An environmental problem which is of concern across the globe nowadays is air pollution. The extent of air pollution is often studied based on data on the observed level of air pollution. Although the analysis of air pollution data that is available in the literature is numerous, studies on the dynamics of air pollution with the allowance for spatial interaction effects through the use of the Markov chain model are very limited. Accordingly, this study aims to explore the potential impact of spatial dependence over time and space on the distribution of air pollution based on the spatial Markov chain (SMC) model using the longitudinal air pollution index (API) data. This SMC model is pertinent to be applied since the daily data of API from 2012 to 2014 that have been gathered from 37 different air quality stations in Peninsular Malaysia is found to exhibit the property of spatial autocorrelation. Based on the spatial transition probability matrices found from the SMC model, specific characteristics of air pollution are studied in the regional context. These characteristics are the long-run proportion and the mean first passage time for each state of air pollution. It is found that the probability for a particular station's state to remain good is 0.814 if its neighbors are in a good state of air pollution and 0.7082 if its neighbors are in a moderate state. For a particular station having neighbors in a good state of air pollution, the proportion of time for it to continue being in a good state is 0.6. This proportion reduces to 0.4, 0.01, and 0 for the cell of moderate, unhealthy, and very unhealthy states, respectively. In addition, there exists a significant spatial dependence of API, indicating that air pollution for a particular station is dependent on the states of the neighboring stations.
Thermal structure and water quality in a large and shallow lake in Malaysia were studied between January 2012 and June 2013 in order to understand variations in relation to water level fluctuations and in-stream mining activities. Environmental variables, namely temperature, turbidity, dissolved oxygen, pH, electrical conductivity, chlorophyll-A and transparency, were measured using a multi-parameter probe and a Secchi disk. Measurements of environmental variables were performed at 0.1 m intervals from the surface to the bottom of the lake during the dry and wet seasons. High water level and strong solar radiation increased temperature stratification. River discharges during the wet season, and unsustainable sand mining activities led to an increased turbidity exceeding 100 NTU, and reduced transparency, which changed the temperature variation and subsequently altered the water quality pattern.
A comprehensive monitoring survey for polycyclic aromatic hydrocarbons (PAHs) and phenolic endocrine disrupting chemicals (EDCs) utilizing mussels as sentinel organisms was conducted in South and Southeast Asia as a part of the Asian Mussel Watch project. Green mussel (Perna viridis) samples collected from a total of 48 locations in India, Indonesia, Singapore, Malaysia, Thailand, Cambodia, Vietnam, and the Philippines during 1994-1999 were analyzed for PAHs, EDCs including nonylphenol (NP), octylphenol (OP) and bisphenol A (BPA), and linear alkylbenzenes (LABs) as molecular markers for sewage. Concentrations of NP ranged from 18 to 643 ng/g-dry tissue. The highest levels of NP in Malaysia, Singapore, the Philippines, and Indonesia were comparable to those observed in Tokyo Bay. Elevated concentrations of EDCs were not observed in Vietnam and Cambodia, probably due to the lower extent of industrialization in these regions. No consistent relationship between concentrations of phenolic EDCs and LABs were found, suggesting that sewage is not a major source of EDCs. Concentrations of PAHs ranged from 11 to 1,133 ng/g-dry, which were categorized as "low to moderate" levels of pollution. The ratio of methylphenanthrenes to phenanthrene (MP/P ratio) was >1.0 in 20 out of 25 locations, indicating extensive input of petrogenic PAHs. This study provides a bench-mark for data on the distribution of anthropogenic contaminants in this region, which is essential in evaluating temporal and spatial variation and effect of future regulatory measures.
