To provide baseline information for the marine ecosystem of Hormozgan province, the distribution of petroleum hydrocarbons was evaluated in 52 stations involved in the mangrove and coastline ecosystem. Coastline sampling sites included areas facing harbor, river, domestic and industrial discharge. Sediment samples were analyzed based on ultraviolet fluorescence spectroscopy. Petroleum hydrocarbons showed narrow variations ranging from non-detectable (ND) to 1.71 and from 0.2 to 0.63μg/g dry weight for coastline and mangrove sediments, respectively. The detected concentrations for total petroleum hydrocarbons were lower than guideline values for ecological risk. Furthermore, the minimum environmental risk was confirmed by background levels for the Persian Gulf, the Sea of Oman, and detected values for reference areas. The results were regarded as background data in the studied area, and, considering the rapid expansion of activities related to the petroleum industry in Hormozgan province, the continuous monitoring of pollutants is recommended.
Studies on the occurrence of pharmaceutical residues in drinking water were conducted especially in developed countries. However, limited studies reported the occurrence of pharmaceutical residues in developing countries. Thus, this study is conducted to fill the knowledge gap of pharmaceutical residue occurrences in developing countries, particularly in Malaysia, along with public awareness level and its potential human health risk. This study investigates public awareness level of drinking water quality and pharmaceutical handling, the occurrence of nine pharmaceutical residues (amoxicillin, caffeine, chloramphenicol, ciprofloxacin, dexamethasone, diclofenac, nitrofurazone, sulfamethoxazole, and triclosan) and potential human health risks in drinking water from Kajang (Malaysia) using commercially competitive enzyme-linked immunosorbent assay kits. In general, the public awareness level of Kajang population showed poor knowledge (82.02%), and less positive attitude (98.88%) with a good practice score (57.3%). Ciprofloxacin was detected at the highest concentration (0.667 ng/L) while amoxicillin was at the lowest concentration (0.001 ng/L) in drinking water from Kajang (Malaysia). Nevertheless, all the reported occurrences were lower than previous studies conducted elsewhere. There was no appreciable potential human health risk for all the pharmaceutical residues as the risk quotient (RQ) values were less than 1 (RQ
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 clastogenic and mutagenic effects of the insecticide Dimethoate (Cygon-2E), herbicides Atrazine, Simazine (Princep), Dicamba (Banvel D) and Picloram (Tordon) were studied using the Tradescantia-micronucleus (Trad-MCN) and Tradescantia-stamen hair mutation (Trad-SHM) assays. In clone 4430, dimethoate fumes both significantly increased the pink mutation events and reduced the number of stamen hairs per filament with increasing dosages. The pink mutation events were elevated by the liquid treatment with Picloram at 100 ppm concentration. The result of Trad-MCN test on Dimethoate fumes was not significantly different between the control and treated groups. The herbicide Atrazine showed positive effects at 10-50 ppm dose (liquid) and signs of overdose at 100 and 500 ppm concentrations. Simazine was mildly positive in elevating the MCN frequencies in the dose range of 5 to 200 ppm (liquid doses). Both Dicamba and Picloram induced a dosage-related increase in MCN frequencies in the Trad-MCN tests using Tradescantia clone 03. However, in higher dosages (200 ppm or higher), there were signs of overdose, reduction of MCN frequencies and physical damage of the leaves and buds of plant cuttings.
Multiple interactions of geogenic and anthropogenic activities can trigger groundwater pollution in the tropical savanna watershed. These interactions and resultant contamination have been studied using applied geochemical modeling, conventional hydrochemical plots, and multivariate geochemometric methods, and the results are presented in this paper. The high alkalinity values recorded for the studied groundwater samples might emanate from the leaching of carbonate soil derived from limestone coupled with low rainfall and high temperature in the area. The principal component analysis (PCA) unveils three components with an eigenvalue > 1 and a total dataset variance of 67.37%; this implies that the temporary hardness of the groundwater and water-rock interaction with evaporite minerals (gypsum, halite, calcite, and trona) is the dominant factor affecting groundwater geochemistry. Likewise, the PCA revealed anthropogenic contamination by discharging [Formula: see text] [Formula: see text][Formula: see text] and [Formula: see text] from agricultural activities and probable sewage leakages. Hierarchical cluster analysis (HCA) also revealed three clusters; cluster I reflects the dissolution of gypsum and halite with a high elevated load of [Formula: see text] released by anthropogenic activities. However, cluster II exhibited high [Formula: see text] and [Formula: see text] loading in the groundwater from weathering of bicarbonate and sylvite minerals. Sulfate ([Formula: see text]) dominated cluster III mineralogy resulting from weathering of anhydrite. The three clusters in the Maiganga watershed indicated anhydrite, gypsum, and halite undersaturation. These results suggest that combined anthropogenic and natural processes in the study area are linked with saturation indexes that regulate the modification of groundwater quality.
