This study investigated the level of bisphenol A (BPA) in surface water used as potable water, drinking water (tap and bottled mineral water) and human plasma in the Langat River basin, Malaysia. BPA was present in 93% of the surface water samples at levels ranging from below limit of quantification (LOQ; 1.3 ng/L) to 215 ng/L while six fold higher levels were detected in samples collected near industrial and municipal sewage treatment plant outlets. Low levels of BPA were detected in most of the drinking water samples. BPA in tap water ranged from 3.5 to 59.8 ng/L with the highest levels detected in samples collected from taps connected to PVC pipes and water filter devices. Bottled mineral water had lower levels of BPA (3.3±2.6 ng/L) although samples stored in poor storage condition had significantly higher levels (11.3±5.3 ng/L). Meanwhile, only 17% of the plasma samples had detectable levels of BPA ranging from 0.81 to 3.65 ng/mL. The study shows that BPA is a ubiquitous contaminant in surface, tap and bottled mineral water. However, exposure to BPA from drinking water is very low and is less than 0.01% of the tolerable daily intake (TDI).
The application of organophosphorus pesticides (OPPs) increased gradually because of the rise in global food demand that triggered the agriculture sector to increase the production, leading to OPP residues in the surface water. This study elucidated the presence of OPPs and estimated its ecological risk in the riverine ecosystem of the urbanised Linggi River, Negeri Sembilan, Malaysia. The OPP concentration in surface water was determined using solid-phase extraction method and high-performance liquid chromatography coupled with diode array detection. Further, the ecological risk was estimated by using the risk quotient (RQ) method. The three OPPs, i.e. chlorpyrifos, diazinon, and quinalphos were detected with mean concentrations of 0.0275 µg/L, 0.0328 µg/L, and 0.0362 µg/L, respectively. The OPPs were at high risk (in general and worst cases) under acute exposure. The estimated risk of diazinon was observed as medium for general (RQm = 0.5857) and high for worst cases (RQex = 4.4678). Notably, the estimated risk for chlorpyrifos was high for both general and worst cases (RQm = 1.9643 and RQex = 11.5643) towards the aquatic ecosystem of the Linggi River. Chronic risk of quinalphos remains unknown because of the absence of toxicity endpoints. This study presented clear knowledge regarding OPP contamination and possible risk for aquatic ecosystems. Hence, OPPs should be listed as one of the main priority contaminants in pesticide mitigation management in the future.
A novel sol-gel hybrid methyltrimethoxysilane-tetraethoxysilane (MTMOS-TEOS) was produced and applied as sorbent for solid phase extraction (SPE). Five selected organophosphorus pesticides (OPPs) were employed as model compounds to evaluate the extraction performance of the synthesized sol-gel organic-inorganic hybrid MTMOS-TEOS. Analysis was performed using gas chromatography-mass spectrometry. Several important SPE parameters were optimized. Under the optimum extraction conditions, the method using the sol-gel organic-inorganic hybrid MTMOS-TEOS as SPE sorbent showed good linearity in the range of 0.001-1 μg L(-1), good repeatability (RSD 2.1-3.1%, n=5), low limits of detection at S/N=3 (0.5-0.9 pg mL(-1)) and limit of quantification (1-3 pg mL(-1), S/N=10). The performance of the MTMOS-TEOS SPE was compared to commercial C18 Supelclean SPE since C18 SPE is widely used for OPPs. The MTMOS-TEOS SPE method LOD was 500-600 × lower than the LOD of commercial C18 SPE. The LOD achieved with the sol-gel organic-inorganic hybrid MTMOS-TEOS SPE sorbent allowed the detection of these OPPs in drinking water well below the level set by European Union (EU) at 0.1 μg L(-1) of each pesticides. The developed MTMOS-TEOS SPE method was successfully applied to real sample analysis of the selected OPPs from several water samples and its application extended to the analysis of several fruits samples. Excellent recoveries and RSDs of the OPPs were obtained from the various water samples (recoveries: 97-111%, RSDs 0.4-2.8%, n=3) and fruit samples (recoveries: 96-111%), RSDs 1-4%, n=5) using the sol-gel organic-inorganic hybrid MTMOS-TEOS SPE sorbent. Recoveries and RSDs of OPPs from river water samples and fruit samples using C18 Supelclean SPE sorbent were 91-97%, RSD 0.9-2.6, n=3 and 86-96%, RSD 3-8%, n=5, respectively). The novel sol-gel hybrid MTMOS-TEOS SPE sorbent demonstrate the potential as an alternative inexpensive extraction sorbent for OPPs with higher sensitivity for the OPPs.