One of the molecular chemical markers used to identify anthropogenic inputs is linear alkylbenzenes (LABs) that cause serious impacts in the bays and coastal ecosystems. The surface sediments samples collected from the East Malaysia, including Brunei bay to estimate the LABs concentration and distribution as molecular markers of anthropogenic indicators. Gas chromatography-mass spectrometry (GC-MS) was used after purification, fractionation the hydrocarbons in the sediment samples to identify the sources of LABs. The analysis of variance (ANOVA) and Pearson correlation coefficient were applied to analyze the difference between sampling stations' significance at p
This study evaluated the adsorptive properties of deep eutectic solvent (DES)-treated palm oil mill sludge adsorbents for methylene blue removal. The adsorbents were prepared at a ratio of 1:2 at 80°C to form P1:D2@80°C, at 25°C to form P1:D2@25°C and without DES to form dry sludge (DS). The adsorbent samples were characterized for surface functional groups, textural properties and surface morphology. The values of specific area were 534, 236 and 184 m2/g, respectively. Batch adsorption of methylene blue at varying concentration, adsorbent dosage, pH, contact time and temperature was performed. The maximum adsorption capacities by Sips model were recorded as 72.07, 56.18 and 48.33 mg/g for P1:D2@80°C, P1:D2@25°C and DS, respectively. P1:D2@80°C displayed the highest rate constant (Ks = 0.0037 g/mg.min). The adsorption data were well fitted into Sips isotherm and pseudo-second-order kinetic models, suggesting that the adsorption is a physical process onto heterogeneous adsorbent surface via pore filling and electrostatic attraction. The adsorption was spontaneous, feasible and exothermic with decreased disorderliness in the solid-bulk solution interface. The DES-treated palm oil mill sludge adsorbent is a promising alternative adsorbent for dye removal from wastewater.
This study presents the kinetics and thermodynamics of biomass pyrolysis. The kinetics of the pyrolysis process was estimated using ten kinetic models from three different mechanisms, namely chemical reaction, diffusion, and nucleation and growth. Results showed that each pyrolysis subdivision was described by a different reaction model, signifying the complex nature of the pyrolysis process. The average values of activation energy determined from the kinetic models for empty fruit bunch, coconut shell, bamboo, and cardboard are 10.2-64.6 kJ/mol, 18.7-186.2 kJ/mol, 8.0-70.8 kJ/mol, and 13.1-277.3 kJ/mol, respectively. The biomass pyrolysis is endothermic and non-spontaneous and would require external energy to initiate the degradation process. The findings are helpful in characterizing the thermal degradation of biomass in exploring its potential as a source of alternative solid fuel.
The spatial distributions of Na, Mg, K, Ca, Cr, Fe, Ni, Cu, Zn, As, Se and Pb in Hemibagrus sp. from Selangor River and a reference site were determined with inductively coupled plasma-mass spectrometer, in comparison to the levels in their surrounding water body and sediments. The results demonstrated significant differences in elemental accumulation pattern in different fish tissues originated from both sites. The variations observed were mainly subjected to their metabolic activities, and also the influence of the surrounding medium. In general, the liver tends to accumulate higher concentration of metals followed by the gills, and muscle tissues. The data also indicate associations between the concentrations of metal contaminants measured in the fish and the levels observed at the sites. The concentrations of hazardous metals As, Se and Pb in all the studied tissues reflect the influence of anthropogenic inputs. This suggests the potential utility of widely available Hemibagrus sp. as a valuable bioindicator of metal pollution in environmental monitoring and assessment.
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.
This case study uses several univariate and multivariate statistical techniques to evaluate and interpret a water quality data set obtained from the Klang River basin located within the state of Selangor and the Federal Territory of Kuala Lumpur, Malaysia. The river drains an area of 1,288 km(2), from the steep mountain rainforests of the main Central Range along Peninsular Malaysia to the river mouth in Port Klang, into the Straits of Malacca. Water quality was monitored at 20 stations, nine of which are situated along the main river and 11 along six tributaries. Data was collected from 1997 to 2007 for seven parameters used to evaluate the status of the water quality, namely dissolved oxygen, biochemical oxygen demand, chemical oxygen demand, suspended solids, ammoniacal nitrogen, pH, and temperature. The data were first investigated using descriptive statistical tools, followed by two practical multivariate analyses that reduced the data dimensions for better interpretation. The analyses employed were factor analysis and principal component analysis, which explain 60 and 81.6% of the total variation in the data, respectively. We found that the resulting latent variables from the factor analysis are interpretable and beneficial for describing the water quality in the Klang River. This study presents the usefulness of several statistical methods in evaluating and interpreting water quality data for the purpose of monitoring the effectiveness of water resource management. The results should provide more straightforward data interpretation as well as valuable insight for managers to conceive optimum action plans for controlling pollution in river water.
