Seasonal influences on the levels of particulate metals In Kuantan River, East Coast Malaysia using principal component analysis

Principal component analysis (PCA) were performed to evaluate temporal variations of trace metals of Kuantan River waters. Water samples from 12 sampling stations were taken from downstream of the estuary towards the upstream of Kuantan River during the Northeast Monsoon (NEM) and Southwest Monsoon (SWM). Particulate metals were filtered, dried, weighed, analyzed using Teflon Bomb digestion processes and detected using ICP-MS. The metals distribution in suspended particulate matter was found influenced by monsoon seasons particularly during NEM. The PCA/FA identified six varifactors, which were responsible for 83.30% of total variance in the dataset. The PCA results showed that the main source of river water pollution is mostly due to the point sources such as domestic wastewater, wastewater treatment plants and industries as well as non-point sources namely agriculture and oil palm plantations. This study illustrates the usefulness of PCA for identification of pollution sources and understanding temporal variations in river water for effective river water management

Distributions of dissolved toxic elements during seasonal variation in Kuantan river, Pahang, Malaysia

The concentrations of toxic metals were determined in estuary and freshwater zones from Kuantan River basin. Water samples were collected from the surface and bottom layers of nine sampling stations, from the downstream of the estuary towards the upstream along the mainstream drainage channel, traversing past the city center and industries of Kuantan city. The general physico-chemical parameters (salinity, temperature, pH and dissolved oxygen) and concentration of total dissolved metals, Cadmium (Cd), Chromium (Cr) and Lead (Pb)were measured during dry season (May and June 2012) and wet season (September and October 2012). Metal concentration was determined using Inductively Coupled Plasma Mass Spectrometry (ICP-MS).Metal concentrations ranged from 0.299 - 1.815µg/Lfor Cr, undetectable to 0.034µg/L for Cd and 4.697 – 16.017µg/L for Pb, respectively. The present measurements can be used as a baseline data for any future monitoring and comparison of trace metals distribution in the Kuantan River

Development of trace metals concentration model for river: application of principal component analysis and artificial neural network

Rapid development along the Kuantan River was long perceived as the rivers serve many communities in terms of drinking water source, domestic, fisheries, recreation, and agricultural purposes. Due to the rapid changes in technology and upsurge in chemical usage, pollutant alterations turn out to be more drastic with respect to space and time. Research on the trace metals in river water is quite limited in Malaysia, probably due to their ppb-level existence and the need for special handling techniques. Hence, the aim of this study is to forecast heavy metals concentration in Kuantan River waters using a collective of 10 years (2007 – 2016) dataset of heavy metals that provided by the Department of Environment, Malaysia. Principal Component Analysis (PCA) was used to compute the data, which showed that As, Cr, Fe, Zn and Cd explain 67.3% of the total variance through three principal components. For ANN computation, those significant metals extracted from rotating PCA was selected and used in ANN model. The developed approaches were trained and tested using 80% and 20% of the data, respectively. Then, the coefficient of determination (R2) was executed to calculate the model performance. Out of five metals, only As shown acceptable R2 for ANN models with 0.8690 and 0.8088 for training and testing, respectively, probably due to the model’s limitation. Generally, this study illustrates the usefulness of PCA and ANN for analysis and interpretation of complex data sets and understanding the temporal and spatial variations in the Kuantan River for effective river water management

Fractionation of rare earth elements in surface sediment of Peninsular Malaysia coastal waters

The environmental fate of rare earth elements (REEs) in the Malaysian environment is limitedly known; however, industrial emission is increasing. This study focused on the REE assessment of the surface sediments obtained from rocky shore ecosystems along the Peninsular Malaysia coastal waters, on deliberating interspatial variability, and on describing their partitioning. Samples were treated with the Teflon Bomb technique, and the concentration of 14 natural REEs was measured through inductively coupled plasma mass spectrometry (ICP- MS). Through quality control practices, the results were verified by employing a standard reference material BCR 667. The tendency of REE distribution was the most mutual property of particular places worldwide and in Malaysia. Among REEs present in sediment, strong correlations were observed, which indicated REEs they behave coherently to each other in different processes of geochemical fractionation. The contaminant metals, namely manganese, arsenic, cadmium and copper, were strongly correlated with REEs (p < 0.01 and p < 0.05); hence, these metals may be nonanthropogenic in origin because REEs are geogenic in origin. The enrichment factor (EF) values of the comparative results were divided by the region-specified deficiency to minimal enrichment in all the regions, except in the east coast region, which presented considerable enrichment, suggesting a probability of discharge of the anthropogenic effluent. The results of the analysis normalized to chondrite presented patterns of low atomic weight rare earth elements (LREEs) enrichment, gradual downward pattern and depletion through high atomic weight rare earth elements (HREEs) concentrations

