Occurrence, distribution, and sources of emerging organic contaminants in tropical coastal sediments of anthropogenically impacted Klang River estuary, Malaysia

Marine Pollution Bulletin 131 (2018) 284–293

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Baseline

Occurrence, distribution, and sources of emerging organic contaminants in tropical coastal sediments of anthropogenically impacted Klang River estuary, Malaysia

T

⁎

Tuan Fauzan Tuan Omara, Ahmad Zaharin Arisa,c, , Fatimah Md. Yusoffb, Shuhaimi Mustafac a

Department of Environmental Sciences, Faculty of Environmental Studies, Universiti Putra Malaysia, 43400 UPM Serdang, Selangor, Malaysia Laboratory of Marine Biotechnology, Institute of Bioscience, Universiti Putra Malaysia, 43400 UPM Serdang, Selangor, Malaysia c Laboratory of Halal Science Research, Halal Product Research Institute, Universiti Putra Malaysia, 43400 UPM Serdang, Selangor, Malaysia b

A R T I C LE I N FO

A B S T R A C T

Keywords: Emerging organic contaminant Klang River estuary, Malaysia Tropical estuarine sediment Endocrine-disrupting compound Baseline

This baseline assessment reports on the occurrence, distribution, and sources of emerging organic contaminants (EOCs) in tropical coastal sediments of anthropogenically impacted Klang River estuary, Malaysia. Bisphenol A was the highest concentration detected at 16.84 ng g−1 dry weight, followed by diclofenac (13.88 ng g−1 dry weight) and E1 (12.47 ng g−1 dry weight). Five compounds, namely, amoxicillin, progesterone, diazinon, bisphenol A, and E1, were found in all sampling stations assessed, and other compounds such as primidone, diclofenac, testosterone, E2, and EE2 were ubiquitously present in sediment samples, with percentage of detection range from 89.04% to 98.38%. Organic carbon content and pH were the important factors controlling the fate of targeted compounds in the tropical estuarine sediment. On the basis of the literature from other studies, the sources of EOCs are thought to be from wastewater treatment plants, domestic/medical waste discharge, livestock activities, industrial waste discharge, and agricultural activities.

Urbanization and industrialization along river basins have become a significant threat to the coastal and estuarine ecosystems. These anthropogenic activities have resulted in increasing pollution load in various environmental compartments within the coastal ecosystem. One of the important compartments of the coastal ecosystem is the sediment matrix, which is regarded as a sink for various types of chemical pollution. Chemical contaminants, particularly emerging organic pollutants, have been detected in estuarine sediments at trace concentrations (Omar et al., 2017). These types of chemical pollutants consisted of endocrine-disrupting compounds (EDCs) as well as various classes of organic micro-pollutants such as pharmaceuticals and personal care products, pesticides, estrogenic hormones, polyaromatic hydrocarbon, dioxins, and polychlorinated compounds. The presence of EDCs in the environmental compartment has been the main concern since the last few decades because of their potential human and environmental risks. Several human illnesses such as prostate and breast cancer, decreased or increased in thyroid activity, alteration in male and female reproduction systems, and changes in neuroendocrinology have been linked with EDC contaminants (Fowler et al., 2012; Bergman et al., 2013; Sifakis et al., 2017). Previous studies also reported on the potency of EDC accumulation in aquatic organisms because of sediment contamination (Salgueiro-González et al., 2015; de Castro-Català et al., ⁎

Corresponding author. E-mail address: [email protected] (A.Z. Aris).

https://doi.org/10.1016/j.marpolbul.2018.04.019 Received 10 August 2017; Received in revised form 1 April 2018; Accepted 10 April 2018 0025-326X/ © 2018 Elsevier Ltd. All rights reserved.

