Groundwater Pollution and Human Health Risks in an Industrialized Region of Southern India: Impacts of the COVID-19 Lockdown and the Monsoon Seasonal Cycles

Appraising groundwater quality and probabilistic human health risks from fluoride-enriched groundwater using the pollution index of groundwater (PIG) and GIS: a case study of adama town and its vicinities in the central main Ethiopian rift valley

This research's main objective is to identify the level of contamination in drinking water in Adama town and its environs by employing PIG, GIS and HHRA. The physical-chemical parameters of groundwater were determined, and the results were compared to regional and global drinking water quality guidelines. The pH of groundwater is alkaline, and the contents of Ca2+, Na+, HCO3 -, and F- in the majority of samples surpassed the permissible drinking limit. The hydrochemical facies were identified in the following order: Ca-Mg-HCO3, Na-Ca-HCO3, and Na-HCO3. Cation exchange and Rock-water interaction are the major dominant natural mechanisms controlling groundwater chemistry. Using IDW interpolation methods with Arc GIS 10.8, spatial analysis of the physico-geochemical content of water divulged that TDS, pH, TH, EC, Mg2+, Ca2+, K+, Na+, Cl-, HCO3 -, F-, and SO4 2- all exhibit a positive trend in the direction of groundwater flow from the upland to the lowland (rift floor). As per PIG, the results show that 57%, 33%, 7% and 3% of the samples were found in the insignificant, low, moderate and high, correspondingly. The total hazard index (THI) is calculated from hazard quotients (HQIntake and HQDermal) results showing 83%, 73%, and 57% of the samples exceed the non-carcinogenic health threat of fluoride THI >1 in drinking water for children, women and men. Children are more susceptible to danger than either males or women, according to the THI data, based on body weights and consumption rates. Similarly, females are also more vulnerable to health risks than men.

Future groundwater potential mapping using machine learning algorithms and climate change scenarios in Bangladesh

The aim of the study was to estimate future groundwater potential zones based on machine learning algorithms and climate change scenarios. Fourteen parameters (i.e., curvature, drainage density, slope, roughness, rainfall, temperature, relative humidity, lineament density, land use and land cover, general soil types, geology, geomorphology, topographic position index (TPI), topographic wetness index (TWI)) were used in developing machine learning algorithms. Three machine learning algorithms (i.e., artificial neural network (ANN), logistic model tree (LMT), and logistic regression (LR)) were applied to identify groundwater potential zones. The best-fit model was selected based on the ROC curve. Representative concentration pathways (RCP) of 2.5, 4.5, 6.0, and 8.5 climate scenarios of precipitation were used for modeling future climate change. Finally, future groundwater potential zones were identified for 2025, 2030, 2035, and 2040 based on the best machine learning model and future RCP models. According to findings, ANN shows better accuracy than the other two models (AUC: 0.875). The ANN model predicted that 23.10 percent of the land was in very high groundwater potential zones, whereas 33.50 percent was in extremely high groundwater potential zones. The study forecasts precipitation values under different climate change scenarios (RCP2.6, RCP4.5, RCP6, and RCP8.5) for 2025, 2030, 2035, and 2040 using an ANN model and shows spatial distribution maps for each scenario. Finally, sixteen scenarios were generated for future groundwater potential zones. Government officials may utilize the study's results to inform evidence-based choices on water management and planning at the national level.

Thauera sp. for efficient nitrate removal in continuous denitrifying moving bed biofilm reactor

Thauera is the most widely found dominant denitrifying genus in wastewater. In earlier study, MBBR augmented with a specially developed denitrifying five-membered bacterial consortium (DC5) where Thauera was found to be the most abundant and persistent genus. Therefore, to check the functional potential of Thauera in the removal of nitrate-containing wastewater in the present study Thauera sp.V14 one of the member of the consortium DC5 was used as the model organism. Thauera sp.V14 exhibited strong hydrophobicity, auto-aggregation ability, biofilm formation and denitrification ability, which indicated its robust adaptability short colonization and nitrate removal efficiency. Continuous reactor studies with Thauera sp.V14 in 10 L dMBBR showed 91% of denitrification efficiency with an initial nitrate concentration of 620 mg L-1 within 3 h of HRT. Thus, it revealed that Thauera can be employed as an effective microorganism for nitrate removal from wastewater based on its performance in the present studies.

