The occurrence and estrogenic activities of steroid estrogens, such as the natural estrone (E1), 17β estradiol (E2), and estriol (E3), as well as the synthetic 17α-ethynylestradiol (EE2), were investigated in eight sampling points along the Langat River (Malaysia). Surface water samples were collected at 0.5 m and surface sediment 0-5 cm from the river surface. Instrument analysis of steroid estrogens was determined by UPLC-ESI-MS with an ultra-performance liquid chromatograph (Perkin Elmer FX15) coupled to a Q Trap function mass spectrophotometer (model 3200: AB Sciex). Steroid estrogen concentrations were higher in the Langat River sediments than those in its surface water. In surface water, E1 was not detected in any sampling point, E2 was only detected in two midstream sampling points (range 0-0.004 ng/L), E3 in three sampling points (range 0-0.002 ng/L), and EE2 in four sampling points (range 0-0.02 ng/L). E1 and E2 were detected in sediments from all sampling points, E3 in five sampling points, while EE2 only in one midstream sample (3.29E-4 ng/g). Sewage treatment plants, farming waste, and agricultural activities particularly present midstream and downstream were identified as potential sources of estrogens. Estrogenic activity expressed as estradiol equivalents (EEQs) was below 1 ng/L in all samples for both surface water and sediment, indicating therefore a low potential estrogenic risk to the aquatic environment. Although the health risks are still uncertain for drinking water consumers exposed to low levels of steroid estrogen concentrations, Langat River water is unacceptable for direct drinking purposes without treatment. Further studies of endocrine disruptors in Malaysian waters are highly recommended.
Principal component analysis (PCA) is capable of handling large sets of data. However, lack of consistent method in data pre-treatment and its importance are the limitations in PCA applications. This study examined pre-treatments methods (log (x + 1) transformation, outlier removal, and granulometric and geochemical normalization) on dataset of Mengkabong Lagoon, Sabah, mangrove surface sediment at high and low tides. The study revealed that geochemical normalization using Al with outliers removal resulted in a better classification of the mangrove surface sediment than that outliers removal, granulometric normalization using clay and log (x + 1) transformation. PCA output using geochemical normalization with outliers removal demonstrated associations between environmental variables and tides of mangrove surface sediment, Mengkabong Lagoon, Sabah. The PCA outputs at high and low tides also provided to better interpret information about the sediment and its controlling factors in the intertidal zone. The study showed data pre-treatment method to be a useful procedure to standardize the datasets and reducing the influence of outliers.
This study aims to determine the status of potentially toxic element concentrations of road dust in a medium-sized city (Rawang, Malaysia). This study adopts source identification via enrichment factor, Pearson correlation analysis, and Fourier spectral analysis to identify sources of potentially toxic element concentrations in road dust in Rawang City, Malaysia. Health risk assessment was conducted to determine potential health risks (carcinogenic and non-carcinogenic risks) among adults and children via multiple pathways (i.e., ingestion, dermal contact, and inhalation). Mean of potentially toxic element concentrations were found in the order of Pb > Zn > Cr(IV) > Cu > Ni > Cd > As > Co. Source identification revealed that Cu, Cd, Pb, Zn, Ni, and Cr(IV) are associated with anthropogenic sources in industrial and highly populated areas in northern and southern Rawang, cement factories in southern Rawang, as well as the rapid development and population growth in northwestern Rawang, which have resulted in high traffic congestion. Cobalt, Fe, and As are related to geological background and lithologies in Rawang. Pathway orders for both carcinogenic and non-carcinogenic risks are ingestion, dermal contact, and inhalation, involving adults and children. Non-carcinogenic health risks in adults were attributed to Cr(IV), Pb, and Cd, whereas Cu, Cd, Cr(IV), Pb, and Zn were found to have non-carcinogenic health risks for children. Cd, Cr(IV), Pb, and As may induce carcinogenic risks in adults and children, and the total lifetime cancer risk values exceeded incremental lifetime.
