The aquatic environments of the Pearl River Delta (PRD) in China have been contaminated by various industrial chemicals from local industries. In this study, the spatial–temporal distribution of six priority phthalate esters (PAEs) in surface water and sediments from the PRD was investigated. The PAEs were detected with total concentrations (Σ6PAEs) ranging from 0.35 to 20.70 μg L−1 in surface water and dry weight ranging from 0.88 to 5.69 μg g−1 in sediments. The Σ6PAEs concentrations in surface water were higher in the wet season than those in the dry season, while the opposite pattern was observed in sediments. Di(2-ethylhexyl) phthalate (DEHP) was the most abundant congener, which was higher than those reported in the literature. Risk quotients for relevant aquatic organisms were obtained and showed that most of these PAEs, in particular, butyl benzyl phthalate, DEHP and di-n-octyl phthalate, have significant potential health and ecological risks for the aquatic environment studied.

INTRODUCTION

Phthalate esters (PAEs) are a class of synthetic organic chemicals. The lower molecular weight PAEs are typically used in cosmetics and personal care products, while longer/branching alkyl chain PAEs are widely used as plasticizers in polyvinyl chloride (PVC) plastics. Since PAEs are not covalently bonded to the polymeric matrix, they are easily discharged into the environment during the process of plastic aging and decomposition (Dargnat et al. 2009). The occurrence of PAEs has been detected in atmosphere (Pei et al. 2013), surface water (Mackintosh et al. 2006; Bergé et al. 2013) and sediment (Liu et al. 2010; Liu et al. 2014) in many regions around the world. Most of the PAEs are known to bioaccumulate in aquatic organisms and produce endocrine-disrupting effects (Horn et al. 2004). Studies showed that PAEs and their metabolites produced reproductive and developmental toxicities (Ema et al. 2007; Gray et al. 2000). Recently, other studies demonstrated that dimethyl phthalate (DMP), diethyl phthalate (DEP) and dioctyl phthalate (DOP) inhibited the soil microbial urease activity (Chen et al. 2013). In addition, dibutyl phthalate (DBP) and DEP have demonstrated potential neurotoxicity in zebra fish embryos via inhibiting acetylcholinesterase activity (Xu et al. 2013a). Therefore, potential health risks of PAEs are of great concern because human beings are inevitably exposed to PAEs from consumption of contaminated surface water and aquatic organisms. Considering the health risks, the United States Environmental Protection Agency and the Chinese Environmental Agency have defined DMP, DEP, DBP, butyl benzyl phthalate (BBP), di-(2-ethylhexyl) phthalate (DEHP) and DOP as priority pollutants. The Pearl River Delta (PRD) region is one of the largest economic centers of China. Rapid industrial developments in recent decades have resulted in serious environmental pollutions in the region. Several studies reported that the PRD region had been polluted with aromatic hydrocarbons (Zhang et al. 2013), organochlorine pesticides (Yu et al. 2013) and polybrominated diphenyl ethers (Chen et al. 2013b). In this paper, the spatial–temporal distributions of the six priority PAEs were studied in surface water and sediments from seven riverine outlets of the PRD. A preliminary risk assessment was also carried out to assess the potential environmental risks involving a broad range of aquatic vertebrate and invertebrate species.

MATERIALS AND METHODS

The standard mixtures containing DMP, DEP, DBP, BBP, DEHP and di-n-octyl phthalate (DnOP) in isooctane at 1,000 mg L−1 each, a surrogate standard solution containing three standards (diisophenyl phthalate, di-n-phenyl phthalate and di-n-benzyl phthalate) and an internal standard (benzyl benzoate) in acetone at 500 mg L−1 each were supplied by Dr Ehrenstorfer GmbH (Germany). The stock solutions of the six phthalate mixtures were prepared in n-hexane of 100 mg L−1. Calibration standard solutions with concentrations of 0.5, 1, 5, 10, 20, 30, 40 and 50 mg L−1 were prepared by diluting the stock standard solution with n-hexane. Stock and calibration standard solutions were stored at 4 °C in a refrigerator. The calibration curve established for each PAE, and calibration solutions were replaced every month. Water and sediment samples were collected at seven riverine outlets of the PRD during January 2013 and April 2013, which were representative months for the dry season and the wet season, respectively. The seven outlet locations were recorded by GPS and are shown in Figure 1. Surface water taken from the top layer (0–50 cm) was collected with a 5 L pre-cleaned stainless steel barrel and stored in pre-cleaned 10 L brown glass containers. Sediment samples were taken using a gravity corer and sliced at 5–10 cm intervals then collected into pre-cleaned aluminum foil envelopes. All sampling was conducted in triplicate during the ebb tide in order to avoid tidal influences.

