Due to the rapid development of economy and society around the world, the most urban city is experiencing tropospheric ozone or commonly known as ground-level air pollutants. The concentration of air pollutants must be identified as an early precaution step by the local environmental or health agencies. This work aims to apply the artificial neural network (ANN) in estimating the ozone concentration forecast in Bangi. It consists of input variables such as temperature, relative humidity, concentration of nitrogen dioxide, time, UVA and UVB rays obtained from routine monitoring, and data recorded. Ten hidden layer is utilized to obtain the optimized ozone concentration, which is the output layer of the ANN framework. The finding showed that the meteorology condition and emission patterns play an important part in influencing the ozone concentration. However, a single network is sufficient enough to estimate the concentration despite any circumstances. Thus, it can be concluded that ANN is able to give reliable and satisfactory estimations of ozone concentration for the following day.
A study was carried out to determine the concentrations of rare earth elements (REEs) in Linggi river sediments collected from 113 sampling locations. The sediment analysis was performed by Neutron activation analysis (NAA) and Inductively coupled plasma - mass spectrometry (ICP-MS). The results of Linggi river sediment were normalized to "recent" reference shale values. The means of total concentrations of REEs (ΣREE), light REEs (ΣLREE) and heavy REEs (ΣHREE) in Linggi sediment were 241.2, 219.2, and 22.0 mg/kg, respectively, which indicates enrichment compared to ΣREE, ΣLREE and ΣHREE reference shale values. Results obtained from enrichment factors (EF) show no enrichment to moderate enrichment of Linggi sediments, indicating the sources of REEs pollution originated from natural and land-based activities. A similar pattern was observed by comparing the REEs values of Linggi sediments to other references shale values. Ce (δCe) and Eu (δEu) anomalies indicate Linggi sediments showed positive anomaly of Ce whilst negative anomaly of Eu.
High population density and economic development attributing to the changes in water quality in Pa Sak River, Lopburi River, and Mekong River have attracted great attention. This research aimed to determine the pollution of heavy metals in collected clams at three different study sites. Bioaccumulation of heavy metals in Asian clam (Corbicula fluminea) may be likely to cause serious health effects on human beings. The clams sampled from three different rivers (Mekong, Pa Sak, and Lopburi) from Thailand were analyzed for the presence of heavy metals (Zn, Cu, Cd, Cr, Mn, and Pb) with an air-acetylene flame atomic absorption spectrophotometer (AAS). Among the heavy metals studied, Zn was recorded as having the highest concentration (127.33-163.65 μg/g) among the three rivers. The observed mean concentration of Cu was in the range of 84.61-127.15 μg/g followed by Mn (13.96-100.63 μg/g), Cr (5.79-15.00 μg/g), Pb (3.43-8.55 μg/g), and Cd (0.88-1.95 μg/g). Overall, Asian clam from Pa Sak River was found to contain high concentrations of Zn, Cu, Cd, Cr, and Pb compared to Mekong and Lopburi River.
The upper catchment region of the Baram River in Sarawak (Malaysian Borneo) is undergoing severe land degradation due to soil erosion. Heavy rainfall with high erosive power has led to a number of soil erosion hotspots. The goal of the present study is to generate an understanding about the spatial characteristics of seasonal and annual rainfall erosivity (R), which not only control sediment delivery from the region but also determine the quantity of material potentially eroded. Mean annual rainfall and rainfall erosivity range from 2170 to 5167 mm and 1632 to 5319 MJ mm ha-1 h-1 year-1, respectively. Seasonal rainfall and rainfall erosivity range from 848 to 1872 mm and 558 to 1883 MJ mm ha-1 h-1 year-1 for the southwest (SW) monsoon, 902 to 2200 mm and 664 to 2793 MJ mm ha-1h-1year-1 for the northeast (NE) monsoon and 400 to 933 mm and 331 to 1075 MJ mm ha-1 h-1 year-1 during the inter-monsoon (IM) period. Linear regression, Spearman's Rho and Mann Kendall tests were applied. Considering the regional mean rainfall erosivity in the study area, all the methods show an overall non-significant decreasing trend (- 9.34, - 0.25 and - 0.30 MJ mm ha-1 h-1 year-1, respectively for linear regression, Spearman's Rho and Mann Kendall tests). However, during SW monsoon and IM periods, rainfall erosivity showed a non-significant decreasing trend (- 25.45, - 0.52, - 0.40, and - 8.86, - 1.07, - 0.77 MJ mm ha-1 h-1 year-1, respectively) whereas in NE, monsoon season erosivity showed a non-significant increasing trend (14.90, 1.59 and 1.60 MJ mm ha-1 h-1 year-1, respectively). The mean erosivity density ranges from 0.77 to 1.38 MJ ha-1 h-1 year-1 and shows decreasing trend. Spatial distribution pattern of erosivity density indicates significantly higher occurrence of erosive rainfall in the lower elevation portion of the study area. The spatial pattern of mean rainfall erosivity trends (linear, Spearman's Rho and Mann Kendall) suggests that the study area can be divided into two zones with increasing rainfall erosivity trends in the northern zone and decreasing trends in the southern zone. These results can be used to plan conservation measures to reduce sediment delivery from localized soil erosion hotspots.
