phase were 2–5 orders of magnitude lower than those in SPM and sediment phases, and the levels in sediment were 1–2 orders of magnitude lower than that in SPM. These results show that PAE congeners found in this estuary seemed to easily accumulate in SPM and sediment phases because of the weak polarities of PAEs. Moreover, the hydrodynamic condition and environment might have substantially more influence on PAEs

2.4. Quality control and quality assurance With each batch of 5 stations, a sample duplicate, a procedural blank, a spiked blank were arranged in field sampling. Additionally, a spiked matrix sample and a spiked matrix duplicate were added and processed in the laboratory. The relative error of two parallel samples should be lower than 6% for all PAE congeners in water samples, lower than 7.2% in SPM samples and lower than 6.5% in sediment samples. The limits of quantification (LOQs) were defined as the concentration equivalent to a 10-fold 3

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Wet season

Normal season

Conc. (

Conc. (

16

8

8

12

RR DEHP

RMR

MR Wet season

12

8

RR DEHP

RMR

MR

Normal season

12

8

8

8

2

4 2

0 RMR

MR

12

RMR

0 12

MR

10

10

8

)

8

)

8

6

6

Conc. (

Normal season

Conc. (

RR DIBP

10

6

4

4

4

2

2

2

MR

2

1

0

RMR

RR DBP

RMR

MR

2

Normal season

MR Dry season

RR DBP

RMR

MR Dry season

)

Wet season

1

0

Conc. (

RMR

)

RR DBP

Conc. (

Conc. (

)

2

RR DIBP

MR Dry season

4

)

Wet season

RMR

2

0 RR DIBP

RR DEHP

6

Conc. (

12

6

Conc. (

Conc. (

Conc. (

4

)

10

)

10

)

10

6

Fig. 3. Spatial distribution of ∑ 6PAEs and abundant DEHP, DIBP and DBP in water-phase in the Jiulong River estuary (RR: River Region; RMR: River-Marine Region; MR: Marine Region).

Conc. (

16

16

Dry season

24

)

24

)

)

24

1

0

composition with a contribution of 9.5% ± 3.7% in water, SPM and sediment phases for all the 3 seasons. DINP, with the highest partition coefficient (Kow) between octanol and water of all quantified PAE congeners in this work, tended to be absorbed by SPM in water and then transferred into sediment. DMP and DEP were distributed the least of all detected PAE congeners in all 3 phases. The contribution of dominant PAEs in water, SPM and sediment phase, e.g., DEHP, DIBP and DBP, was above 95.1%, 89.7% and 75.6%, respectively, in this studied estuary. This result is consistent with previous studies where DEHP, DIBP and DBP were the dominant components of the PAE distributions in water (Vethaak et al., 2005; Xie et al., 2007; Wang et al., 2008a) and sediment (Yuan et al., 2002; Mackintosh et al., 2006) and is also in accordance with the report that DEHP, DIBP and DBP were the most commonly produced PAEs (Vitali et al., 1997).

distribution equilibrium between SPM and sediment, which caused PAE congeners to enrich SPM compared with sediment. 3.2. Chemical composition of PAEs in water, SPM and sediment In the water phase, DMP, DEP, DIBP, DBP and DEHP were identified with a detection factor (DF) of 100% of all sampling sites; with the exception of DINP, which was found with a DF of 40% and 80% of sampling sites in the wet and dry seasons and was not detected in the normal season, as shown in Table 1. The occurrence of PAEs in SPM and sediment phases were quite similar, e.g., DEP, DIBP, DBP and DEHP were the most frequently found species (DF = 80%–100%), while DINP (DF = 7%–67%) and DMP (DF = 13%–100%) were detected at several sampling sites, as shown in Table 2 and Table 3. The proportional distribution of the PAE congeners presented in Fig. 2 show that DIBP and DEHP were the most abundant species with contributions of 88.4%–89.2%, 74.0%–89.1% and 64.1%–77.3% in water, SPM and sediment phases for all 3 seasons, respectively. DBP was a relatively minor participant that seemed like a relatively stable

3.3. Spatial distribution and seasonal variation of PAEs in water, SPM and sediment The spatial distribution of PAEs in the estuarine zone was not only 4

