Chemosphere 88 (2012) 1292–1299
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Determination and partitioning behavior of perﬂuoroalkyl carboxylic acids and perﬂuorooctanesulfonate in water and sediment from Dianchi Lake, China Yuan Zhang a,b, Wei Meng a,b,⇑, Changsheng Guo a,b, Jian Xu a,b, Tao Yu a,b, Wenhong Fan c, Lei Li a,b a
State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China Laboratory of Riverine Ecological Conservation and Technology, Chinese Research Academy of Environmental Sciences, Beijing 100012, China c Department of Environmental Science and Engineering, School of Chemistry and Environment, Beihang University, Beijing 100191, China b
a r t i c l e
i n f o
Article history: Received 26 October 2011 Received in revised form 16 March 2012 Accepted 31 March 2012 Available online 11 May 2012 Keywords: Perﬂuorinated compounds (PFCs) HPLC–MS/MS Partition Dianchi Lake
a b s t r a c t Perﬂuorinated compounds (PFCs) have received much attention on their distribution in various matrices including water bodies, precipitations, sediment and biota in different areas globally, however, little attention has been paid to their occurrence and distribution in urban lakes. In this study, water and sediment samples collected from 26 sites in Dianchi Lake, a plateau urban lake in the southwestern part of China were analyzed via high performance liquid chromatography–tandem mass spectrometry (HPLC–MS/MS) for ten analytes involving nine perﬂuoroalkyl carboxylic acids (PFOAs) and perﬂuorooctanesulfonate (PFOS). Total levels of PFCs were 30.98 ± 32.19 ng L1 in water and 0.95 ± 0.63 ng g1 in sediment. In water samples PFOA was the dominant PFC contaminant, with concentrations ranging from 3.41 to 35.44 ng L1, while in sediments PFOS was the main PFC contaminant at levels from 0.07– 0.83 ng g1 dry weight. Field-based sediment water distribution coefﬁcients (KD) were calculated and corrected for organic carbon content (Koc), which reduced variability among samples. The log K oc ranged from 2.54 to 3.57 for C8–C12 perﬂuorinated carboxylic acids, increasing by 0.1–0.4 log units with each additional CF2 moiety. The log K oc of PFOS was 3.35 ± 0.32. Magnitudes and trends in log K D or log K oc appeared to agree well with previously published laboratory data. Results showed that different PFC composition proﬁles were observed for samples from the lake water and sediments, indicating the presence of dissimilar characteristics of the PFCs compounds, which is important for PFC fate modeling and risk assessment. Ó 2012 Elsevier Ltd. All rights reserved.
1. Introduction Perﬂuorinated compounds (PFCs) consisting of perﬂuorosulfonates (PFSAs) and perﬂuorocarboxylates (PFCAs) are a new class of emerging organic pollutants, and make up a group of surfactants that have been in production for more than 50 years (Prevedouros et al., 2005; Teng et al., 2009). These PFCs have attractive properties for industrial applications, such as interfacial activity, resistance to acid and high temperatures, and water and oil repellency. They are highly stable, bio-accumulative and resistant to degradation in the environment. The widespread applications of PFCs coupled with their unique characteristics make them ubiquitously distributed in various types of environmental matrices including river and ocean water (Yamashita et al., 2008; Zushi and Masunaga, 2009), sediments (Zushi et al., 2010), wildlife biota (Senthil et al., 2009), and the human body (Zhang et al., 2010).