Sustainable agriculture is important for preserving environmental health and simultaneously gaining economic profits while maintaining social and economic equity. One way to evaluate sustainable agriculture is by studying agricultural eco-efficiency (AEE). Hence, this study constructed a data-driven method to evaluate and optimize AEE with the aim of providing a basis for improving the sustainable development of regional agriculture. Sixteen cities in Anhui Province, China, were considered in the study, and the variables used were agricultural resource inputs, environmental pollution, and agricultural economic development. Agricultural non-point source pollution (NPSP) emissions were considered the undesired output to build an AEE evaluation index system. Furthermore, a data envelopment analysis (DEA) model was established to analyse AEE from the static and dynamic perspectives. The spatial development and the temporal and spatial characteristics of AEE were also analysed. In addition, we applied a random effect (RE) panel Tobit model to quantitatively analyse the influencing factors of AEE from the input perspective and then proposed reasonable suggestions for improving the sustainable development of regional agriculture. Our findings show that the overall agricultural development in the 16 cities in Anhui Province has been continuously improving, even though there is an agglomeration of spatial development in some regions. In conclusion, this study provides suggestions and references for policy makers and agricultural practitioners regarding how to improve regional AEE and promote the sustainable development of the regional agricultural economy.
Landfill leachate is one of the sources of surface water pollution in Selangor State (SS), Malaysia. Leachate volume prediction is essential for sustainable waste management and leachate treatment processes. The accurate estimation of leachate generation rates is often considered a challenge, especially in developing countries, due to the lack of reliable data and high measurement costs. Leachate generation is related to several variable factors, including meteorological data, waste generation rates, and landfill design conditions. Large variations in these factors lead to complicated leachate modeling processes. The aims of this study are to determine the key elements contributing to leachate production and then develop an adaptive neural fuzzy inference system (ANFIS) model to predict leachate generation rates. Accuracy of the final model performance was tested and evaluated using the root mean square error (RMSE), the mean absolute error (MAE), and the correlation coefficient (R). The study results defined dumped waste quantity, rainfall level, and emanated gases as the most significant contributing factors in leachate generation. The best model structure consisted of two triangular fuzzy membership functions and a hybrid training algorithm with eight fuzzy rules. The proposed ANFIS model showed a good performance with an overall correlation coefficient of 0.952.
This is the first attempt in the world to depict the vertical distribution of radionuclides in the soil samples along several heights (900 feet, 1550 feet, and 1650 feet) of Marayon Tong hill in the Chittagong Hill Tracts, Bandarban by HPGe gamma-ray spectrometry. The average activity concentrations of 232Th, 226Ra, and 40K were found to be 37.15 ± 3.76 Bqkg-1, 19.69 ± 2.15 Bqkg-1, and 347.82 ± 24.50 Bqkg-1, respectively, where in most cases, 232Th exceeded the world average value of 30 Bqkg-1. According to soil characterization, soils ranged from slightly acidic to moderately acidic, with low soluble salts. The radium equivalent activity, outdoor and indoor absorbed dose rate, external and internal hazard indices, external and internal effective dose rates, gamma level index, and excess lifetime cancer risk were evaluated and found to be below the recommended or world average values; but a measurable activity of 137Cs was found at soils collected from ground level and at an altitude of 1550 feet, which possibly arises from the nuclear fallout. The evaluation of cumulative radiation doses to the inhabitants via periodic measurement is recommended due to the elevated levels of 232Th.This pioneering work in mapping the vertical distribution of naturally occurring radioactive materials (NORMs) can be an essential factual baseline data for the scientific community that may be used to evaluate the variation in NORMs in the future, especially after the commissioning of the Rooppur Nuclear Power Plant in Bangladesh in 2024.