Investigating the impacts of heavy metal(loid)s on ecology and human health in the lower basin of Hungary's Danube River: A Python and Monte Carlo simulation-based study

This study aimed to determine the environmental and health risks of the heavy metal levels in the Danube River in Hungary. The metals, including Fe, Mn, Zn, Cu, Ni, Cr, Pb, and As, were measured in the period from 2013 to 2019. The Spearman correlation and heatmap cluster analysis were utilized to determine the origin of pollution and the factors that control surface water quality. Several indices, such as the heavy metal pollution index (HPI), metal index (MI), hazard quotient oral and dermal (HQ), hazard index oral and dermal (HI), and carcinogenic risk (CR), were conducted to evaluate the potential risks for the environment and human health. The values of the HPI were between the range of 15 < HPI < 30, which indicated moderate pollution; however, the MI results showed high pollution in Dunaföldvár and Hercegszántó cities. The ecological risk (RI < 30) and HI values (< 1) showed low environmental risks and non-carcinogenic impacts of the existing metals, either on adults or children. The mean CR value of oral arsenic was 2.2E-04 and 2.5E-04 during April-September and October-March, respectively, indicating that children were the most vulnerable to arsenic-carcinogenic oral effects. While lead's CR oral values for children during April-September exceeded the threshold of 1.0E-04, chromium's oral and dermal CR values for both adults and children were 2.08E-04, 6.11E-04, 1.97E-04, and 5.82E-04 during April-September and October-March, respectively. These results demonstrate the potential carcinogenic risks related to chromium exposure within the two pathways in Hungary and highlight the need for effective measures to mitigate these risks.

Probabilistic modelling is superior to deterministic approaches in the human health risk assessment: an example from a tribal stretch in central India

This case drew national attention in 2018. About 100 people died and more than 300 hospitalized in a span of few years in a village of 1200 people in a tribal stretch in central India. Medical teams visiting the area reported severe renal failure and blamed the local eating and drinking habits as causative factors. This human health assessment based on geochemical investigations finds nitrate (NO3-) and fluoride (F-) pollution as well in village's groundwater. Both deterministic and probabilistic techniques are employed to decipher the contamination pathways and extent of contamination. Source apportionments of NO3- and F- and their relationship with other ions in groundwater are carried out through chemometric modelling. Latent factors controlling the hydrogeochemistry of groundwater too are explored. While hazard quotients ([Formula: see text]) of the chemical parameters ([Formula: see text] and [Formula: see text]) identify ingestion as the prominent pathway, the calculated risk certainty levels (RCL) of the hazard index (HI) values above unity are compared between the deterministic and probabilistic approaches. Deterministic model overestimates the HI values and magnify the contamination problems. Probabilistic model gives realistic results that stand at infants ([Formula: see text] = 34.03%, [Formula: see text] = 24.17%) > children ([Formula: see text] = 23.01%, [Formula: see text] = 10.56%) > teens ([Formula: see text] = 13.17%, [Formula: see text] = 2.00%) > adults ([Formula: see text] = 11.62%, [Formula: see text] = 1.25%). Geochemically, about 90% of the samples are controlled by rock-water interaction with Ca2+-Mg2+-HCO3- (~ 56%) as the dominant hydrochemical facies. Chemometric modelling confirms Ca2+, Mg2+, HCO3-, F-, and SO42- to originate from geogenic sources, Cl- and NO3- from anthropogenic inputs and Na+ and K+ from mixed factors. The area needs treated groundwater for human consumption.

The Effect of the COVID-19 Pandemic on Environmental Health (Two Sides of the Same Coin): A Systematic Review

BACKGROUND

The outbreak of the COVID-19 pandemic in late 2019 has led to many changes such as reduced human activities and effects on the environment. There is no big picture of the effects of pandemics on the environment using related evidence.

OBJECTIVES

This study was conducted to investigate the effect of the COVID-19 pandemic on environmental health.

METHODS

A systematic search of English language studies was performed in major electronic databases; Web of Science, PubMed, Scopus, and Google scholar web search engine from December 2019 to February 2022. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) standard guidelines were used to follow up the review process. finally 58 articles entered the review procedure.

RESULTS

The results of indicate a significant reduction of air pollutants and improved air quality. It improved the water quality of some rivers, canals, and seas during the lockdown of the COVID-19 pandemic. The effects of this disease on the environment cannot be fully described yet.

CONCLUSION

In the short term, the amount of air, water, and coastal pollution has been reduced. few studies have examined the effects of pandemics on the environment in the long run, which paves the way for more researches.

COVID-19 pandemic lockdown modulation of physico-chemical parameters of surface water, Karamana river basin, Southwest India: A weighted arithmetic index and geostatistical perspective

The coronavirus disease or COVID-19 pandemic continues imposing restrictions on the human population from full-scale normal/routine activities all over the world. This study primarily spotlights the consequences of the COVID-19-pandemic-lockdown on physicochemical parameters of water (samples) of the Karamana river system (KRS) during the pre-monsoons (or January) of 2021 and 2022, using the Weighted Arithmetic Index method and Geostatistical analysis (ArcMap 10.2). Even though the Karamana river supported the water needs of the people during the past several decades, the quality of water deteriorated due to the rising population and consequent anthropogenic activities. Hence, it is imperative to evaluate the water quality during the post-COVID-19 lockdowns and document the spatial distribution of parameters listed in the BIS (Bureau of Indian standard) IS10500, 2012. This was accomplished by establishing a water quality index (WQI), Geostatistical analysis, and weighted overlay analysis (WOA). The estimated WQI suggested that about 45.11km2 (6.43%) area has declined from the excellent category of water quality between 2021 and 2022. Similarly, WOA results deciphered that the area under the poor category has drastically and negatively changed from 27.85 km2 (4.0%) to 60.42 km2 (8.6%) after revoking of lockdown restrictions. The lessons learned from syn-Covid-19, the spike or uptrend of the water quality compared to the past decades, offer ample scientific basis to policymakers, administrators, and environmentalists for restoration of river system health from huge anthropogenic stress.