Cyclodextrin-ionic liquid polymer (βCD-BIMOTs-TDI) is a new class of macroporous material and has great potential to be used as an SPE adsorbent material for extraction of phenols in river water samples. Six phenols, as model analytes, were extracted on a βCD-BIMOTs-TDI SPE cartridge, and then, eluted with 2 mL of methanol containing 1% acetic acid. The optimum experimental condition was 15 mL of sample volume (sample at pH 6) and 2 mL of methanol containing 1% acetic acid as an eluent solvent. The eluent concentration was determined by using Gas Chromatography-Flame Ionization Detector (GC-FID). Under optimized condition, high sensitivity (detection limits 0.23-0.35 µg/L) and good recoveries (87-116%) were achieved with satisfactory relative standard deviation (RSD) (0.1-1.7%). The developed βCD-BIMOTs-TDI-SPE was then compared with other adsorbents, and the obtained results showed that the βCD-BIMOTs-TDI exhibited higher extraction recovery due to the unique structure and properties. Finally, the βCD-BIMOTs-TDI was applied as a solid phase extraction sorbent for phenols determination under optimized condition, in river and tap waters, prior to the GC-FID separation.
This study investigates the applicability of multivariate statistical techniques including cluster analysis (CA), discriminant analysis (DA), and factor analysis (FA) for the assessment of seasonal variations in the surface water quality of tropical pastures. The study was carried out in the TPU catchment, Kuala Lumpur, Malaysia. The dataset consisted of 1-year monitoring of 14 parameters at six sampling sites. The CA yielded two groups of similarity between the sampling sites, i.e., less polluted (LP) and moderately polluted (MP) at temporal scale. Fecal coliform (FC), NO3, DO, and pH were significantly related to the stream grouping in the dry season, whereas NH3, BOD, Escherichia coli, and FC were significantly related to the stream grouping in the rainy season. The best predictors for distinguishing clusters in temporal scale were FC, NH3, and E. coli, respectively. FC, E. coli, and BOD with strong positive loadings were introduced as the first varifactors in the dry season which indicates the biological source of variability. EC with a strong positive loading and DO with a strong negative loading were introduced as the first varifactors in the rainy season, which represents the physiochemical source of variability. Multivariate statistical techniques were effective analytical techniques for classification and processing of large datasets of water quality and the identification of major sources of water pollution in tropical pastures.
Multivariate statistical techniques such as multivariate analysis of variance (MANOVA) and discriminant analysis (DA) were applied for analyzing the data obtained from two rivers in the Penang State of Malaysia for the concentration of heavy metal ions (As, Cr, Cd, Zn, Cu, Pb, and Hg) using a flame atomic absorption spectrometry (F-AAS) for Cr, Cd, Zn, Cu, Pb, As and cold vapor atomic absorption spectrometry (CV-AAS) for Hg. The two locations of interest with 20 sampling points of each location were Kuala Juru (Juru River) and Bukit Tambun (Jejawi River). MANOVA showed a strong significant difference between the two rivers in terms of heavy metal concentrations in water samples. DA gave the best result to identify the relative contribution for all parameters in discriminating (distinguishing) the two rivers. It provided an important data reduction as it used four parameters (Zn, Pb, Cd and Cr) affording 100% correct assignations. Results indicated that the two rivers were different in terms of heavy metals concentrations in water, and the major difference was due to the contribution of Zn. A negative correlation was found between discriminate functions (DF) and Cr and As, whereas positive correlation was exhibited with other heavy metals. Therefore, DA allowed a reduction in the dimensionality of the data set, delineating a few indicator parameters responsible for large variations in heavy metal concentrations. Correlation matrix between the parameters exhibited a strong evidence of mutual dependence of these metals.
