Distribution and bioaccumulation of trace elements in two Cyprinidae fish species in the Indus river, Pakistan, including the impact of hydraulic structure on macroinvertebrates' biodiversity.

The concentration of trace elements (chromium, lead, zinc, copper, manganese, and iron) was determined in water, sediment and tissues of two Cyprinidae fish species - Labeo rohita and Tor putitora - collected from the eight sampling stations of Indus River in 2022 for four successive seasons (autumn, winter, spring, summer), and also study the present condition of macroinvertebrates after the construction of hydraulic structure. The obtained results of trace element concentrations in the Indus River were higher than the acceptable drinking water standards by WHO. The nitrate concentration ranges from 5.2 to 59.6 mg l-1, turbidity ranges from 3.00 to 63.9 NTU, total suspended solids and ammonium ions are below the detection limit (<0.05). In the liver, highest dry wt trace elements (µg/g) such as Cr (4.32), Pb (7.07), Zn (58.26), Cu (8.38), Mn (50.27), and Fe (83.9) for the Labeo rohita; and Tor Putitora has significantly greater accumulated concentration (Cr, Pb, Zn, Cu, Mn, Fe) in muscle and liver than did Labeo rohita species. Additionally, lower number of macroinvertebrates were recorded during the monsoonal season than pre-monsoon and post-monsoon. Local communities surrounded by polluted environments are more probably to consume more fish and expose them to higher concentrations of toxic trace elements (lead and copper). The findings also provide a basis for broader ecological management of the Indus River, which significantly influenced human beings and socioeconomic disasters, particularly in the local community.

How contaminated is flatfish living near World Wars' munition dumping sites with energetic compounds?

Seas worldwide are threatened by an emerging source of pollution as millions of tons of warfare materials were dumped after the World Wars. As their metal shells are progressively corroding, energetic compounds (EC) leak out and distribute in the marine environment. EC are taken up by aquatic organisms and pose a threat to both the marine ecosphere and the human seafood consumer because of their toxicity and potential carcinogenicity. Here, sediment samples and fish from different locations in the German North Sea of Lower Saxony were examined to determine whether EC transfer to fish living close to munition dumping areas. EC were found in sediments with a maximum concentration of 1.5 ng/kg. All analyzed fish muscle tissues/fillets and bile samples were positive for EC detection. In bile, the max. EC concentrations ranged between 0.25 and 1.25 ng/mL. Interestingly, while detected TNT metabolites in the muscle tissues were in concentrations of max. 1 ng/g (dry weight), TNT itself was found in concentrations of up to 4 ng/g (dry weight). As we found considerable higher amounts of non-metabolized TNT in the fish muscle, rather than TNT metabolites, we conclude an additional absorption route of EC into fish other than per diet. This is the first study to detect EC in the edible parts of fish caught randomly in the North Sea.

Evidencing anthropogenic pollution of surface waters in a tropical region: a case study of the Culiacan River basin.

Nowadays, one of the most critical challenges is reduced access to water. Climate change, industrialization, and population growth have caused many countries to suffer from water crises, especially in arid and semi-arid areas. The Culiacan River basin in Sinaloa is a region of great importance in Mexico due to its intensive agricultural activity. Hence, water quality assessment has become a necessity to ensure sustainable water use. This study describes the spatiotemporal water quality features of the Humaya, Tamazula, and Culiacan Rivers within the Culiacan River basin and their sources of contamination. Twenty-two water quality parameters were analyzed from samples taken every 6 months from 2012 to 2020 at 19 sampling sites in the basin. A multivariate statistical analysis revealed significant correlations (r > 0.85) between the water quality parameters. The modified Integrated Water Quality Index (IWQI) identified severe pollution in samples from the urban river section of the basin, while good water quality conditions were found upstream. Severe contamination was observed in 26.32% of the samples, whereas only 13.45% evidenced good water quality. The Water Quality Index (WQI) indicated that 94.74% of the samples presented fair water quality, suggesting that the surface waters of the Culiacan River Basin are suitable for agricultural irrigation. This study provides insights into the current water quality status of the surface waters in the Culiacan River Basin, identifying significant pollution sources and areas of concern. The spatiotemporal dynamics of water quality in the Culiacan River basin revealed the importance of continuous monitoring and effective water management practices to improve water quality and achieve sustainable agricultural practices.

