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Isomeric specific partitioning behaviors of perfluoroalkyl substances in water dissolved phase, suspended particulate matters and sediments in Liao River Basin and Taihu Lake, China Xinwei Chen a, Lingyan Zhu a,*, Xiaoyu Pan b, Shuhong Fang a, Yifeng Zhang a, Liping Yang a a

Key Laboratory of Pollution Processes and Environmental Criteria, Ministry of Education, Tianjin Key Laboratory of Environmental Remediation and Pollution Control, College of Environmental Science and Engineering, Nankai University, Tianjin 300071, PR China b College of Marine Science of Engineering, Tianjin Key Laboratory of Marine Resources and Chemistry, Tianjin University of Science and Technology, Tianjin 300457, PR China

article info

abstract

Article history:

The occurrence and distribution of eleven perfluoroalkyl substances (PFASs) and the isomers

Received 25 December 2014

of perfluorooctanoate (PFOA), perfluorooctanesulfonate (PFOS) and perfluorooctane sulfon-

Received in revised form

amide (PFOSA) were investigated in water dissolved phase, sediment and suspended par-

17 April 2015

ticulate matter (SPM) in two typical watersheds in China: Liao River Basin and Taihu Lake.

Accepted 19 April 2015

The total concentrations of the PFASs in the dissolved phase were 44.4e781 ng/L in Liao River

Available online 14 May 2015

with high contribution of perfluorobutane sulfonate (PFBS) (75.7%) and PFOA (9.86%). The P PFASs in the dissolved phase in Taihu Lake was 17.2e94.4 ng/L with PFOA (39.8%), per-

Keywords:

fluorohexanoate (PFHxA) (30.1%) and PFOS (16.8%) as the dominant PFASs. The log Koc values

Perfluoroalkyl substances

of the PFASs in both SPM and sediment increased with increasing the perfluorinated carbon

Isomers

chain length. In Liao River Basin, the long chain perfluorocarboxylates (C10-12) bound with

Partition

SPM contributed >30% to the total amount in water, suggesting that SPM could not be ignored

Suspended matters

when the environmental load of long chain PFASs in water was assessed. For the isomers of

Telomer

PFOA, PFOS and PFOSA, the linear isomers always displayed higher partition coefficients on particulate phases than the branched ones. An established isomer-profiling technique was applied to assess the relative contributions of various industrial origins for PFOA. In Liao River, when SPM was included in the water samples, there were contributions of PFOA from electrochemical fluorination (ECF) (~55%), linear telomer (~41%) and isopropyl telomer (~4%) sources. While, the results based on the dissolved phase alone indicated more contribution of ECF (~70%) source and lower contribution from linear telomer (~26%) source. The discrepancy suggests that omitting SPM from water samples might lead to misunderstanding on the industrial origins of PFOA. In Taihu Lake, the isomer profile of PFOA was influenced mainly by ECF (~88%) and partially by linear-telomer (~12%) sources. © 2015 Elsevier Ltd. All rights reserved.

* Corresponding author. E-mail address: [email protected] (L. Zhu). http://dx.doi.org/10.1016/j.watres.2015.04.032 0043-1354/© 2015 Elsevier Ltd. All rights reserved.

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1.

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Introduction

Over the past 60 years, perfluoroalkyl substances (PFASs) have been synthesized and applied in surfactants, textile, aqueous fire-fighting foams, and other commercial products due to their attractive characteristics, such as water and oil repellency, chemical and thermal stability (Patrolecco et al., 2010). They have been widely detected in various environmental matrices (Dreyer et al., 2010; Muller et al., 2011; Myers et al., 2012; Wang et al., 2012), wildlife (Taniyasu et al., 2003; Tomy et al., 2009) and humans (Olsen et al., 2012; Sundstrom et al., 2011; Wang et al., 2011). Perfluorooctanoate (PFOA) and perfluorooctanesulfonate (PFOS) are two of the most detected PFASs in the environment and it is reported that they might cause adverse effects to animals and humans (Lau et al., 2007; Reagen et al., 2007). Although PFOS and its related compounds were listed as persistent organic pollutants under the International Stockholm Convention Treaty (Wang et al., 2009), commercial production and application of PFASs continue in China and it was reported that about 15 Chinese manufacturers produced more than 220e240 tons of PFOS-related chemicals annually in 2001e2011 (Xie et al., 2013). Due to the low volatility and high solubility of PFASs, aquatic environment is an important sink for them and their distribution between water and particles, including suspended particulate matters (SPM) and sediment, is considered as an important process in controlling their transport and fate (You et al., 2010). Some studies have been conducted to investigate the partitioning of PFASs between sediment and water, and demonstrated that the distribution was influenced by the physicochemical properties of PFASs, sediment compositions and water chemistry (Ahrens et al., 2009b; Higgins and Luthy, 2006, 2007). However, little is known about the partition of PFASs between the dissolved phase and SPM. There are many reports on the occurrence of PFASs in surface water around the world (Huset et al., 2008; Murakami et al., 2008; Yu et al., 2013). In most of these studies, the PFASs were only measured in the dissolved phase by filtering the water samples to remove SPM, which was not included in the total water sample. Herein, the burden of PFASs in water could be underestimated and the transport behaviors might be misunderstood considering that some PFAS homologues could be bound with SPM (Ahrens et al., 2009a). Electrochemical fluorination (ECF) and telomerization are the two major synthetic techniques to produce PFOA and result in different isomeric compositions. The ECF method, which produces a mixture of linear and branched isomers, had been largely used by 3M to produce PFASs, and phased out by 3M since 2002. However, ECF process still continues in China (Benskin et al., 2010). The ECF PFOA produced by 3M from 1950s to 2002 had a consistent isomer composition: 78 ± 1.2% linear and 22 ± 1.3% branched isomers (Reagen et al., 2007). Telomerization retains the structure of the starting telogen and produces a purely linear or isopropyl product (Loveless et al., 2006). Different from PFOA, PFOS is only manufactured by ECF method and it consistently composes of

