The efficient design of turbofan engine nacelles is critical for enhancing aircraft performance and supporting sustainable aviation goals. This study investigates the aerodynamic and thermal performance of various nacelle configurations for the Boeing 777X GE9x engine, focusing on innovative cooling strategies and drag reduction. Using Computational Fluid Dynamics simulations, nacelle shapes of varying lengths (10 m and 5.5 m), including long and short nacelles with and without chevrons, as well as an optimized ultra-short nacelle, were analyzed under cruise conditions. Models were developed using MATLAB and SolidWorks, and simulations were performed in ANSYS Fluent. Results indicate that the long nacelle with chevrons provided the best overall thermal and aerodynamic performance among the conventional designs, reducing drag and block fuel consumption by 10.13%. However, the optimized ultra-short nacelle, developed using a hybrid NSGA-Non Dominated Sorting Genetic Algorithm II and fmincon- Find Minimum of Constrained optimization approach using MATLAB, achieved a significantly lower drag coefficient and reduced block fuel consumption by 80.13%. These findings demonstrate the potential of advanced nacelle designs to improve heat dissipation, reduce aerodynamic drag, and lower emissions, aligning with stringent EASA standards and contributing to sustainable aviation advancements.
This research introduces a novel single-step hybrid block method with four intra-step points that attains six-order accuracy, ensures A-stability, consistency, and convergence, and provides an efficient, accurate, and computationally economical tool for solving first-order ordinary differential equations. The formulation incorporates interpolation techniques to approximate function values at points where terms are not explicitly defined on the computational grid. In addition to the construction of the scheme, the paper rigorously investigates its theoretical properties. The results obtained show that the method not only achieves high accuracy but also performs competitively when compared with other established numerical techniques reported in the literature.
Every year, African countries face the tragic loss of life and destruction of natural and personal property due to forest fires. This issue has been the subject of research for many years in an effort to find a solution. This article aims to study the application of 3D multilateration positioning based on a hybrid of received signal strength indicator (RSSI) and angle of arrival (AoA) (RSSI/AoA) using an artificial neural network (ANN) to optimise the position of Radio Frequency Identification (RFID) sensors for forest fire prevention/detection. The first approach is based on the most commonly used radio measurement techniques, such as the hybrid RSSI/AoA technique based on the linear least squares (LLS) method to find a solution that minimises the error in the position of the RFID reader. The second approach presents a method using an RNA to correct the observed RSSI/AoA measurements, thereby aiming to locate RFID sensors in forests where obstacles are present and may influence signals. The simulation results of the RNN model show the best performance, achieving a location error of 0.2208m using four RFID sensors. This research highlights the importance of selecting artificial intelligence models for monitoring forest fires around the world.
Although water-related issues are no stranger to conventional fuel cells, unitised regenerative fuel cells (URFC) sustain amplified effects from this condition due to their transition states. Fuel cell (FC) mode start-ups post water electrolyser (WE) operations suffer significantly due to flooding. Past studies validated the significance of water and heat distribution towards the dynamic response of URFC. Due to complications involved in the numerical study of mode change conditions, this paper suggests the basic procedures required for numerical analysis of the WE to FC mode conversion in a URFC where the final result of each mode is taken as the initial result for the next one. Water removal through gas purging is currently one of the best methods to reduce transient time and increase FC start-up efficiency. However, crucial purging conditions such as operating current density, temperature and purging period play an important role in the successful transition. Lower operating current density, ranging below 0.02A/cm2 is reported to have a smoother transition compared to current density above 0.12A/cm2. Gas purge relative humidity is only effective up to 4% at the anode and poses no effect during a severe flooding condition. Furthermore, the temperature has the lowest response towards the cell heat source, increasing the transient period. The cell experiences high WE mode efficiency at 80˚C, but it suffers significant catalytic loss. The insight will provide a more profound comprehension of water management during WE mode and a suitable administrative method to achieve smooth FC start-ups.