2016; Casatta et al., 2016; Liu et al., 2017). In addition, several studies showed that the elevated concentrations of EDCs in environmental samples were found to cause intersex changes in fish (Aris et al., 2014; Zheng et al., 2015; Adeogun et al., 2016), which might result in the possible reduction of fish species in the ecosystem. The estuary area is an important economic zone where most of the major commercial ports are situated at this heavily urbanized and industrialized area. One of the largest and busiest ports in peninsular Malaysia is Port Klang. Port Klang is comprised of three ports (Westport, Northport, and Southport) and surrounded by various industrial establishments within the area (Fig. 1). It is located at the estuary of Klang and Langat rivers, the two main rivers in Greater Kuala Lumpur and Klang Valley (GKL & KV). These rivers flow through urbanized and populated cities such as Kuala Lumpur (capital city of Malaysia), Shah Alam (capital state of Selangor), and Petaling Jaya (industrial and commercial activities), which increases the potential for discharge of various emerging organic pollutants in the Klang River estuary ecosystem. The estuary is also surrounded by several industrial zones such as Pandamaran Industrial Park, Pulau Indah Industrial Park, Westport Industrial Estate, and Teluk Gong Industrial Park. Meanwhile, land use encircling the estuary is mainly for residential, industrial, plantation, and commercial activities. Besides various industrial and

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Fig. 1. Map shows (a) peninsular Malaysia and (b) sampling points at Klang River estuary.

commercial activities, the estuary is a well-known spot for fishing activities for local population and also home for various aquatic animals such as fish, mollusks, cockles, and mussels. Previous studies on the assessment of chemical pollution in the sediment of Klang River estuary mostly focused on metal contamination (Naji and Ismail, 2012; Sany et al., 2013; Haris and Aris, 2015). It is noted that there are few data on the concentrations of emerging organic contaminants (EOCs) in the sediment of Klang River estuary. Therefore,

the objectives of the present study are (i) to assess the concentration of selected EOCs in the collected sediment samples, (ii) to evaluate the distribution pattern of EOCs in the sediment samples, and (iii) to identify the potential sources of EOC contamination in the sediment of Klang River estuary. Sixteen multi-class EOCs consist of pharmaceuticals (dexamethasone, primidone, sulfamethoxazole, diclofenac, amoxicillin, testosterone, and progesterone), steroid hormones (17βestradiol (E2), 17α-ethynyl estradiol (EE2), and estrone (E1)),

