Browsing by Author "Senapathi, Venkatramanan"

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A New Approach from Public Behavioral Attitudes and Perceptions Towards Microplastics: Influencing Factors, and Policy Proposals
(Elsevier, 2024-07-01) Al Masud, Abdulla; Islam, Abu Reza Md Towfiqul; Al Mamun, Abdullah; Alam, G.M. Monirul; Arabameri, Alireza; Bari, A.B.M. Mainul; Pal, Subodh Chandra; Rakib, Md Refat Jahan; Senapathi, Venkatramanan; Bodrud-Doza, Md.; Idris, Abubakr M.; Malafaia, Guilherme
This research paper addresses the urgent environmental concern of microplastic (MP) emissions, focusing on the behavioral attitudes and perceptions of the general populace in Shyamnagar Upazila, Bangladesh. Against the backdrop of escalating MP pollution globally, this study investigates the level of awareness and the factors influencing public engagement in mitigating MP prevalence. Leveraging survey data from 350 respondents, the ordered logistic regression (OLR) and boosted regression tree (BRT) models are employed for comprehensive data analysis. The findings expose a concerning lack of awareness about MPs, as only 12% of respondents possessed prior knowledge, and a notable 63% remained uninformed about MP pollution. The OLR model reveals a positive correlation between heightened awareness of MPs and an increased willingness to take action. Gender differences become evident, with women exhibiting greater willingness than men to mitigate MP emissions, and environmental practitioners displaying heightened motivation. The BRT model underscores construction materials and industrial pollution as the primary influential factors amplifying MP pollution. These insights not only illuminate the existing scenario but also provide a basis for fostering favorable behavioral attitudes and perceptions to mitigate the prevalence of MPs within the coastal milieu.
A review of recent advances and future prospects in calculation of reference evapotranspiration in Bangladesh using soft computing models
(Scopus, 2024) Alam, Md Mahfuz; Akter, Mst. Yeasmin; Reza, Abu; Islam, Md Towfiqul; Mallick, Javed; Kabir, Zobaidul; Chu, Ronghao; Arabameri, Alireza; Pal, Subodh Chandra; Masud, Md Abdullah Al; Costache, Romulus; Senapathi, Venkatramanan
Evapotranspiration (ETo) is a complex and non-linear hydrological process with a significant impact on efficient water resource planning and long-term management. The Penman-Monteith (PM) equation method, developed by the Food and Agriculture Organization of the United Nations (FAO), represents an advancement over earlier approaches for estimating ETo. Eto though reliable, faces limitations due to the requirement for climatological data not always available at specific locations. To address this, researchers have explored soft computing (SC) models as alternatives to conventional methods, known for their exceptional accuracy across disciplines. This critical review aims to enhance understanding of cutting-edge SC frameworks for ETo estimation, highlighting advancements in evolutionary models, hybrid and ensemble approaches, and optimization strategies. Recent applications of SC in various climatic zones in Bangladesh are evaluated, with the order of preference being ANFIS > Bi-LSTM > RT > DENFIS > SVR-PSOGWO > PSO–HFS due to their consistently high accuracy (RMSE and ). This review introduces a benchmark for incorporating evolutionary computation algorithms (EC) into ETo modeling. Each subsection addresses the strengths and weaknesses of known SC models, offering valuable insights. The review serves as a valuable resource for experienced water resource engineers and hydrologists, both domestically and internationally, providing comprehensive SC modeling studies for ETo forecasting. Furthermore, it provides an improved water resources monitoring and management plans.
Analysis and risk evaluation of soil microplastics in the Rohingya refugee camp area, Bangladesh: A comprehensive study
(Scopus, 2024) Hossain, Aowlad; Adham, Md. Ibrahim; Hasan, Mehedi; Ali, Mir Mohammad; Siddique, Md. Abu Bakar; Senapathi, Venkatramanan; Islam, Abu Reza Md. Towfiqul
The global concern over the pollution-induced by microplastics (MPs) has intensified due to its adverse effects on the environment, particularly in terrestrial ecosystems, where it poses potential threats to soil quality and resident species. However, there is a noticeable research gap regarding soil MPs in dumping sites, specifically within the Rohingya Refugee Camp (RRC), the world's largest humanitarian crisis located in Bangladesh. The main objective of this study is to assess soil MPs' abundance, spatial distribution, and inherent risks in the RRC. The investigation involved extracting MPs from ten soil sampling sites in Kutupalong RRC, home to Rohingya refugees who sought refuge in Bangladesh following the 2017 ethnic atrocities in Northern Rakhine State, Myanmar. Stereomicroscopy and Fourier transform infrared spectroscopy were employed for identification purposes. The concentration of MPs in the study area varied from 67 to 126 (items/kg) (dry weight), with a mean concentration of 103.80 ± 20.671 (items/kg). MPs with sizes <0.5 mm constituted the majority at 83 %, with fragments (68 %) being the prevailing shape, and transparent (63 %) as the most abundant color. Predominant polymers included polyethylene (53 %) and polypropylene (46 %). Negative correlations were observed between MP abundance and pH and moisture content (p<0.05), while a positive correlation was found between MP abundance and organic matter. PCA results suggested that human-induced inappropriate waste and air deposition are the primary sources of soil MP pollution. Contamination factor values suggested moderate pollution with MPs in the study area. According to the geo-accumulation index (Igeo), the area was classified as pollution grade II, signifying 'uncontaminated to moderately contaminated.' However, pollutant load index and potential ecological risk index indicated Hazard Level-I and Pollution Grade-I, respectively. This study illuminates the contamination scenario with MPs, underscoring concerns for eco-environmental safety and providing crucial data for future investigations into MPs in terrestrial dumping habitats.
