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© Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences. Published by Elsevier B.V. and Science Press. All rights reserved. ISSN 1001–0742 Journal of Environmental Sciences Vol. 24 No. 9 2012

CONTENTS Aquatic environment

Initial identification of heavy metals contamination in Taihu Lake, a eutrophic lake in China Xia Jiang, Wenwen Wang, Shuhang Wang, Bo Zhang, Jiachen Hu ························································································································ 1539 Adsorptive removal of hydrophobic organic compounds by carbonaceous adsorbents: A comparative study of waste-polymer-based, coal-based activated carbon, and carbon nanotubes Fei Lian, Chun Chang, Yang Du, Lingyan Zhu, Baoshan Xing, Chang Liu ··············································································································· 1549 Evaluation of carbon-based nanosorbents synthesised by ethylene decomposition on stainless steel substrates as potential sequestrating materials for nickel ions in aqueous solution X. J. Lee, L. Y. Lee, L. P. Y. Foo, K. W. Tan, D. G. Hassell ································································································································ 1559 Three-dimensional unstructured-mesh eutrophication model and its application to the Xiangxi River, China Jian Li, Danxun Li, Xingkui Wang··························································································································································· 1569 Ciprofloxacin adsorption from aqueous solution onto chemically prepared carbon from date palm leaflets El-Said Ibrahim El-Shafey, Haider Al-Lawati, Asmaa Soliman Al-Sumri ················································································································· 1579 Ammonium removal pathways and microbial community in GAC-sand dual media filter in drinking water treatment Shuo Feng, Shuguang Xie, Xiaojian Zhang, Zhiyu Yang, Wei Ding, Xiaobin Liao, Yuanyuan Liu, Chao Chen ········································································ 1587 Removal of sulfamethazine antibiotics by aerobic sludge and an isolated Achromobacter sp. S-3 Manhong Huang, Shixuan Tian, Dong hui Chen, Wei Zhang, Jun Wu, Liang Chen ······································································································ 1594 Faecal sterols as sewage markers in the Langat River, Malaysia: Integration of biomarker and multivariate statistical approaches Nur Hazirah Adnan, Mohamad Pauzi Zakaria, Hafizan Juahir, Masni Mohd Ali·········································································································· 1600

Effects of Ca(OH)2 assisted aluminum sulfate coagulation on the removal of humic acid and the formation potentials of tri-halomethanes and haloacetic acids in chlorination Jinming Duan, Xiaoting Cao, Cheng Chen, Dongrui Shi, Genmao Li, Dennis Mulcahy ································································································· 1609 Atmospheric environment

Nitrous oxide emission by denitrifying phosphorus removal culture using polyhydroxyalkanoates as carbon source Yan Zhou, Melvin Lim, Soekendro Harjono, Wun Jern Ng································································································································· 1616 Effect of unburned carbon content in fly ash on the retention of 12 elements out of coal-combustion flue gas Lucie Bartonovˇ a,´ Bohum´ır Cech,ˇ Lucie Ruppenthalova,´ Vendula Majvelderova,´ Dagmar Juchelkova,´ Zdenekˇ Klika·································································· 1624 Terrestrial environment pH-dependent leaching behaviour and other performance properties of cement-treated mixed contaminated soil Reginald B. Kogbara, Abir Al-Tabbaa, Yaolin Yi, Julia A. Stegemann ···················································································································· 1630 Enhanced oxidation of benzo[a]pyrene by crude enzyme extracts produced during interspecific fungal interaction of Trametes versicolor and Phanerochaete chrysosporium Linbo Qian, Baoliang Chen ·································································································································································· 1639 Influence of soil type and genotype on Cd bioavailability and uptake by rice and implications for food safety Xinxin Ye, Yibing Ma, Bo Sun ······························································································································································ 1647 Topsoil dichlorodiphenyltrichloroethane and polychlorinated biphenyl concentrations and sources along an urban-rural gradient in the Yellow River Delta Wenjun Xie, Aiping Chen, Jianyong Li, Qing Liu, Hongjun Yang, Tao Wu, Zhaohua Lu ································································································ 1655 Environmental health and toxicology

Degradation of pyrene by immobilized microorganisms in saline-alkaline soil Shanxian Wang, Xiaojun Li, Wan Liu, Peijun Li, Lingxue Kong, Wenjie Ren, Haiyan Wu, Ying Tu···················································································· 1662 Environmental catalysis and materials

Characterizing the optimal operation of photocatalytic degradation of BDE-209 by nano-sized TiO2 Ka Lai Chow, Yu Bon Man, Jin Shu Zheng, Yan Liang, Nora Fung Yee Tam, Ming Hung Wong ······················································································· 1670 Photocatalytic degradation of 4-tert-octylphenol in a spiral photoreactor system Yanlin Wu, Haixia Yuan, Xiaoxuan Jiang, Guanran Wei, Chunlei Li, Wenbo Dong ······································································································ 1679

