COVID-19 and urban rivers: Effects of lockdown period on surface water pollution and quality- A case study of the Zarjoub River, north of Iran

Utilization of AI - reshaping the future of food safety, agriculture and food security - a critical review

Artificial intelligence is an emerging technology which harbors a suite of mechanisms that have the potential to be leveraged for reaping value across multiple domains. Lately, there is an increased interest in embracing applications associated with Artificial Intelligence to positively contribute to food safety. These applications such as machine learning, computer vision, predictive analytics algorithms, sensor networks, robotic inspection systems, and supply chain optimization tools have been established to contribute to several domains of food safety such as early warning of outbreaks, risk prediction, detection and identification of food associated pathogens. Simultaneously, the ambition toward establishing a sustainable food system has motivated the adoption of cutting-edge technologies such as Artificial Intelligence to strengthen food security. Given the myriad challenges confronting stakeholders in their endeavors to safeguard food security, Artificial Intelligence emerges as a promising tool capable of crafting holistic management strategies for food security. This entails maximizing crop yields, mitigating losses, and trimming operational expenses. AI models present notable benefits in efficiency, precision, uniformity, automation, pattern identification, accessibility, and scalability for food security endeavors. The escalation in the global trend for adopting alternative protein sources such as edible insects and microalgae as a sustainable food source reflects a growing recognition of the need for sustainable and resilient food systems to address the challenges of population growth, environmental degradation, and food insecurity. Artificial Intelligence offers a range of capabilities to enhance food safety in the production and consumption of alternative proteins like microalgae and edible insects, contributing to a sustainable and secure food system.

Source specific sedimentary response towards the differential anthropogenic impacts in terms of potentially toxic elements in an urban river

To investigate the interplay between varying anthropogenic activities and sediment dynamics in an urban river (Turag, Bangladesh), this study involved 37-sediment samples from 11 different sections of the river. Neutron activation analysis and atomic absorption spectrometry were utilized to quantify the concentrations of 14 metal(oid)s (Al, Ti, Co, Fe, As, Cd, Cr, Cu, Fe, Hg, Mn, Ni, Pb, Zn). This study revealed significant toxic metal trends, with Principal coordinate analysis explaining 62.91 % of the variance from upstream to downstream. The largest RSDs for Zn(287 %), Mn(120 %), and Cd(323 %) implies an irregular regional distribution throughout the river. The UNMIX-model and PMF-model were utilized to identify potential sources of metal(oid)s in sediments. ∼63.65-66.7 % of metal(oid)s in sediments originated from anthropogenic sources, while remaining attributed to natural sources in both models. Strikingly, all measured metal(oid)s' concentrations surpassed the threshold effect level, with Zn and Ni exceeding probable effect levels when compared to SQGs.

Assessing metal(loid)s-Induced long-term spatiotemporal health risks in Coastal Regions, Bay of Bengal: A chemometric study

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.

Assessing the impact of COVID-19 lockdown on surface water quality in Ireland using advanced Irish water quality index (IEWQI) model

The COVID-19 pandemic has significantly impacted various aspects of life, including environmental conditions. Surface water quality (WQ) is one area affected by lockdowns imposed to control the virus's spread. Numerous recent studies have revealed the considerable impact of COVID-19 lockdowns on surface WQ. In response, this research aimed to assess the impact of COVID-19 lockdowns on surface water quality in Ireland using an advanced WQ model. To achieve this goal, six years of water quality monitoring data from 2017 to 2022 were collected for nine water quality indicators in Cork Harbour, Ireland, before, during, and after the lockdowns. These indicators include pH, water temperature (TEMP), salinity (SAL), biological oxygen demand (BOD5), dissolved oxygen (DOX), transparency (TRAN), and three nutrient enrichment indicators-dissolved inorganic nitrogen (DIN), molybdate reactive phosphorus (MRP), and total oxidized nitrogen (TON). The results showed that the lockdown had a significant impact on various WQ indicators, particularly pH, TEMP, TON, and BOD5. Over the study period, most indicators were within the permissible limit except for MRP, with the exception of during COVID-19. During the pandemic, TON and DIN decreased, while water transparency significantly improved. In contrast, after COVID-19, WQ at 7% of monitoring sites significantly deteriorated. Overall, WQ in Cork Harbour was categorized as "good," "fair," and "marginal" classes over the study period. Compared to temporal variation, WQ improved at 17% of monitoring sites during the lockdown period in Cork Harbour. However, no significant trend in WQ was observed. Furthermore, the study analyzed the advanced model's performance in assessing the impact of COVID-19 on WQ. The results indicate that the advanced WQ model could be an effective tool for monitoring and evaluating lockdowns' impact on surface water quality. The model can provide valuable information for decision-making and planning to protect aquatic ecosystems.

