Cadmium (Cd) and lead (Pb) are ubiquitous metals widely distributed in the environment, resulting in toxic health effects. This project aims to evaluate Pb and Cd as toxic elements in 15 different tobacco cigarette brands produced and/or sold in Selangor state, Peninsular Malaysia. The concentrations of Pb and Cd in all tobacco brands tested in this study were determined using the air-acetylene flame atomic absorption spectrophotometer (AAS). On average, the concentrations of Pb and Cd in different tobacco brand samples ranged from 3.05 and 0.80 μg/g dw, respectively. The results indicate that assessment mean values of Pb inhaled from smoking one packet of 20 cigarettes were in the range of 1.55-3.51 μg. Furthermore, the concentration of Cd inhaled per packet of cigarettes (20 sticks) is estimated to be 0.04-0.36 μg. However, there was a significant difference in the concentrations of Pb and Cd between the different brands of tobacco cigarettes, among cigarette prices (cheap versus expensive) of tobacco brands. In conclusion, cigarette smokers in Selangor, Malaysia, are heavily exposed to Pb and Cd, and such exposure could adversely affect their health in the long term. The impact of toxic heavy metals on smokers in this state would be an area for future research.
The ambient air of hospitals contains a wide range of biological and chemical pollutants. Exposure to these indoor pollutants can be hazardous to the health of hospital staff. This study aims to evaluate the factors affecting indoor air quality and their effect on the respiratory health of staff members in a busy Iranian hospital. We surveyed 226 hospital staff as a case group and 222 office staff as a control group. All the subjects were asked to fill in a standard respiratory questionnaire. Pulmonary function parameters were simultaneously measured via a spirometry test. Environmental measurements of bio-aerosols, particulate matter, and volatile organic compounds in the hospital and offices were conducted. T-tests, chi-square tests, and multivariable logistic regressions were used to analyze the data. The concentration of selected air pollutants measured in the hospital wards was more than those in the administrative wards. Parameters of pulmonary functions were not statistically significant (p > 0.05) between the two groups. However, respiratory symptoms such as coughs, phlegm, phlegmatic coughs, and wheezing were more prevalent among the hospital staff. Laboratory staff members were more at risk of respiratory symptoms compared to other occupational groups in the hospital. The prevalence of sputum among nurses was significant, and the odds ratio for the presence of phlegm among nurses was 4.61 times greater than office staff (p = 0.002). The accumulation of indoor pollutants in the hospital environment revealed the failure of hospital ventilation systems. Hence, the design and implementation of an improved ventilation system in the studied hospital is recommended.
The city of Dhaka has been ranked repeatedly as the most polluted, the most populous, and the most unbearable city in the world. More than 19.5 million inhabitants live in Dhaka, and the population growth rate of urban areas in Bangladesh is almost double that of rural areas. Rapid urbanization is one of the leading contributors to water pollution in Dhaka and could prevent the country from achieving sustainable development. Therefore, this study estimates respondents' willingness to pay (WTP) to improve water pollution management systems and identifies factors that influence WTP in Dhaka. This study employed the contingent valuation method (CVM) to estimate WTP of the respondents. Data were collected using a structured questionnaire with CVM questions, which was distributed to households in the study areas. The results revealed that 67% of the respondents are willing to pay for an improved water pollution management system, while 31.8% of households are unwilling to pay. The study also found that socio-economic factors (e.g., income and education) and perception significantly influence WTP. Therefore, this paper will provide directives for policymakers in developing an effective policy framework, as well as sensitize all stakeholders to the management of water pollution in Dhaka. The study suggests that social institutions, financial institutions, banks, non-government organizations (NGOs), insurance companies, and the government could provide effective outreach programs for water pollution management as part of their social responsibility.