This study marks the first-ever assessment of radiological hazards linked to the sands and rocks of Patuartek Sea Beach, situated along one of the world's longest sea beaches in Cox' Bazar of Bangladesh. Through the utilization of an HPGe detector, a comprehensive analysis of the activity concentrations of 226Ra, 232Th, and 40 K was conducted, and their activity ranged from 7 to 23 Bq/kg, 9-58 Bq/kg, and 172-340 Bq/kg, respectively, in soils, and 19-24 Bq/kg, 27-39 Bq/kg, and 340-410 Bq/kg, respectively, in rocks. Some sand samples exhibited elevated levels of 232Th, while the rock samples displayed higher levels of 40 K compared to the global average. The radiological hazard parameters were assessed, and no values surpassed the recommended limits set by several international organizations. Hence, the sands and rocks of Patuartek sea beach pose no significant radiological risk to the residents or tourists. The findings of this study provide crucial insights for the development of a radiological baseline map in the country, which is important due to the commissioning of the country's first nuclear power plant Rooppur Nuclear Power Plant. The data may also stimulate interest in the rare-earth minerals present in the area, which is important for the electronics industry, thorium-based nuclear fuel cycles.
Bangladesh is a rapidly developing country, which is vulnerable to various types of pollution due to the large-scale industrial and associated human activities that might potentially affect the locally harvested foodstuffs. Therefore, the transfer factor is an essential tool to assess the safety of foodstuffs due to the presence of natural radioactivity in environmental matrix and/or strata. This is a first study of its kind conducted in a well-known region for mango farming in Bangladesh, measuring the uptake of naturally occurring radioactive materials (NORMs) by grass and mango from soil to assess the ingestion doses to humans. The HPGe gamma-ray detector was used to determine the concentrations of NORMs in samples of soil (20), grass (10), and mango (10), which were then used to calculate the transfer factors of soil to grass and soil to mango. Average activity concentrations of 226Ra, 232Th, and 40K in associated soil samples (47.27 ± 4.10, 64.49 ± 4.32, 421.60 ± 28.85) of mango and 226Ra and 232Th in associated soil samples (45.07 ± 3.93, 52.17 ± 3.95) of grass were found to exceed the world average values. The average transfer factors (TFs) for mango were obtained in the order of 40K(0.80) > 226Ra (0.61) > 232Th (0.31), and for grass, it shows the order of 40K (0.78) > 232Th (0.64) > 226Ra (0.56). However, a few values (3 mango samples and 3 grass samples) of the estimated TFs exceeded the recommended limits. Moreover, Bangladesh lacks the transfer factors for most of the food crops; therefore, calculation of TFs in the major agricultural products is required all over Bangladesh, especially the foodstuffs produced near the Rooppur Nuclear Power Plant, which is scheduled to be commissioned in 2023.
Miners, factory workers, traders, end-users, and foodstuff consumers all run the risk of encountering health hazards derived from the presence of elevated levels of radiation in fertilizers, as these groups often come into direct or indirect contact with fertilizers as well as raw materials throughout various linked processes such as mineral extractions, fertilizer production, agricultural practices. A total of 30 samples of various kinds of fertilizer produced in different factories in Dhaka megacity were analyzed to quantify the concentrations of primordial radionuclides using HPGe detector. Among the analyzed samples, average (range) concentration of 40K was found to be 9920 ± 1091 (8700 ± 957-11,500 ± 1265), 9100 ± 1001 (8600 ± 946-9600 ± 1056), 2565 ± 282 (2540 ± 279-2590 ± 285), and 3560 ± 392 (2620 ± 288-4500 ± 495) Bq/kg in the samples of Muriate of Potash Fertilizer, Sulphate of Potash Fertilizer, Humic Acid Fertilizer, and NPKS Fertilizer, respectively. Elevated concentration of 226Ra was found in Triple Super Phosphate Fertilizer with a mean (range) of 335 ± 37 (290 ± 32-380 ± 42) Bq/kg. The higher activity of 40K can be linked to the greater levels of elemental potassium in phosphate fertilizer. Elevated concentrations of radionuclides may also result from variations in chemical processes as well as the local geology of the mining areas where the raw materials were extracted for fertilizer production. Numerous fertilizer brands surpass prescribed limits for various hazardous parameters, presenting significant health risks to factory workers, farmers, and consumers of agricultural products. This study provides baseline information on the radioactivity of fertilizers, which could be used to develop mitigation methods, establish national fertilizer usage limits, justify regulatory frameworks, and raise public awareness of fertilizer overuse. The findings of the study could potentially help to explore the impact of fertilizer on the food chain.
