Method For Removal Research Articles

Digital light processing based multimaterial 3D printing: challenges, solutions and perspectives

Abstract Multimaterial (MM) 3D printing shows great potential for application in metamaterials, flexible electronics, biomedical devices and robots, since it can seamlessly integrate distinctive materials into one printed structure. Among numerous MM 3D printing technologies, digital light processing (DLP) MM 3D printing is compatible with a wide range of materials from hydrogels to ceramics, and can print MM 3D structures with high resolution, high complexity and fast speed. This paper introduces the fundamental mechanisms of DLP 3D printing, and reviews the recent advances of DLP MM 3D printing technologies with emphasis on material switching methods and material contamination issues. It also summarizes a number of typical examples of DLP MM 3D printing systems developed in the past decade, and introduces their system structures, working principles, material switching methods, residual resin removal methods, printing steps, as well as the representative structures and applications. Finally, we provide perspectives on the directions of the further development of DLP MM 3D printing technology.

Selective lipase-catalyzed hydrolysis for removal of diglyceride in palm oil

Palm-based transformer oil is an environmentally friendly and renewable alternative to mineral-based oil for use as an insulating oil. However, the crystallization of palm oil at low temperatures can cause operational issues in transformers. In this research, low diglyceride palm oil is first proposed as a promising base stock for palm-based insulating oil to overcome this issue. The research focuses on the removal of diglycerides (DG) from palm oil by selective enzymatic hydrolysis under a solvent-free system. The results indicate that the lipase GS-250G specifically catalyzes only DG molecules without hydrolyzing TG molecules, despite TG molecules being more prone to hydrolysis than DG molecules due to their higher concentration in palm oil. This unique behavior is probably attributed to steric hindrance by bulky amino acids surrounding the catalytic pocket of lipase GS-250G. Under optimum conditions (30 °C, atmospheric pressure, water content of 16 wt%, agitation speed of 850 rpm, lipase loading of 0.005 wt%, and 4 h of reaction time), the lipase GS-250G reduced the DG content in palm oil from 7 % to 0.5 % with a degree of DG hydrolysis of 95 %. After purification, the final product was composed of 99 % triglyceride (TG). The cold stability test suggested that the nucleation and crystallization rate during the crystal formation of palm oil were reduced by decreasing the DG content. The finding suggests that the proposed procedure in this work is a rapid and environmentally sustainable method for DG removal, which can solve the major problem of palm oil. This discovery opens new opportunities for palm oil to be used as a raw material only for insulating oil but also for various palm based products.

Physical Model of Inclusions Removal at Static Steel–Slag Interface

Inclusions are one of the important factors affecting the cleanliness of molten steel. The current optimization of inclusion removal methods mainly focuses on promoting inclusions to float to the slag–steel interface so that the inclusions can be absorbed and removed by the refining slag. However, the research on the floating removal of inclusions cannot be carried out directly in the ladle, so methods such as mathematical models and physical models were developed. This article uses silicone oil to simulate the slag layer; polypropylene particles; and aluminum oxide particles to simulate inclusions to establish a water model experiment. By changing the viscosity of silicone oil and the diameter of particles, the factors affecting the movement of inclusions at the slag–steel interface were explored. Based on the water model, a mathematical model of the floating behavior of inclusions at the slag–steel interface was constructed, and parameters such as particle diameter and interfacial tension in the water model experiment were studied by the mathematical model for calculation. Both the mathematical model and the water model experimental results show that after the viscosity of silicone oil increases from 0.048 Pa·s to 0.096 Pa·s, the dimensionless displacement and terminal velocity of the particles decreases. When the diameter of the same particle increases, the dimensionless displacement and terminal velocity increases. The dimensionless displacement of polypropylene particles of the same diameter is larger than that of aluminum oxide particles, and the terminal velocity is smaller than that of aluminum oxide particles. This is attributed to the better overall three-phase wettability of polypropylene particle. When the liquid level increases, the dimensionless displacement and terminal velocity of particles under the same conditions show only slight differences (less than 10%).