⇑ Corresponding author at: State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China. Tel.: +86 10 84915237; fax: +86 10 84926073. E-mail address: [email protected]
(W. Meng). 0045-6535/$ - see front matter Ó 2012 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.chemosphere.2012.03.103
They were even found in remote areas, such as the Arctic (Martin et al., 2003) and Tibetan Plateau (Shi et al., 2010). Identifying the transport and fate of PFCs in aquatic environment is necessary for strategy designing of pollution control. The understanding of PFCs fate in aquatic systems is still incomplete and so far there is only limited data on their distribution between water and sediment (Kwadijk et al., 2010; Li et al., 2011). PFCs can accumulate in aquatic systems and are readily transported by typical hydrological or adsorbable processes (Houde et al., 2006; Lau et al., 2007; Eschauzier et al., 2010). There are a few laboratory studies on sorption processes providing sorption data under controlled laboratory conditions (Higgins et al., 2005; Higgins and Luthy, 2006, 2007; Johnson et al., 2007; Ochoa-Herrera and Sierra-Alvarez, 2008). Hydrophobic interaction was reported to play an important role in PFCs sorption on sediment (Higgins and Luthy, 2006). The partitioning behavior of PFCs has also demonstrated that the sediment–water distribution depends on solution parameters such as pH (Higgins and Luthy, 2006) and sediment organic carbon fraction (foc) (Liu and Lee, 2005; Ahrens et al., 2010). However, adsorption parameters of PFCs obtained from laboratory studies were different from ﬁeld based sediment–water
Y. Zhang et al. / Chemosphere 88 (2012) 1292–1299
distribution coefﬁcients (Liu and Lee, 2005; Ahrens et al., 2010; Kwadijk et al., 2010). The extent to which the resulting distribution parameters and mechanistic inferences apply to ﬁeld conditions is not yet clear. Besides, limited data show that the distribution of different PFC homologues between sediment and water were different. The short-chain perﬂuorinated carboxylic acids (PFCAs) (C8) and perﬂuoroalkyls sulfonates (PFASs) appeared to be bound to sediment (Ahrens et al., 2009, 2010). There is still a relative lack of ﬁeld-based PFC distribution coefﬁcients, which is essential for environmental fate modeling. Dianchi Lake (24°280 –25°280 N, 102°300 –103°000 E) is located in the middle of Yunnan-Guizhou Plateau in Southwest China. The entire basin has a total area of approximately 2920 km2, including part of Kunming City (the capital of Yunnan Province), Songming, Chenggong, Jinning, and Xishan Counties. The lake serves many social and economic purposes, with 2.68 million residents in the Dianchi Basin, and yearly burden of 216 million m3 of household wastewater and 47.6 million m3 of industrial waste water (Yang et al., 2010). Previous researches performed in Dianchi Lake were mostly focused on high COD, TN and TP contents which caused the serious eutrophication in the lake (Lu et al., 2007; Yang et al., 2010). The information on PFCs contamination, however, to the best of our knowledge, is not available in this region. In this study, the occurrence and spatial distribution of PFCs in water and sediments from Dianchi Lake was determined, and the composition proﬁles of PFCs in both water and sediment samples were investigated. Partition coefﬁcients were also calculated to investigate the partition behavior of these PFCs compounds between water and sediment.
2. Experimental 2.1. Chemicals and regents The standards, perﬂuorobutanoate (PFBA, 99.5%), perﬂuoropentanoate (PFPeA, 95%), perﬂuorododecanoate (PFDoA, 95%) and perﬂuorooctane sulfonate (PFOS, 99%) were purchased from Sigma–Aldrich (St. Louis, MO, USA). Perﬂuorohexanoate (PFHxA, 98%), perﬂuoroheptanoate (PFHpA, 98%) and perﬂuoroundecanoate (PFUnA, 96%) were purchased from Matrix Scientiﬁc (Columbia, SC, USA). Perﬂuorooctanoate (PFOA, 98%), perﬂuorononanoate (PFNA, 98%) and perﬂuorodecanoate (PFDA, 98%) were purchased from Wellington Laboratories (Guelph, Ontario, Canada). 13C8-labeled PFOA (Cambridge Isotope Laboratories, Andover, MA, USA) and 13 C4-labeled sodium PFOS (Wellington Laboratories, Guelph, Ontario, Canada) were used as the internal standards. All stock solutions were prepared in methanol and stored in polypropylene (PP) tubes or vials at 4 °C. Methyl tert-butyl ether (MTBE), acetone, methanol, acetic acid and ammonium acetate were of HPLC reagent grade and purchased from Beijing Chemical Reagent Factory (Beijing, China).