Radiation exposure and health concerns associated with the environmental geochemistry of relatively higher radioactivity in a fresh water basin

This study was carried out on a negligible anthropogenically impacted Indo-Bangla transboundary river basin (Atrai, Bangladesh) to elicit radionuclides' and elemental distributions. Thirty sediment samples were collected from the Bangladesh portion of the river, and instrumental neutron activation analysis and HPGe γ-Spectrometry techniques were used to determine environmental radionuclides (e.g., 232Th, 226Ra, 40K) and associated elemental concentrations, respectively. Metal concentrations (Sc, V, Fe, Eu, Sm, La, Yb, Ce, Lu, Ta, Hf) were determined to comprehend the genesis of greater radioactivity. Recognizing the mean concentration of absorbed gamma dose rate (158.7 hGyh-1) is 2.88-times more than the recommended value (55 hGyh-1) that describes ionizing radiation concerns regarding potential health risks to the surrounding communities and the houses of native residents, which are constructed by Atrai river sediment. This work will assist relevant policymakers in exploring valuable heavy minerals and provide information regarding radiological health risks from a fluvial system.

Geospatial assessment of groundwater quality using entropy-based irrigation water quality index and heavy metal pollution indices

Groundwater contamination has become a serious environmental threat throughout the world in the era of Anthropocene. Thus, the present study examined the groundwater quality for irrigation purposes based on the entropy method and heavy metal pollution indices. To compute the entropy-based groundwater irrigation quality index (EIWQI), physicochemical parameters such as pH, chloride (Cl-) and nitrate (NO3-), irrigation indices including electrical conductivity (EC), sodium absorption ratio (SAR), sodium percentage (%Na), soluble sodium percentage (SSP), residual sodium carbonate (RSC), magnesium hazard (MH), Kelley's ration (KR), permeability index (PI) and heavy metals such as manganese (Mn), iron (Fe), zinc (Zn) and arsenic (As) have been employed for the 37 sample wells of the Damodar fan delta (DFD), India, which is a semi-critical agriculture-dominated region. Shannon's entropy method has been used to assign the weights of the different parameters for constructing the EIWQI. The results portray a spatial variation of the irrigation water quality in the DFD. The EIWQI revealed that 27.03%, 59.46%, 8.11%, 2.7% and 2.7% of the sample wells, respectively, contain excellent, good, moderate, poor and very poor quality of irrigation water. On the other hand, heavy metal pollution indices (modified degree of contamination, pollution load index, Nemerow index and modified heavy metal pollution index) show that 15-20% of sample wells of the DFD are contaminated by heavy metal pollution. The pockets of pollution are concentrated in the southwestern, northeastern and central parts of the DFD. The study found that the spatial variation in groundwater quality is controlled by the higher sodium concentration, carbonate weathering and expansion of agricultural and urban-industrial areas.

UV-Light-Driven Photocatalytic Dye Degradation and Antibacterial Potentials of Biosynthesized SiO2 Nanoparticles

