Fuzzy logic, geostatistics, and multiple linear models to evaluate irrigation metrics and their influencing factors in a drought-prone agricultural region.

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.

Assessing the challenges to medical waste management during the COVID-19 pandemic: Implications for the environmental sustainability in the emerging economies.

Emerging economies are struggling with proper and efficient management of waste due to their constrained resources and weak management. In recent days, this crisis has worsened due to the outbreak of the highly contagious COVID-19 pandemic. To avoid building up stockpiles and contaminating communities with potentially contagious medical waste (MW), and to ensure sustainability in the current and post-COVID-19 era, it is a dire need to develop and implement a safe and efficient medical waste management (MWM) system. This research, thereby, aims to identify, assess, and prioritize the key challenges to efficient and sustainable MWM to mitigate the impacts of the disruptions caused by situations like the pandemic in emerging economies. An integrated approach consisting of the Best-Worst Method (BWM), Interpretive Structural Modeling (ISM), and Cross-Impact Matrix Multiplication Applied to Classification (MICMAC) has been proposed to achieve the objectives. Based on the literature review and expert feedback, a total of seventeen challenges were identified and later prioritized by using BWM. The top twelve challenges have been further analyzed using ISM-MICMAC to examine their interrelationships. This study reveals that lack of proper law enforcement and insufficient financial support from investors and the government are two crucial challenges for efficient MWM implementation. The research insights can assist healthcare facility administrators, practitioners, and city managers in identifying the associated challenges and shaping strategic decisions for establishing and managing efficient MWM systems to ensure sustainable development in the post-COVID-19 era.

Exploring the barriers to implement industrial symbiosis in the apparel manufacturing industry: Implications for sustainable development.

Industrial symbiosis, a promising approach for sustainable industrial practices, has garnered attention in recent days for its ability to enhance resource efficiency, minimize waste, and preserve the environment through collaborative exchanges among industries. In emerging economies like Bangladesh, integrating industrial symbiosis in the manufacturing industries offers the potential to balance economic growth with environmental sustainability. However, this integration encounters various barriers that complicate the implementation. Despite research on industrial symbiosis in robust economies, studies on emerging and developed economies are still scarce. To date, no research has yet investigated the barriers hindering the performance of industrial symbiosis in the Bangladeshi apparel manufacturing sector. To address this gap, this study integrates the Bayes theorem and the Best-Worst Method to identify and prioritize barriers to the Bangladeshi apparel manufacturing sector. From extensive literature reviews and expert validation, 17 barriers were identified. Findings reveal the "lack of technology and infrastructure readiness" as the most significant barrier, followed by "lack of inter-company cooperation" and "lack of management support". Conquering these barriers empowers emerging economies to fortify the apparel manufacturing sector's resilience, resource efficiency, and environmental performance while fostering sustainable development via circular economy practices. This study is expected to guide policymakers and stakeholders in crafting targeted strategies for promoting steady growth and sustainable development in the apparel manufacturing sector of emerging economies like Bangladesh.

Impact of climate change on vector-borne diseases: Exploring hotspots, recent trends and future outlooks in Bangladesh.

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.

Predicting groundwater phosphate levels in coastal multi-aquifers: A geostatistical and data-driven approach.

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+Na+pH, Ca2+Mg2+NO3-, and HCO3-SO42-PO43-F-. 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.

A review of microplastic threat mitigation in Asian lentic environments.

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.

Analysis of the fire risks and mitigation approaches in the apparel manufacturing industry: Implications toward operational safety and sustainability.

Fire risks pose a substantial threat to the apparel manufacturing industry since they can lead to immense property damage, potential loss of life, disruption of business operations, and reputational damage. In an emerging economy like Bangladesh, fire-related hazards are crucial due to the numerous deadly industrial fire incidents in recent years. This research, thereby, proposes an integrated multi-criteria decision-making (MCDM) framework to identify and mitigate fire risk hazards in the apparel manufacturing industry. Initially, the study identified 30 significant fire risk factors from the literature review. Then, after expert validation, an integrated Best Worst Method (BWM) and Weighted Sum Model (WSM) framework was utilized to prioritize the fire risk factors. Twenty-three mitigation actions were proposed afterward for the top-ranked risk factors based on National Fire Protection Association (NFPA) codes. An Interpretive Structural Modeling (ISM) with a Cross-Impact Matrix Multiplication Applied to Classification (MICMAC) analysis was later used to explore the interrelationships and dependencies among the mitigation actions. The ranking obtained from the BWM-WSM assessment revealed 'combustible storage unseparated by fire-rated construction,' 'non-standard inspection, testing, and maintenance', and 'inadequate means of egress for the occupant load' as the three most critical fire risk factors. The ISM-MICMAC analysis revealed 'fire-rated construction' and 'standardized detection and protection' as the most-driving mitigation actions. The study outcomes are expected to aid the managers and policymakers in emerging economies in formulating sustainable fire risk management strategies for the apparel industry and thus improve the operational safety and resilience of the sector.

Evaluating barriers to sustainable boiler operation in the apparel manufacturing industry: Implications for mitigating operational hazards in the emerging economies.