Figure 1

Map of sampling site locations in Pearl River Delta in China.

Figure 1

Map of sampling site locations in Pearl River Delta in China.

The methods for sample pre-treatment and analytical procedures of water and sediment samples were adapted from the literature with slight modifications (Zeng et al. 2008; Liu et al. 2010). One-litre water samples were filtered through glass fiber filters (Whatman GF/F, 0.45 μm pore sizes), spiked with 20 μL of the surrogate standards stock solution and serially extracted with 40, 40 and 30 mL of dichloromethane in a separatory funnel. The extract was dried with anhydrous sodium sulfate, collected in a Bunsen flask and reduced to approximately 2.0 mL using a rotary evaporator. Sediment samples were air-dried, ground and homogenized. Sediment samples of 20 g were spiked with 20 μL of 100 mg L−1 surrogate standards and extracted with 40 mL of acetone/n-hexane (1:1, v:v) in a conical flask for 30 min. Activated copper granules were added to the extraction flasks during the extraction to remove elemental sulfur. Then merged extracts were filtered and the sediment samples were extracted for another two times. The merged extracts were transferred to a Bunsen flask and reduced to nearly dry, then 10 mL of n-hexane was added to exchange solvent and further reduced to approximately 2.0 mL using a rotary evaporator; then the extracts were cleaned and fractionated on a 10-mm i.d. silica gel glass column packed, from the bottom to top, with anhydrous sodium sulfate (1 cm), 10 g neutral silica gel and anhydrous sodium sulfate (1 cm). The concentrated extracts were added into the column and washed with 40 mL of n-hexane, velocity control at 2 mL min–1. Then PAEs were eluted with 80 mL of mixed solvent of diethyl ether/n-hexane (3:7, v:v). The extracts were concentrated using a rotary evaporator, and reduced to 0.1 mL under a stream of pure N2. Determined quantities of internal standard were added to the sample prior to gas chromatography–mass spectrometry analysis. Analyses of the samples were conducted in triplicate. Quality control and quality assurance were conducted in the experiments. For each set of sample analyzed, a procedural blank, a spiked blank, a matrix-spiked, a sample duplicate and a solvent blank were processed every 10 field samples. Only a few PAEs were detected in the blanks: they were DBP (0.02 μg) and DEHP (0.04 μg) and all the reported concentrations were corrected for the blank values. The surrogate recoveries in all samples were within acceptable limits. Recoveries of six PAEs ranged from 76.3 to 106% and the relative standard deviations were all below 10.7%. The limit of detection was determined as signal-to-noise ratio of 3:1, which was 0.010 μg/L for water and 0.008 μg/g for sediment samples. The potential environmental risks of PAEs were assessed based on risk quotients (RQs) according to the European technical guidance document on risk assessment (EC 2003). The RQ values were calculated through the measured environmental concentration divided by the predicted no-observed-effect concentrations (PNECs). For the determination of PNECs, EC50 (half maximal effect concentration) or NOEC (no observed effect concentration) values for the most sensitive aquatic species were divided by an assessment factor (EC 2003; Gros et al. 2010). The selection of EC50 or NOEC values and assessment factor was made from the US EPA ECOTOX database (http://cfpub.epa.gov/ecotox/). A search for the most sensitive aquatic species was performed in the literature (Xu et al. 2013b). It should be mentioned that the lowest EC50 or NOEC values were selected. To better illustrate the risk level, the ratios were classified into three risk levels: 0.1–1, low risk; 1–10, medium risk; >10, high risk (Cristale et al. 2013).