Endocrine disrupting compound (EDC) contamination in food is a global concern. Concerning potential environmental and human health exposed to EDCs via food intake, an experiment was conducted on the selected EDCs concentration in the mariculture fish, Trachinotus blochii (golden pomfret), Lutjanus campechanus (snapper), and Lates calcarifer (sea bass) at Pulau Kukup, Johor. Mariculture activity at Pulau Kukup involves active export of fishes to Singapore and Indonesia. The recovery of BPA (bisphenol A), 4OP (4-octylphenol), and 4NP (4-nonylphenol) were 61.54%-93.00%, 16.79%-17.13%, and 61.24%-71.49%, respectively. Relatively high concentration of BPA was recorded in T. blochii (0.322ng/g), followed by L. calcarifer (0.124ng/g) and L. campechanus (0.023ng/g). Furthermore, 4OP and 4NP were detected only in T. blochii at concentrations of 0.084ng/g and 0.078ng/g, respectively. The results of the present study provide insights on monitoring and managing mariculture activity in relation to environmental protection and food safety.
In this paper, numerous studies on groundwater in Malaysia were reviewed with the aim of evaluating past trends and the current status for discerning the sustainability of the water resources in the country. It was found that most of the previous groundwater studies (44 %) focused on the islands and mostly concentrated on qualitative assessment with more emphasis being placed on seawater intrusion studies. This was then followed by inland-based studies, with Selangor state leading the studies which reflected the current water challenges facing the state. From a methodological perspective, geophysics, graphical methods, and statistical analysis are the dominant techniques (38, 25, and 25 %) respectively. The geophysical methods especially the 2D resistivity method cut across many subjects such as seawater intrusion studies, quantitative assessment, and hydraulic parameters estimation. The statistical techniques used include multivariate statistical analysis techniques and ANOVA among others, most of which are quality related studies using major ions, in situ parameters, and heavy metals. Conversely, numerical techniques like MODFLOW were somewhat less admired which is likely due to their complexity in nature and high data demand. This work will facilitate researchers in identifying the specific areas which need improvement and focus, while, at the same time, provide policymakers and managers with an executive summary and knowledge of the current situation in groundwater studies and where more work needs to be done for sustainable development.
In this study, geophysics, geochemistry, and geostatistical techniques were integrated to assess seawater intrusion in Kapas Island due to its geological complexity and multiple contamination sources. Five resistivity profiles were measured using an electric resistivity technique. The results reveal very low resistivity <1 Ωm, suggesting either marine clay deposit or seawater intrusion or both along the majority of the resistivity images. As a result, geochemistry was further employed to verify the resistivity evidence. The Chadha and Stiff diagrams classify the island groundwater into Ca-HCO3, Ca-Na-HCO3, Na-HCO3, and Na-Cl water types, with Ca-HCO3 as the dominant. The Mg(2+)/Mg(2+)+Ca(2+), HCO3 (-)/anion, Cl(-)/HCO3 (-), Na(+)/Cl(-), and SO4 (2-)/Cl(-) ratios show that some sampling sites are affected by seawater intrusion; these sampling sites fall within the same areas that show low-resistivity values. The resulting ratios and resistivity values were then used in the geographical information system (GIS) environment to create the geostatistical map of individual indicators. These maps were then overlaid to create the final map showing seawater-affected areas. The final map successfully delineates the area that is actually undergoing seawater intrusion. The proposed technique is not area specific, and hence, it can work in any place with similar completed characteristics or under the influence of multiple contaminants so as to distinguish the area that is truly affected by any targeted pollutants from the rest. This information would provide managers and policy makers with the knowledge of the current situation and will serve as a guide and standard in water research for sustainable management plan.
The identification of spatio-temporal patterns of the urban growth phenomenon has become one of the most significant challenges in monitoring and assessing current and future trends of the urban growth issue. Therefore, spatio-temporal and quantitative techniques should be used hand in hand for a deeper understanding of various aspects of urban growth. The main purpose of this study is to monitor and assess the significant patterns of urban growth in Seremban using a spatio-temporal built-up area analysis. The concentric circles approach was used to measure the compactness and dispersion of built-up area by employing Shannon's Entropy method. The spatial directions approach was also utilised to measure the sustainability and speed of development, while the gradient approach was used to measure urban dynamics by employing landscape matrices. The overall results confirm that urban growth in Seremban is dispersed, unbalanced and unsustainable with a rapid speed of regional development. The main contribution of using existing methods with other methods is to provide several spatial and statistical dimensions that can help researchers, decision makers and local authorities understand the trend of growth and its patterns in order to take the appropriate decisions for future urban planning. For example, Shannon's Entropy findings indicate a high value of dispersion between the years 1990 and 2000 and from 2010 to 2016 with a growth rate of approximately 94 and 14%, respectively. Therefore, these results can help and support decision makers to implement alternative urban forms such as the compactness form to achieve an urban form that is more suitable and sustainable. The results of this study confirm the importance of using spatio-temporal built-up area and quantitative analysis to protect the sustainability of land use, as well as to improve the urban planning system via the effective monitoring and assessment of urban growth trends and patterns.
