Browsing by Author "Islam, Abu Reza Md. Towfiqul"

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A review of microplastic threat mitigation in Asian lentic environments
(Scopus, 2024-01-31) Sadia, Moriom Rahman; Hasan, Mehedi; Islam, Abu Reza Md. Towfiqul; Jion, Most. Mastura Munia Farjana; Masud, Md Abdullah Al; Rahman, Md. Naimur
Microplastic (MP) pollution has evolved into a significant worldwide environmental concern due to its widespread sources, enduring presence, and adverse effects on lentic ecosystems and human well-being. The growing awareness of the hidden threat posed by MPs in lentic ecosystems has emphasized the need for more in-depth research. Unlike marine environments, there remain unanswered questions about MP hotspots, ecotoxic effects, transport mechanisms, and fragmentation in lentic ecosystems. The introduction of MPs represents a novel threat to long-term environmental health, posing unresolved challenges for sustainable management. While MP pollution in lentic ecosystems has garnered global attention due to its ecotoxicity, our understanding of MP hotspots in lakes from an Asian perspective remains limited. Hence, the aim of this review is to provide a comprehensive analysis of MP hotspots, morphological attributes, ecotoxic impacts, sustainable solutions, and future challenges across Asia. The review summarizes the methods employed in previous studies and the techniques for sampling and analyzing microplastics in lake water and sediment. Notably, most studies concerning lake microplastics tend to follow the order of China > India > Pakistan > Nepal > Turkey > Bangladesh. Additionally, this review critically addresses the analysis of microplastics in lake water and sediment, shedding light on the prevalent net-based sampling methods. Ultimately, this study emphasizes the existing research gaps and suggests new research directions, taking into account recent advancements in the study of microplastics in lentic environments. In conclusion, the review advocates for sustainable interventions to mitigate MP pollution in the future, highlighting the presence of MPs in Asian lakes, water, and sediment, and their potential ecotoxicological repercussions on both the environment and human health.
A systematic review of cyclonic disaster: Damage-loss, consequences, adaptation strategies, and future scopes
(Scopus, 2024-06-30) Islam, Abu Reza Md. Towfiqul; Siddik, Md. Abubakkor
Tropical cyclones have direct and indirect repercussions in many coastal areas worldwide. In coastal regions, several studies have identified the driving factors of cyclonic hazards and their associated impacts. However, previous studies have focused little on cyclone-induced damage and loss, consequences, and adaptation strategies. As a result, it is critical to explore the global focus areas of cyclone-related studies. This review systematically examined cyclone-induced damage and loss, its consequences, adaptation strategies in coastal regions, and associated research gaps. Results revealed eight main types of cyclone-induced damages and losses. About 46 % of studies focused on vegetation damages, followed by water and sanitation (11 %), crop damages (8 %), income or business losses (8 %), health and injuries (8 %), land use and land cover changes (8 %), infrastructural damages (5 %), and mixed damages and losses (5 %). These damages and losses led to further consequences, including disruption of biocenoses, fish death because defoliated leaves carried carbon into the water, changes in forest structure and composition, loss of timber plantation confidence, hampering the steady supply of safe drinking water, raising drinking water costs, unsanitary circumstances, an increase in infectious diseases, a decrease in protein consumption, and business and supply chain interruptions. Approximately 35 % of the studies addressed one or more of the thirteen adaptation strategies identified in this review. Most of these studies documented the use of natural regeneration and tree planting as responses to vegetation damage and water purification and the distribution of emergency-safe water in response to water and sanitation damage. The findings have led to a proposal for an adaptation framework for cyclone-induced damage and loss. This review recommended investigating cyclone-induced land use and land cover change, damage to vegetation functional traits and patterns, health and injuries, service networks, and infrastructural damages.