Geostatistical assessment of heavy metals and nutrients availability in soil of oil palm plantation affected by bauxite mining

This study describes the contamination of heavy metals (Cu, Zn, Mn, Pb and Fe) and their effect on K, Ca and Mg availability in oil palm cultivated areas affected by bauxite mining activities using the combinations of geostatistic and geospatial analysis. A total of 64 soil samples were collected covering a total area of 420.21 ha by grid sampling technique. Spatial distributions of the heavy metals were determined using semivariogram and mapped using ArcGIS. The mean concentrations of Cu (138.94 ± 79.08 mg kg-1), Zn (233.55 ± 79.16 mg kg-1), Mn (847.88 ± 267.02) mg kg-1) and Fe (249 703.71 ± 101 408.72 mg kg-1) in this study were greater than the background values, the 95% ‘Investigation Levels’ determined for Malaysia soil and Dutch target values. Geoaccumulation index showed that the contamination was in the order of Fe> Cu>Pb>Zn> Mn. Semivariogram analysis of pH, Mn, Zn and Fe was aligned with the principal component analysis results, showing the contamination source originated from a similar identical source. In correlation to the nutrients, only Kex., was found to be affected by the contaminants. These results provide a useful basis for the related agencies in identifying hotspots for future rehabilitation programs

Integrated approach of heavy metal evaluation using geostatistical and pollution assessment index in soil of bauxite mining area

Heavy metals contamination in soil is one of the global issues, posing a threat not just to the environment but also to human health. Identifying the source and distribution of heavy metal pollutants around mining areas can provide a scientific basis for future environmental control. Distributions of the heavy metals (Cd, Cr, As, and Ni) in this study were evaluated using descriptive and multivariate statistics and further described using a geostatistical approach and pollution indices. The total content of Cr, Cd, and Ni in surface soil was observed with a higher concentration level according to the Dutch target values and the 95% Investigation Levels determined for Malaysia soil. Statistical analyses, geostatistics, and GIS mapping suggested that Cd, Cr, and Ni were derived mainly from anthropogenic sources, including mining and agricultural activities, while As could be derived from lithogenic and anthropogenic sources. Geoaccumulation index analysis demonstrated that the contamination that occurred with Cd posed the greatest risk of contamination, followed by Cr, Ni, and As. A spatial interpolated map showed a higher concentration of heavy metals in the vicinity of the mining area. These findings highlight the effectiveness of principal component analysis, geostatistics, and geospatial analyses in evaluating heavy metal contents in the study area. The obtained results could be used by authorities to identify areas requiring remediation management and establish scientific baseline data related to soil quality

Microplastics contamination in bivalves off the island in the strait of malacca and its potential health risks

The widespread presence of microplastics in the ocean is a significant threat to marine life and humans. A study was conducted to investigate the extent of microplastic contamination in the coastal waters of Langkawi and Penang, situated on the northern coast of Peninsular Malaysia. Rock oysters (Saccostrea cucullata) were utilized as bioindicators due to its availability in all sampling sites to evaluate microplastics,by considering its abundance, types, polymer composition, and potential health risks related to consumption. Soft tissues were digested with 10% KOH, and the resulting microplastics were examined using a stereo microscope and microplastics polymer were identified through ATR-FTIR. Kok Beach and Penarak Beach exhibited notably higher microplastic abundance, mainly in the form of filaments with predominant black and red colours. The most common polymer types were cellulose triacetate (CTA) and polycyclohexanedimethylene terephthalate (PCT). Hazard Quotient values, indicating potential health risks from consuming S. cucullata, surpassed a critical threshold at all locations. The study's findings suggest that it serves as a fundamental reference for future research on microplastic contamination in the islands along the northern coast of Peninsular Malaysia