Integrated machine learning-based model and WQI for groundwater quality assessment: ML, geospatial, and hydro-index approaches

The demands upon the arid area for water supply pose threats to both the quantity and quality of social and economic activities. Thus, a widely used machine learning model, namely the support vector machines (SVM) integrated with water quality indices (WQI), was used to assess the groundwater quality. The predictive ability of the SVM model was assessed using a field dataset for groundwater from Abu-Sweir and Abu-Hammad, Ismalia, Egypt. Multiple water quality parameters were chosen as independent variables to build the model. The results revealed that the permissible and unsuitable class values range from 36 to 27%, 45 to 36%, and 68 to 15% for the WQI approach, SVM method and SVM-WQI model respectively. Besides, the SVM-WQI model shows a low percentage of the area for excellent class compared to the SVM model and WQI. The SVM model trained with all predictors with a mean square error (MSE) of 0.002 and 0.41; the models that had higher accuracy reached 0.88. Moreover, the study highlighted that SVM-WQI can be successfully implemented for the assessment of groundwater quality (0.90 accuracy). The resulting groundwater model in the study sites indicates that the groundwater is influenced by rock-water interaction and the effect of leaching and dissolution. Overall, the integrated ML model and WQI give an understanding of water quality assessment, which may be helpful in the future development of such areas.

Using space-time scan statistic for studying the effects of COVID-19 in Punjab, Pakistan: a guideline for policy measures in regional agriculture

Pakistan is included in top 50 countries which are estimated to face serious agriculture and food deficiency related challenges due to the worldwide pandemic coronavirus 2019 (COVID-19). The aim of this study was to evaluate the effects of COVID-19 on food supply chain and agriculture in Punjab, Pakistan, by using space-time scan statistic (STSS). A survey was conducted at 720 points in different districts of the province. The STSS detected "active" and emerging clusters that are current at the end of our study area-particularly, 17 clusters were formed while adding the updated case data. Software ArcGIS 10.3 was used to find relative risk (RR) values; the maximum RR value was found to be 42.19 and maximum observed cases 53,265 during June 15-July 1, 2020. It was not always necessary that if the number of active cases in Punjab increased, there should be higher relative risk for more number of districts and vice versa. Due to the highest number of cases of COVID-19 and RR values during July, mostly farmers faced many difficulties during the cultivation of cotton and rice. Mostly farmers (72%) observed increase in prices of inputs (fertilizers and pesticides) during lockdown. If the supply chain of agriculture related inputs is disturbed, farmers may find it quite difficult to access markets, which could result in a decline in production and sales of crops and livestock in study area. It is suggested that to protect the food security and to decrease the effect of the lockdown, Punjab government needs to review food policy and analyse how market forces will respond to the imbalanced storage facilities and capacity, supply and demand and price control of products. The findings of this study can also help policy-makers to formulate an effective food security and agriculture adaptation strategy.

COVID-19 and Water Variables: Review and Scientometric Analysis

COVID-19 has changed the world since 2020, and the field of water specifically, boosting scientific productivity (in terms of published articles). This paper focuses on the influence of COVID-19 on scientific productivity with respect to four water variables: (i) wastewater, (ii) renewable water resources, (iii) freshwater withdrawal, and (iv) access to improved and safe drinking water. The field's literature was firstly reviewed, and then the maps were built, emphasizing the strong connections between COVID-19 and water-related variables. A total of 94 countries with publications that assess COVID-19 vs. water were considered and evaluated for how they clustered. The final step of the research shows that, on average, scientific productivity on the water topic was mostly conducted in countries with lower COVID-19 infection rates but higher development levels as represented by gross domestic product (GDP) per capita and the human development index (HDI). According to the statistical analysis, the water-related variables are highly significant, with positive coefficients. This validates that countries with higher water-related values conducted more research on the relationship with COVID-19. Wastewater and freshwater withdrawal had the highest impact on the scientific productivity with respect to COVID-19. Access to safe drinking water becomes insignificant in the presence of the development parameters.

Hydrogeochemical evolution and assessment of groundwater quality for drinking and irrigation purposes in the Gushegu Municipality and some parts of East Mamprusi District, Ghana