2.2. Sample collection and preparation Water and sediment samples were collected from Dianchi Lake in October, 2010 (Fig. 1), with their geographic information given in Table SI-1 in Appendix Supplemental Information (SI). Two parallel water samples were collected at a depth of approximately 0.5 m below the surface water with a stainless steel bucket, and stored in 5 L polypropylene (PP) bottles. Surface sediment samples (0–10 cm) were collected with a stainless steel grab sampler and placed in PP bags. Samples were transported to laboratory on ice for further treatment. All sampling vessels were pre-cleaned with
methanol, Milli-Q water, and water from the speciﬁc site before sampling. Temperature of the water sample was from 17.2–20.7 °C during sampling campaign. The pH and total dissolved solids (TDS) of water samples were determined and the values are listed in Table SI-1. The TDS of water samples from Dianchi Lake did not vary a lot, ranging from 204 (S14) to 310 mg L1 (S1 and S2). pH values ranged from 7.08 (S1) to 9.87 (S11, and S13). foc of sediments were determined by the method of potassium dichromate–sulfuric acid oxidation (Li et al., 2011), and are also listed in Table SI-1. 2.3. Extraction and cleanup Water samples (1500 mL) were ﬁltered through GF/A glass ﬁber ﬁlter (Whatman Inc., USA) to remove large particles and biota, and then spiked with internal standards (including 5 ng of 13C8-PFOA and 5 ng of 13C4-PFOS), followed by solid phase extraction (SPE) by Oasis HLB cartridges (500 mg, 6 mL, Waters Corp., Milford, MA, USA). Prior to SPE extraction, the cartridge was preconditioned by 10 mL of methanol and 10 mL of Milli-Q water. The ﬁltered water samples were passed through the cartridges at a ﬂow rate of 5 mL min1, and the cartridge was then rinsed by 5 mL of 40% methanol in water. Finally, the target fraction was eluted with 8 mL of methanol. The extract was reduced to 1 mL under a gentle N2 stream, and transferred into a polypropylene vial for chemical analysis. PFCs in the sediment were analyzed according to the method reported by Naile et al. (Higgins et al., 2005; Naile et al., 2010) with some modiﬁcations. The extraction procedure consisted of two steps, (a) extraction of the PFCs from the sediments by sonication and (b) enrichment and clean-up of the extract by SPE. 2.0 g of homogenized freeze-dried sediment (from Dianchi Lake) were transferred to 50 mL PP centrifuge tubes and spiked with 5 ng internal standard, to which 10 mL of 1% acetic acid solution (pH = 3) was added. Each tube was vortexed, and placed in a heated sonication bath (40 °C) for 15 min. The tubes were then centrifuged at 4000 rpm for 5 min and the supernatant was decanted into a new clean 50 mL PP tube. 2.5 mL of 90:10 (v/v) methanol and 1% acetic acid mixture was then added to the original tube. The mixture was sonicated for 15 min, centrifuged, and the supernatant was combined into the second tube. This process was repeated one more time, and a ﬁnal 10 mL of extracting solution was preformed. All extracts were combined in the second tube before SPE. To test the extraction efﬁciency of different solvents, in this study pure methanol instead of the above extraction solvents was used to extract PFCs from sediments, following the similar procedure described above. 2.4. HPLC–MS/MS analysis PFCs were analyzed by HPLC–MS/MS. The HPLC separation was performed on an Agilent 1200 series (Palo Alto, CA, USA) equipped with an Agilent Zorbax Eclipse XDB-C18 column (2.1 100 mm, 5 lm). The column was maintained at 40 °C during the sample analysis. The mobile phase consisted of eluent A (methanol) and eluent B (2.5 mM ammonium acetate solution). Flow rate was kept at 0.25 mL min1, and the injection volume was 20 lL. The separation of PFCs was achieved with a gradient program, with an initial gradient of 30% A, and increased to 40% A at 4 min, and continuously increased to 90% A at 9 min. The gradient was reverted to 30% A at 13 min and was maintained for 2 min. Mass spectrometric analyses were performed on an Agilent 6410 triple quadrupole mass spectrometer equipped with an electrospray ionization (ESI) source that operated in the negative ionization mode. The nebulizer pressure was set to 35 psi and the ﬂow rate of drying gas was 3 L min1. The capillary and nozzle voltages
Y. Zhang et al. / Chemosphere 88 (2012) 1292–1299
Fig. 1. Sampling sites in Dianchi Lake.
