EnvironmentAsia AvailableAvailable online online at www.tshe.org/EA at www.tshe.org/EA The international journal published by the Thai Society of Higher Education Institutes on Environment EnvironmentAsiaEnvironmentAsia 24(1) (2009) (2011) 50-54 53-61

Genotoxicity Assessment of Mercuric Chloride in the Marine Fish Therapon jaruba Assessment Cu, Ni and Zn Pollution in the Surface Sediments in the Southern Peninsular MalaysiaNagarajan using Cluster Nagarani, Analysis, Arumugam Ratios Kuppusamy of Geochemical Kumaraguru, Nonresistant Velmurugan to Resistant Janaki Devi Fractions, and Chandrasekaranand Geochemical Archana Indices Devi

Center for Marine and Coastal Studies,Yap. C. SchoolK. and ofWong, Energy, C. H.Environment and Natural Resources, Madurai Kamaraj University, Madurai-625021, India Department of Biology, Faculty of Science, Universiti Putra Malaysia, 43400 UPM, Serdang, Selangor, Malaysia

Abstract Abstract The aim of the present study was to standardize and to assess the predictive value of the cytogenetic analysis by MicronucleusThe intertidal (MN) sediment test in samples fish erythrocytes collected asin aMay biomarker 2007 from for marine 12 sampling environmental sites in thecontamination. southern part Micronucleus of Peninsular frequencyMalaysia, werebaseline determined in erythrocytes for the total was concentrationsevaluated in and of genotoxicCu, Ni and potential Zn and theirof a commonfour geochemical chemical fractions. was determined The total inconcentrations fish experimentally (μg/g dry exposed weight) ofin Cu,aquarium Ni and underZn ranged controlled from 9.48 conditions. to 115.82, Fish 12.95 (Therapon to 36.18 and jaruba 45.35) towere 136.56, exposed respectively. for 96 hrsThe to ratios a single of nonresistant heavy metal to (mercuricresistant fractions chloride). based Chromosomal on geochemical damage analysis was determinedrevealed that as the micronuclei Pantai Lido frequency and Senibong in fishhad >erythrocytes. 1.0, indicating Significant > 50% of theincrease total concentrations in MN frequency of Cu, was Ni observed and Cu were in erythrocytes contributed byof anthropogenicfish exposed tosources. mercuric This chloride.is well complemented Concentration by of the 0.25 cluster ppm analysisinduced thein which highest Pantai MN frequencyLido and Senibong (2.95 micronucleated are clustered cells/1000 together based cells oncompared the three tometals 1 MNcell/1000 clustering pattern. cells in By control using Feanimals). as a normalizing The study element, revealed Cu that found micronucleus at Pantai Lido test, and as Senibong an index showed of cumulative > 1.5 for exposure,the enrichment appears factor to (EF),be a sensitivewhich indicated model thatto evaluate the Cu was genotoxic delivered compounds from non-crustal in fish materialsunder controlled or anthropogenic conditions. origins while all sampling sites showed Ni and Zn may be entirely from crustal materials. Based on the geoaccumulation index Keywords:(Igeo) (Müller, genotoxicity; 1981), similar mercuric pattern chloride; was also micronucleus found for Pantai Lido and Senibong in which again only Cu concentrations ranged from 1-2, indicating ‘moderate pollution’ (Igeo 1 < 2; Class 2).while other sites can be considered as ‘unpolluted’ (Igeo < 0; Class 0) by Cu, Ni and Zn. Ratios of NR/R exhibited better in the assessment of polluted sites while EF and Igeo should be revised according to Malaysian sedimentary characteristics. This study should prompt more biochemical and 1.molecular Introduction studies on the intertidal molluscs from the Straits of Johorelaboratory since and the identifiedfield conditions. two sites Inare 2006 located Soumendra in the Straits of Johore, especially the commercial mussel Perna viridis. et al., made an attempt to detect genetic biomarkers In India, about 200 tons of mercury and its in two fish species, Labeo bata and Oreochromis compoundsKeywords: heavy are metals;introduced surface into sediments; the environment geochemical indices;mossambica, geochemical fractionsby MN and binucleate (BN) annually as effluents from industries (Saffi, 1981). erythrocytes in the gill and kidney erythrocytes Mercuric chloride has been used in agriculture as a exposed to thermal power plant discharge at fungicide,1. Introduction in medicine as a topical antiseptic and Titagarhclustering Thermal patterns Poweraccording Plant, to sites Kolkata, receiving India. anthro- disinfectant, and in chemistry as an intermediate in pogenicThe presentsources. study However, was conducted sometimes to it determine is difficult the productionMetal contamination of other mercury in the sediment compounds. cannot The be theto understand acute genotoxicity the clustering of the heavypatterns metal without compound the cor- simply evaluated by examining metal concentrations relation analysis and other supporting data. Ratios of contamination of aquatic ecosystems by heavy HgCl2 in static systems. Mercuric chloride is toxic, metalsalone (Zhang and pesticides et al., 2009). has gained It should increasing be complemented attention solvablegeochemical in water nonresistant hence it to can resistant penetrate fractions the aquatic (NR/R), inby speciationrecent decades. of the metals. Chronic Sediment exposure is believed to andto be animals.and geochemical Mutagenic indices studies are importantwith native information fish species that accumulationthe final metal ofrepository these chemicals in aquatic in environments aquatic biota and representcan help understand an important the anthropogeniceffort in determining sampling thesites canonly result a minor in fraction tissue ofburdens materials that escapes produce back adverse into the potentialwith different effects sources. of toxic In thisagents. study, This the studynonresistant was effectswater. However, not only inheavy the directly metal levels exposed in sediments organisms, are carried(NR) geochemical out to evaluate fraction the useis a of summation the micronucleus of easily, butoften also analyzed in human based beings. on the total metal content, and testfreely, (MN) leacheable for the estimationor exchangeable of aquatic (EFLE), pollution acid- this Fishproves provides insufficient a suitable understanding model for of monitoring the environ- usingreducible marine and oxidisable-organicedible fish under lab fractions conditions. generated by aquaticmental behaviour genotoxicity and origins and ofwastewater these heavy qualitymetals in sequential extraction technique in the surface sediment, becausethe sediments of its ability(Badri toand metabolize Aston, 1983; xenobiotics Martin et and al., 2.in whichMaterials these andthree methods geochemical fractions are related accumulated1987; Tack and pollutants. Verloo, 1995). A micronucleus Therefore, geochemical assay has to anthropogenic sources (Badri and Aston, 1983; Yap beenstudy used is conducted successfully to estimate in several the nonresistant species (De fractions Flora, 2.1.et al .,Sample 2002). TheCollection last fraction is resistant (R) which is etof metalsal., 1993, which Al-Sabti are related and to Metcalfe, anthropogenic 1995). sources. The natural-origin related. Therefore, the ratio NR/R can micronucleusBesides the statistical (MN) analysis test has on the been metal developed data to ease be potentiallyThe fish species used as selected an indicator for the of presentanthropogenic- study togetherthe interpretation, with DNA-unwindingcalculation of some assaysgeochemical as wasrelated collected sampling from site. Pudhumadam coast of Gulf of perspectiveindices and comparison methods withfor masssediment monitoring quality values of Mannar, The geochemicalSoutheast Coast normalization of India. has Therapon been used clastogenicitycan help in the andassessment genotoxicity of heavy in fishmetal and pollution mussels of jarbuaextensively belongs to obtain to the enrichment order Perciformes factor (EF) of and the to (Dailianisthe study area.et al., 2003). familyassess anthropogenicTheraponidae. contributions The fish species, of metals Therapon in sedi- TheCluster MN analysis tests have is one been of the successfully multivariate used analyses as jarbuaments being(6-6.3 studied cm in length(Acevedo-Figueroa and 4-4.25 g et in al weight)., 2006). athat measure aims to of summarize genotoxic all stress the variables in fish, intounder different both wasIn the selected calculation for the of EF,detection we used of Fegenotoxic as a normalizer effect Yap. C. K. and Wong, C. H. / EnvironmentAsia 4(1) (2011) 53-61 since Fe is also an abundant element in the structure concentrations with pre-industrial levels. The Igeo of clay minerals and several authors have successfully index can assess to the estimation of these pollution used iron to normalize heavy metals contaminants (Feng process. Müller (1981) has distinguished seven classes et al., 1998; Mucha et al., 2003). This is due to Fe in the of Igeo. estuarine sediment is mainly from natural weathering The objective of this study was to assess the con- processes and has been broadly used to normalize the tamination of Cu, Ni and Zn collected from southern metal concentrations in order to reduce particle grain intertidal area of Peninsular Malaysia by comparing to size influence because variations in Fe concentration EF and Igeo values besides the ratios of nonresistant to could be explained by particle grain size differences, resistant geochemical fractions. with fine-grained sediments having high Fe concentra- tions, besides its geochemistry is similar to that of many 2. Materials and Methods trace metals and its natural sediment concentration tends to be uniform. (Daskalakis and O’Connor 1995; Feng The sediment samples for this study were collected et al., 1998). Although there is no such study reported between 8-11 May 2007. It comprised of 12 sampling from Malaysia, at least there is ground for us to use Fe sites located in the southern part of Peninsular Malaysia as a normalizer in this study. Therefore, we believe it (Fig. 1). The positions, sampling dates and site descrip- is reasonable to use Fe to calculate metal enrichment tions are given in Table 3. The top 3-5 cm of surface factor. The assessment criteria for EF used in this study sediments were collected at each sampling site. Each followed those suggested by Zhang and Liu (2002) and sediment sample was put in a plastic bag and frozen Acevedo-Figueroa et al. (2006). Another criterion to prior to analysis. evaluate the heavy metal pollution in the surface sedi- Sediment samples were dried by using an oven ments is the geoaccumulation index (Igeo) by Müller at 60°C until constant dry weights. Later, the dried (1981). This index is to determine and define metals sediments were pounded by using a clean pestle and contamination in sediments, by comparing current mortal and were sieved through a 63 μm stainless steel

