Phosphorus (P) plays an important role in regulating primary production in estuarine environments. However, knowledge of the P-functional gene composition of microbial communities and the mechanisms of microbial adaptation to changes in available P in estuaries remain limited. This study coupling 16 s rDNA and metagenomics sequencing was conducted to reveal the relationship between P cycling functional genes, microbial interactions, and P availability in the Jiulong River Estuary. The results showed that the relative abundance of P cycling functions genes was highest in winter, and lowest in summer. Spatially, the total relative abundance of P cycling functions genes was higher in the riverward than that in the seaward. P cycling functional microbial interactions and P cycling gene coupling were strongest in summer and in the seaward. Changes in both temperature and salinity had significant direct and indirect effects on P cycling function, and the influence of salinity on P cycling function was greater than that on the microbial community in the estuary. Salinity had significant direct negative effects on inorganic P-solubilization (IP), organic P-mineralization (OP), and P uptake and transport functions (PT). Whereas, salinity had a significant positive effect on P-starvation response regulation (PR) function. Thus, salinity and microbial communities regulate the soluble reactive phosphate concentrations in estuarine environments by strengthening internal coupling among P cycling functions, promoting PR function, and facilitating PT gene expression. PR is the most important predictors, PR, PT, and PR-PT together explained 38.56 % of the overall soluble reactive phosphorus (SRP) variation. Over 66 % of the explained SRP variations can be predicted by the PR, PT, and PR-PT functional genes. This finding improves the knowledge base of the microbial processes for P cycling and provides a foundation for eutrophication management strategies in the estuary.
The approach of combining cost-effective nanopore sequencing and emerging environmental DNA (eDNA) metabarcoding could prove to be a promising tool for biodiversity documentation, especially in Malaysia. Given the substantial funding constraints in recent years, especially in relation to the country's biodiversity, many researchers have been limited to conduct restricted research without extended monitoring periods, potentially hindering comprehensive surveys and could compromise the conservation efforts. Therefore, the present study aimed to evaluate the application of eDNA metabarcoding on freshwater fish using short reads generated through nanopore sequencing. This assessment focused on species detection in three selected rivers within the Endau Rompin Landscape in Malaysia. Additionally, the study compared levels of species detection between eDNA metabarcoding and conventional sampling methods, examined the effectiveness of primer choice, and applied both metabarcoding and shotgun sequencing to the eDNA approach. We successfully identified a total of 22 and 71 species with an identification threshold of >97% and >90%, respectively, through the MinION platform. The eDNA metabarcoding approach detected over 13% more freshwater fish species than when the conventional method was used. Notably, the distinction in freshwater fish detection between eDNA primers for 12S rRNA and cytochrome oxidase I was insignificant. The cost for eDNA metabarcoding proved to be more effective compared to conventional sampling with cost reduction at 33.4%. With favourable cost-effectiveness and increased species detection, eDNA metabarcoding could complement existing methods, enhance holistic diversity documentation for targeted habitats and facilitate effective conservation planning.
Organophosphate esters (OPEs) have received considerable attention in environmental research due to their extensive production, wide-ranging applications, prevalent presence, potential for bioaccumulation, and associated ecological and health concerns. Low efficiency of OPE removal results in the effluents of wastewater treatment plants emerging as a significant contributor to OPE contamination. Their notable solubility and mobility give OPEs the potential to be transported to coastal ecosystems via river discharge and atmospheric deposition. Previous research has indicated that OPEs have been widely detected in the atmosphere and water bodies. Atmospheric deposition across air-water exchange is the main input route for OPEs into the environment and ecosystems. The main processes that contribute to air-water exchange is air-water diffusion, dry deposition, wet deposition, and the air-water volatilization process. The present minireview links together the source, occurrence, and exchange of OPEs in water and air, integrates the occurrence and profile data, and summarizes their air-water exchange in the environment.
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.
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.