This paper presents the adsorption capacity of a biosorbent derived from the inner part of durian (Durio zibethinus) rinds, which are a low-cost and abundant agro-waste material. The durian rind sorbent has been successfully utilized to remove lanthanum (La) and yttrium (Y) ions from their binary aqueous solution. The effects of several adsorption parameters including contact time, pH, concentrations of La and Y, and temperature on the removal of La and Y ions were investigated. The adsorption isotherm and kinetics of the metal ions were also evaluated in detail. Both La and Y ions were efficiently adsorbed by the biosorbent with optimum adsorption capacity as high as 71 mg La and 35 mg Y per gram biosorbent, respectively. The simultaneous adsorption of La and Y ions follows Langmuir isotherm model, due to the favorable chelation and strong chemical interactions between the functional groups on the surface of the biosorbent and the metal ions. The addition of oxygen content after adsorption offers an interpretation that the rare-earth metal ions are chelated and incorporated most probably in the form of metal oxides. With such high adsorption capacity of La and Y ions, the durian rind sorbent could potentially be used to treat contaminated wastewater containing La and Y metal ions, as well as for separating and extracting rare-earth metal ions from crude minerals.
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.
A widely distributed urban bird, the house crow (Corvus splendens), was used to assess bioavailable heavy metals in urban and rural environments across Pakistan. Bioaccumulation of arsenic (As), zinc (Zn), lead (Pb), cadmium (Cd), nickel (Ni), iron (Fe), manganese (Mn), chromium (Cr), and copper (Cu) was investigated in wing feathers of 96 crows collected from eight locations and categorized into four groups pertaining to their geographical and environmental similarities. Results revealed that the concentrations of Pb, Ni, Mn, Cu, and Cr were positively correlated and varied significantly among the four groups. Zn, Fe, Cr, and Cu regarded as industrial outputs, were observed in birds both in industrialized cities and in adjoining rural agricultural areas irrigated through the Indus Basin Irrigation System. Birds in both urban regions accrued Pb more than the metal toxicity thresholds for birds. The house crow was ranked in the middle on the metal accumulation levels in feathers between highly accumulating raptor and piscivore and less contaminated insectivore and granivore species in the studied areas,. This study suggests that the house crow is an efficient bioindicator and supports the feasibility of using feathers to discriminate the local pollution differences among terrestrial environments having different levels and kinds of anthropogenic activities.
The assessment of surface water quality is often laborious, expensive and tedious, as well as impractical, especially for the developing and middle-income countries in the ASEAN region. The application of the water quality index (WQI), which depends on several independent key parameters, has great potential and is a useful tool in this region. Therefore, this study aims to find out the spatial variability of various water quality parameters in geographical information system (GIS) environment and perform a comparative study among the ASEAN WQI systems. At present, there are four ASEAN countries which have implemented the WQI system to evaluate their surface water quality, which are (i) Own WQI system-Malaysia, Thailand and Vietnam-and (ii) Adopted WQI system: Indonesia. A spatial distribution of 12 water quality parameters in the Selangor river basin, Malaysia, was plotted and then applied into the different ASEAN WQI systems. The WQI values obtained from the different WQI systems have an appreciable difference, even for the same water samples due to the disparity in the parameter selection and the standards among them. WQI systems which consider all biophysicochemical parameters provide a consistent evaluation (Very Poor), but the system which either considers physicochemical or biochemical parameters gives a relatively lenient evaluation (Fair-Poor). The Selangor river basin is stressed and impacted by all physical, biological and chemical parameters caused by both the aridity of the climate and anthropogenic activities. Therefore, it is crucial to include all these aspects into the evaluation and corresponding actions should be taken.
