This study develops an oil spill environmental vulnerability model for predicting and mapping the oil slick trajectory pattern in Kota Tinggi, Malaysia. The impact of seasonal variations on the vulnerability of the coastal resources to oil spill was modelled by estimating the quantity of coastal resources affected across three climatic seasons (northeast monsoon, southwest monsoon and pre-monsoon). Twelve 100 m3 (10,000 splots) medium oil spill scenarios were simulated using General National Oceanic and Atmospheric Administration Operational Oil Modeling Environment (GNOME) model. The output was integrated with coastal resources, comprising biological, socio-economic and physical shoreline features. Results revealed that the speed of an oil slick (40.8 m per minute) is higher during the pre-monsoon period in a southwestern direction and lower during the northeast monsoon (36.9 m per minute). Evaporation, floating and spreading are the major weathering processes identified in this study, with approximately 70% of the slick reaching the shoreline or remaining in the water column during the first 24 h (h) of the spill. Oil spill impacts were most severe during the southwest monsoon, and physical shoreline resources are the most vulnerable to oil spill in the study area. The study concluded that variation in climatic seasons significantly influence the vulnerability of coastal resources to marine oil spill.
We sampled the Klang estuary during the inter-monsoon and northeast monsoon period (July-Nov 2011, Oct-Nov 2012), which coincided with higher rainfall and elevated Klang River flow. The increased freshwater inflow into the estuary resulted in water column stratification that was observed during both sampling periods. Dissolved oxygen (DO) dropped below 63 μM, and hypoxia was observed. Elevated river flow also transported dissolved inorganic nutrients, chlorophyll a and bacteria to the estuary. However, bacterial production did not correlate with DO concentration in this study. As hypoxia was probably not due to in situ heterotrophic processes, deoxygenated waters were probably from upstream. We surmised this as DO correlated with salinity (R2 = 0.664, df = 86, p 6.7 h), hypoxia could occur at the Klang estuary. Here, we presented a model that related riverine flow rate to the post-heavy rainfall hypoxia that explicated the episodic hypoxia at Klang estuary. As Klang estuary supports aquaculture and cockle culture, our results could help protect the aquaculture and cockle culture industry here.
Landfills are a potential threat to human health and the environment, especially from the detrimental and toxic heavy metals. This study focuses on the assessment of heavy metals contamination in leachate and surface soils from different landfills in Malaysia. Maximum quality rating scale (QRS) values of As (787) and Cr (552) denotes progressive deterioration of leachate contamination in landfill. The impacted soils showed high heavy metal concentrations especially at non-sanitary unlined landfills, as compared to background values, and natural soil nearby the landfills. In addition, to examine the environmental impacts of the landfill area (soil) in more detail, specific indexes; geo-accumulation index (Igeo), pollution index (PI) and integrated pollution index (IPI) were determined. Maximum As (3.122) and Cd (2.633) for Igeo and As (34.037) and Cd (20.881) for PI revealed that the soil samples in non-sanitary landfills were moderate to strongly polluted. The difference in range of IPI values for sanitary (0.294-0.322) and non-sanitary landfill soils (1.263-1.956) confirmed advanced decline of the soil quality in non-sanitary landfills. Arsenic concentrations were found to be statistically significant (ANOVA) for leachate and impacted soil in landfills investigated. It is also important to realize that rise in metal contents in landfill environments were not only caused by anthropogenic sources such as from the waste disposed, but also some other factors such as redox conditions, anoxic environments, pH, oxidation state of metals and microbial activities. Those conditions will actively promotes leaching of metals from waste and also natural soils in the landfill.