This study presents the use of a wavelet-based time series model to forecast the daily average particulate matter with an aerodynamic diameter of less than 10 μm (PM10) in Peninsular Malaysia. The highlight of this study is the use of a discrete wavelet transform (DWT) in order to improve the forecast accuracy. The DWT was applied to convert the highly variable PM10 series into more stable approximations and details sub-series, and the ARIMA-GARCH time series models were developed for each sub-series. Two different forecast periods, one was during normal days, while the other was during haze episodes, were designed to justify the usefulness of DWT. The models' performance was evaluated by four indices, namely root mean square error, mean absolute percentage error, probability of detection and false alarm rate. The results showed that the model incorporated with DWT yielded more accurate forecasts than the conventional method without DWT for both the forecast periods, and the improvement was more prominent for the period during the haze episodes.
This work investigates the metals concentration in the tissues of Asian swamp eel, Monopterus albus. Five selected tissues, including liver, gill, bone, skin, and muscle were examined for the concentration of Zn, Cu, Cd, Pb, and Ni. The concentrations of Cd and Pb were found high in the muscle tissues of the eels. Additionally, high amounts of Zn and Cu metals were observed in the liver, whereas the Cd, Pb, and Ni metals were highly detected in gill. The accumulation of Zn, Cu, Cd, Pb, and Ni in both skin and bone of the eel seems to vary between seasons. Low levels of Zn, Cu, and Ni were identified in the muscle tissues of the eels. This study revealed that the concentration of Cd and Pb in the muscle tissues of Asian swamp eels exceeded the permissible limits by the US EPA, suggesting the consumption of the muscle may be hazardous and can severely affect one's health.
Plastic debris is a worldwide problem. This is particularly acute in the Pacific region, where its scale is a reason for serious concerns. There is an obvious need for studies to assess the extent to which plastic debris affects the Pacific. Therefore, this research aims to address this need by undertaking a systematic assessment of the ecological and health impacts of plastic debris on Pacific islands. Using pertinent historical qualitative and quantitative data of the distribution of plastic debris in the region, this study identified pollution and contamination trends and risks to ecosystems, and suggests some measures which may be deployed to address the identified problems. The study illustrates the fact that Pacific Island States are being disproportionately affected by plastic, and reiterates that further studies and integrated strategies are needed, involving public education and empowerment, governmental action, as well as ecologically sustainable industry leadership. It is also clear that more research is needed in respect of developing alternatives to conventional plastic, by the production of bio-plastic, i.e. plastic which is produced from natural (e.g. non-fossil fuel-based sources) materials, and which can be fully biodegradable.
To manage and conserve biodiversity, one must know what is being lost, where, and why, as well as which remedies are likely to be most effective. Metabarcoding technology can characterise the species compositions of mass samples of eukaryotes or of environmental DNA. Here, we validate metabarcoding by testing it against three high-quality standard data sets that were collected in Malaysia (tropical), China (subtropical) and the United Kingdom (temperate) and that comprised 55,813 arthropod and bird specimens identified to species level with the expenditure of 2,505 person-hours of taxonomic expertise. The metabarcode and standard data sets exhibit statistically correlated alpha- and beta-diversities, and the two data sets produce similar policy conclusions for two conservation applications: restoration ecology and systematic conservation planning. Compared with standard biodiversity data sets, metabarcoded samples are taxonomically more comprehensive, many times quicker to produce, less reliant on taxonomic expertise and auditable by third parties, which is essential for dispute resolution.
