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This research is to develop dictated metrics using a multi-proxy approach such as spatial-temporal analysis, statistical evaluation, and hydrogeochemical analysis. We have collected 45 groundwater samples located in the Tamirabarani river basin. To evaluate the aptness of developed metrics for agriculture and domestic needs and eleven years dataset has been analyzed and compared with national and international standards BIS, ICMAR, and WHO Monitoring and all the analysis results revealed that the concentration of calcium (Ca-1679 to 4937 mg/L; and Cl ions 236 to 1126 mg/L) and chloride ions was on the higher side in locations. These higher values may be attributed to the regional point sources as untreated water disposal and off-peak sources as agriculture practices. According to the results of the principal component analysis, the post-monsoon season accounted for an 84.2% variance. The major analyzed cations and anions have been observed in the following order: Na +  > Ca 2+  > Mg 2+  > K + and Cl -  > HCO 3 -  > SO 4 2-  > NO 3 - respectively. Ca-Mg-HCO 3 , Mg-Ca-Cl, Na-C1, and infused waters have been discovered in the basin region, indicating that anion and cation dominance is not prevalent. This specifies that groundwater quality in this region is significantly degraded and suffers from extensive salinity due to the urban pollutants mixed with unprotected river sites., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

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, Ca 2+ Mg 2+ NO₃ - , and HCO₃ - SO₄ 2- PO 4 3- 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, R 2 , RAE, CC, and MAE. Phosphate dissolution and saltwater intrusion, along with phosphorus fertilizers, increase PO 4 3- 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, R 2  = 0.999, RAE = 0.057, CC = 1.00) and testing (RMSE = 0.001, MAE = 0.002, R 2  = 0.989, RAE = 0.057, CC = 0.998). Na + , K + , and Mg 2+ 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 PO 4 3- distribution in GW. These findings are crucial for developing conservation and strategic plans for sustainable utilization of coastal GW resources., 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 B.V. All rights reserved.)

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., 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 B.V. All rights reserved.)

Understanding the major factors influencing groundwater chemistry and its evolution in irrigation areas is crucial for efficient irrigation management. Major ions and isotopes (δD-H 2 O together with δ 18 O-H 2 O) were used to identify the natural and anthropogenic factors contributing to groundwater salinization in the shallow aquifer of the Wadi Guenniche Plain (WGP) in the Mediterranean region of Tunisia. A comprehensive geochemical investigation of groundwater was conducted during both the low irrigation season (L-IR) and the high irrigation season (H-IR). The results show that the variation range and average concentrations of almost all the ions in both the L-IR and H-IR seasons are high. The groundwater in both seasons is characterized by high electrical conductivity and CaMgCl/SO 4 and NaCl types. The dissolution of halite and gypsum, the precipitation of calcite and dolomite, and Na-Ca exchange are the main chemical reactions in the geochemical evolution of groundwater in the Wadi Guenniche Shallow Aquifer (WGSA). Stable isotopes of hydrogen and oxygen (δ 18 O-H 2 O and δD-H 2 O) indicate that groundwater in WGSA originated from local precipitation. In the H-IR season, the δ 18 O-H 2 O and δD-H 2 O values indicate that the groundwater experienced noticeable evaporation. The enriched isotopic signatures reveal that the WGSA's groundwater was influenced by irrigation return flow and seawater intrusion. The proportions of mixing with seawater were found to vary between 0.12% and 5.95%, and between 0.13% and 8.42% during the L-IR and H-IR seasons, respectively. Irrigation return flow and the associated evaporation increase the dissolved solids content in groundwater during the irrigation season. The long-term human activities (fertilization, irrigation, and septic waste infiltration) are the main drives of the high nitrate-N concentrations in groundwater. In coastal irrigation areas suffering from water scarcity, these results can help planners and policy makers understand the complexities of groundwater salinization to enable more sustainable management and development., 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 Inc. All rights reserved.)

While global attention has been primarily focused on the occurrence and persistence of microplastics (MP) in urban lakes, relatively little attention has been paid to the problem of MP pollution in rural recreational lakes. This pioneering study aims to shed light on MP size, composition, abundance, spatial distribution, and contributing factors in a rural recreational lake, 'Nikli Lake' in Kishoreganj, Bangladesh. Using density separation, MPs were extracted from 30 water and 30 sediment samples taken from ten different locations in the lake. Subsequent characterization was carried out using a combination of techniques, including a stereomicroscope, Fourier transform infrared spectroscopy (FTIR) and field emission scanning electron microscopy (FE-SEM). The results showed a significant prevalence of MPs in all samples, with an average amount of 109.667 ± 10.892 pieces/kg 3 (dw) in the sediment and 98.167 ± 12.849 pieces/m 3 in the water. Small MPs (<0.5 mm), fragments and transparent colored particles formed the majority, accounting for 80.2%, 64.5% and 55.3% in water and 78.9%, 66.4% and 64.3% in sediment, respectively. In line with global trends, polypropylene (PP) (53%) and polyethylene (PE) (43%) emerged as the predominant polymers within the MPs. MP contents in water and sediment showed positive correlations with outflow, while they correlated negatively with inflow and lake depth (p > 0.05). Local activities such as the discharge of domestic sewage, fishing waste and agricultural runoff significantly influence the distribution of polypropylene. Assessment of pollution factor, pollution risk index and pollution load index values at the sampling sites confirmed the presence of MPs, with values above 1. This study is a baseline database that provides a comprehensive understanding of MP pollution in the freshwater ecosystem of Bangladesh, particularly in a rural recreational lake. A crucial next step is to explore ecotoxicological mechanisms, legislative measures and future research challenges triggered by MP pollution., 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 Inc. All rights reserved.)

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., (© 2024. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Groundwater is an essential resource in the Sundarban regions of India and Bangladesh, but its quality is deteriorating due to anthropogenic impacts. However, the integrated factors affecting groundwater chemistry, source distribution, and health risk are poorly understood along the Indo-Bangla coastal border. The goal of this study is to assess groundwater chemistry, associated driving factors, source contributions, and potential non-carcinogenic health risks (PN-CHR) using unsupervised machine learning models such as a self-organizing map (SOM), positive matrix factorization (PMF), ion ratios, and Monte Carlo simulation. For the Sundarban part of Bangladesh, the SOM clustering approach yielded six clusters, while it yielded five for the Indian Sundarbans. The SOM results showed high correlations among Ca 2+ , Mg 2+ , and K + , indicating a common origin. In the Bangladesh Sundarbans, mixed water predominated in all clusters except for cluster 3, whereas in the Indian Sundarbans, Cl - -Na + and mixed water dominated in clusters 1 and 2, and both water types dominated the remaining clusters. Coupling of SOM, PMF, and ionic ratios identified rock weathering as a driving factor for groundwater chemistry. Clusters 1 and 3 were found to be influenced by mineral dissolution and geogenic inputs (overall contribution of 47.7%), while agricultural and industrial effluents dominated clusters 4 and 5 (contribution of 52.7%) in the Bangladesh Sundarbans. Industrial effluents and agricultural activities were associated with clusters 3, 4, and 5 (contributions of 29.5% and 25.4%, respectively) and geogenic sources (contributions of 23 and 22.1% in clusters 1 and 2) in Indian Sundarbans. The probabilistic health risk assessment showed that NO 3 - poses a higher PN-CHR risk to human health than F - and As, and that potential risk to children is more evident in the Bangladesh Sundarban area than in the Indian Sundarbans. Local authorities must take urgent action to control NO 3 - emissions in the Indo-Bangla Sundarbans region., 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.)