Rapid socioeconomic development in the Linggi River Basin has contributed to the significant increase of pollution discharge into the Linggi River and its adjacent coastal areas. The toxic element contents and distributions in the sediment samples collected along the Linggi River were determined using neutron activation analysis (NAA) and inductively coupled plasma-mass spectrometry (ICP-MS) techniques. The measured mean concentration of As, Cd, Pb, Sb, U, Th and Zn is relatively higher compared to the continental crust value of the respective element. Most of the elements (As, Cr, Fe, Pb, Sb and Zn) exceeded the freshwater sediment quality guideline-threshold effect concentration (FSQG-TEC) value. Downstream stations of the Linggi River showed that As concentrations in sediment exceeded the freshwater sediment quality guideline-probable effect concentration (FSQG-PEC) value. This indicates that the concentration of As will give an adverse effect to the growth of sediment-dwelling organisms. Generally, the Linggi River sediment can be categorised as unpolluted to strongly polluted and unpolluted to strongly to extremely polluted. The correlation matrix of metal-metal relationship, principle component analysis (PCA) and cluster analysis (CA) indicates that the pollution sources of Cu, Ni, Zn, Cd and Pb in sediments of the Linggi River originated from the industry of electronics and electroplating. Elements of As, Cr, Sb and Fe mainly originated from motor-vehicle workshops and metal work, whilst U and Th originated from natural processes such as terrestrial runoff and land erosion.
An analytical method that facilitated the analysis of 11 pharmaceuticals residue (caffeine, prazosin, enalapril, carbamazepine, nifedipine, levonorgestrel, simvastatin, hydrochlorothiazide, gliclazide, diclofenac-Na, and mefenamic acid) with a single pre-treatment protocol was developed. The proposed method included an isolation and concentration procedure using solid phase extraction (Oasis HLB), a separation step using high-performance liquid chromatography, and a detection procedure that applies time-of-flight mass spectrometry. The method was validated for drinking water (DW), surface water (SW), sewage treatment plant (STP) influent and effluent, and hospital (HSP) influent and effluent. The limits of quantification were as low as 0.4, 1.6, 5, 3, 2.2 and 11 ng/L in DW, SW, HSP influent and effluent, STP effluent, and STP influent, respectively. On average, good recoveries higher than 75% were obtained for most of the target analytes in all matrices. Matrix effect was evaluated for all samples matrices. The proposed method successfully determined and quantified the target compounds in raw and treated wastewater of four STPs and three hospitals in Malaysia, as well as in two SW sites. The results showed that a number of the studied compounds pose moderate to high persistency in sewage treatment effluents as well as in the recipient rivers, namely; caffeine, simvastatin, and hydrochlorothiazide. Ten out of 11 compounds were detected and quantified in 13 sampling points. Caffeine was detected with the highest level, with concentrations reaching up to 9099 ng/L in STP influent.
Pollutants such as human pharmaceuticals and synthetic hormones that are not covered by environmental legislation have increasingly become important emerging aquatic contaminants. This paper reports the development of a sensitive and selective multi-residue method for simultaneous determination and quantification of 23 pharmaceuticals and synthetic hormones from different therapeutic classes in water samples. Target pharmaceuticals include anti-diabetic, antihypertensive, hypolipidemic agents, β2-adrenergic receptor agonist, antihistamine, analgesic and sex hormones. The developed method is based on solid phase extraction (SPE) followed by instrumental analysis using liquid chromatography-electrospray ionization-tandem mass spectrometry (LC-ESI-MS/MS) with 30 min total run time. River water samples (150 mL) and (sewage treatment plant) STP effluents (100 mL) adjusted to pH 2, were loaded into MCX (3 cm(3), 60 mg) cartridge and eluted with four different reagents for maximum recovery. Quantification was achieved by using eight isotopically labeled internal standards (I.S.) that effectively correct for losses during sample preparation and matrix effects during LC-ESI-MS/MS analysis. Good recoveries higher than 70% were obtained for most of target analytes in all matrices. Method detection limit (MDL) ranged from 0.2 to 281 ng/L. The developed method was applied to determine the levels of target analytes in various samples, including river water and STP effluents. Among the tested emerging pollutants, chlorothiazide was found at the highest level, with concentrations reaching up to 865 ng/L in STP effluent, and 182 ng/L in river water.