Figure 1. Sampling mapFigure showing 1. Sampling the sampling map showing sites for the surface sampling sediments sites for in surface the intertidal sediments area in theof theintertidal southern area part of the of Peninsular Malaysia. southern part of Peninsular Malaysia.

Geochemical fractions of Cu, Ni and Zn in the sediment were obtained by using the Sequential Extraction Technique (SET) which was described by Badri and Aston (1983) and modified by Yap et al. (2002). They are four fractions considered in this method: ‘easily, freely, 54 leacheable or exchangeable’ (EFLE), acid-reducible, oxidisable-organic and resistant fractions. Before the next fractionation, the residue for each fraction was weighed. Residue was rinsed by 20 ml double distilled water. After that it was filtered through a Whatman No.1 (Filter speed: medium) filter paper in a funnel and the filtrate were stored for the next step. For each fraction of the sequential extraction procedure, a blank was employed by using the same procedure to ensure that the samples and chemicals used were free of contamination. After filtration, the sample was determined for Cu, Ni and Zn by using an air-acetylene flame Atomic Absorption Spectrophotometer (AAS), an inorganic analytical instrument made by Perkin-Elmer Model AAnalyst 800. All the data were presented in µg/g dry weight basis. The quality of the method used was checked with a Certified Reference Material (CRM) for Soil (International Atomic Energy Agency, Soil-5, Vienna, Austria). The agreement between the analytical results for the reference material and its certified values for each metal was satisfactory with the percentages of recovery being between 88.3% for Cu (certified value: 77.1 µg/g; measured value: 68.1 µg/g), 106.4% for Ni (Certified value: 13 ȝg/g dry weight and Measured value: 12.3±3.0 ȝg/g dry weight) and 87.8% for Zn (certified value: 368 µg/g; measured value: 323 µg/g). Procedural blanks and quality control samples made from the