Analysis and risk evaluation of soil microplastics in the Rohingya refugee camp area, Bangladesh: A comprehensive study
(Regional Studies in Marine Science, 2024-12) Hossain, Aowlad; Adham, Md. Ibrahim; Hasan, Mehedi; Ali, Mir Mohammad; Siddique, Md. Abu Bakar; Senapathi, Venkatramanan; Islam, Abu Reza Md. Towfiqul
The global concern over the pollution-induced by microplastics (MPs) has intensified due to its adverse effects on the environment, particularly in terrestrial ecosystems, where it poses potential threats to soil quality and resident species. However, there is a noticeable research gap regarding soil MPs in dumping sites, specifically within the Rohingya Refugee Camp (RRC), the world's largest humanitarian crisis located in Bangladesh. The main objective of this study is to assess soil MPs' abundance, spatial distribution, and inherent risks in the RRC. The investigation involved extracting MPs from ten soil sampling sites in Kutupalong RRC, home to Rohingya refugees who sought refuge in Bangladesh following the 2017 ethnic atrocities in Northern Rakhine State, Myanmar. Stereomicroscopy and Fourier transform infrared spectroscopy were employed for identification purposes. The concentration of MPs in the study area varied from 67 to 126 (items/kg) (dry weight), with a mean concentration of 103.80 ± 20.671 (items/kg). MPs with sizes <0.5 mm constituted the majority at 83 %, with fragments (68 %) being the prevailing shape, and transparent (63 %) as the most abundant color. Predominant polymers included polyethylene (53 %) and polypropylene (46 %). Negative correlations were observed between MP abundance and pH and moisture content (p<0.05), while a positive correlation was found between MP abundance and organic matter. PCA results suggested that human-induced inappropriate waste and air deposition are the primary sources of soil MP pollution. Contamination factor values suggested moderate pollution with MPs in the study area. According to the geo-accumulation index (Igeo), the area was classified as pollution grade II, signifying 'uncontaminated to moderately contaminated.' However, pollutant load index and potential ecological risk index indicated Hazard Level-I and Pollution Grade-I, respectively. This study illuminates the contamination scenario with MPs, underscoring concerns for eco-environmental safety and providing crucial data for future investigations into MPs in terrestrial dumping habitats.
Analysis and Risk Evaluation of Soil Microplastics in the Rohingya Refugee Camp Area, Bangladesh: A Comprehensive Study
(Elsevier, 2024-12-15) Hossain, Aowlad; Adham, Md. Ibrahim; Hasan, Mehedi; Ali, Mir Mohammad; Siddique, Md. Abu Bakar; Senapathi, Venkatramanan; Islam, Abu Reza Md. Towfiqul
The global concern over the pollution-induced by microplastics (MPs) has intensified due to its adverse effects on the environment, particularly in terrestrial ecosystems, where it poses potential threats to soil quality and resident species. However, there is a noticeable research gap regarding soil MPs in dumping sites, specifically within the Rohingya Refugee Camp (RRC), the world's largest humanitarian crisis located in Bangladesh. The main objective of this study is to assess soil MPs' abundance, spatial distribution, and inherent risks in the RRC. The investigation involved extracting MPs from ten soil sampling sites in Kutupalong RRC, home to Rohingya refugees who sought refuge in Bangladesh following the 2017 ethnic atrocities in Northern Rakhine State, Myanmar. Stereomicroscopy and Fourier transform infrared spectroscopy were employed for identification purposes. The concentration of MPs in the study area varied from 67 to 126 (items/kg) (dry weight), with a mean concentration of 103.80 ± 20.671 (items/kg). MPs with sizes <0.5 mm constituted the majority at 83 %, with fragments (68 %) being the prevailing shape, and transparent (63 %) as the most abundant color. Predominant polymers included polyethylene (53 %) and polypropylene (46 %). Negative correlations were observed between MP abundance and pH and moisture content (p<0.05), while a positive correlation was found between MP abundance and organic matter. PCA results suggested that human-induced inappropriate waste and air deposition are the primary sources of soil MP pollution. Contamination factor values suggested moderate pollution with MPs in the study area. According to the geo-accumulation index (Igeo), the area was classified as pollution grade II, signifying 'uncontaminated to moderately contaminated.' However, pollutant load index and potential ecological risk index indicated Hazard Level-I and Pollution Grade-I, respectively. This study illuminates the contamination scenario with MPs, underscoring concerns for eco-environmental safety and providing crucial data for future investigations into MPs in terrestrial dumping habitats.