A Systematic Review of Cyclonic Disaster: Damage-loss, Consequences, Adaptation Strategies, and Future Scopes
(Elsevier, 2024-07-20) Siddik, Md. Abubakkor; Islam, Abu Reza Md. Towfiqul
Tropical cyclones have direct and indirect repercussions in many coastal areas worldwide. In coastal regions, several studies have identified the driving factors of cyclonic hazards and their associated impacts. However, previous studies have focused little on cyclone-induced damage and loss, consequences, and adaptation strategies. As a result, it is critical to explore the global focus areas of cyclone-related studies. This review systematically examined cyclone-induced damage and loss, its consequences, adaptation strategies in coastal regions, and associated research gaps. Results revealed eight main types of cyclone-induced damages and losses. About 46 % of studies focused on vegetation damages, followed by water and sanitation (11 %), crop damages (8 %), income or business losses (8 %), health and injuries (8 %), land use and land cover changes (8 %), infrastructural damages (5 %), and mixed damages and losses (5 %). These damages and losses led to further consequences, including disruption of biocenoses, fish death because defoliated leaves carried carbon into the water, changes in forest structure and composition, loss of timber plantation confidence, hampering the steady supply of safe drinking water, raising drinking water costs, unsanitary circumstances, an increase in infectious diseases, a decrease in protein consumption, and business and supply chain interruptions. Approximately 35 % of the studies addressed one or more of the thirteen adaptation strategies identified in this review. Most of these studies documented the use of natural regeneration and tree planting as responses to vegetation damage and water purification and the distribution of emergency-safe water in response to water and sanitation damage. The findings have led to a proposal for an adaptation framework for cyclone-induced damage and loss. This review recommended investigating cyclone-induced land use and land cover change, damage to vegetation functional traits and patterns, health and injuries, service networks, and infrastructural damages.
A systematic review of the nexus between climate change and social media: present status, trends, and future challenges
(Scopus, 2024-10-14) Sultana, Bebe Chand; Prodhan, Md. Tabiur Rahman; Alam, Edris; Sohel, Md. Salman; Bari, A. B. M. Mainul; Pal, Subodh Chandra; Islam, Abu Reza Md. Towfiqul; Islam, Md. Kamrul
: Social media and climate change are some of the most controversial issues of the 21st century. Despite numerous studies, our understanding of current social media trends, popular hot topics, and future challenges related to climate change remains significantly limited. This research presents a systematic review of climate change and social media for the first time. Review the studies published between 2009 and 2022 in places like Google Scholar, Science Direct, Web-of-Science, Scopus, ResearchGate, and others. For this systematic review, we found 1,057 articles. Forty-five articles were the most relevant according to our goals and study design, which followed the PRISMA framework. The results of this review demonstrate that Twitter is the most popular platform. Every year, we identify rising trends in the number of publications. Past studies often focused on just one social media site, like Twitter (n = 26) or Facebook (n = 5). Although most studies focus on the United States, the study area is primarily “all over the world.” This study offers a theoretical framework by examining the relationship between social media platforms and the discourse surrounding climate change. It looked into how social media trends influence public perception, raise awareness, and spur action on climate change. In practical terms, the study focuses on important and trending topics like nonbelievers and climate change. The contribution consists of synthesizing the body of research, providing insights into the state of the digital world, and suggesting future lines of inquiry for the field of social media and climate change studies. We highlighted the studies’ quality assessment result of “moderate quality.” This systematic review provides information about how climate change is now portrayed on social media and lays the groundwork for further study in this area.
A systematic review of the nexus between climate change and social media: present status, trends, and future challenges
(Scopus, 2024-10-14) Sultana, Bebe Chand; Prodhan, Md. Tabiur Rahman; Alam, Edris; Sohel, Md. Salman; Bari, A. B. M. Mainul; Pal, Subodh Chandra; Islam, Md. Kamrul; Islam, Abu Reza Md. Towfiqul
Social media and climate change are some of the most controversial issues of the 21st century. Despite numerous studies, our understanding of current social media trends, popular hot topics, and future challenges related to climate change remains significantly limited. This research presents a systematic review of climate change and social media for the first time. Review the studies published between 2009 and 2022 in places like Google Scholar, Science Direct, Web-of-Science, Scopus, ResearchGate, and others. For this systematic review, we found 1,057 articles. Forty-five articles were the most relevant according to our goals and study design, which followed the PRISMA framework. The results of this review demonstrate that Twitter is the most popular platform. Every year, we identify rising trends in the number of publications. Past studies often focused on just one social media site, like Twitter (n = 26) or Facebook (n = 5). Although most studies focus on the United States, the study area is primarily “all over the world.” This study offers a theoretical framework by examining the relationship between social media platforms and the discourse surrounding climate change. It looked into how social media trends influence public perception, raise awareness, and spur action on climate change. In practical terms, the study focuses on important and trending topics like nonbelievers and climate change. The contribution consists of synthesizing the body of research, providing insights into the state of the digital world, and suggesting future lines of inquiry for the field of social media and climate change studies. We highlighted the studies’ quality assessment result of “moderate quality.” This systematic review provides information about how climate change is now portrayed on social media and lays the groundwork for further study in this area.
