Heavy metal pollution has become a global concern due to accumulation in tissue and transferable effects to humans via the food chain. This study focused on monitoring the accumulation of cadmium (Cd) and lead (Pb) in surface soil and body content: bone, heart, brain, liver, lung, muscle, kidney, feathers, feces, and gizzard contents of house crow Corvus splendens in the Klang region, Malaysia. The results revealed the occurrence of Pb and Cd in all biological samples from house crows, food contents, and surface soil samples. Heart and kidney accrued high amounts of Cd, while high amounts of Pb were found to accumulate in bones and feathers. Major discrepancies were also discovered in the concentrations of metals between juvenile and adults, as well as female and male bird samples. Concentrations of Pb and Cd in house crow internal tissues correlated significantly with that of bird feathers, but none could be established with that of surface soil. In addition, a significant correlation was observed between Pb concentration in the internal tissues to that of the feces, but the same was not the case when compared with the surface soil concentration. Metal accrual in the house crows feathers and feces may be through a long-term transmission via the food chain, which are eliminated from feathers via molting. This may suggest the utility of molted breast feathers of house crow in the bio-monitoring of Cd and Pb contamination, whereas feces of house crow appear only to be suitable for the bio-monitoring of Pb contamination.
Frequent haze occurrences in Malaysia have made the management of PM10 (particulate matter with aerodynamic less than 10 μm) pollution a critical task. This requires knowledge on factors associating with PM10 variation and good forecast of PM10 concentrations. Hence, this paper demonstrates the prediction of 1-day-ahead daily average PM10 concentrations based on predictor variables including meteorological parameters and gaseous pollutants. Three different models were built. They were multiple linear regression (MLR) model with lagged predictor variables (MLR1), MLR model with lagged predictor variables and PM10 concentrations (MLR2) and regression with time series error (RTSE) model. The findings revealed that humidity, temperature, wind speed, wind direction, carbon monoxide and ozone were the main factors explaining the PM10 variation in Peninsular Malaysia. Comparison among the three models showed that MLR2 model was on a same level with RTSE model in terms of forecasting accuracy, while MLR1 model was the worst.
The marine aquaculture industry has caused a suite of adverse environmental consequences, including offshore eutrophication. However, little is known about the extent to which aquaculture effluents affect nearby wetland ecosystems. We carried out a field experiment in a mangrove stand located between two effluent-receiving creeks to estimate the extent to which marine aquaculture affects the soil nutrient distribution and plant nutrient status of adjacent mangroves. Carbon (C), nitrogen (N), and phosphorus (P) contents and C isotopic signatures were determined seasonally in creeks, pore water, surface soils, and in the leaves of the dominant mangrove species Kandelia obovata. The creeks exhibited nutrient enrichment (2.44 mg N L-1 and 0.09 mg P L-1 on average). The soils had N (from 1.40 to 2.70 g kg-1) and P (from 0.58 to 2.76 g kg-1) much greater than those of pristine mangrove forests. Combined analyses of the N:P ratio, nutrient resorption efficiency, and proficiency indicated that soil P met plant demands, but plants in most plots showed N limitation, suggesting that soil nutrient accumulation did not fundamentally impact the plant nutrient status. Collectively, this case study shows that marine aquaculture farms can affect adjacent mangrove stands even though their effluents are not directly discharged into the mangrove stands, but mangrove forests may have substantial buffering capabilities for long-term nutrient loading.
The agriculture sector responsible for global food and nutrition security has an urgent need to examine climatic trends so that adaptations can be exercised in advance. Freely available dataset from satellite sources can greatly ease rainfall analysis, especially for smallholder farmers who typically operate under limited resources. Tests to determine their accuracy, however, are so far not deployed in tropical Southeast Asia. We compared in situ observations with dataset from the Global Satellite Mapping of Precipitation (GSMaP) and the Prediction of Worldwide Energy Resources (POWER) in two sites located 180 km apart in the tropical Malay Peninsula for 30 days. We found that in situ precipitation values were markedly overestimated by GSMaP (34.9-67.5%) and POWER (180.5-289.2%), and the possible reasons are discussed. Nonetheless, we conclude that GSMaP remains the best hope for smallholder farmers and its dataset can still be used under the precaution of error margins determined by the practical method described herein.