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 study presents the determination of the spatial variation and source identification of heavy metal pollution in surface water along the Straits of Malacca using several chemometric techniques. Clustering and discrimination of heavy metal compounds in surface water into two groups (northern and southern regions) are observed according to level of concentrations via the application of chemometric techniques. Principal component analysis (PCA) demonstrates that Cu and Cr dominate the source apportionment in northern region with a total variance of 57.62% and is identified with mining and shipping activities. These are the major contamination contributors in the Straits. Land-based pollution originating from vehicular emission with a total variance of 59.43% is attributed to the high level of Pb concentration in the southern region. The results revealed that one state representing each cluster (northern and southern regions) is significant as the main location for investigating heavy metal concentration in the Straits of Malacca which would save monitoring cost and time.
CAPSULE: The monitoring of spatial variation and source of heavy metals pollution at the northern and southern regions of the Straits of Malacca, Malaysia, using chemometric analysis.
The use of antifouling paints to the boats and ships is one among the threats facing coastal resources including coral reefs in recent decades. This study reports the current contamination status of diuron and its behaviour in the coastal waters of Malaysia. The maximum concentration of diuron was 285 ng/L detected at Johor port. All samples from Redang and Bidong coral reef islands were contaminated with diuron. Temporal variation showed relatively high concentrations but no significant difference (P>0.05) during November and January (North-East monsoon) in Klang ports (North, South and West), while higher levels of diuron were detected during April, 2012 (Inter monsoon) in Kemaman, and Johor port. Although no site has shown concentration above maximum permissible concentration (430 ng/L) as restricted by the Dutch Authorities, however, long term exposure studies for environmental relevance levels of diuron around coastal areas should be given a priority in the future.
The analysis of total organic carbon (TOC) by the American Public Health Association (APHA) closed-tube reflux colorimetric method requires potassium dichromate (K2Cr2O7), silver sulfate (AgSO4), and mercury (HgSO4) sulfate in addition to large volumes of both reagents and samples. The method relies on the release of oxygen from dichromate on heating which is consumed by carbon associated with organic compounds. The method risks environmental pollution by discharging large amounts of chromium (VI) and silver and mercury sulfates. The present method used potassium monochromate (K2CrO4) to generate the K2Cr2O7 on demand in the first phase. In addition, miniaturizing the procedure to semi microanalysis decreased the consumption of reagents and samples. In the second phase, mercury sulfate was eliminated as part of the digestion mixture through the introduction of sodium bismuthate (NaBiO3) for the removal of chlorides from the sample. The modified method, the potassium monochromate closed-tube colorimetry with sodium bismuthate chloride removal (KMCC-Bi), generates the potassium dichromate on demand and eliminates mercury sulfate. The semi microanalysis procedure leads to a 60% reduction in sample volume and ≈ 33.33 and 60% reduction in monochromate and silver sulfate consumption respectively. The LOD and LOQ were 10.17 and 33.90 mg L-1 for APHA, and 4.95 and 16.95 mg L-1 for KMCC-Bi. Recovery was between 83 to 98% APHA and 92 to 104% KMCC-Bi, while the RSD (%) ranged between 0.8 to 5.0% APHA and 0.00 to 0.62% KMCC-Bi. The method was applied for the UV-Vis spectrometry determination of COD in water and wastewater. Statistics was done by MINITAB 17 or MS Excel 2016. ᅟ Graphical abstract.
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.