The present work shows the obtainment of biosynthesized SiO2 with the aid of Jasminum grandiflorum plant extract and the study of its photocatalytic ability in dye degradation and antibacterial activity. The obtained biosynthesized SiO2 nanoparticles were characterized using X-ray diffractometer analysis, Fourier transform infrared spectroscopy analysis, ultraviolet–visible diffuse reflectance spectroscopy, field-emission scanning electron microscope with energy-dispersive X-ray analysis, transmission electron microscopy and X-ray photoelectron spectroscopy. The UV-light irradiated photocatalytic activity of the biosynthesized SiO2 nanoparticles was examined using methylene blue dye solution. Its reusability efficiency was determined over 20 cycles and compared with the commercial P-25 titanium dioxide. The bacterial resistivity of the biosynthesized SiO2 nanoparticles was examined using S. aureus and E. coli. The biosynthesized SiO2 nanoparticles showed a high level of crystallinity with no impurities, and they had an optimum crystallite size of 23 nm, a bandgap of 4 eV, no Si-OH groups and quasi-spherical shapes with Si-2p at 104 eV and O-1s at 533 eV. Their photocatalytic activity on methylene blue dye solution could reach 90% degradation after 40 min of UV light exposure, and their reusability efficiency was only 4% less than that of commercial P-25 titanium dioxide. At the concentration of 100 μg/mL, the biosynthesized SiO2 nanoparticles could allow the resistivity of E. coli to become borderline to the resistant range of an antibiotic called Amikacin.

Pollution trends and ecological risks of heavy metal(loid)s in coastal zones of Bangladesh: A chemometric review

Heavy metal(loid)s inputs contribute to human and environmental stresses in the coastal zones of Bangladesh. Several studies have been conducted on metal(loid)s pollution in sediment, soil, and water in the coastal zones. However, they are sporadic, and no attempt has been made in coastal zones from the standpoint of chemometric review. The current work aims to provide a chemometric assessment of the pollution trend of metal(loid)s, namely arsenic (As), chromium (Cr), cadmium (Cd), lead (Pb), copper (Cu), zinc (Zn), and nickel (Ni) in sediments, soils, and water across the coastal zones from 2015 to 2022. The findings showed that 45.7, 15.2, and 39.1 % of studies on heavy metal(loid)s were concentrated in the eastern, central, and western zones of coastal Bangladesh. The obtained data were further modeled using chemometric approaches, such as the contamination factor, pollution load index, geoaccumulation index, degree of contamination, Nemerow's pollution index, and ecological risk index. The results revealed that metal(loid)s, primarily Cd, have severely polluted the sediments (contamination factor, CF = 5.20) and soils (CF = 9.35) of coastal regions. Water was moderately polluted (Nemerow's pollution index, P_N=5.22 ± 6.26) in the coastal area. The eastern zone was the most polluted compared to other zones, except for a few observations in the central zone. The overall ecological risks posed by metal(loid)s highlighted the significant ecological risk in sediments (ecological risk index, RI = 123.50) and soils (RI = 238.93) along the eastern coast. The coastal zone may have higher pollution levels due to the proximity of industrial effluent, residential sewage discharge, agricultural activities, sea transport, metallurgical industries, shipbreaking and recycling operations, and seaport activities, which are the major sources of metal(loid)s. This study will provide useful information to the relevant authorities and serve as the foundation for future management and policy decisions to reduce metal(loid) pollution in the coastal zones of southern Bangladesh.

Influence of COVID-19 lockdown on river water quality and assessment of environmental health in an industrialized belt of southern Western Ghats, India