Mining activities in the Chini Lake catchment area have been extensive for several years, contributing to acid mine drainage (AMD) events with high concentrations of iron (Fe) and other heavy metals impacting the surface water. However, during the restriction period due to the COVID-19 outbreak, anthropogenic activities have been suspended, which clearly shows a good opportunity for a better environment. Therefore, we aimed to analyze the variation of AMD-associated water pollution in three main zones of the Chini Lake catchment area using Sentinel-2 data for the periods pre-movement control order (MCO), during MCO, and post-MCO from 2019 to 2021. These three zones were chosen due to their proximity to mining areas: zone 1 in the northeastern part, zone 2 in the southeastern part, and zone 3 in the southern part of the Chini Lake area. The acid mine water index (AMWI) was a specific index used to estimate acid mine water. The AMWI values from Sentinel-2 images exhibited that the mean AMWI values in all zones during the MCO period decreased by 14% compared with the pre-MCO period. The spatiotemporal analysis found that the highest polluted zones were recorded in zone 1, followed by zone 3 and zone 2. As compared with during the MCO period, the maximum percentage of increment during post-MCO in all zones was up to 25%. The loosened restriction policy has resulted in more AMD flowing into surface water and increased pollution in Chini Lake. As a whole, our outputs revealed that Sentinel-2 data had a major potential for assessing the AMD-associated pollution of water.
Sediment is the ultimate reservoir of effluent from landmasses. This includes octylphenol (OP) and nonylphenol (NP), two chemical compounds which are known with the ability to disrupt the normal functions of hormones in the organism. To our knowledge, no study of these compounds in the marine sediment of Malaysia has been published to date. Hence, this study presents the level of OP and NP in the sediment of the South China Sea and Malacca Strait, Malaysia. The extraction of compounds was done using the liquid-liquid extraction method and followed by clean-up using solid-phase extraction cartridges. The range of OP in Malacca Strait (1.00-27.16 ng/g dw) was greater than in the South China Sea (5.12-14.16 ng/g dw) whereas a similar range of NP was found in the South China Sea (1.32-23.76 ng/g dw) and Malacca Strait (0.79-27.59 ng/g dw). The concentration of both compounds was consistently high near Redang Island (E2A) and Penang (W32 and W43) suggesting continuous input of these chemicals from this nearby land. Risk quotient (RQ) values of OP showed the potential risk to benthic communities in 4/7 and 21/47 sampling points of the respective South China Sea and Malacca Strait. Both water bodies are located far from the wastewater effluent and yet able to retain these chemicals in their sediment. This suggests that the wastewater treatment system as well as dilution effects do not prevent these chemicals to be ended up in the marine environment.
This paper presents an assessment of the start-up performance of aerobic granular sludge (AGS) for the treatment of low-strength (chemical oxygen demand, COD
Recent increase in awareness of the extent of microplastic contamination in marine and freshwater systems has heightened concerns over the ecological and human health risks of this ubiquitous material. Assessing risks posed by microplastic in freshwater systems requires sampling to establish contamination levels, but standard sampling protocols have yet to be established. An important question is whether sampling and assessment should focus on microplastic concentrations in the water or the amount deposited on the bed. On three dates, five replicated water and bed sediment samples were collected from each of the eight sites along the upper reach of the Semenyih River, Malaysia. Microplastics were found in all 160 samples, with mean concentrations of 3.12 ± 2.49 particles/L in river water and 6027.39 ± 16,585.87 particles/m2 deposited on the surface of riverbed sediments. Fibres were the dominant type of microplastic in all samples, but fragments made up a greater proportion of the material on the bed than in the water. Within-site variability in microplastic abundance was high for both water and bed sediments, and very often greater than between-site variability. Patterns suggest that microplastic accumulation on the bed is spatially variable, and single samples are therefore inadequate for assessing bed contamination levels at a site. Sites with the highest mean concentrations in samples of water were not those with the highest concentrations on the bed, indicating that monitoring based only on water samples may not provide a good picture of either relative or absolute bed contamination levels, nor the risks posed to benthic organisms.