An advanced image processing approach integrated with communication technologies and a camera for waste bin level detection has been presented. The proposed system is developed to address environmental concerns associated with waste bins and the variety of waste being disposed in them. A gray level aura matrix (GLAM) approach is proposed to extract the bin image texture. GLAM parameters, such as neighboring systems, are investigated to determine their optimal values. To evaluate the performance of the system, the extracted image is trained and tested using multi-layer perceptions (MLPs) and K-nearest neighbor (KNN) classifiers. The results have shown that the accuracy of bin level classification reach acceptable performance levels for class and grade classification with rates of 98.98% and 90.19% using the MLP classifier and 96.91% and 89.14% using the KNN classifier, respectively. The results demonstrated that the system performance is robust and can be applied to a variety of waste and waste bin level detection under various conditions.
In the backdrop of prompt advancement, information and communication technology (ICT) has become an inevitable part to plan and design of modern solid waste management (SWM) systems. This study presents a critical review of the existing ICTs and their usage in SWM systems to unfold the issues and challenges towards using integrated technologies based system. To plan, monitor, collect and manage solid waste, the ICTs are divided into four categories such as spatial technologies, identification technologies, data acquisition technologies and data communication technologies. The ICT based SWM systems classified in this paper are based on the first three technologies while the forth one is employed by almost every systems. This review may guide the reader about the basics of available ICTs and their application in SWM to facilitate the search for planning and design of a sustainable new system.
A new home-made diffusive bag-type passive sampler called Lanwatsu was developed for benzene, toluene, ethylbenzene and xylene monitoring in roadside air. The passive samplers were outdoor validated and deployed together with two commercial passive samplers, Ultra I SKC Inc. and Radiello, for daily roadside air monitoring in East Asian cities including HoChiMinh, Hanoi, Cantho, Danang, Vungtau, Hue (Vietnam), Kuala Lumpur (Malaysia), Kyoto, Osaka (Japan), Nanjing (China) and Singapore in 2011. High daily benzene concentrations of 87, 52, 32, 23, 13, 12 and 48 µg/m³ were observed in HoChiMinh, Hanoi, Cantho, Danang, Hue, Vung Tau (Vietnam), and Kuala Lumpur (Malaysia), respectively. Kyoto and Osaka (Japan) were clean with daily benzene concentrations below 2.3 μg/m³. The daily benzene concentrations in Nanjing (China) and Singapore were 5.6 and 6.9 μg/m³, respectively. The three passive samplers were equivalent. Passive sampling by the Lanwatsu passive sampler is acceptable for daily outdoor benzene monitoring.
Although coastal water marine algae have been popularly used by others as indicators of heavy metal pollution, data within the Bay of Bengal for the estuarine Cox's Bazar region and Saint Martin's Island has remained scarce. Using marine algae, the study herein forms an effort in biomonitoring of metal contamination in the aforementioned Bangladesh areas. A total of 10 seaweed species were collected, including edible varieties, analyzed for metal levels through the use of the technique of EDXRF. From greatest to least, measured mean metal concentrations in descending order have been found to be K > Fe > Zr > Br > Sr > Zn > Mn > Rb > Cu > As > Pb > Cr > Co. Potential toxic heavy metals such as Pb, As, and Cr appear at lower concentration values compared to that found for essential mineral elements. However, the presence of Pb in Sargassum oligocystum species has been observed to exceed the maximum international guidance level. Given that some of the algae species are cultivated for human consumption, the non-carcinogenic and carcinogenic indices were calculated, shown to be slightly lower than the maxima recommended by the international organizations. Overall, the present results are consistent with literature data suggesting that heavy metal macroalgae biomonitoring may be species-specific. To the best of our knowledge, this study represents the first comprehensive macroalgae biomonitoring study of metal contamination from the coastal waters of Cox's Bazar and beyond.
In this paper, an attempt has been made to assess, prognosis and observe dynamism of soil erosion by universal soil loss equation (USLE) method at Penang Island, Malaysia. Multi-source (map-, space- and ground-based) datasets were used to obtain both static and dynamic factors of USLE, and an integrated analysis was carried out in raster format of GIS. A landslide location map was generated on the basis of image elements interpretation from aerial photos, satellite data and field observations and was used to validate soil erosion intensity in the study area. Further, a statistical-based frequency ratio analysis was carried out in the study area for correlation purposes. The results of the statistical correlation showed a satisfactory agreement between the prepared USLE-based soil erosion map and landslide events/locations, and are directly proportional to each other. Prognosis analysis on soil erosion helps the user agencies/decision makers to design proper conservation planning program to reduce soil erosion. Temporal statistics on soil erosion in these dynamic and rapid developments in Penang Island indicate the co-existence and balance of ecosystem.