We sampled the Klang estuary during the inter-monsoon and northeast monsoon period (July-Nov 2011, Oct-Nov 2012), which coincided with higher rainfall and elevated Klang River flow. The increased freshwater inflow into the estuary resulted in water column stratification that was observed during both sampling periods. Dissolved oxygen (DO) dropped below 63 μM, and hypoxia was observed. Elevated river flow also transported dissolved inorganic nutrients, chlorophyll a and bacteria to the estuary. However, bacterial production did not correlate with DO concentration in this study. As hypoxia was probably not due to in situ heterotrophic processes, deoxygenated waters were probably from upstream. We surmised this as DO correlated with salinity (R2 = 0.664, df = 86, p 6.7 h), hypoxia could occur at the Klang estuary. Here, we presented a model that related riverine flow rate to the post-heavy rainfall hypoxia that explicated the episodic hypoxia at Klang estuary. As Klang estuary supports aquaculture and cockle culture, our results could help protect the aquaculture and cockle culture industry here.
Stormwater runoff is a major concern in urban areas which is mostly the result of vast urbanization. To reduce urban stormwater runoff and improve water quality, low impact development (LID) is used in urban areas. Therefore, it is vital to find the optimal combination of LID controls to achieve maximum reduction in both stormwater runoff and pollutants with optimal cost. In this study, a simulation-optimization model was developed by linking the EPA Storm Water Management Model (SWMM) to the Multi-Objective Particle Swarm Optimization (MOPSO) using MATLAB. The coupled model could carry out multi-objective optimization (MOO) and find potential solutions to the optimization objectives using the SWMM simulation model outputs. The SWMM model was developed using data from the BUNUS catchment in Kuala Lumpur, Malaysia. The total suspended solids (TSS) and total nitrogen (TN) were selected as pollutants to be used in the simulation model. Vegetated swale and rain garden were selected as LID controls for the study area. The LID controls were assigned to the model using the catchment characteristics. The target objectives were to minimize peak stormwater runoff, TSS, and TN with the minimum number of LID controls applications. The LID combination scenarios were also tested in SWMM to identify the best LID types and combination to achieve maximum reduction in both peak runoff and pollutants. This study found that the peak runoff, TSS, and TN were reduced by 13%, 38%, and 24%, respectively. The optimal number of LID controls that could be used at the BUNUS catchment area was also found to be 25.
The massive destruction and loss caused by the 2004 Sumatra-Andaman tsunami were attributed to the lack of knowledge on tsunami and low regional detection and communication systems for early warning in that region. This study aimed to identify locations at risk of impending tsunami from Andaman Sea for the safety of community and proper development planning at the coastal areas by providing an updated and revised inundation maps. The last study on this area was conducted several years ago which open the possibility to new findings. Generated by tsunami simulation models, the maps illustrate the extent and level of inundation to which the coastal community and infrastructure would be subjected. As a result of coastal changes and availability of better topographic data, the existing inundation maps for the coastal areas of northwest Peninsular Malaysia at risk to impending tsunami from the Andaman Sea are revised. This paper documented the computational setup leading to the generation of the revised inundation maps. The tsunami simulation model TUNA was used to simulate the generation, propagation, and subsequent run-up and inundation of tsunamis triggered by earthquakes of moment magnitudes (Mw) 8.5, 9.0, and 9.25 along the Sunda Trench. From the simulations, it was found that at Mw 9.25, Balik Pulau, Pulau Pinang would be subjected to inundation of as far as 3.47 km with 5.40-m-deep inundation at the highest section.
Rivers in Malaysia are classified based on water quality index (WQI) that comprises of six parameters, namely, ammoniacal nitrogen (AN), biochemical oxygen demand (BOD), chemical oxygen demand (COD), dissolved oxygen (DO), pH, and suspended solids (SS). Due to its tropical climate, the impact of seasonal monsoons on river quality is significant, with the increased occurrence of extreme precipitation events; however, there has been little discussion on the application of artificial intelligence models for monsoonal river classification. In light of these, this study had applied artificial neural network (ANN) and support vector machine (SVM) models for monsoonal (dry and wet seasons) river classification using three of the water quality parameters to minimise the cost of river monitoring and associated errors in WQI computation. A structured trial-and-error approach was applied on input parameter selection and hyperparameter optimisation for both models. Accuracy, sensitivity, and precision were selected as the performance criteria. For dry season, BOD-DO-pH was selected as the optimum input combination by both ANN and SVM models, with testing accuracy of 88.7% and 82.1%, respectively. As for wet season, the optimum input combinations of ANN and SVM models were BOD-pH-SS and BOD-DO-pH with testing accuracy of 89.5% and 88.0%, respectively. As a result, both optimised ANN and SVM models have proven their prediction capacities for river classification, which may be deployed as effective and reliable tools in tropical regions. Notably, better learning and higher capacity of the ANN model for dataset characteristics extraction generated better predictability and generalisability than SVM model under imbalanced dataset.
