The occurrence and estrogenic activities of steroid estrogens, such as the natural estrone (E1), 17β estradiol (E2), and estriol (E3), as well as the synthetic 17α-ethynylestradiol (EE2), were investigated in eight sampling points along the Langat River (Malaysia). Surface water samples were collected at 0.5 m and surface sediment 0-5 cm from the river surface. Instrument analysis of steroid estrogens was determined by UPLC-ESI-MS with an ultra-performance liquid chromatograph (Perkin Elmer FX15) coupled to a Q Trap function mass spectrophotometer (model 3200: AB Sciex). Steroid estrogen concentrations were higher in the Langat River sediments than those in its surface water. In surface water, E1 was not detected in any sampling point, E2 was only detected in two midstream sampling points (range 0-0.004 ng/L), E3 in three sampling points (range 0-0.002 ng/L), and EE2 in four sampling points (range 0-0.02 ng/L). E1 and E2 were detected in sediments from all sampling points, E3 in five sampling points, while EE2 only in one midstream sample (3.29E-4 ng/g). Sewage treatment plants, farming waste, and agricultural activities particularly present midstream and downstream were identified as potential sources of estrogens. Estrogenic activity expressed as estradiol equivalents (EEQs) was below 1 ng/L in all samples for both surface water and sediment, indicating therefore a low potential estrogenic risk to the aquatic environment. Although the health risks are still uncertain for drinking water consumers exposed to low levels of steroid estrogen concentrations, Langat River water is unacceptable for direct drinking purposes without treatment. Further studies of endocrine disruptors in Malaysian waters are highly recommended.
This study investigated the occurrence of nine pharmaceuticals (amoxicillin, caffeine, chloramphenicol, ciprofloxacin, dexamethasone, diclofenac, nitrofurazone, sulfamethoxazole, and triclosan) and to evaluate potential risks (human health and ecotoxicological) in Lui, Gombak and Selangor (Malaysia) rivers using commercial competitive Enzyme-Linked Immunosorbent Assay (ELISA) kit assays. Physicochemical properties of these rivers showed the surface samples belong to Class II of Malaysian National Water Quality Standards which requires conventional treatment before consumption. All the pharmaceuticals were detected in all three rivers except for triclosan, dexamethasone and diclofenac which were not detected in few of sampling locations in these three rivers. Highest pharmaceutical concentrations were detected in Gombak river in line of being as one of the most polluted rivers in Malaysia. Ciprofloxacin concentrations were detected in all the sampling locations with the highest at 299.88 ng/L. While triclosan, dexamethasone and diclofenac concentrations were not detected in a few of sampling locations in these three rivers. All these nine pharmaceuticals were within the levels reported previously in literature. Pharmaceutical production, wastewater treatment technologies and treated sewage effluent were found as the potential sources which can be related with pharmaceuticals occurrence in surface water samples. Potential human risk assessment showed low health risk except for ciprofloxacin and dexamethasone. Instead, ecotoxicological risk assessment indicated moderate risks were present for these rivers. Nevertheless, results confirmation using instrumental techniques is needed for higher degree of specificity. It is crucial to continuously monitor the surface water bodies for pharmaceuticals using a cost-effective prioritisation approach to assess sensitive sub-populations risk.
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.
Pesticides are of great concern because of their existence in ecosystems at trace concentrations. Worldwide pesticide use and its ecological impacts (i.e., altered environmental distribution and toxicity of pesticides) have increased over time. Exposure and toxicity studies are vital for reducing the extent of pesticide exposure and risk to the environment and humans. Regional regulatory actions may be less relevant in some regions because the contamination and distribution of pesticides vary across regions and countries. The risk quotient (RQ) method was applied to assess the potential risk of organophosphorus pesticides (OPPs), primarily focusing on riverine ecosystems. Using the available ecotoxicity data, aquatic risks from OPPs (diazinon and chlorpyrifos) in the surface water of the Langat River, Selangor, Malaysia were evaluated based on general (RQm) and worst-case (RQex) scenarios. Since the ecotoxicity of quinalphos has not been well established, quinalphos was excluded from the risk assessment. The calculated RQs indicate medium risk (RQm = 0.17 and RQex = 0.66; 0.1 ≤ RQ 1 (high risk) was observed for both the general and worst cases of chlorpyrifos, but only for the worst cases of diazinon at all sites from downstream to upstream regions. Thus, chlorpyrifos posed a higher risk than diazinon along the Langat River, suggesting that organisms and humans could be exposed to potentially high levels of OPPs.