Efficiency and degradation products elucidation of the photodegradation of mefenpyrdiethyl in water interface using TiO2 P-25 and Hombikat UV100 Amina Chnirheb, Mourad Harir, Basem Kanawati, Mohammed El Azzouzi, Istvan Gebefugi,¨ Philippe Schmitt-Kopplin ····························································· 1686 Response surface methodology analysis of the photocatalytic removal of Methylene Blue using bismuth vanadate prepared via polyol route Abdul Halim Abdullah, Hui Jia Melanie Moey, Nor Azah Yusof ·························································································································· 1694 Poly[β-(1→4)-2-amino-2-deoxy-D-glucopyranose] based zero valent nickel nanocomposite for efficient reduction of nitrate in water Sheriff Adewuyi, Nurudeen O. Sanyaolu, Saliu A. Amolegbe, Abdulahi O. Sobola, Olujinmi M. Folarin ·············································································· 1702 Environmental analytical methods

A flow cytometer based protocol for quantitative analysis of bloom-forming cyanobacteria (Microcystis) in lake sediments Quan Zhou, Wei Chen, Huiyong Zhang, Liang Peng, Liming Liu, Zhiguo Han, Neng Wan, Lin Li, Lirong Song ······································································ 1709 A simple and sensitive method for the determination of 4-n-octylphenol based on multi-walled carbon nanotubes modified glassy carbon electrode Qiaoli Zheng, Ping Yang, He Xu, Jianshe Liu, Litong Jin ·································································································································· 1717

Serial parameter: CN 11-2629/X*1989*m*184*en*P*23*2012-9 Available online at www.sciencedirect.com JOURNAL OF ENVIRONMENTAL SCIENCES ISSN 1001-0742 CN 11-2629/X Journal of Environmental Sciences 2012, 24(9) 1600–1608 www.jesc.ac.cn

Faecal sterols as sewage markers in the Langat River, Malaysia: Integration of biomarker and multivariate statistical approaches

Nur Hazirah Adnan1, Mohamad Pauzi Zakaria1, Hafizan Juahir2, Masni Mohd Ali3,∗

1. Centre of Excellence for Environmental Forensics, Faculty of Environmental Studies, Universiti Putra Malaysia 43400 Serdang, Selangor, Malaysia 2. Department of Environmental Sciences, Faculty of Environmental Studies, Universiti Putra Malaysia, 43400 Serdang, Selangor, Malaysia 3. School of Environmental and Natural Resource Sciences, Faculty of Science and Technology, Universiti Kebangsaan Malaysia, 43600 Bangi, Selangor, Malaysia

Received 11 November 2011; revised 13 January 2012; accepted 18 January 2012

Abstract The Langat River in Malaysia has been experiencing anthropogenic input from urban, rural and industrial activities for many years. Sewage contamination, possibly originating from the greater than three million inhabitants of the Langat River Basin, were examined. Sediment samples from 22 stations (SL01–SL22) along the Langat River were collected, extracted and analysed by GC-MS. Six different sterols were identified and quantified. The highest sterol concentration was found at station SL02 (618.29 ng/g dry weight), which situated in the Balak River whereas the other sediment samples ranged between 11.60 and 446.52 ng/g dry weight. Sterol ratios were used to identify sources, occurrence and partitioning of faecal matter in sediments and majority of the ratios clearly demonstrated that sewage contamination was occurring at most stations in the Langat River. A multivariate statistical analysis was used in conjunction with a combination of biomarkers to better understand the data that clearly separated the compounds. Most sediments of the Langat River were found to contain low to mid-range sewage contamination with some containing ‘significant’ levels of contamination. This is the first report on sewage pollution in the Langat River based on a combination of biomarker and multivariate statistical approaches that will establish a new standard for sewage detection using faecal sterols. Key words: sterols; biomarkers; surface sediments; sewage pollution; Langat River; principal component analysis DOI: 10.1016/S1001-0742(11)60979-0

