The current study aims to investigate the influence of seasonal changes on the pollution loads of the sediment of a coastal area in terms of its physicochemical features. The research will focus on analyzing the nutrients, organic carbon and particle size of the sediment samples collected from 12 different sampling stations in 3 different seasons along the coastal area. Additionally, the study discusses about the impact of anthropogenic activities such as agriculture and urbanization and natural activities such as monsoon on the sediment quality of the coastal area. The nutrient changes in the sediment were found to be: pH (7.96-9.45), EC (2.89-5.23 dS/m), nitrogen (23.98-57.23 mg/kg), phosphorus (7.75-11.36 mg/kg), potassium (217-398 mg/kg), overall organic carbon (0.35-0.99%), and sediment proportions (8.91-9.3%). Several statistical methods were used to investigate changes in sediment quality. According to the three-way ANOVA test, the mean value of the sediments differs significantly with each season. It correlates significantly with principal factor analysis and cluster analysis across seasons, implying contamination from both natural and man-made sources. This study will contribute to developing effective management strategies for the protection and restoration of degraded coastal ecosystem.
Steroid estrogens such as 17β-Estradiol (E2) and 17α-Ethynylestradiol (EE2) are highly potent estrogens that widely detected in environmental samples. Mathematical modelling such as concentration addition (CA) and estradiol equivalent concentration (EEQ) models are usually associated with measuring techniques to assess risk, predict the mixture response and evaluate the estrogenic activity of mixture. Wastewater has played a crucial role because wastewater treatment plant (WWTP) is the major sources of estrogenic activity in aquatic environment. The aims of this is to determine E2 and EE2 concentrations in six WWTPs effluent, to predict the estrogenic activity of the WWTPs effluent using CA and EEQ models where lastly the effectiveness of two models is evaluated. Results showed that all the six WWTPs effluent had relative high E2 concentration (35.1-85.2 ng/L) compared to EE2 (0.02-1.0 ng/L). The estrogenic activity predicted by CA model was similar among the six WWTPs (105.4 ng/L), due to the similarity of individual dose potency ratio calculated by respective WWTPs. The predicted total EEQ was ranged from 35.1 EEQ-ng/L to 85.3 EEQ-ng/L, explained by high E2 concentration in WWTPs effluent and E2 EEF value that standardized to 1.0 μg/L. The CA model is more effective than EEQ model in estrogenic activity prediction because EEQ model used less data and causes disassociation from the predicted behavior. Although both models predicted relative high estrogenic activity in WWTPs effluent, dilution effects in receiving river may lower the estrogenic response to aquatic inhabitants.
The Damoh district, which is located in the central India and characterized by limestone, shales, and sandstone compact rock. The district has been facing groundwater development challenges and problems for several decades. To facilitate groundwater management, it is crucial to monitoring and planning based on geology, slope, relief, land use, geomorphology, and the types of the basaltic aquifer in the drought-groundwater deficit area. Moreover, the majority of farmers in the area are heavily dependent on groundwater for their crops. Therefore, delineation of groundwater potential zones (GPZ) is essential, which is defined based on various thematic layers, including geology, geomorphology, slope, aspect, drainage density, lineament density, topographic wetness index (TWI), topographic ruggedness index (TRI), and land use/land cover (LULC). The processing and analysis of this information were carried out using Geographic Information System (GIS) and Analytic Hierarchy Process (AHP) methods. The validity of the results was trained and tested using Receiver Operating Characteristic (ROC) curves, which showed training and testing accuracies of 0.713 and 0.701, respectively. The GPZ map was classified into five classes such as very high, high, moderate, low, and very low. The study revealed that approximately 45% of the area falls under the moderate GPZ, while only 30% of the region is classified as having a high GPZ. The area receives high rainfall but has very high surface runoff due to no proper developed soil and lack of water conservation structures. Every summer season show a declined groundwater level. In this context, results of study area are useful to maintain the groundwater under climate change and summer season. The GPZ map plays an important role in implementing artificial recharge structures (ARS), such as percolation ponds, tube wells, bore wells, cement nala bunds (CNBs), continuous contour trenching (CCTs), and others for development of ground level. This study is significant for developing sustainable groundwater management policies in semi-arid regions, that are experiencing climate change. Proper groundwater potential mapping and watershed development policies can help mitigate the effects of drought, climate change, and water scarcity, while preserving the ecosystem in the Limestone, Shales, and Sandstone compact rock region. The results of this study are essential for farmers, regional planners, policy-makers, climate change experts, and local governments, enabling them to understand the groundwater development possibilities in the study area.