Optimizing coagulant dosage for drinking water treatment is essential for enhancing water quality. It also improves operational efficiency and cost-effectiveness. Traditionally, treatment plants focus on removing turbidity, often neglecting other critical factors such as co-pollutant removal, residual coagulant levels, and sludge production. This study addresses these limitations by optimizing coagulant dosage to simultaneously maximize turbidity and chemical oxygen demand (COD) removal, minimize residual Al concentrations, and reduce sludge generation. It employs a multi–parameter approach to improve the water treatment process, targeting low (10 NTU), medium (50 NTU), and high (400 NTU) turbidity synthetic water samples, representative of Mahaweli River water quality. The methodology includes preparing synthetic water, conducting jar tests to evaluate coagulation performance, and using design of experiments with Response Surface Methodology to identify optimal coagulant dosages and mixing speeds. Poly-aluminum chloride (PAC) was found to be the most effective coagulant for low- and medium-turbidity waters, with optimal dosages of 7 mg/l and 7.8 mg/l, and mixing speeds of 220 rpm and 216 rpm. Under these conditions, the final turbidity of water was 0.1648 NTU and 0.6890 NTU, with sludge weights of 0.0047 g and 0.0382 g, respectively. For high turbidity water, alum was optimal at 27 mg/l, with a mixing speed of 226 rpm, resulting in a turbidity of 2.3904 NTU and a sludge weight of 0.2203 g. COD removal percentages for low, medium, and high turbidity samples were 49.12%, 53.45%, and 49.57%. Residual aluminum levels remained below 10 ppm across all samples, measured via titration and Atomic Absorption Spectroscopy (AAS). These findings show that optimized coagulant dosage improves water quality, reduces sludge, and minimizes chemical residuals, providing cost-effective and sustainable improvements in water treatment. The study recommends multi–parameter optimization strategies and mechanical mixing methods in conventional water treatment plants to enhance efficiency and ensure high-quality drinking water.
Metal-induced respiratory diseases are not well documented in Bangladesh. The objective of this study is to assess metal toxicity in terms of concentration levels in exudative lung disorder patients. After acid digestion of blood collected from exudative lung disorder patients, the concentration of eight elements (Cd, Cr, Cu, Pb, Mn, Ni, Fe and Zn) was measured using AAS. The age of the exudative lung disorder patients of both genders ranged from 20 to 75 years, living in urban and rural areas from 11 districts of the Chittagong division. Patients were categorized into three groups: smokers, nonsmokers and former smokers. The role of smoking in the metal toxicity of exudative lung disorder patients was also investigated. Blood samples were collected from healthy persons aged 20-35 years. They were used as a control to compare the metal status of patients. It is shown that current smokers with lung diseases have lower Zn levels in their blood than the patients of former smokers. Linear regression analysis for Ni and Fe in the blood of smokers showed a significant correlation between Fe and Ni at p=0.008 and p=0.003. Correlation of Mn was insignificant at p=0.371, which clearly indicates that smoking may not be a probable factor for increasing Mn in blood. But the level of Fe and Mn in the blood of nonsmokers showed a strong and positive correlation with the coefficient value of 0.814 (p<0.001). The investigation showed that metal toxicity is caused more by breathing polluted air from fuel combustion in industries and vehicles than by smoking.
This study systematically investigates both the effects of replacement level and particle size of silica fume (SF) on concrete, identifying critical insights for optimising its use as a supplementary cementitious material (SCM). The key finding is that while SF significantly enhances mechanical properties, its optimal performance is contingent on two distinct factors: a specific replacement percentage for different strengths and a refined particle size for overall efficacy. Specifically, compressive strength was maximised at a 20%wt cement replacement, achieving 49.5 MPa at 56 days, whereas flexural strength peaked at a lower 10%wt replacement, showing a 40% increase over the control. This divergence underscores distinct strengthening mechanisms; compressive strength is governed by enhanced bulk hydration, while flexural strength is more sensitive to the densification of the interfacial transition zone (ITZ). Concurrently, any incorporation of SF markedly reduced workability, with slump values plummeting from 178 mm for the control mix to just 25 mm at 25%wt replacement, primarily due to its fine particle morphology. Beyond replacement level, particle size was identified as a decisive factor. Grinding SF from a median diameter of 76 µm to a finer median diameter of 47 µm profoundly improved concrete performance, leading to a 25% increase in early compressive strength and a remarkable more than 60% increase in flexural strength compared to mixes with larger, unground SF particles, despite a manageable reduction in slump. These results demonstrate that the sustainability and structural efficiency gains from using SF are not inherent but must be engineered. Ultimately, successfully balancing the often-competing demands of workability and strength requires a tailored approach that simultaneously optimises both its proportion in the mix and its physical fineness.