were 4000 and 0 V, respectively. The ﬂow rate and temperature of the sheath gas (nitrogen) were 7 L min1 and 350 °C, respectively. The collision gas was argon, and the collision energies are listed in Table SI-2. Multiple responses monitoring (MRM) analysis was used to identify analytes. For each analyte, quantiﬁcation was based on the response of a single product ion (Table SI-2). Internal calibration was used to quantify analytes. 13C8-PFOA and 13C4-PFOS were used as the internal standards for PFCAs and PFOS, respectively. The analytical procedure was carried out in triplicates to evaluate the precision. 2.5. Quality assurance During the sampling and analytical processes, Teﬂon coated lab wares were avoided to minimize contamination. Along with each batch of ten samples, one procedure blank was run to make sure the analytical procedure was operating correctly. Solvent blanks containing Milli-Q water and methanol (1:1, v/v) were prepared to run after every ten samples for monitoring the instrumental background. Recoveries of the PFCs were tested with the water and sediment from Dianchi Lake. Per matrix, a sample was spiked with 2 and 20 ng of each PFC. A duplicate of the unspiked sample was also performed in the case of the sediment, and calculated as the percentages of the measured concentrations relative to the spiked concentrations. Quantiﬁcation of each PFCs compound was obtained using the internal standard method. Calibration curves were constructed for the range of 0.2–50 lg L1 for the PFCs, with linearity of r2 > 0.995. Limit of detection (LOD) and limit of quantiﬁcation (LOQ) of the PFCs were calculated with signal/
noise ratios (S/N) of 3 and 10, respectively. The S/N ratios were obtained by using the software Masshunter (Agilent) processing the results of the recovery test done at the concentration of 0.2 lg kg1.
3. Results and discussion 3.1. Recoveries of PFCs from sediment The extraction solvent is crucial on the extraction of PFCs from sediments, as PFCs tend to complexate with organic matters and adsorb strongly onto sediment (Powley et al., 2005; Voogt and Sáez, 2006). In 2005 Higgins et al. for the ﬁrst time developed an acetic acid extraction method to analyze PFCs in sediment and domestic sludge (Higgins et al., 2005; Naile et al., 2010), which was used in many following studies. The half dry alkaline method was also used to extract the PFCs from the sediment with NaOH in 20% H2O/80% methanol solvents (Powley et al., 2005; Ahrens et al., 2009). In the present study, the effect of the extraction solvent was evaluated by extracting the PFCs from spiked sediments by acid solution and by pure methanol solvent. For each extraction method, triplicate samples of sediment (2 g) were spiked with 20 lL and 200 lL of 100 ng mL1 mixture solution (containing PFCAs and PFOS), and recoveries of two-step extraction for various PFCAs and PFOS were determined. Results were summarized in Table 1. It indicated that the efﬁciencies of acetic acid solution and methanol extraction method for PFOS and short-chain PFCAs were similar, with recoveries ranging from 61% to 100%. However, for some long-chain PFCAs, methanol extraction gave better recoveries
Y. Zhang et al. / Chemosphere 88 (2012) 1292–1299 Table 1 Recoveries, LODs and LOQs for individual PFCs in sediment. Analyte
PFBA PFPeA PFHxA PFHpA PFOA PFNA PFDA PFUnA PFDoA PFOS a b c
% Recovery (SD) from sediment Acid method
Pure methanol method
2 ng g1
20 ng g1
2 ng g1
20 ng g1
74 67 61 83 74 79 62 41 47 75
71 79 63 76 62 64 55 53 36 69
75 (4) 100 (2) 83 (8) 97 (7) 90 (4) 81 (6) 67 (3) 99 (7) 101 (2) 74 (5)
76 86 79 76 89 82 79 86 77 88
(4) (3) (3) (2) (8) (4) (2) (3) (5) (7)
(3) (2) (3) (6) (2) (2) (3) (3) (2) (4)
(2) (2) (7) (2) (3) (4) (3) (2) (3) (3)
Sediment (ng g
0.029 0.028 0.020 0.028 0.011 0.014 0.018 0.014 0.013 0.010
Water (ng L
0.23 0.11 0.24 0.35 0.33 0.22 0.17 0.24 0.16 0.22
Sediment (ng g
0.096 0.066 0.066 0.092 0.02 0.033 0.059 0.046 0.043 0.020
Linearity (r2)c 1
Water (ng L
0.55 0.43 0.63 0.92 0.94 0.86 0.38 0.72 0.31 0.74
0.9953 0.9994 0.9995 0.9988 0.9987 0.9982 0.9988 0.9998 0.9982 0.9989
Limit of detection. Limit of quantiﬁcation. Calibration curves (0.2–50 lg L1 for each compound).