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pesticides (diazinon, quinalphos, and chlorpyrifos), and phenolic xenoestrogens (bisphenol A (BPA), 4-nonylphenol (4-NP), and 4-octylphenol (4-OP)) were evaluated. This study will be the first to provide a baseline concentration of different multi-class emerging organic contaminants in the sediments of Klang River estuary, a tropical regional setting, as well as to establish EOC contamination profiles for this estuarine area. An Ekman grab sampler was used to collect surface sediment samples (0–10 cm) from 12 sampling points along Klang River estuary (Fig. 1). The sediment samples were homogenized in a stainless steel tray and transferred using stainless steel scoop into pre-cleaned methanol-rinsed ambient glass bottles, kept in ice box, and transported to the laboratory at 4 °C. Upon arriving at the laboratory, the samples were air dried until constant weight, followed by sieving through < 125 μm sieve. Portions of the sieved sediment samples were analyzed for physico-chemical parameters such as pH, particle size analysis, and organic carbon content. Particle size analysis was performed using the pipette method as described by Teh and Talib (2006), and organic carbon was analyzed using Total Carbon Analyzer (TOC-VCSH, Shimadzu, Japan). The sediment samples for EOC determination were kept in a freezer at −20 °C until further analysis. Extraction of sediment samples was carried out following the method described in Omar et al. (2017). Briefly, sediment samples (5.000 g ± 0.001) were weighed, mixed with aluminum oxide (Al2O3) and hydromatrix, and subsequently ground with a mortar into finely divided solid particles. Samples were then transferred into a cellulose extraction thimble, spiked with deuterated labeled surrogate standard, and Soxhlet-extracted for 8 h with 200 mL mixture of MeOH:acetone (50:50) as the extraction solvent. After extraction, samples were reduced to approximately 1–2 mL using a rotary evaporator and reconstituted with ultrapure water:acetonitrile (90:10) to 15–20 mL prior to solid phase extraction (SPE). Solid phase extraction clean-up was carried out using Strata-X polymeric reversed-phase C18 cartridges based on optimized SPE protocol as described in detail by Omar et al. (2017). After SPE clean-up, the extracts were reduced to approximately 1–2 mL by a rotary evaporator and then further concentrated to near dryness under a gentle stream of nitrogen. The extracts were than reconstituted with ultrapure water:acetonitrile (70:30) to a final volume of 1 mL. The final extracts were filtered with a 0.20 μm PTFE membrane filter (Agilent Technologies, USA) before being introduced for LC MS-MS analysis. Quality assurance and quality control protocols were employed throughout the analytical procedure. Before every usage, the apparatus and glassware were thoroughly washed with laboratory detergent (Decon 90), subsequently washed with deionized water, and rinsed with organic solvent, followed by drying in an oven at a temperature of 90 °C. High-grade chemicals and solvents (HPLC grade) were used for sample preparation, and an LC MS grade solvent was used for preparing the analytical standard as well as eluent for the organic mobile phase. For every batch of samples, QC spike and procedural blank were analyzed to check for extraction efficiency and to monitor for any possible contamination during sample analysis. Isotope labeled standards 17αethynylestradiol (D4, 98%), 17β-estradiol (D4, 97%), progesterone (D9, 98%), primidone (D5, 98%), and testosterone (D5, 98%) were used as surrogate standards in this study to compensate for analyte losses during extraction and clean-up. Analyses were carried out in duplicate, and the mean concentration was calculated as the final analytical result. Efficiency of extraction and clean-up, expressed as % recovery, was

Table 1 Extraction efficiency (% recovery), method detection limit and linearity for targeted compounds. Compounds

% Recovery

% RSD

MDL, ng g−1

Linearity, r

Primidone Sulfamethoxazole Dexamethasone Testosterone Quinalphos Progesterone Diazinon Chlorpyrifos Amoxicillin Diclofenac 17β-estradiol Estrone 17α-ethnylestradiol Bisphenol A 4-octylphenol 4-nonylphenol

91 74 85 81 82 82 78 90 93 82 83 81 70 97 78 62

1.66 1.35 15.29 5.59 9.20 3.07 9.68 12.85 5.95 5.52 3.61 11.11 6.47 8.25 4.52 7.32

0.12 1.73 2.13 0.06 0.14 0.07 0.08 5.62 0.23 0.35 0.22 0.02 0.12 0.29 0.30 0.81

0.999 0.998 0.993 0.999 0.994 0.997 0.997 0.996 0.995 0.998 0.999 0.994 0.998 0.997 0.999 0.995

RSD = relative standard deviation; MDL = method detection limit.

Table 2 Physico-chemical characteristic of sediment samples collected from Klang River estuary. Sediment

S1 S2 S3 S4 S5 S6 S7 S8 S9 S10 S11 S12

pH

7.97 8.20 8.28 8.19 6.78 6.11 8.20 8.48 8.57 8.38 8.43 8.61

TOC (%)

3.36 2.17 1.88 1.83 3.06 2.55 1.87 2.23 1.18 1.33 1.41 1.83

Particle size distribution % Clay

% Silt

% Sand

Classification (USDA)