This review paper exhibits the underexplored realm of heavy metal contamination and associated risks in sea cucumbers (SCs), which hold significant importance in traditional Asian marine diets and are globally harvested for the Asian market. The assessment focuses on heavy metals (HMs) presence in various SC species, revealing a global trend in HMs concentrations across anatomical parts: Fe > Zn > As > Cu > Hg > Pb > Mn > Cr > Ni > Cd. Specific species, such as Eupentacta fraudatrix, Holothuria mammata, Holothuria polii, Holothuria tubulosa, and Holothuria atra, exhibit heightened arsenic levels, while Stichopus herrmanni raises concerns with mercury levels, notably reaching 3.75 mg/kg in some instances, posing potential risks, particularly for children. The study sheds light on anthropogenic activities such as cultivation, fishing, and shipping, releasing HMs into marine ecosystems and thereby threatening ocean and coastal environments due to the accumulation and toxicity of these elements. In response to these findings, the paper suggests SCs as promising bioindicator species for assessing metal pollution in marine environments. It underscores the adverse effects of human actions on sediment composition and advocates for ongoing monitoring efforts both at sea and along coastlines., Competing Interests: Declaration of competing interest The authors claim that the results of this investigation were not influenced by any known conflicting financial or personal interests., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Groundwater salinization in coastal aquifers is a major socioeconomic challenge in Oman and many other regions worldwide due to several anthropogenic activities and natural drivers. Therefore, assessing the salinization of groundwater resources is crucial to ensure the protection of water resources and sustainable management. The aim of this study is to apply a novel approach using predictive optimized ensemble trees-based (ETB) machine learning models, namely Catboost regression (CBR), Extra trees regression (ETR), and Bagging regression (BA), at two levels of modeling strategy for predicting groundwater TDS as an indicator for seawater intrusion in a coastal aquifer, Oman. At level 1, ETR and CBR models were used as base models or inputs for BA in level 2. The results show that the models at level 1 (i.e., ETR and CBR) yielded satisfactory results using a limited number of inputs (Cl, K, and Sr) from a few sets of 40 groundwater wells. The BA model at level 2 improved the overall performance of the modeling by extracting more information from ETR and CBR models at level 1 models. At level 2, the BA model achieved a significant improvement in accuracy (MSE = 0.0002, RSR = 0.062, R 2  = 0.995 and NSE = 0.996) compared to each individual model of ETR (MSE = 0.0007, RSR = 0.245, R 2  = 0.98 and NSE = 0.94), and CBR (MSE = 0.0035, RSR = 0.258, R 2  = 0.933 and NSE = 0.934) at level 1 models in the testing dataset. BA model at level 2 outperformed all models regarding predictive accuracy, best generalization of new data, and matching the locations of the polluted and unpolluted wells. Our approach predicts groundwater TDS with high accuracy and thus provides early warnings of water quality deterioration along coastal aquifers which will improve water resources sustainability., 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 Ltd. All rights reserved.)

Evapotranspiration (ETo) is a complex and non-linear hydrological process with a significant impact on efficient water resource planning and long-term management. The Penman-Monteith (PM) equation method, developed by the Food and Agriculture Organization of the United Nations (FAO), represents an advancement over earlier approaches for estimating ETo. Eto though reliable, faces limitations due to the requirement for climatological data not always available at specific locations. To address this, researchers have explored soft computing (SC) models as alternatives to conventional methods, known for their exceptional accuracy across disciplines. This critical review aims to enhance understanding of cutting-edge SC frameworks for ETo estimation, highlighting advancements in evolutionary models, hybrid and ensemble approaches, and optimization strategies. Recent applications of SC in various climatic zones in Bangladesh are evaluated, with the order of preference being ANFIS > Bi-LSTM > RT > DENFIS > SVR-PSOGWO > PSO-HFS due to their consistently high accuracy (RMSE and R 2 ). This review introduces a benchmark for incorporating evolutionary computation algorithms (EC) into ETo modeling. Each subsection addresses the strengths and weaknesses of known SC models, offering valuable insights. The review serves as a valuable resource for experienced water resource engineers and hydrologists, both domestically and internationally, providing comprehensive SC modeling studies for ETo forecasting. Furthermore, it provides an improved water resources monitoring and management plans., 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 Ltd. All rights reserved.)

In this study, microplastic (MP) pollution in the coastal sediments and tidal waters of Bushehr province in the Persian Gulf was comprehensively investigated. The sampling stations were selected based on their proximity to various human activities in January and February 2022, such as tourism, fishing, urban development and industry. The results showed that the abundance of MP associated with different human activities varied. The highest concentrations were observed near the petrochemical industry in Asaluyeh, followed by the densely populated Bushehr and the fishing port of Dayyer. Other areas such as Ganaveh, Deylam and Mand also showed varying levels of MP contamination. The average MP concentration was 1.67 × 104 particles/km 2 in surface water and 1346.67 ± 601.69 particles/kg in dry sediment. Fiber particles were in the majority in both sediment and water samples, mainly black. The sediment samples had a size range of 100-500 μm (41.34 %), while the water samples were between 500 and 1000 μm (33.44 %). The main polymers found were polyethylene (PE) and polypropylene (PP). This assessment highlights the widespread problem of microplastic pollution in the coastal and intertidal zones of Bushehr province in the Persian Gulf., 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 Ltd. All rights reserved.)

Due to its harmful effects on ecosystems and human health, microplastic (MP) pollution has become a significant environmental problem on a global scale. Although MPs' pollution path and toxic effects on marine habitats have been examined worldwide, the studies are limited to the rare biodiversity estuary region of Hatiya Island from the northern Bay of Bengal. This study aimed to investigate the MP pollution path and its influencing factors in estuarine sediments and water in rare biodiversity Hatiya Island in the northern Bay of Bengal. Sixty water and sediment samples were collected from 10 sampling sites on the Island and analyzed for MPs. The abundance of MPs in sediment ranged from 67 to 143 pieces/kg, while the abundance in water ranged from 24.34 to 59 pieces/m 3 . The average concentrations of MPs in sediment and water were 110.90 ± 20.62 pieces/kg and 38.77 ± 10.09 pieces/m 3 , respectively. Most identified MPs from sediment samples were transparent (51%), while about 54.1% of the identified MPs from water samples were colored. The fragment was the most common form of MP in both compartments, with a value of 64.6% in sediment samples and 60.6% in water samples. In sediment and water samples, almost 74% and 80% of MP were <0.5 mm, respectively. Polypropylene (PP) was the most abundant polymer type, accounting for 51% of all identified polymers. The contamination factor, pollution load index, polymer risk score, and pollution risk score values indicated that the study area was moderately polluted with MPs. The spatial distribution patterns and hotspots of MPs echoed profound human pathways. Based on the results, sustainable management strategies and intervention measures were proposed to reduce the pollution level in the ecologically diverse area. This study provides important insights into evaluating estuary ecosystem susceptibility and mitigation policies against persistent MP issues., Competing Interests: Declaration of Competing Interest All authors certify that they have no affiliations with or involvement in any organization or entity with any financial or non-financial interest in the subject matter or materials discussed in this manuscript., (Copyright © 2023 Elsevier B.V. All rights reserved.)

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., Competing Interests: Declaration of Competing Interest All authors certify that they have no affiliations with or involvement in any organization or entity with any financial or non-financial interest in the subject matter or materials discussed in this manuscript., (Copyright © 2023 Elsevier B.V. All rights reserved.)