The objective of this study is to delineate groundwater flowing well zone potential in An-Najif Province of Iraq in a data-driven evidential belief function model developed in a geographical information system (GIS) environment. An inventory map of 68 groundwater flowing wells was prepared through field survey. Seventy percent or 43 wells were used for training the evidential belief functions model and the reset 30 % or 19 wells were used for validation of the model. Seven groundwater conditioning factors mostly derived from RS were used, namely elevation, slope angle, curvature, topographic wetness index, stream power index, lithological units, and distance to the Euphrates River in this study. The relationship between training flowing well locations and the conditioning factors were investigated using evidential belief functions technique in a GIS environment. The integrated belief values were classified into five categories using natural break classification scheme to predict spatial zoning of groundwater flowing well, namely very low (0.17-0.34), low (0.34-0.46), moderate (0.46-0.58), high (0.58-0.80), and very high (0.80-0.99). The results show that very low and low zones cover 72 % (19,282 km(2)) of the study area mostly clustered in the central part, the moderate zone concentrated in the west part covers 13 % (3481 km(2)), and the high and very high zones extended over the northern part cover 15 % (3977 km(2)) of the study area. The vast spatial extension of very low and low zones indicates that groundwater flowing wells potential in the study area is low. The performance of the evidential belief functions spatial model was validated using the receiver operating characteristic curve. A success rate of 0.95 and a prediction rate of 0.94 were estimated from the area under relative operating characteristics curves, which indicate that the developed model has excellent capability to predict groundwater flowing well zones. The produced map of groundwater flowing well zones could be used to identify new wells and manage groundwater storage in a sustainable manner.
Results are presented of a demonstration of real-time fish blast location in Sabah, Malaysia using a networked hydroacoustic array based on the ShotSpotter gunshot location system. A total of six acoustic sensors - some fixed and others mobile - were deployed at ranges from 1 to 9 km to detect signals from controlled test blasts. This allowed the blast locations to be determined to within 60 m accuracy, and for the calculated locations to be displayed on a map on designated internet-connected computers within 10 s. A smaller three-sensor system was then installed near Semporna in Eastern Sabah that determined the locations of uncontrolled blasts set off by local fishermen. The success of these demonstrations shows that existing technology can be used to protect reefs and permit more effective management of blast fishing activity through improved detection and enforcement measures and enhanced community engagement.
Coral cover on reefs is declining globally due to coastal development, overfishing and climate change. Reefs isolated from direct human influence can recover from natural acute disturbances, but little is known about long term recovery of reefs experiencing chronic human disturbances. Here we investigate responses to acute bleaching disturbances on turbid reefs off Singapore, at two depths over a period of 27 years. Coral cover declined and there were marked changes in coral and benthic community structure during the first decade of monitoring at both depths. At shallower reef crest sites (3-4 m), benthic community structure recovered towards pre-disturbance states within a decade. In contrast, there was a net decline in coral cover and continuing shifts in community structure at deeper reef slope sites (6-7 m). There was no evidence of phase shifts to macroalgal dominance but coral habitats at deeper sites were replaced by unstable substrata such as fine sediments and rubble. The persistence of coral dominance at chronically disturbed shallow sites is likely due to an abundance of coral taxa which are tolerant to environmental stress. In addition, high turbidity may interact antagonistically with other disturbances to reduce the impact of thermal stress and limit macroalgal growth rates.
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.
Rare earth elements (REEs) are becoming significant due to their huge applications in many industries, large-scale mining and refining activities. Increasing usage of such metals pose negative environmental impacts. In this research ICP-MS has been used to analyze soil samples collected from former ex-mining areas in the depths of 0-20 cm, 21-40 cm, and 41-60 cm of residential, mining, natural, and industrial areas of Perak. Principal component analysis (PCA) revealed that soil samples taken from different mining, industrial, residential, and natural areas are separated into four clusters. It was observed that REEs were abundant in most of the samples from mining areas. Concentration of the rare elements decrease in general as we move from surface soil to deeper soils.