Landslides are the third most frequent form of natural disaster in Malaysia, following floods and storms. It can cause significant damage to anything in its path, depending on the size and velocity of its debris. Due to the danger that it poses, determining the susceptibility of an area to landslides is a crucial step in risk mitigation. Landslide occurrences are dependent on the numerous environmental variables, which can provide information on the level of susceptibility of other locations with similar variables. To quantify the significance of each variable to landslide occurrence, a supervised Machine Learning model – an Artificial Neural Network was developed for this study. Furthermore, landslide occurrences have been associated with the disturbance of natural slopes to accommodate development, which was the main reason behind the selection of Western Sarawak as the area of interest in this study. The model was developed to understand and make landslide susceptibility predictions based on aspect, curvature, elevation, lithology type, rainfall intensity, slope angle, soil type, and TWI. Evaluating the area under the curve score and recall for the model revealed that, based on the available inputs, the model performed well with a score of 1 and 0.99, respectively.
Conventional biodiesel production from palm oil requires separate extraction and transesterification steps, leading to increased costs and complexity. This study introduces an innovative in-situ transesterification method utilizing oil palm pulp, eliminating the need for oil extraction and simplifying the production process, which ultimately reduces costs. The effects of catalyst type, methanol-to-pulp ratio, and hexane addition on biodiesel yield were systematically evaluated. Gas chromatography-mass spectrometry (GC-MS) was employed to confirm the biodiesel purity and assess the composition. Results showed that sulphuric acid (H₂SO₄) outperformed sodium hydroxide (NaOH) due to reduced soap formation, which hindered phase separation. The highest biodiesel yield of 38.79% was achieved at 75°C, using 3 wt% sulphuric acid, a 2:1 methanol-to-pulp ratio (ml:g), and a 24-hour reaction time, with no hexane addition. The presence of hexane as a co-solvent had minimal impact on biodiesel yield. This study demonstrates a cost-effective, simplified process for biodiesel production from oil palm pulp, offering significant potential for scaling up production. Future research could focus on conducting a detailed cost analysis and exploring the scalability of the in-situ process to validate its commercial viability.
Nanofluid is a promising technique for crude oil extraction in reservoirs by changing the interfacial tension (IFT) and wettability. This study aims to evaluate the capability of the nanofluid comprising palm kernel bio-surfactant (PS) and SiO2 nanoparticles (NPs). The PS incorporated with the SiO2 NPs revealed significant adsorption at various operation conditions. The optimal adsorption parameters of the palm kernel surfactant nanoparticles (PSNP) were found to be 120 minutes contact time, 0.2 %wt SiO2 NPs dosage, 40 oC temperature, pH 9, and 3 % PS concentration. The adsorption isotherms data fitted with the Langmuir isotherm (R-squared value of 0.9). Furthermore, the nanofluid has demonstrated appreciable foam stability due to the good foam morphologies observed. It was found that PSNP nanofluid decreased the IFT of the oil/brine system from 6.22 mN/m to a low level of 1 x 10-2 mN/m. Additionally, the nanofluid changed the wettability to a 10% water-wet state. Consequently, PSNP biosurfactant foam can be utilized in foam flooding enhanced oil recovery (EOR) technique.
This study explores the use of resin-treated kelempayan (Neolamarckia cadamba) as a sustainable raw material for a portable television stand prototype. The use of kelempayan as an alternative material to hardwood species promotes the use of fast-growing species that can be harvested and replanted, ensuring the long-term sustainability of tropical forest resources. However, kelempayan is a light hardwood species that requires treatment to increase its durability. The aims of this study are to determine the dimensional stability properties of treated kelempayan with phenol formaldehyde resin and, to evaluate the perception of a portable television stand prototype made from resin-treated kelempayan wood on raw material, design, marketing and satisfaction. Treated specimens showed better stability, as evidenced by the significant 101% increase in weight percent gain, 86.3% in anti-swelling efficiency, 133% in resistance to water absorption, 100% in leaching and 35% bulking enhancement through PF resin infilling into the cell lumens. Thus, increasing the chemical concentration and enhancing biological resistance and dimensional stability make it a viable option for furniture manufacturers. Besides, the analysis showed significant positive correlations, with satisfaction moderately linked to raw material (r = 0.569), and strongly associated with design (r = 0.735) and marketing (r = 0.764). The findings on consumers' satisfaction indicated that the use of treated kelempayan as an alternative raw material for furniture is acceptable. Meanwhile, the portable and simple design of the product demonstrates the potential for sustainable raw materials to be used in the production of green products that meet consumers' needs and preferences. Overall, this study contributes to the knowledge of sustainable raw materials for green products and promotes the use of alternative materials that are environmentally friendly and socially responsible. The use of resin-treated kelempayan as a sustainable raw material for a portable television stand is a step towards a more sustainable and eco-friendly furniture industry.