Water and soft drink bottles made from polyethylene terephthalate (PET) sink at sea unless they contain trapped air, whereas their lids are made from polymers that float and can drift long distances. We sampled loose lids and bottles at 21 South African beaches to compare their origins. The proportions of foreign-made bottles and lids were correlated, and increased away from urban centres, indicating that much land-based litter strands close to source areas. Over 80 % of foreign-made drink bottles and 90 % of lids came from Asia, but most bottles were manufactured in China, Malaysia-Singapore and the UAE, and were dumped from ships. By comparison, most loose lids were in poor condition after being carried across the Indian Ocean from Indonesia by the South Equatorial Current. Reducing PET drink bottles at sea requires enforcement of regulations banning dumping at sea, whereas reducing their lids requires better control of littering in source countries.
This research provides a comprehensive analysis of groundwater pollution in the Lower Anayari Catchment (LAC) through δ2H and δ18O isotopic analysis, along with positive matrix factorization (PMF) and PCS-MLR receptor models. Forty groundwater samples were collected from hand-dug wells and equipped boreholes across the LAC. Flame photometry for Na+ and K+, complexometric titration for Ca2+, ion chromatography for Cl-, F-, NO3-, SO42-, and PO43-, and atomic absorption spectrometry for Mg2+, Fe, Pb, Cd, As, and Ni were analytical techniques/instruments employed. In regard to cations, Na+ has the highest average concentration of 63.0 mg/L, while Mg2+ has the lowest at 2.58 mg/L. Concerning the anions and nutrients, Cl- has the highest mean concentration of 18.7 mg/L, and Fl- has the lowest at 0.50 mg/L. Metalloids were detected in trace amount with Fe displaying the highest mean concentration of 0.077 mg/L whereas Cd and As recorded lowest (0.001 mg/L). The average values for groundwater δ18O and δ2H were - 3.64‰ and - 20.7‰, respectively; the average values for rainwater isotopic composition were - 3.41‰ for δ18O and - 17.4‰ for δ2H. It is believed that natural geological features, particularly biotite granitoid and volcanic flow/subvolcanic rocks from the Birimian Supergroup, significantly influence groundwater mineralisation. Additionally, the impact of anthropogenic activities on water quality, with urban development and agricultural practices, may be attributed to increasing levels of certain contaminants such as Fe, Ni, NO3-, and PO43-. This research contributes to the broader field of hydrological study and provides practical implications for managing and conserving water resources in similar contexts. The innovative combination of isotopic and statistical analyses sets a new standard for future studies in groundwater quality assessment, emphasising the need for comprehensive approaches that consider both geological characteristics and human impacts for sustainable water resource management.
Owing to a wide range of advantages, such as stability, non-invasiveness, and ease of sampling, hair has been used progressively for comprehensive biomonitoring of organic pollutants for the last three decades. This has led to the development of new analytical and multi-class analysis methods for the assessment of a broad range of organic pollutants in various population groups, ranging from small-scale studies to advanced studies with a large number of participants based on different exposure settings. This meta-analysis summarizes the existing literature on the assessment of organic pollutants in hair in terms of residue levels, the correlation of hair residue levels with those of other biological matrices and socio-demographic factors, the reliability of hair versus other biomatrices for exposure assessment, the use of segmental hair analysis for chronic exposure evaluation and the effect of external contamination on hair residue levels. Significantly high concentrations of organic pollutants such as pesticides, flame retardants, polychlorinated biphenyls and polycyclic aromatic hydrocarbon were reported in human hair samples from different regions and under different exposure settings. Similarly, high concentrations of pesticides (from agricultural activities), flame retardants (E-waste dismantling activities), dioxins and furans were observed in various occupational settings. Moreover, significant correlations (p
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.