~70% linear and ~30% branched isomers (Reagen et al., 2007). It was reported that the bioaccumulation and elimination properties and toxicities of PFASs were isomer-specific (Loveless et al., 2006, O'Brien et al. (2011)). Thus, it is important to investigate the fractionation of PFAS isomers during the partitioning process, which would affect the distribution and migration of the isomers in aquatic environment. Although there are a few studies reporting the isomer profiles of PFOA and PFOS in the environment, most of them focused on only one compartment but not on the isomeric partitioning between different matrices (Benskin et al., 2010; Yu et al., 2013). Several studies reported enrichment of branched PFOS isomers in water phase, which could be due to the different partition behaviors of the PFOS isomers and deserves further investigation (Benskin et al., 2010; Houde et al., 2008). An important issue pertaining to the regulation on PFASs is the extent of the environmental burden attributed to historical production (ECF) versus ongoing production (telomerization). Benskin et al. developed a method to quantitatively assess the contributions from ECF and telomerization sources by comparing the isomeric profiles of PFASs in environmental samples with those of commercials products, and applied to the water in North America, Asia and Europe (Benskin et al., 2010). In their study, the source apportionment was only performed to the dissolve phase of water while SPM was removed. Some bias could be induced considering that isomeric fractionation could occur due to the different partitioning of the isomers to the SPM. Liao River Basin is one of the most heavily polluted watershed in China, consisting of Liao River, Hun River and Taizi River (Fig. 1). They flow through Liaoning and Jilin provinces, where there are many oil refining plants, chemical plants, and smelting plants (Wang et al., 2012). In addition, the largest fluorochemical industrial facility of northern China is in the northwest of Liaoning province. The Taihu Lake is located in eastern China and is the second largest freshwater lake in China. The watershed of Taihu Lake covers several highly dense and industrialized regions, including Jiangsu and Zhejiang provinces, where PFAS manufacturing and PFAS-related industries such as textile treatment, metal plating, fire-fighting and semiconductor enterprises are densely distributed (Li et al., 2014; Xie et al., 2013). To the northeast of Taihu Lake, there is an industrial facility for fluorinated products. Relatively high level of PFASs was reported in the water of Taihu lake (17.8e448 ng/l) and Liao River Basin (1.4e131 ng/l) (Wang et al., 2012; Yang et al., 2011). The current study aimed to investigate the isomeric partitioning behaviors of PFASs between water dissolved phase and particular phases, including suspended particulate matter (SPM) and sediment. Field samples were taken from two watersheds in China: Liao River Basin and Taihu Lake. In addition, an established isomer-profiling technique was applied to determine the relative contributions of industrial origins (ECF, telomer (linear- or isopropyl-telomer)) for PFOA in both watersheds. The impact of SPM on the source apportionment was also investigated by including and excluding SPM in the model.

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2.

Materials and methods

perfluorooctane sulfonamide (PFOSA). The detailed information is provided in SI.

2.1.

Sample collection and preparation

2.3.

The samples of water, sediment and suspended particulate matter (SPM) were collected from Taihu Lake and Liao River Basin, China, in May and August 2012, respectively. The sampling points were selected according to guidelines of National Environmental Monitoring Program of China. As shown in Fig. 1 and Table S1, 22 sampling sites (T1-22) were located in Taihu Lake while 25 sites (HR1-11, LR1-14) were deployed along Liao River. The detailed information of the sampling is provided in SI.

2.2.