In this study, the microcrystalline cellulose/metal-organic framework 199 hybrid (MCC/MOF-199) was applied as sorbent for the dispersive micro-solid phase-extraction (D-μSPE) of chlorophenols. The D-μSPE method combined with high-performance liquid chromatography- ultraviolet detection (HPLC-UV) was employed to determine of four chlorophenols including 2-chlorophenol (2-CP), 4-chlorophenol (4-CP), 2,3-dichlorophenol (2,3-DCP), and 2,5-dichlorophenol (2,5-DCP) in aqueous. The main parameters of the D-μSPE process that influence the extraction (i.e. the amount of sorbent, elution condition, extraction time, and pH) were investigated and optimized. Based on the outputs, the presence of MCC on the surface of MOF-199 leads to improve the properties of MOF-199 and the MCC/MOF-199 has the highest sorption capacity, durability, and porosity in comparison with MCC and MOF-199. According to the validation study at the optimized conditions, the linearity for the analytes was achieved in the range from 0.1 to 200 ng mL-1 for 2-CP and 4-CP and 0.15 to 200 ng mL-1 for 2,3-DCP and 2,5-DCP with correlation coefficients between 0.9928 and 0.9965. The limits of detection calculated at S/N=3 were in the range of 0.03-0.05 ng mL-1. Besides, the relative standard deviations (RSDs) for three spiking levels (0.2, 10,100 ng mL-1) do not exceed 6.8% and extraction recoveries are between 81.0% and 88.3%. Finally, the D-μSPE-HPLC-UV method was successfully applied to the analysis of CPs in real water samples (mineral, river and wastewater samples) with good recoveries (95.8 to 99.5%) and satisfactory precisions (RSD < 6.8%).
Muscle, stomach and gill from four dominant fish species, Mytus nemurus, Pristolepis fasciata, Ompok bimaculatus and Osteochilus hasseltii, caught from Bebar peat swamp forest river were analyzed for mercury (Hg). The concentration of Hg was measured with a fast and sensitive Flow Injector Mercury Spectrometer (FIMS). The average Hg concentration of all species caught was 0.169 microg g(-1) dry weights, lower than a limit for human consumption recommended by the World Health Organization, 0.5 microg g(-1) dry weights. The mean concentration of Hg was relatively high in stomach (0.28 +/- 0.12 microg g(-1) dry weights) followed by gill (0.17 +/- 0.06 microg g(-1) dry weights) and lowest in muscle (0.05 +/- 0.02 microg g(-1) dry weights). The positive relationship of Hg with fish length and weight suggesting that the accumulation of Hg were formed in the fish.
Since landfilling is the common method of waste disposal in Malaysia, river water is greatly exposed to the risk of contamination from leachate unless proper leachate management is carried out. In this study, leachates from three different types of landfills, namely active uncontrolled, active controlled and closed controlled, were characterized, and their relationships with river water chemistry were examined monthly for a year. The influence of leachate on river water chemistry from each type of landfill depended on many factors, including the presence of a leachate control mechanism, leachate characteristics, precipitation, surface runoff and the applied treatment. The impact of leachate from an active uncontrolled landfill was the highest, as the organic content, NH(4)(+)-N, Cd and Mn levels appeared high in the river. At the same time, influences of leachate were also observed from both types of controlled landfills in the form of inorganic nitrogen (NH(4)(+)-N, NO(3)(-)-N and NO(2)(-)-N) and heavy metals (Fe, Cr, Ni and Mn). Improper treatment practice led to high levels of some contaminants in the stream near the closed controlled landfill. Meanwhile, the active controlled landfill, which was located near the coastline, was exposed to the risk of contamination resulting from the pyrite oxidation of the surrounding area.
Male-specific RNA coliphages (FRNA) have been recommended as indicators of fecal contamination and of the virological quality of water. In this study, 16 river water and 183 animal fecal samples were examined for the presence of FRNA coliphages by a plaque assay using Salmonella typhimurium WG49 and WG25 to differentiate between male-specific and somatic phages, a RNase spot test to differentiate between DNA and RNA phages and a reverse transcriptase-polymerase chain reaction (RT-PCR) for the specific identification of FRNA phages. The overall recovery rate for F-specific coliphages was 8.0%. (4.4% from animal fecal matter and 50% from river water samples). Plaque counts were generally low (< 6 x 10(2) pfu per g feces or ml water), with FRNA (6.5%) and Male-specific DNA coliphages (FDNA) (7.0%) phages occurring at almost equal frequencies. The RT-PCR was positive in all FRNA plaques and was able to identify FRNA phages in mixed populations of FRNA, FDNA and somatic phages.