42.72 22.50 62.30 19.75 15.70 26.02 12.74 7.39 17.33 16.17 26.42 4.40

41.13 21.94 26.97 24.90 43.32 43.26 25.91 11.53 22.66 20.15 34.13 16.17

16.06 55.45 10.69 55.02 22.56 16.63 61.09 80.66 59.71 63.40 39.32 79.31

Silty clay Sandy clay loam Silt loam Sandy loam Silt loam Silt loam Sandy loam Loamy sand Sandy loam Sandy loam Loam Loamy sand

evaluated by checking the recoveries for each of the targeted compounds in pre-spiked sediment samples. Extraction recoveries for targeted compounds were in the range of 62%–97% (Table 1), indicating that a satisfactory accuracy was achieved for the analytical method as well as data obtained from this study. The method detection limit for all compounds, calculated based on 3:1 signal-to-noise ratio, ranged from 0.02 to 5.62 ng g−1, and good linearity was obtained for all targeted compounds injected into the LC MS-MS system (Table 1). Instrumentation analysis was accomplished using the Spark Holland HPLC system coupled to AB Sciex 3200 Q-trap triple quadrupole mass spectrometry (AB Sciex, MA, USA). Multiple reaction monitoring for each of the targeted compounds was conducted by optimizing the compound-dependent parameters such as declustering potential, entrance potential (EP), exit potential (EP), and collision energy.

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287

0.16 ( ± 3.69) 0.48 ( ± 5.43) 1.47 ( ± 3.19) 0.17 ( ± 7.79) 0.51 ( ± 3.05) 0.31 ( ± 3.25) 0.34 ( ± 5.82) 0.46 ( ± 3.09) < 0.12–1.47 0.33 118.67 89.04

Concentration, ng g−1 dry weight ( ± %RSD)

S5

Mean %CV % detection

Sediment

S8

S7

S6

S5

S4

S3

S2

S1

Range

S12

S11

S10

S9

S8

S7

0.97 ( ± 4.37) 0.81 ( ± 5.23) 0.60 ( ± 3.65) 0.49 ( ± 2.85) 0.48 ( ± 2.17) 0.45 ( ± 4.54) 0.42 ( ± 6.44) 0.67 ( ± 7.14)

Amoxicillin

< 0.12

S4

S6

< 0.12

S3

– – –

– – –

0.50 ( ± 1.97) 6.63 ( ± 3.69) 1.24 ( ± 8.54) 3.16 ( ± 3.58) 3.89 ( ± 4.50)

13.88 ( ± 1.72) 4.94 ( ± 2.48) < 0.35

16.84 ( ± 0.58) 10.79 ( ± 5.75) 8.82 ( ± 1.46) 10.82 ( ± 6.13) 15.81 ( ± 1.07) 12.06 ( ± 1.08) 8.50 ( ± 3.18) 11.96 ( ± 0.95)

BPA

–

–

Diclofenac

< 2.13

< 2.13

< 2.13

< 2.13

< 2.13

< 2.13

< 2.13

< 2.13

< 2.13

< 2.13

< 2.13

< 2.13

Dexamethasone

< 1.73

< 1.73

< 1.73

< 1.73

< 1.73

< 1.73

< 1.73

< 1.73

< 1.73

< 1.73

< 1.73

< 0.12

S2

< 1.73

Sulfamethoxazole

< 0.12

Primidone

Concentration, ng g−1 dry weight ( ± %RSD)

S1

Sediment

1.02 ( ± 9.32) 1.39 ( ± 1.76) 0.37 ( ± 2.73) 0.25 ( ± 11.80) 0.64 ( ± 5.37)

6.92 ( ± 3.66) 0.28 ( ± 3.40) < 0.22

E2

0.27 112.15 91.62

1.01 ( ± 10.68) 0.65 ( ± 2.96) 0.26 ( ± 12.57) 0.17 ( ± 5.45) 0.36 ( ± 11.82) 0.49 ( ± 2.60) 0.34 ( ± 5.60) < 0.06–1.01

< 0.06

< 0.06

< 0.06

< 0.06

< 0.06

Testosterone

Table 3 Concentration of emerging organic contaminants in sediment samples collected from Klang River estuary.