Water contamination undermines human survival and economic growth. Water resource protection and management require knowledge of water hydrochemistry and drinking water quality characteristics, mechanisms, and factors. Self-organizing maps (SOM) have been developed using quantization and topographic error approaches to cluster hydrochemistry datasets. The Piper diagram, saturation index (SI), and cation exchange method were used to determine the driving mechanism of hydrochemistry in both surface and groundwater, while the Gibbs diagram was used for surface water. In addition, redundancy analysis (RDA) and a generalized linear model (GLM) were used to determine the key drinking water quality parameters in the study area. Additionally, the study aimed to utilize Explainable Artificial Intelligence (XAI) techniques to gain insights into the relative importance and impact of different parameters on the entropy water quality index (EWQI). The SOM results showed that thirty neurons generated the hydrochemical properties of water and were organized into four clusters. The Piper diagram showed that the primary hydrochemical facies were HCO 3 - -Ca 2+ (cluster 4), Cl---Na + (all clusters), and mixed (clusters 1 and 4). Results from SI and cation exchange show that demineralization and ion exchange are the driving mechanisms of water hydrochemistry. About 45 % of the studied samples are classified as "medium quality"," that could be suitable as drinking water with further refinement. Cl - may pose increased non-carcinogenic risk to adults, with children at double risk. Cluster 4 water is low-risk, supporting EWQI findings. The RDA and GLM observations agree in that Ca 2+ , Mg 2+ , Na + , Cl - and HCO 3 - all have a positive and significant effect on EWQI, with the exception of K + . TDS, EC, Na+, and Ca 2+ have been identified as influencing factors based on bagging-based XAI analysis at global and local levels. The analysis also addressed the importance of SO 4 , HCO 3 , Cl, Mg 2+ , K+, and pH at specific locations., 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. Published by Elsevier B.V.)

Plastic pollution has emerged as a global challenge affecting ecosystem health and biodiversity conservation. Terrestrial environments exhibit significantly higher plastic concentrations compared to aquatic systems. Micro/nano plastics (MNPs) have the potential to disrupt soil biology, alter soil properties, and influence soil-borne pathogens and roundworms. However, limited research has explored the presence and impact of MNPs on aquaculture systems. MNPs have been found to inhibit plant and seedling growth and affect gene expression, leading to cytogenotoxicity through increased oxygen radical production. The article discusses the potential phytotoxicity process caused by large-scale microplastics, particularly those unable to penetrate cell pores. It also examines the available data, albeit limited, to assess the potential risks to human health through plant uptake., 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 The Authors. Published by Elsevier Inc. All rights reserved.)

This study examined coastal aquifer vulnerability to seawater intrusion (SWI) in the Shiramin area in northwest Iran. Here, six types of hydrogeological data layers existing in the traditional GALDIT framework (TGF) were used to build one vulnerability map. Moreover, a modified traditional GALDIT framework (mod-TGF) was prepared by eliminating the data layer of aquifer type from the GALDIT model and adding the data layers of aquifer media and well density. To the best of our knowledge, there is a research gap to improve the TGF using deep learning algorithms. Therefore, this research adopted the Convolutional Neural Network (CNN) as a new deep learning algorithm to improve the mod-TGF framework for assessing the coastal aquifer vulnerability. Based on the findings, the CNN model could increase the performance of the mod-TGF by >30 %. This research can be a reference for further aquifer vulnerability studies., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Ata Allah Nadiri reports financial support was provided by Iran National Science Foundation (INSF). Ata Allah Nadiri reports financial support was provided by University of Tabriz. Ata Allah Nadiri reports a relationship with University of Tabriz that includes: board membership., (Copyright © 2023. Published by Elsevier Ltd.)

Contamination of fish with metals is a worldwide consumer safety concern. In this study, three metals such as arsenic (As), chromium (Cr), and lead (Pb) were measured in two commonly consumed fish species Oreochromis niloticus (Tilapia) and Pangasianodon hypophthalmus (Pangasius) that are commercially farmed. The concentration of the metals studied was found within the permissible limits. The concentrations of As, Cr, and Pb in tilapia fluctuated, ranging from not detected (ND) to 0.114 mg/kg, ND to 0.009 mg/kg, and ND to 0.085 mg/kg, respectively. For Pangasius, the concentrations were in the range of 0.014 to 0.118 mg/kg for As, ND to 0.02 mg/kg for Cr, and ND to 0.047 mg/kg for Pb. Hierarchical clustering revealed that As was possibly taken up by leachate and groundwater, while Cr and Pb were from contaminated feed. The results of the calculations for estimated daily intake, target hazard quotient, hazard index, and carcinogenic risk made it clear that consumption of the fish studied does not have a significant adverse effect on consumer health. In conclusion, the contamination levels of farmed tilapia and Pangasius sold in the study area are within acceptable limits, but regular monitoring is required to ensure safe production., (© 2023. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

Studying total soil carbon (STC), which encompasses organic (SOC) and inorganic carbon (SIC), as well as investigating the influence of soil carbon on other soil properties, is crucial for effective global soil carbon management. This knowledge is invaluable for evaluating carbon sequestration, although its scope is currently limited. Boosting soil carbon sequestration, particularly in arid regions, has direct and indirect implications for achieving over four Sustainable Development Goals: mitigating hunger, extreme poverty, enhancing environmental preservation, and addressing global climate concerns. Research into changes within SOC and SIC across surface and subsurface soils was conducted on aeolian deposits. In this specific case study, two sites sharing similar climates and conditions were chosen as sources of wind-blown sediment parent material. The aim was to discern variations in SOC, SIC, and STC storage in surface and subsurface soils between Sistan and Baluchistan Province (with rapeseed and date orchard cultivation) and Kerman Province (with maize cultivation) in southeastern Iran. The findings highlighted an opposing pattern in SOC and storage concerning soil depth, unlike SIC. The average SOC content was higher in maize cultivation (0.2%) compared to date orchard and rapeseed cultivation (0.11%), attributed to the greater evolution of these arid soils (aridisols) in comparison to the other region (entisols). Conversely, SIC content in the three soil uses demonstrated minimal variation. The mean STC storage was greater in maize cultivation (60.35 Mg ha -1 ) than in date orchard (54.67 Mg ha -1 ) and rapeseed cultivation (53.42 Mg ha -1 ). Within the examined drylands, SIC, originating from aeolian deposits and soil processes, assumes a more prominent role in total carbon storage than SOC, particularly within subsurface soils. Notably, over 90% of total carbon storage exists in the form of inorganic carbon in soils., (© 2023. The Author(s).)

Global production of plastics has increased dramatically in recent decades and is considered a major threat to marine life and human health due to their stability, persistence, and potential to move through food chains. The study was conducted to detect, identify and quantify microplastics (MP) in the gastrointestinal tract (GI) of some commercial fish species in the North Persian Gulf in Bushehr Province: Psettodes erumei, Sphyraena jello, Sillago sihama, Metapenaeus affinis and Portunus segnis. A total of 216 plastic particles were collected from 102 individuals (72.68% of all sampled individuals; MP prevalence of 85.1% for M. affinis, 80% for P. segnis, 70% for P.erumei, 60.3% for S.sihama, 45.2% for S.jello). The average number of microplastics per organism was 2.26 ± 0.38 MP/ind (considering only species that ingested plastic, n = 102) and 1.51 ± 0.40 pieces/ind (considering all species studied, n = 140). Microfibers accounted for 58.49% of the total microplastics, followed by fragments (33.02%) and pellets (8.49%). The most common color of microplastic was black (52.83%), followed by blue (22.64%) and transparent (15.09%). The length of microplastic ranged from 100 to 5000 μm with an average of 854 ± 312 μm. Microplastics were significantly (p < 0.05) abundant in two shrimp studied: M. affinis and P. segnis (plastic in 80% of individuals studied) and to a lesser extent in the pelagic barracuda fish S. jello (plastic in 45% of individuals studied). The main synthetic polymers identified by Fourier transform infrared spectroscopy (FTIR) were polyethylene (38%), polypropylene (24%), polystyrene (17%), polyethylene terephthalate (11%) and polyamide (10%). The pollutant load index and lifetime accumulation index were calculated to identify the most polluted species and their toxicity to human health. The white shrimp M. affinis was identified as the most polluted and toxic species for MP based on PLI. The present study can provide valuable data for further research and a background for the control and monitoring of this pollutant in the coastal environment of Bushehr province., 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 Ltd. All rights reserved.)