Introduction to trace sewage pollution. Such microbiological markers have been widely utilised due to the fact that application of Domestic sewage discharge to marine systems, as a result this method for quantification is relatively straightforward of human interference in nature, has increasingly become and fast (da Costa and Carreira, 2005). Most countries, of great concern in recent years (da Costa and Carreira, including Malaysia, still use coliform bacteria for water 2005). The detection of sewage contamination in Malaysia, quality guidelines based on the number of this bacteria particularly in the Selangor area, is of paramount impor- present. Nevertheless, this method can be arguably prone tance for health, aesthetics and the ecosystem because the to some major hindrances such as rapid biodegradation river is used for recreational activities and is a source in aquatic environments and inconstancy in numbers. of potable water for the highly populated municipalities Moreover, faecal pollution that originates from different surrounding it. In tropical and subtropical Asia, there is sources cannot be distinguished by coliform bacteria alone a strong correlation between sewage contamination and (Leeming et al., 1996). many waterborne diseases, which are wide-ranging in Sterols, which act as chemical markers, have been suc- these regions (Isobe et al., 2002). As such, the assessment cessfully applied as organic molecular markers to evaluate of river sediment for possible human faecal contamination and distinguish between the varied sources of sewage is a critical step towards improving water quality and contamination (Eganhouse, 1997). Even though chemical reducing the risk of infectious diseases (Wang et al., 2010; markers are more expensive and complicated to use, they Rosenfeld and Gallagher, 1964). remain in the environment longer than bacteria and have Sewage contamination can be evaluated by microbio- higher source specificity (Takada et al., 1997). These logical and chemical markers (Vivian, 1986; Takada and compounds are better conserved in sediments than other Eganhouse, 1998). For several decades, the microbiologi- biological products like amino acids and carbohydrates cal marker, coliform bacteria, has been used as an indicator (Saliot et al., 1991; Mudge and Duce, 2005; Piah et al., 2008). Once the faecal matter has been incorporated into the sediment, sterols are expected to persist. Any decline * Corresponding author. E-mail: [email protected] jesc.ac.cn No. 9 Faecal sterols as sewage markers in the Langat River, Malaysia: Integration of biomarker and multivariate statistical approaches 1601 in concentration can be attributed to physical sediment most marine plankton. Because this compound is a by- transport (Bartlett, 1987). In sewage impact studies, the product of the excretion of higher mammals, such as most cited sterols are coprostanol and epicoprostanol, also humans, it is also associated with sewage discharge. The known as fecal sterols because they do not naturally derive use of cholesterol on its own as a biomarker is somewhat from aquatic sediments (Venkatesan and Kaplan, 1990). limited due to the diversity of potential source organisms. Coprostanol, produced by the microbial degradation of However, cholesterol can be used in conjunction with other cholesterol in the digestive tract of humans, has been sterols to calculate key ratios for sewage pollution analysis. recognised as a biomarker for human-derived sewage The Langat River Basin is one of the most populated pollution due to its persistence in the natural environment and fastest-growing economic regions in Malaysia (Saim (Wang et al., 2010). It comprises 40%–60% of the total et al., 2009). Domestic sewage from a nearby treatment sterols excreted in human waste (Nichols et al., 1996; plant contributed 28% of the major pollutants, acting as a Martins et al., 2007) and, as a result, is associated with constant polluter to the river. Department of Environment anthropogenic sewage. In spite of being considered a Malaysia (1999) stated that, there were 13 polluted tribu- biomarker for evaluating contamination from domestic taries all over Malaysia with 36 polluted rivers including effluents, it exhibits a strong resistance to degradation by Langat River and the problem were strongly related with microbial communities, especially in anoxic sediments. the human activities such as industrial, agriculture and Grimalt et al. (1990) and McCaffrey (1990) have highlight- construction. Furthermore, existing wastewater treatment ed the possible production of coprostanol by in-situ anoxic facilities unable to process the increasing domestic sewage sediments as an independent source. Therefore, the analy- throughout the year. Due to the concern of this problem, we sis of coprostanol alone has been deemed insufficient, and systematically analysed the sterol distribution in surface one must consider the ratios and concentrations together, sediments along the Langat River and investigated the level along with other structurally related sterols. of sewage pollution using a combination of biomarker Other sterols have also been studied for the evaluation of and multivariate statistical approaches that will able to sewage contamination in the Langat River. Epicoprostanol, provide information on the sanitary condition for this the isomer of coprostanol, can be used to indicate the level current status. No previous sterol study of the Langat River of treatment or age of faecal matter. This compound is has ever been conducted using a combination of these two formed during the treatment of wastewaters and sewage approaches. sludge digestion. However, epicoprostanol may also be produced from cholesterol during extensive anaerobic 1 Materials and methods sewage treatment. By using the relative proportions of those compounds, the degree of sewage treatment can be 1.1 Sample collection and extraction evaluated by calculating the ratio between epicoprostanol and coprostanol (McCalley et al., 1981). Another sterol Twenty-two surface sediment samples (0–5 cm) were compound that has been used in conjunction with co- collected from the Langat River, Selangor (Fig. 1, Table 1). prostanol is cholesterol (Volkman, 1986) which is present The sediment samples were collected in January 2010 in many marine organisms and is the major sterol for using an Ekman dredge. They were then wrapped in

Table 1 Sampling sites and description area for the sediments collected from the Langat River

Station Latitude (N) Longitude (E) Description area

SL01 03◦02′25.1′′ 101◦47′18.2′′ Industrial and residential area in Long River (tributaries of Langat River) SL02 03◦00′56.7′′ 101◦45′43.3′′ Industrial and residential area in Balak River (tributaries of Langat River), which is near the Cheras Jaya Sewage Treatment Plant SL03 02◦57′55.4′′ 101◦47′07.5′′ Industrial and residential area in Bangi which is near to the Bangi Sewage Treatment Plant SL04 02◦55′04.1′′ 101◦45′29.5′′ Residential area near the Teras Jernang Sewage Treatment Plant SL05 02◦54′40.0′′ 101◦45′13.6′′ Residential area, farmhouse plantation and livestock area SL06 02◦54′25.5′′ 101◦44′54.9′′ Residential area, farmhouse plantation and livestock area SL07 02◦54′19.0′′ 101◦44′34.5′′ Livestock, agricultural and industrial area SL08 02◦53′46.5′′ 101◦44′02.9′′ Livestock, agricultural and industrial area SL09 02◦53′46.6′′ 101◦43′45.3′′ Livestock, agricultural and industrial area SL10 02◦51′23.4′′ 101◦40′58.7′′ Wet market area in Dengkil SL11 02◦48′47.5′′ 101◦31′33.5′′ Residential area in Teluk Dato’ SL12 02◦48′52.9′′ 101◦31′30.4′′ Residential area in Teluk Dato’ SL13 02◦48′55.8′′ 101◦30′24.9′′ Residential area in Teluk Dato’ SL14 02◦50′27.5′′ 101◦30′57.6′′ Landfill and dumping site SL15 02◦50′32.6′′ 101◦30′52.6′′ Landfill and dumping site SL16 02◦50′36.7′′ 101◦30′51.2′′ Landfill and dumping site SL17 02◦50′56.7′′ 101◦30′42.4′′ Rural area in Kg. Serdang Belah SL18 02◦51′01.2′′ 101◦30′44.4′′ Rural area in Kg. Serdang Belah SL19 02◦51′01.1′′ 101◦30′47.7′′ Effluent of leachate from landfill site SL20 02◦51′02.7′′ 101◦30′52.8′′ Effluent of leachate from landfill site SL21 02◦51′04.9′′ 101◦30′52.6′′ Furthest point in rural area in Kg. Serdang Belah SL22 02◦51′07.2′′ 101◦30′59.3′′ Furthest point in effluent of leachate from landfill site