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.
Anthropogenic Drivers Induced Desertification Under Changing Climate
(Elsevier, 2023-12-17) Pal, Subodh Chandra; Chatterjee, Uday; Chakrabortty, Rabin; Roy, Paramita; Chowdhuri, Indrajit; Saha, Asish; Islam, Abu Reza Md. Towfiqul; Alam, Edris; Islam, Md Kamrul
A study of the extended desertification due to anthropogenic causes under climate change (CC) associated with its impact is presented here. Desertification, the main environmental issue, severely impacts agricultural output, causing poverty and economic instability in a nation like India. The regional distribution of desertification was determined using the RF and MaxEnt models. The western, central, and southern portions of the nation are very high, high, and moderately susceptible to desertification, respectively, according to the RF model. The MaxEnt model indicates that the western, central, and southern parts of the country exhibit a significant susceptibility to desertification, with the eastern parts also showing a moderate level of vulnerability. The remaining portion of this region, mainly in the north, east, and northeast, is particularly resistant to desertification. The outcome demonstrated that the country's desertification process had expanded from the west to the south. However, there are some spatial differences associated with the mentioned part of the country. This relevant information is crucial for decision maker of this country to take suitable remedies in regard to the reduction of the intensity of desertification.
Application of Bagging and Boosting Ensemble Machine Learning Techniques for Groundwater Potential Mapping in a Drought-prone Agriculture Region of Eastern India
(Springer, 2024-09-02) Halder, Krishnagopal; Srivastava, Amit Kumar; Ghosh, Anitabha; Nabik, Ranajit; Pan, Subrata; Chatterjee, Uday; Bisai, Dipak; Pal, Subodh Chandra; Zeng, Wenzhi; Ewert, Frank; Gaiser, Thomas; Pande, Chaitanya Baliram; Islam, Abu Reza Md. Towfiqul; Alam, Edris; Islam, Md Kamrul
Groundwater is a primary source of drinking water for billions worldwide. It plays a crucial role in irrigation, domestic, and industrial uses, and significantly contributes to drought resilience in various regions. However, excessive groundwater discharge has left many areas vulnerable to potable water shortages. Therefore, assessing groundwater potential zones (GWPZ) is essential for implementing sustainable management practices to ensure the availability of groundwater for present and future generations. This study aims to delineate areas with high groundwater potential in the Bankura district of West Bengal using four machine learning methods: Random Forest (RF), Adaptive Boosting (AdaBoost), Extreme Gradient Boosting (XGBoost), and Voting Ensemble (VE). The models used 161 data points, comprising 70% of the training dataset, to identify significant correlations between the presence and absence of groundwater in the region. Among the methods, Random Forest (RF) and Extreme Gradient Boosting (XGBoost) proved to be the most effective in mapping groundwater potential, suggesting their applicability in other regions with similar hydrogeological conditions. The performance metrics for RF are very good with a precision of 0.919, recall of 0.971, F1-score of 0.944, and accuracy of 0.943. This indicates a strong capability to accurately predict groundwater zones with minimal false positives and negatives. Adaptive Boosting (AdaBoost) demonstrated comparable performance across all metrics (precision: 0.919, recall: 0.971, F1-score: 0.944, accuracy: 0.943), highlighting its effectiveness in predicting groundwater potential areas accurately; whereas, Extreme Gradient Boosting (XGBoost) outperformed the other models slightly, with higher values in all metrics: precision (0.944), recall (0.971), F1-score (0.958), and accuracy (0.957), suggesting a more refined model performance. The Voting Ensemble (VE) approach also showed enhanced performance, mirroring XGBoost's metrics (precision: 0.944, recall: 0.971, F1-score: 0.958, accuracy: 0.957). This indicates that combining the strengths of individual models leads to better predictions. The groundwater potentiality zoning across the Bankura district varied significantly, with areas of very low potentiality accounting for 41.81% and very high potentiality at 24.35%. The uncertainty in predictions ranged from 0.0 to 0.75 across the study area, reflecting the variability in groundwater availability and the need for targeted management strategies. In summary, this study highlights the critical need for assessing and managing groundwater resources effectively using advanced machine learning techniques. The findings provide a foundation for better groundwater management practices, ensuring sustainable use and conservation in Bankura district and beyond.
