This study aimed to address the pressing issue of plastic pollution in aquatic ecosystems by assessing the prevalence and distribution of microplastics (MPs) in water and riverbank sediments of the Pekalongan River, a vital water source in Indonesia. From the present findings, MP concentrations in water ranged from 45.2 to 99.1 particles/L, while sediment concentrations ranged from 0.77 to 1.01 particles/g. This study revealed that fragment and film MPs constituted 30.1 % and 25.4 % of the total, respectively, with MPs measuring <1 mm and constituting 51.4 % of the total. Colored MPs, particularly blue and black MPs, accounted for 34 % of the total. The primary polymer components, as determined via Fourier transform infrared spectroscopy, were identified as polystyrene, polyester, and polyamide. In response to the escalating plastic waste crisis caused by single-use plastics, Pekalongan's local government implemented refuse segregation and recycling programs as part of its efforts to transition toward zero-waste practices.
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.
Agarose film liquid phase microextraction (AF-LPME) procedure for the extraction and preconcentration of polycyclic aromatic hydrocarbons (PAHs) in water has been investigated. Agarose film was used for the first time as an interface between donor and acceptor phases in liquid phase microextraction which allowed for selective extraction of the analytes prior to gas chromatography-mass spectrometry. Using 1-octanol as acceptor phase, high enrichment factors in the range of 57-106 for the targeted analytes (fluorene, phenanthrene, fluoranthene and pyrene) were achieved. Under the optimum extraction conditions, the method showed good linearity in the range of 0.1-200 μgL(-1), good correlation coefficients in the range of 0.9963-0.9999, acceptable reproducibility (RSD 6.1-9.2%, n=3), low limits of detection (0.01-0.04 μgL(-1)) and satisfactory relative recoveries (92.9-104.7%). As the AF-LPME device was non-expensive, reuse or recycle of the film was not required, thus eliminating the possibility of analytes carry-over between runs. The AF-LPME technique is environment-friendly and compatible with the green chemistry concept as agarose is biodegradable polysaccharide extracted from seaweed and the procedure requires small volume of organic solvent and generates little waste. The validated method was successfully applied to the analysis of the four analytes in river water samples.
Estuary sediments are one of the important components of coastal ecosystems and have been regarded as a sink for various types of organic pollutants. Organic pollutants such as endocrine disrupting compounds (EDCs) which have been associated with various environmental and human health effects were detected in the estuary sediment at trace level. Considering various interferences that may exist in the estuarine sediment, a sensitive and selective method, capable of detecting multiclass EDC pollutants at the trace levels, needs to be developed and optimized to be applied for environmental analysis. A combination of Soxhlet extraction followed by offline solid phase extraction (SPE) cleaned up with detection based on LC triple quadrupole MS was optimized and validated in this study. The targeted compounds consisted of ten multiclass EDCs, namely, diclofenac, primidone, bisphenol A, estrone (E1), 17β-estradiol (E2), 17α-ethynylestradiol (EE2), 4-octylphenol (4-OP), 4-nonylphenol (4-NP), progesterone, and testosterone. The method showed high extraction efficiency with percentage of recovery from 78% to 108% and excellent sensitivity with detection limit between 0.02ngg-1 and 0.81ngg-1. Excellent linearity from 0.991 to 0.999 was achieved for the developed compounds and the relative standard deviation was less than 18%, an indication of good precision analysis. Evaluation of the matrix effects showed ionization suppression for all the developed compounds. Verification of the method was carried out by analyzing the estuarine sediment collected from Langat River. The analyzed estuarine sediments showed a trace concentration of diclofenac, bisphenol A, progesterone, testosterone, primidone, and E1. However, E2, EE2, 4-OP, and 4-NP were below the method's detection limit. Diclofenac exhibited the highest concentration at 2.67ngg-1 followed by bisphenol A (1.78ngg-1) while E1 showed the lowest concentration at 0.07ngg-1.
As an inland dryland lake basin, the rivers and lakes within the Lake Bosten basin provide scarce but valuable water resources for a fragile environment and play a vital role in the development and sustainability of the local societies. Based on the Google Earth Engine (GEE) platform, combined with the geographic information system (GIS) and remote sensing (RS) technology, we used the index WI2019 to extract and analyze the water body area changes of the Bosten Lake basin from 2000 to 2021 when the threshold value is -0.25 and the slope mask is 8°. The driving factors of water body area changes were also analyzed using the partial least squares-structural equation model (PLS-SEM). The result shows that in the last 20 years, the area of water bodies in the Bosten Lake basin generally fluctuated during the dry, wet, and permanent seasons, with a decreasing trend from 2000 to 2015 and an increasing trend between 2015 and 2019 followed by a steadily decreasing trend afterward. The main driver of the change in wet season water bodies in the Bosten Lake basin is the climatic factors, with anthropogenic factors having a greater influence on the water body area of dry season and permanent season than that of wet season. Our study achieved an accurate and convenient extraction of water body area and drivers, providing up-to-date information to fully understand the spatial and temporal variation of surface water body area and its drivers in the basin, which can be used to effectively manage water resources.