jesc.ac.cn 1602 Journal of Environmental Sciences 2012, 24(9) 1600–1608 / Nur Hazirah Adnan et al. Vol. 24

Legend Upstream Main river Gulf of Thailand Study location

Cheras South China Sea Kajang Malaysia SL02: Balak River Putrajava (tributary of Langat River) Malaysia Teluk Datok which situated near

Teluk Panglima Garang to Cheras Jaya SL04: residential area which near to Teras Jernang STP

Downstream

Fig. 1 Sediment sampling sites on the Langat River. aluminium foil, put in zip lock bags and stored in a freezer to 14 mL vials. Anhydrous sodium sulphate was then at –4°C until further analysis. added to remove any remaining water and polar com- The study included the following sterols: coprostanol pounds remaining in the samples. The solution was then (5β-cholestan-3β-ol), epicoprostanol (5β-cholestan-3α- filtered through Number 2 Whatman filter paper and dried ol), cholesterol (cholest-5-en-3β-ol) and cholestanol under oxygen-free nitrogen (OFN). Sample derivitisation (5α-cholestan-3β-ol). In addition, campesterol was required for compound analysis by gas chromatogra- (24-methylcholest-5-en-3β-ol) and brassicasterol (24- phy. Bis-(trimethylsilyl) triflouroacetamide (BSTFA) (2–3 methylcholesta-5, 22-dien-3β-ol) were quantified. drops) was added to the samples. BSTFA replaces ac- Sterol extraction from sediments included three stages: tive hydrogen atoms with a trimethylsilyl (TMS) group, sediment reflux, liquid-liquid extraction and derivitisation. –Si(CH3), making the compound more volatile and stable The extraction and procedures were adapted from previous for gas chromatographic analysis. Samples were then heat- publications (Mudge and Norris, 1997; Mudge et al.,1998). ed in an aluminium block for 10 min at 60°C, evaporated to Experiments with spiked reference materials have shown dryness under OFN and then stored at –20°C until further that these methods release > 95% of the sterols (Mudge analysis. and Norris, 1997; Pereira, 1999). Each sediment sample 1.2 Total organic carbon (TOC) analysis was spiked with an internal standard, 5α-androstan-3β-ol, purchased from Sigma Aldrich, USA. The TOC analytical procedures used here were described Approximately 30–40 g wet weight of sediment were by Nelson and Sommers (1996). Briefly, the samples were hydrolysed for 4 hr with 50 mL of 6% (W/V) potassium dried overnight at 60°C in an oven and then homogenised hydroxide in methanol to obtain > 95% recovery (Pereira, using a mortar and pestle. Samples were leached by 1999; Ali and Mudge, 2006). This process enables the mixing 1–1.5 g of the sample was mixed with 1–2 mL lipids to be released from their ester/ether linkages. The of hydrochloric acid (HCl) 1 mol/L to remove carbonates overall efficiency of the extraction process is determined (i.e., eliminate inorganic carbon) and then dried for 10 by performing repeated reflux on selected samples. It is to hr at 100–105°C to eliminate residual HCl. The TOC maximise the results of analysis as well as to ensure there percentage was then determined on a carbon analyser are no identified sterols left during the extraction process. (EA1108, Fison, USA) with the furnace temperature at The refluxed samples were then centrifuged at 2500 r/min 350°C and an oxygen boost time of 60 sec. The standard for 5 min, after which the supernatant was decanted into a used here was sulphanilamide methionine. separating flask. 1.3 Instrumental analysis and quantification Approximately 20 mL of hexane and 10 mL of Milli-Q water were added to the supernatant to extract free non- A Perkin Elmer Clarus 500 (USA) gas chromatography- polar lipids, and the mixture was shaken vigorously. The mass spectrometry (GC-MS) was used to analyse sterols non-polar fraction was transferred to a Florentine flask, from the sediments on a non-polar, DB5-HT capillary and the entire procedure was repeated to ensure maximum column (30 m × 0.25 mm × 0.10 µm). Helium carrier gas extraction. The combined non-polar fractions were evapo- (99.999% purity) was used at a flow rate of 1 mL/min and rated at 40°C in a rotary evaporator, and the samples were a column pressure of 50 kPa. The temperature program then re-dissolved in 2–3 mL of hexane and transferred started at 60°C, increasing at 15°C/min to a maximum of

jesc.ac.cn No. 9 Faecal sterols as sewage markers in the Langat River, Malaysia: Integration of biomarker and multivariate statistical approaches 1603