Long-term (21-30 years) erosional responses of rainforest terrain in the Upper Segama catchment, Sabah, to selective logging are assessed at slope, small and large catchment scales. In the 0.44 km(2) Baru catchment, slope erosion measurements over 1990-2010 and sediment fingerprinting indicate that sediment sources 21 years after logging in 1989 are mainly road-linked, including fresh landslips and gullying of scars and toe deposits of 1994-1996 landslides. Analysis and modelling of 5-15 min stream-suspended sediment and discharge data demonstrate a reduction in storm-sediment response between 1996 and 2009, but not yet to pre-logging levels. An unmixing model using bed-sediment geochemical data indicates that 49 per cent of the 216 t km(-2) a(-1) 2009 sediment yield comes from 10 per cent of its area affected by road-linked landslides. Fallout (210)Pb and (137)Cs values from a lateral bench core indicate that sedimentation rates in the 721 km(2) Upper Segama catchment less than doubled with initially highly selective, low-slope logging in the 1980s, but rose 7-13 times when steep terrain was logged in 1992-1993 and 1999-2000. The need to keep steeplands under forest is emphasized if landsliding associated with current and predicted rises in extreme rainstorm magnitude-frequency is to be reduced in scale.
Malacca River water quality is affected due to rapid urbanization development. The present study applied LULC changes towards water quality detection in Malacca River. The method uses LULC, PCA, CCA, HCA, NHCA, and ANOVA. PCA confirmed DS, EC, salinity, turbidity, TSS, DO, BOD, COD, As, Hg, Zn, Fe, E. coli, and total coliform. CCA confirmed 14 variables into two variates; first variate involves residential and industrial activities; and second variate involves agriculture, sewage treatment plant, and animal husbandry. HCA and NHCA emphasize that cluster 1 occurs in urban area with Hg, Fe, total coliform, and DO pollution; cluster 3 occurs in suburban area with salinity, EC, and DS; and cluster 2 occurs in rural area with salinity and EC. ANOVA between LULC and water quality data indicates that built-up area significantly polluted the water quality through E. coli, total coliform, EC, BOD, COD, TSS, Hg, Zn, and Fe, while agriculture activities cause EC, TSS, salinity, E. coli, total coliform, arsenic, and iron pollution; and open space causes contamination of turbidity, salinity, EC, and TSS. Research finding provided useful information in identifying pollution sources and understanding LULC with river water quality as references to policy maker for proper management of Land Use area.
The aim of this study was to investigate and apply supported ionic liquid membrane (SILM) in two-phase micro-electrodriven membrane extraction combined with high performance liquid chromatography-ultraviolet detection (HPLC-UV) for pre-concentration and determination of three selected antidepressant drugs in water samples. A thin agarose film impregnated with 1-hexyl-3-methylimidazolium hexafluorophosphate, [C6MIM] [PF6], was prepared and used as supported ionic liquid membrane between aqueous sample solution and acceptor phase for extraction of imipramine, amitriptyline and chlorpromazine. Under the optimized extraction conditions, the method provided good linearity in the range of 1.0-1000μgL(-1), good coefficients of determination (r(2)=0.9974-0.9992) and low limits of detection (0.1-0.4μgL(-1)). The method showed high enrichment factors in the range of 110-150 and high relative recoveries in the range of 88.2-111.4% and 90.9-107.0%, for river water and tap water samples, respectively with RSDs of ≤7.6 (n=3). This method was successfully applied to the determination of the drugs in river and tap water samples. It is envisaged that the SILM improved the perm-selectivity by providing a pathway for targeted analytes which resulted in rapid extraction with high degree of selectivity and high enrichment factor.
A new approach based on the integration of the free liquid membrane (FLM) into electrokinetic supercharging (EKS) was demonstrated to be a new powerful tool used in order to enhance online preconcentration efficiency in capillary electrophoresis (CE). A small plug of water immiscible organic solvent was used as a membrane interface during the electrokinetic sample injection step in EKS in order to significantly enhance the analyte stacking efficiency. The new online preconcentration strategy was evaluated for the determination of paraquat and diquat present in the environmental water samples. The optimised FLM-EKS conditions employed were as follows: hydrodynamic injection (HI) of 20mM potassium chloride as leading electrolyte at 50mbar for 75s (3% of the total capillary volume) followed by the HI of tris(2-ethylhexyl) phosphate (TEHP) as FLM at a 1mm length (0.1% of the capillary volume). The sample was injected at 10kV for 360s, followed by the HI of 20mM cetyl trimethylammonium bromide (CTAB) as terminating electrolyte at 50mbar for 50s (2% of the total capillary volume). The separation was performed in 12mM ammonium acetate and 30mM NaCl containing 20% MeOH at +25kV with UV detection at 205nm. Under optimised conditions, the sensitivity was enhanced between 1500- and 1866-fold when compared with the typical HI at 50mbar for 50s. The detection limit of the method for paraquat and diquat was 0.15-0.20ng/mL, with RSDs below 5.5%. Relative recoveries in spiked river water were in the range of 95.4-97.5%. A comparison was also made between the proposed approach with sole preconcentration of the field-enhanced sample injection (FASI) and EKS in the absence of the FLM.