Reagents and standards

All native and 13C-labeled internal standards, including PFACMXB, MPFAC-MXA, brPFOSK, TPFOA, PFOSA and M8FOSA-M were purchased from Wellington Laboratories (Guelph, ON, Canada). PFAC-MXB and MPFAC are mixture of native and mass labeled linear standards of perfluorohexanoate (PFHxA), perfluoroheptanoate (PFHpA), PFOA, perfluorononanoate (PFNA), perfluorodecanoate (PFDA), perfluoroundecanoate (PFUdA), perfluorododecanoate (PFDoA), perfluorotetridecanoate (PFTrDA), perflurotetradecanoate (PFTeDA), perfluorobutanesulfonate (PFBS), perfluorohexanesulfonate (PFHxS), PFOS and perfluorodecanesulfonate (PFDS). M8FOSAM is a mass labeled internal standard for linear

Sample pretreatment and analyses

In order to separate the dissolved and particulate phases, 4 L of water was filtered through a glass fiber filter (142 mm, pore diameter 0.7 mm, Millipore Corp. USA), which was combusted at 450
C for 5 h before filtration and weighed, to get the dissolved phase. After filtration, the filter was freeze-dried and weighed and the SPM content remaining on the filter was determined. The target analytes in the dissolved phase were extracted by a solid phase extraction cartridge (Cleanert PEP, 6 mL 500 mg, Agela Technology, China). Sediment and SPM were extracted by ultrasonication with methanol and followed by purification with Cleanert PEP cartridges. The details about the extraction and purification, determination of the contents of organic carbon (foc) in SPM and in sediment are provided in SI. PFASs and the isomers of PFOS and PFOA were separated and quantified by HPLC-MS/MS (electrospray ionization in negative mode) with a FluoroSep-RP Octyl column. The information about LC-MS/MS and quality control is provided in SI. The optimized parameters of LC-MS/MS are supplied in Table S2 and the method detection limits and recoveries of each PFAS are provided in Table S3.

2.4.

Nomenclature for isomers

The nomenclature system for PFAS isomers was developed by Langlois and Oehme (2006) and modified by Benskin et al. (2007)

Fig. 1 e Sampling sites in Liao River and Taihu Lake of China.

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for the limited number of isomers present in commercial formulation. Linear and perfluoroisopropyl branches are abbreviated as n- and iso-PFAS, respectively. For the remaining monomethyl branched isomers, m refers to the perfluoromethyl branch, and the number preceding it indicates the carbon number on which the branch resides (e.g., 1perfluoromethyl-PFOS is 1m-PFOS). The sum of all diperP fluoromethyl isomers are abbreviated as m2-. The terms PFOS P and PFOA are used when referring to the sum of all isomers. The major PFOS and PFOA isomers are listed in Table S2.

2.5.

Data analysis

The fraction of PFASs bounded to SPM (j) was calculated using the following equation. J ¼ CSPM =ðCw þ CSPM Þ

(1)

where CSPM and Cw are the concentrations of PFASs in SPM (ng/ L) and in water dissolved phase (ng/L). Water-sediment (or water/SPM) distribution coefficient (Kd, cm3/g) was calculated according to the following equation: Kd ¼ Cs =Cw  1000

3.

Results and discussion

3.1. Distribution of PFASs in the surface water of Liao River and Taihu Lake 3.1.1.

PFASs in dissolved phase

The concentrations of all PFASs in the samples in Liao River and Taihu Lake are listed in Table S4 and S5, respectively. All the target compounds were detected at all sampling sites except PFDoA with a detection frequency of 88% in Liao River. P The total concentrations of the PFASs ( PFASs) in the dissolved phase ranged from 44.4 to 781 ng/L with PFBS as the predominant homologue (arithmetic mean 134 ng/L), followed P by PFOA (mean 12.0 ng/L) (See Fig. 2). The level of PFASs in the dissolved phase was higher than that reported in a preP vious study ( PFASs, mean 12 ng/L, range 3.2e121 ng/L), in which only C7eC11 perfluorocarboxylates (PFCAs) and C6eC8 perfluorosulfonates (PFSAs) were quantified in Liaoning province (Liugu River in Huludao, Daliao River and Xiaoliao River in Panjing, Taizi River in Yingkou and Liao River in Panjin) (Wang et al., 2012). The prevalence of PFBS in Liao River

(2)

Cs is PFAS concentration in sediment (ng/g dw) or SPM (ng/g dw). The organic carbon normalized distribution coefficient (Koc, cm3/g) of PFASs between sediment (SPM) and water dissolved phased was calculated as follows:  Koc ¼ Kd  100 foc

(3)

foc is the percentage of organic carbon in sediment (SPM). Field-based Koc was also calculated using the above equation to describe the partitioning of PFASs between water and sediment in field, although it is in a dynamic partitioning process and may be affected by many field factors. An established isomer-profiling technique was applied to estimate the relative contribution of industrial origins for PFOA: linear-telomer (i.e. 100% n-PFOA), isopropyl-telomer (i.e. 100% iso-PFOA), and ECF (ca. 82% linear/18% branched PFOA) (Benskin et al., 2010). The detailed information about the source apportionment is provided in SI.

2.6.