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.
This study integrates the application of Dempster-Shafer-driven evidential belief function (DS-EBF) methodology with remote sensing and geographic information system techniques to analyze surface and subsurface data sets for the spatial prediction of groundwater potential in Perak Province, Malaysia. The study used additional data obtained from the records of the groundwater yield rate of approximately 28 bore well locations. The processed surface and subsurface data produced sets of groundwater potential conditioning factors (GPCFs) from which multiple surface hydrologic and subsurface hydrogeologic parameter thematic maps were generated. The bore well location inventories were partitioned randomly into a ratio of 70% (19 wells) for model training to 30% (9 wells) for model testing. Application results of the DS-EBF relationship model algorithms of the surface- and subsurface-based GPCF thematic maps and the bore well locations produced two groundwater potential prediction (GPP) maps based on surface hydrologic and subsurface hydrogeologic characteristics which established that more than 60% of the study area falling within the moderate-high groundwater potential zones and less than 35% falling within the low potential zones. The estimated uncertainty values within the range of 0 to 17% for the predicted potential zones were quantified using the uncertainty algorithm of the model. The validation results of the GPP maps using relative operating characteristic curve method yielded 80 and 68% success rates and 89 and 53% prediction rates for the subsurface hydrogeologic factor (SUHF)- and surface hydrologic factor (SHF)-based GPP maps, respectively. The study results revealed that the SUHF-based GPP map accurately delineated groundwater potential zones better than the SHF-based GPP map. However, significant information on the low degree of uncertainty of the predicted potential zones established the suitability of the two GPP maps for future development of groundwater resources in the area. The overall results proved the efficacy of the data mining model and the geospatial technology in groundwater potential mapping.
The spatial distribution of 19 polycyclic aromatic hydrocarbons (tPAHs) was quantified in aquacultures located in intertidal mudflats of the west coast of Peninsular Malaysia in order to investigate bioaccumulation of PAH in blood cockles, Anadara granosa (A. granosa). Fifty-four samples from environmental matrices and A. granosa were collected. The sampling locations were representative of a remote area as well as PAH-polluted areas. The relationship of increased background levels of PAH to anthropogenic PAH sources in the environment and their effects on bioaccumulation levels of A. granosa are investigated in this study. The levels of PAH in the most polluted station were found to be up to ten-fold higher than in remote areas in blood cockle. These high concentrations of PAHs reflected background contamination, which originates from distant airborne and waterborne transportation of contaminated particles. The fraction and source identification of PAHs, based on fate and transport considerations, showed a mix of petrogenic and pyrogenic sources. The relative biota-sediment accumulation factors (RBSAF), relative bioaccumulation factors from filtered water (RBAFw), and from suspended particulate matter (SPM) (RBAFSP) showed higher bioaccumulations of the lower molecular weight of PAHs (LMWs) in all stations, except Kuala Juru, which showed higher bioaccumulation of the higher molecular weight of PAHs (HMWs). Calculations of bioaccumulation factors showed that blood cockle can accumulate PAHs from sediment as well as water samples, based on the physico-chemical characteristics of habitat and behaviour of blood cockles. Correlations among concentrations of PAHs in water, SPM, sediment and A. granosa at the same sites were also found. Identification of PAH levels in different matrices showed that A. granosa can be used as a good biomonitor for LMW of PAHs and tPAHs in mudflats. Considering the toxicity and carcinogenicity of PAHs, the bioaccumulation by blood cockles are a potential hazard for both blood cockles and their consumers.
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.
This work presents a study of human hair as a bio-indicator for detection of heavy metals as part of environmental health surveillance programs project to develop a subject of interest in the biomedical and environmental sciences. A total of 34 hair samples were analyzed that consisting of 29 samples from sanitation workers and five samples from students. The hair samples were prepared and treated in accordance to the International Atomic Energy Agency (IAEA) recommendations. The concentrations of heavy metals were analyzed using the energy dispersive X-ray fluorescence (EDXRF) technique by X-50 Mobile X-ray Fluorescence (XRF) at Oceanography Institute, Universiti Malaysia Terengganu. The performance of EDXRF analyzer was tested by Standard Reference Material (SRM 2711) Montana Soil which was in good agreement with certified value within 14% deviations except for Hg. While seven heavy metals: Mn, Fe, Ni, Cu, Zn, Se, and Sb were detected in both groups, three additional elements, i.e. As, Hg and Pb, were detected only in sanitation workers group. For sanitation workers group, the mean concentration of six elements, Mn, Fe, Cu, Zn, Se, and Sb, shows elevated concentration as compared to the control samples concentration. Results from both groups were compared and discussed in relation to their respective heavy metals concentrations.