Analysis of Self-Organizing Maps and Explainable Artificial Intelligence to Identify Hydrochemical Factors That Drive Drinking Water Quality in Haor Region
(Elsevier, 2023-12-04) Mia, Md. Yousuf; Haque, Md. Emdadul; Islam, Abu Reza Md Towfiqul; Jannat, Jannatun Nahar; Jion, Most. Mastura Munia Farjana; Islam, Md. Saiful; Siddique, Md. Abu Bakar; Idris, Abubakr M.; Senapathi, Venkatramanan; Talukdar, Swapan; Rahman, Atiqur
Water contamination undermines human survival and economic growth. Water resource protection and management require knowledge of water hydrochemistry and drinking water quality characteristics, mechanisms, and factors. Self-organizing maps (SOM) have been developed using quantization and topographic error approaches to cluster hydrochemistry datasets. The Piper diagram, saturation index (SI), and cation exchange method were used to determine the driving mechanism of hydrochemistry in both surface and groundwater, while the Gibbs diagram was used for surface water. In addition, redundancy analysis (RDA) and a generalized linear model (GLM) were used to determine the key drinking water quality parameters in the study area. Additionally, the study aimed to utilize Explainable Artificial Intelligence (XAI) techniques to gain insights into the relative importance and impact of different parameters on the entropy water quality index (EWQI). The SOM results showed that thirty neurons generated the hydrochemical properties of water and were organized into four clusters. The Piper diagram showed that the primary hydrochemical facies were HCO3−-Ca2+ (cluster 4), Cl---Na+ (all clusters), and mixed (clusters 1 and 4). Results from SI and cation exchange show that demineralization and ion exchange are the driving mechanisms of water hydrochemistry. About 45 % of the studied samples are classified as “medium quality”,” that could be suitable as drinking water with further refinement. Cl− may pose increased non-carcinogenic risk to adults, with children at double risk. Cluster 4 water is low-risk, supporting EWQI findings. The RDA and GLM observations agree in that Ca2+, Mg2+, Na+, Cl− and HCO3− all have a positive and significant effect on EWQI, with the exception of K+. TDS, EC, Na+, and Ca2+ have been identified as influencing factors based on bagging-based XAI analysis at global and local levels. The analysis also addressed the importance of SO4, HCO3, Cl, Mg2+, K+, and pH at specific locations.
Assessing metal(loid)s-Induced long-term spatiotemporal health risks in Coastal Regions, Bay of Bengal: A chemometric study
(Scopus, 2024) Aktar, Shammi; Islam, Abu Reza Md. Towfiqul; Mia, Md Yousuf; Jannat, Jannatun Nahar; Islam, Md Saiful; Masud, Md Abdullah Al; Idris, Abubakr M.; Pal, Subodh Chandra; Senapathi, Venkatramanan
Despite sporadic and irregular studies on heavy metal(loid)s health risks in water, fish, and soil in the coastal areas of the Bay of Bengal, no chemometric approaches have been applied to assess the human health risks comprehensively. This review aims to employ chemometric analysis to evaluate the long-term spatiotemporal health risks of metal(loid)s e.g., Fe, Mn, Zn, Cd, As, Cr, Pb, Cu, and Ni in coastal water, fish, and soils from 2003 to 2023. Across coastal parts, studies on metal(loid)s were distributed with 40% in the southeast, 28% in the south-central, and 32% in the southwest regions. The southeastern area exhibited the highest contamination levels, primarily due to elevated Zn content (156.8 to 147.2 mg/L for Mn in water, 15.3 to 13.2 mg/kg for Cu in fish, and 50.6 to 46.4 mg/kg for Ni in soil), except for a few sites in the south-central region. Health risks associated with the ingestion of Fe, As, and Cd (water), Ni, Cr, and Pb (fish), and Cd, Cr, and Pb (soil) were identified, with non-carcinogenic risks existing exclusively through this route. Moreover, As, Cr, and Ni pose cancer risks for adults and children via ingestion in the southeastern region. Overall non-carcinogenic risks emphasized a significantly higher risk for children compared to adults, with six, two-, and six-times higher health risks through ingestion of water, fish, and soils along the southeastern coast. The study offers innovative sustainable management strategies and remediation policies aimed at reducing metal(loid)s contamination in various environmental media along coastal Bangladesh.