Centella asiatica is a commonly used medicinal plant in Malaysia. As heavy metal accumulation in medicinal plants which are highly consumed by human is a serious issue, thus the assessment of heavy metals in C. asiatica is important for the safety of consumers. In this study, the heavy metal accumulation in C. asiatica and the potential health risks were investigated. Samples of C. asiatica and surface soils were collected from nine different sites around Peninsular Malaysia. The concentration of six heavy metals namely Cd, Cu, Ni, Fe, Pb and Zn were determined by air-acetylene flame atomic absorption spectrophotometer (AAS). The degree of anthropogenic influence was assessed by calculating the enrichment factor (EF) and index of geoaccumulation (Igeo). The heavy metal uptake into the plant was estimated through the calculation of translocation factor (TF), bioconcentration factor (BCF) and correlation study. Estimated daily intakes (EDI) and target hazard quotients (THQ) were used to determine the potential health risk of consuming C. asiatica. The results showed that the overall surface soil was polluted by Cd, Cu and Pb, while the uptake of Zn and Ni by the plants was high. The value of EDI and THQ showed that the potential of Pb toxicity in C. asiatica was high as well. As heavy metal accumulation was confirmed in C. asiatica, daily consumption of the plant derived from polluted sites in Malaysia was not recommended.
It is accepted that occupants who are more satisfied with their workplace's building internal environment are more productive. The main objective of the study was to measure the occupants' level of satisfaction and the perceived importance of the design or refurbishment on office conditions. The study also attempted to determine the factors affecting the occupants' satisfaction with their building or office conditions. Post-occupancy evaluations were conducted using a structured questionnaire developed by the Built Environment Research Group at the University of Manchester, UK. Our questionnaires incorporate 22 factors relating to the internal environment and rate these in terms of "user satisfaction" and "degree of importance." The questions were modified to reflect the specific setting of the study and take into consideration the local conditions and climate in Malaysia. The overall mean satisfaction of the occupants toward their office environment was 5.35. The results were measured by a single item of overall liking of office conditions in general. Occupants were more satisfied with their state of health in the workplace, but they were extremely dissatisfied with the distance away from a window. The factor analysis divided the variables into three groups, namely intrusion, air quality, and office appearance. Structural equation modeling (SEM) was then used to determine which factor had the most significant influence on occupants' satisfaction: appearance. The findings from the study suggest that continuous improvement in aspects of the building's appearance needs to be supported with effective and comprehensive maintenance to sustain the occupants' satisfaction.
The use of organochlorine pesticides has caused concern due to their effects on human health and the Malaysian aquatic ecosystem, particularly so in view of their persistent and bioaccumulative properties. Since the extent of organochlorine pesticide pollution in Malaysian waterways is unknown except for isolated instances, a systematic survey has now been carried out. Water samples from various rivers were extracted, cleaned up with Florisil and analysed for the individual organochlorine pesticides by gas chromatography (GC) with an electron capture detector (ECD). DDE, DDT and heptachlor were present in all the river water samples of the west coast of Peninsular Malaysia. Other organochlorine pesticides were also identified from the water samples. However, the levels of all these are still below criteria values for Malaysian aquatic life, indicating that organochlorine pesticide pollution is less of a problem than other organic or inorganic pollutants.
Information on waste generation, socioeconomic characteristics, and willingness of the households to separate waste was obtained from interviews with 402 respondents in Dhaka city. Ordinary least square regression was used to determine the dominant factors that might influence the waste generation of the households. The results showed that the waste generation of the households in Dhaka city was significantly affected by household size, income, concern about the environment, and willingness to separate the waste. These factors are necessary to effectively improve waste management, growth and performance, as well as to reduce the environmental degradation of the household waste.