In February 2013, forty-seven Notched threadfin bream, the Nemipterus peronii, were sampled from the eastern coastal waters of the South China Sea. The concentration of various elements, namely cadmium (Cd), chromium (Cr), copper (Cu), mercury (Hg), strontium (Sr), manganese (Mn), selenium (Se), Lead (Pb), nickel (Ni), aluminum (Al), arsenic (As), iron (Fe), and Zinc (Zn) were analyzed in the liver, muscle, and kidney organs of the host, as well as in their parasites Hysterothalycium reliquens (nematode) and the Paraphilometroides nemipteri (nematode), using inductively coupled plasma mass spectrometry (ICP-MS). The former group of parasites showed highest accumulation capacity for Cr, Cu, Fe, Mn, Se, Ni, and Zn while the latter group had high accumulation potential of As, Hg, Cd, Al, Pb, and Sr. The divergence in heavy-metal accumulation profiles of both nematodes is linked with the specificity of microhabitats, cuticle morphology, and interspecific competition. The outcome of this study indicates that both parasite models can be used for biomonitoring of metal pollution in marine ecosystems.
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.
Fine particulate matter (PM2.5) is a significant air pollutant that drives the most chronic health problems and premature mortality in big metropolitans such as Delhi. In such a context, accurate prediction of PM2.5 concentration is critical for raising public awareness, allowing sensitive populations to plan ahead, and providing governments with information for public health alerts. This study applies a novel hybridization of extreme learning machine (ELM) with a snake optimization algorithm called the ELM-SO model to forecast PM2.5 concentrations. The model has been developed on air quality inputs and meteorological parameters. Furthermore, the ELM-SO hybrid model is compared with individual machine learning models, such as Support Vector Regression (SVR), Random Forest (RF), Extreme Learning Machines (ELM), Gradient Boosting Regressor (GBR), XGBoost, and a deep learning model known as Long Short-Term Memory networks (LSTM), in forecasting PM2.5 concentrations. The study results suggested that ELM-SO exhibited the highest level of predictive performance among the five models, with a testing value of squared correlation coefficient (R2) of 0.928, and root mean square error of 30.325 µg/m3. The study's findings suggest that the ELM-SO technique is a valuable tool for accurately forecasting PM2.5 concentrations and could help advance the field of air quality forecasting. By developing state-of-the-art air pollution prediction models that incorporate ELM-SO, it may be possible to understand better and anticipate the effects of air pollution on human health and the environment.
In this work, a genetic algorithm is applied for the automatic detection of oil spills. The procedure is implemented using sequences from RADARSAT-2 SAR ScanSAR Narrow single-beam data acquired in the Gulf of Mexico. The study demonstrates that the implementation of crossover allows for the generation of an accurate oil spill pattern. This conclusion is confirmed by the receiver-operating characteristic (ROC) curve. The ROC curve indicates that the existence of oil slick footprints can be identified using the area between the ROC curve and the no-discrimination line of 90%, which is greater than that of other surrounding environmental features. In conclusion, the genetic algorithm can be used as a tool for the automatic detection of oil spills, and the ScanSAR Narrow single-beam mode serves as an excellent sensor for oil spill detection and survey.
Malaysia is facing an increasing trend in industrial solid waste generation due to industrial development. Thus, there is a paramount need in taking practical actions and measurements to move toward sustainable industrial waste management. The main aim of this study is to assess practicing solid waste minimization by manufacturing firms. Analysis showed that majority of firms (92%) dispose of their wastes rather than utilize other sustainable waste management options. Also, waste minimization methods such as segregation of wastes, on-site recycle and reuse, improved housekeeping, and equipment modification were found to have significant contribution to waste reduction (p
Identification of Pelargonium radula as bioindicator for mercury (Hg) detection confers a new hope for monitoring the safety of drinking water consumption. Hg, like other non-essential metals, inflicts the deterioration of biological functions in human and other creatures. In the present study, effects of Hg on the physiology and biochemical content of P. radula were undertaken to understand the occurrence of the morphological changes observed. Young leaves of P. radula were treated with different concentrations of Hg-containing solution (0.5, 1.0 and 2.0 ppb) along with controls for 4 h, prior to further analysis. Elevated Hg concentration in treatment solution significantly prompted an increased accumulation of Hg in the leaf tissues. Meanwhile, total protein, chlorophyll and low molecular mass thiol contents (cysteine, glutathione and oxidized glutathione) decreased as Hg accumulation increased. However, phytochelatin 2 productions were induced in the treated leaves, in comparison to the control. Based on these findings, it is postulated that as low as 0.5 ppb of Hg interferes with the metabolic processes of plant cells, which was reflected from the morphological changes exhibited on P. radula leaves-the colour of the Hg-treated leaves changed from green to yellowish-brown, became chlorosis and wilted. Changes in the tested characteristics of plant are closely related to the Hg-induced morphological changes on P. radula leaves, a potential bioindicator for detecting Hg in drinking water.