than acetic acid solution. As shown in Table 1, recoveries of PFDA, PFUnA and PFDoA (C10–C12) ranged from 67–101% by methanol extraction, while by acetic acid extraction, the recoveries were from 36–62%. Long-chain PFCs tend to strongly adsorb to sediments, causing it difﬁcult to be extracted (Yang et al., 2011). Methanol extraction method provided better recovery for most PFCs than the acid method, especially for long-chain PFCAs. In this study, PFCs in sediments were extracted by methanol.
3.2. Spatial distribution of PFCs in water samples Although 10 different PFCs compounds were determined in this study, in the following sections PFOS and PFOA would be primarily discussed since these two compounds were consistently found at the greatest concentrations. The occurrence and concentrations of PFCs in surface water samples collected from Dianchi Lake were summarized in Fig. 2a. PFOA and PFOS were detected in all samples. For long-chain PFAs (C9–12), PFNA, PFDA, PFUnA and PFDoA, their detection frequencies (chance to be detected) in water samples were from 19.2% to 30.7%, while short-chain PFAs (C4–7) were detected in much higher frequency (30.8–34.6%). The proﬁles of relative concentrations of 10 PFCs in water from Dianchi Lake were shown in Fig. 3a. In the study sites, PFOA contributed 10.8–87.8% of the total PFCs, however, relatively smaller contributions of PFOS were determined between 6.0% and 60.9% of all analytes. Comparable to PFOS, PFHxA and PFHpA contributed 7.9–34.2% and 10.0–39.0% of the total target analytes in these locations (Fig. 3a). The other six PFAs including PFBA, PFPeA, PFNA, PFDA, PFUnA and PFDoA were measured with less frequency and at lower concentrations. For instance, PFUnA and PFDoA were not detected in most of the water samples, and their levels were ranging from
Fig. 2. Spatial distribution of PFCs in surface water (a) and sediment (b) from Dianchi Lake.
PFOS and PFOA were the dominant compounds in surface water from Dianchi Lake, with concentrations ranging from 1.71– 40.90 ng L1 and 3.4–35.44 ng L1, respectively, which was comparable to the levels in other aquatic environments around the world. As shown in Table 2, the levels of PFOA and PFOS in Dianchi Lake were similar to those reported in Taihu Lake and Liao River in China (Yang et al., 2011), and relatively lower than those reported in
Y. Zhang et al. / Chemosphere 88 (2012) 1292–1299
Fig. 3. Average contribution of each compound to the total PFCs in water (a) and sediment (b) from Dianchi Lake.