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 +, Ca 2+ , Cl - , K + , and HCO 3 - 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 Mg 2+ 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., 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 Inc. All rights reserved.)

The main challenge of the twenty-first century is to find a balance between environmental sustainability and crop productivity in a world with a rapidly growing population. Soil health is the backbone of a resilient environment and stable food production systems. In recent years, the use of biochar to bind nutrients, sorption of pollutants, and increase crop productivity has gained popularity. This article reviews key recent studies on the environmental impacts of biochar and the benefits of its unique physicochemical features in paddy soils. This review provides critical information on the role of biochar properties on environmental pollutants, carbon and nitrogen cycling, plant growth regulation, and microbial activities. Biochar improves the soil properties of paddy soils through increasing microbial activities and nutrient availability, accelerating carbon and nitrogen cycle, and reducing the availability of heavy metals and micropollutants. For example, a study showed that the application of a maximum of 40 t ha -1 of biochar from rice husks prior to cultivation (at high temperature and slow pyrolysis) increases nutrient utilization and rice grain yield by 40%. Biochar can be used to minimize the use of chemical fertilizers to ensure sustainable food production., 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 The Authors. Published by Elsevier Inc. All rights reserved.)

Chennai, the capital city of Tamil Nadu in India, has experienced several instances of severe flooding over the past two decades, primarily attributed to persistent heavy rainfall. Accurate mapping of flood-prone regions in the basin is crucial for the comprehensive flood risk management. This study used the GIS-MCDA model, a multi-criteria decision analysis (MCDA) model that incorporated geographic information system (GIS) technology to support decision making processes. Remote sensing, GIS, and analytical hierarchy technique (AHP) were used to identify flood-prone zones and to determine the weights of various factors affecting flood risk, such as rainfall, distance to river, elevation, slope, land use/land cover, drainage density, soil type, and lithology. Four groups (zones) were identified by the flood susceptibility map including high, medium, low, and very low. These zones occupied 16.41%, 67.33%, 16.18%, and 0.08% of the area, respectively. Historical flood events in the study area coincided with the flood risk classification and flood vulnerability map. Regions situated close to rivers, characterized by low elevation, slope, and high runoff density were found to be more susceptible to flooding. The flood susceptibility map generated by the GIS-MCDA accurately described the flood-prone regions in the study area., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

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., Competing Interests: Declaration of competing interest All authors certify that they have no affiliations with or involvement in any organization or entity with any financial or non-financial interest in the subject matter or materials discussed in this manuscript., (Copyright © 2023 Elsevier B.V. All rights reserved.)

Understanding the impact of urbanization on groundwater quality is critical. Effective water management requires understanding the relationship between land use and water quality. The study's goals were to compare the effects of land use, identify the types of land that impact hydrochemistry, and define how different land use affects water quality. For this purpose, the comparative relationship between groundwater quality, land use classes and landscape metrics were established for the years 2016 and 2021. Water samples were collected from 42 wells, and different hydro-chemical variables were considered to calculate the water quality index (WQI). The WQI value in 2016 ranged from 26.49 to 151.03 and 29.65 to 155.62 in 2021. The results indicate that the water quality in most parts of the study area is moderate for drinking and domestic purpose use. The google earth engine platform was used and radiometrically corrected and orthorectified Sentinel-2 satellite images were processed to classify land use classes for selected years. Five buffer zones were established within a 2-km watershed along each well site, and the effects of land use types and landscape metrics on water quality in the buffer zones were analyzed. Results revealed that the effects of land use types on water quality were mainly reflected in buffer 1 (B1), buffer 4 (B4), buffer 5 (B5) in 2016 and B1, buffer 3 (B3), and B5 in 2021. The impacts of landscape-level metrics on water quality are mainly reflected in buffer 2 (B2) and B3 in 2021, while at the class-level, they are mainly reflected in B1 and B4 in 2021. The redundancy analysis revealed that different hydro-chemical variables behaved differently with the land use classes and landscape metrics in the various buffer zones., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

In the race for economic development and prosperity, our earth is becoming more polluted with each passing day. Technological advances in agriculture and rapid industrialization have drastically polluted the two pillars of natural resources, land and water. Toxic chemicals and microbial contaminants/agents created by natural and anthropogenic activities are rapidly becoming environmental hazards (EH) with increased potential to affect the natural environment and human health. This review has attempted to describe the various agents (chemical, biological, and physical) responsible for environmental contamination, remediation methods, and risk assessment techniques (RA). The main focus is on finding ways to mitigate the harmful effects of EHs through the simultaneous application of remediation methods and RA for sustainable development. It is recommended to apply the combination of different remediation methods using RA techniques to promote recycling and reuse of different resources for sustainable development. The report advocates for the development of site-specific, farmer-driven, sequential, and plant-based remediation strategies along with policy support for effective decontamination. This review also focuses on the fact that the lack of knowledge about environmental health is directly related to public health risks and, therefore, focuses on promoting awareness of effective ways to reduce anthropological burden and pollution and on providing valuable data that can be used in environmental monitoring assessments and lead to sustainable development., (© 2023. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

The sustainability of agricultural practices is seriously threatened by the quality of water used for irrigation. This paper aims to evaluate the suitability of irrigation water and identify the region suitable for agricultural use in the Haor basin of Bangladesh using conventional irrigation indices such as sodium adsorption ratio (SAR), percent sodium (Na%), magnesium hazard ratio (MHR), permeability index (PI), and Kelly's ratio (KR), as well as novel irrigation indices such as, Shannon's entropy index for irrigation water quality (EWQ) and fuzzy logic index for irrigation water quality (FIWQI). The main influences of groundwater and surface water parameters on irrigation indices were predicted using automatic linear modeling (ALM). Forty water samples were collected from shallow tube wells, rivers, canals, ponds, and drainage systems within agricultural land sampled and analyzed for cations and anions. SAR and KR show that 52.5% and 60% of the samples exceeded the allowable level, respectively, indicating that they were unsuitable for irrigation. According to EWQI, about 55% of the analyzed samples were of good quality, while 45% were of medium quality. ALM predicted that KR (0.98), Na% (0.87), and MHR (0.14) were the main significant factors affecting SAR and KR. ALM shows that elevated sodium, magnesium, and calcium are the most important factors affecting irrigation water suitability. The EWQI and FIWQI integrated models showed that water from nearly 30% of the sampling sites would need treatment before use. A new suitability map created by overlaying all parameters showed that surface water and some groundwater in the western and southwestern portions are suitable for agriculture. The north-central part is unsuitable for irrigation due to excessive sodium and magnesium levels. This paper will highlight the irrigation pattern for regional water resource use, identify new suitable regions, and improve sustainable agricultural practices in the Haor basin., 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 Inc. All rights reserved.)