Satellite observations for regional air quality assessment rely on comprehensive spatial coverage, and daily monitoring with reliable, cloud-free data quality. We investigated spatiotemporal variation and data quality of two global satellite Aerosol Optical Depth (AOD) products derived from MODIS and VIIRS imagery. AOD is considered an essential atmospheric parameter strongly related to ground Particulate Matter (PM) in Southeast Asia (SEA). We analyze seasonal variation, urban/rural area influence, and biomass burning effects on atmospheric pollution. Validation indicated a strong relationship between AERONET ground AOD and both MODIS AOD (R2 = 0.81) and VIIRS AOD (R2 = 0.68). The monthly variation of satellite AOD and AERONET AOD reflects two seasonal trends of air quality separately for mainland countries including Myanmar, Laos, Cambodia, Thailand, Vietnam, and Taiwan, Hong Kong, and for maritime countries consisting of Indonesia, Philippines, Malaysia, Brunei, Singapore, and Timor Leste. The mainland SEA has a pattern of monthly AOD variation in which AODs peak in March/April, decreasing during wet season from May-September, and increasing to the second peak in October. However, in maritime SEA, AOD concentration peaks in October. The three countries with the highest annual satellite AODs are Singapore, Hong Kong, and Vietnam. High urban population proportions in Singapore (40.7%) and Hong Kong (21.6%) were associated with high AOD concentrations as expected. AOD values in SEA urban areas were a factor of 1.4 higher than in rural areas, with respective averages of 0.477 and 0.336. The AOD values varied proportionately to the frequency of biomass burning in which both active fires and AOD peak in March/April and September/October. Peak AOD in September/October in some countries could be related to pollutant transport of Indonesia forest fires. This study analyzed satellite aerosol product quality in relation to AERONET in SEA countries and highlighted framework of air quality assessment over a large, complicated region.
A priori assessments of a site's biophysical and socio-economic capacity for accommodating tourism are less common than tourism impact studies. A priori evaluations can provide a contextual understanding of ecological, economic and socio-cultural forces, which shape the prospects for sustainable tourism development at the host destination, and can avert adverse impacts of tourism. We conduct an a priori assessment of the biophysical environment of Pulau Banggi, in the Malaysian state of Sabah for sustainable tourism development. We characterise baseline conditions of the island's marine biodiversity, seasonality, and infrastructure. We then evaluate how existing biophysical conditions will influence options for sustainable tourism development. In particular, we suggest conditions, if there are any, which constitute a limit to future tourism development in terms of compatibility for recreation and resilience to visitor impacts. We find that the biggest constraint is the lack of adequate water and sanitation infrastructure. Blast fishing, although occurring less than once per hour, can potentially destroy the major attraction for tourists. We conclude that while Pulau Banggi possesses natural qualities that are attractive for ecotourism, financial and institutional support must be made available to provide facilities and services that will enable local participation in environmental protection and enhance prospects for future sustainable tourism.
This is the first report on bioaccumulation of polycyclic aromatic hydrocarbons (PAHs) and their derivatives (oxygen, nitrogen, sulfur, hydroxyl, carbonyl and methyl-containing PAHs) in three edible marine fishes, namely Lutjanus argentimaculatus, Lethrinus microdon and Scomberomorus guttatus, from Kharg Island, Persian Gulf, Iran. The concentrations (ng g-1dw) of Σ39PAHs resulted significantly higher in fish liver than muscle, with the PAH composition pattern dominated by low molecular weight compounds (naphthalene, alkyl-naphthalenes and phenanthrene). The highest mean concentrations of ∑9 oxygenated and ∑15 hydroxylated PAHs (ng g-1dw) were found ound in L. microdon and L. argentimaculatus, respectively, while the lowest values in S. guttatus. Additionally, the highest mean concentrations of Σ5 carbonylic PAHs (ng g-1dw) were found in L. argentimaculatus, followed by L. microdon. The PAHs levels and distribution in fish liver and muscle were dependent on both the Kow of PAHs congeners and fish lipid contents. Overall, the present findings provide important baseline data for further research on the ecotoxicity of PAHs in aquatic organisms, and consequent implications for human health.