Application of Novel Binary Optimized Machine Learning Models for Monthly Streamflow Prediction
(Springer, 2023-04-08) Adnan, Rana Muhammad; Dai, Hong‑Liang; Mostafa, Reham R.; Islam, Abu Reza Md. Towfiqul; Kisi, Ozgur; Elbeltagi, Ahmed; Kermani, Mohammad Zounemat
Accurate measurements of available water resources play a key role in achieving a sustainable environment of a society. Precise river flow estimation is an essential task for optimal use of hydropower generation, flood forecasting, and best utilization of water resources in river engineering. The current paper presents the development and verification of the prediction abilities of new hybrid extreme learning machine (ELM)-based models coupling with metaheuristic methods, e.g., Particle swarm optimization (PSO), Mayfly optimization algorithm (MOA), Grey wolf optimization (GWO), and simulated annealing (SA) for monthly streamflow prediction. Prediction precision of standalone ELM model was compared with two-phase optimized state-of-the-arts models, e.g., ELM–PSO, ELM–MOA, ELM–PSOGWO, and ELM–SAMOA, respectively. Hydro-meteorological data acquired from Gorai and Padma Hardinge Bridge stations at Padma River Basin, northwestern Bangladesh, were utilized as inputs in this study to employ models in the form of seven different input combinations. The model’s performances are appraised using Nash–Sutcliffe efficiency, root-mean-square-error (RMSE), mean absolute error, mean absolute percentage error and determination coefficient. The tested results of both stations reported that the ELM–SAMOA and ELM–PSOGWO models offered the best accuracy in the prediction of monthly streamflows compared to ELM–PSO, ELM–MOA, and ELM models. Based on the local data, the ELM–SAMOA reduced the RMSE of ELM, ELM–PSO, ELM–MOA, and ELM–PSOGWO by 31%, 27%, 19%, and 14% for the Gorai station and by 29%, 27%, 19%, and 14% for Padma Hardinge bridge station, in the testing stage, respectively. In contrast, based on external data, ELM–PSOGWO improves in RMSE of ELM, ELM–PSO, ELM–MOA, and ELM–SAMOA by 20%, 5.1%, 6.2%, and 4.6% in the testing stage, respectively. The results confirmed the superiority of two-phase optimized ELM–SAMOA and ELM–PSOGWO models over a single ELM model. The overall results suggest that ELM–SAMOA and ELM–PSOGWO models can be successfully applied in modeling monthly streamflow prediction with either local or external hydro-meteorological datasets.