The determinant factors for macroinvertebrate assemblages in river ecosystems are varied and are unique and specific to the type of macroinvertebrate family. This study aims to assess the determinant factors for macroinvertebrate assemblages in a recreational river. The study was conducted on the Ulu Bendul River, Negeri Sembilan, Malaysia. A total of ten sampling stations were selected. The research methodology included (1) water quality measurement, (2) habitat characterization, and (3) macroinvertebrate identification and distribution analysis. The statistical analysis used in this study was canonical correspondence analysis (CCA) to represent the relationship between the environmental factors and macroinvertebrate assemblages in the recreational river. This study found that most of the families of macroinvertebrates were very dependent on the temperature, DO, NH3-N, type of riverbed, etc. All of these factors are important for the survival of the particular type of macroinvertebrate, plus they are also important for selecting egg-laying areas and providing suitable conditions for the larvae to grow. This study advises that improved landscape design for watershed management be implemented in order to enhance water quality and physical habitats, and hence the protection and recovery of the macroinvertebrate biodiversity.
Fluoride enrichment of groundwater has been adjudged to be a global environmental challenge in the past decade as most humans depend on groundwater for their domestic needs. This study was conducted to investigate the ionic and fluoride concentrations in borehole water and its associated health risk potentials to residents of Makurdi town and its environs, Benue state, Nigeria. Multivariate statistical techniques were for the first time used to explain the mechanisms of fluoride occurrence in groundwater in the study area. An aggregate of sixty-three (63) groundwater samples were retrieved from boreholes in twenty-one (21) diverse points within the study area and assessed for its physico-chemical composition with emphasis on fluoride content and health risk potentials following standard field and laboratory procedures. It was observed that fluoride content in the sampled water exceeded the stipulated safe limit of 1.5 mg/L in about 33.33% of the total samples and ranged from 0.34 to 2.06 mg/L with an average of 1.26 ± 0.41 mg/L. Moderate affirmative relationships were observed to exist between F- and TDS, F- and EC, F- and Cl-, and F- and NO3- in the water samples indicative of a common source pollution. Principal component analysis (PCA) revealed that high fluoride content in the water samples was associated with the dissolutions from quartzite and shale into the underlying deep aquifers as well as from contributions from anthropogenic activities including fertilizer and pesticide uses. Fluoride risk assessment indicated that the hazard quotient (HQ) for ingestion of fluoride laden water exceeded the threshold value in 66.7, 71.4, 52.4, and 9.5% of the samples for infants, children, teenagers, and adults respectively. It was found that multivariate statistical procedures such as PCA and correlation analysis (CA) are capable of establishing the relationship among groundwater pollutants, while hierarchical cluster analysis (HCA) was found suitable for explaining the likely sources/processes of pollutant enrichment in the groundwater. It is recommended that the findings of this study would serve as a basis for policy makers and regulatory bodies towards ameliorating the menace of groundwater contamination within the study area.