12.47 ( ± 2.43) 0.89 ( ± 8.65) 0.77 ( ± 1.09) 1.41 ( ± 4.15) 2.90 ( ± 1.34) 2.04 ( ± 3.61) 1.07 ( ± 11.05) 1.49 ( ± 3.81)

E1

– – –

–

< 0.14

< 0.14

< 0.14

< 0.14

< 0.14

< 0.14

< 0.14

< 0.14

< 0.14

< 0.14

< 0.14

< 0.14

Quinalphos

0.99 ( ± 1.99)

0.37 ( ± 13.58) 0.64 ( ± 1.69) 0.39 ( ± 4.04) 5.88 ( ± 2.87) 1.48 ( ± 4.97) < 0.12

< 0.12

EE2

2.31 64.71 100.00

5.34 ( ± 1.85) 4.07 ( ± 3.84) 0.76 ( ± 4.02) 2.13 ( ± 1.73) 4.62 ( ± 3.04) 2.44 ( ± 5.12) 1.44 ( ± 9.27) 2.53 ( ± 10.18) 1.15 ( ± 10.46) 1.38 ( ± 12.67) 1.18 ( ± 7.62) 0.70 ( ± 5.86) 0.70–5.34

Progesterone

< 0.81

< 0.30

(continued on next page)

< 0.81

< 0.81

< 0.81

< 0.81

< 0.81

< 0.81

< 0.81

4-NP

– – –

–

< 5.62

< 5.62

< 5.62

< 5.62

< 5.62

< 5.62

< 5.62

< 5.62

< 5.62

< 5.62

< 5.62

< 5.62

Chlorpyrifos

< 0.30

< 0.30

0.66 ( ± 2.62) 0.57 ( ± 3.92) 0.46 ( ± 10.16) < 0.30

< 0.30

4-OP

0.13 5.16 100.00

0.13 ( ± 12.11) 0.13 ( ± 12.81) 0.13 ( ± 5.78) 0.13 ( ± 8.19) 0.13 ( ± 11.56) 0.14 ( ± 14.26) 0.15 ( ± 9.15) 0.14 ( ± 10.95) 0.13 ( ± 9.52) 0.13 ( ± 9.97) 0.13 ( ± 11.89) 0.13 ( ± 5.56) 0.13–0.15

Diazinon

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– – – – < 0.30–0.66 0.56 17.18 38.50 Range Mean %CV % detection

S12

S11

BPA = bisphenol A; E2 = 17β-estradiol; E1 = estrone; EE2 = 17α-ethynyl estradiol; 4-OP = 4-octylphenol; 4-NP = 4-nonylphenol.