Morphological mentum deformities which represent sublethal effect of exposure to different types of pollutants were evaluated in Chironomus spp. larvae inhabiting three polluted rivers of Juru River Basin in northwestern peninsular Malaysia. Using mentum deformity incidences, the modified toxic score index (MTSI) was developed based on Lenat's toxic score index (TSI). The suggested MTSI was compared with TSI in terms of its effectiveness to identify different pollutants including heavy metals. The MTSI showed stronger relationship to total deformity incidence expressed as percentage. Additionally, the multivariate RDA model showed higher capability of MTSI to explain the variations in heavy metal contents of the river sediments. The MTSI was recommended in bioassessment of water and sediment quality using the mentum deformities of Chironomus spp. larvae from aquatic ecosystems receiving anthropogenic, agricultural, or industrial discharges.
The environmental reservoirs of sulfonamide (SA) resistome are still poorly understood. We investigated the potential sources and reservoir of SA resistance (SR) in Larut River and Sangga Besar River by measuring the SA residues, sulfamethoxazole resistant (SMXr) in bacteria and their resistance genes (SRGs). The SA residues measured ranged from lower than quantification limits (LOQ) to 33.13 ng L-1 with sulfadiazine (SDZ), sulfadimethoxine (SDM) and SMX as most detected. Hospital wastewater effluent was detected with the highest SA residues concentration followed by the slaughterhouse and zoo wastewater effluents. The wastewater effluents also harbored the highest abundance of SMXr-bacteria (107 CFU mL-1) and SRGs (10-1/16S copies mL-1). Pearson correlation showed only positive correlation between the PO4 and SMXr-bacteria. In conclusion, wastewater effluents from the zoo, hospital and slaughterhouse could serve as important sources of SA residues that could lead to the consequent emergence of SMXr-bacteria and SRGs in the river.
This study analyzed the levels of cadmium (Cd), copper (Cu), and zinc (Zn) by the flame atomic absorption spectrophotometer (FAAS), in the muscle tissues, exoskeletons, and gills from freshwater prawn (Macrobrachium rosenbergii) (n = 20) harvested from natural habitat in Kerang River, Malaysia on 25th November 2015. Significant increase of the metals level in muscle tissue and gill (r > 0.70, p
This study aimed to evaluate the spatial and temporal distribution of heavy metals (Cd, Cr, Cu, Co, Fe, Pb, Ni, V, and Zn) in the sediments of Bayan Lepas Free Industrial Zone of Penang, Malaysia. Ten sampling stations were selected and sediment samples were collected during low tide (2012-2013). Metals were analyzed and the spatial distribution of metals were evaluated based on GIS mapping. According to interim sediment quality guidelines (ISQG), metal contents ranged from below low level to above high level at different stations. Based on the geoaccumulation index (Igeo) of sediment, sampling stations were categorized from unpolluted to strongly polluted. The enrichment factor (EF) of metals in the sediment varied between no enrichment to extremely high enrichment. The potential ecological risk index (RI) indicated Bayan Lepas FIZ was at low risk.
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.