Table 2 Concentrations of PFOS and PFOA in water (ng L1) and sediment (ng g1 dw) in samples around the world. Sampling
Yangtzi River Estuary, China Orge River near Paris, France Estuarine and coastal areas of Korea Several River of Japan Daliao River system of northeast China San Francisco Bay, USA Pearl River Delta, China Yangtzi River near Shanghai Zhujiang River, Guangzhou, China Taihu Lake, China Haihe River, Tianjin China Dianchi Lake, China
Water Sediment Water Sediment Water Sediment water Sediment Sediment Sediment water Water Sediment Water Sediment Water Sediment Water Sediment Water Sediment
2008 2008 2010 2010 2008 2008 2003 2005 2008 2004 2003–2004 2005 2009 2004 2009 2009 2009 2010 2010 2010 2010
4 4 12 12 15 12 5 9 10 17 8 12 9 6 22 32 32 16 16 26 26
Great Lakes of North America (Boulanger et al., 2004; Kannan et al., 2005), Mississippi River Basin (Nakayama et al., 2010), South China Sea (So et al., 2004), Tokyo Bay and coastal areas of Korea (Yamashita et al., 2005; Naile et al., 2010). The highest concentration of PFOA detected in Dianchi Lake (35.44 ng L1) was much lower than the highest level found in Yangtzi River (206 ng L1) (So et al., 2007) and the rivers from Tokyo Bay (192 ng L1) (Yamashita et al., 2005). The mean concentrations of PFOA and PFOS in Dianchi
36.3–703.3 72.9–536.7 17.4 ± 2.2 4.3 ± 0.3 4.11–450 59 ± 112 Nd-2.0 7.9–110 Nd-3.9 0.06–0.37 n.d.-3.76 0.02–12 0.62–14 ND-0.46 0.90–99 n.d.3.1 3.6–394 0.06–0.31 2.02–7.62 1.76–7.32 1.71–15.12 0.07–0.83
NA NA 9.4 ± 0.6 <0.07 2.95–68.6 20.6 ± 19.8 Nd-2.0 4.1–10 Nd-6.4 0.09–0.17 n.d.-0.625 0.24–16 22–260 0.20–0.64 0.85–13 0.09–0.28 10.6–36.7 <0.02–0.52 14.4–42.1 0.92–3.69 ND-35.44 ND-0.71
(Pan and You, 2010) (Labadie and Chevreuil, 2011) (Naile et al., 2010) (Senthilkumar et al., 2007) (Bao et al., 2009) (Higgins et al., 2005) (So et al., 2004) (So et al., 2007) (Bao et al., 2010) (So et al., 2007) (Bao et al., 2010) (Yang et al., 2011) (Li et al., 2011) This study
Lake were approximately 10.31 ng L1 and 7.78 ng L1, respectively. 3.3. Spatial distribution of PFCs in sediment Distribution of PFCs in the sediment of Dianchi Lake was shown in Fig. 2b. The RPFCs ranged between 0.21 and 2.45 ng g1 dry weight. Similar to the spatial distribution tendency of PFCs in sur-
Y. Zhang et al. / Chemosphere 88 (2012) 1292–1299
face water, relatively higher RPFCs were found in Caohai, with the highest RPFCs appeared in S2 with a concentration up to 2.45 ng g1 dw. Corresponding low RPFCs were observed in sediments of Waihai area. In contrast to the similarity of spatial distribution with water samples, the PFCs in the sediment showed a different composite proﬁle, as shown in Fig. 3b. In aqueous phase long-chain PFCs were less detected, while in sediments more PFCs including the longchain PFCAs such as PFNA, PFDA, PFUnA and PFDoA were detected with high detection frequencies (57.7–69.2%). Different composite proﬁles observed between water and sediment indicated that the distribution of individual PFCs was closely dependent on their physicochemical characteristics. Short-chain PFCAs tend to exist in water phase, while long-chain PFCAs and PFOS seem to bind more strongly to sediment. This suggests that long-chain PFCs are prone to partition to sediment, which may act as a sink for these chemicals in the environment. PFOS was the predominant PFC and was detected in all sediment samples, which contributed 24.0–84.8% of the total PFCs in the sediments. However, relatively smaller contribution of PFOA was determined between 11.5% and 41.2% of the total detectable analytes, followed by PFHpA (8.3–24.7%) and PFNA (3.7–22.9%). Levels of PFOS were determined between 0.07 and 0.83 ng g1 dw, with a median value of 0.25 ng g1, while levels of PFOA were ranged below LOD to 0.71 ng g1 dw with a median value of 0.12 ng g1 dw. For PFNA, PFDA, PFUnA and PFDoA, their concentrations in sediments were from below LOD to 0.30 ng g, 0.18 ng g1, 0.17 ng g1 and 0.14 ng g1 dw, respectively. The concentrations of PFBA and PFPeA in sediments were measured below their LOQs in most of the sampling sites. The highest concentration