The efficiency with which conventional boilers perform, in terms of sustainability, is affected by a variety of factors. Unsustainable boiler operating practices are still surprisingly frequent in developing countries, resulting in environmental liabilities and catastrophic accidents. It is a serious problem in developing countries like Bangladesh, where boilers are utilized extensively in the apparel manufacturing sector. However, no research has yet examined the challenges or barriers associated with sustainable boiler operation in the apparel manufacturing sector. This study, thereby, utilizes an integrated MCDM approach, combining the fuzzy theory and the decision-making trial and evaluation laboratory (DEMATEL) method, to identify, prioritize, and explore the relations among the barriers to sustainable boiler operation in the apparel manufacturing industry, from an emerging economy perspective. The barriers were initially identified from the literature and a visual survey of 127 factories. After expert validation, thirteen barriers were finally selected to be analyzed utilizing the fuzzy DEMATEL method. The study findings revealed that 'Absence of water treatment facilities', 'Fossil fuel burning and GHG emissions', and 'Excessive consumption of groundwater' are the three most prominent barriers to sustainable boiler operation. The cause-effect relations among the barriers suggest that 'Inadequate compliance with safety and hazard regulations' is the most influential and 'Fossil fuel burning and GHG emissions' is the most influenced barrier. This study is expected to guide the managers and policymakers of the apparel manufacturing sector in successfully overcoming the barriers to sustainable boiler operation, thus mitigating the operational hazards and achieving the sustainable development goals (SDGs).

Assessing the critical success factors for implementing industry 4.0 in the pharmaceutical industry: Implications for supply chain sustainability in emerging economies.

The emerging technologies of Industry 4.0 (I4.0) are crucial to incorporating agility, sustainability, smartness, and competitiveness in the business model, enabling long-term sustainability practices in the pharmaceutical supply chain (PSC). By leveraging the latest technologies of I4.0, pharmaceutical companies can gain real-time visibility into their supply chain (SC) operations, allowing them to make data-driven decisions that improve SC performance, efficiency, resilience, and sustainability. However, to date, no research has examined the critical success factors (CSFs) that enable the pharmaceutical industry to adopt I4.0 successfully to enhance overall SC sustainability. This study, therefore, analyzed the potential CSFs for adopting I4.0 to increase all facets of sustainability in the PSC, especially from the perspective of an emerging economy like Bangladesh. Initially, sixteen CSFs were identified through a comprehensive literature review and expert validation. Later, the finalized CSFs were clustered into three relevant groups and analyzed using a Bayesian best-worst method (BWM)-based multi-criteria decision-making (MCDM) framework. The study findings revealed that "sufficient investment for technological advancement", "digitalized product monitoring and traceability", and "dedicated and robust research and development (R&D) team" are the top three CSFs to adopt I4.0 in the PSC. The study's findings can aid industrial practitioners, managers, and policymakers in creating effective action plans for efficiently adopting I4.0 in PSC to avail of its competitive benefits and ensure a sustainable future for the pharmaceutical industry.

Personal protective equipment-derived pollution during Covid-19 era: A critical review of ecotoxicology impacts, intervention strategies, and future challenges.

During the COVID-19 pandemic, people used personal protective equipment (PPE) to lessen the spread of the virus. The release of microplastics (MPs) from discarded PPE is a new threat to the long-term health of the environment and poses challenges that are not yet clear. PPE-derived MPs have been found in multi-environmental compartments, e.g., water, sediments, air, and soil across the Bay of Bengal (BoB). As COVID-19 spreads, healthcare facilities use more plastic PPE, polluting aquatic ecosystems. Excessive PPE use releases MPs into the ecosystem, which aquatic organisms ingest, distressing the food chain and possibly causing ongoing health problems in humans. Thus, post-COVID-19 sustainability depends on proper intervention strategies for PPE waste, which have received scholarly interest. Although many studies have investigated PPE-induced MPs pollution in the BoB countries (e.g., India, Bangladesh, Sri Lanka, and Myanmar), the ecotoxicity impacts, intervention strategies, and future challenges of PPE-derived waste have largely gone unnoticed. Our study presents a critical literature review covering the ecotoxicity impacts, intervention strategies, and future challenges across the BoB countries (e.g., India (162,034.45 tons), Bangladesh (67,996 tons), Sri Lanka (35,707.95 tons), and Myanmar (22,593.5 tons). The ecotoxicity impacts of PPE-derived MPs on human health and other environmental compartments are critically addressed. The review's findings infer a gap in the 5R (Reduce, Reuse, Recycle, Redesign, and Restructure) Strategy's implementation in the BoB coastal regions, hindering the achievement of UN SDG-12. Despite widespread research advancements in the BoB, many questions about PPE-derived MPs pollution from the perspective of the COVID-19 era still need to be answered. In response to the post-COVID-19 environmental remediation concerns, this study highlights the present research gaps and suggests new research directions considering the current MPs' research advancements on COVID-related PPE waste. Finally, the review suggests a framework for proper intervention strategies for reducing and monitoring PPE-derived MPs pollution in the BoB countries.

Managing the invisible threat of microplastics in marine ecosystems: Lessons from coast of the Bay of Bengal.

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.

Evaluating factors contributing to the failure of information system in the banking industry.

The increasing use of Information Technology (IT) has led to many security and other related failures in the banks and other financial institutions in Bangladesh. In this paper, we investigated the factors contributing to the failurein the IT system of the banking industry in Bangladesh. Based on the experts' opinions and weight on the specified evaluating criteria, an empirical test was conducted using a rough set theory to produce a framework for the IT system failure factors. In this study, an extended approach involving the integration of rough set theory based flexible Failure Mode and Effect Analysis (FMEA) and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) has beenapplied to help the managers of the corresponding field to identify the factors responsible for the failure of the IT system in the banking industries and then prioritize them accordingly, for the ease of decision-making.In this research, eleven such failure factors were identified, which were then quantitatively analyzed to facilitate managers in crucial decision-making. It was observed that cyber-attack, database hack risks, server failure, network interruption, broadcast data error, and virus effect were the most significant factors for the failure of the IT system. The framework developed in this research can be utilized to assist in efficient decision-makingin other serviceindustries where IT systems play a key role. To the best of the knowledge, this is the first study thatempirically tested key failure factors of the IT system for the banking sector using an integrated method.