RESULTS AND DISCUSSION

The individual and total concentrations of six PAEs in surface water are shown in Table 1. All six PAEs were found in surface water, indicating their widespread presence in the PRD region. Total PAEs' concentrations (Σ6PAEs) ranged from 2.69 to 20.70 μg L−1 with an average of 7.60 μg L−1 in the wet season, and from 0.35 to 5.03 μg L−1 with an average of 1.99 μg L−1 in the dry season. The mean levels of total PAEs in the two seasons were obviously lower than the concentration found in the Ogun river, Nigeria (Adeniyi et al. 2011) and similar to those in the False Creek Harbor, Canada (Mackintosh et al. 2006). Figure 2 shows the concentration of total PAEs in each sampling site during the wet and dry seasons. The highest concentration was found at S2 (20.7 μg L−1) in the wet season and at S1 (5.03 μg L−1) in the dry season. This might be due to the larger past usage and continuous release of PAEs in this area, surrounded by the Pearl River Power Station and a number of dyeing and leather factories. Other high concentrations were found at S5 (9.72 μg L−1) and S7 (8.75 μg L−1), located at downstream of Zhongshan, which is a densely populated commercial city. A relatively lower concentration was found at S4 (0.46 μg L−1), located at downstream of the Nansha scenic region, which received less domestic and industrial wastewater discharge compared to other sites. In general, concentrations of PAEs in surface water in the wet season were higher than those in the dry season. This might be due to the urban storm water runoff and atmospheric wet deposition in study region. Amongst the six PAEs analyzed, DMP, BBP, DEHP and DnOP were ubiquitously present in the wet season, while only DBP and DEHP were detected in the dry season. DEHP was the most abundant PAE in the surface water, with the concentrations ranging from 1.08 to 8.84 μg L−1 in the wet season and from 0.15 to 1.36 μg L−1 in the dry season. In the wet season, the concentration of DEHP at S2 was higher than that of the highest concentration (6.00 μg L−1) in the Safe Drinking Water Act. The concentrations of DEHP in the surface water was higher than those in the Yangtze River, China, with the concentration ranging from 0.010 to 0.836 μg L−1 (He et al. 2011) and the Seine River estuary, France, with the concentration ranging from 0.160 to 0.314 μg L−1 (Dargnat et al. 2009), indicative of the extensive use in plastic industries in the study area. The Σ6PAEs in surface water were higher than those in the Yangtze River in Jiangsu Province, China, where the concentration ranged from 0.178 to 1.474 μg L−1 (He et al. 2011), but lower than those in the Yellow River, China, where the concentration ranged from 3.99 to 45.45 μg L−1 (Xia et al. 2007).

Table 1

Summary of PAE concentrations in surface water of seven riverine outlets of Pearl River Delta in China (μg L−1)