Marine biota, especially commercially important species, serves as a basis for human nutrition. However, millions of tons of plastic litter are produced and enter the marine environment every year, with potential adverse impacts on marine organisms. In the present study, we investigated the occurrence and characteristics of microplastic (MP) pollution in the digestive tracts of 13 species of wild nektons from 20 stations sampled in the South China Sea (SCS) and the Indian Ocean (IO), and assessed the human health risks of MPs. The detection rate of MPs ranged from 0.00% to 50.00% from the SCS, which was dramatically lower than that from the IO (10.00-80.00%). The average abundance of MP was 0.18 ± 0.06 items g wet weight-1 (ww-1) in the SCS, which was significantly lower than that in the IO with a concentration of 0.70 ± 0.16 items g ww-1. Most MPs were fibers in type, black in color, and polyester (PES) in polymer composition in both the SCS and IO. Interestingly, distinct profiles of MP pollution were found between the benthic and pelagic nektons: 1) The predominant MP composition was PES in the benthic nektons, whereas polyamide (PA) accounted for a larger part of the total MP count in the pelagic nektons within the SCS; 2) The abundance of MP in the benthic nektons (0.52 ± 0.24 items individual-1) was higher than that in the pelagic nektons (0.30 ± 0.11 items individual-1). Accordingly, the mean hazard score of MPs detected in the benthic nektons (220.66 ± 210.75) was higher than that in the pelagic nektons (49.53 ± 22.87); 3) The mean size of the MP in the pelagic nektons (0.84 ± 0.17 mm) was larger than that in the benthic nektons (0.49 ± 0.09 mm). Our findings highlight the need to further investigate the ecological impacts of MPs on wild nekton, especially commercially important species, and its potential implications for human health.
A study on distribution and diversity of benthic foraminifera in surface sediments was carried out in Northwestern Sarawak waters, Malaysia. The range of water depth at the study site was between 43 m and 71 m. A total of seven sediment samples were taken for this study. As a result, 11 genera were identified from a total of 1,222 individuals of foraminifera. 200 individuals were picked out from each sample. The 11 genera that were identified from the study site included Heterolepaspp., Textulariaspp., Quinqueloculinaspp.,Operculina spp. Pseudorotaliaspp., Amphisteginaspp., Cylindroclavulinaspp., Elphidiumspp., Ammobaculitesspp., Asterorotaliaspp. and Bolivinaspp.. The common genera found in the sediments of the study areas were Heterolepa, Textularia, Quincoloculina, Operculinaand Pseudorotalia. The highest and lowest values of Fisher alpha and Shannon-Wiener indices were shown at Station C287 and Station B482 respectively. The highest value of Fisher alpha was 3.23 and the lowest value was 1.97. The highest and lowest values of Shannon-Wiener were 2.30 and 1.91. The highest index value of diversity was 3.23 at depth 67.76 m and the lowest value was 1.53 at depth 45.54 m and 68.45 m. From this study, depth is not the main factor that influencesthe diversity of benthic foraminiferal in northwestern Sarawak waters.
The presence of pharmaceuticals and endocrine-disrupting compounds in aquatic systems is a matter of great concern. The occurrence, fate, and potential toxicity of these compounds have triggered the interest of the scientific community. As a result of their high solubility and low volatility, they are common in aquatic systems, and wastewater treatment plants (WWTP) are the main reservoir for these contaminants. Conventional WWTPs have demonstrated an inability to remove these contaminants completely; hence, different advanced treatment processes have been explored to compensate for the lapses of the conventional system. The outcome of this study revealed the significant improvements made using advanced treatment processes to diminish the number of contaminants; however, some contaminants have proven to be refractory. Thus, there is a need to modify various advanced treatment processes or employ additional treatment processes. Polymer inclusion membranes (PIMs) are a liquid membrane technology that is highly efficient at removing contaminants from water. They have been widely studied for the removal of heavy metals and nutrients from aquatic systems; however, only a few studies have investigated the use of PIMs to remove pharmaceutically active compounds from aquatic systems. This research aims to raise awareness on the application of PIMs as a promising water treatment technology which has a great potential for the remediation of pharmaceuticals and endocrine disruptors in the aquatic system, due to its versatility, ease/low cost of preparation and high contaminant selectivity.
This paper aims to study the spatial and temporal patterns of selected agricultural runoff, specifically in terms of glyphosate, nitrate, and ammonia in bottom water, as well as their possible sources, within an active cockle farming area in Bagan Pasir, Perak, Malaysia. Samples were taken along the cockle farming area from March to November 2019. Glyphosate was analyzed using HPLC with both extraction and derivatization methods using 9-fluorenyl-methyl chloroformate (FMOC-Cl), while nitrate and ammonia levels were determined using the standard Hach method. Generally, glyphosate, nitrate, and ammonia were present within the study site with the average concentration of 37.44 ± 12.27 μg/l, 1.65 ± 0.52 mg/l, and 0.37 ± 0.19 mg/l, respectively. The results suggest that glyphosate and nitrate might be derived from an inland source, while a uniform and low level of ammonia suggested might originate from lithogenic origins. Continuous monitoring remains encouraged.