3 Yap. C. K. and Wong, C. H. / EnvironmentAsia 4(1) (2011) 53-61 aperture. While sifting, the sieve was shaken vigorously double distilled water. After that it was filtered through to produce homogeneity (Yap et al., 2002) and stored a Whatman No.1 (Filter speed: medium) filter paper in in clean and new plastic bags. a funnel and the filtrate were stored for the next step. The direct aqua-regia method was used to deter- For each fraction of the sequential extraction procedure, mine the concentrations of Cu, Ni and Zn in the dried a blank was employed by using the same procedure to sediment samples. Firstly, about 1 g of each dried ensure that the samples and chemicals used were free sample was weighed and digested in a combination of of contamination. concentrated nitric acid (HNO3, AnalaR grade, BDH After filtration, the sample was determined for

69%) and perchloric acid (HCIO4, AnalaR grade, BDH Cu, Ni and Zn by using an air-acetylene flame Atomic 60%) in the ratio of 4: 1. After that, the tubes were put Absorption Spectrophotometer (AAS), an inorganic into the digestion block at the low temperature (40°C) analytical instrument made by Perkin-Elmer Model for 1 hour and then the temperature was increased to AAnalyst 800. All the data were presented in µg/g dry 140°C for at least 3 hours. The digested samples were weight basis. diluted to 40 ml by double distilled water and filtered The quality of the method used was checked with through Whatman No.1 (filter speed: medium) filter a Certified Reference Material (CRM) for Soil (Interna- paper in a funnel into acid washed pillboxes. They were tional Atomic Energy Agency, Soil-5, Vienna, Austria). stored until metal determination. The agreement between the analytical results for the Geochemical fractions of Cu, Ni and Zn in the reference material and its certified values for each metal sediment were obtained by using the Sequential was satisfactory with the percentages of recovery Extraction Technique (SET) which was described being between 88.3% for Cu (certified value: 77.1 µg/g; by Badri and Aston (1983) and modified by Yap measured value: 68.1 µg/g), 106.4% for Ni (Certified et al. (2002). They are four fractions considered in value: 13 μg/g dry weight and Measured value: 12.3±3.0 this method: ‘easily, freely, leacheable or exchange- μg/g dry weight) and 87.8% for Zn (certified value: 368 able’ (EFLE), acid-reducible, oxidisable-organic and µg/g; measured value: 323 µg/g). Procedural blanks resistant fractions. and quality control samples made from the standard Before the next fractionation, the residue for each solutions for Cu, Ni and Zn were prepared from 1000 fraction was weighed. Residue was rinsed by 20 ml mg/L stock solution (MERCK Titrisol) of each metal,

Table 1. Positions, sampling dates, and descriptions of the sampling sites.

Description of Sampling sites Latitude-North Longtitude-East Sampling date sampling site Malacca-1 (Telok Mas), 2°45.686’ 101°46.769’ 8 May 2007 A small fishing village. A. Malacca Malacca-2 (Crystal Bay), 2° 10.026’ 102° 18.419’ 8 May 2007 Residential development B. Malacca area C. Parit Jawa, Johore 1°57.013’ 102°37.967’ 9 May 2007 Fishing village. Kukup-1 (Offshore), 1°19.507’ 103°26.364’ 9 May 2007 Fish aquaculture area. D. Johore Kukup-2 (Inshore), 1°19.557’ 103°26.503’ 9 May 2007 Restaurant and residential E. Johore area. F. Tg. Kupang, Johore 1°22.766’ 103°38.106’ 10 May 2007 Fishing village. G. Pantai Lido, Johore 1°28.146’ 103°46.895’ 10 May 2007 Urban area. Senibong, Johore 1°29.106’ 103°49.020’ 10 May 2007 Mussel aquaculture, fishing H. and industrial area. Kg. Pasir Puteh-1, Johore 1°29.108’ 103°49.003’ 10 May 2007 Mussel aquaculture, fishing I. and industrial area. Kg. Pasir Puteh-2, Johore 1°29.108’ 103°49.003’ 10 May 2007 Mussel aquaculture, fishing J. and industrial area. K. Kuala Pontian, Pahang 2°45.636’ 103°31.176’ 11 May 2007 A fishing village. L. Nenasi, Pahang 3°08.153’ 103°26.598’ 11 May 2007 Fisherman’s landing site.

Note: The sampling sites followed the alphabets in Fig. 1.

55 standard solutions for Cu, Ni and Zn were prepared from 1000 mg/L stock solution (MERCK Titrisol) of each metal, were analyzed for every five to ten samples in order to check for sample accuracy.

Table 1. Positions, sampling dates, and descriptions of the sampling sites.

