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Paleoliquefaction investigations are crucial for assessing seismic hazard potential and identifying regions susceptible to liquefaction, which is essential for seismic risk-sensitive land-use planning. This research aimed to identify paleoliquefaction sites by reviewing documented descriptions of the damages and ground deformations in Bangladesh during three significant historical earthquakes: the Bengal Earthquake (1885), the Great Assam Earthquake (1897), and the Srimangal Earthquake (1918). A paleoliquefaction map for Bangladesh was generated, locating the paleoliquefaction sites during these three major historical earthquakes. In addition, Standard Penetration Test (SPT) blow count and Down-hole Seismic Tests (DST) were conducted at selected locations to assess the Liquefaction Potential Index (LPI) by using deterministic (simplified) and probabilistic procedures. The results confirmed a high likelihood of liquefaction during future large-magnitude earthquakes. The research outcome will help to distinguish and characterize Bangladesh's susceptible regions to soil liquefaction during potential earthquakes in the future and is recommended for consideration in large-scale construction or development plans.

期刊论文 2025-06-01 DOI: 10.1007/s10064-025-04316-w ISSN: 1435-9529

Floods pose a significant risk for Bangladesh due to the country's geographical and climatic conditions. Traditional methods of predicting flood risk often fail to do justice to the complex dynamics of flood vulnerability in this region. This report provides a comprehensive overview of the use of advanced machine learning (ML) algorithms for flood risk prediction in Bangladesh. It addresses four primary areas of research: (a) factors influencing floods considered in ML-based studies, (b) performance metrics of ML models, and (c) research gaps and future challenges in ML-based flood risk prediction. This review identified 42 unique factors that influence flooding, with precipitation, distance from the river, elevation, orientation, land use and land cover, and soil type emerging as the most important. ML models showed high predictive performance with an accuracy of 82% to 95%, depending on the algorithm and dataset used. However, there are still problems with data quality and regional variability that affect the reliability of the models. To improve flood forecasting, integrating real-time data, combining ML with physical models and promoting stakeholder engagement are crucial. Future research should focus on improving data quality, combining ML and physical models, and integrating future climate projections to refine flood hazard mapping. By considering these aspects, this study contributes to improving flood risk assessment and sustainable flood management strategies in Bangladesh, which could reduce socio-economic losses and environmental damage -in high-risk areas by 20-30.

期刊论文 2025-03-01 DOI: 10.1007/s12145-025-01816-x ISSN: 1865-0473

Flash floods are one of the most prevalent natural disasters, triggering deadly damage to homesteads, crops, infrastructure, road networks, communications, and the natural environment in the Haor (Wetland) region of Bangladesh. The purpose of the study aims to identify eleven (11) hydro-geomorphological driving factors, namely elevation, slope, aspect, rainfall, land use and land cover (LULC), lithology, soil type, topographic wetness index (TWI), Normalized Difference Vegetation Index (NDVI), distance from the river, and drainage density, which are being explored for mapping flood-prone areas. This research has produced a flash flood susceptibility map using the Analytical Hierarchy Process (AHP) and Analytical Network Process (ANP), which are interactive decision-making approaches under multi-criteria decision analysis (MCDA) in ArcGIS 10.8. The findings of this study showed that the susceptibility to flood hazards differs significantly among the seven Haor districts. As a result of the ANP and AHP, a more significant proportion of the Haor region is moderately susceptible to flooding (8685.09-9275.15 sq. km.), whereas 35.34 %-38.32 % (7069.70-7668.67 sq. km.) accounts for high susceptible to flooding. Furthermore, 200 flood locations were identified in the northeast Haor region, where 140 (70 %) randomly selected floods were used for training, and the remaining 60 (30 %) were employed for validation purposes. The validation results showed that the AHP model had greater prediction accuracy (the area under the receiver operating curve (AUROC) = 92.1 %) than the ANP (AUROC = 88.5%) model. Therefore, the study findings can be helpful for researchers, academics, policymakers, and planners for sustainable flood mitigation strategies, particularly in Haor areas.

期刊论文 2025-01-01 DOI: 10.1016/j.watcyc.2024.09.003

Naturally occurring radioactive materials (NORMs: 232Th, 226Ra, 40K) can reach our respiratory system by breathing of road dust which can cause severe health risks. Targeting the pioneering consideration of health risks from the NORMs in road dust, this work reveals the radioactivity abundances of NORMs in road dust from a megacity (Dhaka) of a developing country (Bangladesh). Bulk chemical compositions of U, Th, and K obtained from neutron activation analysis were converted to the equivalent radioactivities. Radioactivity concentrations of 226Ra, 232Th, and 40K in road dust ranged from 60-106, 110-159, and 488-709 Bq kg-1 with an average of 84.4 +/- 13.1, 126 +/- 11, and 549 +/- 48 Bq kg-1, respectively. Estimated 226Ra, 232Th, and 40K radioactivities were, respectively, 1.7-3.0-, 3.7-5.3-, and 1.2-1.8-folds greater than the affiliated world average values. Mechanistic pathway of NORMs' enrichment and fractionation relative to the major origin (pedosphere) were evaluated concerning the water logging, relative solubility-controlled leaching and translocation, climatic conditions, and aerodynamic fractionations (dry and wet atmospheric depositions). Computation of customary radiological risk indices invokes health risks. Noticing the ingress of NOMR-holding dust into the human respiratory system along with the associated ionizing radiations, the computed radiological indices represent only the least probable health hazards. Nevertheless, in real situations, alpha-particles from the radioactive decay products of 232Th and 238U can create acute radiation damages of respiratory system. Policymakers should emphasize on limiting the dust particle evolution, and public awareness is required to alleviate the health risks.