Highly efficient electrocatalysis of oxygen to hydroxyl radical by FeN2O2 single-atom catalyst for refractory organic pollutant removal

The heterogeneous electro-Fenton (Hetero-EF) provides an effective and environmentally friendly method for refractory pollutants removal by strongly oxidative •OH. However, the •OH generation shows an insufficient activity in activating H2O2 to •OH due to the too strong H2O2 binding on the catalytic site. Here, an iron single-atom FeN2O2 catalyst anchored on hollow spherical porous carbon (FeN2O2-HPC) was designed to enhance •OH production by modulating the H2O2 binding. The FeN2O2-HPC Hetero-EF system showed a •OH production rate of 25.0 μmol h−1 and kinetic rate constant of 2.06 h−1 for phenol removal, which exceeded the FeN4 catalyst (the most reported iron single-atom). Density function theory calculations revealed that FeN2O2 could lower the H2O2 adsorption energy and energy barrier of H2O2 activation to •OH compared with FeN4, thus enhancing •OH production. This work gives a new insight into the •OH generation enhancement of Hetero-EF by modulating single-atom coordination environment for refractory pollutants removal.

Phase Transformation of Arsenic, Antimony and Lead in High-Grade Copper Matte Converting

The duration of the high-grade matte converting process is short, the amount of slag is small, and it is difficult for the original impurity removal operation in the low-grade matte converting process to meet the current production demand. Because the removal method for impurity elements during high-grade matte converting is unclear, the phase transformation of impurity elements during this process is investigated in this study. The results show that arsenic exists mainly in the form of FeAsO4 and As2O5, antimony in the form of Sb and Sb2O5, and lead in the form of PbS and PbO in high-grade matte. During the converting process, arsenic and antimony mainly exist in the melt in the form of oxides and gradually aggregate into large particles with increasing copper content in the melt. Lead exists in matte in the form of PbS until the end of the converting process, and PbS is not completely oxidized until the matte converted to blister copper phase. The phase transformation characteristics of copper, iron, sulfur and impurity elements in the process of high-grade matte converting were revealed. This study provides a theoretical reference for the formulation of an efficient impurity removal scheme for the converting process.

Stacking with Recursive Feature Elimination-Isolation Forest for classification of diabetes mellitus.

Diabetes Mellitus is one of the oldest diseases known to humankind, dating back to ancient Egypt. The disease is a chronic metabolic disorder that heavily burdens healthcare providers worldwide due to the steady increment of patients yearly. Worryingly, diabetes affects not only the aging population but also children. It is prevalent to control this problem, as diabetes can lead to many health complications. As evolution happens, humankind starts integrating computer technology with the healthcare system. The utilization of artificial intelligence assists healthcare to be more efficient in diagnosing diabetes patients, better healthcare delivery, and more patient eccentric. Among the advanced data mining techniques in artificial intelligence, stacking is among the most prominent methods applied in the diabetes domain. Hence, this study opts to investigate the potential of stacking ensembles. The aim of this study is to reduce the high complexity inherent in stacking, as this problem contributes to longer training time and reduces the outliers in the diabetes data to improve the classification performance. In addressing this concern, a novel machine learning method called the Stacking Recursive Feature Elimination-Isolation Forest was introduced for diabetes prediction. The application of stacking with Recursive Feature Elimination is to design an efficient model for diabetes diagnosis while using fewer features as resources. This method also incorporates the utilization of Isolation Forest as an outlier removal method. The study uses accuracy, precision, recall, F1 measure, training time, and standard deviation metrics to identify the classification performances. The proposed method acquired an accuracy of 79.077% for PIMA Indians Diabetes and 97.446% for the Diabetes Prediction dataset, outperforming many existing methods and demonstrating effectiveness in the diabetes domain.

A Method of Skin Disease Detection Using Image Processing and Machine Learning

Skin conditions are prevalent health issues globally. The dangers posed by these infections are unseen, leading to physical discomfort and mental anguish. In severe cases, skin diseases can even progress to skin cancer. Consequently, the identification of skin diseases from clinical images remains a significant challenge in medical image analysis. Furthermore, manual diagnosis by medical professionals is time-consuming and subjective. Therefore, there is a need for automated skin disease prediction to expedite treatment planning for both patients and dermatologists. These studies presents a digital hair removal method and de-blurs or denoise the images. To extract essential patterns from the skin imagesand statistical features techniques are utilized. Two efficient machine learning algorithms, namely Support Vector Machine (SVM), and Convolutional Neural Network (CNN) classifiers, are employed with the extracted features to accurately classify skin images as melanoma (MEL), melanocytic nevus (NV), basal cell carcinoma (BCC), actinic keratosis (AK), benign keratosis (BKL), dermatofibroma (DF), vascular lesion (VASC), and Squamous cell carcinoma (SCC). The models are validated using the ISIC 2019 challenge and HAM10000 datasets, with SVM demonstrating slightly superior performance compared to the other classifiers. Furthermore, a comparison with state-of-the-art methods is conducted to evaluate the effectiveness of the proposed approach.