Poly- and perfluoroalkyl substances (PFAS) are a class of emerging organic contaminants that are impervious to standard physicochemical treatments. The widespread use of PFAS poses serious environmental issues. PFAS pollution of soils and water has become a significant issue due to the harmful effects of these chemicals both on the environment and public health. Owing to their complex chemical structures and interaction with soil and water, PFAS are difficult to remove from the environment. Traditional soil remediation procedures have not been successful in reducing or removing them from the environment. Therefore, this review focuses on new phytoremediation techniques for PFAS contamination of soils and water. The bioaccumulation and dispersion of PFAS inside plant compartments has shown great potential for phytoremediation, which is a promising and unique technology that is realistic, cost-effective, and may be employed as a wide scale in situ remediation strategy., 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 © 2022 Elsevier Inc. All rights reserved.)

In aquatic environments, microplastics (MPs) are pervasive which could have a considerable negative impact on the environment, organisms and pose a risk to human health. However, knowledge about the exposure and ecological risk of MPs in the coastal ecosystems of developing countries is limited. In this study, we analyzed salt samples from five commonly consumed processed and unprocessed sea salts of different commercial brands originated from 15 salt pans in Bangladesh to assess the abundance, characteristics and potential risks of MPs. The quantities of MPs in unprocessed salts (average 195 ± 56 item/kg) were higher than those in the processed salts (average 157 ± 34 item/kg). One-way analysis of variance (ANOVA) showed significant (p < 0.05) differences among the average numbers of MPs in both processed and unprocessed salts. MP levels in this study were 2-3 times higher than those reported from some other countries. Fiber-shaped and transparent MPs were dominant in both cases. MPs less than 0.5 mm in size were the most abundant in both unprocessed (58.2%) and processed (62.2%) salts. Fourier-transform infrared spectroscopy (FTIR) analysis confirmed five types of polymers, including polyethylene terephthalate (PET-35%), polypropylene (PP-27.5%), polyethylene (PE-25%), polystyrene (PS-10%), and Nylon (2.5%) in the studied salts. The sea salts were classified as potential hazard index (PHI) levels IV to V, indicating serious MP contamination, whereas potential ecological risk factor (E i ), potential ecological risk index (RI), and pollutant load index (PLI) indicated moderate levels of pollution of MPs. Domestic and municipal wastewater effluents to Bay of Bengal and fishing activities may attributed to presence of MPs in the sea salt. These findings can be used by consumers, salt industries and policy makers to reduce MPs levels during consumption, production and policymaking., 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 © 2022 Elsevier Ltd. All rights reserved.)

Water shortage in arid and semi-arid areas like Iran makes groundwater contamination a crucial issue. In the Khoy aquifer, NW Iran, contaminants (e.g., arsenic (As), nitrate (NO 3 - ), lead (Pb), and zinc (Zn)) may originate from both geological and anthropogenic sources. The objectives of the study are to (1) employ soft modeling framework to abstract available hydrogeochemical information into a perceptual model and (2) build a conceptual model using the risk cells (RCs) by applying the following two steps: (i) study Origin-Source-Pathways-Receptor-Consequence (OSPRC) as a risk system; and (ii) apply "soft modeling" as a set of diverse and classical tools including graphical representations, geological surveys, and multivariate statistical analysis to validate the information by evaluating their convergence or divergence behaviors among different tools used for investigating the groundwater contaminants. According to the perceptual model, the Khoy aquifer contains four RCs. RC4 (southern of plain) and RC2 (northern of the plain) contain high levels of As, while RC2 contains high amounts of Zn. In RC1 (northern of plain) and RC3 (middle of plain), a high concentration of Pb is detected, while in RC3 and RC4, there is a high concentration of NO 3 - . It was found that a soft modeling approach can only identify the dominant hydrogeochemical processes for each RC as a descriptive model, rather than the use of quantitative models if sufficient data are available., 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 © 2022 Elsevier Ltd. All rights reserved.)

The purpose of this study was to evaluate the metal concentrations in the Halda River in Bangladesh to determine the quality of the water and sediment in the natural spawning zone. Fe > Zn > Cr > Cd > Cu was the order of the metals in water, whereas Fe > Zn > Cd > Cu was the order in sediments. Almost all of the heavy metals in the water and sediment had been found within the established limits, with the exception of Cr and Fe in the river and Cu in the sediment. In the case of water, Cr vs. Zn was found to have the strongest correlation (r = 0.96). Due to the coagulation and adsorption processes, it was shown that Fe and Zn had a substantial correlation of 0.96, Cu and Cd of 0.91, and Cr of 0.78 with Zn. Hazard quotient values of Cd show the not potable nature of Halda river surface water and might give adverse health effects for all age groups except Cu and Zn. Pollution load index values indicated the uncontaminated nature of the river bottom sediments. Natural and human activities were the key factors influencing the accumulation and movement of heavy metals in the water and sediments. Contamination sources are industrial effluents, garbage runoff, farming operations, and oil spills from fishing vessels which are comparable according to multivariate statistical analysis. Ion exchange, absorption, precipitation, complexation, filtration, bio-absorption, redox reaction, and reverse osmosis were considered to be effective for the degradation of metal concentrations. The feasibility of the suggested metal reduction procedures has to be studied to know which is optimally appropriate for this river region. It is expected that this study could provide a useful suggestion to decrease the metal pollution in the river., (© 2022. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

Submarine groundwater discharge (SGD) is the groundwater flow from land to the sea across the seabed, and it includes both terrane freshwater and recirculated seawater in the sub-surface. This review (i) systematically evaluates findings of various quantification methodologies, (ii) examines the estimated SGD in scientific publications between 2000 and 2020, and (iii) quantitatively evaluates current situation of coastal zone management through the bibliometric analysis of research papers. Apart from enhancing the shortage of groundwater resources in coastal area, the SGD brings nutrients (nitrate and phosphate), toxic heavy metals, and organic compounds, and thus contaminate the seawater. Therefore, the improved understanding about location and quantity of global SGD is essential to conserve the coastal and ocean ecosystems., (© 2022. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

Remote sensing and GIS technology were very helpful to determine an appropriate location of freshwater storage in Amhara, Ethiopia. The techniques were used to investigate the impact of lithology, surface geomorphology, slope parameters, drainage flow, drainage density, lineament density, land cover parameters on relief, and aerial and linear features and to understand their interrelationships. Morphometric parameters such as mean stream length (Lsm), stream length ratio (RL), bifurcation ratio (Rb), mean bifurcation ratio (Rbm), relief ratio (Rh), drainage density (Dd), stream frequency (Fs), drainage texture (Rt), form factor (Rf), circularity ratio (Rc), and elongation ratio (Re) were calculated. Spatial maps of morphometric parameters were produced by using AHP (analytical hierarchy process) of ArcGIS 10.3. Final priority map was generated by the overlay of those parameters with five categories of poor (16.6%), low (41.63%), moderate (29.61%), high (8.88%), and very high (3.28%) storage locations. The map showed that this study area belonged to the low to moderate storage location. The results exhibit precision-based assessment of the suitability for the dam construction sites of 6, 7, and 9 sub-basin zones. The outcome of this study strengthens the knowledge of geospatial analysis for water resources vulnerability and also allows policymakers in this drought-prone area to sustainably manage water supplies., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