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 employs an artificial neural network optimization algorithm, enhanced with a Genetic Algorithm-Back Propagation (GA-BP) network, to assess the service quality of urban water bodies and green spaces, aiming to promote healthy urban environments. From an initial set of 95 variables, 29 key variables were selected, including 17 input variables, such as water and green space area, population size, and urbanization rate, six hidden layer neurons, such as patch number, patch density, and average patch size, and one output variable for the comprehensive value of blue-green landscape quality. The results indicate that the GA-BP network achieves an average relative error of 0.94772%, which is superior to the 1.5988% of the traditional BP network. Moreover, it boasts a prediction accuracy of 90% for the comprehensive value of landscape quality from 2015 to 2022, significantly outperforming the BP network's approximate 70% accuracy. This method enhances the accuracy of landscape quality assessment but also aids in identifying crucial factors influencing quality. It provides scientific and objective guidance for future urban landscape structure and layout, contributing to high-quality urban development and the creation of exemplary living areas.
The accumulation of potentially toxic elements (PTEs) has raised public awareness due to harmful contamination to both human and marine creatures. This study was designed to determine the concentration of copper (Cu), zinc (Zn), cadmium (Cd), and nickel (Ni) in the intestine, kidney, muscle, gill, and liver tissues of local commercial edible fish, fourfinger threadfin (Eleutheronema tetradactylum), and black pomfret (Parastromateus niger) collected from Morib (M) and Kuala Selangor (KS). Among the studied PTEs, Cu and Zn were essential elements to regulate body metabolism with certain dosages required while Cd and Ni were considered as non-essential elements that posed chronic and carcinogenic risk. The concentration of PTEs in fish tissue samples was analyzed using flame atomic absorption spectrometry (F-AAS). By comparing the concentration of PTEs in fish tissues as a bioindicator, the environmental risk of Morib was more serious than Kuala Selangor because both fish species collected from Morib resulted in a higher PTEs concentration. For an average 62 kg adult with a fish ingestion rate (FIR) of 0.16 kg/person/day in Malaysia, the estimated weekly intake (EWI) of Cd from the consumption of E. tetradactylum (M: 0.0135 mg/kg; KS: 0.0134 mg/kg) and P. niger (M: 0.0140 mg/kg; KS: 0.0132 mg/kg) had exceeded the provisional tolerable weekly intake (Cd: 0.007 mg/kg) established by the Joint FAO/WHO Expert Committee on Food Additives (JECFA) and oral reference dose (ORD) values of Cd (0.001 mg/kg/day) as provided by the United States Environmental Protection Agency (USEPA) regional screening level, thus it posed chronic risks for daily basis consumption. Besides, the value of the carcinogenic risk of Cd (0.7-3 to 0.8-3) and Ni (0.5-3 to 0.6-3) were in between the acceptable range (10-6 to 10-4) of the health index that indicates a relatively low possibility cancer occurrence to the consumers in both Morib and Kuala Selangor. This study recommended FIR to be 0.80 kg/person/day to reduce the possibility of posing chronic and carcinogenic risks while at the same time obtaining the essential nutrients from the fish.
Bioelectrochemical sensors for environment monitoring have the potential to provide facility operators with real-time data, allowing for better and more timely decision-making regarding water and wastewater treatment. To assess the robustness and sensitivity of the Sentry™ biosensor in local conditions, it was tested in Malaysia using domestically available wastewater. The study objectives included (1) enrich the biosensor locally, (2) operate and test the biosensor with local domestic wastewater, and (3) determine the biosensor's responsiveness to model pollutants through pollutant spike and immersion test as well as response to absence of wastewater. Lab-scale operation shows the biosensor was successfully enriched with (1) local University Kebangsaan Malaysia's, microbial community strain collection and (2) local municipal wastewater microflora, operated for more than 50 days with a stable yet responsive carbon consumption rate (CCR) signal. Meanwhile, two independent biosensors were also enriched and operated in Indah Water Research Centre's crude sewage holding tank, showing a stable response to the wastewater. Next, a pilot scale setup was constructed to test the enriched biosensors for the spiked-pollutant test. The biosensors showed a proportional CCR response (pollutant presence detected) towards several organic compounds in the sewage, including ethanol, chicken blood, and dilution of tested sewage but less to curry powder, methanol, and isopropanol. Conversely, there was no significant response (pollutant presence not detected) towards hexane, Congo red, engine oil, and paint, which may be due to their non-biodegradability and/or insoluble nature. Additionally, the biosensors were exposed to air for 6 h to assess their robustness towards aerobic shock with a positive result. Overall, the study suggested that the biosensor could be a powerful monitoring tool, given its responsiveness towards organic compounds in sewage under normal conditions.