The Gushegu Municipality and the East Mamprusi District in Ghana are dominated by the Oti/Pendjari Group within the Voltaian Supergroup. The major rock types found in the area are quartzites, siltstones, conglomerates, and shales with minor occurrences of tillites, silexites, limestones, and barite-rich dolomites. The inhabitants of the area are mainly peasant farmers, and their activities might be influencing the groundwater chemistry, but little is known about the quality of the groundwater. Therefore, this study evaluated the suitability of groundwater resources in the Gushegu Municipality, and some parts of the East Mamprusi District in Ghana for domestic and irrigation uses, employing hydrogeochemical graphing, geochemical modelling, multivariate statistical analysis, and computation of water quality indices. Sodium (Na⁺), with concentrations ranging from 4.93 to 323 mg/L and a mean of 169 mg/L, is found to be the major cation in the groundwater, while bicarbonate (HCO₃^-), with concentrations ranging from 19.9 to 685 mg/L and a mean of 397 mg/L, is the major anion in the area. The dominant hydrochemical facies is the Na-HCO3 type, accounting for about 72.7% of the study area's groundwater and is influenced by silicate weathering, carbonate mineral dissolution, and ion exchange reactions. Other factors accounting for this dominance may be anthropogenic activities, including the dissolution and leaching of fertilizers from farmlands. Overall, this study reveals that the groundwater in the area is suitable for drinking based on the WQI classification. There are localized contaminations with respect to B and F^-, making the water in those areas unsuitable for drinking. Also, the groundwater in the area is unsuitable for irrigation purposes due to the high Na% values (43 to 99% with a mean of 86%), magnesium hazard values (1 to 312 with a mean of 88), and sodium adsorption ratio (0.57 to 42.4 with a mean of 12.7). All these indices exceed their respective standards for irrigation purposes.

Assessment of groundwater salinity using principal component analysis (PCA): a case study from Mewat (Nuh), Haryana, India

In the present study, principal component analysis (PCA) is used to investigate the processes controlling groundwater salinity in the Mewat (Nuh) district, Haryana, India. Twenty groundwater samples were collected from salinity-affected areas in the March-April months of years 2018 and 2019 and were analyzed for chemical variables pH, EC, Ca²⁺, Mg²⁺, Na⁺, K⁺, [Formula: see text], Cl^-, SO₄^2-, [Formula: see text], TDS, and total hardness. Three principal components were selected based on the eigen value, which explains 79.58% and 85.08% of the total variation in the years 2018 and 2019, respectively. The first principal component (PC-1) is identified with salinity, the second principal component (PC-2) with alkalinity, and the third principal component (PC-3) described the pollution. When the yearly comparison was made, the samples collected in 2019 were found to have an increased salinity compared to 2018, which shows an increased vulnerability to the aquifer of Mewat on account of the decline in rainfall recharge. It was also evident that declining recharge also triggered the recharge from other sources; thus, the impact of pollution is more pronounced in 2019 compared to 2018.

Comparative assessment of groundwater quality indices of Kannur District, Kerala, India using multivariate statistical approaches and GIS

The aim of the study was to determine the groundwater characteristics of rural and industrial zones in the Kannur region. In 2011, 25 groundwater data were collected from the centre for water resource development management (CWRDM), and in 2019, 25 groundwater samples from rural and near-industrial areas were collected and analysed for major anions (HCO₃-, CO₃^2-, Cl^-, NO₃- and SO₄^2-), and cations (TH, Ca²⁺, Mg²⁺, Na⁺, K⁺ and Fe²⁺) using APHA standards. To better understand the link between water quality parameters, multivariate statistical analysis approaches such as principal component analysis (PCA), hierarchical cluster analysis (HCA), correlation matrix analysis (CMA), and Pearson correlation bivariate one-tailed analysis (PCBOTA) were used to analyse the inter-relationship of data. The Inverse Distance Weighed (IDW) method was used to generate the spatial distribution of the groundwater quality index (GWQI). In 2011, the water quality index (WQI) value of groundwater samples was excellent at 24.42% and good at 54.14%, which were used for drinking purposes and moderate at 17.22% and poor at 4.22% for irrigation purposes in this study area. In 2019, excellent 21.62%, good 51.56% were used for drinking purpose, and moderate at 18.14%, and poor at 8.68% for irrigation purposes. By comparing the data with BIS and WHO standards, it is clear that groundwater in Kannur district is of good quality. In groundwater samples, the PCA eigen values were reported in 2011 (84.7%) and 2019 (73.4%) for statistical approaches. This study uses HCA and PCBOTA to analyse the elements, resulting in a better understanding of groundwater quality development. GIS based WQI maps were obtained and utilised to gain a better knowledge of the study area's past and present water quality status. We observed that the quality of groundwater in the study region's north-western portion is insufficient for drinking water.

Human health risk assessment of heavy metal and pathogenic contamination in surface water of the Punnakayal estuary, South India

Variation in levels of toxic heavy metals in river system during the COVID-19 pandemic lockdown might potentially assist in development of a public health risk mitigation system associated with the water consumption. The water quality of Punnakayal estuary in the Thamirabarani River system from the south India, a vital source of water for drinking and domestic purposes, industrial usage, and irrigation was assessed here. A comparitive assessment of physico-chemical variables (pH, EC, TDS, DO, BOD, turbidity and NO₃), microbiological parameters (total coliform bacteria, fecal coliform bacteria, fecal streptococci and escherichia coli) and toxic metals (As, Cr, Fe, Cu, Zn, Cd, and Pb) suggested a decrease of 20% in the contaminant ratio during the lockdown period in comparison to the pre-lockdown period. The Health risk assessment models (HQ, HI, and TCR) highlighted carcinogenic and non-carcinogenic hazards for both children and adults through the ingestion and dermal adsorption exposures. The HI values for both As and Cr exceeded the acceptable limit (>1) during the lockdown period, but the potential risk for children and adults remained low in compaisio with the pre-lockdown period. Our results suggested that the Thamirabarani River system remained hostile to human health even during the lockdown period, and it requires regular monitoring through a volunteer water quality committee with private and government participations.