The study aims to determine the impact of global meteorological parameters on SARS-COV-2, including population density and initiation of lockdown in twelve different countries. The daily trend of these parameters and COVID-19 variables from February 15th to April 25th, 2020, were considered. Asian countries show an increasing trend between infection rate and population density. A direct relationship between the time-lapse of the first infected case and the period of suspension of movement controls the transmissivity of COVID-19 in Asian countries. The increase in temperature has led to an increase in COVID-19 spread, while the decrease in humidity is consistent with the trend in daily deaths during the peak of the pandemic in European countries. Countries with 65°F temperature and 5 mm rainfall have a negative impact on COVID-19 spread. Lower oxygen availability in the atmosphere, fine droplets of submicron size together with infectious aerosols, and low wind speed have contributed to the increase in total cases and mortality in Germany and France. The onset of the D614G mutation and subsequent changes to D614 before March, later G614 in mid-March, and S943P, A831V, D839/Y/N/E in April were observed in Asian and European countries. The results of the correlation and factor analysis show that the COVID-19 cases and the climatic factors are significantly correlated with each other. The optimum meteorological conditions for the prevalence of G614 were identified. It was observed that the complex interaction of global meteorological factors and changes in the mutational form of CoV-2 phase I influenced the daily mortality rate along with other comorbid factors. The results of this study could help the public and policymakers to create awareness of the COVID-19 pandemic., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Although groundwater (GW) potential zoning can be beneficial for water management, it is currently lacking in several places around the world, including Pakistan's Quetta Valley. Due to ever increasing population growth and industrial development, GW is being used indiscriminately all over the world. Recognizing the importance of GW potential for sustainable growth, this study used to 16 GW drive factors to evaluate their effectiveness by using six machine learning algorithms (MLA's) that include artificial neural networks (ANN), random forest (RF), support vector machine (SVM), K- Nearest Neighbor (KNN), Naïve Bayes (NB) and Extreme Gradient Boosting (XGBoost). The GW yield data were collected and divided into 70% for training and 30% for validation. The training data of GW yields were integrated into the MLA's along with the GW driver variables and the projected results were checked using the Receiver Operating Characteristic (ROC) curve and the validation data. Out of six ML algorithms, ROC curve showed that the XGBoost, RF and ANN models performed well with 98.3%, 96.8% and 93.5% accuracy respectively. In addition, the accuracy of the models was evaluated using the mean absolute error (MAE), root mean square error (RMSE), F-score and correlation-coefficient. Hydro-chemical data were evaluated, and the water quality index (WQI) was also calculated. The final GW productivity potential (GWPP) maps were created using the MLA's output and WQI as they identify the different classification zones that can be used by the government and other agenciesto locate new GW wells and provide a basis for water management in rocky terrain., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

Contamination of fish with heavy metals (Heavy metals) is one of the most severe environmental and human health issues. However, the contamination levels in tropical fishes from Bangladesh are still unknown. To this end, the evaluated concentrations of arsenic (As), chromium (Cr), cadmium (Cd), and lead (Pb) in 12 different commercially important fish species (Tenualosa ilisha, Gudusia chapra, Otolithoides pama, Setipinna phasa, Glossogobius giuris, Pseudeutropius atherinoides, Polynemus paradiseus, Sillaginopsis panijus, Corica soborna, Amblypharyngodon mola, Trichogaster fasciata, and Wallago attu) were collected from the Kirtankhola River assess human health risk for the consumers, both in the summer and winter seasons. Toxic metals surpassed the acceptable international limits in P. atherinoides, P. paradiseus, S. panijus, C. soborna, and W. attu. The target hazard quotient (THQ) revealed that non-carcinogenic health effects (HI < 1) for children and adults, and the carcinogenic risk (CR) indicated safety. Results show that children are more susceptible to carcinogenic and non-carcinogenic hazards from higher As. The multivariate analysis justified that heavy metals were from anthropogenic actions. The lessening of toxic metals might need strict rules and regulations as metal enrichment would continue to increase in this tidal river from both the anthropogenic and natural sources., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

Uranium (U) in groundwater is hazardous to human health, especially if it is present in drinking water. The semiarid regions of southern India chiefly depend on groundwater for drinking purposes. In this regard, a comprehensive sampling strategy was adopted to collect groundwater representing different lithologies of the region. The samples were collected in two different seasons and analysed for major and minor ions along with total U in the groundwater. Two samples during pre monsoon (PRM) and seven samples during post monsoon (POM) had U > 30 μgL -1 , which is above the World Health Organization's provisional guideline value. The high concentration of U (188 μgL -1 ) was observed in the alluvial formation though a few samples showed the release of U near the pink granite (39 μgL -1 ) and the concentration was low in the lateritic formation (10 μgL -1 ). The uranyl carbonato complexes UO 2 (CO 3 ) 2 2- and UO 2 (CO 3 ) 3 4- were associated with high pH which facilitated the transport of U into groundwater especially during POM. U 3 O 8 is the major form observed in groundwater compared to either UO 2 or UO 3 in the both seasons. The uranium oxides were observed to be more prevalent at the neutral pH. Though U concentration increases with pH, it is mainly governed by the redox conditions. The principal component analysis (PCA) analysis also suggested redox conditions in groundwater to be the major process facilitating the U release mechanism regardless of the season. The POM season has an additional source of U in groundwater due to the application of nitrogenous fertilizers in the alluvium region. Furthermore, redox mobilization factor was predominantly observed near the coastal region and in the agricultural regions. The process of infiltration of the fertilizer-induced U was enhanced by the agricultural runoff into the surface water bodies in the region. Health risk assessment was also carried out by determining annual effective dose rate, cancer mortality risk, lifetime average daily dose and hazard quotient to assess the portability of groundwater in the study area. Artificial recharge technique and reducing the usage of chemical based fertilizers for irrigation are suggested as sustainable plans to safeguard the vulnerable water resource in this region., (Copyright © 2021 Elsevier Inc. All rights reserved.)

The accurate evaluation of groundwater contamination vulnerability is essential for the management and prevention of groundwater contamination in the watershed. In this study, advanced multiple machine learning (ML) models of Radial Basis Neural Networks (RBNN), Support Vector Regression (SVR), and ensemble Random Forest Regression (RFR) were applied to determine the most accurate performance for the evaluation of groundwater contamination vulnerability. Eight vulnerability factors of DRASTIC-L were rated based on the modified DRASTIC model (MDM) and were used as input data. The adjusted vulnerability index (AVI) with nitrate values was used as output data for the modeling process. The performance of three models was verified using the statistical performance criteria of MAE, RMSE, r 2 , and ROC/AUC values. The ensemble RFR model showed the highest performance in comparison with standalone SVR and RBNN models. Specifically, ensemble RFR kept all promising solutions during the model performance due to its flexibility and robustness, and the vulnerability map obtained by the RFR model was more accurate for predicting the most vulnerable areas to contamination. It was concluded that ensemble RFR was a robust tool to enhance the evaluation of groundwater contamination vulnerability, and that it could contribute to environmental safety against groundwater contamination., (Copyright © 2021 The Authors. Published by Elsevier Inc. All rights reserved.)