The upper catchment region of the Baram River in Sarawak (Malaysian Borneo) is undergoing severe land degradation due to soil erosion. Heavy rainfall with high erosive power has led to a number of soil erosion hotspots. The goal of the present study is to generate an understanding about the spatial characteristics of seasonal and annual rainfall erosivity (R), which not only control sediment delivery from the region but also determine the quantity of material potentially eroded. Mean annual rainfall and rainfall erosivity range from 2170 to 5167 mm and 1632 to 5319 MJ mm ha-1 h-1 year-1, respectively. Seasonal rainfall and rainfall erosivity range from 848 to 1872 mm and 558 to 1883 MJ mm ha-1 h-1 year-1 for the southwest (SW) monsoon, 902 to 2200 mm and 664 to 2793 MJ mm ha-1h-1year-1 for the northeast (NE) monsoon and 400 to 933 mm and 331 to 1075 MJ mm ha-1 h-1 year-1 during the inter-monsoon (IM) period. Linear regression, Spearman's Rho and Mann Kendall tests were applied. Considering the regional mean rainfall erosivity in the study area, all the methods show an overall non-significant decreasing trend (- 9.34, - 0.25 and - 0.30 MJ mm ha-1 h-1 year-1, respectively for linear regression, Spearman's Rho and Mann Kendall tests). However, during SW monsoon and IM periods, rainfall erosivity showed a non-significant decreasing trend (- 25.45, - 0.52, - 0.40, and - 8.86, - 1.07, - 0.77 MJ mm ha-1 h-1 year-1, respectively) whereas in NE, monsoon season erosivity showed a non-significant increasing trend (14.90, 1.59 and 1.60 MJ mm ha-1 h-1 year-1, respectively). The mean erosivity density ranges from 0.77 to 1.38 MJ ha-1 h-1 year-1 and shows decreasing trend. Spatial distribution pattern of erosivity density indicates significantly higher occurrence of erosive rainfall in the lower elevation portion of the study area. The spatial pattern of mean rainfall erosivity trends (linear, Spearman's Rho and Mann Kendall) suggests that the study area can be divided into two zones with increasing rainfall erosivity trends in the northern zone and decreasing trends in the southern zone. These results can be used to plan conservation measures to reduce sediment delivery from localized soil erosion hotspots.
Understanding the drivers of community structure is fundamental for adequately managing ecosystems under global change. Here we used a large dataset of eighty-four headwater stream sites in three catchments in the Eastern Highlands of Zimbabwe, which represent a variety of abiotic conditions and levels of impairment, to examine the drivers of benthic macroinvertebrate community structure. We focused our assessment on macroinvertebrate family level community composition and functional feeding group classifications. Taxonomic richness was weakly positively correlated with ammonium, phosphates and pH, and weakly negatively correlated with detrital cover and dissolved oxygen. Measured abiotic variables, however, had limited influence on both macroinvertebrate diversity and functional feeding group structure, with the exception of ammonium, channel width and phosphates. This reflected the fact that many macroinvertebrate families and functional feeding guilds were well represented across a broad range of habitats. Predatory macroinvertebrates were relatively abundant, with collector-filterers having the lowest relative abundances. The findings of the study suggest that for certain ecological questions, a more detailed taxonomic resolution may be required to adequately understand the ecology of aquatic macroinvertebrates within river systems. We further recommend management and conservation initiatives on the Save River system, which showed significant impact from catchment developmental pressures, such as urbanisation, agriculture and illegal mining.
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.
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.
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.
Corbicula fluminea serves as traditional food to the local people in Kelantan, Malaysia. Concerns regarding river contamination, smoking method, and associated adverse effects on public health had been increasing. Hence, this study aims to measure the level of heavy metals (Cd, Cu, Mn, Pb, and Zn) and assess human health risk in C. fluminea consumption at Kelantan. Heavy-metal analysis was done using flame atomic absorption spectrophotometry, while human health risk was assessed using provisional tolerable weekly intake (PTWI), target hazard quotient (THQ), and hazard index (HI). The estimated weekly intake (EWI) for all metals was found within PTWI, while THQ for Cd, Cu, Mn, Pb, and Zn was 0.12, 0.06, 0.04, 0.41, and 0.03, respectively. The HI was calculated at 0.61 which is less than 1, considered as the safe consumption level. Therefore, C. fluminea consumption in this study was found safe from the health risk of noncarcinogenic effect over a lifetime.