Airborne Microplastics (MPs), an emerging environmental issue, have gained recent attention due to their newfound presence in indoor environments. Utilizing the Web of Science database for literature collection, the paper presents a comprehensive review of airborne MPs including emission sources, assessment methods, exposure risks, and mitigation strategies. This review delves into the diverse sources and mechanisms influencing indoor airborne MP pollution, underscoring the complex interplay between human activities, ventilation systems, and the characteristics of indoor environments. Major sources include the abrasion of synthetic textiles and the deterioration of flooring materials, with factors like carpeting, airflow, and ventilation significantly impacting MP levels. Human activities, such as increased movement in indoor spaces and the intensive use of plastic-based personal protective equipment (PPE) post-pandemic, notably elevate indoor MP concentrations. The potential health impacts of airborne MPs are increasingly concerning, with evidence suggesting their role in respiratory, immune, and nervous system diseases. Despite this, there is a scarcity of information on MPs in diverse indoor environments and the inhalation risks associated with the frequent use of PPE. This review also stresses the importance of developing effective strategies to reduce MP emissions, such as employing HEPA-filtered vacuums, minimizing the use of synthetic textiles, and enhancing indoor ventilation. Several future research directions were proposed, including detailed temporal analyses of indoor MP levels, interactions of MP with other atmospheric pollutants, the transport dynamics of inhalable MPs (≤10 μm), and comprehensive human exposure risk assessments.
Organic pollution continues to be an important worldwide obstacle for tackling health and environmental concerns that require ongoing and prompt response. To identify the LAB content levels as molecular indicators for sewage pollution, surface sediments had obtained from the South region of Malaysia. The origins of the LABs were identified using gas chromatography-mass spectrometry (GC-MS). ANOVA and a Pearson correlation coefficient at p
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.
Polycyclic Aromatic Hydrocarbons (PAHs) profoundly impact public and environmental health. Gaining a comprehensive understanding of their intricate functions, exposure pathways, and potential health implications is imperative to implement remedial strategies and legislation effectively. This review seeks to explore PAH mobility, direct exposure pathways, and cutting-edge bioremediation technologies essential for combating the pervasive contamination of environments by PAHs, thereby expanding our foundational knowledge. PAHs, characterised by their toxicity and possession of two or more aromatic rings, exhibit diverse configurations. Their lipophilicity and remarkable persistence contribute to their widespread prevalence as hazardous environmental contaminants and byproducts. Primary sources of PAHs include contaminated food, water, and soil, which enter the human body through inhalation, ingestion, and dermal exposure. While short-term consequences encompass eye irritation, nausea, and vomiting, long-term exposure poses risks of kidney and liver damage, difficulty breathing, and asthma-like symptoms. Notably, cities with elevated PAH levels may witness exacerbation of bronchial asthma and chronic obstructive pulmonary disease (COPD). Bioremediation techniques utilising microorganisms emerge as a promising avenue to mitigate PAH-related health risks by facilitating the breakdown of these compounds in polluted environments. Furthermore, this review delves into the global concern of antimicrobial resistance associated with PAHs, highlighting its implications. The environmental effects and applications of genetically altered microbes in addressing this challenge warrant further exploration, emphasising the dynamic nature of ongoing research in this field.
The Guerouaou aquifer investigation spanning 280 km2 in Ain Zohra yields promising outcomes, instilling optimism for regional water quality. These analyses were applied to 45 sampling instances from 43 wells, enabling a comprehensive water quality assessment. Groundwater conductivity ranged from medium to high, peaking at 18360 ms/cm2. The conductivity reveals insights about the groundwater's mineralization. Key physiochemical parameters fell within desirable thresholds, bolstering the positive perspective. HCO3- levels spanned 82-420 mg/L, while chloride content ranged from 38 to 5316 mg/L, benefiting water quality. NO3- ions, vital for gauging pollution, ranged from 0 to 260 mg/L, indicating favorable results. Cation concentrations exhibited encouraging variations: Ca2+- 24 to 647 mg/L, Mg2+- 12 to 440 mg/L, Na+- 18 to 2722 mg/L, K+- 1.75 to 28.65 mg/L. These collectively favor water quality. Halite breakdown dominated mineralization, as evidenced by the prevalence of Na-Cl-Na-SO4 facies. Water resource management and local communities need effective management and mitigation strategies to prevent saltwater intrusion.