The aim of the present study was to assess the status of heavy metal contamination and health risks associated with the use of water from River Gomti by millions of people. The value of the degree of contamination (C d ) was found to be '11.93', signifying 'high' risk levels due to heavy metal contamination in River Gomti across an approximate stretch of 61 km including upstream, midstream, and downstream locations of Lucknow city. The potential sources of heavy metal pollution in River Gomti include both sewage and industrial effluents, being transported by drains which overflow into the river. The heavy metals were found to have low mobility owing to the 'near neutral' pH of river water. The findings from the human health risk assessment revealed that the hazard index associated with non-carcinogenic risks exceeded the permissible limits at all sampling stations. The highest health risk was found at Bharwara sewage treatment plant discharge point, downstream of Lucknow city signifying the elevated levels of heavy metal in the river water post treatment from Bharwara STP. The results of carcinogenic risk assessment suggested that children were more susceptible to health risks, and immediate remedial measures are required to control the elevated levels of heavy metals at all the sampling stations., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

A reliable assessment of the aquifer contamination vulnerability is essential for the conservation and management of groundwater resources. In this study, a recent technique in artificial intelligence modeling and computational optimization algorithms have been adopted to enhance the groundwater contamination vulnerability assessment. The original DRASTIC model (ODM) suffers from the inherited subjectivity and a lack of robustness to assess the final aquifer vulnerability to nitrate contamination. To overcome the drawbacks of the ODM, and to maximize the accuracy of the final contamination vulnerability index, two levels of modeling strategy were proposed. The first modeling strategy used particle swarm optimization (PSO) and differential evolution (DE) algorithms to determine the effective weights of DRASTIC parameters and to produce new indices of ODVI-PSO and ODVI-DE based on the ODM formula. For strategy-2, a deep learning neural networks (DLNN) model used two indices resulting from strategy-1 as the input data. The adjusted vulnerability index in strategy-2 using the DLNN model showed more superior performance compared to the other index models when it was validated for nitrate values. Study results affirmed the capability of the DLNN model in strategy-2 to extract the further information from ODVI-PSO and ODVI-DE indices. This research concluded that strategy-2 provided higher accuracy for modeling the aquifer contamination vulnerability in the study area and established the efficient applicability for the aquifer contamination vulnerability modeling., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

We assessed groundwater pollution index (GPI) and groundwater quality of coastal aquifers from Tiruchendur in South India for drinking and irrigation by evaluating the physico-chemical parameters of 35 samples of mainly Na-Cl type in an area of 470 km 2 with respect to the World Health Organization (WHO) standard as well as by estimating different indices such as total hardness (TH), sodium percentage (Na%), magnesium ratio (MR), Kelley's ratio index (KR), potential salinity (PS), Langelier saturation index (LSI), residual sodium carbonate (RSC), sodium adsorption rate (SAR), permeability index (PI), and the irrigation water quality index (IWQI). Minimal influence of aquifer lithology and the dominant influence of evaporation on groundwater chemistry reflected the semi-arid climate of the study area. Electrical conductivity (EC) of about 89% of the samples across 418 km 2 exceeded the permissible limit and Ca values of 74% of samples, however, remained within the allowable limit for drinking. More chloride was caused by influx of seawater and salt leaching and higher K was due to excessive fertilizer usage for agriculture. The spatial distribution map created using inverse distance weighting (IDW) method shows that the suitable groundwater is present close to the river basin. GPI values between 0.40 and 4.7, with an average of 1.5, classify insignificant pollution in 43% of the study region and the groundwater suitable for drinking purposes. In addition, 17% of the groundwater samples are also marginally suitable for drinking. The irrigation water quality indices provided contradictory assessments. Indices of TH, Na%, MR, PS, and LSI suggested 32-95% of the samples as unsuitable for irrigation, whereas the indices of RSC, SAR, and PI grouped 72-100% samples as permissible for irrigation. The IWQI map, however, indicated that the groundwater from more than half of the study area are not apt for irrigation and the groundwater of about one-third of the area could only be applied to salt-resistant plants.

The enhanced assessment of groundwater contamination vulnerability is necessary for the management and conservation of groundwater resources because groundwater contamination has been much increased continuously in the world by anthropogenic origin. The purpose of this study is to determine the best model among three ANFIS-MOA models (the adaptive neuro-fuzzy inference system (ANFIS) combined with metaheuristic optimization algorithms (MOAs) such as genetic algorithm (GA), differential evolution algorithm (DE) and particle swarm optimization (PSO)) in assessing groundwater contamination vulnerability at a nitrate contaminated area. The Miryang City of South Korea was selected as the study area because the nitrate contamination was widespread in the city with two functions of urban and rural activities. Eight parameters (depth to water, net recharge, topographic slope, aquifer type, impact to vadose zone, hydraulic conductivity and landuse) were classified into the numerical ratings on basis of modified DRASTIC method (MDM) for the input variables of ANFIS-MOA models. The Original ANFIS, and 3 combined models of ANFIS-PSO, ANFIS-DE and, ANFIS-GA used 95 adjusted vulnerability indices (AVI) as the target data of training (70% data) and testing (30% data) processing. The performance of 4 models was evaluated by mean absolute errors (MAE), root mean square errors (RMSE), correlation coefficients (R), ROC/AUC curves and predicted AVI (PAVI) maps. The statistical results, spatial vulnerability maps and correlation coefficients between PAVIs and nitrate concentrations revealed that the order of model excellence was ANFIS-PSO, ANFIS-DE, ANFIS-GA, and Original ANFIS, and that ANFIS-PSO showed the highest performance in training and testing processing. The performance rates of ANFIS-MOA models were also compared with 10 recent popular worldwide models using the correlation coefficients between PVI and nitrate concentrations, and they were superior to other recent popular models. ANFIS-MOA models were also useful for resolving the subjectivity of physical and hydrogeological parameters in original DRASTIC method (ODM) and MDM. It is expected that ANFIS-PSO models will produce the excellent results in assessing groundwater contamination vulnerability and that they can greatly contribute to the groundwater security in other areas of the world as well as Miryang City of South Korea., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

A capability for aggregating risks to aquifers is explored in this paper for cases with sparse data exposed to anthropogenic and geogenic contaminants driven by poor/non-existent planning/regulation practices. The capability seeks 'Total Information Management' (TIM) under sparse data by studying hydrogeochemical processes, which is in contrast to Human Health Risk Assessment (HHRA) by the USEPA for using sample data and a procedure with prescribed parameters without deriving their values from site data. The methodology for TIM pools together the following five dimensions: (i) a perceptual model to collect existing knowledge-base; (ii) a conceptual model to analyse a sample of ion-concentrations to determine groundwater type, origin, and dominant processes (e.g. statistical, graphical, multivariate analysis and geological survey); (iii) risk cells to contextualise contaminants, where the paper considers nitrate, arsenic, iron and lead occurring more than three times their permissible values; (iv) 'soft modelling' to firm up information by learning from convergences and/or divergences within the conceptual model; and (v) study the processes within each risk cell through the OSPRC framework (Origins, Sources, Pathways, Receptors and Consequence). The study area comprises a series of patchy aquifers but HHRA ignores such contextual data and provides some evidence on both carcinogenic and non-carcinogenic risks to human health. The TIM capability provides a greater insight for the processes to unacceptable risks from minor ions of anthropogenic nitrate pollutions and from trace ions of arsenic, iron and lead contaminants.

Groundwater is the major freshwater resource in urban and rural areas of India that provides potable water. The quality evaluation of existing groundwater resources is vital and it's quantity for the optimal utilization and maintenance. The bounding coordinates of the selected study area of Tuticorin industrial area is between 8°38'24" and 8°51'0" latitude and between 77°54'36" and 78°12'36" longitude. Groundwater samples were collected as grid form at 40 locations during the pre- and postmonsoon seasons in the year 2017. Fe, Zn, Co, Pb, Mn, Ni, Cr, and Cu metal concentrations were determined using AAS (Atomic Absorption Spectrophotometer)-Perkin Elmer makes the model AAnalyst 200. Most of the groundwater samples were exceeded by the WHO 2008; USEPA 2009; and BIS 2012 guideline for drinking water standards. Further to assess the groundwater pollution status based on the heavy metal indices such as heavy metal pollution index (HPI), heavy metal evaluation index (HEI), degree of contamination (DOC), hazard quotient (HQ), hazard index (HI). Statistical analyses to found the appropriateness of groundwater for consumption and factors of contamination. The evaluation results indicate that groundwater is highly deteriorated and unsuitable for drinking in premonsoon period. While evaporation of water which increases the heavy metal concentration in premonsoon and dilution factor was affected in postmonsoon season. The increased concentration of heavy metals in groundwater might have been caused by evaporation, anthropogenic activities, and dissolution of rock formations which poses risk to human health. If this kind of growing contamination in the groundwater is unattended, it may lead to various health issues to the people from this region. Therefore, a consistent and sustainable water management should be carried out in this region in order to improve the groundwater quality.