We studied the water quality of the riparian firefly sanctuary of Sungai Rembau, or Rembau River, in Negeri Sembilan, Malaysia, from January 2018 to November 2018 to determine the possible influence of the physico-chemical characteristics of the water on the firefly populations living within the sanctuary. We set up a total of five water quality sampling stations and 10 firefly sampling stations along the river. Dissolved oxygen (DO), temperature, pH and electrical conductivity (EC) were measured in situ, while chemical oxygen demand (COD), total suspended solids (TSS), biochemical oxygen demand (BOD) and ammonia-nitrogen (NH3-N) were analysed in the laboratory. Firefly samples were collected using a sweep net at both day and night for 1 min. Sungai Rembau was categorized as Class II on the Malaysian water quality index (WQI), which indicates slight pollution. Except for EC and DO, the water quality parameter values were not significantly different (p > 0.05) between the sampling stations. A total of 529 firefly individuals consisting of Pteroptyx tener (n = 525, 99.24%), P. malaccae (n = 3, 0.57%) and P. asymmetria (n = 1, 0.19%) were collected. There was significant correlation between firefly abundance and BOD (r = - 0.198, p
Synthetic dyes used in the textile and paper industries pose a major threat to the environment. In the present research work, the adsorption efficiency of the natural adsorbent Strychnos potatorum Linn (Fam: Loganiaceae) seeds were examined against the reactive orange-M2R dye from aqueous solution by varying the process conditions such as contact time, pH, adsorbent dosage, and initial dye concentration on adsorption of anionic azo dye. This study compares different types of artificial neural networks which are feedforward artificial neural network (FANN) and nonlinear autoregressive exogenous (NARX) model to predict the efficiency of a cost-effective natural adsorbent Strychnos potatorum Linn seeds on removing reactive orange-M2R dye from aqueous solution. Twelve training algorithms of neural network were compared, and the prediction on the adsorption performance of anionic azo dye from aqueous solution using Strychnos potatonum Linn seeds was evaluated by using the root mean squared error (RMSE), mean absolute error (MAE), coefficient of determination (R2), and accuracy. For FANN model, Levenberg-Marquardt (LM) backpropagation with 19 hidden neurons was selected as the optimum FANN model, with R2 of 0.994 and accuracy of 87.20%, 98.21%, and 66.60% for training, testing, and validation datasets, respectively. For NARX model, LM with 8 hidden neurons was selected as the most suitable training algorithm, with R2 value of more than 0.99 and accuracy of 88.00%, 90.91%, and 75.00% for training, testing, and validation datasets, respectively. NARX model accurately predicted the adsorption of anionic azo dye from aqueous solution using Strychnos potatonum Linn seeds with better performance than FANN model.
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.
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.
Quantitative indices are classically employed to evaluate the contamination status of metals with reference to the baseline concentrations. The baselines vary considerably across different geographical zones. It is imperative to determine the local geochemical baseline to evaluate the contamination status. No study has been done to establish the background concentrations in tropical rivers of this region. This paper reports the background concentrations of metals in water and sediment of the Baleh River, Sarawak, derived based on the statistical methods where the areas possibly disturbed are distinguished from the undisturbed area. The baseline levels of six elements in water determined were Al (0.34 mg/L), Fe (0.51 mg/L), Mn (0.12 mg/L), Cu (0.01 mg/L), Pb (0.03 mg/L), and Zn (0.05 mg/L). Arsenic and selenium were below the detection limit. For sediment, the background values were established according to statistical methods including (mean + 2σ), iterative 2σ, cumulative distribution frequency, interquartile, and calculation distribution function. The background values derived using the iterative 2σ algorithm and calculated distribution function were relatively lower. The baseline levels calculated were within the range reported in the literatures mainly from tropical and sub-tropical regions. The upper limits proposed for nine elements in sediment were Al (100,879 mg/kg), Cr (75.45 mg/kg), Cu (34.59 mg/kg), Fe (37,823 mg/kg), Mn (793 mg/kg), Ni (22.88 mg/kg), Pb (27.26 mg/kg), Zn (70.64 mg/kg), and Hg (0.33 mg/kg). Quantitative indices calculated suggest low risk of contamination at the Baleh River.