0.51 ( ± 3.47) < 0.22–6.92 0.95 195.33 92.82

< 0.22

< 0.22

1.95 ( ± 2.63) 2.86 ( ± 4.09) 4.30 ( ± 1.81) < 0.35–13.88 3.61 101.68 98.38 S10

Chromatographic separation was performed on reversed-phase C18 analytical column (Gemini NX, 50 mm × 2.0 mm, 3 μm, Phenomenex, CA, USA). Mobile phases consisted of ultrapure water (UPW) for the aqueous phase (mobile phase A), and a mixture of acetonitrile:methanol (60:40) was used as an organic phase (mobile phase B). To improve the ionization of compounds in the mass spectrometry analyzer, ammonium hydroxide (NH4OH, 0.2%, v/v) and formic acid (CH2O2, 0.2%, v/ v) were added into the mobile phase composition for the negative and positive ionization modes, respectively. Separation of compounds for both ionization modes was achieved using gradient elution by increasing mobile phase B concentration from 5% (initial concentration) to 95% in 4 min and by holding it constant for 2 min. After readjusting to the initial concentration, the system was equilibrated for 2 min before proceeding to the next run. The oven column temperature was fixed at 40 °C, in which the flow rate for the mobile phase was 0.30 mL min−1. The injection volume for blank, standards, and samples was set at 20.0 μL. The operating conditions for the mass spectrometry analyzer were the following: curtain gas, 20 psi; CAD gas 1, 40 psi; CAD gas 2, 40 psi; temperature, 600 °C (positive) and 550 °C (negative); and ion spray voltage, 4500 V (positive) and 5500 V (negative). The sediment physico-chemical characteristics of Klang River estuary are presented in Table 2. On the basis of the United States Department of Agriculture classification, the sediments were categorized into silty clay, sandy clay loam, silt loam, sandy loam, loamy sand, and loam (Teh and Talib, 2006). The pH of the sediments ranges from 6.11 to 8.61, and total organic carbon ranges from 1.18% to 3.36%. Data analysis was carried out using statistical software IBM SPSS (Statistical Package for Social Sciences) version 23. Spatial variation and distribution were evaluated using descriptive statistics, and bivariate analysis was used to observe the significant association of targeted emerging organic contaminants with sediment physico-chemical characteristic. Principal component analysis with varimax rotation was applied to classify the sources of EOCs in the sediments of Klang River estuary. Concentrations of the targeted EOCs in the sediments of Klang River estuary are shown in Table 3. Most of the EOCs analyzed in this study showed a coefficient of variation > 30%, indicating a high variation of EOC concentration among sampling stations assessed, with the exception of diazinon, amoxicillin, bisphenol A, and 4-OP. The sediment samples of Klang River estuary showed the presence of EOCs in most of the sampling stations. From 16 compounds evaluated, 11 of the compounds were detected in the samples, with the exception of dexamethasone, sulfamethoxazole, quinalphos, chlorpyrifos, and 4-nonylphenol, which were below method detection limits at all sampling stations. Higher concentrations were observed for bisphenol A, diclofenac, and E1 as compared to the other compounds. The concentrations of bisphenol A range from 8.50 to 16.84 ng g−1 dry weight, with the highest concentration detected at sampling point S1, a sampling site at the Klang River mouth. Elevated concentrations of diclofenac were also detected in the samples, with concentrations ranging from < 0.35 to 13.88 ng g−1 dry weight, and E1 ranges from 0.25 to 12.47 ng g−1 dry weight. Similar to bisphenol A, the highest concentrations for both diclofenac and E1 were detected at sampling point S1, suggesting that the anthropogenic activities along the river significantly influenced the EOC concentration in the estuarine sediment. The distribution pattern of EOCs in the sediment of Klang River estuary is depicted in Fig. 2. Five compounds, namely, amoxicillin, progesterone, diazinon, bisphenol A, and E1, were present in all sampling points assessed, suggesting that these compounds should be regularly monitored in the sediments of

< 0.12–5.88 0.81 196.31 93.12

< 0.81 < 0.30 < 0.12

< 0.81 < 0.30 < 0.12

< 0.81 < 0.30 < 0.12

< 0.81 < 0.30 < 0.12

0.48 ( ± 3.06) 0.25 ( ± 7.29) 0.28 ( ± 5.58) 0.68 ( ± 3.76) 0.25–12.47 2.06 156.36 100.00 < 0.22

9.46 ( ± 3.29) 8.86 ( ± 1.46) 8.92 ( ± 1.50) 10.11 ( ± 1.61) 8.50–16.84 11.08 23.64 100.00 < 0.35

Diclofenac Amoxicillin

0.45 ( ± 5.31) 0.76 ( ± 2.42) 0.40 ( ± 2.10) 0.67 ( ± 3.56) 0.40–0.97 0.60 28.70 100.00 S9

Sediment

Table 3 (continued)

Concentration, ng g−1 dry weight ( ± %RSD)