Microplastics (MPs) are a pervasive pollutant in the marine environment. Pantai Teluk Likas in Sabah, Malaysia is one of the most visited beaches where tourism, recreational, and fisheries activities are high in this area. Hence, the area suffers from severe pollution, particularly from plastics. This study aims to quantify the microplastic composition in terms of color, shapes, and polymer types in marine bivalves (Anadara granosa, Glauconome virens, and Meretrix lyrata) and water column samples from Pantai Teluk Likas. All samples were digested using sodium hydroxide (NaOH) and incubated in the oven for at least 48 h. Serial filtration was done for each sample before they were observed under the dissecting microscope. The microplastics were identified and counted based on their physical attributes which were colors and shapes. The functional group of the polymers was determined using FTIR spectroscopy. Microplastics were found present in all samples collected. G. virens had the highest abundance of microplastics at 113.6 ± 6.5 particles/g followed by M. lyrata at 78.4 ± 3.7 particles/g. On the contrary, A. granosa had the least microplastics with an abundance of 24.4 ± 0.6 particles/g. Meanwhile, 110.0 ± 36.2 particles/L of microplastics were found in water column samples from Pantai Teluk Likas. Based on the analysis, fibers were the most common shape in bivalves, while fibers and films were common in the water column. In terms of colors, black, blue, and red were a few of the most abundant colors observed in both samples. The most common polymer detected in all bivalve species and water column samples is polycarbonate (PC), followed by polymethyl methacrylate (PMMA). Future study that focuses on the correlation between microplastic abundance in the marine biota and the water column is recommended to better understand microplastic availability and exposure.
Digital image processing has witnessed a significant transformation, owing to the adoption of deep learning (DL) algorithms, which have proven to be vastly superior to conventional methods for crop detection. These DL algorithms have recently found successful applications across various domains, translating input data, such as images of afflicted plants, into valuable insights, like the identification of specific crop diseases. This innovation has spurred the development of cutting-edge techniques for early detection and diagnosis of crop diseases, leveraging tools such as convolutional neural networks (CNN), K-nearest neighbour (KNN), support vector machines (SVM), and artificial neural networks (ANN). This paper offers an all-encompassing exploration of the contemporary literature on methods for diagnosing, categorizing, and gauging the severity of crop diseases. The review examines the performance analysis of the latest machine learning (ML) and DL techniques outlined in these studies. It also scrutinizes the methodologies and datasets and outlines the prevalent recommendations and identified gaps within different research investigations. As a conclusion, the review offers insights into potential solutions and outlines the direction for future research in this field. The review underscores that while most studies have concentrated on traditional ML algorithms and CNN, there has been a noticeable dearth of focus on emerging DL algorithms like capsule neural networks and vision transformers. Furthermore, it sheds light on the fact that several datasets employed for training and evaluating DL models have been tailored to suit specific crop types, emphasizing the pressing need for a comprehensive and expansive image dataset encompassing a wider array of crop varieties. Moreover, the survey draws attention to the prevailing trend where the majority of research endeavours have concentrated on individual plant diseases, ML, or DL algorithms. In light of this, it advocates for the development of a unified framework that harnesses an ensemble of ML and DL algorithms to address the complexities of multiple plant diseases effectively.
A pioneering study employed a holistic geostatistical approach to predict the spatial variability of a non sampled area in the Chenab River, Pakistan, using kriging interpolation for organochlorine pesticide (OCP)-polluted risk zones. The Present research intended to investigate the carcinogenic and non-carcinogenic human health risks, contamination levels, and spatial variation of OCPs in the Chenab River, Pakistan. The residual OCP content in sediment samples (n = 120) ranged from 0.056 to 32.14 ng/g. DDE and α-HCH were prevalent among all the samples analyzed, with mean concentrations of 15.84 ± 8.02 and 12.45 ± 6.72 ng/g, respectively. The order of magnitude of OCPs in sediment samples was DDTs > α-HCH > chlorothalonil > heptachlor > endosulfan > aldrin > dieldrin. The findings of the single (SPI) and Nemerow (Nel) pollution index of α-HCH, heptachlor, and aldrin depicted the Chenab River as a serious pollution risk zone. The outcomes of the Pearson correlation coefficient analysis represent the positive correlation among all OCPs, revealing the common origin. Distribution trends showed substantially higher (p 10-4 illustrated a substantial cancer health risk posed by α-HCH, heptachlor, aldrin, and dieldrin in the downstream zone. We recommend the urgent cessation of the ongoing discharge of OCPs into the Chenab River, which needs to be highlighted owing to the significant cancer risk to public health to ensure the good health and wellbeings.