Soil temperature has a vital importance in biological, physical and chemical processes of terrestrial ecosystem and its modeling at different depths is very important for land-atmosphere interactions. The study compares four machine learning techniques, extreme learning machine (ELM), artificial neural networks (ANN), classification and regression trees (CART) and group method of data handling (GMDH) in estimating monthly soil temperatures at four different depths. Various combinations of climatic variables are utilized as input to the developed models. The models' outcomes are also compared with multi-linear regression based on Nash-Sutcliffe efficiency, root mean square error, and coefficient of determination statistics. ELM is found to be generally performs better than the other four alternatives in estimating soil temperatures. A decrease in performance of the models is observed by an increase in soil depth. It is found that soil temperatures at three depths (5, 10 and 50 cm) could be mapped utilizing only air temperature data as input while solar radiation and wind speed information are also required for estimating soil temperature at the depth of 100 cm.
Several research efforts have been conducted to monitor and analyze the impact of environmental factors on the heavy metal concentrations and physicochemical properties of water bodies (lakes and rivers) in different countries worldwide. This article provides a general overview of the previous works that have been completed in monitoring and analyzing heavy metals. The intention of this review is to introduce the historical studies to distinguish and understand the previous challenges faced by researchers in analyzing heavy metal accumulation. In addition, this review introduces a survey on the importance of time increment sampling (monthly and/or seasonally) to comprehend and determine the rate of change of different parameters on a monthly and seasonal basis. Furthermore, suggestions are made for future research to achieve more understandable figures on heavy metal accumulation by considering climate conditions. Thus, the intent of the current study is the provision of reliable models for predicting future heavy metal accumulation in water bodies in different climates and pollution conditions so that water management can be achieved using intelligent proactive strategies and artificial neural network (ANN) techniques.
We discuss the accuracy and performance of the adaptive neuro-fuzzy inference system (ANFIS) in training and prediction of dissolved oxygen (DO) concentrations. The model was used to analyze historical data generated through continuous monitoring of water quality parameters at several stations on the Johor River to predict DO concentrations. Four water quality parameters were selected for ANFIS modeling, including temperature, pH, nitrate (NO3) concentration, and ammoniacal nitrogen concentration (NH3-NL). Sensitivity analysis was performed to evaluate the effects of the input parameters. The inputs with the greatest effect were those related to oxygen content (NO3) or oxygen demand (NH3-NL). Temperature was the parameter with the least effect, whereas pH provided the lowest contribution to the proposed model. To evaluate the performance of the model, three statistical indices were used: the coefficient of determination (R (2)), the mean absolute prediction error, and the correlation coefficient. The performance of the ANFIS model was compared with an artificial neural network model. The ANFIS model was capable of providing greater accuracy, particularly in the case of extreme events.
Surface water is one of the essential resources for supporting sustainable development. The suitability of such water for a given use depends both on the available quantity and tolerable quality. Temporary status for a surface water quality has been identified extensively. Still the suitability of the water for different purposes needs to be verified. This study proposes a water quality evaluation system to assess the aptitude of the Selangor River water for aquatic biota, drinking water production, leisure and aquatic sport, irrigation use, livestock watering, and aquaculture use. Aptitude of the water has been classified in many parts of the river segment as unsuitable for aquatic biota, drinking water production, leisure and aquatic sport as well as aquaculture use. The water quality aptitude classes of the stream water for nine locations along the river are evaluated to contribute to decision support system. The suitability of the water for five different uses and its aquatic ecosystem are verified.
Water quality degradation in the Citarum river will increase from the year to year due to increasing pollutant loads when released particularly from Bandung region of the upstream areas into the river without treatment. This will be facing the problems on water quality status to use for multi-purposes in the downstream areas. The water quality evaluation system is used to evaluate the available water condition that distinguishes into two categories, i.e., the water quality index (WQI) and water quality aptitude (WQA). The assessment of water quality for the Citarum river from 10 selected stations was found that the WQI situates in the bad category generally and the WQA ranges from the suitable quality for agriculture and livestock watering uses to the unsuitable for biological potential function, drinking water production, and leisure activities and sports in the upstream areas of Saguling dam generally.