In this study, the ingestion of microplastics by the deposit-feeding polychaete Namalycastis sp. in the estuarine area of the Setiu Wetlands, Malaysia was confirmed. Samples were collected from six stations, covering the wetland from the south to the north, bimonthly between November 2016 and November 2017. Microplastics were extracted from polychaete samples following digestion in an alkaline solution (10 M NaOH). They were identified by physical characteristics (i.e., shape and color under dissecting microscope and scanning electron microscope), and chemical analysis using a LUMOS Fourier Transform Infrared Microscope (μ-FTIR). A total of 3277 pieces were identified, which were dominated by filaments (99.79%) and with the majority transparent in color (84.71%). Most of the microplastics identified were polypropylene (PP) followed by polyamide (PA) based on their main peak in the of μ-FTIR spectrum. Principal component analysis demonstrated the dominance of microplastics at stations 3 and 4 of the sampling area, probably because of the influx from the open sea and from aquaculture. The findings of this research provide baseline information on microplastics ingested by benthic organisms and their fate in the estuarine food web.
Indonesia is the second-largest contributor of microplastics (MPs) pollution in the marine ecosystem. Most MPs pollution-related studies in Indonesia focus on seawater, sediment, with less information found on the commercially important fish species used for human consumption. Skipjack Tuna (Euthynnus affinis) is one of the major exporting fishery commodities from Indonesia. This exploratory study aimed to determine MPs presence in the digestive tract of Skipjack Tuna from the Southern Coast of Java, Indonesia. The fish samples were collected from five different fish traditional auction market along the Southern Coast of Java, Indonesia, namely Pangandaran, Pamayang Sari, Ciletuh, Santolo, and Palabuhan Ratu. The gastrointestinal tract of Skipjack tuna was pretreated using alkaline destruction and filtered. The presence of MPs in the treated samples was visually identified using an optical microscope, while Polybrominated diphenyl ethers (PBDEs) contaminants were analyzed using Gas Chromatography-Mass Spectrometry (GC-MS). A total of 19 suspected MPs particles were found in the form of filament (84%), angular (11%), and round (5%). This result would provide a better indication of the MPs contamination in marine life species in the Southern Coast of Java, Indonesia, as useful information for marine environmental monitoring program in the future.
The heavy metal contents (Cr, Cu, Zn, Cd, Pb, Hg, and As) of 88 surface sediment samples from the western Sunda Shelf were analyzed to determine their spatial distribution patterns and contamination status. The results demonstrated that high enrichment regions of heavy metals were focused in the Kelantan, Pahang, and Ambat river estuaries, and deep water regions of the study area. These high enrichment regions were mainly controlled by riverine inputs and their hydrodynamic conditions. The enrichment factor (EF), geoaccumulation index (Igeo), and potential ecological risk index (PERI) were used to assess heavy metal accumulation. The results indicated that the study area was not significantly contaminated overall at the time of the study; however, Cd, As, and Hg were at levels corresponding to moderate contamination at many stations located in the Pahang River estuary, Kelantan River estuary, and north-eastern region of the study area, primarily because of anthropogenic activities.
Rivers in Malaysia are classified based on water quality index (WQI) that comprises of six parameters, namely, ammoniacal nitrogen (AN), biochemical oxygen demand (BOD), chemical oxygen demand (COD), dissolved oxygen (DO), pH, and suspended solids (SS). Due to its tropical climate, the impact of seasonal monsoons on river quality is significant, with the increased occurrence of extreme precipitation events; however, there has been little discussion on the application of artificial intelligence models for monsoonal river classification. In light of these, this study had applied artificial neural network (ANN) and support vector machine (SVM) models for monsoonal (dry and wet seasons) river classification using three of the water quality parameters to minimise the cost of river monitoring and associated errors in WQI computation. A structured trial-and-error approach was applied on input parameter selection and hyperparameter optimisation for both models. Accuracy, sensitivity, and precision were selected as the performance criteria. For dry season, BOD-DO-pH was selected as the optimum input combination by both ANN and SVM models, with testing accuracy of 88.7% and 82.1%, respectively. As for wet season, the optimum input combinations of ANN and SVM models were BOD-pH-SS and BOD-DO-pH with testing accuracy of 89.5% and 88.0%, respectively. As a result, both optimised ANN and SVM models have proven their prediction capacities for river classification, which may be deployed as effective and reliable tools in tropical regions. Notably, better learning and higher capacity of the ANN model for dataset characteristics extraction generated better predictability and generalisability than SVM model under imbalanced dataset.