This is the first extensive report on linear alkylbenzenes (LABs) as sewage molecular markers in surface sediments collected from the Perlis, Kedah, Merbok, Prai, and Perak Rivers and Estuaries in the west of Peninsular Malaysia. Sediment samples were extracted, fractionated, and analyzed using gas chromatography mass spectrometry (GC-MS). The concentrations of total LABs ranged from 68 to 154 (Perlis River), 103 to 314 (Kedah River), 242 to 1062 (Merbok River), 1985 to 2910 (Prai River), and 217 to 329 ng g(-1) (Perak River) dry weight (dw). The highest levels of LABs were found at PI3 (Prai Estuary) due to the rapid industrialization and population growth in this region, while the lowest concentrations of LABs were found at PS1 (upstream of Perlis River). The LABs ratio of internal to external isomers (I/E) in this study ranged from 0.56 at KH1 (upstream of Kedah River) to 1.35 at MK3 (Merbok Estuary) indicating that the rivers receive raw sewage and primary treatment effluents in the study area. In general, the results of this paper highlighted the necessity of continuation of water treatment system improvement in Malaysia.
Rapid industrialization and urbanization have resulted in environmental pollution and unsustainable development of cities. The concentration of 12 potentially toxic metal(loid)s in windowsill dust samples (n = 50) were investigated from different functional areas of Qom city with the highest level of urbanization in Iran. Spatial analyses (ArcGIS 10.3) and multivariate statistics including Principal Component Analysis and Spearman correlation (using STATISTICA-V.12) were adopted to scrutinize the possible sources of pollution. The windowsill dust was very highly enriched with Sb (50 mg/kg) and Pb (1686 mg/kg). Modified degree of contamination (mCd) and the pollution load indices (PLIzone) indicate that windowsill dust in all functional areas was polluted in the order of industrial > commercial > residential > green space. Arsenic, Cd, Mo, Pb, Sb, Cu, and Zn were sourced from a mixture of traffic and industrial activities, while Mn in the dust mainly stemmed from mining activities. Non-carcinogenic health risk (HI) showed chronic exposure of Pb for children in the industrial zone (HI = 1.73). The estimations suggest the possible carcinogenic risk of As, Pb, and Cr in the dust. The findings of this study reveal poor environmental management of the city. Emergency plans should be developed to minimize the health risks of dust to residents.
Sediment can accumulate trace elements in the environment. This study profiled the magnitude of As, Ba, Cd, Co, Cu, Cr, Ni, Pb, Se, and Zn pollution in surface sediments of the west coast of Peninsular Malaysia. Trace elements were digested using aqua regia and were analyzed using the inductively coupled plasma-mass spectrometry. The extent of elemental pollution was evaluated using with the enrichment factor (EF) and geoaccumulation index (Igeo). This study found that the elemental distribution in the sediment in descending order was Zn > Ba > Cr > Pb > Cu > As > Ni > Co > Se > Cd. Zn concentrations in all samples were below the interim sediment quality guideline (ISQG) (124 mg/kg). In contrast, Cd concentrations (2.34 ± 0.01 mg/kg) at Station 31 (Merlimau) exceeded the ISQG (0.70 mg/kg), and the concentrations of As in the samples from Station 9 (Tanjung Dawai) exceeded the probable effect level (41.60 mg/kg). The Igeo and EF revealed that Station 9 and Station 31 were extremely enriched with Se and Cd, respectively. All stations posed low ecological risk, except Station 31, which had moderate ecological risk. The outputs from this study are expected to provide the background levels of pollutants and help develop regional sediment quality guideline values. This study is also important in aiding relevant authorities to set priorities for resources management and policy implementation.
Particulate phosphorus was the dominant phosphorus species and accounted for 72 ± 5% of total phosphorus in coastal habitats, 63 ± 4% in estuaries, 58 ± 6% in lakes and 80 ± 7% in aquaculture farms whereas dissolved inorganic phosphorus (DIP) and dissolved organic phosphorus (DOP) were minor components. Correlation analyses (DIP vs Chl a; R2 = 0.407, df = 31, p