The COVID-19 pandemic and sudden lockdown have severely hampered the country's economic growth and socio-cultural activities while imparting a positive effect on the overall fitness of the environment especially air and water resources. Increased urbanization and rapid industrialization have led to rising pollution and deterioration of rivers and associated sectors such as agriculture, domestic and commercial needs. However, various available studies in different parts of the country indicate that the COVID-19 pandemic has changed the entire ecosystem. But it is noted that studies are lacking in the southern Western Ghats region of India. Therefore, the present study attempts to investigate how the continuous lockdowns affect the River Water Quality (RWQ) during lockdown (October 2020) and post-lockdown (January 2021) periods in the lower catchments (Eloor-Edayar industrialized belt) of Periyar river, Kerala state, South India. A total of thirty samples (15 samples each) were analyzed based on drinking water quality, irrigational suitability, and multivariate statistical methods to evaluate the physical and chemical status of RWQ. The results of the Water Quality Index (WQI) for assessing the drinking water suitability showed a total of 93% of samples in the excellent and good category during the lockdown, while only 47% of samples were found fit for drinking during the post-lockdown period. Irrigational suitability indices like Mg hazard, KR, PI, SAR, and Wilcox diagram revealed lockdown period samples as more suitable for irrigational activities compared to post-lockdown samples with site-specific changes. Spearman rank correlation analysis indicated EC and TDS with a strong positive correlation to Ca2+, Mg2+, Na+, K+, TH, SO42-, and Cl- during both periods as well as strong positive correlations within the alkaline earth elements (Ca2+ and Mg 2+) and alkalis (Na+ and K+). Three significant components were extracted from principal component analysis (PCA), explaining 88.89% and 96.03% of the total variance for lockdown and post-lockdown periods, respectively. Variables like DO, BOD, Ca2+, NO3-, and Cl- remained in the same component loading during both periods elucidating their natural origin in the basin. The results of health risk assessment based on US EPA represented hazard quotient and hazard index values below the acceptable limit signifying no potential noncarcinogenic risk via oral exposure except As, suggesting children as more vulnerable to the negative effects than adults. Furthermore, this study also shows rejuvenation of river health during lockdown offers ample scope to policymakers, administrators and environmentalists for deriving appropriate plans for the restoration of river health from anthropogenic stress.

Indexical and statistical approaches to investigate the integrated origins of elements in the sediment of Teesta River, Bangladesh: sediment quality and ecological risk assessment

This study investigates ecological consequences from the combined provenance (natural and manmade) of fifteen metal(oid)s (Na, Al, K, Ti, Cr, Mn, Co, Zn, As, Rb, Sb, Cs, Ba, Th, and U) from a major Indo-Bangla transboundary river (Teesta). Instrumental neutron activation analysis has been performed to calculate the elemental concentration for a total of thirty sediment samples which accumulated from the upper, middle and downstream section of the Teesta River. In comparison with the crustal origin Rb, Th, and U were 1.5-2.8 times elevated. Elements from upstream and midstream sediments showed greater spatial variability than those from downstream sediments in terms of Na, Rb, Sb, Th, and U. Statistical approaches suggested the dominance of geogenic sources (Na, K, Al, Ti, Co, and Ba) of elements over anthropogenic sources (Cr and Zn). Alkali feldspar and aluminosilicates release lithophilic minerals into the sediments under the redox condition (U/Th = 0.18). Site-specific ecotoxicological indices advocated that some specific locations are highly hazardous relative to Cr and Zn. From SQG-based guidelines, Cr showed higher potential toxicity in some upstream locations relative to Zn, Mn, and As. In order to attain the knowledge limitation of northern transboundary rivers from Bangladesh, this study of origin and relative environmental impact will be beneficial for policy makers.

Human health risk assessment and pollution index of groundwater in Jammu plains of India: A geospatial approach

To examine the drinking water suitability as well as to study the influence of local lithology in controlling groundwater chemistry a study has been carried out in the Jammu plains of India by using 50 groundwater samples during the post-monsoon (POM) and pre-monsoon (PRM) seasons. The groundwater samples are found to be dominated by Mg-Ca-HCO₃, and Ca-Mg-HCO_3, types. Besides this, the Pollution Index of Groundwater (PIG) was also calculated to assess the overall groundwater quality of the study area. As per the PIG, the groundwater quality of the study is suitable for domestic utilization except for a few samples (2%) which need conventional treatment in order to make the groundwater resources potable. Based on rock water interaction, there is a considerable variation in the POM and PRM seasons, which indicates the role of weathering and dissolution of rock minerals. The multivariate statistical analysis reveals that the lithogenic factors, such as rock-water interactions and weathering of carbonate-bearing rocks, are predominantly controlling groundwater chemistry. Further, trace elements such as As, Cu, Cd, Fe, Mn, and Zn were also analyzed to determine the Human Health Risk Assessment (HHRA) in order to know about the carcinogenic risk in adults and children in the study area.