Interpreting the salinization and hydrogeochemical characteristics of groundwater in Dongshan Island, China

The groundwater salinization is a global problem that degrades water quality and endangers sustainable use of water resources, particularly in coastal areas. In this paper, 24 water samples were collected from 12 monitoring wells during the dry (January) and wet (June) seasons for analyzing the salinization and hydrogeochemical characteristics of groundwater in Dongshan Island of China through combined hydrogeochemical and multivariate statistical approaches. Results showed that groundwater in the study area is primarily Cl-Na and followed by Cl-Ca·Mg type in the dry season, Cl-Na and followed by Cl-Ca·Mg and HOC₃·Cl-Na type in the wet season. The groundwater chemistry is predominantly controlled by carbonate, gypsum, and silicate dissolution. However, some areas are strongly influenced by seawater intrusion, sewage infiltration and reverse ion exchange process. Around 40% of water samples from the dry season and 50% from the wet season are at injuriously, highly and severely saline levels while other samples at slightly and moderately saline levels, suggesting that groundwater in the area is partially recharged by seawater. Furthermore, the NO₃^-/Cl^- versus Cl^- diagram and principal component analysis (PCA) indicated nitrate pollution in groundwater that is subjected to anthropogenic activities such as domestic sewage, agricultural and industrial practices, which lead to degradation of groundwater quality in the area. The findings of this study provide helpful insights for understanding the genesis and hydrogeochemical evolution of groundwater in those coastal areas.

Water Quality and Water Pollution in Time of COVID-19: Positive and Negative Repercussions

On 11 March 2020, the World Health Organization declared the new COVID-19 disease a pandemic. Most countries responded with a lockdown to reduce its effects, which brought beneficial consequences to the environment in many regions, but the pandemic also raised a series of challenges. This review proposes an assessment of the COVID-19 pandemic positive and negative impacts on water bodies on different continents. By applying a search protocol on the Web of Science platform, a scientific bank of 35 compatible studies was obtained out of the 62 open-access articles that were initially accessible. Regarding the positive impacts, the SARS-CoV-2 monitoring in sewage waters is a useful mechanism in the promptly exposure of community infections and, during the pandemic, many water bodies all over the world had lower pollution levels. The negative impacts are as follows: SARS-CoV-2 presence in untreated sewage water amplifies the risk to human health; there is a lack of adequate elimination processes of plastics, drugs, and biological pollution in wastewater treatment plants; the amount of municipal and medical waste that pollutes water bodies increased; and waste recycling decreased. Urgent preventive measures need to be taken to implement effective solutions for water protection.

Comprehensive Groundwater Quality Analysis in Chronic Kidney Disease of Unknown Etiology (CKDu) Prevalence Areas of Sri Lanka to Investigate the Responsible Culprit

Chronic kidney disease of unknown etiology (CKDu) is a serious health problem in Sri Lanka especially among agricultural communities in dry zone since 19th century. In the present study, several water quality parameters were studied in well water samples and only four parameters, namely, hardness, cadmium level, fluoride level, and strontium level have shown a relationship with the CKDu prevalence. Higher percentage of well water samples collected from CKDu prevalent area in both pre and postmonsoon seasons have exceeded the WHO recommended levels of hardness. Further, water samples collected in postmonsoon seasons had significantly higher hardness than the well water samples collected in premonsoon season ( $P<0.05$ ). This may be due to the dissolution of calcium carbonate by water recharge. Moreover, cadmium and fluoride contents have exceeded the recommended levels in high-risk area during the premonsoon period. Furthermore, according to principal component analysis (PCA), four clusters were identified depending on the different levels of fluoride, cadmium, hardness, and strontium contents. The control area (Am) fell in to separate cluster with low contents of fluoride, cadmium, hardness, and strontium than in CKDu prevalent area. Since it has been found that the above species are directly involved in renal damage, it can be concluded that a synergetic effect of cadmium, fluoride, hardness, and strontium in well water may be a main cause for CKDu in Sri Lanka.

