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Arsenic (As) contamination in groundwater is emerging as a significant global concern, posing serious risks to the safety of drinking water and public health. To understand the release mechanisms, mobilization processes, spatial distribution, and probabilistic health risks of As in western Bangladesh, forty-seven samples were collected and analyzed using an atomic absorption spectrometer (AAS). The As concentrations in groundwater ranged from 1.97 to 697.4 μg L⁻ 1 (mean: 229.9), significantly exceeding recommended levels. The dominant hydrochemistry of As-enriched groundwater was Ca-Mg-HCO₃, with the primary sources of arsenic in groundwater being the dissolution of arsenic-bearing minerals in sediment and the recharge of aquifers from the Ganges River Basin. The assessment using the Entropy Water Quality Index revealed that the groundwater is unsuitable for drinking, with 89.36% (n = 42) of the samples surpassing the WHO's limit for arsenic. Rock-water interactions, including calcite dissolution and silicate weathering within the confined aquifer, predominantly influenced hydrochemical properties. The significant relationships among Fe, Mn, and As indicate that the reductive dissolution of FeOOH and/or MnOOH considerably contributes to the release of As from sediment into groundwater. Geochemical modeling analysis revealed that siderite and rhodochrosite precipitate into aquifer solids, suggesting a weak to moderate relationship among As, Fe, and Mn. The long residence time of groundwater, combined with the presence of a clayey aquitard, likely controls the mobilization of arsenic in the aquifer. For the first time, Monte Carlo simulations have been used in arsenic-prone areas to assess the severity of arsenic contamination in western Bangladesh. The analysis indicates that out of 100,000 people, 10 may develop cancer as a result of drinking arsenic-contaminated water, with children being more susceptible than adults., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Groundwater in northwestern parts of Bangladesh, mainly in the Chapainawabganj District, has been contaminated by arsenic. This research documents the geographical distribution of arsenic concentrations utilizing machine learning techniques. The study aims to enhance the accuracy of model predictions by precisely identifying occurrences of groundwater arsenic, enabling effective mitigation actions and yielding more beneficial results. The reductive dissolution of arsenic-rich iron oxides/hydroxides is identified as the primary mechanism responsible for the release of arsenic from sediment into groundwater. The study reveals that in the research region, alongside elevated arsenic concentrations, significant levels of sodium (Na), iron (Fe), manganese (Mn), and calcium (Ca) were present. Statistical analysis was employed for feature selection, identifying pH, electrical conductivity (EC), sulfate (SO 4 ), nitrate (NO 3 ), Fe, Mn, Na, K, Ca, Mg, bicarbonate (HCO 3 ), phosphate (PO 4 ), and As as features closely associated with arsenic mobilization. Subsequently, various machine learning models, including Naïve Bayes, Random Forest, Support Vector Machine, Decision Tree, and logistic regression, were employed. The models utilized normalized arsenic concentrations categorized as high concentration (HC) or low concentration (LC), along with physiochemical properties as features, to predict arsenic occurrences. Among all machine learning models, the logistic regression and support vector machine models demonstrated high performance based on accuracy and confusion matrix analysis. In this study, a spatial distribution prediction map was generated to identify arsenic-prone areas. The prediction map also displays that Baroghoria Union and Rajarampur region under Chapainawabganj municipality are high-risk areas and Maharajpur Union and Baliadanga Union are comparatively low-risk areas of the research area. This map will facilitate researchers and legislators in implementing mitigation strategies. Logistic regression (LR) and support vector machine (SVM) models will be utilized to monitor arsenic concentration values continuously., (© 2024. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