The Bio-ecological Drainage System, or BIOECODS, is an urban drainage system located at the Engineering Campus, Universiti Sains Malaysia. It consists of a constructed wetland as a part of the urban drainage system to carry storm water in a closed system. In this closed system, the constructed wetland was designed particularly for further treatment of storm water. For the purpose of studying the water balance of the constructed wetland, data collection was carried out for two years (2007 and 2009). The results show that the constructed wetland has a consistent volume of water storage compared to the outflow for both years with correlation coefficients (R(2)) of 0.99 in 2007 and 0.86 in 2009.
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.
Synthetic plastics, which are lightweight, durable, elastic, mouldable, cheap, and hydrophobic, were originally invented for human convenience. However, their non-biodegradability and continuous accumulation at an alarming rate as well as subsequent conversion into micro/nano plastic scale structures via mechanical and physio-chemical degradation pose significant threats to living beings, organisms, and the environment. Various minuscule forms of plastics detected in water, soil, and air are making their passage into living cells. High temperature and ambient humidity increase the degradation potential of plastic polymers photo-catalytically under sunlight or UV-B radiations. Microplastics (MPs) of polyethylene terephthalate, polyethylene, polystyrene, polypropylene, and polyvinyl chloride have been detected in bottled water. These microplastics are entering into the food chain cycle, causing serious harm to all living organisms. MPs entering into the food chain are usually inert in nature, possessing different sizes and shapes. Once they enter a cell or tissue, it causes mechanical damage, induces inflammation, disturbs metabolism, and even lead to necrosis. Various generation routes, types, impacts, identification, and treatment of microplastics entering the water bodies and getting associated with various pollutants are discussed in this review. It emphasizes potential detection techniques like pyrolysis, gas chromatography-mass spectrometry (GC-MS), micro-Raman spectroscopy, and fourier transform infrared spectroscopy (FT IR) spectroscopy for microplastics from water samples.
Mining activities in the Chini Lake catchment area have been extensive for several years, contributing to acid mine drainage (AMD) events with high concentrations of iron (Fe) and other heavy metals impacting the surface water. However, during the restriction period due to the COVID-19 outbreak, anthropogenic activities have been suspended, which clearly shows a good opportunity for a better environment. Therefore, we aimed to analyze the variation of AMD-associated water pollution in three main zones of the Chini Lake catchment area using Sentinel-2 data for the periods pre-movement control order (MCO), during MCO, and post-MCO from 2019 to 2021. These three zones were chosen due to their proximity to mining areas: zone 1 in the northeastern part, zone 2 in the southeastern part, and zone 3 in the southern part of the Chini Lake area. The acid mine water index (AMWI) was a specific index used to estimate acid mine water. The AMWI values from Sentinel-2 images exhibited that the mean AMWI values in all zones during the MCO period decreased by 14% compared with the pre-MCO period. The spatiotemporal analysis found that the highest polluted zones were recorded in zone 1, followed by zone 3 and zone 2. As compared with during the MCO period, the maximum percentage of increment during post-MCO in all zones was up to 25%. The loosened restriction policy has resulted in more AMD flowing into surface water and increased pollution in Chini Lake. As a whole, our outputs revealed that Sentinel-2 data had a major potential for assessing the AMD-associated pollution of water.
Environmental risk assessment of chemicals is reliant on good estimates of product usage information and robust exposure models. Over the past 20 to 30 years, much progress has been made with the development of exposure models that simulate the transport and distribution of chemicals in the environment. However, little progress has been made in our ability to estimate chemical emissions of home and personal care (HPC) products. In this project, we have developed an approach to estimate subnational emission inventory of chemical ingredients used in HPC products for 12 Asian countries including Bangladesh, Cambodia, China, India, Indonesia, Laos, Malaysia, Pakistan, Philippines, Sri Lanka, Thailand, and Vietnam (Asia-12). To develop this inventory, we have coupled a 1 km grid of per capita gross domestic product (GDP) estimates with market research data of HPC product sales. We explore the necessity of accounting for a population's ability to purchase HPC products in determining their subnational distribution in regions where wealth is not uniform. The implications of using high resolution data on inter- and intracountry subnational emission estimates for a range of hypothetical and actual HPC product types were explored. It was demonstrated that for low value products (<500 US$ per capita/annum required to purchase product) the maximum deviation from baseline (emission distributed via population) is less than a factor of 3 and it would not result in significant differences in chemical risk assessments. However, for other product types (>500 US$ per capita/annum required to purchase product) the implications on emissions being assigned to subnational regions can vary by several orders of magnitude. The implications of this on conducting national or regional level risk assessments may be significant. Further work is needed to explore the implications of this variability in HPC emissions to enable the HPC industry and/or governments to advance risk-based chemical management policies in emerging markets.