Statistical analysis

All statistical analyses were performed with IBM.SPSS. Statistics.v20. Spearman correlation analysis was performed to evaluate correlation between the concentrations of the PFASs. One-way analysis of variance (ANOVA) was used in PFOA source apportionment. Student's t-test was used for comparing the concentration of PFASs in different sampling sites and repeated measures ANOVA with Bonferroni correction was applied to compare the log Koc of PFAS isomers.

Fig. 2 e The distribution of PFASs in the dissolved water phase (ng/L) in Liao River (A) and Taihu Lake (B). X-axis labels correspond to the sites along the water body shown in Fig. 1.

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is unexpected since PFOA and PFOS are usually the predominant homologues reported in many previous studies (Benskin et al., 2012; Myers et al., 2012; Zhang et al., 2012). A fluorochemical industrial park, which covers an area of 7.1 km2 with several fluorochemical plants, was built in 2004 in Fuxin, which is located in the northwest of Liaoning province. The potassium salt of PFBS and polytetrafluoroethylene (PTFE), which could be degraded to PFOA, are the major products of the park (Bao et al., 2011). This may help to explain the high level of PFBS and PFOA in the surface water of Liao River. It was reported that PFBS was also the predominant PFAS (with an average concentration of 3660 ng/L) in the surface water of Tangxun Lake in Wuhan, China (Zhou et al., 2013). This could be a result of the introduction of short-chain PFASs as substitutes for long-chain homologues in recent years. As for the PFCAs with long carbon chain length, such as PFUnA (mean 0.087 ng/L) and PFDoA (mean 0.073 ng/L), their concentrations in dissolved phase were much lower. PFOSA, one of the precursors of PFOS, was detected in all of the samples but at a low level (mean 0.037 ng/L). A significant positive correlation (r ¼ 0.51, p < 0.05) was observed between PFOS and PFOSA, indicating that they may share the same source or PFOSA may degrade to PFOS (Benskin et al., 2013). The highest level of P PFASs occurred at site HR7 (781 ng/L), followed by HR11 (667 ng/L). HR7 is located at the downstream of Shenyang, the capital of Liaoning province; while HR11 is close to the city of Yingkou and at the downstream of Hun River. Liao River is one of the seven largest rivers in China and goes through several heavy industrial cities, such as Shenyang, Panjin, Fushun, Fuxin and Yingkou. The heavy industrial and municipal activities may contribute to the high level of PFASs in Liao River. P In the branch Hun River, the PFASs at the upstream (HR1-6, mean 65.1 ng/L) was significantly (p < 0.05) lower than those at the downstream (HR7-11, mean 385 ng/L), indicating the impacts of industrial and municipal activities on the pollution of PFASs in Liao River Basin. In Taihu Lake, all the PFASs were detected in the dissolved P phase with detection frequency of 100% and the PFASs was in the range of 17.2e94.4 ng/L (see Fig. 2). This level was P slightly lower than those ( PFASs 62e126 ng/L) reported by Yu et al. (2013). For the individual PFASs, PFOA, PFHxA and PFOS were the most prevalent compounds. The compositions of PFASs in Taihu Lake were different from those in Liao River, suggesting that different PFAS products are used in the two regions. Short-chain perfluorinated alternatives (C < 6) are produced and used as substitutes of PFOS and PFOA due to the regulation on PFOS/PFOA and related products. This may explain the relatively high level of PFHxA. In addition, the PFOS concentration (2.3e18.3 ng/L) in Taihu Lake was significantly higher than that in Liao River (0.089e9.5 ng/L) (P < 0.005). According to a survey on industrial source of PFOS in China in 2012 (Xie et al., 2013), Jiangsu, a typical industrial province in China, releases almost 10 tons of PFOS into the environment annually. Textile treatment and metal plating are the most significant PFOS source and responsible for 53% and 43% of the total PFOS emission in Jiangsu province. Relatively high level of PFOS (14.4e18.3 ng/L) appeared at T1, T2, T3, T7 and T17. All these sites are close to industrial cities such as Wuxi and Yixing. The PFASs with perfluoroalkyl chains longer than eight carbons such as PFNA, PFDA, PFUnA,

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PFDoA, displayed much lower concentrations, which were 1.18, 0.59, 0.17 and 0.032 ng/L, respectively. Similar to Liao River, PFOSA (mean 0.052 ng/L) was 2e3 orders of magnitude lower than that of PFOS. The fluctuation of PFHxA concentration distinctly affects the geographic distribution of P PFASs in Taihu Lake. When the concentration of PFHxA was P taken out of the calculation of PFASs, the highest level of total other 10 PFASs appeared at T2 (78.7 ng/L) in the north of Meiliang bay. Close to the Meiliang bay is Wuxi city, in which there are many manufacturers for textile, plastic and electronics (Zhang et al., 2010). It is speculated that the discharge of effluent from the municipal waste water treatment plants or direct discharge of waste water may contribute for the relatively high level of PFASs in the north area of Taihu Lake.

3.1.2.