Effects of COVID-19 era on a subtropical river basin in Bangladesh: Heavy metal(loid)s distribution, sources and probable human health risks

The COVID-19 era has profoundly affected everyday human life, the environment, and freshwater ecosystems worldwide. Despite the numerous influences, a strict COVID-19 lockdown might improve the surface water quality and thus provide an unprecedented opportunity to restore the degraded freshwater resource. Therefore, we intend to investigate the spatiotemporal water quality, sources, and preliminary health risks of heavy metal(loid)s in the Karatoya River basin (KRB), a tropical urban river in Bangladesh. Seventy water samples were collected from 35 stations in KRB in 2019 and 2022 during the dry season. The results showed that the concentrations of Ni, Cu, Zn, Pb, Cd, and Cr were significantly reduced by 89.3-99.7 % during the post-lockdown period (p < 0.05). However, pH, Fe, Mn, and As concentrations increased due to the rise of urban waste and the usage of disinfectants during the post-lockdown phase. In the post-lockdown phase, the heavy metal pollution index, heavy metal evaluation index, and Nemerow's pollution index values lessened by 8.58 %, 42.86 %, and 22.86 %, respectively. Besides, the irrigation water quality indices also improved by 59 %-62 %. The total hazard index values increased by 24 % (children) and 22 % (adults) due to the rise in Mn and As concentrations during the lockdown. In comparison, total carcinogenic risk values were reduced by 54 % (children) and 53 % (adults) in the post-lockdown. We found no significant changes in river flow, rainfall, or land cover near the river from the pre to post-lockdown phase. The results of semivariogram models have demonstrated that most attributes have weak spatial dependence, indicating restricted industrial and agricultural effluents during the lockdown, significantly improving river water quality. Our study confirms that the lockdown provides a unique opportunity for the remarkable improvement of degraded freshwater resources. Long-term management policies and regular monitoring should reduce river pollution and clean surface water.

Natural and anthropogenic contributions to the elemental compositions and subsequent ecological consequences of a transboundary river's sediments (Punarbhaba, Bangladesh)

An anthropogenically less affected transboundary river (Punarbhaba, Bangladesh) was studied to detect associated risks from the combined origin(s) of geochemically and toxicologically significant elements in benthic sediments. A total of 30 river bed sediments were analyzed by instrumental neutron activation analysis targeting the 15 chemical elements viz., Na, Al, K, Ti, Cr, Mn, Co, Zn, As, Rb, Sb, Cs, Ba, Th, and U. Among the estimated elements, the mean abundances (μg/g) of Rb (136), Sb (0.66), Cs (6.66), Th (14.6), and U (3.92) were 1.4-1.7 times higher than the crustal origin. These elements are primarily responsible for the contaminated state of the Punarbhaba River. The studied area is 'moderately polluted' (I_geo: 2.01 to 0.02) and possesses 'minor enrichment' (EF: 1.98 to 0.48) in terms of the measured elements. The output of statistical analyses projected that the studied elements are geochemically fractionated in an oxidizing environment (U/Th = 0.44) and mostly originated from felsic sources, thus confirming the mineral is comprised of aluminosilicates and alkali feldspar. However, SQGs-based and ecological risk indices invoked minor (Cr: 6.67%) to no potential ecotoxicological threats for Cr, Mn, Co, Zn, As, and Sb. Nonetheless, altered distribution patterns caused by geogenic activities increased Cr and Zn in the environment which may cause toxicity (Cr: 22-53%, Zn: 35-70%), and pose potential ecological risks, specifically in upstream locations (P-2, P-3, P-5). Further, this study broadened the perspective of sediment deposition from fractionation, fluvial transportation, and weathering events beyond the industrial disintegration of elements, which will aid researchers and policymakers to comprehend combined risks from suspended sediments.