Advanced sensor technology, especially those that incorporate artificial intelligence (AI), has been recognized as increasingly important in various contemporary applications, including navigation, automation, water under imaging, environmental monitoring, and robotics. Data-driven decision-making and higher efficiency have enabled more excellent infrastructure thanks to integrating AI with sensors. The agricultural sector is one such area that has seen significant promise from this technology using the Internet of Things (IoT) capabilities. This paper describes an intelligent system for monitoring and analyzing agricultural environmental conditions, including weather, soil, and crop health, that uses internet-connected sensors and equipment. This work makes two significant contributions. It first makes it possible to use sensors linked to the IoT to accurately monitor the environment remotely. Gathering and analyzing data over time may give us valuable insights into daily fluctuations and long-term patterns. The second benefit of AI integration is the remote control; it provides for essential activities like irrigation, pest management, and disease detection. The technology can optimize water usage by tracking plant development and health and adjusting watering schedules accordingly. Intelligent Control Systems (Matlab/Simulink Ver. 2022b) use a hybrid controller that combines fuzzy logic with standard PID control to get high-efficiency performance from water pumps. In addition to monitoring crops, smart cameras allow farmers to make real-time adjustments based on soil moisture and plant needs. Potentially revolutionizing contemporary agriculture, this revolutionary approach might boost production, sustainability, and efficiency.
Bisphenol A (BPA) is an essential and extensively utilized chemical compound with significant environmental and public health risks. This review critically assesses the current water purification techniques for BPA removal, emphasizing the efficacy of adsorption technology. Within this context, we probe into the synthesis of magnetic biochar (MBC) using co-precipitation, hydrothermal carbonization, mechanical ball milling, and impregnation pyrolysis as widely applied techniques. Our analysis scrutinizes the strengths and drawbacks of these techniques, with pyrolytic temperature emerging as a critical variable influencing the physicochemical properties and performance of MBC. We explored various modification techniques including oxidation, acid and alkaline modifications, element doping, surface functional modification, nanomaterial loading, and biological alteration, to overcome the drawbacks of pristine MBC, which typically exhibits reduced adsorption performance due to its magnetic medium. These modifications enhance the physicochemical properties of MBC, enabling it to efficiently adsorb contaminants from water. MBC is efficient in the removal of BPA from water. Magnetite and maghemite iron oxides are commonly used in MBC production, with MBC demonstrating effective BPA removal fitting well with Freundlich and Langmuir models. Notably, the pseudo-second-order model accurately describes BPA removal kinetics. Key adsorption mechanisms include pore filling, electrostatic attraction, hydrophobic interactions, hydrogen bonding, π-π interactions, and electron transfer surface interactions. This review provides valuable insights into BPA removal from water using MBC and suggests future research directions for real-world water purification applications.
This study investigated the impact of soil type, pH, and geographical locations on the accumulation of arsenic (As), lead (Pb), and cadmium (Cd) in rice grains cultivated in Ghana. One hundred rice farms for the sampling of rice grains and soil were selected from two regions in Ghana-Volta and Oti. The concentrations of As, Pb, and Cd were analyzed using ICP-OES. Speciation modeling and multivariate statistics were employed to ascertain the relations among measured parameters. The results showed significant variations in soil-As, Pb, and Cd levels across different soil types and pH ranges, with the highest soil-As and Cd found in alkaline vertisols. For soil-As and Cd, the vertisols with a pH more than 7.0 exhibited the highest mean concentration of As (2.51 ± 0.932 mgkg-1) and Cd (1.00 ± 0.244 mgkg-1) whereas for soil-Pb, the luvisols of soil types with a pH less than 6.0 exhibited the highest mean concentration of Pb (4.91 ± 1.540 mgkg-1). Grain As, Pb, and Cd also varied across soil types and pH levels. In regards to grain-As, the vertisols soil type, with a pH less than 6.0, shows the highest mean concentration of grain As, at 0.238 ± 0.107 mgkg-1. Furthermore, vertisols soil types with a pH level less than 6.0 showed the highest mean concentration of grain Cd, averaging at 0.231 ± 0.068 mgkg-1 while luvisols, with a pH less than 6.0, exhibited the highest mean concentration of grain Pb at 0.713 ± 0.099 mgkg-1. Speciation modeling indicated increased bioavailability of grains Cd2+ and Pb2+ ions in acidic conditions. A significant interaction was found between soil-Cd and pH, affecting grain-As uptake. The average concentrations of soil As, Pb, and Cd aligned with international standards. Generally, the carcinogenic metals detected in grain samples collected from the Volta region are higher than that of the Oti region but the differences are insignificant, and this may be attributed to geographical differences and anthropogenic activities. About 51% of the study area showed a hazard risk associated with grain metal levels, although, no carcinogenic risks were recognized. This study highlights the complex soil-plant interactions governing metal bioaccumulation and emphasizes the need for tailored strategies to minimize metal transfer into grains.