PFASs in SPM

In Liao River, all the PFASs were detected in the SPM samples with detection frequency in the range of 96e100% and the P mean PFASs was 64.0 ng/g dw. The level of PFASs in the SPM was much higher than that in the basin of Tokyo bay (6.4e15.1 ng/g dw) (Ahrens et al., 2010; Zushi et al., 2012). In contrast to the dissolved phase, PFOA predominated in the SPM in Liao River, contributing 46.9% of total PFASs, and was followed by PFHxA and PFHpA, accounting for 17.9 and 12.4% P of PFASs. For the SPM in Taihu Lake, all the PFASs were detected in 100% of the samples except for PFHxS (86.4%) and the mean P PFASs in the SPM was 109 ng/g dw. In contrast to the results P in the dissolved phase, the level of PFASs in the SPM of Taihu Lake was much higher than Liao River. The predominant PFAS compounds were PFHxA, PFOS and PFOA with an average contribution of 40.0, 21.4 and 12.0% respectively. The different distribution of PFASs in SPM and dissolved phase may be attributed to the different partitioning behavior of each PFAS between the two phases.

3.2. Distribution of PFASs in the sediment of Liao River and Taihu Lake P The PFASs in the sediment samples in Liao River was in the range of 0.54e2.34 ng/g dw with mean concentration of 1.03 ng/g dw (Table S4), which was comparable to those in Zhujiang River (range 0.09e3.6 ng/g dw), Huangpu River (range 0.25e1.1 ng/g dw) (Bao et al., 2010) and Daliao River of China P (0.29e1.3 ng/g dw) (Bao et al., 2009). The highest PFASs in sediment (2.34 ng/g dw) occurred at site HR5, which is situated close to Shenyang city, a typical heavy industrial city in northeast China. The major PFASs in the sediment samples were PFHxA (mean 0.55 ng/g dw), followed by PFOA (mean 0.18 ng/g dw), PFDoA (mean 0.076 ng/g dw) and PFOS (mean 0.042 ng/g dw). While PFBS (mean 0.016 ng/g dw) in the sediment only contributed 1.92%, which could be due to the lower partitioning of PFBS in sediment as compared to PFOA and PFOS. P In Taihu Lake, the PFASs in sediment were in the range of 0.57e17.9 ng/g dw, with a mean concentration of 4.12 ng/g dw (Table S5). A notable high concentration was observed at site T9 (17.9 ng/g dw), which might be influenced by the discharge of waste water from Yixing city. Similar to Liao River, the major PFASs in the sediment of Taihu were PFHxA (mean

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1.47 ng/g dw), PFHpA (mean 1.22 ng/g dw), PFOA (mean 0.35 ng/g dw) and PFOS (mean 0.29 ng/g dw).

3.3. Partitioning of PFASs between water dissolved phase and particulate phases Field-based water-sediment distribution coefficients (Kd) were calculated to describe the partitioning of PFASs between water dissolved phase and sediment. It was found that the Kd values of PFHxA, PFOA, PFNA, PFDA and PFUnA correlated significantly (p < 0.05) with foc. This agrees with a previous field study conducted in Netherlands which reported a strong correlation between Kd and foc for PFOS and PFOA (Kwadijk et al., 2010). Despite that PFASs are both hydrophobic and lipophobic, several studies demonstrated that their sorption to sediment is greatly dependent on the hydrophobic interaction between PFASs and organic carbon (Higgins and Luthy, 2006). Thus, log Koc values were calculated for both Liao River and Taihu Lake, and no significant difference was observed between the two watersheds (p > 0.05). Hence, the data of the two watersheds were grouped together and the average log Koc values of PFASs are listed in Table 1. For PFCAs, the log Koc ranged in 2.26e5.01; for PFSAs, it was in the range of 1.62e3.26. The log Koc of PFOA (3.09) was similar to the results reported in other field studies, such as Netherlands (2.63 ± 0.34) (Kwadijk et al., 2010), Haihe river in Tianjin, China (3.1 ± 0.3) (Li et al., 2011). For PFOS, the log Koc (3.26) was also similar to that in Netherlands (3.16 ± 0.28) (Kwadijk et al., 2010), Dianchi lake, China (3.35 ± 0.32) (Zhang et al., 2012), but lower than that in Haihe river in Tianjin, China (4.4 ± 0.3) (Li et al., 2011). In general, the log Koc increased with increasing the perfluorinated carbon chain length (Higgins and Luthy, 2006; Sun

Table 1 e Average log Koc (cm3/g) in sediment and SPM in Liao River and Taihu Lake. Compounds PFHxA PFHpA n-PFOA iso 4m 5m P PFOA PFNA PFDA PFUnA PFDoA PFBS PFHxS n-PFOS iso 1m 4m 3þ5m m2 P PFOS n-PFOSA Br-PFOSA P PFOSA