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.
Polycyclic aromatic hydrocarbons (PAHs) and linear alkylbenzenes (LABs) were used as anthropogenic markers of organic chemical pollution of sediments in the Selangor River, Peninsular Malaysia. This study was conducted on sediment samples from the beginning of the estuary to the upstream river during dry and rainy seasons. The concentrations of ƩPAHs and ƩLABs ranged from 203 to 964 and from 23 to 113 ng g(-1) dry weight (dw), respectively. In particular, the Selangor River was found to have higher sedimentary levels of PAHs and LABs during the wet season than in the dry season, which was primarily associated with the intensity of domestic wastewater discharge and high amounts of urban runoff washing the pollutants from the surrounding area. The concentrations of the toxic contaminants were determined according to the Sediment Quality Guidelines (SQGs). The PAH levels in the Selangor River did not exceed the SQGs, for example, the effects range low (ERL) value, indicating that they cannot exert adverse biological effects.
An investigative study was carried out in Langat River to determine the heavy metal pollution in the sediment with 22 sampling stations selected for the collection of sediment samples. The sediment samples were digested and analyzed for extractable metal ((48)Cd, (29)Cu, (30)Zn, (33)As, (82)Pb) using the Inductively Coupled Plasma-Mass Spectrometry (ICP-MS). Parameters, such as pH, Eh, electrical conductivity (EC), salinity, cation exchange capacity (CEC) and loss on ignition (LOI) were also determined. The assessment of heavy metal pollution was derived using the enrichment factors (EF) and geoaccumulation index (I(geo)). This study revealed that the sediment is predominantly by As > Cd > Pb > Zn > Cu. As recorded the highest EF value at 187.45 followed by Cd (100.59), Pb (20.32), Zn (12.42) and Cu (3.46). This is similar to the I(geo), which indicates that the highest level goes to As (2.2), exhibits moderately polluted. Meanwhile, Cd recorded 1.8 and Pb (0.23), which illustrates that both of these elements vary from unpolluted to moderately polluted. The Cu and Zn levels are below 0, which demonstrates background concentrations. The findings are expected to update the current status of the heavy metal pollution as well as creating awareness concerning the security of the river water as a drinking water source.
Toxicity Identification Evaluation (TIE) is a useful method for the classification and identification of toxicants in a composite environment water sample. However, its extension to a larger sample size has been restrained owing to the limited throughput of toxicity bioassays. Here we reported the development of a high-throughput method of TIE Phase I. This newly developed method was assisted by the fluorescence-based cellular oxidation (CO) biosensor fabricated with roGFP2-expressing bacterial cells in 96-well microplate format. The assessment of four river water samples from Langat river basin by this new method demonstrated that the contaminant composition of the four samples can be classified into two distinct groups. The entire toxicity assay consisted of 2338 tests was completed within 12 h with a fluorescence microplate reader. Concurrently, the sample volume for each assay was reduced to 50 μL, which is 600 to 4700 times lesser to compare with conventional bioassays. These imply that the throughput of the CO biosensor-assisted TIE Phase I is now feasible for constructing a large-scale toxicity monitoring system, which would cover a whole watershed scale.
This article describes design and application of feed-forward, fully-connected, three-layer perceptron neural network model for computing the water quality index (WQI)(1) for Kinta River (Malaysia). The modeling efforts showed that the optimal network architecture was 23-34-1 and that the best WQI predictions were associated with the quick propagation (QP) training algorithm; a learning rate of 0.06; and a QP coefficient of 1.75. The WQI predictions of this model had significant, positive, very high correlation (r=0.977, p<0.01) with the measured WQI values, implying that the model predictions explain around 95.4% of the variation in the measured WQI values. The approach presented in this article offers useful and powerful alternative to WQI computation and prediction, especially in the case of WQI calculation methods which involve lengthy computations and use of various sub-index formulae for each value, or range of values, of the constituent water quality variables.