Contamination by endocrine disrupting compounds (EDCs) concerns the security and sustainability of a drinking water supply system and human exposure via water consumption. This study analyzed the selected EDCs in source (river water, n = 10) and supply (tap water, n = 155) points and the associated risks. A total of 14 multiclass EDCs was detected in the drinking water supply system in Malaysia. Triclosan (an antimicrobial agent) and 4-octylphenol (a plasticizer) were only detected in the tap water (up to 9.74 and 0.44 ng/L, respectively). Meanwhile, chloramphenicol and 4-nonylphenol in the system were below the method detection limits. Bisphenol A was observed to be highest in tap water at 66.40 ng/L (detection: 100%; median concentration: 0.28 ng/L). There was a significant difference in triclosan contamination between the river and tap water (p
The aim of the present study was to appraise the levels of heavy metal contamination (Zn and Pb) in sediment of the Langat River (Selangor, Malaysia). Samples were collected randomly from 15 sampling stations located along the Langat River. The parameters measured were pH, redox potential, salinity, electrical conductivity, loss of ignition, cation exchanges capacity (Na, Mg, Ca, K), and metal ions (Zn and Pb). The geo-accumulation index (I geo) and contamination factor (C f) were applied to determine and classify the magnitude of heavy metal pollution in this urban river sediment. Results revealed that the I geo of Pb indicated unpolluted to moderately polluted sediment at most of the sampling stations, whereas Zn was considered to be within background concentration. The I geo results were refined by the C f values, which showed Pb with very high C f at 12 stations. Zinc, on the other hand, had low to moderate C f values. These findings indicated that the sediment of the Langat River is severely polluted with Pb. The Zn concentration at most sampling points was well below most sediment quality guidelines. However, 40% of the sampling points were found to have a Pb concentration higher than the consensus-based probable effect concentration of 128 mg/kg (concentrations above this value are likely to cause harmful effects). This result not only highlights the severity of Pb pollution in the sediment of the Langat River, but also the potential risk it poses to the environment.
Ever increasing demand for water resources for different purposes makes it essential to have better understanding and knowledge about water resources. As known, groundwater resources are one of the main water resources especially in countries with arid climatic condition. Thus, this study seeks to provide groundwater potential maps (GPMs) employing new algorithms. Accordingly, this study aims to validate the performance of C5.0, random forest (RF), and multivariate adaptive regression splines (MARS) algorithms for generating GPMs in the eastern part of Mashhad Plain, Iran. For this purpose, a dataset was produced consisting of spring locations as indicator and groundwater-conditioning factors (GCFs) as input. In this research, 13 GCFs were selected including altitude, slope aspect, slope angle, plan curvature, profile curvature, topographic wetness index (TWI), slope length, distance from rivers and faults, rivers and faults density, land use, and lithology. The mentioned dataset was divided into two classes of training and validation with 70 and 30% of the springs, respectively. Then, C5.0, RF, and MARS algorithms were employed using R statistical software, and the final values were transformed into GPMs. Finally, two evaluation criteria including Kappa and area under receiver operating characteristics curve (AUC-ROC) were calculated. According to the findings of this research, MARS had the best performance with AUC-ROC of 84.2%, followed by RF and C5.0 algorithms with AUC-ROC values of 79.7 and 77.3%, respectively. The results indicated that AUC-ROC values for the employed models are more than 70% which shows their acceptable performance. As a conclusion, the produced methodology could be used in other geographical areas. GPMs could be used by water resource managers and related organizations to accelerate and facilitate water resource exploitation.