This article proposes a novel data selection technique called the mixed peak-over-threshold-block-maxima (POT-BM) approach for modeling unhealthy air pollution events. The POT technique is employed to obtain a group of blocks containing data points satisfying extreme-event criteria that are greater than a particular threshold u. The selected groups are defined as POT blocks. In parallel with that, a declustering technique is used to overcome the problem of dependency behaviors that occurs among adjacent POT blocks. Finally, the BM concept is integrated to determine the maximum data points for each POT block. Results show that the extreme data points determined by the mixed POT-BM approach satisfy the independent properties of extreme events, with satisfactory fitted model precision results. Overall, this study concludes that the mixed POT-BM approach provides a balanced tradeoff between bias and variance in the statistical modeling of extreme-value events. A case study was conducted by modeling an extreme event based on unhealthy air pollution events with a threshold u > 100 in Klang, Malaysia.
The determinant factors for macroinvertebrate assemblages in river ecosystems are varied and are unique and specific to the type of macroinvertebrate family. This study aims to assess the determinant factors for macroinvertebrate assemblages in a recreational river. The study was conducted on the Ulu Bendul River, Negeri Sembilan, Malaysia. A total of ten sampling stations were selected. The research methodology included (1) water quality measurement, (2) habitat characterization, and (3) macroinvertebrate identification and distribution analysis. The statistical analysis used in this study was canonical correspondence analysis (CCA) to represent the relationship between the environmental factors and macroinvertebrate assemblages in the recreational river. This study found that most of the families of macroinvertebrates were very dependent on the temperature, DO, NH3-N, type of riverbed, etc. All of these factors are important for the survival of the particular type of macroinvertebrate, plus they are also important for selecting egg-laying areas and providing suitable conditions for the larvae to grow. This study advises that improved landscape design for watershed management be implemented in order to enhance water quality and physical habitats, and hence the protection and recovery of the macroinvertebrate biodiversity.
Algal communities possess many attributes as biological indicators of spatial and temporal environmental changes. Algal parameters, especially the community structural and functional variables that have been used in biological monitoring programs, are highlighted in this document. Biological indicators like algae have only recently been included in water quality assessments in some areas of Malaysia. The use of algal parameters in identifying various types of water degradation is essential and complementary to other environmental indicators.
Algal communities possess many attributes as biological indicators of spatial and temporal environmental changes. Algal parameters, especially the community structural and functional variables that have been used in biological monitoring programs, are highlighted in this document. Biological indicators like algae have only recently been included in water quality assessments in some areas of Malaysia. The use of algal parameters in identifying various types of water degradation is essential and complementary to other environmental indicators.
Rapid urbanization and industrial development in the Langat Basin has disturbed the groundwater quality. The populations' reliance on groundwater sources may induce possible risks to human health such as cancer and endocrine dysfunction. This study aims to determine the groundwater quality of an urbanized basin through 24 studied hydrochemical parameters from 45 groundwater samples obtained from 15 different sampling stations by employing integrated multivariate analysis. The abundance of the major ions was in the following order: bicarbonate (HCO3-) > chloride (Cl-) > sodium (Na+) > sulphate (SO42-) > calcium (Ca2+) > potassium (K+) > magnesium (Mg2+). Heavy metal dominance was in the following order: Fe > Mn > Zn > As > Hg > Pb > Ni > Cu > Cd > Se > Sr. Classification of the groundwater facies indicated that the studied groundwater belongs to the Na-Cl with saline water type and Na-HCO3 with mix water type characteristics. The saline water type characteristics are derived from agricultural activities, while the mixed water types occur from water-rock interaction. Multivariate analysis performance suggests that industrial, agricultural, and weathering activities have contributed to groundwater contamination. The study will help in the understanding of the groundwater quality issue and serve as a reference for other basins with similar characteristics.