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Wet season

30

Normal season

30

20

20

20

10

10

10

RR DEHP

RMR

MR

Wet season

0 25

RR DEHP

RMR

MR

Normal season

Conc. (

Conc. ( RMR

0 8

MR

Wet season

RR DIBP

RMR

Normal season

)

)

Conc. (

4

Conc. (

2

2

RR DINP

RMR

0

MR

Wet season

2

RR DINP

RMR

Normal season

RR DBP

RMR

MR

Conc. (

0.0

4 3 2

RR DBP

RMR

MR

Normal season

0.0

4

Dry season

3

)

Wet season

MR

Dry season

)

) MR

RMR

1

Conc. (

Conc. (

2

RMR

)

)

3

RR DBP

Conc. (

4

RR DINP

2

1

1

0.0

0

MR

2

2

MR

Dry season

6

4

Conc. (

4

0

0 8

MR

6

)

6

RMR

)

)

) Conc. (

RR DIBP

RR DIBP

5

5

5 0 8

MR

Dry season

10

10

10

RMR

15

15

15

RR DEHP

20

20

20

0 25

Fig. 4. Spatial distribution of ∑ 6PAEs and abundant DEHP, DIBP, DINP and DBP in SPM-phase in the Jiulong River estuary (RR: River Region; RMR: River-Marine Region; MR: Marine Region).

2

Conc. (

0 25

Dry season

30

1

1

1

0

0

0

riverine runoff (PAE pollution mainly came from sewage runoff). The second region (5‰ ≤ salinity ≤ 25‰), named river-marine region (RMR), was alternatively influenced by the river and marine in accordance with the tidal cycle of the Taiwan strait (PAE pollution mainly came from tourism, sand mining, harbors, anchorages, aquiculture, drainage, and shipping). The third region (salinity ≥ 25‰), named

influenced by the mixing process of fresh water and salt water but also the hydrological condition and the environment of the estuary. In this work, the estuary was roughly classified into 3 regions according to the salinity gradient and the functional regionalization by the local municipal government (Fig. 1S). The first region (salinity < 5‰), named river region (RR), was at the river end and was mainly influenced by the 5

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Wet season

Dry season

Normal season

600

600

600

400

400

400

200

200

200

0 400

RR DEHP

RMR

MR Wet season

0 400

RR DEHP

RMR

MR

Normal season

0 400

300

300

300

200

200

200

100

100

100

0 120

RR DIBP

RMR

MR

0 120

Wet season

RR DIBP

RMR

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RMR

MR

0 120

Wet season

RR DINP

RMR

MR

Normal season

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RMR

MR Wet season

0 100

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0 100

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0 RR

RMR

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RMR

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RMR

RR

RMR

0 120

100

0 100

RR DIBP

Normal season

80

RR DINP

RMR

0 120

80

0 120

RR DEHP

Fig. 5. Spatial distribution of ∑ 6PAEs and abundant DEHP, DIBP, DINP and DBP in sediment-phase in the Jiulong River estuary (RR: River Region; RMR: River-Marine Region; MR: Marine Region).

MR Dry season

MR Dry season

MR Dry season

MR Dry season

0 RR

RMR

MR

MR

Fig. 3, had a similar trend for wet, normal and dry seasons, e.g., the concentration levels increased going from RR to RMR and MR in the studied estuary. The spatial distribution pattern of ∑6PAEs was in agreement with that of the abundant PAE congeners (DEHP, DIBP and DBP) for all 3 seasons. The difference was that the increasing trend for ∑6PAEs and abundant PAE congeners when going from RR to RMR was rapid in the wet season, while it was gradual in normal and dry seasons; this might represent the influence of riverine runoff on the spatial distribution in the estuary.

marine region (MR), was at the marine end and was significantly influenced by seawater (PAE pollution mainly come from harbors, anchorages, drainage, and shipping). Based on the above classification, Site S1 was in RR, and Sites 10–15 were in MR. The other sites, including Sites S2-S9, were in RMR. Fig. 3, Fig. 4 and Fig. 5 show the spatial distribution of ∑6PAEs and abundant PAE congeners in the RR, RMR and MR zones for water, SPM and sediment phases for all 3 seasons. In the water phase, the spatial distribution of ∑6PAEs, as shown in 6