Latitude- Longtitude- Sampling Description of Sampling sites North East date sampling site Malacca-1 (Telok Mas), A small fishing A. Malacca 2°45.686’ 101°46.769’ 8 May 2007 village. Malacca-2 (Crystal Residential B. Bay), Malacca 2° 10.026’ 102° 18.419’ 8 May 2007 development area C. Parit Jawa, Johore 1°57.013’ 102°37.967’ 9 May 2007 Fishing village. Kukup-1 (Offshore), D. Johore 1°19.507’ 103°26.364’ 9 May 2007 Fish aquaculture area. Kukup-2 (Inshore), Restaurant and E. Johore 1°19.557’ 103°26.503’ 9 May 2007 residential area. F. Tg. Kupang, Johore 1°22.766’ 103°38.106’ 10 May 2007 Fishing village. G. Pantai Lido, Johore 1°28.146’ 103°46.895’ 10 May 2007 Urban area. Mussel aquaculture, fishing and industrial H. Senibong, Johore 1°29.106’Yap. C. K. and 103°49.020’Wong, C. H. / EnvironmentAsia 10 May 2007 4(1)area. (2011) 53-61 Mussel aquaculture, Kg. Pasir Puteh-1, fishing and industrial I. Johore 1°29.108’ 103°49.003’ 10 May 2007 area. were analyzed for every five to ten samples in order to The presentMussel ranges aquaculture, for Cu, Ni and Zn were lower check Kg.for Pasir sample Puteh-2, accuracy. than those fishingreported and forindustrial polluted drainage sediments J. Johore 1°29.108’ 103°49.003’ 10 May 2007 area. For the statistical analysis, the data were log10 from Peninsular Malaysia (Cu: 1019 µg/g dry weight; K. Kuala Pontian, Pahang 2°45.636’ 103°31.176’ 11 May 2007 A fishing village. (mean + 1) transformed before correlation and cluster Zn: 484 µg/gFisherman's dry weight; landing Ni: 121 µg/g dry weight) (Yap analysisL. Nenasi, in order Pahang to reduce 3°08.153’the variance 103°26.598’(Zar, 1996). 11et May al., 2007 2007). site. To compare with the marine sediments, Cu Note:The Thecluster sampling analysis sites followed based onthe Singlealphabets Linkage in Fig. 1. Euclid- and Zn ranges from this study were higher than those ean distances, on the metal concentrations in the four for the offshore sediments in the Straits of Malacca geochemicalFor the fractionsstatistical analysis,and non-resistant the data were fractions log10 (mean for + 1)(Cu: transformed 0.25-13.8 before µg/g correlation dry weight; Zn: 4.00–79.05 µg/g and cluster analysis in order to reduce the variance (Zar, 1996). The cluster analysis based on Singlethe surface Linkage sediments Euclidean collected distances, fromon the 12 metal sampling concentrations site, indry the weight) four geochemical (Yap et al fractions., 2002, 2003) and a proclaimed andwas non-resistant done by using fractions STATISTICA for the surface 99 edition.sediments collected fromRamsar 12 sampling wetland site, sitewas atdone Tg. by Piai (Cu: 3.43-3.81 µg/g using InSTATISTICA this paper, 99we edition. used a metal enrichment factor dry weight; Zn: 40–43 µg/g dry weight) (Yap et al., In(EF) this accordingpaper, we used to Ergin a metal et enrichmental. (1991), factor as follows: (EF) according to2006a). Ergin et For al. (1991), Ni ranges, as follows: our data was also higher than that for Tg. Piai (Ni: 10-11 µg/g dry weight) (Yap Me ( )Sample et al., 2006a). The present levels of Cu, Ni and Zn were EF Fe also higher than those reported for the Dumai coast in Me ( )Background Indonesia (Cu: 1.61-13.8 µg/g dry weight; Zn: 31–87 Fe µg/g dry weight; Ni: 7–19.9 µg/g dry weight) (Amin where (Me/Fe)Sample is the metal to Fe ratio in the et al., 2009). On the other hand, the Cu and Zn ranges where (Me/Fe)Sample is the metal to Fe ratio in the samples of interest; (Me/Fe)Background is thesamples natural of background interest; (Me/Fe)Backgroundvalue of metal to Fe ratio. is theAs wenatural do not havefrom metal this background study were values lower for than those for the intertidal ourbackground study area, valuewe adopt of themetal values to Fefrom ratio. crust As material, we do which not givessediments 32 µg/g infor the Cu, west 50 µg/g coast for of Peninsular Malaysia (Cu: Ni,have 127 metal µg/g forbackground Zn and 35900 values µg/g forfor Feour (Martin study andarea, Whitfield, we 0.40-315 1983). The µg/g above dry equation weight; Zn: 3-306 µg/g dry weight) usedadopt in the presentvalues study from can crust estimate material, the EF which of Cu, givesNi and 32 Zn in (Yapthe sediments et al., 2002; of the 2003). sampling Our Ni levels were also lower sitesµg/g using for Cu, Fe as50 a µg/gnormalizer for Ni, to 127 correct µg/g for for differences Zn and 35900 in sediments than grain Pearl size River and mineralogy. Estuary (China) (Ni: 13-318 µg/g dry The Igeo index can be calculated by the following equation: µg/g for Fe (Martin and Whitfield, 1983). The above weight) (Li et al., 2007). equation used in the present study can estimate the EF The correlation coefficients between geochemical of Cu, Ni and Zn in the sediments of the sampling sites fractions for Cu, Ni and Zn4 are presented in Table 3. using Fe as a normalizer to correct for differences in It is found that the nonresistant fractions for Cu are sediments grain size and mineralogy. significantly (P< 0.05) related to F1, F2, F3 and F4 The Igeo index can be calculated by the following of the Cu while the nonresistant fractions for Zn and equation: Ni are significantly (P< 0.05) related to F1, F2 and