Air pollution events can be categorized as extreme or non-extreme on the basis of their magnitude of severity. High-risk extreme air pollution events will exert a disastrous effect on the environment. Therefore, public health and policy-making authorities must be able to determine the characteristics of these events. This study proposes a probabilistic machine learning technique for predicting the classification of extreme and non-extreme events on the basis of data features to address the above issue. The use of the naïve Bayes model in the prediction of air pollution classes is proposed to leverage its simplicity as well as high accuracy and efficiency. A case study was conducted on the air pollution index data of Klang, Malaysia, for the period of January 01, 1997, to August 31, 2020. The trained naïve Bayes model achieves high accuracy, sensitivity, and specificity on the training and test datasets. Therefore, the naïve Bayes model can be easily applied in air pollution analysis while providing a promising solution for the accurate and efficient prediction of extreme or non-extreme air pollution events. The findings of this study provide reliable information to public authorities for monitoring and managing sustainable air quality over time.
The presence of harmful substances in the atmosphere poses significant risks to the environment and public health. These pollutants can come from natural sources like dust and wildfires, or from human activities such as industrial, transportation, and agricultural practices. The objective of this study was to assess air quality on the East Coast of Peninsular Malaysia by analyzing historical data from the Department of Environment, Malaysia. Daily measurements of PM10, O3, SO2, NO2, and CO were collected from eight monitoring stations over 11 years (2011-2021) and analyzed using environmetric techniques. Hierarchical agglomerative cluster analysis (HACA) classified two stations as belonging to the high pollution cluster (HPC), three stations as part of the moderate pollution cluster (MPC), and three stations as the low pollution cluster (LPC). Discriminant analysis revealed a correct assignment rate of 90.50%, indicating that all five parameters were able to differentiate pollution levels with high significance (p
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.
Pakistan is the fourth largest yarn producer in the world heavily that relies on cotton crop which receives a substantial 62% of all pesticide applications. The present study was conducted to quantify the levels of pesticides such as bifenthrin, spirotetramat, pyriproxyfen, imidacloprid, and diafenthiuron in soil and plants residue at selected cotton fields of Multan District, Pakistan. In addition to pesticides, the assessment of heavy metal concentration was also conducted in order to determine the overall risks that these compounds to both plants and human population. For this analysis, 20 soil samples and 10 plant samples were collected from 10 selected cotton fields. Pesticides and heavy metals in soil and plant samples were analyzed using high-performance liquid chromatography (HPLC) and Inductively Coupled Plasma-Optical Emission Spectroscopy (ICP-OES), respectively. It was observed that all samples collected from selected fields contained pesticide residue in top soil (0-15 cm). However, no pesticides were detected in the lower soil layer (16-30 cm). In case of heavy metals, the highest concentration of Fe, Pb, and Mn was observed in both soil and plant residue samples. The heavy metals were found in the order of Fe > Mn > Pb > Zn > Cu > Cd in the soil. The total carcinogenic risk values for a few pesticides were found to range from 10-6 to 10-2, indicating that residents of the study area have low to higher chances of developing cancer. A positive correlation was observed among the pesticides (r = 0.18-0.95) as well as in metals related parameters (r = 0.49-0.96), where a weak negative correlation was found among metal to pesticide parameters except Pd where the maximum r value was 0.62. In general, the finding of this study encourages the development and adoption of sustainable agricultural practices that lower the dependence on toxic pesticides and endorse environmentally friendly alternatives.