Microplastic (MP) pollution has emerged as a pressing environmental concern due to its ubiquity and longevity. Biodegradation of MPs has garnered significant attention in combatting global MP contamination. This study focused on MPs within sediments near the sewage outlet of Shenzhen Bay. The objective was to elucidate the microbial communities in sediments with varying MPs, particularly those with high MP loads, and to identify microorganisms associated with MP degradation. The results revealed varying MP abundance, ranging from 211 to 4140 items kg-1 dry weight (d. w.), with the highest concentration observed near the outfall. Metagenomic analysis confirmed the enrichment of Psychrobacter species in sediments with high MP content. Psychrobacter accounted for ∼16.71% of the total bacterial community and 41.71% of hydrocarbon degrading bacteria at the S3 site, exhibiting a higher abundance than at other sampling sites. Psychrobacter contributed significantly to bacterial function at S3, as evidenced by the Kyoto Encyclopedia of Genes and Genomes pathway and enzyme analysis. Notably, 28 enzymes involved in MP biodegradation were identified, predominantly comprising oxidoreductases, hydrolases, transferases, ligases, lyases, and isomerases. We propose a putative mechanism for MP biodegradation, involving the breakdown of long-chain plastic polymers and subsequent oxidation of short-chain oligomers, ultimately leading to thorough mineralization.
Microplastics (MPs) pose a threat to ecosystems due to their capacity to bind with toxic chemicals. While the occurrence of MPs in aquatic environmental matrices like water, sediments, and biota is well studied, their presence in the atmosphere remains less understood. This study aimed to determine the presence of airborne MPs and their characteristics through ground-based sampling in the coastal city of Kuala Nerus, Terengganu, Malaysia. Airborne MP samples were collected using passive sampling technique in December 2019. MPs were manually counted and identified using a stereomicroscope based on their colour and shape. The average deposition rate of airborne MPs during the sampling period was 5476 ± 3796 particles/m2/day, ranging from 576 to 15,562 particles/m2/day. Various colours such as transparent (38%), blue (25%), black (20%), red (13%), and others (4%) were observed. The predominant shape of airborne MPs was fibres (> 99%). The morphology structure of MPs observed using a scanning electron microscope (SEM) showed a cracked surface on MPs, suggesting weathering and irregular fragmentation. Further elemental analysis using energy dispersive X-ray spectroscopy (EDS) showed the presence of heavy metals such as aluminium (Al) and cadmium (Cd) on the surface of MPs, attributed to the adsorption capacities of MPs. Polymer types of airborne MPs were analysed using attenuated total reflectance-Fourier transform infrared spectroscopy (ATR-FTIR), which revealed particles composed of polyester (PES), polyethylene (PE), and polypropylene (PP). The preliminary findings could provide additional information for further investigations of MPs, especially in the atmosphere, to better understand their sources and potential human exposure.
Even though Pacific - Indian Ocean exchange [Indonesian Throughflow (ITF)] has been measured for the last three decades, the measurements of microplastic in the region is very limited. This study was the initial investigation of the vertical distribution of microplastic in the deep-sea areas across the ITF Pathway. Niskin water samples were utilized to obtain the samples from a water column in a range of 5 to 2450 m. A total of 924 microplastic particles with an average abundance of 1.062 ± 0.646. n/L were found in the water column. Our findings indicate that water temperature and water density are the most significant factors correlated to the microplastic concentration. This study will be the first report discussing the distribution of microplastics in the deep-sea water column that could be highly significant in determining the fate and transport of microplastic within Indonesian waters that exits into the Indian Ocean.