Acid mine drainage (AMD) is recognized as a major environmental challenge in the Western United States, particularly in Colorado, leading to extreme subsurface contamination issue. Given Colorado's arid climate and dependence on groundwater, an accurate assessment of AMD-induced contamination is deemed crucial. While in past, machine learning (ML)-based inversion algorithms were used to reconstruct ground electrical properties (GEP) such as relative dielectric permittivity (RDP) from ground penetrating radar (GPR) data for contamination assessment, their inherent non-linear nature can introduce significant uncertainty and non-uniqueness into the reconstructed models. This is a challenge that traditional ML methods are not explicitly designed to address. In this study, a probabilistic hybrid technique has been introduced that combines the DeepLabv3+ architecture-based deep convolutional neural network (DCNN) with an ensemble prediction-based Monte Carlo (MC) dropout method. Different MC dropout rates (1%, 5%, and 10%) were initially evaluated using 1D and 2D synthetic GPR data for accurate and reliable RDP model prediction. The optimal rate was chosen based on minimal prediction uncertainty and the closest alignment of the mean or median model with the true RDP model. Notably, with the optimal MC dropout rate, prediction accuracy of over 95% for the 1D and 2D cases was achieved. Motivated by these results, the hybrid technique was applied to field GPR data collected over an AMD-impacted wetland near Silverton, Colorado. The field results underscored the hybrid technique's ability to predict an accurate subsurface RDP distribution for estimating the spatial extent of AMD-induced contamination. Notably, this technique not only provides a precise assessment of subsurface contamination but also ensures consistent interpretations of subsurface condition by different environmentalists examining the same GPR data. In conclusion, the hybrid technique presents a promising avenue for future environmental studies in regions affected by AMD or other contaminants that alter the natural distribution of GEP.
Today, insular Southeast Asia is important for both its remarkably rich biodiversity and globally significant roles in atmospheric and oceanic circulation. Despite the fundamental importance of environmental history for diversity and conservation, there is little primary evidence concerning the nature of vegetation in north equatorial Southeast Asia during the Last Glacial Period (LGP). As a result, even the general distribution of vegetation during the Last Glacial Maximum is debated. Here we show, using the stable carbon isotope composition of ancient cave guano profiles, that there was a substantial forest contraction during the LGP on both peninsular Malaysia and Palawan, while rainforest was maintained in northern Borneo. These results directly support rainforest "refugia" hypotheses and provide evidence that environmental barriers likely reduced genetic mixing between Borneo and Sumatra flora and fauna. Moreover, it sheds light on possible early human dispersal events.
The Jakarta Bay is the estuary for thirteen rivers that flow through densely populated and industrialized upstream regions. This condition has the potential to pollute the Jakarta Bay with microplastics that are transported from the upstream river. Meanwhile, people, particularly fishermen, continue to use Jakarta Bay for fishing and aquaculture. This study examined microplastics (MP) abundance in the whole tissues of green mussels (Perna viridis) grown in Jakarta Bay, Indonesia, and their health risks. MP was identified in all 120 green mussels, with fiber > film > fragment being the most common kinds. The abundance of fiber was 19 items/g of tissue, whereas the abundances of fragments and film were 14.5 items/g and 15 item/g, respectively. Fourier transform infrared spectroscopy tests on MP from the tissues of green mussels showed that there were 12 different types of MP polymers. The estimated amount of MP that humans consume each year varied from 29,120 MP items/year to 218,400 MP items/year for different age groups. Based on the total mean number of MP found in the tissues of green mussels and the amount of shellfish consumed per person in Indonesia, it was estimated that people ate 775,180 MP through shellfish each year.
Asymmetrical street aspect ratios, i.e. different height-to-width (H1/W-H2/W) ratios, have not received much attention in the study of urban climates. Putrajaya Boulevard (northeast to southwest orientation) in Malaysia was selected to study the influence of six asymmetrical aspect ratio scenarios on the street microclimate using the Envi-met three-dimensional microclimate model (V3.1 Beta). Putrajaya Boulevard suffers from high surface and air temperature during the day due to the orientation, the low aspect ratio and the wide sky view factor. These issues are a common dilemma in many boulevards. Further, low and high symmetrical streets are incompatible with tropical regions as they offer conflicting properties during the day and at night. These scenarios are examined, therefore, to find asymmetrical streets which are able to reduce the impact of the day microclimate on boulevards, and as an alternative strategy fulfilling tropical day and night climatic conditions. Asymmetrical streets are better than low symmetrical streets in enhancing wind flow and blocking solar radiation, when tall buildings confront winds direction or solar altitudes. Therefore, mitigating heat islands or improving microclimates in asymmetrical streets based on tall buildings position which captures wind or caste shades. In northeast to southwest direction, aspect ratios of 0.8-2 reduce the morning microclimate and night heat islands yet the negative effects during the day are greater than the positive effects in the night. An aspect ratio of 2-0.8 reduces the temperature of surfaces by 10 to 14 °C and the air by 4.7 °C, recommended for enhancing boulevard microclimates and mitigating tropical heat islands.