This paper describes the design of an artificial neural network (ANN) model to predict the water quality index (WQI) using land use areas as predictors. Ten-year records of land use statistics and water quality data for Kinta River (Malaysia) were employed in the modeling process. The most accurate WQI predictions were obtained with the network architecture 7-23-1; the back propagation training algorithm; and a learning rate of 0.02. The WQI forecasts of this model had significant (p < 0.01), positive, very high correlation (ρs = 0.882) with the measured WQI values. Sensitivity analysis revealed that the relative importance of the land use classes to WQI predictions followed the order: mining > rubber > forest > logging > urban areas > agriculture > oil palm. These findings show that the ANNs are highly reliable means of relating water quality to land use, thus integrating land use development with river water quality management.
A study was carried out to determine the level of rare earth elements (REEs) in water and sediment samples from ex-mining lakes and River in Kinta Valley, Perak, Malaysia. Surface water and sediments from an ex-mining lake and Kinta River water samples were analyzed for REEs by inductively coupled plasma mass spectrometry. The total concentration of REEs in the ex-mining lake water samples and sediments were found to be 3685 mg/l and 14159 mg/kg, respectively, while the total concentration of REEs in Kinta River water sample was found to be 1224 mg/l. REEs in mining lake water were found to be within 2.42 mg/l (Tb) to 46.50 mg/l (Ce), while for the Kinta River, it was 1.33 mg/l (Ho) to 29.95 mg/l (Ce). Sediment samples were also found with REEs from 9.81 mg/kg (Ho) to 765.84 mg/kg (Ce). Ce showed the highest average concentrations for mining lake (3.88 to 49.08 mg/l) and Kinta River (4.44 to 33.15 mg/l) water samples, while the concentration of La was the highest (11.59 to 771.61 mg/kg) in the mining lake sediment. Lu was shown to have the highest enrichment of REEs in ex-mining lake sediments (107.3). Multivariate statistical analyses such as factor analysis and principal component analysis indicated that REEs were associated and controlled by mixed origin, with similar contributions from anthropogenic and geogenic sources. The speciation study of REEs in ex-tin mining sediments using a modified five-stage sequential extraction procedure indicated that yttrium (Y), gadolinium (Gd), and lanthanum (La) were obtained at higher percentages from the adsorbed/exchanged/carbonate fraction. The average potential mobility of the REEs was arranged in a descending order: Yb > Gd > Y = Dy > Pr > Er > Tm > Eu > Nd > Tb > Sc > Lu > Ce > La, implying that under favorable conditions, these REEs could be released and subsequently pollute the environment.
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.
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.
The presence of endocrine disruptors in source water is of great concern because of their suspected adverse effects on humans, even when present at very low levels. As the main source of potable water supply, rivers in Malaysia are highly susceptible to contamination by various endocrine disruptors originating from anthropogenic activities. In this study, the contamination levels of 1,1,1-trichloro-2,2-bis (4-chlorophenyl) ethane (DDT) and its metabolites and di-(2-ethylhexyl) phthalate (DEHP) in rivers of Selangor were examined using gas chromatography-mass spectrometry. Samples were collected from sites representing source water for 18 drinking water treatment plants in Selangor between July 2008 and July 2009. DDT and its metabolites were detected in only 14% of the 192 samples analysed at levels ranging from 0.6 to 14.6 ng/L. Meanwhile DEHP was detected in 96.8% of the samples at levels ranging from below quantitation level (18 ng/L) to 970 ng/L. The detected levels of DDTs and DEHP were lower than the WHO and Malaysian Guidelines for Drinking Water Quality. Data obtained from this study should also serve as a reference point for future surveillance on these endocrine disruptors.
Rivers, the main source of the domestic water supply in Malaysia, have been threatened by frequent flooding in recent years. This study aims to assess human health risks associated with exposure to concentrated heavy metals in a flood-prone region of Malaysia and investigate the affected individuals' willingness to participate in managing water resources. Hazard indices and cancer risks associated with water contamination by heavy metals have been assessed following the method prescribed by the US Environmental Protection Agency. Yearly data of heavy metal contamination (Cd, Cr, Pb, Zn, Fe), water quality parameters (DO, BOD, COD, pH), and climatic information (annual rainfall, annual temperature) have been collected from the Department of Environment and Meteorological Department of Malaysia, respectively. The inductively coupled plasma mass spectrometry technique has been used by the department of environment for analyzing heavy metal concentration in river water samples. In this study, data from a stratified random sample of households in the affected region were analyzed, using partial least squares structural equation modeling, to predict the link between individuals' perceptions and attitudes about water resources and their willingness to engage in water management program. The health risk estimation indicated that the hazard index values were below the acceptable limit, representing no non-carcinogenic risk to adults and children residing in the study area via oral intake and dermal adsorption of water. However, the calculated value for cancer risk signified possible carcinogenic risks associated with Pb and Cd. In general, contamination due to pollution and flooding tends to increase in the basin region, and appropriate management is needed. The results identified perceived water quality as a significant factor influencing people's attitudes toward involvement in water management programs. As in many developing countries, there is no legal provision guaranteeing public representation in water management in Malaysia. The conclusion discusses the importance of these for the literature and for informing future policy actions.