BPA

E2

E1

EE2

4-OP

4-NP

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et al. (2012), and Sangster et al. (2015). Besides organic carbon, several compounds showed a significant correlation with pH, such as progesterone (r = −0.565, p < 0.05), E1 (r = −0.534, p < 0.05), E2 (r = −0.400, p < 0.05), 4-octylphenol (r = −0.317, p < 0.05), and bisphenol A (r = −0.270, p < 0.05), suggesting that pH is one of the significant parameters influencing the sorption of EOCs in the tropical estuarine sediment. The bi-plot of principle component analysis after varimax rotation is presented in Fig. 3. Three principal components were successfully extracted and explained 80.14% of the total variance. Component 1 (48.18%) was largely contributed by strong loadings of pharmaceutical residues (amoxicillin, diclofenac, and progesterone), estrogenic hormones (E2 and E1), and phenolic xenoestrogen (bisphenol A). Most of these compounds were detected at higher concentrations in sampling

Klang River estuary. Other contaminants such as primidone, testosterone, diclofenac, E2, and EE2 were also ubiquitously present in most of the sampling stations, with percentage of detection at 89.04%, 91.62%, 98.38%, 92.82%, and 93.12%, respectively (Table 3), and 4OP (38.50%) was the compound less detected in the sediments of Klang River estuary. The occurrence and fate of emerging organic contaminants in the sediment matrices were significantly influenced by organic carbon content. Significant associations were observed for most of the targeted compounds with total organic carbon, ranging from a weak positive correlation (r = 0.204, p < 0.05, 4-octylphenol) to a strong positive correlation (r = 0.779, p < 0.01, E1) as shown in Table 4. Organic carbon content had been reported to influence the adsorption and fate of EOCs in the sediment samples as described by Gong et al. (2011), Sun

Fig. 2. Spatial distribution of emerging organic contaminants in sediment of Klang River estuary. Sampling stations are denoted by S1–S12.

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Fig. 2. (continued)

medical waste discharge along Klang River. Component 2 accounted for 18.37% of the variance and consisted of two classes of EOCs, estrogenic hormone, EE2, and phenolic xenoestrogen, 4-OP. Both compounds were mostly detected at sampling points S2, S3, and S4, indicating that the

points S1, S5, and S6, the sampling locations which were directly receiving input from the Klang River discharge. Therefore, it can be classified that principal component 1 represented EOC pollution that originated from various industrial activities as well as domestic and

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1.000 0.121 −0.127 0.064 −0.191 −0.032 0.222 0.033 0.191 0.723⁎⁎ 0.259