Mapping Chini Lake (Pahang, Malaysia) using Sentinel-2 images to determine the effect of acid mine drainage in the pre- to post-COVID-19 restriction period

Mining activities in the Chini Lake catchment area have been extensive for several years, contributing to acid mine drainage (AMD) events with high concentrations of iron (Fe) and other heavy metals impacting the surface water. However, during the restriction period due to the COVID-19 outbreak, anthropogenic activities have been suspended, which clearly shows a good opportunity for a better environment. Therefore, we aimed to analyze the variation of AMD-associated water pollution in three main zones of the Chini Lake catchment area using Sentinel-2 data for the periods pre-movement control order (MCO), during MCO, and post-MCO from 2019 to 2021. These three zones were chosen due to their proximity to mining areas: zone 1 in the northeastern part, zone 2 in the southeastern part, and zone 3 in the southern part of the Chini Lake area. The acid mine water index (AMWI) was a specific index used to estimate acid mine water. The AMWI values from Sentinel-2 images exhibited that the mean AMWI values in all zones during the MCO period decreased by 14% compared with the pre-MCO period. The spatiotemporal analysis found that the highest polluted zones were recorded in zone 1, followed by zone 3 and zone 2. As compared with during the MCO period, the maximum percentage of increment during post-MCO in all zones was up to 25%. The loosened restriction policy has resulted in more AMD flowing into surface water and increased pollution in Chini Lake. As a whole, our outputs revealed that Sentinel-2 data had a major potential for assessing the AMD-associated pollution of water.

The plight of Najafgarh drain in NCT of Delhi, India: assessment of the sources, statistical water quality evaluation, and fate of water pollutants

The Najafgarh drain is the first major drain that joins the Yamuna River at Wazirabad in Delhi, India, and is known to contribute to the maximum pollution load to this river. The drain is originally an extension of the Sahibi River and was intentionally constructed as a canal to carry stormwater, but presently, it is carrying more of sewage, agricultural, and industrial effluents received through various small and large secondary drains. The present study has analyzed the water quality status of this interconnected system, i.e., the Najafgarh drain, its associated secondary drains, and the Yamuna River for physicochemical parameters (n = 16), microbiological parameter (n = 1), and heavy metal concentrations (n = 8). The analysis of the surface water samples collected during pre- and post-monsoon seasons showed that secondary drain discharges significantly impacted the water quality of the Najafgarh drain, which in turn affected the Yamuna River. Out of the eight selected secondary drains for this study, the Goyla dairy outlet came out as the most polluted site in terms of organic pollutants while the Basaidarapur drain was loaded with heavy metal contaminants. Statistical tools comprising hierarchical cluster analysis (HCA), Pearson's correlation, and principal component analysis (PCA) were further implemented on the water quality dataset for a better understanding of the possible sources of contamination for organic and inorganic pollutants in the selected sampling sites. The present study, thus, might help in providing key highlights to the policymakers for effective regulation and management of the point source discharges in Najafgarh drain, which will ultimately restrict its pollution loadings in Yamuna River, Delhi, and also help in the restoration of this important water body.

Combining stable isotope and WQI methods to study the groundwater quality: a case study in Essaouira city, Morocco

Groundwater is an important water resource in arid and semi-arid regions. Therefore, this study aimed to assess groundwater's suitability for drinking and irrigation using the Water Quality Index (WQI) and the Irrigation Water Quality Index (IWQI). To this end, groundwater data were collected from 58 sites in 2019 (wet season) and 61 samples in 2020 (dry season) in the Meskala-Ouazzi sub-basin. The Piper diagram showed that Ca–Mg–Cl was the dominant groundwater facies type. The confinement due to COVID-19 has significantly improved the water quality of the Meskala-Ouazzi sub-basin. Instead, approximately 50% of sites showed improved water quality when calculating the WQI and IWQI. However, the sodium adsorption ratio (SAR) showed that most samples below 10 are found in all of the examined samples, which are mostly found, indicating excellent irrigation water, and the Wilcox diagram depicted 20.14% of samples lying in the unsuitable region. Stable isotopes (δ¹⁸O and δ²H) of groundwater reveal that local precipitation is the main source of recharge. However, groundwater recharge is affected by the evaporation process due to the different geological conditions caused by topographic differences in the study area. The present study is useful for proper planning and managing water resources available for consumption and irrigation.

Water quality has improved during lockdown due to COVID-19.

Assessment of water drinking and irrigation by two models (WQI, and IWQI) in a semi-arid environment.

The main source of groundwater recharge in coastal aquifers is rainfall, based on a stable isotope (δ²H, δ¹⁸O).