300°C, then at 5°C/min to a maximum of 350°C, held for centration variation effect. The sterol data was subjected 10 min. to Principal Component Analysis (PCA) to obtain further Standard methods and techniques were adopted insight into the relationship between samples and sterols. throughout the analysis. Accuracy and efficiency of It is advisable to rotate the principal components (PCs) the extraction procedure of sterol compound was also using a Varimax rotation because the PCs generated by determined by performing triplicate samples (n = 3) PCA cannot always be readily interpreted. The PCA was with relative standard deviation less than 14%. Blanks performed using XL-STAT 2010. and calibration standards were used throughout the GC injections. A blank was injected, followed by 2 Results and discussion the calibration standard again. A standard mixture of coprostanol, epicoprostanol, cholesterol and cholestanol 2.1 Sterol distribution were purchased from Sigma Aldrich for qualitative and quantitative analysis. Cholesterol-TMS was used to Individual concentrations for all selected sterols are ff calibrate and quantify peaks obtained from the analysis. shown in Table 2, which includes two di erent markers: Procedural blanks were also analyzed and no compounds sewage markers (coprostanol, epicoprostanol, cholesterol of interest were measured in any of these samples. The and cholestanol) and terrestrial markers (brassicasterol and internal standard recovery ranged from 70% to 120%. campesterol). The reported values for sterols concentration were subjected to average of triplicates. The former com- 1.4 Statistical analysis pounds were the main objective in the present study, and Many researchers have highlighted the advantages of a the latter were used for the multivariate statistical approach multivariate statistical approach on biomarkers to extract to identify sampling stations and their particular sources. the maximum amount of information from complex mix- The sum of the sterol concentrations varied from 618.25 / tures of lipid compounds (Mudge and Bebiano, 1997; to 11.49 ng g dry weight (Table 2). Coprostanol was the Yunker et al., 1995). Information regarding the origin of most abundant sterol throughout the river. This sterol organic matter in sediments can be established by using is a product of the biohydrogenation of cholesterol by individual compounds and the biomarker ratio approach, enteric bacteria of higher mammals, particularly humans while more information can be extracted from the data (Seguel et al., 2001), and was present in all samples through the use of multivariate statistical methods in a analysed. This sterol comprised 49.96% of the total sterols / single analysis (Martins et al., 2007). Most quantitative with concentrations ranging from 2.77 to 417.66 ng g statistical methods require normally distributed data. How- dry weight and an overall mean concentration of 84.96 / ever, as with most environmental data, there is a range ng g dry weight (Fig. 2). The greatest concentration was of values from below the limit of detection to relatively observed at SL04, which is situated in the Teras Jernang high values in source or near source samples, resulting area. This area is located within a highly populated and in non-normally distributed data (Mudge, 2002). Thus, to well-developed urban area consisting of Kajang and Bangi. overcome the problem, data were expressed as proportions The high levels of coprostanol found in these sediments of the total sterol concentration prior to analysis for better are similar to those reported in highly urbanised areas separation and interpretation, as well as to remove any con- as a result of untreated sewage being discharged into the

Table 2 Concentrations of individual sterols, selected ratios and total organic carbon in surface sediments from the Langat River

∑ Station Cop E-cop Choles Cholest Brass Campes -OLs Cop/Choles 5β/(5β+5α) Choles/ E-cop/ TOC Sediment (ng/g dw) (ng/g dw) (ng/g dw) (ng/g dw) (ng/g dw) (ng/g dw) (ng/g dw) Cholest Cop (%) type

SL01 38.95 1.81 24.62 8.02

jesc.ac.cn 1604 Journal of Environmental Sciences 2012, 24(9) 1600–1608 / Nur Hazirah Adnan et al. Vol. 24