Fuzzy Logic, Geostatistics, and Multiple Linear Models To Evaluate Irrigation Metrics and Their Influencing Factors in a Drought-Prone Agricultural Region
(Springer, 2023-10-01) Zihad, S.M. Rabbi Al; Islam, Abu Reza Md Towfiqul; Siddique, Md Abu Bakar; Mia, Md Yousuf; Islam, Md Saiful; Islam, Md Aminul; Bari, A.B.M. Mainul; Bodrud-Doza, Md.; Yakout, Sobhy M.; Senapathi, Venkatramanan; Chatterjee, Sumanta
The quality of water used for irrigation is one of the major threats to maintaining the long-term sustainability of agricultural practices. Although some studies have addressed the suitability of irrigation water in different parts of Bangladesh, the irrigation water quality in the drought-prone region has yet to be thoroughly studied using integrated novel approaches. This study aims to assess the suitability of irrigation water in the drought-prone agricultural region of Bangladesh using traditional irrigation metrics such as sodium percentage (NA%), magnesium adsorption ratio (MAR), Kelley's ratio (KR), sodium adsorption ratio (SAR), total hardness (TH), permeability index (PI), and soluble sodium percentage (SSP), along with novel irrigation indices such as irrigation water quality index (IWQI) and fuzzy irrigation water quality index (FIWQI). Thirty-eight water samples were taken from tube wells, river systems, streamlets, and canals in agricultural areas, then analyzed for cations and anions. The multiple linear regression model predicted that SAR (0.66), KR (0.74), and PI (0.84) were the primary important elements influencing electrical conductivity (EC). Based on the IWQI, all water samples fall into the “suitable” category for irrigation. The FIWQI suggests that 75% of the groundwater and 100% of the surface water samples are excellent for irrigation. The semivariogram model indicates that most irrigation metrics have moderate to low spatial dependence, suggesting strong agricultural and rural influence. Redundancy analysis shows that Na+, Ca2+, Cl−, K+, and HCO3− in water increase with decreasing temperature. Surface water and some groundwater in the southwestern and southeastern parts are suitable for irrigation. The northern and central parts are less suitable for agriculture because of elevated K+ and Mg2+ levels. This study determines irrigation metrics for regional water management and pinpoints suitable areas in the drought-prone region, which provides a comprehensive understanding of sustainable water management and actionable steps for stakeholders and decision-makers.
Heavy metal and mineral analysis of cultivated seaweeds from Cox’s Bazar Coast, Bay of Bengal, Bangladesh: a human health risk implication
(Discover Oceans, 2024-06-24) Bhuyan, Md. Simul; Kunda, Mrityunjoy; Bakar, Muhammad Abu; Senapathi, Venkatramanan; Husain, Sk. Abid; Chowdhury, Enam; Ali, Mir Mohammad; Pandit, Debasish
Seaweeds are grown for their use in food and other sectors, however heavy metals (HMs) contamination raises serious issues for the environment and public health. This study focuses on seaweed samples (Hypnea musciformes and Gracilaria lemaneiformis) collected from the Rezu Khal seaweed culture site, Cox’s Bazar coast, Bangladesh. HMs and minerals were determined using Atomic Absorption Spectrophotometry (AAS). Among the elements examined, H. musciformes displayed the highest mean concentrations of minerals and HMs, including Magnesium (Mg) (8663.00 ±2302.06 mg/kg), Copper (Cu) (10.59±1.61 mg/kg), Iron (Fe) (7566.29±2842.47 mg/kg), Manganese (Mn) (9.93±2.88 mg/kg), Zinc (Zn) (29.54±7.51 mg/kg), and Nickel (Ni) (11.77±2.63 mg/kg). Conversely, G. lemaneiformis exhibited the highest levels of Calcium (Ca) (798.14±143.40 mg/kg), Lead (Pb) (3.91±1.74 mg/kg), and Chromium (Cr) (0.59±0.30 mg/kg). Specifically, Mg was prominently abundant in H. musciformes, while Cawas more prevalent in G. lemaneiformis. Both seaweed types contained Pb and Cr. None of the elements was significantly different between the species (p <0.05). The consumers are not exposed to any carcinogenic or non-carcinogenic risks related to these concentrations, according to the evaluation of carcinogenic and non-carcinogenic risks.
Identifying Factors Affecting Irrigation Metrics in the Haor Basin Using Integrated Shannon’s Entropy, Fuzzy Logic and Automatic Linear Model
(Elsevier, 2023-06-01) Mia, Md Yousuf; Islam, Abu Reza Md Towfiqul; Jannat, Jannatun Nahar; Jion, Most Mastura Munia Farjana; Sarker, Aniruddha; Tokatli, Cem; Siddique, Md Abu Bakar; Ibrahim, Sobhy M.; Senapathi, Venkatramanan
The sustainability of agricultural practices is seriously threatened by the quality of water used for irrigation. This paper aims to evaluate the suitability of irrigation water and identify the region suitable for agricultural use in the Haor basin of Bangladesh using conventional irrigation indices such as sodium adsorption ratio (SAR), percent sodium (Na%), magnesium hazard ratio (MHR), permeability index (PI), and Kelly's ratio (KR), as well as novel irrigation indices such as, Shannon's entropy index for irrigation water quality (EWQ) and fuzzy logic index for irrigation water quality (FIWQI). The main influences of groundwater and surface water parameters on irrigation indices were predicted using automatic linear modeling (ALM). Forty water samples were collected from shallow tube wells, rivers, canals, ponds, and drainage systems within agricultural land sampled and analyzed for cations and anions. SAR and KR show that 52.5% and 60% of the samples exceeded the allowable level, respectively, indicating that they were unsuitable for irrigation. According to EWQI, about 55% of the analyzed samples were of good quality, while 45% were of medium quality. ALM predicted that KR (0.98), Na% (0.87), and MHR (0.14) were the main significant factors affecting SAR and KR. ALM shows that elevated sodium, magnesium, and calcium are the most important factors affecting irrigation water suitability. The EWQI and FIWQI integrated models showed that water from nearly 30% of the sampling sites would need treatment before use. A new suitability map created by overlaying all parameters showed that surface water and some groundwater in the western and southwestern portions are suitable for agriculture. The north-central part is unsuitable for irrigation due to excessive sodium and magnesium levels. This paper will highlight the irrigation pattern for regional water resource use, identify new suitable regions, and improve sustainable agricultural practices in the Haor basin.