Sediment-derived log Koc 2.26 2.53 3.11 2.96 2.77 2.82 3.09 3.71 4.29 4.73 5.01 1.62 2.29 3.38 3.17 2.42 2.22 2.53 2.65 3.26 4.41 3.63 4.28

± 0.53 ± 0.36 ± 0.38 ± 0.48 ± 0.53 ± 0.51 ± 0.35 ± 0.51 ± 0.47 ± 0.47 ± 0.30 ± 0.37 ± 0.49 ± 0.43 ± 0.51 ± 0.71 ± 0.64 ± 0.42 ± 0.63 ± 0.43 ± 0.71 ± 0.63 ± 0.71

SPM-derived log Koc 1.99 2.00 3.68 3.11 2.44 2.57 3.62 3.87 4.47 4.76 4.93 1.79 2.28 4.03 3.42 2.60 2.47 2.60 2.71 3.80 4.32 3.33 4.18

± 0.61 ± 0.62 ± 0.81 ± 0.79 ± 0.78 ± 0.90 ± 0.79 ± 0.46 ± 0.48 ± 0.46 ± 0.54 ± 0.80 ± 0.81 ± 0.56 ± 0.75 ± 0.73 ± 0.98 ± 0.68 ± 0.53 ± 0.56 ± 0.55 ± 0.65 ± 0.54

et al., 2011). The slope of log Koc versus the number of carbon atoms was calculated by linear regression and it was 0.49 for PFCAs and 0.41 for PFSAs respectively (Fig. 3). The results agree with those of Higgins and Luthy (2006), who reported that log Koc increased by 0.45 log units with each additional CF2 for PFCAs and 0.5 log units for PFSAs. To understand the partitioning behaviors of PFASs between SPM and water, a SPM-derived partitioning coefficient log Koc was also estimated, and the results are listed in Table 1. In general, the SPM-derived log Koc values were similar to the sediment related log Koc values, although the foc of SPM (4.38e35.0%) was almost one order of magnitude higher than that of sediment (0.26e6.90%). They also increased with the perfluorinated carbon chain length. These support that organic carbon played an important role in the partitioning of PFASs between particulate and dissolved phases. To estimate the contribution of SPM to the total water samples (which were defined as the sum of dissolved phase and SPM), particulate bound PFAS fraction (j) was calculated and the results are shown in Table S6. The average j of P PFASs was 2.21% and 2.05% for Liao River and Taihu Lake, respectively, suggesting that PFASs are mostly present in the dissolved phase. This is similar to the result in seawater of P Tokyo Bay, where the j was 3% for PFASs (Ahrens et al., 2010). For individual PFASs, the j was in the range 0.09e33.8%. This is different from the typical hydrophobic organic pollutants. It was reported that 72% of overall polyaromatic hydrocarbons (PAHs) were partitioned in SPM (the amount of SPM in water was 0.016e0.024 g/L) (Patrolecco et al., 2010), and up to 70% of the total tri-, tetra- and pentabrominated diphenyl ethers were partitioned in SPM due to their very strong hydrophobicity (Wurl et al., 2006). The much lower j values of PFASs was due to the lower partitioning affinity of PFASs to particulate compared to the hydrophobic pollutants. The calculated log Koc of PFASs was 1.62e5.01, much lower than that of PBDEs (5.9e6.0) (Tlili et al., 2012) and PAHs (5.0e7.0) (Patrolecco et al., 2010). For the PFCAs with long carbon chain length, such as PFDA, PFUnA, PFDoA, and PFOSA, relatively higher j values (16.5e33.8%) were observed in Liao River. This suggests that the environmental load of

Fig. 3 e Correlation between sediment-derived log Koc and perfluorinated carbon chain length.

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these long-chained analogs and hydrophobic precursors in water could be underestimated if only dissolved phase were monitored, and their fate could also be misunderstood. The SPM-bound fractions of PFASs in Liao River were generally higher than those in Taihu Lake, presumably due to the higher mass fraction of SPM in Liao River (mean 0.082 g/L) than in Taihu Lake (0.020 g/L).