The development of a novel model to study the fate and environmental impact factor (EIF) of harmful chemical compounds in polluted water discharges from an offshore installation in Nigeria's marine environment was carried out in this study. The developed numerical fate model incorporates the environmental impact factor, , derived stochastically on a specific fuzzy logic-based framework, and the boundary value problem of the resulting fate and EIF model was solved via finite element method in MATLAB environment and the Dose-related Risk and Effects Assessment Model (DREAM) software using prevailing field and meteorological conditions of the marine environment. The fate concentrations of oil dispersants, harmful heavy metals (such as copper and mercury), and aromatic compounds (such as naphthalene, benzene-toluene-ethylbenzene-xylene (BTEX)) simulated at polluted water discharge rates of 3,000, 5,000, 25,000 and 75,000 barrels/day (bpd)) and average temperature of 27oC were used to compute EIFs of harmful chemical compounds in the marine environment. The results showed the produced water (PW) discharged volume and the corresponding EIF. For produced water discharge rates of 3,000, 5,000, 25,000 and 75,000 bpd, the simulated EIFs are 0, 5.6135, 5.3072 and 3.7150respectively, which is indicative of environmental risk far greater than the commonly accepted 5% risk margin in the water column in the cases of 5,000, 25,000 and 75,000 bpd. Higher risk impact derived from higher discharge rates may be effectively handled by water dilution and transport.
Unconstrained exposure of humans and their immediate environments to electrostatic fields generated by high-voltage transmission lines has raised a lot of concerns regarding public health safety. These transmission lines, often sited near human residential and urban areas, may pose long-term health risks depending on the strength and duration of exposure. Various studies have linked prolonged exposure to electromagnetic fields to various health conditions, including neuropsychological disorders, cardiovascular diseases, and central nervous system complications. While high-voltage transmission lines are essential for efficient power distribution, their proximity to populated areas necessitates regulatory policies to mitigate potential risks. This study aims to analyse the spatial variation and intensity of the electrostatic field distribution around high-voltage power transmission lines in Malaysia, using two numerical methods, considering the country’s infrastructure features and regulatory emphasis on public exposure limits. The Finite Difference Method (FDM) and the Crank-Nicolson Method (CNM) are applied to solve Laplace’s Equation, which governs electrostatic potential, field intensity and distribution. Factors such as voltage levels, tower configurations, and conductor height are considered in the analysis. The study compares the accuracy, convergence rate, computational efficiency, and execution time of both numerical techniques to determine which of the methods is more suitable to solve such a problem. Our result demonstrates that FDM is fundamentally more suited for solving the Laplace equation governing electrostatic potential, field intensity, and spatial distribution due to its direct discretisation of spatial derivatives while using CNM in this context only introduces unnecessary complexity and computational overhead without providing any benefits in returns. The study provides insights into safe management practices by identifying critical zones of elevated electrostatic field intensity, indicating minimum safe distances for human exposure, and supporting infrastructure planning in accordance with Malaysian regulatory standards.
In this study, the kinetic and thermodynamics study of solid-liquid extraction of sweet sorghum juice was carried out. Five kinetic models namely Patricelli, Peleg, log, power and Page’s models were tested in order to determine the one that best fits the recovery of soluble solids (RSS) and the juice yield data obtained at 35–65 ℃ and 0–100 minutes. The assessment of the performance of the models was achieved from statistical data such as , adjusted , root mean square error (RMSE), and percentage average absolute relative deviation (AARD) obtained by comparing the experimental data with the predicted date. The thermodynamic parameters determined were activation energy (), enthalpy change (), entropy change (), and free energy change (). The results showed that the RSS and juice yield increased with an increase in the temperature with the highest values achieved at 65 ℃. The extraction process was the fastest at the beginning until after 10 minutes when the effect of time became insignificant. Also, Patricelli’s model had the best performance while Page’s model had the worst performance. Finally, the extraction processes were endothermic (positive enthalpy change), reversible (negative entropy change), and not spontaneous but endergonic (positive free energy change). The determination of these kinetic and thermodynamic parameters will help in understanding the extraction mechanisms, scaling up and designing the extraction process, and improving energy efficiency.