Cn F3 for both metals. Therefore, the contribution of the Igeo log 2( ) nonresistant fractions for Zn and Ni are expected since 1.5Bn F1, F2 and F3 formed the nonresistant fraction. This where Cn Cn is is the the measured measured concentration concentration of the of theexamined examined metal (n)again in the was sediment well supportedand Bn is the by the ratios of NR/R which geochemicalmetal (n) in background the sediment concentration and Bn isof the metalgeochemical (n). Factor 1.5are is significantlythe background (P<0.05matrix ) correlated with F1, F2 and correctionbackground factor concentration due to lithogenic of the effects. metal Because (n). Factor we did 1.5 not haveF3 the for background Zn and Ni. values This ofwas the not found for Cu in which metalsis the backgroundof interest, same matrix as we correction did in EF calculation,factor due towe litho adopt- theratios earth crustof NR/R values are(Martin significantly and (P<0.05) correlated Whitfield,genic effects. 1983) Because in Igeo calculation. we did not have the background with F1, F3 and F4 for Cu. 3.values Results of andthe Discussionmetals of interest, same as we did in EF The EF and Igeo values for all sampling sites are calculation, we adopt the earth crust values (Martin and given in Table 2. By using Fe as a normalizing element, Whitfield,The total1983) metal in Igeoconcentrations calculation. (ȝg/g dry weight) and theirall respective the sampling geochemical site showed < 1.5 for the Cu EF. Ac- fractions are given in Table 2. The total Cu concentrations of the cordingsediment to samples Zhang ranged and Liu from (2002)’s criterion, sites at Pan- 9.483. Results to 116. andMost Discussionof the sites registered a Cu concentration of lesstai than Lido 40.0, and with Senibong only two had sites exceeded 1.5 value, which having Cu concentrations of higher than 100. The total Zn concentrations of the sediment samples ranged from 45 to 136, with five sites exceeding 100. Thesuggested total Ni concentrations that a significant of the portion of Cu is delivered sediments The totalcollected metal ranged concentrations from 12.9 to 36.2.(μg/g dry weight) from non-crustal materials or non-natural weathering and theirThe respective present ranges geochemical for Cu, Ni fractions and Zn were are lower given than in thoseprocesses reported (Feng for polluted et al., 1998). However, for Ni and Zn, drainageTable 2. sediments The total from Cu Peninsularconcentrations Malaysia of (Cu:the sediment1019 µg/g dryall weight; the sampling Zn: 484 sitesµg/g dryexhibited EF values lower than 1.5, weight;samples Ni: ranged 121 µg/g from dry 9.48 weight) to 116. (Yap Most et al .,of 2007). the sites To compare reg- indicatingwith the marine unpolluted sediments, condition Cu or natural weathering and Zn ranges from this study were higher than those for the offshore sediments in the Straits of Malaccaistered a (Cu: Cu 0.25-13.8concentration µg/g dry of weight;less than Zn: 40.0, 4.00–79.05 with only µg/g dryprocesses. weight) (Yap Based et al on., 2002, the Igeo values, similar pattern is 2003)two sites and havinga proclaimed Cu concentrations Ramsar wetland of site higher at Tg. than Piai (Cu:100. 3.43-3.81 also found µg/g dry for weight; Pantai Zn: Lido 40– and Senibong in which the 43The µg/g total dry Zn weight) concentrations (Yap et al., 2006a).of the Forsediment Ni ranges, samples our data wasCu concentrationsalso higher than thatranged for Tg. from 1-2, indicating ‘moder- Piairanged (Ni: from10-11 45 µg/g to dry136, weight) with (Yapfive etsites al., 2006a).exceeding The present100. atelevels pollution’ of Cu, Ni (Igeo and Zn 1<2; were Class 2).while other sites can alsoThe highertotal Ni than concentrations those reported forof the Dumaisediments coas tcollected in Indonesia (Cu:be considered 1.61-13.8 µg/g as ‘unpolluted’ dry weight; (Igeo<0; Class 0) by Cu, Zn: 31–87 µg/g dry weight; Ni: 7–19.9 µg/g dry weight) (Amin et al., 2009). On the other hand, theranged Cu and from Zn 12.9ranges to from 36.2. this study were lower than those for theNi intertidal and Zn. sediments in the west coast of Peninsular Malaysia (Cu: 0.40-315 µg/g dry weight; Zn: 3-306 µg/g dry weight) (Yap et al., 2002; 2003). Our Ni levels were also lower than Pearl River Estuary (China) (Ni: 13- 318 µg/g dry weight) (Li et al., 2007). The correlation coefficients between geochemical fractions56 for Cu, Ni and Zn are presented in Table 3. It is found that the nonresistant fractions for Cu are significantly (P< 0.05) related to F1, F2, F3 and F4 of the Cu while the nonresistant fractions for Zn and Ni are significantly (P< 0.05) related to F1, F2 and F3 for both metals. Therefore, the contribution of the nonresistant fractions for Zn and Ni are expected since F1, F2 and F3 formed the nonresistant fraction. This again was well supported by the ratios of NR/R which are significantly (P<0.05) correlated with F1, F2 and F3 for Zn and Ni. This was not found for Cu in which ratios of NR/R are significantly (P<0.05) correlated with F1, F3 and F4 for Cu. The EF and Igeo values for all sampling sites are given in Table 2. By using Fe as a normalizing element, all the sampling site showed < 1.5 for the Cu EF. According to Zhang and Liu (2002)’s criterion, sites at Pantai Lido and Senibong had exceeded 1.5 value, which suggested that a significant portion of Cu is delivered from non-crustal materials or non-natural weathering processes (Feng et al., 1998). However, for Ni and Zn, all the sampling sites exhibited EF values lower than 1.5, indicating unpolluted condition or natural weathering processes. Based on the Igeo values, similar pattern is also found for Pantai Lido and Senibong in which the Cu concentrations ranged from 1-2, indicating ‘moderate pollution’ (Igeo 1<2; Class 2).while other sites can be considered as ‘unpolluted’ (Igeo<0; Class 0) by Cu, Ni and Zn.