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160

160

Normal season

120

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0 0

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Water-SPM

RR

log Kd

3 2 1 DMP DEP DIBP DBP DEHP DINP

Normal season

3 2 1 0 3

8 7 6

logKd and

4

3

Water-Sediment 9 8 7 6 5 4 3 2 1 DMP DEP DIBP DBP DEHP DINP 8 Normal season 7 6 5 4

1

3

3 2

2

0

1 DEP

DIBP

DBP

9 8 7 6 5 4 3 2 1

5 Dry season

log Kd

4 3 2

3

8

ii

ffi i

f6 A

DEP

DIBP

DBP

DEHP 9 8 7 6 5 4 3 2 1

Dry season

2

1

0

DMP DEP DIBP DBP DEHP DINP

i

1 DMP

DEHP

log K'd

DMP

log Kow

2

Fig. 8. Partition coefficient of 6 PAE congeners between water and SPM, water and sediment in 3-season (left: Water-SPM; right: WaterSediment).

logK’d

log K'd

log Kd

5

MR

2 log Kow

4

RMR

Wet season

log K'd

Wet season

4

log Kow

9 8 7 6 5 4 3 2 1

4

5

30

Fig. 7. Size distribution of the SPM in Jiulong River estuary in wet-, normal- and dry-season (RR: River Region; RMR: River-Marine Region; MR: Marine Region).

logKow

5

20

(%)

(%)

75

10

log Kow

0

Fig. 6. Spatial distribution of SPM in the Jiulong River estuary over 3 seasons.

Dry season

log Kow

Wet season

log Kow

160

DMP DEP DIBP DBP DEHP DINP

b

dS

7

d

di

i

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partition coefficients (Kow) between octanol-water of quantified PAEs for the 3 seasons are shown in Fig. 8. The values of logKow in Fig. 8 increased with the alkyl chain length in the ester bond of PAE congeners, while logKd and logKd′ had no significant regularity with alkyl chain length at the SPM-water and sediment-water interfaces for the normal, dry and wet seasons. The results in Fig. 8 demonstrate that the complication of the fluid dynamic condition in this estuary for the 3 seasons would be a key factor in influencing the vertical and horizontal diffusions of riverine and seawater. The micro-equilibrium of sorption-desorption at the SPM-water and sediment-water interfaces really but insufficiently occurred, which was quite different from that of the urban lakes in Guangzhou (Zeng et al., 2009) that usually represent a stationary state. The irregularity of logKd′ for the 3 seasons could be further explained by the sampling process because SPM was filtered and separated from the corresponding water sample, but the overlying water and sediment had no corresponding relationship in the horizontal direction. The logKd values of PAEs were approximately 1–2 magnitudes higher those that of logKd′ in this work, which is consistent with a previous study on PFAA in the Pearl River (Liu et al., 2015). This could be explained as the following: 1) the structure discrepancy between sediment and SPM, e.g., the different adsorption capacities for PAEs, exerted an influence on this variability. 2) The influx of fresh water might result in disequilibrium between water and SPM, leading to higher concentrations of PAEs in SPM and logKd values (Ahrens et al., 2010; Liu et al., 2015). As a result of the complicated hydrographic condition in the estuary compared with laboratory conditions, the logKow values of PAEs were higher than those of logKd and logKd′.