Abundance and diversity of benthic macroinvertebrates as well as physico-chemical parameters were investigated in five rivers of the Juru River Basin in northern Peninsula Malaysia: Ceruk Tok Kun River (CTKR), Pasir River (PR), Permatang Rawa River (PRR), Kilang Ubi River (KUR), and Juru River (JR). The physico-chemical parameters and calculated water quality index (WQI) were significantly different among the investigated rivers (ANOVA, P<0.05). The WQI classified CTKR, PR, and JR into class III (slightly polluted). However, PRR and KUR fell into class IV (polluted). High diversity and abundance of macroinvertebrates, especially the intolerant taxa, Ephemeroptera, Plecoptera, and Trichoptera, were observed in the least polluted river, CTKR. Decreasing abundance of macroinvertebrates followed the deterioration of river water quality with the least number of the most tolerant taxa collected from PR. On the basis of composition and sensitivity of macroinvertebrates to pollutants in each river, the highest Biological Monitoring Working Party (BMWP) index score of 93 was reported in CTKR (good water quality). BMWP scores in PRR and JR were 38.7 and 20.1, respectively, classifying both of them into "moderate water quality" category. Poor water quality was reported in PR and KUR. The outcome of the multivariate analysis (CCA) was highly satisfactory, explaining 43.32% of the variance for the assemblages of macroinvertebrates as influenced by 19 physical and chemical variables. According to the CCA model, we assert that there were three levels of stresses on macroinvertebrate communities in the investigated rivers: Level 1, characterized of undisturbed or slightly polluted as in the case of CTKR; Level 2, characterized by a lower habitat quality (the JR) compared to the CTKR; and Level 3 showed severe environmental stresses (PRR, PR, and KUR) primarily contributed by agricultural, industrial, and municipal discharges.
Rivers are the main sources of freshwater supply for the world population. However, many economic activities contribute to river water pollution. River water quality can be monitored using various parameters, such as the pH level, dissolved oxygen, total suspended solids, and the chemical properties. Analyzing the trend and pattern of these parameters enables the prediction of the water quality so that proactive measures can be made by relevant authorities to prevent water pollution and predict the effectiveness of water restoration measures. Machine learning regression algorithms can be applied for this purpose. Here, eight machine learning regression techniques, including decision tree regression, linear regression, ridge, Lasso, support vector regression, random forest regression, extra tree regression, and the artificial neural network, are applied for the purpose of water quality index prediction. Historical data from Indian rivers are adopted for this study. The data refer to six water parameters. Twelve other features are then derived from the original six parameters. The performances of the models using different algorithms and sets of features are compared. The derived water quality rating scale features are identified to contribute toward the development of better regression models, while the linear regression and ridge offer the best performance. The best mean square error achieved is 0 and the correlation coefficient is 1.
This study focused on the influence of ultramafic terrains on soil and surface water environmental chemistry in Peninsular Malaysia and in the State of Sabah also in Malaysia. The sampling included 27 soils from four isolated outcrops at Cheroh, Bentong, Bukit Rokan, and Petasih from Peninsular Malaysia and sites near Ranau in Sabah. Water samples were also collected from rivers and subsurface waters interacting with the ultramafic bodies in these study sites. Physico-chemical parameters (including pH, EC, CEC) as well as the concentration of major and trace elements were measured in these soils and waters. Geochemical indices (geoaccumulation index, enrichment factor, and concentration factor) were calculated. Al2O3 and Fe2O3 had relatively high concentrations in the samples. A depletion in MgO, CaO, and Na2O was observed as a result of leaching in tropical climate, and in relation to weathering and pedogenesis processes. Chromium, Ni, and Co were enriched and confirmed by the significant values obtained for Igeo, EF, and CF, which correspond to the extreme levels of contamination for Cr and high to moderate levels of contamination for Ni and Co. The concentrations of Cr, Ni, and Co in surface waters did not reflect the local geochemistry and were within the permissible ranges according to WHO and INWQS standards. Subsurface waters were strongly enriched by these elements and exceeded these standards. The association between Cr and Ni was confirmed by factor analysis. The unexpected enrichment of Cu in an isolated component can be explained by localized mineralization in Sabah.