Impacts of COVID-19 lockdown on private domestic groundwater sample numbers, E. coli presence and E. coli concentration across Ontario, January 2020-March 2021: An interrupted time-series analysis

Approximately 1.5 million individuals in Ontario are supplied by private water wells (private groundwater supplies). Unlike municipal supplies, private well water quality remains unregulated, with owners responsible for testing, treating, and maintaining their own water supplies. The COVID-19 global pandemic and associated non-pharmaceutical interventions (NPIs) have impacted many environmental (e.g., surface water and air quality) and human (e.g., healthcare, transportation) systems over the past 15-months (January 2020 to March 2021). To date, the impact of these interventions on private groundwater systems remains largely unknown. Accordingly, the current study aimed to investigate the impact of a province-wide COVID-19 lockdown (late-March 2020) on health behaviours (i.e., private domestic groundwater sampling) and groundwater quality (via Escherichia coli (E. coli) detection and concentration) in private well water in Ontario, using time-series analyses (seasonal decomposition, interrupted time-series) of a large-spatio-temporal dataset (January 2016 to March 2021; N = 743,200 samples). Findings indicate that lockdown concurred with an immediate (p = 0.015) and sustained (p < 0.001) decrease in sampling rates, equating to approximately 2200 fewer samples received per week post-interruption. Likewise, a slightly decreased E. coli detection rate was observed approximately one month after lockdowns began (p = 0.003), while the proportion of "highly contaminated" samples (i.e., E. coli > 10 CFU/100 mL) was shown to increase within one month (p = 0.02), followed by a sustained decrease for the remainder of the year (May 2020-December 2020). Analyses strongly suggest that COVID-19 interventions resulted in discernible impacts on both well user behaviours and hydrogeological mechanisms. Findings may be used as an evidence-base for assisting policy makers, public health practitioners and private well owners in developing recommendations and mitigation strategies to manage public health risks during extreme and/or unprecedented future events.

Provincial and seasonal influences on heavy metals in the Noyyal River of South India and their human health hazards

This study was carried out to evaluate the heavy metals (Lead (Pb), Nickel (Ni), Chromium (Cr), Copper (Cu), Cadmium (Cd) and Zinc (Zn)) pollution in the Noyyal River of South India by collecting 130 river water samples (65 each in pre- and post-monsoon). The heavy metals were measured using Atomic Absorption Spectrophotometer (AAS). The data were used to calculate the associated health hazards for the inhabitants consume river water. Correlation analyses and average concentration of heavy metals denoted that post-monsoon metal concentrations were lesser compared to the pre-monsoon due to dilution effect. Modified Contamination Degree (MCD) indicated that 45% of pre-monsoon and 25% of post-monsoon samples were classified under extremely polluted category. Heavy metal pollution index (HPI) showed that all the regions fall under highly polluted category except 'Region I' where 20% of samples were under safe category during the pre-monsoon, whereas 9%,28%, 17% and 26% of samples in Regions I, II, III and IV were highly polluted during the post-monsoon season, respectively. Ecological Risk Index (ERI) revealed that high risks attained in Regions II (78%) and III (82%) during pre-monsoon, and reduced risks found in Regions II (28%) and III (45%) during post-monsoon season due to dilution by monsoon rainfall. Non-carcinogenic risks as inferred by the Hazard Index (HI) indicated that 78% and 52% of samples for infants, 75% and 49% of samples for teens and 71% and 45% of samples for adults exceeded the threshold limits of USEPA (HI > 1) and possessed risks during pre- and post-monsoon, respectively. The cancer risk assessment based on ingestion of heavy metals indicated that the order of risk is Ni > Cr > Cu. The HI for infants and teens was notably high to that of adults in both the seasons. This study will be useful to develop effective strategies for improving river water quality and to reduce human health hazards.

Implications of COVID-19 on global environmental pollution and carbon emissions with strategies for sustainability in the COVID-19 era

The impacts of COVID-19 on global environmental pollution since its onset in December 2019 require special attention. The rapid spread of COVID-19 globally has led countries to lock down cities, restrict traffic travel and impose strict safety measures, all of which have implications on the environment. This review aims to systematically and comprehensively present and analyze the positive and negative impacts of COVID-19 on global environmental pollution and carbon emissions. It also aims to propose strategies to prolong the beneficial, while minimize the adverse environmental impacts of COVID-19. It systematically and comprehensively reviewed more than 100 peer-reviewed papers and publications related to the impacts of COVID-19 on air, water and soil pollution, carbon emissions as well as the sustainable strategies forward. It revealed that PM2.5, PM10, NO2, and CO levels reduced in most regions globally but SO2 and O3 levels increased or did not show significant changes. Surface water, coastal water and groundwater quality improved globally during COVID-19 lockdown except few reservoirs and coastal areas. Soil contamination worsened mainly due to waste from the use of personal protective equipment particularly masks and the packaging, besides household waste. Carbon emissions were reduced primarily due to travel restrictions and less usage of utilities though emissions from certain ships did not change significantly to maintain supply of the essentials. Sustainable strategies post-COVID-19 include the development and adoption of nanomaterial adsorption and microbial remediation technologies, integrated waste management measures, "sterilization wave" technology and energy-efficient technologies. This review provides important insight and novel coverage of the environmental implications of COVID-19 in more than 25 countries across different global regions to permit formulation of specific pollution control and sustainability strategies in the COVID-19 and post-COVID-19 eras for better environmental quality and human health.