  DMP DEP DBP BBP DEHP DnOP Σ6PAEs 
Wet season (n = 7) 
Sites S1 0.07 0.02 0.13 1.24 1.79 0.08 3.35 
S2 0.14 0.95 1.14 5.32 8.84 4.30 20.7 
S3 0.07 0.02 0.10 1.28 2.53 0.30 4.29 
S4 0.04 0.01 0.09 0.79 1.08 0.77 2.78 
S5 0.06 n.d. 2.04 2.75 4.14 0.73 9.72 
S6 0.05 0.02 0.53 1.27 1.41 0.59 3.86 
S7 0.06 0.02 n.d. 2.45 5.46 0.76 8.82 
Range  0.04–0.14 n.d.–0.95 n.d.–2.04 0.79–5.32 1.08–8.84 0.08–4.30 2.78–20.7 
Mean  0.07 0.15 0.55 2.16 3.61 1.07 7.60 
DF  100 85.7 57.1 100 100 100 100 
Dry season (n = 7) 
Sites S1 3.39 0.43 1.01 n.d. 0.20 n.d. 5.03 
S2 0.58 0.38 0.84 0.80 1.36 0.13 4.08 
S3 0.20 n.d. 0.19 0.08 0.15 0.02 0.64 
S4 0.08 0.09 0.04 0.10 0.23 n.d. 0.53 
S5 0.15 0.01 0.05 n.d. 0.28 0.02 0.50 
S6 n.d. 0.13 0.31 0.14 0.93 0.01 1.53 
S7 0.09 0.49 0.35 0.23 0.86 0.02 2.05 
Range  n.d.–3.39 n.d.–0.49 0.04–1.01 n.d.–0.80 0.15–1.36 n.d.–0.13 0.50–5.03 
Mean  0.57 0.22 0.41 0.19 0.57 0.03 1.99 
DF  57.1 85.7 100 71.4 100 71.4 100 
Whole year (n = 14) 
Range  n.d.–3.39 n.d.–0.95 n.d.–2.04 n.d.–5.32 0.15–8.84 n.d.–4.30 0.50–20.7 
Mean  0.32 0.18 0.48 1.18 2.09 0.55 4.80 
DF  78.6 85.7 78.6 85.7 100 85.7 100 
  DMP DEP DBP BBP DEHP DnOP Σ6PAEs 
Wet season (n = 7) 
Sites S1 0.07 0.02 0.13 1.24 1.79 0.08 3.35 
S2 0.14 0.95 1.14 5.32 8.84 4.30 20.7 
S3 0.07 0.02 0.10 1.28 2.53 0.30 4.29 
S4 0.04 0.01 0.09 0.79 1.08 0.77 2.78 
S5 0.06 n.d. 2.04 2.75 4.14 0.73 9.72 
S6 0.05 0.02 0.53 1.27 1.41 0.59 3.86 
S7 0.06 0.02 n.d. 2.45 5.46 0.76 8.82 
Range  0.04–0.14 n.d.–0.95 n.d.–2.04 0.79–5.32 1.08–8.84 0.08–4.30 2.78–20.7 
Mean  0.07 0.15 0.55 2.16 3.61 1.07 7.60 
DF  100 85.7 57.1 100 100 100 100 
Dry season (n = 7) 
Sites S1 3.39 0.43 1.01 n.d. 0.20 n.d. 5.03 
S2 0.58 0.38 0.84 0.80 1.36 0.13 4.08 
S3 0.20 n.d. 0.19 0.08 0.15 0.02 0.64 
S4 0.08 0.09 0.04 0.10 0.23 n.d. 0.53 
S5 0.15 0.01 0.05 n.d. 0.28 0.02 0.50 
S6 n.d. 0.13 0.31 0.14 0.93 0.01 1.53 
S7 0.09 0.49 0.35 0.23 0.86 0.02 2.05 
Range  n.d.–3.39 n.d.–0.49 0.04–1.01 n.d.–0.80 0.15–1.36 n.d.–0.13 0.50–5.03 
Mean  0.57 0.22 0.41 0.19 0.57 0.03 1.99 
DF  57.1 85.7 100 71.4 100 71.4 100 
Whole year (n = 14) 
Range  n.d.–3.39 n.d.–0.95 n.d.–2.04 n.d.–5.32 0.15–8.84 n.d.–4.30 0.50–20.7 
Mean  0.32 0.18 0.48 1.18 2.09 0.55 4.80 
DF  78.6 85.7 78.6 85.7 100 85.7 100 

n.d.: concentration was lower than the method detection limit; DF: detected frequency (%).

Figure 2

The Σ6PAEs concentrations in surface water from seven riverine outlets during wet and dry seasons.

Figure 2

The Σ6PAEs concentrations in surface water from seven riverine outlets during wet and dry seasons.