Recent Advances in Technologies for Removing Nanoparticles from Water

Abstract:: Nanoparticles are widely used in manufacturing, daily life applications, and other fields because of their unique properties. However, the nanoparticles that end up in surface water are difficult to break down naturally and cause environmental hazards that cannot be ignored. In this paper, the migration mode of nanoparticles in the environment was proposed, and the factors affecting the removal efficiency of nanoparticles mainly include ionic strength, natural organic matter, surface properties, etc. The common methods for removing nanoparticles mainly include coagulation precipitation methods, activated sludge methods, membrane filtration methods, and adsorption methods. In addition, new technologies such as photothermal removal and electro-adsorption have also been applied to remove nanoparticles in water. In future research, combining the advantages of different removal methods and using different methods interactively to remove nanoparticles in water could become a new research direction.

Smoke deposition and extraction in compartment fires with different ignition sources

The paper presents the experimental research findings on the characteristics of smoke emission and deposition during compartment fires with different ignition sources: an open flame, a heated surface, local heating sources and exposed electrical conductors. The research involved the interior design and construction materials typical of residential and industrial premises: wood, linoleum and cardboard. Adaptive approaches were proposed to the creation of smoke deposition conditions at incipient fire stages using limited volumes of liquid. The foaming agent emulsion was found to be very effective for smoke suppression. The efficiency of several methods of smoke extraction using supply and exhaust ventilation was investigated. Efficient combined techniques of smoke extraction and deposition were identified. Smoke extraction was found to be most efficient at an air velocity of less than 3 m/s. The alternation of intermittent activation of the spraying system and supply and exhaust ventilation system is the most efficient method of smoke removal. Mathematical equations were derived to predict the characteristics of sprinkler and ventilation systems, providing effective smoke deposition and extraction.

Efficient photocatalytic removal of ciprofloxacin through in-situ growth of g-C3N4 on the surface of clinoptilolite

Natural mineral clinoptilolite has many advantages such as porous structure, stability, low price, environmental protection, and simple modification process, making it an ideal choice for wastewater treatment materials. Loading photocatalysts on the surface of zeolite can effectively exert adsorption degradation synergy in wastewater treatment, improve pollutant removal and mineralization capabilities, and further reduce the harm of wastewater to the environment. In this work, g-C3N4 was in-situ grown on the surface of clinoptilolite using a one-step calcination method for efficient photocatalytic removal of the pollutant ciprofloxacin from water. In-situ growth of g-C3N4 on clinoptilolite enables the catalyst to have strong adsorption capacity for pollutants. At the same time, the large specific surface area and extended photo-generated carrier lifetime make the composite photocatalyst exhibit excellent visible light adsorption degradation ability. The CN/CLI-60 with the best photocatalytic performance showed a removal rate of over 90 % of ciprofloxacin within 60 min, much higher than pure g-C3N4 and clinoptilolite. In addition, the pH value, pollutant concentration, catalyst quantity, and cycle stability have all been investigated to evaluate the practical application potential of this catalyst. This work can provide industrial guidance for the rational design of low-cost and high-efficiency photocatalysts using natural clinoptilolite.

Selective electrocatalytic oxidation of ammonia to nitrogen by using titanium dioxide nanorod array decorated with ultrasmall Ir nanoparticles and non-noble metal Fe nanoparticles

Electrochemical ammonia oxidation process through active chlorine has been proposed as a potentially effective method for ammonia removal. Currently, most of the anodes require to use high-stable TiO2 loaded with large particles of noble metal Ru or Ir, which have low activity and high cost. Herein, we prepare ultrasmall and uniform metal nanoparticles of Ir on TiO2 to remove ammonia. Moreover, we use non-noble metal Fe to replace noble metals. The ammonia removal efficiency of Fe/TiO2 under 2 VVS Ag / AgCl during 2 h is 100 % and 94 % of ammonia is converted to N2. The Fe/TiO2 anodes not only have higher catalytic activity but also show excellent stability and reusability. Fe/TiO2 anodes still exhibit excellence activity and selectivity after 1 year. As a common metal, Fe will have more application space than iridium in ammonia removal for its low cost and selectively high efficiency.