Hydrogeochemical assessment of groundwater quality and suitability for irrigation in the coastal part of Cuddalore district, Tamil Nadu, India

A study was undertaken to identify in the irrigational suitability of groundwater in the cuddalore district (coastal part), Tamil Nadu, India. An entire study, 132 shallow and deep groundwater samples was gathered during Pre monsoon period (PRM) year of 2017 and post monsoon (POM) period samples collected year of 2018. Rock water interaction, silicate weathering and domestic waste are dominant sources for the water quality in the study area. The groundwater classification and irrigational suitability of groundwater were performed for both seasons. From the results of Chloro-Alkaline Indices (CAI I), and Chloro-Alkaline Indices (CAI II), during both seasons and classes, the direct ions exchange processes are predominant when compare with reverse ions exchange processes. The r₁ and r₂ results represents that most of the samples found as saline sources as Na⁺ - SO₄^2- facies and performing with Deep Meteoric Percolation (DMP) than shallow meteoric percolation During PRM season, r₁ represents 65 (98%) samples for Na⁺ - SO₄^2- facies and 1 (2%) sample represents Na⁺ - HCO₃^- facies and during POM season, r₁ represents 63 (95%) samples for Na⁺ - SO₄^2- facies and 3 (5%) samples represent Na⁺ - HCO₃^- facies respectively. Irrigation water quality parameters like and satisfied the analysed water's irrigation suitability. However, according to MAR parameters, 5% of water samples were unsuitable for irrigation in PRM based on KR parameters, 41% of samples collected in the PRM season only were unsuitable for irrigation. The Wilcox diagram showed that 35% of water samples are suitable for irrigation. Sodium Adsorption Ratio (SAR), Soluble Sodium Percentage (SSP), Magnesium Adsorption Ratio (MAR), Permeability Index (PI), Potential Salinity (PS), and Total Dissolved Solids (TDS) are indicating the irrigational appropriateness of the groundwater samples, which is more suitable in post monsoon season compare to pre monsoon due to enrichment of Na⁺ by seawater intrusion and other processes. During POM season, the most number of groundwater samples are representing excellent to good categories might be due to an effective rainfall recharge by the monsoonal rain in the study area. The parameters indicated the introduction of geogenic and anthropogenic pollutions. The coastal community's knowledge is crucial to the long conservation of coastal water resources.

COVID-19 lockdown impacts on heavy metals and microbes in shallow groundwater and expected health risks in an industrial city of South India

In this investigation, the positive impact of COVID-19 lockdown on heavy metals concentration and biological parameters in the shallow groundwater samples of Coimbatore city of South India was ascertained. The groundwater samples (n=15) were obtained from shallow open wells during before lockdown (24-25 February 2020) and after lockdown (2-3 June 2020) periods. These samples were analysed for heavy metals (Fe, Mn, Ni, Cr and Pb) and biological parameters (E. coli, Fecal coliforms, Fecal streptococci and Total coliforms). Fe concentration was within the permissible limit but, the concentrations of Mn, Ni, Cr and Pb were above the allowable limits for drinking uses as per the WHO. However, after lockdown the number of samples crossing the cutoff limit had considerably decreased (Mn: from 2 to 0 mg/L; Ni: from 13 to 10 mg/L; Cr: 7 to 5 mg/L and Pb: from 13 to 8 mg/L). The heavy metal pollution index (HPI) revealed that 176.75 km² (67.4%) and 85.35 km² (32.6%) areas fell under unsuitable and very poor categories, respectively, during the pre-lockdown period, whereas 138.23 km² (52.6%), 118.98 km² (45.3%) and 4.89 km² (2.1%) areas fell under very poor, poor and good categories, respectively, during the post-lockdown period. Similarly, Total coliform, Fecal coliform and E. coli had decreased distinctly due to the pandemic lockdown. Therefore, the shutdown of small and large-scale industries during the lockdown period had improved the groundwater quality. The health risk assessment showed that 93%, 87% and 80% of pre-lockdown samples, and 87%, 80% and 73% of post-lockdown samples possessed non-carcinogenic risks (HI > 1) for children, female and male categories, respectively.

In vitro toxicity of arsenic rich waters from an abandoned gold mine in northeast Portugal

This is a follow-up study of physicochemical water monitoring data from the abandoned Freixeda gold mine in Portugal, where arsenic (As) has remained above drinking water and irrigation limits over the years. The main objective of the current work was to investigate the toxicological potential of As-containing water on human cell line as an indicator of a potential health risk to humans. Six water samples collected in February 2018 were analysed for arsenic, major anions, cations and trace elements. Toxicity experiments were carried out on the human gastrointestinal cell line Caco-2 with five water samples containing As above 10 μg L^-1. The results show that groundwater contains higher amounts of dissolved minerals than surface water, particularly with higher concentrations of SO₄^2-, Fe and HCO₃^- and also higher As(III), reaching 336 μg L^-1 (As(T) = 607 μg L^-1). In surface waters As concentration decreased and reached 150 μg L^-1, mainly as As(V). Metabolic activity was generally lower in Caco-2 cells exposed to As-containing water samples compared to pure As(III) solution, adapted to As concentrations, while production of reactive oxygen species (ROS) was higher. Short-term exposure to As-contaminated water samples also resulted in increased genotoxicity. This study suggests that mixture of As with various chemical elements in water may have a synergistic effect in promoting cytotoxicity. It is likely that prolonged exposure, as is common in areas with contaminated water, would have even more harmful effects.