3.4. PFOA isomer profiles and partitioning between water and particular phases The isomer profiles of PFOA in dissolved phase and in total P water samples are illustrated in Fig. 4. For PFOA in the dissolved phase of Liao River and Taihu Lake, n-PFOA predominated with an average contribution of (84.2, 89.2%). It was followed by iso-PFOA (6.88, 7.81%), 5m-PFOA (3.25, 4.45%) and 4m-PFOA (2.08, 3.68%). This composition was similar to ECF PFOA product, which is n-PFOA (78%), iso-PFOA (10.1%), 4mPFOA (3.9%) and 5m-PFOA (3.12%) (Loveless et al., 2006). The proportion of n-PFOA was comparable to that in Mississippi River, U.S. (mean 84.9%), Hangzhou (mean 82.2%) (Benskin et al., 2010), Taihu Lake (mean 92.4%) and Huai River (mean 90.5%), China (Yu et al., 2013), but lower than in Lake Ontario (97e98%) (De Silva et al., 2009). In the sediment and SPM samples, n-PFOA was still predominant, and the proportion of n-PFOA was in a range of 72.7e98.9% in sediment and 87.0e99.6% in SPM. The sediment and SPM related log Koc values of PFOA isomers were calculated and they were in the order of: n-PFOA (3.11, 3.68), iso- (2.96, 3.11), 5m- (2.82, 2.57), 4m- (2.77, 2.44). The results suggest that n-PFOA is more inclined to distribute in particulate phases than branched isomers and thus n-PFOA is enriched in sediment and SPM. The different partitioning behaviors of PFOA isomers could be attributed to their physicochemical properties. Until now, there are no reports on the physicochemical properties of PFOA isomers. It is believed that the HPLC elution behaviors of the isomers are related to their properties, such as polarity, hydrophobicity (Benskin et al., 2007). Thus, it seems plausible to correlate the physicochemical properties of PFOA isomers to their HPLC elution orders on reversed-phase stationary phase. In the analysis of PFOA isomers by HPLC, n-PFOA is the latest eluting isomers on both C18 column (Benskin et al., 2007) and FluoroSep-RP Octyl column, which was used in the present study, implying that nPFOA is the most hydrophobic as compared to branched ones. There was no significant difference among the log Koc values of the branched isomers (p > 0.05), including iso-, 4m-, and 5mPFOA. This could be due to the minor differences in their structures and physicochemical characteristics. To the best of our knowledge, this is the first report on the partitioning behavior of PFOA isomers between sediment and water.

3.5.

Estimating the manufacturing origins of PFOA

In comparison to SPM and sediment, branched isomers of PFOA made greater contribution to the total PFOA in dissolved phase. However, the proportion of n-PFOA in dissolved phase was still higher than in ECF standard (78%), which is suggestive that PFOA in Liao River and Taihu Lake was probably not exclusively from ECF. Herein, an established isomer-profiling

Fig. 4 e Profiles of PFOA in Liao River (A, dissolved phase plus SPM; B, dissolved phase only) and in Taihu River (C, dissolved phase plus SPM; D, dissolved phase only).

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technique was applied to estimate the relative contribution of industrial origins (ECF and telomer including linear- or isopropyl-telomer) for PFOA in Liao River and Taihu Lake (Benskin et al., 2010). It is noting that previous studies only focused on PFOA in dissolved phase, which might lead to misunderstanding considering the partitioning behaviors of PFOA isomers between dissolved phase and SPM. Herein, the sum of PFOA in dissolved phase and SPM was applied for comparison in the present work. For Liao River, as both the dissolved phase and SPM were considered, a significant difference was observed in the branched: n-PFOA isomer ratios (P < 0.05) as compared to ECF PFOA, suggesting that there was linear-telomer source of PFOA except ECF PFOA. A follow-up statistical analysis indicated that there were significant differences in the branched: iso-PFOA isomer ratios (P < 0.05), implying that the isopropyl telomer might also contribute to the PFOA in Liao River. The contribution of ECF, linear and isopropyl sources was approximately 55%, 41% and 4% respectively. This result is similar to the results reported in Tokyo Bay, in which there was relatively high contribution of linear and isopropyl sources to PFOA contamination (Benskin et al., 2010). Different result was observed if only dissolved phase was considered: the contribution of ECF, linear and isopropyl sources was about 70, 26 and 4% respectively. For Taihu Lake, in both cases, significant difference (P < 0.05) was observed in the ratios of branched: n-PFOA isomers, indicating that Taihu Lake could be greatly influenced by linear-telomer besides the ECF source. However, no significant difference was observed in the branched: iso-PFOA isomer ratios (P > 0.05), suggesting that there was no contribution of isopropyl source. The contribution of ECF and linear-telomer sources to PFOA in the water of Taihu Lake was estimated to be approximate 88 and 12% respectively. These results imply the existence of telomer sources in China. Taken together, the inconsistent result between the statistical analysis including and excluding SPM in Liao River is indicative that omitting particulate phase from water samples might lead to misunderstanding when one intends to determine the relative contribution of industrial origins.

3.6.

Isomeric profiles of PFOS in water and sediment

It was reported that the isomer profile of 3M PFOS has a consistent composition of 70 ± 1.1% linear and 30 ± 0.8% branched isomers despite different manufacturing locations and batches (Reagen et al., 2007). Despite the limited information on manufacturing PFOS in China, Benskin et al. (2010) reported that three commercial PFOS products manufactured in China had similar compositions with 69.1e78.2% n-PFOS. In both Liao River and Taihu Lake, n-PFOS was predominate in dissolved phase (average contribution 43.2 and 40.3% for Liao River and Taihu Lake), followed by iso-PFOS (22.5, 20.9%), 3þ5m-PFOS (18.0, 18.8%), 4m-PFOS (11.9, 12.5%), m2PFOS (3.43, 5.62%) and 1m-PFOS (1.01, 1.94%) (Fig. S1). Compared to the commercial products, a highly enrichment of branched isomers appeared in the dissolved phase (Liao River 56.8%; Taihu Lake 59.7% branched), which is in agreement with the results of previous studies, mean 54.9% branched PFOS in Taihu Lake (Yu et al., 2013), 51.9% in Mississippi River