For the first time, different pollution indices and a receptor model have been used to quantify eco-environmental and health risk assessments as well as identify the sources of potentially toxic elements in soil along the Barapukuria Coal Mine (BCM). Individual indices include enrichment and contamination factors showing the soil samples are moderately to highly contaminated by arsenic, cobalt, chromium, copper, lead, and zinc and heavily contaminated by sulfur. According to the geo-accumulation index, there is significant pollution with arsenic (1.24 ± 0.38), lead (1.49 ± 0.58), cobalt (1.49 ± 0.58), and sulfur (1.63 ± 0.38). Modified hazard quotient and ecological risk factor values also suggest low to moderate environmental risk hazards from the same elements. The nemerow pollution index, pollution load index, nemerow risk index, ecological risk index, and toxic risk index of soil range from 1.65 to 3.03, 0.82-1.23, 11-26, 77-165, and 6.82-11.76 suggest low toxic risk and moderate pollution, among other synergistic indices. Health risk assessment indicates that iron poses lower cancer risk for children than adults, while both face unacceptable cancer risks from inhaling chromium, cobalt, or arsenic. Principal component and phylogenetic cluster analysis extracted by the multiple linear regression with the absolute principal component score (APCS-MLR) model refer to the fact that manganese, iron, titanium, and nickel have originated from geogenic sources, while coal mine effluents enrich elements like arsenic, chromium, zinc, lead, uranium, sulfur, thorium, and zinc and phosphorous sourced from agriculture. In addition, geogenic and anthropogenic sources, including mine and agriculture activities, could potentially pollute the soil and ecosystem. The findings are crucial for regional and national planners in devising strategies to mitigate potentially toxic element pollution in soil along coal mine areas., Competing Interests: We declare that this manuscript is original, has not been published before, and is not currently being considered for publication elsewhere. We know of no conflict of interest associated with this publication, and there has been no significant financial support for this work that could have influenced the outcome. As corresponding authors, we confirm that the manuscript has been read and approved by all the names of the authors., (© 2024 The Authors.)

One of the biggest environmental worries in the world today is the risk of arsenic (As) contamination in groundwater. The Atomic Absorption Spectrometer (AAS) was used in this work to assess the As content in groundwater samples from 38 shallow (27 m) tubewells in northwest Bangladesh to determine the existing situation, potential source(s), and likely health risk of As and other important water quality parameters. The range of arsenic concentrations (μgL -1 ) was troublesome and greater than the WHO recommended level for drinking water, ranging from 0.50 to 164 (mean ± SD: 20.22 ± 36.46). In groundwater, the concentrations of Fe, and Mn vary from 0.04 to 52.75 mgL -1 (mean ± SD: 4.23 ± 9.68), and 0.23 to 3.27 mgL -1 (mean ± SD: 1.10 ± 0.67). The obtained groundwater samples have pH values ranging from 5.9 to 7.1, which indicates a somewhat acidic to neutral character. Major cations have an average abundance that is as follows: Ca 2+  > Mg 2+  > Na +  > K + , while major anions have an average abundance that is as follows: HCO 3 -  > Cl -  > SO 4 2-  > NO 3 - ; Ca 2+ and HCO 3 - are the main cation and anion, respectively. The groundwater in the Rajarampur village was deemed unfit for drinking or irrigation based on analyses of water quality performed using the entropy water quality index. The Ca-HCO 3 type of water, in which Ca 2+ and HCO 3 - are the main positive ions and negative ions, is suggested by the Piper tri-linear diagram. It was discovered that silicate weathering regulates the hydro-geochemical activities in groundwater using a bi-variate examination of several hydro-chemical variables. Four major clusters were observed for the water sample. According to reductive dissolution processes and principal component analysis, the arsenic in groundwater is geogenic in origin. Arsenic is discharged from sediment to groundwater by reductive dissolution of FeOOH and MnOOH, as shown by the modest connection between As, Fe, and Mn. The United Nations Environmental Protection Agency's (USEPA) suggested value for probable cancer risk assessment was 10 -6 , however the probable cancer risk assessment found a higher value, indicating that the population in the study region was at high risk for cancer. Remedial measures for arsenic mitigation include removing arsenic from groundwater after it is extracted, searching for alternative aquifers, and implementing various water-supply technologies such as dugwells, deep tubewells, pond-sand filters, and rainwater harvesting systems., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2024 The Author(s).)

Eleven trace metals (Cd, Cr, Fe, Mn, Cu, Ni, Co, Zn, As, Pb, and Ag) in sediments of Bangladesh's ship breaking area were measured by an atomic absorption spectrometer to determine origin, contamination extent, spatial distributions, and associated ecological and human health hazards. This study found considerable quantities of Pb, Cd, Mn, Zn, and Cu when compared with standards and high levels of Pb, Cd, Zn, Cu, As, and Ag contamination according to pollution evaluation indices. Different indices indicate most of the sampling sites were highly polluted. However, spatial distribution maps indicate that trace metals were predominantly deposited in the northern and southern region. The ecological risk index revealed that Cd has the highest while Pb and As had moderate risk. Based on the health index values, Zn for both adults and children were higher than the safe limit while Mn, Pb, Cr, As, Fe, Cu, Ni, and Co for children were close to the threshold. The mean total carcinogenic risk values of Cr, As, and Ni for children and Ni for adults exceeded the permissible threshold. The cancer risk possibilities were further assessed using Monte Carlo simulation. Most trace metals have anthropogenic origins, which were attributed to ship breaking activities., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier B.V. All rights reserved.)