450.00 Coprostanol 400.00 Epicoprostanol

350.00 Cholesterol Cholestanol 300.00

250.00

200.00

150.00

Concentration (ng/g dry weight) (ng/g Concentration 100.00

50.00

0.00 SL01 SL02 SL03 SL04 SL05 SL06 SL07 SL08 SL09 SL10 SL11 SL12 SL13 SL14 SL15 SL16 SL17 SL18 SL19 SL20 SL21 SL22 Station Fig. 2 Concentration of coprostanol, epicoprostanol, cholesterol and cholestanol with mean standard deviation of three replicates, p< 0.05 at each sampling station. river (Isobe et al., 2002). Another factor affecting the those of coprostanol because the samples were taken concentration of coprostanol at this station is the sediment from river sediments. These sediments contain a lower type, which is dominated by clay (95.2%). The highest number of marine organisms compared to marine and concentrations of sterols were found in sediments with estuarine sediments, which frequently contain substantial higher proportions of clay, as reported by Froehner et al. amounts of cholesterol (Mudge and Seguel, 1997). Low (2010). A depletion in the concentration of coprostanol concentrations of cholesterol were also found at SL21, was identified at SL21, situated in a rural location (Kg. suggesting that this station was not polluted with domestic Serdang Belah) with lower amounts of human sewage and sewage discharge. This area was also noted as having low other domestic sewage being discharged into the river. concentrations of coprostanol. These results are in agreement with the study by Heng et The concentration of epicoprostanol was analysed as al. (2006) which stated that pollution in the Langat River an indicator of the level of treatment or age of faecal is strongly correlated with population increases and water material. Concentrations ranged from 0.88 to 14.93 ng/g deficits and further aggravated by river pollution. A study dry weight, constituting 2.43% of total sterols present in by Gonzalez-Oreja´ and Saiz-Salinaz (1998) found that all samples (Fig. 2). Samples from SL04, SL18, SL02 and coprostanol concentrations greater than 500 ng/g are con- SL05 were indicative of untreated materials, as the epi- sidered to be indicative of ‘significant’ sewage pollution. In coprostanol content was relatively small compared to the the majority of samples, levels were comparatively lower other sampling stations. This might be expected because than 500 ng/g, indicating minor sewage contamination. the majority of the samples came from untreated sewage However, based on Grimalt et al. (1990), values above 100 that had been directly discharged into the river. Other ng/g could be classified as being contaminated by sewage. samples are likely to have been only partially treated due Thus, considering only the concentration of coprostanol to the low concentrations of epicoprostanol present. This and using values adopted from Grimalt et al. (1990), five compound is a by-product of the sewage treatment system stations can be categorized as sewage contaminated. and will only occur in low concentrations if sewage is not Cholesterol was the second most abundant sterol found fully treated or is only partially treated. Only one of the in the sediment samples from the Langat River. Its con- stations, SL21, was found to have a high concentration of centration ranged from 4.68 to 310.65 ng/g dry weight, epicoprostanol, indicating that it originated from treated or comprising 35.76% of total sterols (Fig. 2). The highest old samples because it correlated with low concentrations concentration of cholesterol was found at SL02, located of coprostanol and cholesterol. We can also assume that within the upper stream of the Langat River Basin. The the pollution load at SL21 is relatively low compared to sampling station was situated on the Balak River, which is the other stations, as it is located in a populated urban area. one of the tributaries of the Langat River. The sampling 2.2 Biomarker approaches using diagnostic indices point was near the Cheras Jaya sewage treatment plant (STP) with a highly populated residential area and an Considering different diagnostic indices between select- industrial area that largely contributed to the abundance ed sterols may enhance the reliability of sterols as of cholesterol. Cholesterol is present in many marine markers of sewage contamination. Three diagnostic in- organisms from algae (Volkman, 1986; Barrett et al., 1995) dices were applied in this study: the 5β/(5β+5α) stanol to fish, sharks and seals (Borch-Jensen and Mollerup, index, the coprostanol/cholesterol index and the epico- 1996), as well as in domestic sewage discharges. In this prostanol/coprostanol index. study, total concentrations of cholesterol were less than Results from studies by Jeng and Han (1994) and Fattore

