A review on sea cucumber (Bengali: Somuddro Sosha) as a bioindicator of heavy metal contamination and toxicity.

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.

Appraisal of groundwater quality for drinking and irrigation suitability using multivariate statistical approach in a rapidly developing urban area, Tirunelveli, India.

The quantitative and qualitative stress on groundwater resources has been witnessed across the globe. The current study assesses the groundwater quality of Tirunelveli district which faces the hazard of groundwater contamination through seepage of toxins, considering the open dumping of huge volumes of solid waste. The findings from this study confirmed the presence of more than 20% samples in the "poor to very poor" quality with high concentrations of TDS, Cl-, and NO3-, unfit for drinking, and other domestic purposes. The spatial distribution of TDS and NO3- highlighted the potential impact of solid waste dumping in the nearby landfill sites. K-means hierarchical clustering and multivariate analysis suggested that salinization and nitrate pollution was highly influenced by anthropogenic sources in comparison to geogenic sources. Rock water interaction and evaporation processes emerged as the two major dominant natural mechanisms controlling the groundwater chemistry. Four hydro-chemical facies were identified in the order of Ca-HCO3 > Ca-Mg-Cl > Na-Cl > mixed Ca-Na-HCO3. Thus, this study creates an urgent need of mitigation measures towards curbing and management of solid waste disposal and hence, the potential hazard of contaminant seepage into the groundwater.

Inferences on metal pollution in the natural spawning zone of Bangladesh river and pollution management strategies.

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.

A review on global status of fresh and saline groundwater discharge into the ocean.

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.

Microplastics from face masks: A potential hazard post Covid-19 pandemic.

The tremendous use of plastic products to averse the infection rate during Covid-19 pandemic has developed great pressure on the management and disposal systems of plastic waste. The compulsory use of face masks to curb the infection and prevent transmission of the virus has led to addition of millions of face masks into the terrestrial and marine environment. The current study attempts to assess and quantify the rate of infection in coherence with the annual usage of face masks in various nations across the globe. The ecological footprint of the plastic waste generated from used and discarded face masks along with their potential impacts have also been discussed. The current study has quantified the total annual face masks across thirty-six nations to be more than 1.5 million ton. The total estimated figure for annual plastic waste and microplastics in all these nations was ∼4.2 million tonnes and 9774 thousand tonnes, which emerges as a great threat to the global efforts towards reduction of plastic usage. The emergence of Covid-19 pandemic has modified the living habits with new enterprises being set up for Covid essential products, but the associated hazard of these products has been significantly ignored. Hence this study attempts to present a quantitative baseline database towards interpretation and understanding of the hazards associated with microplastics and increased dependence on plastic products.

Seasonal behavior and accumulation of some toxic metals in commercial fishes from Kirtankhola tidal river of Bangladesh - A health risk taxation.

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.

Comparative study of machine learning models for evaluating groundwater vulnerability to nitrate contamination.

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, r2, 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.

Site selection of check dams using geospatial techniques in Debre Berhan region, Ethiopia - water management perspective.

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.

Appraisal of COVID-19 lockdown and unlocking effects on the air quality of North India.

The COVID-19 pandemic lockdown supposedly provided a 'window' of reinstatement to natural resources including the air quality, but the scenario after the phased unlocking is yet to be explored. Consequently, here we evaluated the status of air quality during the 8th phase of unlocking of COVID-19 lockdown (January 2021) at three locations of North India. The first site (S1) was located at Punjab Agricultural University, Ludhiana-PPCB; the second site (S2) at Yamunapuram, Bulandshahr-UPPCB; and the third site (S3) at Okhla Phase-2, Delhi-DPCC. The levels of PM2.5 showed a significant increase of 525.2%, 281.2%, and 185.0% at sites S1, S2 and S3, respectively in the unlock 8 (January 2021), in comparison to its concentration in the lockdown phase. Coherently, the levels of PM10 also showed a prominent increase of 284.5%, 189.1%, and 103.9% at sites S3, S1, and S2, respectively during the unlock 8 as compared to its concentration in the lockdown phase. This rise in the concentration of PM2.5 and PM10 could be primarily attributed to the use of biomass fuel, industrial and vehicular emissions, stubble burning considering the agricultural activities at sites S1 and S2. Site S3 is a major industrial hub and has the highest population density among all three sites. Consequently, the maximum increase (295.7%) in the NO2 levels during the unlock 8 was witnessed at site S3. The strong correlation between PM2.5, PM10, and CO, along with the PM2.5/PM10 ratio confirmed the similar origin of these pollutants at all the three sites. The improvements in the levels of air quality during the COVID-19 lockdown were major overtaken during the various phases of unlocking consequent to the initiation of anthropogenic processes.

Modeling of aquifer vulnerability index using deep learning neural networks coupling with optimization algorithms.

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.

Environmental contamination by heavy metals and associated human health risk assessment: a case study of surface water in Gomti River Basin, India.

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 (Cd) 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.

Groundwater pollution index (GPI) and GIS-based appraisal of groundwater quality for drinking and irrigation in coastal aquifers of Tiruchendur, South India.

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 km2 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 km2 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.

Effect of COVID-19 lockdown on the water quality index of River Gomti, India, with potential hazard of faecal-oral transmission.

The COVID-19 lockdown has been reported as a "ventilator" for the reinstatement of natural resources across the globe. Hence, the present study attempts to evaluate the impact of COVID-19 lockdown on the water quality of River Gomti across its stretch of ~960 km through the assessment of 'Water Quality Index' (WQI). The study also highlights the potential risk of faecal-oral transmission of COVID-19 through intake of river water facing the issue of direct discharge of domestic sewage. A deterioration in the water quality was witnessed at ~69% sampling locations during the lockdown period (May 2020). Interestingly, none of the water samples during the pre-lockdown, lockdown, and post-lockdown periods across the whole stretch belonged to the "excellent" category (WQI<25). The DO levels fell across ~69% and ~88% of the sites during the lockdown and post-lockdown periods, respectively. Moreover, there was an increase in the BOD5 levels across ~69% and 75% of the sites during lockdown and post-lockdown periods, respectively. These findings indicate that the release of sewage without or with partial treatment is a chief contributor of water pollution in the groundwater fed River Gomti. Thereby, highlighting the possible risk of faecal-oral transmission of the corona virus, and creating a major concern for the residents across its stretch. The urban sprawl and riverfront development in Lucknow city also emerge as potential causes of water quality deterioration in River Gomti, considering that the water quality at five sites within the city was under the "unfit" category regardless of the lockdown situation. Thus, the urgent need of management of domestic sewage release into the river and further research on the potential risk of faecal-oral transmission of COVID-19 have been suggested in the study.

ANFIS-MOA models for the assessment of groundwater contamination vulnerability in a nitrate contaminated area.

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.

Causes of heavy metal contamination in groundwater of Tuticorin industrial block, Tamil Nadu, India.

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.

An investigation to human health risks from multiple contaminants and multiple origins by introducing 'Total Information Management'.

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.

Processes and characteristics of hydrogeochemical variations between unconfined and confined aquifer systems: a case study of the Nakdong River Basin in Busan City, Korea.

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 CaSO4 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.