(Benskin et al., 2010) and 43e56% in Lake Ontario (Houde et al., 2008), respectively. In the sediment and SPM samples, linear isomer n-PFOS was significantly enriched as compared to the dissolved phase (sediment: 70.0e71.4%; SPM: 83.8e85.3%). The sediment-related log Koc values of PFOS isomers were calculated (Table 1), and they were: n-PFOS (3.38), iso- (3.17), m2- (2.65), 3þ5m- (2.53), 1m- (2.42), 4m- (2.22). The SPM derived log Koc of PFOS isomers were similar to the sediment-related log Koc values (Table 1). Moreover, the average log Koc of nPFOS was significantly higher than those of branched isomers (P < 0.05). These results indicate that n-PFOS is inclined to partition to particular phases. This could be due to the higher hydrophobicity of n-PFOS relative to the branched isomers. On both C18 and the FluoroSep-RP Octyl column, n-PFOS eluted the latest, which is suggestive that linear n-PFOS is more hydrophobic than other isomers. Until now, there is only one report on the PFOS isomeric profile in both water and sediment, in which Houde et al. (2008) reported a deficiency of branched PFOS isomers (81e89% linear) in sediment, which was consistent with our results. The isomeric profiles of PFOS in the environmental compartments could also be affected by its precursors. For P PFOSA, branched isomers of PFOSA (Br-PFOSA) were detected in water samples and accounted for 24.7 and 36.0% of P PFOSA in Liao River and Taihu Lake, respectively. The linear PFOSA (n-PFOSA) in sediment accounted for 92.5 and 95.2% of P PFOSA in Liao River and Taihu Lake. The sediment-related and SPM based log Koc of linear PFOSA was 4.41 and 4.32 respectively, higher than that of Br-PFOSA (3.63; 3.33), suggesting that Br-PFOSA is more water soluble than linear one. Previous studies reported preferential absorption and retention of n-PFOSA in hepatic microsomes of rats, fish and humans due to the preferential excretion of Br-PFOSA (Benskin et al., 2009; Tomy et al., 2004; Xu et al., 2004). In addition, it was reported that the branched isomers of a model PFOS precursor were preferentially biotransformed to branched PFOS than linear isomer. Therefore, preferential excretion of branched isomers of PFOS precursors from biota, and their preferential transformation in water may contribute to the relatively higher proportion of branched PFOS isomers. To further understand the partitioning behaviors of PFOS isomers between water and sediment, adsorption experiments were conducted in the lab under controlled conditions with microbial activity inhibited (see SI). The isomeric profile of PFOS in the supernatant showed branched isomer signature: n-PFOS 66.2% and br-PFOS 33.8%. While for sediment, the proportions of PFOS isomers were: n-PFOS 81.5% and br-PFOS 18.5%. The proportion of n-PFOS in the supernatant was much higher than the field results of Liao River and Taihu Lake. The difference between the laboratory and field results indicates that PFOS precursors could make contributions to the isomeric profiles of PFOS in water.

4.

Conclusions

The contamination of PFASs in Liao River and Taihu Lake was widely present. PFBS and PFOA were predominant in the dissolved water phase of Liao River while PFOA, PFHxA and PFOS were the most prevalent compounds in Taihu Lake. The

w a t e r r e s e a r c h 8 0 ( 2 0 1 5 ) 2 3 5 e2 4 4

fraction of PFASs bound with SPM (j) was in the range 0.09e33.8%, much lower than those typical hydrophobic organic pollutants (72% for PAHs). These suggest that PFASs are mostly present in the dissolved phase. The log Koc was in the range of 2.26e5.01 and 1.62e3.26 for the studied PFCAs and PFSAs, respectively. The log Koc values of the PFASs in both SPM and sediment increased with increasing the perfluorinated carbon chain length. For the isomers of PFOA, PFOS and PFOSA, the linear isomers always displayed higher partition coefficients than the branched ones, possibly due to the greater hydrophobicity of the linear isomers. As a result, branched isomers were enriched in the water dissolved phase, and misunderstanding on production origin could be made if SPM was not included in water samples. The results indicated that there are linear telomer source in both watersheds and there is isopropyl telomer source in Liao River.

Acknowledgments We acknowledge financial support from the Natural Science Foundation of China (NSFC 21277077, 21325730, 21077060), Ministry of Education (20130031130005), Ministry of Environmental Protection (201009026) and the Ministry of Education Innovation Team (IRT 13024).

Appendix A. Supplementary data Supplementary data related to this article can be found at http://dx.doi.org/10.1016/j.watres.2015.04.032.

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