The interesting thing was that the spatial distribution patterns of ∑6PAEs and the abundant PAE congeners in the SPM phase were roughly a mirror image of the profile of SPM vs salinity in the RR, RMR and MR zones, as shown in Fig. 4 and Fig. 6. In other words, higher PAE levels and less SPM were found in the MR zone. It could be deduced that the size of suspended particulates, which directly corresponds to the surface area and the adsorption ability, could be one of the most important factors for PAE distribution in the SPM phase. A scanning electron microscope (SEM) was used to investigate the particulate distribution of SPM in the 3 different salinity regions. The results in Fig. 7 show that much finer particulates were found in the MR and RMR zones with higher salinities. In addition, a prior investigation (Lin et al., 2009) has also demonstrated that a strong mixing process occurred in the RMR zone, where the small size of particulates was retained, and larger size particulates eliminated or were removed in this region. The above analysis suggests that the spatial distribution of ∑6PAEs and the abundant PAE congeners are not only controlled by the riverine runoff (or the season) but also the hydrodynamic condition. Moreover, the spatial distributions of ∑6PAEs and PAE congeners in water and SPM phases, as shown in Fig. 3 and Fig. 4, had roughly similar patterns, e.g., relatively higher levels of PAEs occurred in the RMR and MR zones. A possible explanation is that there might have been other pollution sources in the marine end, such as harbors, anchorages, sewage discharge, tourist industry, and shipping lanes, according to the functional regionalization of the estuary of the Jiulong River, which also took part in the mixing process with PAEs from the river end to the RMR and MR zones. This shows that human activities have close relationships with the spatial distribution of PAEs, which is consistent with the previous results of other studies (Sun et al., 2013; Zheng et al., 2014). In sediment, the spatial distributions of ∑6PAEs and the abundant DEHP, DIBP, DINP and DBP were in good agreement with those of SPM distribution vs salinity, e.g., the levels decreased with increased salinity of the overlying water, as shown in Fig. 5. These results are additional evidence demonstrating that larger size particulates were easily removed by sedimentation in the RR zone, where mixing process of freshwater and seawater occurred, and small size particulates were easily transported into the RMR and MR zones. The occurrence of small size particulates was one of the most important factors that made PAEs mainly occur in the water and SPM phases, while the transfer into sediment was difficult.

4. Conclusions This report describes the first time that PAEs were comprehensively surveyed in water, SPM and sediment and provides systematic data on PAE concentration, chemical composition, spatial distribution and seasonal variation in the Jiulong River estuary, Southeast China. Of the 16 PAEs, DMP, DEP, DIBP, DBP, DEHP and DINP were present in all the samples analyzed and were dominated by DEHP, DIBP and DBP, which might be related to their long-term usage in the studied area. The spatial distributions of PAEs were affected by multifactor, e.g., riverine runoff, seasons, hydrodynamic condition, human activities, and the PAE physicochemical properties. This work would be of benefit to pollution control strategies for the future in this estuary.

3.4. Partition of PAEs between water-SPM and water-sediment Acknowledgments The spatial distributions of PAE congeners in the estuary of Jiulong River were not only controlled by the riverine runoff, seasons, hydrodynamic condition and human activities as discussed in 3.3, but also the physicochemical properties, such as molecular structure and polarity, of the PAE congeners. Therefore, the partition coefficients of PAEs between water and SPM, and water and sediment were calculated and studied in this work to estimate this effect. A partition coefficient is usually used to assess the ability of a chemical substance to be absorbed by the solid phase (SPM, sediment) from the liquid phase (water) (Zhou et al., 2013). In this work, Kd and Kd′ represent the partition coefficients of all analyzed PAEs between water-SPM and water-sediment and were calculated using Eqs. (1) and (2):

Kd =

CSPM Cwater

(1)

K d′ =

Cse dim ent Cwater

(2)

The authors appreciate the grant support of Public Welfare Industry Targeted Research Fund from the Ministry of Environmental Protection, China (201309007). The authors also thank Dr. Shuo Zhang, Mr. Yang Zhang, Ms. Jianying Zhu, Ms. Ningning Zhang, Mr. Yidong Lin and Mr. Dong Wang for their kind assistance in the field sampling, as well as Mr. Jianyong Li and Dr. Yuyun Wen from PFI Fareast for their help in the GC–MS analysis. Appendix A. Supplementary data Supplementary data to this article can be found online at http://dx. doi.org/10.1016/j.marpolbul.2017.05.062. References Ahrens, L., Taniyasu, S., Yeung, L.W.Y., Yamashita, N., Lam, P.K.S., Ebinghaus, R., 2010. Distribution of polyfluoroalkyl compounds in water, suspended particulate matter and sediment from Tokyo Bay, Japan. Chemosphere 79, 266–272. Bartolomé, L., Tueros, I., Cortazar, E., Raposo, J.C., Sanz, J., Zuloaga, O., de Diego, A., Etxebarria, N., Fernández, L.A., Madariaga, J.M., 2006. Distribution of trace organic contaminants and total mercury in sediments from the Bilbao and Urdaibai Estuaries (Bay of Biscay). Mar. Pollut. Bull. 52, 1111–1117.

where CSPM is the quantified level of PAEs in SPM (ng/kg), Cwater is the quantified value of PAEs in water (ng/L), and Csediment is the quantified concentration of PAEs in sediment (ng/kg). The logKd, logKd′ and the 8

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