期刊论文 2024-01-01 DOI: 10.1007/s11356-023-31657-4 ISSN: 0944-1344

The quantitative and qualitative characterization of ions and inorganic nitrogen in precipitation assists in understanding the accompanying sources and chemistry of regional precipitation. A total of 212 event-based precipitation samples were collected from four sites in Bangladesh in 2017 to investigate the physicochemical characteristics, sources, and deposition of atmospheric ionic constituents and inorganic nitrogen. During the entire monitoring period, 5.7% of the total samples were acidic (i.e., pH Cox's Bazar > Dinajpur > Sylhet, whereas the anthropogenic species exhibited the order of Dinajpur > Satkhira > Sylhet > Cox's Bazar, underlining the local and regional impacts of these species in Bangladesh. Based on the source apportionment, the sources were categorized as marine (Na+ and Cl-), terrigenous (Ca2+, Mg2+, and HCO3-), fossil fuel combustion (NO3- and SO42-), agriculture (NH4+), and biomass burning (K+). The Cl- in Sylhet and Satkhira suggests additional sources associated with anthropogenic activities. The back-trajectory analyses and the National Centers for Environmental Prediction's final (NCEP FNL) datasets illustrate the presence of significantly diverse air masses with contributions from various sources in the monsoon and non-monsoon climates. Both the amount of precipitation and the ionic quantity governs the fluxes in Bangladesh. The Na+ % and SAR lie under the safe category suggesting a good precipitation water quality for agriculture and soil in Bangladesh, while the deposition of inorganic nitrogen has resulted in a value above the threshold line (10 kg ha(-1) y(-1)). Thus, this study conveys a comprehensive picture of the ionic composition, providing a baseline dataset to assess the atmospheric environment in this lowland region.

期刊论文 2021-02-20 DOI: http://dx.doi.org/10.1016/j.atmosres.2020.105414 ISSN: 0169-8095

Low- and middle-income countries have the largest health burdens associated with air pollution exposure, and are particularly vulnerable to climate change impacts. Substantial opportunities have been identified to simultaneously improve air quality and mitigate climate change due to overlapping sources of greenhouse gas and air pollutant emissions and because a subset of pollutants, short-lived climate pollutants (SLCPs), directly contribute to both impacts. However, planners in low- and middle-income countries often lack practical tools to quantify the air pollution and climate change impacts of different policies and measures. This paper presents a modelling framework implemented in the Low Emissions Analysis Platform - Integrated Benefits Calculator (LEAP-IBC) tool to develop integrated strategies to improve air quality, human health and mitigate climate change. The framework estimates emissions of greenhouse gases, SLCPs and air pollutants for historical years, and future projections for baseline and mitigation scenarios. These emissions are then used to quantify i) population-weighted annual average ambient PM2.5 concentrations across the target country, ii) household PM2.5 exposure of different population groups living in households cooking using different fuels/technologies and iii) radiative forcing from all emissions. Health impacts (premature mortality) attributable to ambient and household PM2.5 exposure and changes in global average temperature change are then estimated. This framework is applied in Bangladesh to evaluate the air quality and climate change benefits from implementation of Bangladesh's Nationally Determined Contribution (NDC) and National Action Plan to reduce SLCPs. Results show that the measures included to reduce GHGs in Bangladesh's NDC also have substantial benefits for air quality and human health. Full implementation of Bangladesh's NDC, and National SLCP Plan would reduce carbon dioxide, methane, black carbon and primary PM2.5 emissions by 25%, 34%, 46% and 45%, respectively in 2030 compared to a baseline scenario. These emission reductions could reduce population-weighted ambient PM2.5 concentrations in Bangladesh by 18% in 2030, and avoid approximately 12,000 and 100,000 premature deaths attributable to ambient and household PM2.5 exposures, respectively, in 2030. As countries are simultaneously planning to achieve the climate goals in the Paris Agreement, improve air quality to reduce health impacts and achieve the Sustainable Development Goals, the LEAP-IBC tool provides a practical framework by which planners can develop integrated strategies, achieving multiple air quality and climate benefits.

期刊论文 2020-12-01 DOI: 10.1016/j.envint.2020.106155 ISSN: 0160-4120
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