jesc.ac.cn No. 9 Faecal sterols as sewage markers in the Langat River, Malaysia: Integration of biomarker and multivariate statistical approaches 1605 et al. (1996) have confirmed that a value of > 0.7 for treatment or age of sewage in the system (Fig. 3). Basically, the 5β/(5β+5α) stanol index is characteristic of urban sediments that receive untreated sewage exhibit a lower sewage pollution. Because the formation of cholestanol ratio (< 0.2), while values higher than 0.8 are related to can originate from biogenic and anthropogenic processes, partially treated (primary or secondary) sewage. All sites it is difficult to confirm the source of pollution for interme- in the present study had ratios characteristic of untreated diate values (0.3–0.7). Both concentrations of coprostanol sewage inputs. The highest epicoprostanol/coprostanol ra- and 5β/(5β+5α) stanol are required to elucidate the rela- tio was recorded at SL21 (0.32), while all other sites had tive contribution of sewage sources and natural reduction a value of < 0.2. This indicates that the majority of the sources to sedimentary sterols (Grimalt et al., 1990; Fattore sediments received untreated or partially treated sewage as et al., 1996; Reeves and Patton, 2005). Overall, this is a result of the ineffectiveness of sewage treatment systems a very useful tool to elucidate sources of sterol input to currently in place in Malaysia. recent sediments (Reeves and Patton, 2005). Of the 22 stations, only 8 of the sampling points (SL13, SL14, SL15, 2.3 Multivariate statistical approach – Principal Com- SL16, SL19, SL20, SL21 and SL22) had a value of < 0.7, ponent Analysis (PCA) while most of the samples had a ratio of > 0.7 (Table 2). All of the samples having < 0.7 came from the Kuala Langat To establish relationships and clusters within the labora- area (downstream), which is less populated than the middle tory dataset, PCA was performed on the data as detailed and upper stream areas of the Langat River. Most of the in Section 1.4. The sterol data was subjected to PCA to samples containing high concentrations of coprostanol had further investigate the differences between the sources of a ratio value of > 0.7, as the diagnostic index approach the organic matter found in the Langat River sediments by enhances the reliability of sterols as biomarkers to confirm calculating the coefficient of variation for each variable. the occurrence of sewage contamination. The first two components consisted of PC1, 49.02%, and The coprostanol/cholesterol ratio elucidated the con- PC2, 28.55%, which accounted for 77.57% of the total tributions (McCalley et al., 1981) from biogenic and variance. Figure 4 shows the loadings for the variables and sewage sources. Ratios < 1 are reported to originate from the scores of the sampling sites. The PC1 axis (PCA load- biogenic sources, while ratios > 1 come from sewage ings) showed a positive correlation with all compounds, sources (Fattore et al., 1996; Nichols et al.,1996; Reeves notably with brassicasterol, campesterol, cholestanol and and Patton, 2005). There were 10 sites with values < 1, epicoprostanol. On the other hand, for the PC2 axis, while the other 12 sites (SL01, SL03, SL04, SL05, SL06, most of the compounds showed a positive correlation, SL07, SL08, SL09, SL11, SL12, SL13 and SL18) had particularly coprostanol and cholesterol compounds, while values > 1. This implies that the majority of the sampling only one compound (brassicasterol) showed a negative points in the Langat River were polluted with sewage, correlation. The main discrimination was observed with rather than biogenic sources. In this study, the values PC2, which shows a positive correlation for most of the of the coprostanol/cholesterol ratios were consistent with compounds that result from the concentration of the sterol the 5β/(5β + 5α) stanol index, with the exception of in the sediments. We can see from Fig. 4a that coprostanol SL02, SL10 and SL13. Values as high as 28.87 (SL04) and cholesterol showed strong positive loadings, as these were measured in more heavily contaminated areas, while two compounds were dominant in the sediments. The two values below 1 (0.96) at SL10 indicated the overwhelming compounds were tabulated near to each other because influence of plankton-derived cholesterol from the total coprostanol is the product of the microbial degradation organic matter (da Costa and Carreira, 2005). of cholesterol in the digestive tract of humans (Seguel et A study by Mudge and Seguel (1999) proposed that the al., 2001). Thus, both of these compounds are strongly ratio between epicoprostanol and coprostanol provides a correlated to each other. Moderate loadings came from useful means of assessing the degree of sewage treatment. epicoprostanol, cholestanol and campesterol, as these com- A scatter plot of the ratio of epicoprostanol/coprostanol pounds were present at intermediate concentration in the against coprostanol/cholesterol can indicate the likely sediment samples. Brassicasterol was the only compound

0.35 21 0.30 Treated or old sewage 0.25 0.20 19 22 14 0.15 15 13 20 10 0.10 16 12 07 11 03 17 01 06 0.05 09 08 02 18 Untreated sewage Epicoprostanol/Coprostanol 04 0.00 05 0.00 5.00 10.00 15.00 20.00 25.00 30.00 35.00 Coprostanol/Cholesterol Fig. 3 Relationship between epicoprostanol/coprostanol and coprostanol/cholesterol ratios at all samples. Sampling stations SL01–SL22 are labelled as 1–22. jesc.ac.cn 1606 Journal of Environmental Sciences 2012, 24(9) 1600–1608 / Nur Hazirah Adnan et al. Vol. 24

1.00 4 Coprostanol a b 0.75 Cholesterol 3 SL02 0.50 Epicoprostanol Cholestanol 2 SL04 0.25 Campesterol

SL09 0 1 SL05 SL03 Brassicasterol -0.25 SL08 SL10 0 SL12 SL01 SL18 SL06 SL13 SL19 SL07 SL16 -0.50 SL11 SL14SL15 Scores on PC2 (28.55%) SL21 SL17SL22 Loadings on PC2 (28.55%) Loadings -1 -0.75 SL20