Artificial Neural Network-Based Land Use-Specific Carbon Patterns and Their Effects on Land Surface Temperature as a Result of the Rohingya Refugee Influx
(IEEE, 2023-12-21) Sarkar, Showmitra Kumar; Saroar, MD. Mustafa; Das, Palash Chandra; Chakraborty, Tanmoy; Rudra, Rhyme Rubayet; Alam, Edris; Islam, MD. Kamrul; Islam, Abu Reza Md. Towfiqul
The objective of the research is to investigate how refugees’ influx has altered the carbon dynamics of different land uses and the relationship between land use specific carbon emissions and land surface temperature (LST). Two upazilais of the Cox’s Bazar district, Bangladesh (i.e., Ukhiya and Teknaf), were mostly affected by the Rohingya refugee influx and are the focus of the study. The study classified the land use land cover (LULC) into four classes (e.g., agricultural, forest, settlement, and water) for two different time periods (i.e., before and after the influx of Rohingya refugees) using an artificial neural network algorithm and sentinel satellite imagery. Carbon emissions and absorptions specific to land use were calculated using classified land use land cover and coefficients. Again, two time series of Landsat 8 imagery were applied to estimate land surface temperature shifts. The area of forests was found to have decreased by 21.19 square miles (9.58 percent) and the area of settlements to have increased by 18.24 square miles (8.25 percent) between 2017 and 2021. There was a negative net land-use based carbon emission of -5187.02 tons per year in 2017. In 2021, it was predicted that annual net emissions would total 2208.24 tons. LST during the study period has increased as a result of human activities that release greenhouse gases into the atmosphere. The findings of this research will inform policymakers’ decisions about the conservation and sustainable development of natural resources in the region experiencing an influx of Rohingya refugees.
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.
Assessing Seismicity in Bangladesh: An Application of Guttenberg-Richter Relationship and Spectral Analysis
(Taylor & Francis Group, 2023-08-21) Islam, Abu Reza Md. Towfiqul; Akter, Mst. Yeasmin; Amanat, Sumaia; Alam, Edris; Sultana, Mst. Laila; Shahid, Shamsuddin; Das, Arnob; Peu, Susmita Datta; Mallick, Javed
Bangladesh has a high risk of earthquakes because the Dauki, Jamuna, and Chittagong-Myanmar faults are still active. However, the assessment of seismicity remains a big challenge due to the complex geologic setting of Bangladesh. This study employed the Guttenberg-Richter relationship and the spectral models to assess and analyze the earthquake conditions in Bangladesh. Besides, an instrumental earthquake catalogue, obtained from the Bangladesh Meteorological Department (BMD), covering 1985–2017, is established. The results revealed that the Guttenberg-Richter constants of a and b were 2.981 and 0.392, which propagated a strain release from 1992 to 2017. The spectral model analyses, e.g. wavelet transform (WT), short-time Fourier transformation (STFT), and multitaper model (MTM), demonstrated the magnitude and strain release anomalies of the same magnitude ranging from 4.8 to 5.7, indicating the probable precursor of an upcoming earthquake. Notably, magnitudes have been running around 4.5–5.8, which may act as a signal to major earthquakes that have not been evident before. The proposed models allowed for the completion of the Bangladesh earthquake catalogue and provided a platform for future seismicity assessment and earthquake probability analysis. These results should be considered in determining how likely earthquakes are to happen in an area or region.
Assessment of Soil Heavy Metal Pollution and Associated Ecological Risk of Agriculture Dominated Mid-Channel Bars in a Subtropical River Basin
(Springer Nature Limited, 2023-07-09) Hoque, Md. Mofizul; Islam, Aznarul; Islam, Abu Reza Md. Towfiqul; Pal, Subodh Chandra; Mahammad, Sadik; Alam, Edris
The elevated concentrations of heavy metals in soil considerably threaten ecological and human health. To this end, the present study assesses metals pollution and its threat to ecology from the mid-channel bar’s (char) agricultural soil in the Damodar River basin, India. For this, the contamination factor (CF), enrichment factor (EF), geoaccumulation index (Igeo), pollution index, and ecological risk index (RI) were measured on 60 soil samples at 30 stations (2 from each station, i.e., surface and sub-surface) in different parts of the mid-channel bar. The CF and EF indicate that both levels of char soil have low contamination and hence portray a higher potential for future enrichment by heavy metals. Moreover, Igeo portrays that soil samples are uncontaminated to moderately contaminated. Further, pollution indices indicate that all the samples (both levels) are unpolluted with a mean of 0.062 for surface soils and 0.048 for sub-surface soils. Both levels of the char have a low potentiality for ecological risk with an average RI of 0.20 for the surface soils and 0.19 for the sub-surface soils. Moreover, Technique for order preference by similarity to ideal solution (TOPSIS) indicates that the sub-surface soils have lower pollution than the surface soils. The geostatistical modeling reveals that the simple kriging technique was estimated as the most appropriate interpolation model. The present investigation exhibits that reduced heavy metal pollution is due to the sandy nature of soils and frequent flooding. However, the limited pollution is revealed due to the intensive agricultural practices on riverine chars. Therefore, this would be helpful to regional planners, agricultural engineers, and stakeholders in a basin area.