Impact of climate change on vector-borne diseases: Exploring hotspots, recent trends and future outlooks in Bangladesh
(2024-11-24) Jibon, Md. Jannatul Naeem; Prodhan Ruku, S.M. Ridwana; Towfiqul Islam, Abu Reza Md; Khan, Md. Nuruzzaman; Mallick, Javed; Mainul Bari, A.B.M.; Senapathi, Venkatramanan
Climate change is a significant risk multiplier and profoundly influences the transmission dynamics, geographical distribution, and resurgence of vector-borne diseases (VBDs). Bangladesh has a noticeable rise in VBDs attributed to climate change. Despite the severity of this issue, the interconnections between climate change and VBDs in Bangladesh have yet to be thoroughly explored. To address this research gap, our review meticulously examined existing literature on the relationship between climate change and VBDs in Bangladesh. Using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) approach, we identified 3849 records from SCOPUS, Web of Science, and Google Scholar databases. Ultimately, 22 research articles meeting specific criteria were included. We identified that the literature on the subject matter of this study is non-contemporaneous, with 68% of studies investing datasets before 2014, despite studies on climate change and dengue nexus having increased recently. We pinpointed Dhaka and Chittagong Hill Tracts as the dengue and malaria research hotspots, respectively. We highlighted that the 2023 dengue outbreak illustrates a possible shift in dengue-endemic areas in Bangladesh. Moreover, dengue cases surged by 317% in 2023 compared to 2019 records, with a corresponding 607% increase in mortality compared to 2022. A weak connection was observed between dengue incidents and climate drivers, including the El Niño Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD). However, no compelling evidence supported an association between malaria cases, and Sea Surface Temperature (SST) in the Bay of Bengal, along with the NINO3 phenomenon. We observed minimal microclimatic and non-climatic data inclusion in selected studies. Our review holds implications for policymakers, urging the prioritization of mitigation measures such as year-round surveillance and early warning systems. Ultimately, it calls for resource allocation to empower researchers in advancing the understanding of VBD dynamics amidst changing climates.
Impact of Climate Change on Vector-borne Diseases: Exploring Hotspots, Recent Trends and Future Outlooks in Bangladesh
(Elsevier, 2024-11-15) Jibon, Md. Jannatul Naeem; Ruku, S.M. Ridwana Prodhan; Islam, Abu Reza Md Towfiqul; Khan, Md. Nuruzzaman; Mallick, Javed; Bari, A.B.M. Mainul; Senapathi, Venkatramanan
Climate change is a significant risk multiplier and profoundly influences the transmission dynamics, geographical distribution, and resurgence of vector-borne diseases (VBDs). Bangladesh has a noticeable rise in VBDs attributed to climate change. Despite the severity of this issue, the interconnections between climate change and VBDs in Bangladesh have yet to be thoroughly explored. To address this research gap, our review meticulously examined existing literature on the relationship between climate change and VBDs in Bangladesh. Using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) approach, we identified 3849 records from SCOPUS, Web of Science, and Google Scholar databases. Ultimately, 22 research articles meeting specific criteria were included. We identified that the literature on the subject matter of this study is non-contemporaneous, with 68% of studies investing datasets before 2014, despite studies on climate change and dengue nexus having increased recently. We pinpointed Dhaka and Chittagong Hill Tracts as the dengue and malaria research hotspots, respectively. We highlighted that the 2023 dengue outbreak illustrates a possible shift in dengue-endemic areas in Bangladesh. Moreover, dengue cases surged by 317% in 2023 compared to 2019 records, with a corresponding 607% increase in mortality compared to 2022. A weak connection was observed between dengue incidents and climate drivers, including the El Niño Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD). However, no compelling evidence supported an association between malaria cases, and Sea Surface Temperature (SST) in the Bay of Bengal, along with the NINO3 phenomenon. We observed minimal microclimatic and non-climatic data inclusion in selected studies. Our review holds implications for policymakers, urging the prioritization of mitigation measures such as year-round surveillance and early warning systems. Ultimately, it calls for resource allocation to empower researchers in advancing the understanding of VBD dynamics amidst changing climates.