Elemental composition, multivariate statistical analyses with the absolute principal component score-multiple linear regression (APCS-MLR) model, and different pollution indices in Upper and Lower Southwestern Ganges-Brahmaputra-Meghna (GBM) delta sediments were studied to characterize pollution, ecological risk and quantify potential toxic element sources of the area. Toxic metals concentrations were higher in Lower Delta and individual pollution indices showed Upper Delta was moderately polluted by arsenic, chromium, cobalt, copper and lead, and Lower Delta was moderately-strongly polluted by the same metals. Synergistic indices include Potential Ecological, Toxic, Nemerow, and Pollution Risk indices in Upper and Lower Delta sediment ranged from 47.17-128.07, 2.03-12.19, 29.92-65.42, 0.28-1.62, and 69.17-246.90, 8.00-13.47, 20.53-152.92, 1.18-1.58, indicated low and moderate risk pollution, respectively. Statistical models represent the metals dominantly originated from nature for Upper Delta, and both natural and anthropogenic activities contributed to Lower Delta sediment. The study found that the modern deposit in Lower Delta became more contaminated and thus enhanced ecological risk., Competing Interests: Declaration of competing interest All relevant data used for the research described in this article are included in the article. The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article. The authors declare that this manuscript is original, has not been published before, and is not currently being considered for publication elsewhere., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

The concentrations of eleven heavy metals (Pb, Cd, Cr, Fe, Mn, Zn, Cu, Ni, Co, As, and Ag) were assessed in both groundwater and seawater collected from the ship-breaking industrial area of Bangladesh using an atomic absorption spectrometer. The investigation aimed to estimate the water quality and pollution level employing several indices, and its associated health risks for the first time in that area. This study found that Cd, Cr, Fe, Pb, Mn, and Ni were higher in both groundwater and seawater compared with WHO standards. Based on the WQI (water quality index) and EWQI (entropy water quality index) classifications, the quality of most of the groundwater is extremely poor or unsuitable for drinking purposes. Furthermore, the HPI (heavy metal pollution index), HEI (heavy metal evaluation index), and CD (degree of contamination) values of most groundwater and all seawater samples exhibit a higher degree of pollution. In addition, the results of NI (Nemerow pollution index) come to an end that both groundwater and seawater in the study area are mostly polluted by Fe, Mn, Pb, Cr, and Cd. Although the HI (hazard quotient index) values of almost all studied heavy metals in both cases of adults and children are within the safe limit, the HI value of Cr for an adult is near the threshold limit and the maximum HI value of Cr for children exceeds this limit. The carcinogenic risk reveals that Cr, Pb, As, and Cd produce detrimental effects on local people through the direct ingestion of groundwater. The pollution source is identified using principal component analysis and a Pearson correlation matrix as being primarily anthropogenic and attributed to intensive ship-breaking activities or other industries in the area., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

To understand the mechanistic pathway of arsenic (As) enrichment and mobilization in groundwater (southeastern Bangladesh) and to evaluate the water quality as well as associated health risks, a suite of systematically collected groundwater samples (depth: 17-61 m) were analyzed. Arsenic concentrations (μg L -1 ) in the groundwater samples were ranged from 6 to 581 with a mean value of 199 which is significantly higher than the recommended values. The assessment of water quality using entropy water quality index and irrigation water quality indices revealed that the groundwater in the studied region was not recommended for drinking and irrigation, respectively with few exceptions. Dominant water types in the studied area were Ca-Mg-HCO 3, Na-HCO 3 , and Na-Cl types. Various forms of water-rock interactions, leaching of evaporates, and the confined nature of the aquifer mostly control the hydro-chemical parameters. Fe/Mn bound As are likely to be released in the aquifer through the dissolution of carbonate minerals of Fe/Mn while the higher degree of water-rock interaction and probable oxidation of organic materials helped to elevate As concentration. The probable longer residence time of groundwater guided by topographic slope and the neighboring clayey aquitard govern the As mobilization in the aquifer. Probabilistic health risk assessment revealed that groundwaters from the studied area can cause both non-carcinogenic and carcinogenic health risks., (Copyright © 2022 Elsevier Ltd. All rights reserved.)