There is a paucity of information about the occurrence of microplastics (MPs) in edible fish tissues. Here, we investigated the potential presence of MPs in the excised organs (viscera and gills) and eviscerated flesh (whole fish excluding the viscera and gills) of four commonly consumed dried fish species (n = 30 per species). The MP chemical composition was then determined using micro-Raman spectroscopy and elemental analysis with energy-dispersive X-ray spectroscopy (EDX). Out of 61 isolated particles, 59.0% were plastic polymers, 21.3% were pigment particles, 6.55% were non-plastic items (i.e. cellulose or actinolite), while 13.1% remained unidentified. The level of heavy metals on MPs or pigment particles were below the detection limit. Surprisingly, in two species, the eviscerated flesh contained higher MP loads than the excised organs, which highlights that evisceration does not necessarily eliminate the risk of MP intake by consumers. Future studies are encouraged to quantify anthropogenic particle loads in edible fish tissues.
This study investigated the occurrence of nine pharmaceuticals (amoxicillin, caffeine, chloramphenicol, ciprofloxacin, dexamethasone, diclofenac, nitrofurazone, sulfamethoxazole, and triclosan) and to evaluate potential risks (human health and ecotoxicological) in Lui, Gombak and Selangor (Malaysia) rivers using commercial competitive Enzyme-Linked Immunosorbent Assay (ELISA) kit assays. Physicochemical properties of these rivers showed the surface samples belong to Class II of Malaysian National Water Quality Standards which requires conventional treatment before consumption. All the pharmaceuticals were detected in all three rivers except for triclosan, dexamethasone and diclofenac which were not detected in few of sampling locations in these three rivers. Highest pharmaceutical concentrations were detected in Gombak river in line of being as one of the most polluted rivers in Malaysia. Ciprofloxacin concentrations were detected in all the sampling locations with the highest at 299.88 ng/L. While triclosan, dexamethasone and diclofenac concentrations were not detected in a few of sampling locations in these three rivers. All these nine pharmaceuticals were within the levels reported previously in literature. Pharmaceutical production, wastewater treatment technologies and treated sewage effluent were found as the potential sources which can be related with pharmaceuticals occurrence in surface water samples. Potential human risk assessment showed low health risk except for ciprofloxacin and dexamethasone. Instead, ecotoxicological risk assessment indicated moderate risks were present for these rivers. Nevertheless, results confirmation using instrumental techniques is needed for higher degree of specificity. It is crucial to continuously monitor the surface water bodies for pharmaceuticals using a cost-effective prioritisation approach to assess sensitive sub-populations risk.
Lead contamination in topsoil of the mining and smelting area of Mitrovica, Kosovo, was investigated for total concentrations and chemical fractions by sequential extraction analysis, mineralogical fractions by X-ray diffraction (XRD) and scanning electron microscopy with energy-dispersive X-ray spectrometer (SEM-EDX). The study revealed that all samples contained Pb exceeding USEPA standard of 400 mg kg-1. The highest total concentration of Pb (125,000 mg kg-1) was the soil from the former smelter. Sequential extraction results showed that the predominant form of Pb was associated with Fe-Mn oxide-bound fraction which ranged from 45.37 to 71.61% of total concentrations, while carbonate and silicate Pb-binding fractions were dominant when physical measurements (XRD and SEM-EDX) were applied. Application of Pb isotope ratios (206Pb/207Pb and 208Pb/206Pb), measured by inductively coupled plasma mass spectrometry, identified that Pb contamination is originated from similar anthropogenic source. The results reflected that the Pb contamination in the soil of this area is serious. In order to provide proper approaches on remediation and prevention of health impacts to the people in this area, a continuous monitoring and health risk assessment are recommended.