Managing the Invisible Threat of Microplastics in Marine Ecosystems: Lessons From Coast of the Bay of Bengal
(IEEE, 2023-09-01) Mubin, Al-Nure; Arefin, Shahoriar; Mia, Md. Sonir; Islam, Abu Reza Md. Towfiqul; Bari, A.B.M. Mainul; Islam, Md. Saiful; Ali, Mir Mohammad; Siddique, Md. Abu Bakar; Rahman, M. Safiur; Senapathi, Venkatramanan; Idris, Abubakr M.; Malafaia, Guilherme
Invisible microplastics (MP) have become a significant problem worldwide in recent years. Although many studies have highlighted the sources, effects, and fate of MPs pollution on various ecosystems in developed countries, there is limited information on MPs in the marine ecosystem along the northeastern coast of the Bay of Bengal (BoB). Coastal ecosystems along the BoB coasts are critical to a biodiverse ecology that supports human survival and resource extraction. However, the multi-environmental hotspots, ecotoxicity effects, transport mechanisms, fates, and intervention measures to control MP pollution initiatives along the BoB coasts have received little attention. Therefore, this review aims to highlight the multi-environmental hotspots, ecotoxicity effects, sources, fates, and intervention measures of MP in the northeastern BoB to understand how MP spreads in the nearshore marine ecosystem. This study critically evaluates the hotspots and ecotoxic effects of pollution from MP on the coastal multi-environment, e.g., soil, sediment, salt, water, and fish, as well as current intervention measures and additional mitigation recommendations. This study identified the northeastern part of the BoB as a hotspot for MP. In addition, the transport mechanisms and fate of MP in different environmental compartments are highlighted, as are research gaps and potential future research areas. Research on the ecotoxic effects of MP on BoB marine ecosystems must be a top priority, given the increasing use of plastics and the presence of significant marine products worldwide. The knowledge gained from this study would inform decision-makers and stakeholders in a way that could reduce the impact of the legacy of micro- and nanoplastics in the area. This study also proposes structural and non-structural measures to mitigate the effects of MPs and promote sustainable management.
Microplastics contamination through a mighty estuarine island: Distribution, influencing factors, and risk assessment
(2024-12-20) Arefin, Shahoriar; Md. Towfiqul Islam, Abu Reza; Hasan, Mehedi; Mubin, Al-Nure; Alinur Rahman, Md.; Ali, Mir Mohammad; Siddique, Md Abu Bakar; Abdo, Hazem Ghassan; Idris, Abubakr M.; Pal, Subodh chandra; Malafaia, Guilherme; Senapathi, Venkatramanan
The global concern over microplastic (MP) contamination in diverse ecosystems is well-established, yet Nijhum Dwip Island (NDI), known for its ecological diversity, has not undergone a comprehensive study addressing the extent of MP pollution. This research aims to evaluate the spatial distribution, influencing factors, and ecological risks of MPs in both sediment and surface water surrounding NDI, situated in the Northern Bay of Bengal. A meticulous collection of 40 sediment and 40 tidal water samples from various sites facilitated a detailed analysis. The mean abundance of MPs in sediment was 138.39 ± 34.15 pieces/kg, while in water, it was 72.83 ± 30.76 pieces/m³. Various shapes observed on NDI included films, fragments, fibers, and foams, with fragments dominating in sediment (64.05 %) and water (61.51 %). Analysis of FTIR spectra identified two primary polymer types, namely polyethylene (PE) at 57 % and polypropylene (PP) at 40 %. The results indicated elevated pollution levels on NDI, with sediment and water pollution load index measuring 1.32 and 2.01, respectively, signifying significant MP contamination in both compartments. Given the island's rare biodiversity, the vicinity of wastewater sewages, anthropogenic activities, and atmospheric deposition, could be behind MP contamination in water and sediments. No strong correlation between MP and physiochemical properties in water and PCA biplots showed their similar distribution, whereas MP abundances in sediment were significantly correlated with pH and organic matter (p<0.05), signifying a pivotal role in transporting MPs in the aquatic environment. Two canonical variables were identified as important by canonical correlation analysis, demonstrating the interdependence of MP contamination at the sample sites. This research contributes to better insights into the occurrence of MP in the rare islands, which are ecosystems that have been hardly examined for this type of pollution, and it can report sustainable interventions to lessen MP inputs to the Bay of Bengal.
Microplastics contamination through a mighty estuarine island: Distribution, influencing factors, and risk assessment
(Regional Studies in Marine Science, Elsevier, 2024-12-20) Arefin, Shahoriar; Islam, Abu Reza Md. Towfiqul; Hasan, Mehedi; Mubin, Al-Nure; Rahman, Md. Alinur; Ali, Mir Mohammad; Siddique, Md Abu Bakar; Abdo, Hazem Ghassan; Idris, Abubakr M.; Pal, Subodh chandra; Malafaia, Guilherme; Senapathi, Venkatramanan
The global concern over microplastic (MP) contamination in diverse ecosystems is well-established, yet Nijhum Dwip Island (NDI), known for its ecological diversity, has not undergone a comprehensive study addressing the extent of MP pollution. This research aims to evaluate the spatial distribution, influencing factors, and ecological risks of MPs in both sediment and surface water surrounding NDI, situated in the Northern Bay of Bengal. A meticulous collection of 40 sediment and 40 tidal water samples from various sites facilitated a detailed analysis. The mean abundance of MPs in sediment was 138.39 ± 34.15 pieces/kg, while in water, it was 72.83 ± 30.76 pieces/m³. Various shapes observed on NDI included films, fragments, fibers, and foams, with fragments dominating in sediment (64.05 %) and water (61.51 %). Analysis of FTIR spectra identified two primary polymer types, namely polyethylene (PE) at 57 % and polypropylene (PP) at 40 %. The results indicated elevated pollution levels on NDI, with sediment and water pollution load index measuring 1.32 and 2.01, respectively, signifying significant MP contamination in both compartments. Given the island's rare biodiversity, the vicinity of wastewater sewages, anthropogenic activities, and atmospheric deposition, could be behind MP contamination in water and sediments. No strong correlation between MP and physiochemical properties in water and PCA biplots showed their similar distribution, whereas MP abundances in sediment were significantly correlated with pH and organic matter (p<0.05), signifying a pivotal role in transporting MPs in the aquatic environment. Two canonical variables were identified as important by canonical correlation analysis, demonstrating the interdependence of MP contamination at the sample sites. This research contributes to better insights into the occurrence of MP in the rare islands, which are ecosystems that have been hardly examined for this type of pollution, and it can report sustainable interventions to lessen MP inputs to the Bay of Bengal.