Identifying influencing groundwater parameter on human health associate with irrigation indices using the Automatic Linear Model (ALM) in a semi-arid region in India

Quality of water for the purposes of irrigation is a serious threat to the sustainable development of the agriculture sector. The main objective of this study is to evaluate the suitability of groundwater for irrigation purposes using various irrigation indices such as: Sodium Absorption Ratio (SAR), Residual Sodium Carbonate (RSC), Percentage Sodium (%Na), Magnesium Hazards (MH), Permeability Index (PI), Potential Salinity (PS), Residual Sodium Bicarbonate (RBSC), Kelly's Ratio (KR), Synthetic Harmful Coefficient (K), and Exchangeable Sodium Percentage (ESP). A total of 30 samples were collected from the bore well of agricultural farmland and analysed for cations and anions. MH reveal that 53.33 % of samples exceed the permissible level. PS shows that 43.33 % of samples are marginally affected and 33.33 % of samples are unsuitable for use in irrigation. About 76 % of the groundwater samples were suitable for irrigation and the remainder require treatment before use. Automatic Linear Modelling (ALM) is used to predict the major influence parameter for MH and PS are RBSC, RSC and K value of groundwater. ALM shows that excess magnesium concentration and salinity are the primary factors that affect the suitability of groundwater for irrigation use. This integrated technique showed that water from approximately 25 % of the sample locations would require treatment before use. This study will improve the pattern of irrigation, identify sources of contamination and highlight the importance of organic fertilizers to develop and enhance the sustainable practices in the study region.

Biocellulose for Treatment of Wastewaters Generated by Energy Consuming Industries: A Review

Water and energy are two of the most important resources used by humanity. Discharging highly polluting wastewater without prior treatment is known to adversely affect water potability, agriculture, aquatic life and even society. One of the greatest threats to water sources are contaminated effluents, which can be of residential or industrial origin and whose disposal in nature must comply with specific laws aimed at reducing their environmental impact. As the oil industry is closely related to energy consumption, it is among the sectors most responsible for global pollution. The damage caused by this industrial sector is present in all countries, whose legislations require companies to carry out wastewater treatment before disposal or recycling in their production process. Bacterial cellulose membranes have been shown to be efficient as filters for the removal of various contaminants, including biological and chemical agents or heavy metals. Therefore, their use could make an important contribution to bio-based technological development in the circular economy. Moreover, they can be used to produce new materials for industry, taking into consideration current environmental preservation policies aimed at a more efficient use of energy. This review aims to compare and describe the applications of cellulose membranes in the treatment of these effluents.

Effects of COVID-19 pandemic lockdown on microbial and metals contaminations in a part of Thirumanimuthar River, South India: A comparative health hazard perspective

Twenty-two water samples from the Thirumanimuthar River course in southern India were collected before COVID-19 lockdown and during COVID-19 lockdown periods and were analyzed for microbiological parameters (fecal coliform bacteria, total coliform bacteria, Escherichia coli, and fecal streptococci) and heavy metals (Fe, Mn, Zn, Cu, Cd, Ni, Pb and Cr). The lockdown has decreased microbial populations and heavy metals. Fe, Cu, Cd, Ni, Pb and Cr exceeded the drinking water limits, respectively, in 77%, 45%, 27%, 18%, 9% and 91% of the pre-lockdown samples. During the lockdown period, Fe, Cu and Cd concentrations in 23% and Cr in 50% of the samples exceeded the limits. Heavy Metal Pollution Index (PI) expressed that 27%, 64% and 9% of the pre-lockdown samples represented 'low', 'medium' and 'high' pollution categories, respectively, but 68% and 32% of the lockdown period samples represented 'low' and 'medium' categories, respectively. The Metal Index (MI) exposed that all samples of pre-lockdown were under the seriously affected category, whereas 54% and 46% of lockdown samples were under strongly and seriously affected categories, respectively. Health risk evaluation predicted that 95%, 91% and 86% of pre-lockdown samples and 45%, 36% and 33% of lockdown period samples were at risk among children, teenagers and adults, respectively. As there is no integrated study on river water quality of COVID-19 lockdown this work is uniquely carried out by combining heavy metal pollution, microbial contamination and human health risk evaluation.

Sources and Consequences of Groundwater Contamination

Groundwater contamination is a global problem that has a significant impact on human health and ecological services. Studies reported in this special issue focus on contaminants in groundwater of geogenic and anthropogenic origin distributed over a wide geographic range, with contributions from researchers studying groundwater contamination in India, China, Pakistan, Turkey, Ethiopia, and Nigeria. Thus, this special issue reports on the latest research conducted in the eastern hemisphere on the sources and scale of groundwater contamination and the consequences for human health and the environment, as well as technologies for removing selected contaminants from groundwater. In this article, the state of the science on groundwater contamination is reviewed, and the papers published in this special issue are summarized in terms of their contributions to the literature. Finally, some key issues for advancing research on groundwater contamination are proposed.