Reconciling the geogenic and non-crustal origins of elements in an Indo-Bangla transboundary river, Atrai: Pollution status, sediment quality, and preliminary risk assessment

This study has been conducted on an anthropogenically less influenced transboundary river (Atrai: Indo-Bangladesh) to comprehend the inherent geochemistry and identify potential elemental sources. In doing so, across the Bangladeshi portion, 30 river-bed samples were culled and studied by neutron activation analysis to quantify the abundances of 15 geochemically and toxicologically significant elementals (Na, Al, K, Ti, Cr, Mn, Co, Zn, As, Rb, Sb, Cs, Ba, Th, and U). The results revealed that the mean concentrations (μg/g) of Rb (154.6), Cs (7.53), Th (20.90), and U (4.88) were 1.5-2.0 times higher than crustal values. Besides, geo-environmental indices revealed 'uncontaminated to moderately contaminated' pollution status with minor enrichment or contamination for Rb, Th, Sb, U, and Cs, relatively concentrated in the mid-to-downstream zone possessed geogenic and non-crustal origins. The positive matrix factorization and other statistical approaches revealed predominant geogenic enrichment of Na, K, Al, Ti, Zn, Cs, Rb, As, Th, and U from differential mineralogical compositions via weathering, elemental fractionations, and biogeochemical mobilization. Contrariwise, several anthropogenic sources (for Cr, Sb, Co, Mn, Th) were also ascertained in the vicinity of Atari River. However, sediment characterization based on SQG threshold values manifested that Cr and Mn possess rare biological effects on local aquatic organisms. Nevertheless, SQGs-based and ecological risk indices invoked minor to no potential ecotoxicological intimidations for the considered metal(oid)s (Cr, Mn, Co, Zn, As, and Sb). Hence, this study manifested the usefulness of a less anthropogenically affected river to reckon geogenic and non-crustal elemental origins in the compounded riverine sediment.

Groundwater vulnerability and contamination risk mapping of semi-arid Totko river basin, India using GIS-based DRASTIC model and AHP techniques

Totko river basin is a semi-arid watershed, which undergoes severe water crisis during the dry season. Presently, due to increase in population, demand of food has increased leading to a rise in growth of high yield crop variety and usage of chemical fertilizers and pesticides. So, surface water as well as groundwater is getting polluted. In this study assessment of groundwater vulnerability of Totko river basin has been done using DRASTIC and Analytic Hierarchy Process (AHP) models. For this, seven hydrogeological parameters have been considered which are; Depth to water level (D), Net Recharge (R), Aquifer media (A), Soil media (S), Topography (T), Impact of vadose zone (I) and Hydraulic Conductivity (C). Weight and rating analysis of the seven criteria and their sub-criteria have been done using generic DRASTIC algorithm and AHP comparison matrix. Ground Water Vulnerability Map (GWV) obtained from DRASTIC and AHP analysis has been divided into five vulnerable classes. Area of very high vulnerable zone is 6.53% more in AHP based vulnerability as compared to Generic DRASTIC. Similarly, these regions show a high nitrate concentration (30-50 ppm) in groundwater. GWV maps have been validated through nitrate concentration and the accuracy of the models have been assessed through Pearson's correlation coefficient and Kappa coefficient. To prevent groundwater contamination proper land use planning and watershed management are necessary, for which vulnerable zones need to be demarcated and DRASTIC is a useful model for vulnerability assessment.

Satellite-Based Monitoring of the Algal Communities of Aras Dam Reservoir: Meteorological Dependence Analysis and the Footprint of COVID-19 Pandemic Lockdown on the Eutrophication Status