Musa Paradisiaca is a variety of bananas used mainly for cooking instead of being consumed fresh. The peel of bananas, which is frequently seen as a byproduct, holds valuable nutritional and industrial potential. The nutritional banana peel can be applied and transformed into a beneficial product. This research aimed to characterise the nutritional content of the banana peel of Musa Paradisiaca and produce paper from it. The banana peel was analysed for its nutritional content across different ripening stages. The results showed that the nutritional content in the banana peel varies depending on the maturity stages, with unripe peels having the highest dry matter and fat content, ripe peels having the highest moisture, crude fibre, and protein content, and overripe peels having the highest ash content. Moreover, the total sugar content increases during the ripe stage due to enzymatic conversion to starch, and the total phenolic content of the ripe peel is at 7.93 mg GAE/g, indicating strong antioxidant properties in the peel. The paper made from the ripe peel is pale yellow with a rough texture and moderate flexibility compared to regular paper. Furthermore, ATR-FTIR analysis of the derived paper indicates that the presence of functional groups contributes to the paper’s structural integrity. Additionally, the tensile strength of the paper exhibited moderate tensile strength and rigidity. The study indicated a 36.9% weight loss after 10 days in a soil burial experiment, indicating rapid biodegradation of derived paper from ripe Musa Paradisiaca peel.
Solid waste generation and its management system were studied on different types of waste, generated from various sources such as households, hotels, bazaars, hospitals, streets, etc. of 27 wards at the Cumilla City Corporation (CuCC) area for 15 days. Both primary and secondary data on waste materials were collected for this project. The primary data collection process involved weighing waste by truckload while a questionnaire was used for secondary data collection. It was found that a total of 2,268 tons of waste was generated over the 15-day period, with food, vegetable, fish, and chicken residues making up 66%, paper products accounting for 10.64%, and polyethylene, plastic, and rubber wastes comprising 10.26%. The study revealed that approximately 79% of the waste materials were biodegradable, while the rest were non-biodegradable. Among the non-biodegradable waste, about 42% consisted of metals, 35% of glass, and 23% of plastic materials, all of which could be recycled. Additionally, there was a shortage of suitable dustbin systems, and most waste products were dumped in open fields. It was observed that 56% of people were unsatisfied with the existing waste management system of the city corporation, and only 38% were concerned about the environmental, health, and other impacts of these solid wastes. Thus, this research indicates that CuCC’s current waste management system is not up to date. The system needs to be improved, and public awareness should be raised to protect both health and the environment from the harmful effects of solid waste.
This study investigates the performance of different groups of binary liquid mixtures for various aliphatic hydrocarbons of both polar and non-polar types. This highlights the importance of selecting appropriate models based on the specific composition of the mixture for accurate predictions in industrial processes and product optimization. For this purpose, well-known equations of Grunberg-Nissan, Hind, Heric, Ausländer, McAllister 3- body and McAllister 4- body are utilized and tested for the viscosity data of different binary liquid systems, collected from previous research. The systems consist of various aliphatic alkanes, cycloalkanes, and alkanols. They are classified into four groups: Group A (Aliphatic Alkane + Alkane), Group B (Aliphatic Alkane + Cycloalkane), Group C (Aliphatic Alkane + Alkanol) and Group D (Aliphatic Cycloalkane + Alkanol). In order to measure the fitting capabilities for every group of systems, Standard Percentage Deviations (SPD) as well as temperature Average Standard Percentage Deviations (ASPD) for all of the systems are estimated. For both dynamic and kinematic viscosity correlations, among four categories, the best results are found for Group A (Aliphatic Alkanes + Aliphatic Alkanes), followed by Group B (Aliphatic Alkanes + Cycloalkanes), with the poorest results for Group C (Aliphatic Alkanes + Alkanols). In addition, with the increment of the chain length of the systems, a linear change in deviation is also observed.