It was documented that riverine runoff was the most important contributor of contaminants transported from terrestrial sources into the coastal regions (Xu et al. 2013b). The potential environmental risk assessment for water was assessed with RQs, and the PNEC (predicted no effect concentration) values were calculated from the chronic toxicity data and are shown in Table 2. Figure 3 shows the calculated RQs of the six PAEs in the seven riverine outlets. Generally, RQs were higher in the wet season than dry season. Among the six PAEs analyzed, RQs of BBP, DEHP and DnOP were higher than that of DMP, DEP and DBP, indicating that the concentration of BBP, DEHP and DnOP posed higher toxicity to embryo development to the selected aquatic organisms (Haliotis diversicolor spp. supertexta). Especially, DEHP showed relatively higher chronic toxicity to the aquatic organisms (Daphnia magna). Among the seven outlets, BBP, DEHP and DnOP showed a high risk at S2 in the wet season with RQ > 10 (mean). BBP, DEHP and DnOP also showed at least a low potential environmental risk to the aquatic organisms (D. magna) in other sites with low RQs. DBP showed a low potential risk at S1 in the dry season and at S2 and S5 in the wet season. The RQ values for DMP and DEP were almost all less than 0.1 for both sites, suggesting that these compounds were unlikely to cause any adverse toxic effects (reproductive, developmental toxicities and neurotoxicity) on the aquatic organisms such as D. magna and Lepomis macrochirus.

Table 2

Aquatic toxicity data of six PAEs for the most sensitive aquatic species

Compound Standard test species Toxicity data (μg L−1Toxicity Assessment factor PNECa (μg L−1Reference 
DMP Crustaceans Daphnia magna 48 h, mortality, NOECb = 1700 Chronic 100 17 Leblanc (1980)  
DEP Fish Lepomis macrochirus 96 h, mortality, NOEC = 1650 Chronic 100 16.5 Adams (1995)  
DBP Fish Danio rerio (Zebra Danio) 10 d, mortality, NOEC = 100 Chronic 100 Ortiz-Zarragoitia (2006)  
BBP Alga Skeletonema costatum 96 h, population, NOEC = 30 Chronic 100 0.3 Syracuse Research Corp (2000)  
DEHP Crustaceans Daphnia magna 21 d, mortality, EC50 = 77 Chronic 1,000 0.77 Rhodes (1995)  
DnOP Molluscs Haliotis diversicolor spp. supertexta 96 h, development, NOEC = 17.9 Chronic 100 0.179 Liu (2009)  
Compound Standard test species Toxicity data (μg L−1Toxicity Assessment factor PNECa (μg L−1Reference 
DMP Crustaceans Daphnia magna 48 h, mortality, NOECb = 1700 Chronic 100 17 Leblanc (1980)  
DEP Fish Lepomis macrochirus 96 h, mortality, NOEC = 1650 Chronic 100 16.5 Adams (1995)  
DBP Fish Danio rerio (Zebra Danio) 10 d, mortality, NOEC = 100 Chronic 100 Ortiz-Zarragoitia (2006)  
BBP Alga Skeletonema costatum 96 h, population, NOEC = 30 Chronic 100 0.3 Syracuse Research Corp (2000)  
DEHP Crustaceans Daphnia magna 21 d, mortality, EC50 = 77 Chronic 1,000 0.77 Rhodes (1995)  
DnOP Molluscs Haliotis diversicolor spp. supertexta 96 h, development, NOEC = 17.9 Chronic 100 0.179 Liu (2009)  

aPNEC: predicted no effect concentration; bNOEC: no observable effect concentration.

Figure 3

Figure based on the calculated risk quotients (RQs) for the six PAEs detected in surface water from seven riverine outlets (D and W represent the dry season and the wet season, respectively).

Figure 3

Figure based on the calculated risk quotients (RQs) for the six PAEs detected in surface water from seven riverine outlets (D and W represent the dry season and the wet season, respectively).