Photocatalytic degradation of linezolid antibiotic from aqueous solution by magnetically separable nanoheterostructure Fe3O4/ MgAl2O4/BiOBr0.5Cl0.5 synthesized Composite catalyst

The photocatalytic system has been emerging as a practical method for antibiotic removal in an aqueous medium. In this study, novel MgAl2O4/BiOBr0.5Cl0.5 heterojunction was synthesized by the decoration of different mass percentages of MgAl2O4 nanoparticles (10, 20, and 30 %) on the BiOBr0.5Cl0.5 solid solution and used for the photocatalytic degradation of linezolid antibiotic. Also, to facilitate easy separation of 10 % MgAl2O4/BiOBr0.5Cl0.5 from the solution after use, it was magnetized by Fe3O4 as 2 % Fe3O4/10 % MgAl2O4/BiOBr0.5Cl0.5. Synthesized photocatalysts were characterized by XRD, XPS, Raman, FESEM, TEM, EDX, BET-BJH, DRS, PL, Mott–Schottky, VSM, and pHpzc analyses to specify the synthesized photocatalysts and determine their chemical and physical properties. In addition, the influence of experimental parameters, including pH of the initial solution, the dosage of photocatalyst, and linezolid concentration on the performance of photocatalyst in linezolid removal, were elucidated in this study. The results showed that 10 % MgAl2O4/BiOBr0.5Cl0.5 photocatalyst was the optimal sample with a maximum removal efficiency of 95.59 % within 90 min under optimal experimental parameters (1 g/L catalyst, 10 mg/L linezolid, pH = 6.5). The kinetic studies revealed that the degradation rate of 10 % MgAl2O4/BiOBr0.5Cl0.5 photocatalyst was approximately 1.8, 2.7, 2.0, and 6.3 times faster than 20 % MgAl2O4/BiOBr0.5Cl0.5, 30 % MgAl2O4/BiOBr0.5Cl0.5, BiOBr0.5Cl0.5 photocatalyst and photolysis, respectively. Scavenger tests conducted in the same process operation revealed that h+ and •O2− play the predominant roles in linezolid photocatalytic degradation. The 2 % Fe3O4/10 % MgAl2O4/BiOBr0.5Cl0.5 photocatalyst was easily collected by magnet after each use for the next run, and its activity after five runs has reached 90 %.

Enzymatic removal of Numts from Panthera tigris DNA samples

Forensic mitochondrial DNA analysis is a vital investigative tool for wildlife casework, but numts continue to complicate DNA analysis. A major goal of wildlife forensic DNA analysis is to identify non-human biological evidence to its taxonomic source. Species identification is accomplished by sequencing genetic markers on the mitochondrial genome and comparing evidentiary sequence data to published reference sequences. Due to the high level of sequence similarity between mitochondrial genes and numts, current sequencing methods result in co-amplification of the target gene marker and non-target numt. Co-amplification of target and non-target loci results in ambiguous nucleotide calls in sequence data. Reducing the influence of numts during sequence analysis will provide a technique that will maximize accuracy and minimize error in taxonomic identifications. To overcome the analytical burden of numts, we studied the enzymatic removal of numts using exonuclease V. To evaluate the feasibility of exonuclease V as a numt removal method, total Panthera tigris DNA was extracted from blood and liver and divided into three treatment groups: untreated, 1st digest, and 2nd digest. For the untreated sample, 7.6 % of the 620 bp sequence data was classified as ambiguous. Following treatment, all samples demonstrated a reduction in ambiguous calls: liver-1st digest (48 h): 6.6 %, liver-2nd digest (48 h + 16 h): 1.8 %, and blood-1st digest (48 h): 0 %. Based on this preliminary study, exonuclease V treatment effectively removed numts before sequencing analysis. While exonuclease V treatment has demonstrated potential, additional studies are required to optimize the reaction and fully validate the methodology.

Air-water Interfacial Properties of Perfluorosulfonic Acid Salts with Different Chain Lengths

Perfluorosulfonic acids (PFSA) are a class of per- and polyfluoroalkyl substances (PFAS), which have been extensively used in numerous applications. The toxicity and bioaccumulation of PFAS have become a serious worldwide problem. Foam fractionation has been suggested as a promising remediation method for PFAS removal owing to the amphiphilic nature of most of the currently existing PFAS in the environment, allowing them to migrate to the air-water interface during the foaming process. Nevertheless, the current challenge for widespread utilization of foam fractionation is its low removal efficiency, especially for short-chain PFAS. Foam fractionation performance depends on the air-water interfacial properties as well as the ability for PFAS to adsorb at the air-water interface. In the present study, therefore, we investigate surface tensions of PFSA with long and short chain lengths. Different adsorption models are studied to estimate maximum surface excess concentrations for various PFSA. Our results indicate that long-chain PFSA have lower surface tensions, higher surface activities, and form more rigid air-water interfaces. This study marks the first investigation of dilatational interfacial rheology of PFAS, as well as addressing the gap in understanding PFAS interfacial rheology by focusing on the quantification the storage and loss interfacial moduli, which are known to play a significant role in the foaming process.