5 Yap. C. K. and Wong, C. H. / EnvironmentAsia 4(1) (2011) 53-61 -1.697 Igeo -1.474 -1.43 -2.456 -1.55 -2.512 -0.97 -1.62 -1.44 -1.30 1.18 1.27 -0.19 -0.32 -2.34 Igeo -1.57 -1.762 -1.621 -2.154 -1.504 -2.055 -2.534 -1.147 -1.052 0.351 EF 0.575 0.51 0.222 0.46 0.261 0.88 0.51 0.64 0.75 4.15 3.36 1.00 1.28 0.24 EF 0.50 0.404 0.440 0.385 0.551 0.416 0.318 0.824 0.672 47353 Fe 33742 39277 44218 39772 36119 31390 34450 31129 29206 29511 38664 47353 33742 44218 Fe 36119 39277 39772 31390 34450 31129 29206 29511 38664 0.25 SE 0.23 0.05 0.82 0.26 0.56 0.29 0.11 0.40 0.46 0.62 2.51 0.56 0.25 0.19 SE 0.18 0.21 0.27 0.16 0.69 0.30 0.66 0.51 0.59 23.14 AR 27.01 17.81 13.67 16.35 13.15 24.52 15.65 17.73 19.46 109.06 115.82 42.20 38.52 9.48 AR 16.18 22.11 24.38 16.85 26.45 18.05 12.95 33.87 36.18 27.91 SUM 39.85 16.46 16.34 15.35 18.59 23.44 13.87 16.33 18.23 123.93 122.83 42.73 43.48 7.46 SUM 15.30 24.08 27.62 22.43 33.58 22.66 16.46 45.56 43.81 1.17 NR/R 1.04 0.20 0.23 0.17 0.23 0.38 0.14 0.30 0.32 1.37 1.37 0.52 0.36 0.36 NR/R 0.32 0.38 0.29 0.45 0.51 0.56 0.75 2.56 2.72 15.03 NR 20.27 2.72 3.06 2.25 3.47 6.42 1.69 3.73 4.43 71.57 71.08 14.53 11.53 1.96 NR 3.73 6.63 6.23 6.92 11.28 8.15 7.08 32.77 32.02 0.93 SE 2.88 0.06 1.43 1.00 0.77 2.15 0.49 0.05 0.30 2.43 0.93 0.66 0.18 0.83 SE 0.15 0.46 1.63 1.05 0.83 0.63 0.48 0.43 0.33 12.88 F4 19.57 13.74 13.28 13.09 15.11 17.01 12.18 12.60 13.80 52.36 51.75 28.20 31.95 5.50 F4 11.58 17.45 21.39 15.51 22.30 14.51 9.39 12.80 11.78 0.18 SE 0.68 0.16 0.00 0.15 0.02 0.45 0.01 0.42 0.21 3.09 2.72 0.02 0.73 0.18 SE 0.39 0.10 0.05 0.16 0.01 0.10 0.20 0.13 0.58 12.85 F3 16.66 2.03 2.48 1.67 2.91 5.75 1.01 3.07 3.88 69.64 69.54 13.71 10.38 1.50 F3 3.02 5.00 4.65 5.58 9.31 6.68 6.01 29.94 28.17 SE 0.00 0.01 0.06 0.01 0.03 0.03 0.03 0.02 0.02 0.00 0.00 0.01 0.03 0.02 SE 0.00 0.02 0.00 0.08 0.01 0.02 0.04 0.04 0.11 0.01 F2 2.65 0.44 0.34 0.44 0.34 0.45 0.51 0.49 0.40 0.63 0.55 0.53 0.77 0.38 F2 0.40 1.05 0.97 0.81 1.32 0.94 0.65 1.71 2.63 1.45 SE 0.02 0.01 0.03 0.02 0.17 0.00 0.00 0.01 0.01 0.02 0.01 0.00 0.00 0.00 SE 0.11 0.03 0.04 0.01 0.00 0.00 0.02 0.06 0.01 0.05 F1 0.97 0.25 0.24 0.15 0.23 0.23 0.17 0.17 0.15 1.30 0.99 0.29 0.38 0.08 F1 0.30 0.58 0.61 0.53 0.65 0.53 0.41 1.11 1.23 0.73 Cu Kg. Pasir Puteh-2 Malacca-1 Kuala Pontian Malacca-2 Nenasi Parit Jawa Kukup-1 Kukup-2 Tg. Kupang Pantai Lido Senibong Kg. Pasir Puteh-1 Kg. Pasir Puteh-2 Kuala Pontian Ni Nenasi Malacca-1 Malacca-2 Parit Jawa Kukup-1 Kukup-2 Tg. Kupang Pantai Lido Senibong Kg. Pasir Puteh-1 J. A. K. B. L. C. D. E. F. G. H. I. J. K. L. A. B. C. D. E. F. G. H. I. Table 2. Concentrations (µg/g dry weight) of Cu, Ni and Zn in the four geochemical fractions, ratios (NR/R) of nonresistant (NR) to resistant (R) fractions, enrichment factor (EF) factor enrichment fractions, (R) resistant to (NR) nonresistant of (NR/R) ratios fractions, geochemical four the in Zn and Ni Cu, of weight) dry (µg/g Concentrations 2. Table and index of geoaccumulation (Igeo) in the surface intertidal sediments collected from southern part Peninsular Malaysia.