Table 3 shows the detected concentrations of six PAEs in sediments. The results showed that Σ6PAEs concentrations ranged from 0.88 to 5.69 μg g−1 (dry weight (dw)) with an average of 1.82 μg g−1 (dw) in the wet season, and from 1.60 to 4.62 μg g−1 (dw) with an average of 2.97 μg g−1 (dw) in the dry season. In general, Σ6PAEs concentrations in the dry season (January 2013) were higher than those in the wet season (April 2013), which might be attributed to the fact that the water temperature in January was lower than that in April and reduced the biodegradation of the compounds in the PRD region (Liu et al. 2010). The concentrations were similar to those present in Brandenburg and Berlin, Germany (Fromme et al. 2002), False Creek Harbor, Canada (Mackintosh et al. 2006) and Ogun River, Nigeria (Adeniyi et al. 2011). The levels of Σ6PAEs concentration were lower than those detected in rivers of Taiwan (Chang et al. 2002) and the Yellow River, China (Xia et al. 2007). The individual PAEs' composition and concentrations showed that DBP, DEHP and DnOP were the pre-dominant PAEs in sediments. Our study demonstrated that DnBP/DiBP and DEHP were the predominant PAE congeners in an urban lake sediment environment around Guangzhou, which is consistent with a previous study (Zeng et al. 2008). The congener composition also showed that DEHP was the most abundant compound in sediment, because of the mass usage of DEHP by the plastic industry (Gómez-Hens 2003). Another reason was slow degradation of DEHP in the sediment and its tendency to be adsorbed on particulate and dissolved matter in conditions of low flow velocity (Sun et al. 2013). Similar patterns were found in Gomti River, India (Mathur et al. 2010). The concentrations of DBP were similar to those measured in other regions of the world, except for the high concentration of DiBP in Guangzhou (Zeng et al. 2008), DnBP in Taiwan (Chang et al. 2002) and Yellow River in China (Xia et al. 2007). The PAE concentrations in sediment were lower than those in Guangzhou, which ranged from 2.27 to 74.94 μg g−1 (Zeng et al. 2008), and in the PRD region, which ranged from 0.567 to 47.3 μg g−1 (Liu et al. 2014).

Table 3

Summary of PAE concentrations in sediments of seven riverine outlets of Pearl River Delta in China

PAEs Total (μg L−1, n = 50) Wet season (μg g−1, n = 27) Dry season (μg g−1, n = 23) 
Mean Min Max Detection frequency (%) Mean Min Max Detection frequency (%) Mean Min Max Detection frequency (%) 
DMP 0.38 n.d. 1.75 60.0 0.03 n.d. 0.22 25.9 0.78 0.09 1.75 60.9 
DEP 0.06 n.d. 0.18 76.0 0.05 n.d. 0.18 55.6 0.06 0.02 0.17 65.2 
DBP 0.59 0.15 2.50 100 0.53 0.15 2.50 100 0.65 0.28 1.16 100 
BBP 0.03 n.d. 0.16 88.0 0.01 n.d. 0.12 77.8 0.04 0.01 0.16 78.3 
DEHP 1.22 0.47 2.72 100 1.15 0.47 2.72 100 1.30 0.81 2.11 100 
DnOP 0.09 0.01 0.31 100 0.05 0.01 0.31 100 0.13 0.04 0.23 100 
Σ6PAEs 2.35 0.88 5.69 100 1.82 0.88 5.69 100 2.97 1.60 4.62 100 
PAEs Total (μg L−1, n = 50) Wet season (μg g−1, n = 27) Dry season (μg g−1, n = 23) 
Mean Min Max Detection frequency (%) Mean Min Max Detection frequency (%) Mean Min Max Detection frequency (%) 
DMP 0.38 n.d. 1.75 60.0 0.03 n.d. 0.22 25.9 0.78 0.09 1.75 60.9 
DEP 0.06 n.d. 0.18 76.0 0.05 n.d. 0.18 55.6 0.06 0.02 0.17 65.2 
DBP 0.59 0.15 2.50 100 0.53 0.15 2.50 100 0.65 0.28 1.16 100 
BBP 0.03 n.d. 0.16 88.0 0.01 n.d. 0.12 77.8 0.04 0.01 0.16 78.3 
DEHP 1.22 0.47 2.72 100 1.15 0.47 2.72 100 1.30 0.81 2.11 100 
DnOP 0.09 0.01 0.31 100 0.05 0.01 0.31 100 0.13 0.04 0.23 100 
Σ6PAEs 2.35 0.88 5.69 100 1.82 0.88 5.69 100 2.97 1.60 4.62 100 

n.d.: concentration was lower than the method detection limit.