Considerations and Opportunities for Probe Capture Enrichment Sequencing of Emerging Viruses from Wastewater.

Until recently, wastewater-based monitoring for pathogens of public health concern primarily used PCR-based quantification methods and targeted sequencing for specific pathogens (e.g., SARS-CoV-2). In the past three years, researchers have expanded sequencing to monitor a broad range of pathogens, applying probe capture enrichment to wastewater. The goals of those studies included (1) monitoring and expanding fundamental knowledge of disease dynamics for known pathogens and (2) evaluating the potential for early detection of emerging diseases resulting from zoonotic spillover or novel viral variants. Several studies using off-the-shelf probe panels designed for clinical and environmental surveillance reported that enrichment increased virus relative abundance but did not recover complete genomes for most nonenteric viruses. Based on our experience and recent results reported by others using these panels for wastewater, clinical, and synthetic samples, we discuss challenges and technical factors that affect the rates of false positive and false negative results. We identify trade-offs and opportunities throughout the workflow, including in wastewater sample processing, probe panel design, and bioinformatic analysis. We suggest tailored methods of virus concentration and background removal, carefully designed probe panels, and multithresholded bioinformatics analysis.

A novel combined method for nitrate removal by chemical Pd–Cu/alumina bimetallic catalyst and biohydrogen produced by Rhodobacter johrii VT1 in an anaerobic, photo-fermentation process

In this study, biohydrogen was produced by R. johrii strain VT1 using an anaerobic photo-fermentation process on low-cost industrial wastewater and then used for nitrate reduction in the presence of a chemical catalyst. The effect of substrate, light intensity, and pH on biohydrogen production was investigated. For efficient nitrate reduction, a Pd–Cu/alumina bimetallic catalyst was prepared and analyzed by XRD, FTIR, FESEM, and ICP. Accumulative biohydrogen production was 284.67 ml/h (0.409 ± 0.005 mol/m3h), with molasses, a light intensity of 5300 lux, and a pH of 9. Nitrate removal efficiency was 81.70%, and nitrogen selectivity was 94.25%. The XRD results also showed the stability of the catalyst structure during the reduction. Our study shows that this combined method is effective for nitrate removal and has the potential for large-scale work because of the affordable and sustainable green hydrogen production from wastewater. This is the first report of using biological hydrogen for harmful nitrate removal from drinking water in the presence of a chemical catalyst.

Density functional theory-based screening of Ti4C3O2-loaded single atoms for efficient selective catalytic oxidation of formaldehyde

Indoor formaldehyde (HCHO) pollution poses a major risk to human health. Low-temperature catalytic oxidation is an effective method for HCHO removal. The high activity and selectivity of single atomic catalysts provide a possibility for the development of efficient non-precious metal catalysts. In this study, the most stable single-atom catalyst Ti-Ti4C3O2 was screened by density functional theory among many single atomic catalysts with two-dimensional (2D) monolayer Ti4C3O2 as the support. The computational results show that Ti-Ti4C3O2 is highly selective to HCHO and O2 in complex environments. The HCHO oxidation reaction pathways are proposed based on the Eley-Rideal (E-R) and Langmuir-Hinshelwood (L-H) mechanisms. According to the reaction energy and energy span models, the E-R mechanism has a lower maximum energy barrier and higher catalytic efficiency than the L-H mechanism. In addition, the stability of the Ti-Ti4C3O2 structure and active center was verified by diffusion energy barrier and ab initio molecular dynamics simulations. The above results indicate that Ti-Ti4C3O2 is a promising non-precious metal catalyst. The present study provides detailed theoretical insights into the catalytic oxidation of HCHO by Ti-Ti4C3O2, as well as an idea for the development of efficient non-precious metal catalysts based on 2D materials.