Microplastics in sediment and surface water from an island ecosystem in Bay of Bengal
(2024-01-15) Mia, Md. Sonir; Md. Towfiqul Islam, Abu Reza; Ali, Mir Mohammad; Siddique, Md. Abu Bakar; Pal, Subodh Chandra; Idris, Abubakr M.; Senapathi, Venkatramanan
Microplastics (MPs) have garnered global attention as emerging pollutants in aquatic and terrestrial ecosystems. Despite their significance, studies on MP pollution have overlooked a biodiverse island ecosystem in the northeast Bay of Bengal. Hence, the current study is a pioneering effort to delve into this issue with the island. This research embodies the first comprehensive report exploring the presence of MP pollution in sediment and surface water and their influencing factors along Sandwip island in the northeast Bay of Bengal. The average MP concentration was 305 ± 37.16 (items/kg) in sediment and 106.14 ± 22.57 (items/m3) in surface water. Fragments emerged as the predominant type in sediment (78.77%) and surface water (54.64%) samples. Fourier Transform Infrared Spectroscopy identified three plastic polymers, the most abundant being polyethylene (56%) and polypropylene (41%). Anthropogenic activities, particularly fishing practices, improper waste disposal, and inadequate waste management strategies, were pinpointed as potential sources of MP contamination on the island. MP concentrations in water and sediment correlated positively with pH and organic matter (p < 0.000), indicating important factors influencing MP distribution. The spatial distribution and hotspots of MPs followed significant human routes. By shedding light on the extent of MPs' presence and their potential sources, this study contributes essential insights that can inform effective environmental management strategies for the island's future well-being.
Predicting Groundwater Phosphate Levels in Coastal Multi-aquifers A Geostatistical and Data-driven Approach
(Elsevier, 2024-11-15) Abdullah-Al Mamun, Md.; Islam, Abu Reza Md Towfiqul; Aktar, Mst. Nazneen; Uddin, Md Nashir; Islam, Md. Saiful; Pal, Subodh Chandra; Islam, Aznarul; Bari, A.B.M. Mainul; Idris, Abubakr M.; Senapathi, Venkatramanan
Even if you want to make a profit from cryptocurrency, you are worried that you will lose money, and it is difficult to afford it. There are a vast number of papers that study such unpredictable price fluctuations of cryptocurrency. Currently, it is mainstream to use learning deep to predict the price of cryptocurrency. The goal of this research is to predict the price of cryptocurrency over the long-term using deep learning. The algorithms used are LSTM, GRU, and Bi-LSTM. The targeted cryptocurrencies are Bitcoin, Ethereum, Litecoin, and Cardano. Finally, we will compare it with previous research and verify the performance of our model.
Predicting Groundwater Phosphate Levels in Coastal Multi-aquifers: A Geostatistical and Data-driven Approach
(Elsevier, 2024-11-25) Abdullah-Al Mamun, Md.; Islam, Abu Reza Md Towfiqul; Aktar, Mst.Nazneen; Uddin, Md Nashir; Islam, Md. Saiful; Pal, Subodh Chandra; Islam, Aznarul; Bari, A.B.M. Mainul; Idris, Abubakr M.; Senapathi, Venkatramanan
The groundwater (GW) resource plays a central role in securing water supply in the coastal region of Bangladesh and therefore the future sustainability of this valuable resource is crucial for the area. However, there is limited research on the driving factors and prediction of phosphate concentration in groundwater. In this work, geostatistical modeling, self-organizing maps (SOM) and data-driven algorithms were combined to determine the driving factors and predict GW phosphate content in coastal multi-aquifers in southern Bangladesh. The SOM analysis identified three distinct spatial patterns: K+single bondNa+single bondpH, Ca2+single bondMg2+single bondNO₃−, and HCO₃−single bondSO₄2−single bondPO43−single bondF−. Four data-driven algorithms, including CatBoost, Gradient Boosting Machine (GBM), Long Short-Term Memory (LSTM), and Support Vector Regression (SVR) were used to predict phosphate concentration in GW using 380 samples and 15 prediction parameters. Forecasting accuracy was evaluated using RMSE, R2, RAE, CC, and MAE. Phosphate dissolution and saltwater intrusion, along with phosphorus fertilizers, increase PO43− content in GW. Using input parameters selected by multicollinearity and SOM, the CatBoost model showed exceptional performance in both training (RMSE = 0.002, MAE = 0.001, R2 = 0.999, RAE = 0.057, CC = 1.00) and testing (RMSE = 0.001, MAE = 0.002, R2 = 0.989, RAE = 0.057, CC = 0.998). Na+, K+, and Mg2+ significantly influenced prediction accuracy. The uncertainty study revealed a low standard error for the CatBoost model, indicating robustness and consistency. Semi-variogram models confirmed that the most influential attributes showed weak dependence, suggesting that agricultural runoff increases the heterogeneity of PO43− distribution in GW. These findings are crucial for developing conservation and strategic plans for sustainable utilization of coastal GW resources.