57 Yap. C. K. and Wong, C. H. / EnvironmentAsia 4(1) (2011) 53-61 Igeo -1.166 -1.323 -1.016 -0.533 -1.105 -1.422 -0.593 -0.496 -0.645 -0.550 -2.071 -1.744 EF 0.611 0.541 0.848 1.080 0.804 0.688 1.209 0.987 0.727 1.089 0.290 0.445 Fe 39277 39772 31390 34450 31129 29206 29511 38664 47353 33742 44218 36119 SE 1.16 0.83 0.85 1.38 1.10 0.91 0.18 2.34 1.27 1.02 0.41 0.69 AR 84.91 76.16 94.21 131.65 88.57 71.11 126.34 135.08 121.83 130.13 45.35 56.89 SUM 98.86 89.77 101.78 148.59 97.07 75.87 102.93 111.54 114.13 125.56 51.39 65.24 NR/R 0.35 0.39 0.61 0.52 0.64 1.03 1.82 2.05 1.12 0.64 0.35 0.45 NR 25.82 25.19 38.73 50.84 37.87 38.42 66.44 74.92 60.22 48.85 13.31 20.29 SE 0.82 1.58 3.54 0.29 0.15 1.42 0.11 0.04 0.07 0.09 1.66 0.69 F4 73.05 64.58 63.06 97.76 59.20 37.45 36.49 36.63 53.91 76.71 38.08 44.95 SE 1.77 0.93 0.83 0.27 0.95 0.47 0.07 0.21 0.93 0.04 0.39 0.52 F3 17.66 17.52 25.83 33.98 27.83 27.07 43.18 39.24 40.10 44.18 9.46 13.43 SE 0.26 0.15 0.11 0.90 0.11 0.33 0.14 0.01 1.00 0.74 0.19 0.19 F2 8.15 7.67 12.89 16.85 10.04 11.35 21.75 31.00 20.12 3.78 3.85 6.76 SE 0.00 0.00 0.00 0.00 0.00 0.00 0.05 0.01 0.00 0.34 0.00 0.09 F1 0.00 0.00 0.00 0.00 0.00 0.00 1.51 4.67 0.00 0.89 0.00 0.10 Zn Malacca-1 Malacca-2 Parit Jawa Kukup-1 Kukup-2 Tg. Kupang Pantai Lido Senibong Kg. Pasir Puteh-1 Kg. Pasir Puteh-2 Kuala Pontian Nenasi

A. B. C. D. E. F. G. H. I. J. K. L. Note: F1= easily, freely, leacheable or exchangeable, F2= acid-reducible, F3= oxidiable-organic, F4= resistant. SE= standard error. AR= direct digestion by using aqua-regia method; method; aqua-regia using by digestion direct AR= error. standard SE= resistant. F4= oxidiable-organic, F3= acid-reducible, F2= exchangeable, or leacheable freely, easily, F1= Note: SUM= summation of F1, F2, F3 and F4.

58 Yap. C. K. and Wong, C. H. / EnvironmentAsia 4(1) (2011) 53-61

The ratios of NR/R values are also given in Table 2. Finally, based on the cluster analysis in Fig. 2, it can Major contribution (> 50%) of anthropogenic sources, be summarized that sites at Pantai Lido and Senibong as indicated by ratio NR/R >1.0, is shown at Pantai Lido are grouped into a same sub-cluster, indicating that and Senibong for Cu. For Ni, strongly contribution by these two sampling sites received more contamination anthropogenic sources (NR/R >2.0) was evidenced at of Cu, Ni and Zn as shown in Table 3. Since these sites Pantai Lido and Senibong while two sites at Kg. Pasir also had higher (>50%) non-resistant fractions of these Puteh also indicated major contribution of anthropo- metals than the resistant ones. These localized elevated genic inputs (NR/R>1.0). Lastly, for Zn, ratios NR/ metal concentrations could be related to point source R>1.0 were also found at Tg. Kupang, Pantai Lido, discharges related to rapid urbanization and industrial Senibong and Kg. Pasir Puteh-1. Therefore, comparing development at the two sites. The rest of sites are clus- among ratios of NR/R, EF and Igeo, it seems that ratios tered differently, indicating lesser contamination by Cu, of NR/R can better categorize the polluted sites by Zn Ni and Zn. Therefore, the dendrogram based on cluster and Ni contributed by anthropogenic sources while a analysis supports the findings by using the assessment thorough revision on EF and Igeo calculations for Zn of ratios of NR/R and EF. and Ni are needed in order to suit local sedimentary In order to estimate possible environmental con- characteristics. sequences of the analyzed metals at the studied sites,

Table 3. Correlation coefficients between geochemical fractions for each metal. N= 12. Based on log10 (mean +1).

Cu F1 F2 F3 F4 NR NR/R F1 1.00 0.57 0.93 0.87 0.94 0.93 F2 1.00 0.60 0.76 0.61 0.43 F3 1.00 0.93 0.99 0.95 F4 1.00 0.93 0.80 NR 1.00 0.96 NR/R 1.00 SUM AR Zn F1 F2 F3 F4 NR NR/R F1 1.00 0.48 0.51 -0.41 0.60 0.79 F2 1.00 0.62 -0.21 0.78 0.78 F3 1.00 0.14 0.97 0.70 F4 1.00 0.03 -0.56 NR 1.00 0.80 NR/R 1.00 SUM AR Ni F1 F2 F3 F4 NR NR/R F1 1.00 0.96 0.95 0.04 0.97 0.87 F2 1.00 0.90 0.14 0.92 0.77 F3 1.00 -0.16 0.99 0.95 F4 1.00 -0.12 -0.42 NR 1.00 0.94 NR/R 1.00 SUM AR Note: values in bold are significantly correlated at p < 0.05. F1= easily, freely, leacheable or exchangeable, F2= acid-reducible, F3= oxidiable-organic, F4= resistant, AR= digestion based on direct aquaegia method.