Non-destructive microwave techniques for the quantification and elimination of moisture in cultural heritage monuments

In this paper, we present our experimental methodology, which was developed to assess and eliminate the excess moisture levels in the masonry of a Roman archeological monument, namely the Mensa Ponderaria of Tivoli, which is an important landmark dating back to the first century A.D. The need to keep interventions to a minimum were crucial factors for choosing microwave techniques as a non-destructive method for removal and moisture infiltration measurements in the walls. We used a microwave generator connected to a horn antenna to increase the temperature locally at the point of treatment and achieve the elimination of moisture. Additionally, to quantify the amount of eliminated water, we used a free space transmission measurement by two patch micro-strip fed antennas with a resonance at 2.62 GHz connected to a vector network analyser (VNA). S-parameters were measured at a frequency range 2–3 GHz. The phase shift method was used to extract the effective dielectric permittivity by the phase of the transmission S21 parameter. In the final step, we derived the volumetric water content of the wall θ (%) based on the dielectric permittivity of the wall material (tuff). Measurements were performed at several points of the masonry, which were previously treated with microwaves or remained without treatment for comparison. We report an average of 139 gr in water extraction from the treated areas of the masonry with the mild treatment protocol we used, with the possibility of further increase with longer or higher-power drying cycles.

Current Progress on Dual‐Layer Hollow Fiber Mixed‐Matrix Membrane in CO2 Capture

AbstractCarbon dioxide (CO2) is a greenhouse gas which is mainly found in natural gas (NG), biogas, and flue gas. Anthropogenic CO2 emissions are the direct result of burning fossil fuels. Meanwhile, pre‐ and postcombustion CO2 separation is a current state of CO2 removal method in an extensive manner. From environmental, economic, and transportation perspectives, removal of CO2 has driven the development of its separation process technology. Among the reported technologies, membrane‐based gas separation technologies have grown substantially, breakthroughs and advances in past decades. This review paper aims to provide an overview on competitive gas separation processes, different types of membranes available, gas transport mechanisms, and fabrication process of hollow fiber membranes, particularly dual‐layer hollow fiber membrane. The performance of the membranes in CO2 separation and effect of spinning parameters on the formation of hollow fiber membranes are highlighted. In addition, approaches to improve the dual‐layer adhesion, strategies to enhance the filler compatibility in the development of dual‐layer hollow fiber mixed‐matrix membranes, and effect of post‐treatments on the gas separation performance of membrane are also discussed. Finally, challenges and future perspectives of dual‐layer hollow fiber mixed‐matrix membranes toward CO2 capture, particularly on CO2/CH4 and CO2/N2 separation, are also included, due to its substantial and direct relevance to the gas separation industry.

An Updated Ecotoxicological Evaluation and Health Risk Assessment of Metal Contaminants in Perna viridis Mussel Harvested on March to August 2018 from Pasir Gudang Coastal Area, Malaysia

Perna viridis (P. viridis) is a significant protein source globally but is often contaminated by metals due to its filter-feeding behavior. Given that Kampung Pasir Puteh, Pasir Gudang (Johor) is Malaysia's primary P. viridis harvesting site and the last health risk assessment (2015) was incomplete, the metal contamination status remains uncertain. Graphite furnace-atomic absorption spectroscopy was employed to analyze metal contaminant concentrations in P. viridis samples collected from March to August 2018, as per Malaysian legal requirements. The R2 values varied between 0.9976 and 0.9980 for P. viridis mussels and between 0.9976 and 0.9999 for seawater. The recovery for P. viridis mussels and seawater ranged from 93.95% to 106.80% and 92.73% to 108.84%, respectively. Precision and accuracy for both intra and inter-day measurements ranged from 0.15% to 5.49% for P. viridis and 0.05% to 5.58% for seawater. The concentrations of metal contaminants in P. viridis varied significantly among the different months of sampling (p < 0.05). All P. viridis samples had higher concentration of arsenic (3.16 -75.80μgg-1) than that prescribed by the Malaysian law. Higher cadmium concentration was observed during July (2.12μgg-1) and August (2.05μgg-1) alone. With target hazard quotients and hazard indices > 1.0, the likelihood of negative health impacts from consuming these mussels cannot be ignored. TCR values for As and Cd exceeded USEPA standards, indicating a potential lifetime carcinogenic risk from continuous P. viridis consumption. Pb (21.20 to 49.28µgL-1) in all surface seawater samples was invariably higher than the allowable limit for Class 2 water areas. Metal contaminant concentrations varied significantly between P. viridis and surface seawater (p < 0.05), implying inconsistent bioaccumulation due to pollution differences. Given the significance of P. viridis mussels, concerted scientific efforts are essential to devise effective metal contaminant removal methods.