of PFOA and PFOS up to 0.71 ng g1 and 0.83 ng g1 dw appeared in site S1 and S2 that was placed close to the conventional city centre as mentioned earlier. Nevertheless, PFOA contaminations were not observed in sites S16 and S25, where in sites S16 only PFOS and PFUnA was determined as the PFCs contaminant. Although the long-chain PFCAs were still at low levels, the detection frequency and concentrations increased with longer carbon chains. Table 2 summarized the concentrations of PFOA and PFOS in the sediments in some other study areas. PFOA in the sediments of Dianchi Lake was comparable to that in the Taihu Lake, China with mean concentration of 0.16 (0.02–0.52) ng g1 (Yang et al., 2011), slightly higher than that found in the Daliao River system with a mean concentration of 0.12 (0.09–0.17) ng g1 dw (Bao et al., 2009) and in the rivers by San Francisco Bay, USA with a mean concentration of 0.25 (n.d.0.625) ng g1 dw (Higgins et al., 2005). Sediment concentration of PFOA was lower than that in Kyoto River in Japan with the concentration from 1.30–3.90 ng g1 dw (Senthilkumar et al., 2007), much lower than that in Huangpu River in Shanghai and Haihe River in Tianjin, China, where a mean concentration of PFOA was found to be 34.60 (5.20–203) ng g1 and 1.80 (0.90–3.70) ng g1 dw, respectively (So et al., 2007; Li et al., 2011). As for PFOS, its sediment concentration was comparable to those in Taihu Lake, China (0.11 (0.09–0.14) ng g1 dw) (Yang et al., 2011), Roter Main River, Germany (0.201 (0.09–0.348) ng g1) (Becker et al., 2008) and Daliao River (0.21 (0.06–0.37) ng g1) (Bao et al., 2009), but lower than in the San Francisco Bay, USA (n.d.3.76 ng g1 dw) (Higgins et al., 2005), Haihe River, China (5.20(1.80–7.30) ng g1 dw), and Orge River, France (mean concentration of 4.30 ng g1 dw) (Labadie and Chevreuil, 2011). 3.4. Partition of PFCs between sediment and water Partition coefﬁcient was calculated to understand the relative importance of sediment and aqueous PFCs concentrations from Dianchi Lake, according to the following equation:
K D ¼ C sediment =C water where Csediment is the concentration in sediment as expressed in micrograms per kilogram, Cwater is the water concentration in micrograms per liter, and KD is in liters per kilogram. The organic carbon normalized partition coefﬁcient (Koc) was also calculated with the following equation because the organic carbon content of sediments was reported to inﬂuence the transport of PFCs in sediments by previous studies (Ahrens et al., 2010; Kwadijk et al., 2010).
K oc ¼ K D 100=foc where foc is the organic carbon fraction in sediment. The log K D and log K oc values for PFCs were shown in Table SI-3 and Table 3. The average log K D of 1.80 ± 0.29 (n = 26) for PFOS in Dianchi Lake was similar to the reported ﬁeld log K D values (1.2– 1.6; 2.1 ± 0.1; 2.53 ± 0.35) in literatures (Becker et al., 2008; Ahrens et al., 2010; Kwadijk et al., 2010), and much lower than that reported in Haihe River and Dagu River (3.1 ± 0.2) in China (Li et al., 2011). For PFOA, the average value of log K D (1.3 ± 0.4) was higher than previous reports, i.e. 0.04 ± 0.03 (Ahrens et al., 2010) and 0.18–0.48 (Becker et al., 2008), but agreed with the report value (1.83 ± 0.40) in Netherlands (Kwadijk et al., 2010). It should be noted that the values of log K D of the PFOA varied from different sampling points. For example, log K D of PFOA was 0.56 at site S4, but 2.05 at site S9. The sediment properties and water conditions may affect the partition of PFCs in real environment (Yang et al., 2011). The difference of log K D values in different studies was probably related to the different physicochemical characteristics of PFCs. The special physical and chemical properties of anionic PFCs make both hydrophobic and electrostatic effects co-inﬂuence their sorption behavior (Li et al., 2011). For a given PFC class, perﬂuoroalkyl chain length was the dominant structural feature inﬂuencing sorption onto river sediments (Higgins and Luthy, 2006). Water chemistry may also inﬂuence the sorption of PFCs on sediment. A signiﬁcant correlation