The SAR has the ability of all-weather and all-time data acquisition, it can penetrate the cloud and is not affected by extreme weather conditions, and the acquired images have better contrast and rich texture information. This paper aims to investigate the use of an object-oriented classification approach for flood information monitoring in floodplains using backscattering coefficients and interferometric coherence of Sentinel-1 data under time series. Firstly, the backscattering characteristics and interference coherence variation characteristics of SAR time series are used to analyze whether the flood disaster information can be accurately reflected and provide the basis for selecting input classification characteristics of subsequent SAR images. Subsequently, the contribution rate index of the RF model is used to calculate the importance of each index in time series to convert the selected large number of classification features into low dimensional feature space to improve the classification accuracy and reduce the data redundancy. Finally, the SAR image features in each period after multi-scale segmentation and feature selection are jointly used as the input features of RF classification to extract and segment the water in the study area to monitor floods' spatial distribution and dynamic characteristics. The results showed that the various attributes of backscatter coefficients and interferometric coherence under time series could accurately correspond with the actual flood risk, and the combined use of backscattering coefficient and interferometric coherence for flood extraction can significantly improve the accuracy of flood information extraction. Overall, the object-based random forest method using the backscattering coefficient and interference coherence of Sentinel-1 time series for flood extraction advances our understanding of flooding's temporal and spatial dynamics, essential for the timely adoption of adaptation and mitigation strategies for loss reduction.
This study proposes the concept of duration (D) and severity (S) measures, which were derived from unhealthy air pollution events. In parallel with that, the application of a copula model is proposed to evaluate unhealthy air pollution events with respect to their duration and severity characteristics. The bivariate criteria represented by duration and severity indicate their structural dependency, long-tail, and non-identically marginal distributions. A copula approach can provide a good statistical tool to deal with these issues and enable the extraction of valuable information from air pollution data. Based on the copula model, several statistical measurements are proposed for describing the characteristics of unhealthy air pollution events, including the Kendall's τ correlation of the copula, the conditional probability of air pollution severity based on a given duration, the joint OR/AND return period, and the conditional D|S and conditional S|D return periods. A case study based on air pollution data indices was conducted in Klang, Malaysia. The results indicate that a copula approach is beneficial for deriving valuable information for planning and mitigating the risks of unhealthy air pollution events.
Microplastic pollution is widely recognised as a global issue, posing risks to natural ecosystems and human health. The combination of rapid industrial and urban development and relatively limited environmental regulation in many tropical countries may increase the amount of microplastic entering rivers, but basic data on contamination levels are lacking. This is especially the case in tropical South East Asian countries. In this paper, the abundance, composition and spatio-temporal variation of microplastic in the Langat River, Malaysia, were assessed, and the relationship between microplastic concentration and river discharge was investigated. Water samples were collected over a 12-month period from 8 sampling sites on the Langat, extending from forested to heavily urbanised and industrial areas. All 508 water samples collected over this period contained microplastic; mean concentration across all sites and times was 4.39 particles/L but extended up to 90.00 particles/L in some urban tributaries. Most microplastics were secondary in origin, and dominated by fibres. Microplastic counts correlated directly with river discharge, and counts increased and decreased in response to changes in flow. A time-integrated assessment of the microplastic load conveyed by the Langat suggested that the river is typically (50 % of the time) delivering around 5 billion particles per day to the ocean. The positive correlation between the concentration of microplastics and suspended sediments in the Langat suggested that continuously logging turbidity sensors could be used to provide better estimates of microplastic loads and improve assessment of human and ecological health risks.
The present study examines historical perspectives of the macrobenthic community in response to different phases of anthropogenic perturbations in Kakinada Bay, a tropical embayment on the east coast of India. Multivariate analysis of the snapshot data (1958-2017) revealed considerable changes in the Bay environment following a breakwater construction across the Bay mouth in 1997. Subsequently, port expansion activities, industrialization, urbanization, and geomorphic alterations in the Godavari delta brought deterrent changes in the Bay. The fluctuations over the years in hydrographical and sediment characteristics increased environmental heterogeneity and caused significant spatio-temporal shifts in the macrobenthic community between 1995-1996 and 2016-2017. The observed variabilities were suggestive of anthropogenic perturbations of the system with future repercussions on Bay ecosystem functioning. Overall, this study provides evidence on the long-term impact of anthropogenic activities on coastal marine communities and stresses the importance of macrobenthos as bioindicators of such changes in tropical systems.