1.000 −0.197 0.526⁎ −0.329 −0.197 −0.296 −0.311 −0.230 −0.112 −0.512⁎

1.000 0.121 0.273 0.515⁎ 0.515⁎ 0.572⁎ 0.576⁎⁎ 0.155 0.045

1.000 −0.182 0.000 −0.121 −0.159 0.000 −0.190 −0.494⁎

1.000 0.333 0.273 0.286 0.152 −0.086 −0.090

1.000 0.394 0.509⁎ 0.394 −0.017 −0.135

1.000 0.667⁎⁎ 0.697⁎⁎ 0.431 0.090

1.000 0.699⁎⁎ 0.362 0.212

1.000 0.500⁎ 0.225

1.000 0.562⁎

1.000

source of pollution was predominantly from the Langat River discharge. Sampling points S2 and S3 were located near the Langat River mouth, suggesting that the EOC contaminants present in the river might be deposited into the sediment samples. As for component 3, 13.59% of the total variance in this component consisted of primidone and testosterone, where both compounds were detected at sampling points S8, S9, S10, S11, and S12. These sampling points were situated near the Southport and Northport, where various industrial and human activities were performed. The presence of primidone and testosterone at these sampling points could possibly come from domestic waste discharge from the residential area around the estuary. Multi-class detection of emerging organic pollution from the sediment of Klang River estuary showed that the contamination originated from various pollution sources. Generally, the compounds detected in the sediment samples collected from this estuarine area can be categorized into four classes: pharmaceutical residues (diclofenac, amoxicillin, primidone, progesterone, and testosterone), estrogenic hormones (E1, E2, and EE2), phenolic xenoestrogens (bisphenol A and 4OP), and one pesticides (diazinon). Pharmaceutical residues such as diclofenac have been frequently detected in the effluent of wastewater treatment plants (Ternes, 1998; Heberer et al., 2002; Nakada et al., 2006; Kim et al., 2007), and progesterone, testosterone, and primidone have been associated with domestic/medical waste discharge as a result from the improper disposal of unused medications (Oliveira et al., 2015; Verlicchi and Zambello, 2016). Steroid hormones such as E1 and E2 were reported in animal waste (Raman et al., 2004; Hutchins et al., 2007), suggesting that the contaminations originated from livestock activities along the river. Industrial discharge also contributed as one of the pollution sources when bisphenol A and 4-OP were detected in the sediment samples. These compounds were regularly detected in water samples collected adjacent to industrial activities (Latorre et al., 2003; Sánchez-Avila et al., 2009) and were highly associated with sediment interaction because of their high hydrophobicity characteristics. Pesticide residue, diazinon, was also detected in the samples, suggesting that one of the pollution sources is agricultural activities. In summary, the sources of EOC pollution in the sediment of Klang River estuary were potentially from effluent of wastewater treatment plants, domestic/ medical waste discharge, livestock activities, industrial waste discharge, and agricultural activities. This study presented the baseline assessment of EOCs in the sediment samples collected from Klang River estuary. Several EOCs such as bisphenol A, diclofenac, and E1 showed elevated levels of concentration in the sediment samples analyzed. On the basis of the principal component analysis, the presence of bisphenol A, amoxicillin, diclofenac, E1, E2, and progesterone was attributed mainly to the Klang River discharge, and EE2 and 4-OP were from Langat River. Meanwhile, the presence of primidone and testosterone in the sediment of Klang River estuary was influenced by anthropogenic activities adjacent to the ports. This baseline assessment will be useful for future comparative EOC profiles in the sediments of tropical estuarine ecosystems as well as for updating the current emerging organic pollution profile in this anthropogenically impacted area. Further monitoring studies should involve other environmental matrices such as water, suspended particulate matter, and biota for better understanding of the pathways and fate of the emerging pollution in tropical estuarine and coastal ecosystems.

⁎⁎

⁎

Correlation is significant at the 0.05 level (2-tailed). Correlation is significant at the 0.01 level (2-tailed).

1.000 −0.032 0.230 −0.212 0.121 0.030 0.030 −0.212 −0.095 −0.273 −0.121 −0.405 1.000 −0.667⁎⁎ 0.127 −0.033 0.242 0.030 −0.242 0.061 0.182 0.095 0.303 0.190 0.360 1.000 0.394 −0.727⁎⁎ −0.095 −0.230 0.061 −0.030 0.061 −0.182 0.061 −0.127 0.061 −0.086 0.135 1.000 0.137 0.321⁎ −0.290⁎ 0.272⁎ −0.182 0.595⁎⁎ 0.046 0.260⁎ 0.504⁎ 0.595⁎⁎ 0.592⁎⁎ 0.779⁎⁎ 0.486⁎ 0.204⁎ 1.000 −0.462⁎ −0.290 −0.565⁎ 0.504⁎ 0.096 0.116 −0.565⁎ 0.046 −0.015 −0.137 −0.260⁎ −0.400⁎ −0.534⁎ −0.226⁎ −0.317⁎ pH TOC Clay Silt Sand Primidone Testosterone Progesterone Diazinon Amoxicillin Diclofenac BPA E2 E1 EE2 4-OP

Progesterone Testosterone Primidone Sand Silt Clay TOC pH

Table 4 Correlation coefficient of emerging organic contaminants, TOC and sediment particle size based on Kendall's tau-b analysis.

Diazinon

Amoxicillin

Diclofenac

BPA

E2

E1

EE2

4-OP

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Fig. 3. The bi-plot of principal component loadings of variables analyzed from surface sediment of Klang River estuary after varimax rotation.

Acknowledgment

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