-1.00 -2 -1 -0.75 -0.5 -0.25 0 0.25 0.5 0.75 1 -5 -4 -3 -2 -1 0 1 2 3 4 Loadings on PC1 (49.02%) Scores on PC1 (49.02%) Fig. 4 Factor loadings (a) and factor scores (b) of the PCA analysis of sterols in surface sediments from the Langat River. that tabulated a negative loading, as this compound had the 3 Conclusions lowest concentration at all the sampling stations. The PCA scores demonstrate the differences between Faecal sterols and stanols have proven to be useful sewage the samples from each station. Figure 4b shows the sep- markers for the study of sewage pollution distribution aration among stations from PC2, which clearly grouped patterns in surface sediments of the Langat River. The co- each of the samples according to their sterol concentration. prostanol levels in the Langat River were comparable to the SL02 had the highest positive score, as this station is lower to mid-range concentrations for coastal sediments dominated by a high concentration of coprostanol, as well worldwide. In the majority of the samples, levels were as cholesterol and cholestanol. In contrast, SL04 had the comparatively lower (<100 ng/g dry weight), which indi- highest coprostanol concentration, but it was tabulated as cates less sewage contamination. However, some samples being lower than SL02 due to the depletion of cholesterol (e.g., SL04) had concentrations between 100 and 500 ng/g and cholestanol concentration. Therefore, we can see a dry weight, indicating the presence of sewage contami- clear separation on PC2 between these two samples. From nation. The low values of the epicoprostanol/coprostanol the PCA scores, SL09 and SL05 were grouped together ratio and concentrations of epicoprostanol in most of the because these two stations had similar sterol concentra- samples with high levels of faecal sterols show that sewage tions. SL03, however, was tabulated a bit farther from the discharge into the Langat River receives poor or inade- other stations on the positive score because this station quate sewage treatment. Clearly, action should be taken had the highest concentration of epicoprostanol. Another to remedy this situation. Combining Principal Component station that grouped in the positive score was SL10, which Analysis as a multivariate statistical approach with the had the lowest score due to the fact that it had the lowest biomarker/diagnostic index was successful in extracting concentration of coprostanol compared to the other stations the maximum amount of information from a complex grouped in the positive scores on PC2. The other 16 dataset, leading to a greater understanding of distribution stations were grouped in negative scores on PC2 due to patterns which based on the loadings for each compound their lower sterol concentrations. that clearly separated between each other. The sterol data gathered will collectively contribute to the knowledge of 2.4 Total organic carbon these biomarkers, as well as to the sanitation conditions in The concentration of TOC in the surface sediment samples the study area. from the Langat River was relatively low, with a range Acknowledgments of 0.08%–3.42% (Table 2). The sample with the highest TOC concentration was from SL10, whose granulometric We are very thankful to the Universiti Kebangsaan composition is dominated by silt. Overall, a higher level of Malaysia for the OUP Fund (OUP-UKM-FST-2011). We TOC is found in sediments predominantly composed of silt also would like to acknowledge the School of Environmen- and clay, with more fine particles than a sandy composition tal and Natural Resource Sciences, Universiti Kebangsaan (Froehner et al., 2010). Silt and clay possess a greater Malaysia (UKM) for the laboratory and facilities, the surface area, which allows the accumulation of organic Department of Irrigation and Drainage for sample collec- matter. A depletion of TOC was found at SL04. This can tion, the staff at the Faculty of Environmental Studies, be explained by the greater dilution of organic matter in Universiti Putra Malaysia (UPM) for technical support upstream areas. TOC concentrations are generally higher and Nurul Afiqah Mohamd Tahir, Nurhidayah Nordin, downstream (> 1.00%) compared to upstream (< 1.00%) Norazida Manan, Norliza Ismail, Muhammad Raza, Mohd because concentrations of nutrients increase towards the Shazwan, Mohd Roshidee, members of the Centre of mouth of the river, where the number of sewage discharge Excellence UPM, members of the Environmetric Group points and residences and industries are greatest (Froehner and any anonymous referee for their constructive and et al., 2010). helpful comments.

jesc.ac.cn No. 9 Faecal sterols as sewage markers in the Langat River, Malaysia: Integration of biomarker and multivariate statistical approaches 1607

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Editors-in-chief Hongxiao Tang Associate Editors-in-chief Nigel Bell Jiuhui Qu Shu Tao Po-Keung Wong Yahui Zhuang Editorial board R. M. Atlas Alan Baker Nigel Bell Tongbin Chen University of Louisville The University of Melbourne Imperial College London Chinese Academy of Sciences USA Australia United Kingdom China Maohong Fan Jingyun Fang Lam Kin-Che Pinjing He University of Wyoming Peking University The Chinese University of Tongji University Wyoming, USA China Hong Kong, China China Chihpin Huang Jan Japenga David Jenkins Guibin Jiang “National” Chiao Tung University Alterra Green World Research University of California Berkeley Chinese Academy of Sciences Taiwan, China The Netherlands USA China K. W. Kim Clark C. K. Liu Anton Moser Alex L. Murray Gwangju Institute of Science and University of Hawaii Technical University Graz University of York Technology, Korea USA Austria Canada Yi Qian Jiuhui Qu Sheikh Raisuddin Ian Singleton Tsinghua University Chinese Academy of Sciences Hamdard University University of Newcastle upon Tyne China China India United Kingdom Hongxiao Tang Shu Tao Yasutake Teraoka Chunxia Wang Chinese Academy of Sciences Peking University Kyushu University Chinese Academy of Sciences China China Japan China Rusong Wang Xuejun Wang Brian A. Whitton Po-Keung Wong Chinese Academy of Sciences Peking University University of Durham The Chinese University of China China United Kingdom Hong Kong, China Min Yang Zhifeng Yang Hanqing Yu Zhongtang Yu Chinese Academy of Sciences Beijing Normal University University of Science and Ohio State University China China Technology of China USA Yongping Zeng Qixing Zhou Lizhong Zhu Yahui Zhuang Chinese Academy of Sciences Chinese Academy of Sciences Zhejiang University Chinese Academy of Sciences China China China China Editorial office Qingcai Feng (Executive Editor) Zixuan Wang (Editor) Suqin Liu (Editor) Zhengang Mao (Editor) Christine J Watts (English Editor) Journal of Environmental Sciences (Established in 1989) Vol. 24 No. 9 2012

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