Bayesian Optimized Multimodal Deep Hybrid Learning Approach for Tomato Leaf Disease Classification
(Springer Nature, 2024-09-14) Khan, Bodruzzaman; Das, Subhabrata; Fahim, Nafis Shahid; Banerjee, Santanu; Khan, Salma; Al‑Sadoon, Mohammad Khalid; Al‑Otaibi, Hamad S.; Islam, Abu Reza Md. Towfiqul
Manual identification of tomato leaf diseases is a time-consuming and laborious process that may lead to inaccurate results without professional assistance. Therefore, an automated, early, and precise leaf disease recognition system is essential for farmers to ensure the quality and quantity of tomato production by providing timely interventions to mitigate disease spread. In this study, we have proposed seven robust Bayesian optimized deep hybrid learning models leveraging the synergy between deep learning and machine learning for the automated classification of ten types of tomato leaves (nine diseased and one healthy). We customized the popular Convolutional Neural Network (CNN) algorithm for automatic feature extraction due to its ability to capture spatial hierarchies of features directly from raw data and classical machine learning techniques [Random Forest (RF), XGBoost, GaussianNB (GNB), Support Vector Machines (SVM), Multinomial Logistic Regression (MLR), K-Nearest Neighbor (KNN)], and stacking for classifications. Additionally, the study incorported a Boruta feature filtering layer to capture the statistically significant features. The standard, research-oriented PlantVillage dataset was used for the performance testing, which facilitates benchmarking against prior research and enables meaningful comparisons of classification performance across different approaches. We utilized a variety of statistical classification metrics to demonstrate the robustness of our models. Using the CNN-Stacking model, this study achieved the highest classification performance among the seven hybrid models. On an unseen dataset, this model achieved average precision, recall, f1-score, mcc, and accuracy values of 98.527%, 98.533%, 98.527%, 98.525%, and 98.268%, respectively. Our study requires only 0.174 s of testing time to correctly identify noisy, blurry, and transformed images. This indicates our approach's time efficiency and generalizability in images captured under challenging lighting conditions and with complex backgrounds. Based on the comparative analysis, our approach is superior and computationally inexpensive compared to the existing studies. This work will aid in developing a smartphone app to offer farmers a real-time disease diagnosis tool and management strategies.
Change in Cyclone Disaster Vulnerability and Response in Coastal Bangladesh
(John Wiley & Sons, 2023-08-13) Alam, Edris; Collins, Andrew E.; Islam, Abu Reza Md. Towfiqul; Paul, Alak; Islam, Md Kamrul
The number of deaths owing to tropical cyclones in Bangladesh has significantly reduced. Category 4 Cyclone Gorky in 1991 and Sidr in 2007 caused 147,000 and 4,500 deaths respectively, whereas Category 1 Cyclone Mora in 2017 resulted in six. Face-to-face interviews with 362 residents, participant observation, and focus-group discussions answer a research question about how change in coastal areas has contributed to this outcome. The study considered institutional approaches of disaster risk management through legal frameworks, administrative arrangements, cyclone preparedness activities, cyclone detection and early warning dissemination, construction of shelter centres, strengthening of various types of coastal embankments, paved roads, and pre-cyclone evacuation. The findings indicate significant improvement in house structures and design, income levels and diversification, education, awareness, individual capacity, poverty reduction, and lowering dependency on agriculture-based earning. Furthermore, the availability of mobile telephones, radio, television, and social media platforms enhanced social connectivity and greater gender equality and empowerment helped to facilitate disaster preparedness, evacuation, and response.