Table 4 shows the PAE concentrations at different depths of sediment in the wet season. In the first layer (0–5 cm), the Σ6PAEs concentration ranged from 1.17 to 5.69 μg g−1. The highest concentrations were found at the site S4, while the Σ6PAEs concentration was the lowest in surface water at the site S4 in the wet season. This result might be due to the partitioning behavior of PAEs among the water and sediment during the attenuation/exchange processes of the daily tides from the Pearl River (Zeng et al. 2008; Shi et al. 2007). In the second layer (10–15 cm), the Σ6PAEs concentration ranged from 0.98 to 3.50 μg g−1. The highest value was found at the site S4. The site S6 exhibited a higher total concentration because of the high levels of DBP and DEHP, which might have been due to the fact that these PAEs move downward from the surface through some small holes in the sediment or come from the horizontal transport with groundwater (Liu et al. 2010). In the third (20–25 cm) and fourth (30–35 cm) layers, the Σ6PAEs concentrations ranged from 0.91 to 2.05 μg g−1 and from 0.88 to 2.18 μg g−1, respectively, which were similar to those in the second layer. This result implied that a low percentage of PAEs migrated down to the deeper layers or were involved in the downward transport process. This seemed to be in agreement with another study on alluvial sediment in Jianghan Plain (Liu et al. 2010).

Table 4

The PAE concentrations in different depths of sediment in the wet season (μg g−1, dw)