A study was conducted in an oil palm plantation in Peninsular Malaysia to elucidate the effects of applying Magnesium Rich Synthetic Gypsum (MRSG), a by-product of chemical plant, on the chemical properties of soil, the uptake of heavy metals by the palm trees, the oil quality and its impact on the surrounding environment. The results showed that MRSG application onto soil cropped to oil palm could bring positive impact in terms of soil chemical properties and oil palm production. The quality of the oil was not significantly affected by the continuous MRSG application as shown by the low heavy metals and trace elements of concern content (Cu: 0.062 mg/kg; Fe: 2.10 mg/kg; Mn: 1.93 mg/kg; Pb: 0.006 mg/kg; Zn: 0.103 mg/kg; Cr: 0.354 mg/kg; Ni: 0.037 mg/kg). From the I-geochem index, the soil was found to have values ranging from -3.81 to -1.03 which is considered as uncontaminated. Further, its application did not result in negative impact on the surrounding environment; hence, the quality of the soil and surface water in the plantation and/or the surrounding area remained intact. Phytotoxic elements in the oil palm tissue (As: 0.12 mg/kg; Se: 0.05 mg/kg; Zn: 1.48 mg/kg; Ce: 0.47 mg/kg; La: 0.26 mg/kg; Sr: 3.03 mg/kg) and cytotoxic elements in the oil were below the acceptable limit. Based on the results of the Environmental Monitoring out during the period of the study, it was concluded that application of the by-product of the chemical plant as a source of Mg to enhance soil fertility in the oil palm plantation was considered safe and sustainable. The effects of applying MRSG and Chinese kieserite was almost similar. So, MRSG can be used as a possible source of Mg to replace Chinese kieserite for oil palm production on the Ultisols in Peninsular Malaysia.
The objective of this study was to identify the spatial and temporal variabilities of selected nutrients in the Setiu Wetlands Lagoon (SWL), Malaysia. Water samples were collected quarterly at ten monitoring sites. This study presents results from a 10-year field investigation (2003 to 2010 and 2014 to 2015) of water quality in the SWL. For the spatial pattern, four clusters were identified with hierarchical cluster analysis. Analysis of the temporal trend shows that the high total suspended solid loading in 2010 was due to large-scale land clearing upstream of the SWL. The enrichment of ammonium after 2010 could plausibly be due to land-based aquaculture diffuse discharges. In 2005-2007, expansion of oil palm plantations within the Setiu catchment had doubled the phosphorus concentration in the SWL. The natural and anthropogenic alterations of the lagoon inlets profoundly influenced the spatial distribution patterns of nutrients in the SWL. These results suggest that intense anthropogenic disturbances close to the SWL accounted for the water quality deterioration.
Managers of water quality and water monitoring programs are often faced with constraints in terms of budget, time, and laboratory capacity for sample analysis. In such situation, the ideal solution is to reduce the number of sampling sites and/or monitored variables. In this case, selecting appropriate monitoring sites is a challenge. To overcome this problem, this study was conducted to statistically assess and identify the appropriate sampling stations of monitoring network under the monitored parameters. To achieve this goal, two sets of water quality data acquired from two different monitoring networks were used. The hierarchical agglomerative cluster analysis (HACA) were used to group stations with similar characteristics in the networks, the time series analysis was then performed to observe the temporal variation of water quality within the station clusters, and the geo-statistical analysis associated Kendall's coefficient of concordance were finally applied to identify the most appropriate and least appropriate sampling stations. Based on the overall result, five stations were identified in the networks that contribute the most to the knowledge of water quality status of the entire river. In addition, five stations deemed less important were identified and could therefore be considered as redundant in the network. This result demonstrated that geo-statistical technique coupled with Kendall's coefficient of concordance can be a reliable method for water resource managers to identify appropriate sampling sites in a river monitoring network.
The study was performed to examine the occurrence of endocrine disrupting chemicals (EDCs), including four steroid estrogens, one plasticizer, and three preservatives in the Mahakam River, Indonesia. The physicochemical analysis of river water and sediment quality parameters were determined as well as the concentration of EDCs. The range of values for pH, total dissolved solids (TDS), dissolved oxygen (DO), biochemical oxygen demand (BOD), total suspended solids (TSS), nitrate, ammonium, phosphate, and oil/grease in river water and sediment were higher than recommended limits prescribed by the World Health Organization's Guidelines for Drinking-water Quality (GDWQ). Bisphenol A (BPA) was the most widely found EDC with the highest concentration level at 652 ng/L (mean 134 ng/L) in the river water and ranged from ND (not detected) to 952 ng/L (mean 275 ng/L) in the sediment. Correlation analysis to investigate the relationship between the EDCs' concentrations in water and sediment also revealed a significant correlation (R2 = 0.93) between the EDCs' concentrations. High concentrations of EDCs are found in urban and residential areas because these compounds are commonly found in both human and animal bodies, resulting in the disposal of EDCs into canals and rivers in urban and suburban areas, as well as livestock manure and waste that is generated from intensive livestock farming around the suburban area.