Change in cyclone disaster vulnerability and response in coastal Bangladesh
(Scopus, 2023-08-13) Alam, Edris; Collins, Andrew E.; Islam, Abu Reza Md. Towfiqul; Paul, Alak; Islam, Md Kamrul
The number of deaths owing to tropical cyclones in Bangladesh has significantly reduced. Category 4 Cyclone Gorky in 1991 and Sidr in 2007 caused 147,000 and 4,500 deaths respectively, whereas Category 1 Cyclone Mora in 2017 resulted in six. Face-to-face interviews with 362 residents, participant observation, and focus-group discussions answer a research question about how change in coastal areas has contributed to this outcome. The study considered institutional approaches of disaster risk management through legal frameworks, administrative arrangements, cyclone preparedness activities, cyclone detection and early warning dissemination, construction of shelter centres, strengthening of various types of coastal embankments, paved roads, and pre-cyclone evacuation. The findings indicate significant improvement in house structures and design, income levels and diversification, education, awareness, individual capacity, poverty reduction, and lowering dependency on agriculture-based earning. Furthermore, the availability of mobile telephones, radio, television, and social media platforms enhanced social connectivity and greater gender equality and empowerment helped to facilitate disaster preparedness, evacuation, and response.
Change in Cyclone Disaster Vulnerability and Response in Coastal Bangladesh
(John Wiley & Sons, 2023-01-15) Alam, Edris; Collins, Andrew E.; Islam, Abu Reza Md. Towfiqul; Paul, Alak; Islam, Md Kamrul
The number of deaths owing to tropical cyclones in Bangladesh has significantly reduced. Category 4 Cyclone Gorky in 1991 and Sidr in 2007 caused 147,000 and 4,500 deaths respectively, whereas Category 1 Cyclone Mora in 2017 resulted in six. Face-to-face interviews with 362 residents, participant observation, and focus-group discussions answer a research question about how change in coastal areas has contributed to this outcome. The study considered institutional approaches of disaster risk management through legal frameworks, administrative arrangements, cyclone preparedness activities, cyclone detection and early warning dissemination, construction of shelter centres, strengthening of various types of coastal embankments, paved roads, and pre-cyclone evacuation. The findings indicate significant improvement in house structures and design, income levels and diversification, education, awareness, individual capacity, poverty reduction, and lowering dependency on agriculture-based earning. Furthermore, the availability of mobile telephones, radio, television, and social media platforms enhanced social connectivity and greater gender equality and empowerment helped to facilitate disaster preparedness, evacuation, and response.
Climate Change and Its Impacts on Banana Production: A Systematic Analysis
(Springer, 2023-04-03) Abdoussalami, Andlia; Hu, Zhenghua; Islam, Abu Reza Md. Towfiqul; Wu, Zhurong
Climate change and environmental stress limit the growth of plants, including bananas. A systematic review and analysis of the topic are presented for the first time to identify physiological, biochemical, and molecular factors that may confer tolerance to climate change in Musa spp. Searches were conducted in six databases using pre-established inclusion and exclusion criteria (Web of Science, PubMed Central, SAGE, Google Scholar, Wiley, and Scopus Journals). A previously established process and inclusion and exclusion criteria were used to avoid publication bias. This systematic review was specifically focused on the Musa spp. production to climate change, the number of studies included was limited to only 76 articles. This indicates the need for additional research in this area and a potential change in research trends toward other strategies for mitigating the effects of climate change in bananas. Based on the review outcomes, we found a connection between changes in several climatic factors, which impacted banana production, and the cultivation of bananas in various geographic locations. Recently, few comprehensive studies on the effects of water stress on bananas have been conducted, however, they have yet to address the impacts of flood stress. Research gaps were identified addressing the characteristics of banana production and how this varies with location, elevation, and management factors, as well as the effects of changes in drought, water stress, and temperature. Evidence-based innovations are needed to reduce the effects of climate change in banana production.