Sungai Puloh mangrove estuary supports a large diversity of macrobenthic organisms and provides social benefits to the local community. Recently, it became a major recipient of heavy metals originating from industries in the hinterland as a result of industrialization and urbanization. This study was conducted to evaluate mobility and pollution status of heavy metals (Cd, Cu, Ni, Pb, Zn, and Fe) in intertidal surface sediments of this area. Surface sediment samples were collected based on four different anthropogenic sources. Metals concentrations were analyzed using an atomic absorption spectrophotometer (AAS). Results revealed that the mean concentrations were Zn (1023.68 ± 762.93 μg/g), Pb (78.8 ± 49.61 μg/g), Cu (46.89 ± 43.79 μg/g), Ni (35.54 ± 10.75 μg/g), Cd (0.94 ± 0.29 μg/g), and Fe (7.14 ± 0.94%). Most of the mean values of analyzed metals were below both the interim sediment quality guidelines (ISQG-low and ISQG-high), except for Pb concentration (above ISQG-low) and Zn concentration (above ISQG-high), thus suggesting that Pb and Zn may pose some environmental concern. Cadmium, Pb, and Zn concentrations were above the threshold effect level (TEL), indicating seldom adverse effect of these metals on macrobenthic organisms. Pollution load index (PLI) indicated deterioration and other indices revealed the intertidal surface sediment is moderately polluted with Cd, Pb, and Zn. Therefore, this mangrove area requires urgent attention to mitigate further contamination. Finally, this study will contribute to data sources for Malaysia in establishing her own ISQG since it is a baseline study with detailed contamination assessment indices for surface sediment of intertidal mangrove area.
This study was carried out to determine the sorption-desorption, degradation and leaching of napropamide in selected Malaysian soils. The sorption capacities of the selected Malaysian soils for napropamide were the following in descending order: Linau > Teringkap > Gunung Berinchang > Jambu > Rudua > Baging soil. The results indicate that napropamide degradation decreased with increasing soil sorption capacity. Napropamide was leached out earlier in the Baging soil than the other soils. Overall, the application of napropamide in the selected Malaysian soils would not pose a threat to the environment except in soil with low organic matter and clay content and high hydraulic conductivity, such as the Baging soil.
The present study deals with possible contamination of the soil by metal ions which have been affecting the environment. The concentrations of metal ions in 14 borehole samples were studied using the ICP-OES standard method. The degree of contamination was determined on the basis of single element pollution index (SEPI), combined pollution index (CPI), soil enrichment factor (SEF), and geo-accumulation index (Igeo). Geo-accumulation indices and contamination factors indicated moderate to strong contaminations for eight boreholes (BL-1, BL-2, BL-6, BL-8, BL-9, BL-10, BL-12, and BL-13) while the rest were extremely contaminated. Among all the boreholes, BL-3 and BL-11 demonstrated the highest level of Cd(II) and Pb(II) which were found the most polluted sites. The level of metal contamination was also compared with other countries. The development, variation, and limitations regarding the regulations of soil and groundwater contamination can be provided as a helpful guidance for the risk assessment of metal ions in developing countries.
Illuminance level in the softcopy image viewing room is a very important factor to optimize productivity in radiological diagnosis. In today's radiological environment, the illuminance measurements are normally done during the quality control procedure and performed annually. Although the room is equipped with dimmer switches, radiologists are not able to decide the level of illuminance according to the standards. The aim of this study is to develop a simple real-time illuminance detector system to assist the radiologists in deciding an adequate illuminance level during radiological image viewing. The system indicates illuminance in a very simple visual form by using light emitting diodes. By employing the device in the viewing room, illuminance level can be monitored and adjusted effectively.
This study aimed to determine the occurrence of Vibrio parahaemolyticus in cockles (Anadara granosa) at a harvesting area and to detect the presence of virulent strains carrying the thermostable direct hemolysin (tdh) and TDH-related hemolysin genes (trh) using PCR. Of 100 samples, 62 were positive for the presence of V. parahaemolyticus with an MPN (most probable number) value greater than 3.0 (>1100 MPN per g). The PCR analysis revealed 2 samples to be positive for the tdh gene and 11 to be positive for the trh gene. Hence, these results demonstrate the presence of pathogenic V. parahaemolyticus in cockles harvested in the study area and reveal the potential risk of illness associated with their consumption.