was found between pH and sedimentary concentrations of some PFCs, showing increasing sorption of PFCs with decreasing pH of approximately 0.37 log units per unit pH (Higgins and Luthy, 2006; Ahrens et al., 2009; You et al., 2010). Other parameters such as Ca2+ and salinity were also reported to enhance PFC sorption onto sediment, which can be explained that the increased concentration of CaCl2 could neutralize the negative charge on the sediment surface, and reduced the electrostatic repulsion between the negative charged sediment surface and the anionic PFOS. The decreased electrostatic repulsion would certainly promote the sorption of anionic PFOS molecule to the sediment surface through electrostatic attraction (Higgins and Luthy, 2006; You et al., 2010). Another important inﬂuencing factor was the sediment property, for instance, the organic carbon content of sediments (Ahrens et al., 2010; Li et al., 2011). The sediment organic carbon was the dominant sorbent-speciﬁc parameter affecting sorption of PFCs in the dilute solution range, which was Table 3 Average log K D and log K oc (L kg1) at sediment–water interface from Dianchi Lake. Compound
log K D
PFBA PFPeA PFHxA PFHpA PFOA PFNA PFDA PFUnA PFDoA PFOS
S1–S26 S1–S26 S1–S26 S1–S26 S1–S26 S1–S26 S1–S26 S1–S26 S1–S26 S1–S26
1.18 ± 0.096 (n = 3) 1.14 ± 0.38 (n = 3) 1.33 ± 0.37 (n = 5) 1.24 ± 0.15 (n = 7) 1.27 ± 0.40 (n = 24) 1.18 ± 0.21 (n = 8) 1.64 ± 0.28 (n = 6) 1.89 ± 0.11 (n = 4) 1.95 ± 0.35 (n = 6) 1.80 ± 0.29 (n = 26)
2.62 ± 0.10 2.54 ± 0.51 2.72 ± 0.40 2.62 ± 0.21 2.63 ± 0.45 2.75 ± 0.22 3.05 ± 0.30 3.28 ± 0.21 3.57 ± 0.25 3.35 ± 0.32
(n = 3) (n = 3) (n = 5) (n = 7) (n = 24) (n = 8) (n = 6) (n = 4) (n = 6) (n = 26)
Y. Zhang et al. / Chemosphere 88 (2012) 1292–1299
Fig. 4. Correlation between log K oc and perﬂuoroalkyl chain length.
employed to normalize partition coefﬁcients of PFCs to minimize deviations. In this study, the average log K oc values (Table 3) increased with an increasing perﬂuoroalkyl chain length. From PFNA to PFUnA, log K oc values increased by 0.1–0.4 log units with each CF2 moiety (Fig. 4), which was consistent with previous studies (Higgins and Luthy, 2006, 2007; Ahrens et al., 2010; Li et al., 2011). It is notable that the slope of the regression of log K oc vs. f(alkyl chain length) was 0.26 (Fig. 4), which was different from 0.45 reported by Higgins and Luthy (2006). This variation may be due to the difference in sediment properties, and that different PFAs were considered (Labadie and Chevreuil, 2011). For PFOS, the average log K oc of 3.35 ± 0.32 (n = 26) was rather high when compared to the values reported by Johnson et al. (Johnson et al., 2007) and Higgins and Luthy (Higgins and Luthy, 2006, 2007), i.e. log K oc = 2.4–3.1 and 2.57, respectively, and was consistent with the values reported by Kwadijk et al. and Li et al., i.e. log K oc = 3.61 and 4.4 (Kwadijk et al., 2010; Li et al., 2011). In addition to the difference in sediment characteristics, this variation may be partially attributed to the sediment–water equilibrium status. 4. Conclusions A sensitive and reliable analytical method was developed to simultaneously determine the concentration of ten PFCs in water and sediment samples from Dianchi Lake, China. Methanol solution showed better extraction efﬁciency of PFCs from the sediments than the acetic acid method. Pollution of PFCs in Dianchi Lake was in a moderate level, compared with their occurrence in other areas around the world. This study also provided ﬁeld-based distribution coefﬁcients (KD and Koc) for a wide range of PFCs, which were still relatively scarce and useful for a better understanding of the fate of PFCs in aquatic ecosystems. Acknowledgements This work was ﬁnancially supported by China’s national basic Research Program: ‘‘Water environmental quality evolution and water quality criteria in lakes’’ (2008CB418201). Appendix A. Supplementary material Supplementary data associated with this article can be found, in the online version, at http://dx.doi.org/10.1016/j.chemosphere. 2012.03.103.
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