A series of novel asymmetrical bis-benzimidazolium salts were synthesized via a two-step alkylation process, yielding the benzimidazolium salts of N,N'-(ethane/propane/butane-1,2/3/4-diyl)-1-benzylbenzimidazolium-1'-(n-benzonitrile)benzimidazolium dibromide (n = 2,3,4) (1Br – 9Br). These salts served as carbene precursors for the subsequent formation of nitrile-functionalized asymmetrical silver(I) di-NHC complexes (Ag1 – Ag9) (NHC = N-heterocyclic carbene) through an in-situ deprotonation method using Ag2O. Comprehensive characterization of the bis-benzimidazolium salts and their corresponding dinuclear silver(I) di-NHC complexes was performed using melting point determination, CHN elemental analyses, FTIR, and 1H- and 13C-NMR spectroscopy. The successful complexation of nitrile-functionalized NHC ligands with silver(I) ions was evidenced by the disappearance of the acidic-carbene proton peak (δ 9.69 – 10.23 ppm) in the 1H-NMR spectra of the complexes. Furthermore, the formation of Ag-Ccarbene bonds was confirmed by the appearance of characteristic peaks in the 13C-NMR spectra of Ag1 – Ag9 (δ 170.89 – 195.90 ppm). To elucidate structure-property relationships, the Principal Component Analysis (PCA) was applied to the NMR spectroscopic data. The Principal Component Analysis (PCA) of the 1H-NMR data revealed distinct clustering of bis-benzimidazolium salts and their respective silver(I) di-NHC complexes, with the first two principal components accounting for 71.40% of the total variance. Similarly, the PCA of the 13C-NMR data explained 72.08% of the total variance through the first two principal components. These results demonstrate the efficacy of PCA in differentiating and classifying the compounds based on their structural features and functional groups. Moreover, this study highlights the synergistic application of advanced spectroscopic techniques and chemometric analysis in inorganic synthesis chemistry subject and the insights gained from this approach contribute to a deeper understanding of the structural properties and potential applications of these novel NHC complexes, paving the way for future developments in organometallic chemistry and catalysis.
Oil palm is one of the largest economic sectors in Malaysia. Among the problems faced in the estates is oil palm loose fruit deposition, which is currently being collected manually in the industry. Hence, an oil palm loose fruit collector was designed using a cyclone separator mechanism and was studied using computational fluid dynamics (CFD). In the current study, Reynold’s stress model (RSM) and the discrete phase model (DPM) were employed to navigate numerical simulations where air speed intake of the designed machine was varied at 13, 30, and 46 m/s, respectively. The wall was set to a no-slip condition with standard wall functions. The hydraulic diameter of the gas outlet was Bc = 0.1 m. The hydraulic diameters of the particle’s outlet were Jc = 0.15 m and 0.2 m, respectively. Turbulence intensity at the gas and particle outlet was specified at 5%. An injection with density of 995.7 kg/m3 and a diameter of 0.04 m was set to simulate oil palm loose fruit collection into the system. Effects of air speed variations on the pressure drop and collection efficiency were then analyzed. It was found that increasing the inlet air speed from 13 m/s to 30 m/s reduced the collection efficiency by 14.92 % from 80.05% to 66.13%, while a 54.444% collection was recorded at 46 m/s inlet air speed. Ultimately, results indicate that a lower air speed is favorable in terms of pressure drop and collection efficiency.
This study aims to assess the impact of waste dumping on groundwater quality within the Chattogram City Corporation area. Monitoring eight groundwater sampling points over four years, various physical and chemical parameters were analyzed, utilizing the APHA method. Parameters assessed include pH, temperature, dissolved oxygen (DO), electrical conductivity (EC), total dissolved solids (TDS), salinity, biological oxygen demand (BOD), chemical oxygen demand (COD), Turbidity, Total Hardness, Ca-Hardness, Alkalinity, TSS, Chloride, Phosphate, Sulphate, Nitrite, Nitrate, Fluoride, Iron, Arsenic, Zinc, Copper, and Chromium. The findings were compared to the Department of Environment's (DoE) recommended values, as well as the Bangladesh standard and World Health Organization (WHO) values. During sample collection, deep tube wells near the dumping site points were prioritized. According to the investigation CNB, Ananda Bazar Halishahar and Arefin Nagar, deep pump water carries too many irons in their groundwater. Iron levels exceed both WHO and Bangladesh standards across all samples. Specifically, Arefin Nagar and Ananda Bazar Halishahar area sampling points S6, S7, and S8 surpass standards in TDS, Total Hardness, Turbidity, TSS, Chloride, and Iron. Water Quality Index (WQI) calculations suggest unsuitability for drinking purposes in all sampled water, with S5 and S8 demonstrating particularly high values, indicating their unsuitability for human consumption. Heavy Metal Pollution Index (HPI) calculations reveal a decrease at CNB sampling points S1 and S2, where waste dumping ceased in 2017. However, HPI values at other points show an increasing trend, indicating the leaching of heavy metals from solid waste into groundwater. S5 and S8 exhibit notably high HPI values (Average 464.99 and 319.59), suggesting an accumulation of heavy metals in the groundwater. Carcinogenic Risk Analysis of Arsenic highlights the failure of most sampled water to meet Carcinogenic Risk (CR) standards, signalling a potential cancer risk with prolonged use of this water.