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.
This paper describes the concentration of selected heavy metals (Co, Cu, Ni, Pb, and Zn) in the Mamut river sediments and evaluate the degree of contamination of the river polluted by a disused copper mine. Based on the analytical results, copper showed the highest concentration in most of the river samples. A comparison with Interim Canadian Sediment Quality Guidelines (ICSQG) and Germany Sediment Quality Guidelines (GSQG) indicated that the sediment samples in all the sampling stations, except Mamut river control site (M1), exceeded the limit established for Cu, Ni, and Pb. On the contrary, Zn concentrations were reported well below the guidelines limit (ICSQG and GSQG). Mineralogical analysis indicated that the Mamut river sediments were primarily composed of quartz and accessory minerals such as chalcopyrite, pyrite, edenite, kaolinite, mica, and muscovite, reflected by the geological character of the study area. Enrichment factor (EF) and geoaccumulation index (Igeo) were calculated to evaluate the heavy metal pollution in river sediments. Igeo values indicated that all the sites were strongly polluted with the studied metals in most sampling stations, specifically those located along the Mamut main stream. The enrichment factor with value greater than 1.5 suggested that the source of heavy metals was mainly derived from anthropogenic activity such as mining. The degree of metal changes (δfold) revealed that Cu concentration in the river sediments has increased as much as 20 to 38 folds since the preliminary investigation conducted in year 2004.
Concentrations of the heavy metals copper (Cu), cadmium (Cd), zinc (Zn), lead (Pb) and nickel (Ni) were determined in the liver, gills and muscles of tilapia fish from the Langat River and Engineering Lake, Bangi, Selangor, Malaysia. There were differences in the concentrations of the studied heavy metals between different organs and between sites. In the liver samples, Cu>Zn>Ni>Pb>Cd, and in the gills and muscle, Zn>Ni>Cu>Pb>Cd. Levels of Cu, Cd, Zn and Pb in the liver samples from Engineering Lake were higher than in those from the Langat River, whereas the Ni levels in the liver samples from the Langat River were greater than in those from Engineering Lake. Cd levels in the fish muscle from Engineering Lake were lower than in that from the Langat River. Meanwhile, the Cd, Zn and Pb levels in the fish muscle from the Langat River were lower than in that from Engineering Lake, and the Ni levels were almost the same in the fish muscle samples from the two sites. The health risks associated with Cu, Cd, Zn, Pb and Ni were assessed based on the target hazard quotients. In the Langat River, the risk from Cu is minimal compared to the other studied elements, and the concentrations of Pb and Ni were determined to pose the greatest risk. The maximum allowable fish consumption rates (kg/d) based on Cu in Engineering Lake and the Langat River were 2.27 and 1.51 in December and 2.53 and 1.75 in February, respectively. The Cu concentrations resulted in the highest maximum allowable fish consumption rates compared with the other studied heavy metals, whereas those based on Pb were the lowest. A health risk analysis of the heavy metals measured in the fish muscle samples indicated that the fish can be classified at one of the safest levels for the general population and that there are no possible risks pertaining to tilapia fish consumption.
A study on the quality of water abstracted for potable use was conducted in the Selangor River basin from November 2008 to July 2009. Seven sampling sites representing the intake points of water treatment plants in the basin were selected to determine the occurrence and level of 15 organochlorine pesticides (OCPs), six phthalate esters (PAEs) and bisphenol A (BPA). Results indicated OCPs were still detected regularly in 66.1 % of the samples with the Σ(15)OCPs ranging from 0.6-25.2 ng/L. The first data on PAEs contamination in the basin revealed Σ(6)PAEs concentrations were between 39.0 and 1,096.6 ng/L with a median concentration of 186.0 ng/L while BPA concentration ranged from <1.2 to 120.0 ng/L. Although di-n-butyl phthalate was detected in all the samples, concentrations of di-ethyl(hexyl)phthalate were higher. Sampling sites located downstream recorded the highest concentrations, together with samples collected during the dry season. Comparison of the detected contaminants with the Department of Environment Water Quality Index (DOE-WQI) showed some agreement between the concentration and the current classification of stream water. While the results suggest that the sites were only slightly polluted and suitable to be used as drinking water source, its presence is cause for concern especially to the fragile firefly "Pteroptyx tener" ecosystem located further downstream.