Aras Dam Lake is a strategic aquatic ecosystem in Iran and there are reports of toxic phytoplankton blooms in this reservoir. This study was performed to determine the effect of meteorological variables on the formation and expansion of toxic phytoplankton communities in Aras dam reservoir. The data of this project have been obtained using field studies and satellite data (MODIS and Sentinel-2). Sampling to determine the composition of phytoplankton communities in the area was carried out seasonally in two time periods from 2003 to 2014, and environmental assessments were also performed based on meteorological and satellite data over an 18-year period (2003-2020). The Chlorophyll-a content was obtained from MODIS and correlated with meteorological data. The statistical analysis showed that the highest coefficient of determination is related to the correlation of chlorophyll-a and Evaporation (R ² = 0.86). Also, the relative root mean square error is equal to 18%, 18.1% and 21.2% for the chlorophyll-a -SST, chlorophyll-a -wind and chlorophyll-a -Evaporation relations, respectively. Moreover, in a supplementary study, correlation between the chlorophyll-a content with selected meteorological variables including evaporation, wind speed and water surface temperature were investigated seasonally. The results showed that the trend of changes in chlorophyll-a content with three considered variables are parabolic functions and chlorophyll-a -Evp (R ² = 0.86, MAPE = 15.2%) model indicates better performance. The results also showed that the eutrophication rate of the reservoir during lockdown period increased in comparison with the same time at pre-pandemic period, which can be related to increase of incoming waste loads in this reservoir.

Evaluation of water quality using a Takagi-Sugeno fuzzy neural network and determination of heavy metal pollution index in a typical site upstream of the Yellow River

Assessment of river water quality is very important for understanding the impact of human activities on aquatic ecosystems. As the second-largest river in China, the Yellow River's water environment is closely related to the social development and water security of northern China. The Huangshui River is a major tributary of the upper Yellow River, and it supplies water to cities in the lower reaches. In this study, a Takagi-Sugeno (T-S) fuzzy neural network was used to evaluate water quality of the Huangshui River, and pollutant sources were analyzed. The heavy metal pollution index (HPI) was calculated to assess the heavy metal pollution level, and the health risks posed by heavy metal elements were assessed. The results indicated that the main contaminants in the Huangshui River were ammonia nitrogen (NH₃-N) and total phosphorus (TP), which was affected by various activities of industry, agriculture, and urbanization, and the maximum concentration of NH₃-N and TP was 5.90 mg/L and 0.36 mg/L, respectively. The T-S evaluation results of some points in the middle reaches were 3.317 and 3.197, which belonged to Level Ⅳ and the water quality was poor. The concentrations of Cu, Zn and Cr in the river were 0.57-44.58 μg/L, 10-122.50 μg/L and 2-28.67 μg/L, respectively, and they were relatively large. The T-S fuzzy neural network could evaluate water quality, avoiding extreme evaluation results by using fuzzy rules to reduce the influence of pollutant concentrations that are too high or too low. In addition to qualitative categorization of water quality, this approach can also quantitatively assess water quality within a single category. The results of water quality assessment could provide a scientific data support for river management.

Effects of COVID-19 lockdown on water quality, microbial extracellular enzyme activity, and sediment-P release in the Ganga River, India

This study investigates possible improvement in water quality and ecosystem functions in the Ganga River as influenced by COVID-19 lockdown in India. A total of 132 samples were collected during summer-2020 low flow (coinciding COVID-19 lockdown) for water (sub-surface and sediment-water interface) and 132 samples separately for sediment (river bottom and land-water interface) considering 518-km main river stem including three-point sources (one releases urban sewage and the other two add metal-rich industrial effluents) and a pollution-impacted tributary. Parameters such as dissolved oxygen deficit and the concentrations of carbon, nutrients (N and P), and heavy metals were measured in water. Sediment P-release was measured in bottom sediment whereas extracellular enzymes (EE; alkaline phosphatase, FDAase, protease, and β-D-glucosidase) and CO2 emission were measured at land-water interface to evaluate changes in water quality and ecosystem functions. The data comparisons were made with preceding year (2019) measurements. Sediment-P release and the concentrations of carbon, nutrients, and heavy metals declined significantly (p<0.05) in 2020 compared to those recorded in 2019. Unlike the preceding year, we did not observe benthic hypoxia (DO <2.0 mg L-1) in 2020 even at the most polluted site. The EE activities, which declined sharply in the year 2019, showed improvement during the 2020. The stability coefficient and correlative evidences also showed a large improvement in the water quality and functional variables. Positive changes in functional attributes indicated a transient recovery when human perturbations withdrawn. The study suggests that timing the ecosystem recovery windows, as observed here, may help taking management decision to design mitigation actions for rivers to recover from anthropogenic perturbations.