Evaluation of the hydrogeochemical processes governing the heavy metal distribution and the associated health risk is important in managing and protecting the health of freshwater resources. This study mainly focused on the health impacts due to the heavy metals pollution in a known Cretaceous-Tertiary (K/T) contact region (Tiruchinopoly, Tamilnadu) of peninsular India, using various pollution indices, statistical, and geochemical analyses. A total of 63 samples were collected from the hard rock aquifers and sedimentary formations during southwest monsoon and analysed for heavy metals, such as Li, Be, Al, Rb, Sr, Cs, Ba, pb, Mn, Fe, Cr, Zn, Ga, Cu, As, Ni, and Co. Ba was the dominant element that ranged from 441 to 42,638 μg/l in hard rock aquifers, whereas Zn was the major element in sedimentary formations, with concentrations that ranged from 44 to 118,281 μg/l. The concentrations of Fe, Ni, Cr, Al, Cr, and Ni fell above the permissible limit in both of the formations. However, the calculated heavy metal evaluation index (HEI), heavy metal pollution index (HPI), and the degree of contamination (C d ) parameters were higher in the sedimentary formation along the contact zone of the K/T boundary. Excessive health risks from consumption of contaminated groundwater were mostly confined to populations in the northern and southwestern regions of the study area. Carcinogenic risk assessment suggests that there are elevated risks of cancer due to prolonged consumption of untreated groundwater. Ba, Sr, and Zn were found to be geochemically highly mobile due to the partitioning between the rock matrix and groundwater, aided by the formation of soluble carbonato-complexes. Factor analysis indicates that the metals are mainly derived from the host rocks and anthropogenic inputs are relatively insignificant. Overall, this study indicated that groundwater in K/T contact zones is vulnerable to contamination because of the favorable geochemical factors. Long-term monitoring of such contact zones is required to avert the potential health hazards associated with consumption of the contaminated groundwater.

Hydrogeochemical understanding of groundwater is essential for the effective management of groundwater. This study has been carried out to have concrete data for the seasonal variations in hydrogeochemistry of groundwater in central Tamilnadu forming a complex geological terrain with a varied lithology. A total of 244 groundwater samples were collected during four different seasons, viz, southwest monsoon (SWM), summer (SUM), postmonsoon (POM), and northeast monsoon (NEM) from bore wells. The physical parameters such as pH, temperature, TDS, ORP, humidity, and electrical conductivity (EC) were measured insitu, whereas major ions were analyzed in the lab adopting standard procedures. Overall, higher EC and NO 3 values were observed and exceeded the WHO permissible limit irrespective of seasons, except for NO 3 in SWM. Na and HCO 3 are the dominant cation and anion in the groundwater irrespective of seasons. The highest average values of Na (65.06 mg L -1 ) and HCO 3 (350.75 mg L -1 ) were noted during SWM. Statistical analysis was carried out to elucidate the hydrogeochemistry of the region. Initially, to understand the ionic relationship, correlation matrix was used followed by factor analysis for determination of major geochemical control and later factor scores were derived to understand the regional representations. An attempt has also been made to identify the samples influenced by multiple geochemical processes and to understand their spatial variation in the study period. Correlation of geochemical parameters reveals a excellent positive correlation between Ca and NO 3 in SUM, SWM, and NEM due to the dominant of anthropogenic sources and minor influence of weathering process. Strongly loaded factor scores are found to be mostly in the following order POM > NEM > SWM > SUM. Principal component analysis of different seasons indicates the interplay of natural weathering and anthropogenic factors. Overall, the predominant geochemical processes in this region, irrespective of seasons are weathering and, ion exchange and anthropogenic activities.

This study is to assess the hydrogeochemical characteristics of groundwater at the deltaic region of the Nakdong River Basin in the Busan Metropolitan City of Korea. The study area is covered by the Quaternary sedimentary deposits and the Cretaceous granites associated with unconformity. The thick sedimentary deposits consists of two aquifers, i.e., unconfined and confined aquifers on the basis of clay deposit. Groundwater samples were collected from seven boreholes: two from unconfined aquifer and five from confined aquifer systems during the wet season of 2017 year. ORP and DO indicates that the groundwater of the unconfined aquifer exists in the oxidization condition and that of the confined aquifer pertains in the reduction condition. Piper's trilinear diagram shows CaSO 4 type for groundwater of the unconfined aquifer, and NaCl type for that of the confined aquifer. Ionic concentrations of groundwater increase in the confined aquifer because of direct and reverse ion exchange processes. Carbonate weathering and evaporation are other mechanisms in the water-rock interaction. Saturation indices of dolomite and calcite are observed as oversaturated, while halite reveals undersaturation. Hierarchical cluster analysis (HCA) exhibits that cluster 1 and cluster 2 represents the properties of groundwater in unconfined and confined aquifers, respectively. Factor analysis shows that groundwater of the confined aquifer is much influenced by seawater, and includes heavy metals of iron and aluminum. Groundwater samples in unconfined and confined aquifers are located at the rock weathering and evaporation zones in the Gibbs diagram. Inverse geochemical modeling of PHREEQC code suggests that carbonate dissolution and ion exchange of major ions are the prevailing geochemical processes. This comprehensive research provides the distinguished hydrogeochemical characteristics of groundwater in confined and unconfined aquifer systems of the Nakdong River Basin in Busan City, Korea.

This study considered the temporal variations in rainfall and water level patterns as governing factors, which influence the geochemical process of coastal aquifer around Pondicherry, South India. Rainfall and water level data were collected from 2006 to 2016, which showed that the amount of rainfall from 2006 to 2011 was higher than that of 2011 to 2016. To understand the geochemical process governing groundwater, samples were collected during 2006 (n = 54), followed by 2011 (n = 93), and during 2016 (n = 63) as part of continuous observation. The major ions and stable isotopes (δ 18 O and δD) were analyzed in the samples to determine the geochemical variations. The predominant types were noted as Na-HCO 3 and Na-Cl; Ca-HCO 3 and Ca-Mg-Cl; and Na-Cl and Ca-Mg-Cl in 2006, 2011, and 2016, respectively. Saturation states of sulfate and carbonate minerals were compared for the study periods and it indicates that the saturation index (SI) values were increased from 2006 to 2011, but decreased from 2011 to 2016. PHREEQC inverse modeling revealed the predominance for the dissolution and leaching of carbonate minerals during increased rainy periods, and the increase of halite saturation during lesser rainfall period. AQUACHEM mixing studies suggested that geochemical signatures of 2006 and 2011 were preserved in samples of 2016 in different proportions. Considering the major factors, the main processes prevailing in the study area were inferred to be dissolution and leaching during 2006~2011 years and seawater intrusion along with ion exchange during 2011~2016 years. In all these periods of study, anthropogenic impact was also identified in the groundwater samples. Hence, this study revealed that the rainfall and water level gave a significant variation in the geochemical process of groundwater in the coastal aquifer system.