59 In order to estimate possible environmental consequences of the analyzed metals at the studied sites, concentrations of Cu, Ni and Zn were compared to the Sediment Quality Guidelines of Effect Range Low (ERL) and Effect Range Median (ERM) proposed by Long et al. (1995, 1997). For Cu, all sampling sites except for Pantai Lido, Senibong, Kg. Pasir Puteh-1 and -2, were still below the ERL value (34.0) and the ERM value (270 ȝg/g). In particular, Pantai Lido and Senibong also exceeded the ERM values (270 ȝg/g). For Ni, only five sampling sites were still below the ERL value (20.9 ȝg/g) and the ERM value (51.6 ȝg/g) while the other seven sites, including the above four mentioned sites, exceeded Ni ERL but were still below Ni ERL value. Zn concentrations in all stations (45-136 ȝg/g) were still well below the values for ERL (150 ȝg/g) and ERM (410 ȝg/g). Nonetheless, the comparison of the present data with other established sediment quality values (SQV) is not included in this paper because most of the SQVs are establishedYap. based C. K.on and localized Wong, C. sedimentary H. / EnvironmentAsia characteristics. 4(1) (2011) This 53-61 is argued that the assessment of heavy metal pollution based these non-Malaysian SQVs could be misleading and questionable.

Tree Diagram for 12 Cases Single Linkage Euclidean distances

Malacca-1 Malacca-2 Kukup-2 Tg.Kupang P.Jawa Nenasi K.Pontian Kukup-1 Kg.P.Puteh-1 Kg.P. Puteh-2 Pantai Lido Senibong

0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 Linkage Distance Figure 2. Cluster analysis based on Single Linkage Euclidean distances, on the Cu, Ni and Zn concentrations in the four Figure 2. Cluster analysis based on Single Linkage Euclidean distances, on the Cu, Ni and Zn geochemical fractions and non-resistant fractions for the surface sediments collected from 12 sampling sites, based on concentrations in the four geochemical fractions and non-resistant fractions for the surface sediments log10(mean +1) transformed data. collected from 12 sampling sites, based on log10(mean +1) transformed data. concentrations of Cu, NiSince and all Zn these were identified compared sampling to the sites4. Conclusions are located in the Straits of Johore, this finding Sediment Qualityshould Guidelines be of much of relevance Effect Range on the Lowcommercial aquaculture of the green-lipped mussel Perna (ERL) and Effectviridis Range (Yap Median et al., 2006b), (ERM) inproposed which they by are massive-culturedThe concentrations by long-lined of Cu, Ni techniqueand Zn in most on both surface Long et al. (1995,sites of1997). the Johore For Cu, Causeway. all sampling Since sitespreviousl sedimentsy Pantai collectedLido was from reported the southern as a relatively part of Peninsular except for Pantaiuncontaminated Lido, Senibong, site Kg. based Pasir on Puteh-1 our sampling and Malaysiadone in January were found 2000 to(Yap be loweret al., 2002;than the 2003), heavy this metal study should prompt more biochemical and molecular studies on the intertidal molluscs from the -2, were still below the ERL value (34.0) and the ERM levels reported by other studies from Malaysia and the Straits of Johore. value (270 μg/g). In particular, Pantai Lido and Seni- surrounding region. However, Pantai Lido and Seni- bong also exceeded4. Conclusions the ERM values (270 μg/g). For Ni, bong had elevated Cu levels that were higher than the only five sampling sites were still below the ERL value other sites in this study. Sampling sites at Pantai Lido (20.9 μg/g) and the ERMThe valueconcentrations (51.6 μg/g) of Cu,while Ni theand Znand in Senibongmost surface were sediments found as collected contaminated from the sites based other seven sites,southern including part ofthe Peninsular above four Malaysia mentioned were foundon the to ratios be lower of NR/R than andthe heavyEF values. metal From levels monitoring reported sites, exceededby Ni other ERL studies but were from still Malaysia below andNi ERLthe surrou pointnding of region.view, further However, biomonitoring Pantai Lido studies and Senibong should be value. Zn concentrationshad elevated in Cu all levelsstations that (45-136 were higher μg/g) than continuously the other sites done in this in thestudy. future. Sampling sites at Pantai were still well below the values for ERL (150 μg/g) and ERM (410 μg/g). Nonetheless, the comparison of Acknowledgement the present data with other established sediment quality 9 values (SQV) is not included in this paper because most The authors wish to acknowledge the financial support of the SQVs are established based on localized sedimen- provided through the Research University Grant Scheme (RUGS), [Vote no.: 91986], by Universiti Putra Malaysia. tary characteristics. This is argued that the assessment of heavy metal pollution based these non-Malaysian References SQVs could be misleading and questionable. Since all these identified sampling sites are located Acevedo-Figueroa D, Jimenez BD, Rodrý´guez-Sierra CJ. in the Straits of Johore, this finding should be of much Trace metals in sediments of two estuarine lagoons from relevance on the commercial aquaculture of the green- Puerto Rico. Environmental Pollution 2006; 141: lipped mussel Perna viridis (Yap et al., 2006b), in which 336–42. they are massive-cultured by long-lined technique on Amin B, Ismail A, Arshad A, Yap CK, Kamarudin MS. both sites of the Johore Causeway. Since previously Anthropogenic impacts on heavy metal concentrations Pantai Lido was reported as a relatively uncontaminated in the coastal sediments of Dumai, Indonesia. Envi- ronmental Monitoring and Assessment 2009; 148(1-4): site based on our sampling done in January 2000 (Yap 291-305. et al., 2002; 2003), this study should prompt more Badri MA, Aston SR. Observation on heavy metal biochemical and molecular studies on the intertidal geochemical associations in polluted and nonpolluted molluscs from the Straits of Johore. estuarine sediments. Environmental Pollution (Series B), 1983; 6: 181-93.

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