Site Depth/cm DMP DEP DBP BBP DEHP DnOP Σ6PAEs 
S1 0–5 n.d. 0.18 0.26 n.d. 0.76 0.024 1.22 
10–15 n.d. 0.18 0.30 n.d. 0.59 0.014 1.08 
20–25 n.d. 0.18 0.26 n.d. 0.80 0.013 1.25 
30–35 n.d. 0.18 0.25 n.d. 0.83 0.013 1.27 
S2 0–5 0.010 n.d. 0.47 0.12 0.58 0.048 1.22 
10–15 n.d. n.d. 0.40 0.007 0.56 0.023 0.98 
20–25 n.d. n.d. 0.39 0.005 0.50 0.012 0.91 
30–35 n.d. n.d. 0.39 0.005 0.47 0.009 0.88 
S3 0–5 0.006 0.045 0.31 0.038 2.57 0.13 3.09 
10–15 n.d. 0.064 0.31 0.026 2.07 0.12 2.59 
20–25 n.d. 0.046 0.20 0.011 1.71 0.085 2.05 
30–35 n.d. n.d. 0.15 0.023 1.94 0.073 2.18 
S4 0–5 n.d. 0.166 2.50 n.d. 2.72 0.31 5.69 
10–15 n.d. 0.088 1.18 n.d. 2.08 0.15 3.50 
20–25 n.d. 0.032 0.52 0.001 0.74 0.058 1.35 
30–35 n.d. 0.031 0.32 0.006 1.55 0.071 1.97 
S5 0–5 0.16 n.d. 0.95 0.003 1.04 0.061 2.21 
10–15 0.053 n.d. 0.80 0.004 0.81 0.026 1.70 
20–25 0.025 n.d. 0.53 0.002 0.92 0.031 1.51 
30–35 n.d. n.d. 0.43 0.005 0.85 0.024 1.32 
S6 0–5 0.061 0.008 0.35 0.007 1.06 0.015 1.50 
10–15 0.22 0.038 0.55 n.d. 2.36 0.036 3.20 
20–25 0.13 0.007 0.38 0.004 1.11 0.021 1.65 
30–35 0.081 0.007 0.37 0.004 0.89 0.014 1.36 
S7 0–5 0.068 n.d. 0.61 0.009 0.54 0.012 1.23 
10–15 0.054 n.d. 0.73 0.011 0.62 0.014 1.43 
20–25 0.022 n.d. 0.51 0.006 0.50 0.01 1.05 
Site Depth/cm DMP DEP DBP BBP DEHP DnOP Σ6PAEs 
S1 0–5 n.d. 0.18 0.26 n.d. 0.76 0.024 1.22 
10–15 n.d. 0.18 0.30 n.d. 0.59 0.014 1.08 
20–25 n.d. 0.18 0.26 n.d. 0.80 0.013 1.25 
30–35 n.d. 0.18 0.25 n.d. 0.83 0.013 1.27 
S2 0–5 0.010 n.d. 0.47 0.12 0.58 0.048 1.22 
10–15 n.d. n.d. 0.40 0.007 0.56 0.023 0.98 
20–25 n.d. n.d. 0.39 0.005 0.50 0.012 0.91 
30–35 n.d. n.d. 0.39 0.005 0.47 0.009 0.88 
S3 0–5 0.006 0.045 0.31 0.038 2.57 0.13 3.09 
10–15 n.d. 0.064 0.31 0.026 2.07 0.12 2.59 
20–25 n.d. 0.046 0.20 0.011 1.71 0.085 2.05 
30–35 n.d. n.d. 0.15 0.023 1.94 0.073 2.18 
S4 0–5 n.d. 0.166 2.50 n.d. 2.72 0.31 5.69 
10–15 n.d. 0.088 1.18 n.d. 2.08 0.15 3.50 
20–25 n.d. 0.032 0.52 0.001 0.74 0.058 1.35 
30–35 n.d. 0.031 0.32 0.006 1.55 0.071 1.97 
S5 0–5 0.16 n.d. 0.95 0.003 1.04 0.061 2.21 
10–15 0.053 n.d. 0.80 0.004 0.81 0.026 1.70 
20–25 0.025 n.d. 0.53 0.002 0.92 0.031 1.51 
30–35 n.d. n.d. 0.43 0.005 0.85 0.024 1.32 
S6 0–5 0.061 0.008 0.35 0.007 1.06 0.015 1.50 
10–15 0.22 0.038 0.55 n.d. 2.36 0.036 3.20 
20–25 0.13 0.007 0.38 0.004 1.11 0.021 1.65 
30–35 0.081 0.007 0.37 0.004 0.89 0.014 1.36 
S7 0–5 0.068 n.d. 0.61 0.009 0.54 0.012 1.23 
10–15 0.054 n.d. 0.73 0.011 0.62 0.014 1.43 
20–25 0.022 n.d. 0.51 0.006 0.50 0.01 1.05 

n.d.: not detected (below the detection limit).

CONCLUSIONS

This work investigated the occurrence and spatial–temporal distribution of six priority PAEs in surface water and sediments from seven riverine outlets of the PRD in Southern China. All PAEs were detected in surface water and sediments. The total concentration of the six PAE congeners (Σ6PAE) in the surface water ranged from 0.35 to 20.7 μg L−1 and in the sediments ranged from 0.88 to 5.69 μg g−1 (dw), respectively. Temporal variations showed that in surface water, the Σ6PAEs concentrations in the wet season were higher than those in the dry season, while the opposite pattern was observed in sediment. Concentration and composition analysis showed that the DEHP was the dominant variety in all PAEs in the PRD regions, which was related to the extensive use of plastic materials in the PRD regions. Vertical distribution of PAEs in sediments indicated that a small fraction of PAEs moved downwards with the surface water. Preliminary risk assessment using RQs indicated that most of the PAEs in the riverine sites showed relatively high potential environmental risk to the relevant aquatic organisms.

ACKNOWLEDGEMENTS

This research was jointly supported by the National Natural Science Foundation of China – Guangdong (U1133003) and the National Natural Science Foundation of China (41076068).

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