The path of microplastics through the rare biodiversity estuary region of the northern Bay of Bengal
(Scopus, 2024-01) Mubin, Al-Nure; Islam, Abu Reza Md. Towfiqul; Hasan, Mehedi; Islam, Md. Saiful; Ali, Mir Mohammad; Siddique, Md. Abu Bakar; Alam, Md. Sha; Rakib, Md. Refat Jahan; Islam, Muhammad Saiful; Momtaz, Nasima; Senapathi, Venkatramanan; Idris, Abubakr M.; Malafaia, Guilherme
Due to its harmful effects on ecosystems and human health, microplastic (MP) pollution has become a significant environmental problem on a global scale. Although MPs' pollution path and toxic effects on marine habitats have been examined worldwide, the studies are limited to the rare biodiversity estuary region of Hatiya Island from the northern Bay of Bengal. This study aimed to investigate the MP pollution path and its influencing factors in estuarine sediments and water in rare biodiversity Hatiya Island in the northern Bay of Bengal. Sixty water and sediment samples were collected from 10 sampling sites on the Island and analyzed for MPs. The abundance of MPs in sediment ranged from 67 to 143 pieces/kg, while the abundance in water ranged from 24.34 to 59 pieces/m3. The average concentrations of MPs in sediment and water were 110.90 ± 20.62 pieces/kg and 38.77 ± 10.09 pieces/m3, respectively. Most identified MPs from sediment samples were transparent (51%), while about 54.1% of the identified MPs from water samples were colored. The fragment was the most common form of MP in both compartments, with a value of 64.6% in sediment samples and 60.6% in water samples. In sediment and water samples, almost 74% and 80% of MP were <0.5 mm, respectively. Polypropylene (PP) was the most abundant polymer type, accounting for 51% of all identified polymers. The contamination factor, pollution load index, polymer risk score, and pollution risk score values indicated that the study area was moderately polluted with MPs. The spatial distribution patterns and hotspots of MPs echoed profound human pathways. Based on the results, sustainable management strategies and intervention measures were proposed to reduce the pollution level in the ecologically diverse area. This study provides important insights into evaluating estuary ecosystem susceptibility and mitigation policies against persistent MP issues.
The Path of Microplastics Through the Rare Biodiversity Estuary Region of the Northern Bay of Bengal
(Elsevier, 2024-01-20) Mubin, Al-Nure; Islam, Abu Reza Md. Towfiqul; Hasan, Mehedi; Islam, Md. Saiful; Ali, Mir Mohammad; Siddique, Md. Abu Bakar; Alam, Md. Sha; Rakib, Md. Refat Jahan; Islam, Muhammad Saiful; Momtaz, Nasima; Senapathi, Venkatramanan; Idris, Abubakr M.; Malafaia, Guilherme
Due to its harmful effects on ecosystems and human health, microplastic (MP) pollution has become a significant environmental problem on a global scale. Although MPs' pollution path and toxic effects on marine habitats have been examined worldwide, the studies are limited to the rare biodiversity estuary region of Hatiya Island from the northern Bay of Bengal. This study aimed to investigate the MP pollution path and its influencing factors in estuarine sediments and water in rare biodiversity Hatiya Island in the northern Bay of Bengal. Sixty water and sediment samples were collected from 10 sampling sites on the Island and analyzed for MPs. The abundance of MPs in sediment ranged from 67 to 143 pieces/kg, while the abundance in water ranged from 24.34 to 59 pieces/m3. The average concentrations of MPs in sediment and water were 110.90 ± 20.62 pieces/kg and 38.77 ± 10.09 pieces/m3, respectively. Most identified MPs from sediment samples were transparent (51%), while about 54.1% of the identified MPs from water samples were colored. The fragment was the most common form of MP in both compartments, with a value of 64.6% in sediment samples and 60.6% in water samples. In sediment and water samples, almost 74% and 80% of MP were <0.5 mm, respectively. Polypropylene (PP) was the most abundant polymer type, accounting for 51% of all identified polymers. The contamination factor, pollution load index, polymer risk score, and pollution risk score values indicated that the study area was moderately polluted with MPs. The spatial distribution patterns and hotspots of MPs echoed profound human pathways. Based on the results, sustainable management strategies and intervention measures were proposed to reduce the pollution level in the ecologically diverse area. This study provides important insights into evaluating estuary ecosystem susceptibility and mitigation policies against persistent MP issues.