Uncertainty and sensitivity analysis of revised leachate pollution index.

Composite indicators (CIs) are being utilized more frequently to assess and monitor environmental systems. The revised leachate pollution index (r-LPI) is one such composite indicator used to quantify the pollution potential of landfill leachate on a scale of 5-100. The development of CIs involves several steps, and each of these steps has various methodological choices, each of which could lead to different results. Thereby, the reliability of the quantified pollution potential of leachate may be questioned. This study investigated the techniques for developing the r-LPI, examining decisions related to parameter selection, normalization technique, weighting approach, sub-indicator weights, and their aggregation. As the index developer made the decisions, each of these stages was fraught with uncertainty. The uncertainty in the various stages of the development of r-LPI was quantified using the Monte Carlo-based uncertainty analysis and the sensitivity analysis approach. Uncertainty analysis is a helpful but seldom-used step of index development that identifies the model's most dependable sections. Sensitivity analysis was carried out to ascertain the degree of impact the input parameters have on the r-LPI values. The combined use of sensitivity and uncertainty analysis in this study for the formulation of r-LPI affirmed the transparency, credibility, and accuracy of the index.

Exploring spatial and seasonal water quality variations in Kelani River, Sri Lanka: a latent variable approach.

Water quality degradation poses a significant challenge globally, especially in developing nations like Sri Lanka. Extensive monitoring programs designed to address escalating river pollution collect multiple water quality parameters over extended periods and varied locations. However, the sheer volume of data can be overwhelming, making it difficult to process effectively and interpret accurately using conventional methods. In this study, latent variable (LV) and unsupervised machine learning techniques were used to investigate spatial and seasonal variations of surface water quality for 17 parameters across 17 locations along the Kelani River, Sri Lanka, using monthly water quality parameters from 2016 to 2020. Pearson's correlation matrix identified 10 parameters significantly affecting water quality variations and factor analysis (FA) generated five LVs, accounting for 77% of the total variance in the dataset. The identified LVs showed multiple methods of river pollution. Hierarchical clustering analysis and self-organizing mapping methods clustered stations in a closely analogous manner. Stations near industrial zones and the river mouth showed higher water quality variance, often exceeding national guidelines. Correlation testing revealed strong relationships between water quality and catchment hydrometeorological variations during monsoonal seasons. Spatial analyses showed increased LV variance in the Lower Kelani River Basin, indicating higher pollutant levels in different seasons. Industrial effluents (LV-2 and LV-4) and domestic and municipal sewage (LV-3 and LV-5) exhibit greater seasonal fluctuations. The results showed that the proposed LV approach has the potential to assist authorities in addressing water pollution amidst the complexity of multiple water quality parameters.

A case study of using artificial neural networks to predict heavy metal pollution in Lake Iznik.

Artificial neural networks offer a viable route in assessing and understanding the presence and concentration of heavy metals that can cause dangerous complications in the wider context of water quality prediction for the sustainability of the ecosystem. In order to estimate the heavy metal concentrations in Iznik Lake, which is an important water source for the surrounding communities, characterization data were taken from five different water sources flowing into the lake between 2015 and 2021. These characterization results were evaluated with IBM SPSS Statistics 23 software, with the addition of the lake water quality system. For this purpose, seven distinct physicochemical parameters were measured and monitored in Karasu, Kirandere, Olukdere and Sölöz water sources flowing into the lake, to serve as input data. Concentration levels of 15 distinct heavy metals in Karsak Stream originating from the lake were as the output. Specifically, Sn for Karasu (0.999), Sb for Kirandere (1.000), Cr for Olukdere (1.000) and Pb and Se for Sölöz (0.995) indicate parameter estimation R2 coefficients close to 1.000. Sn stands out as the common heavy metal parameter with best estimation prospects. Given the importance of the independent variable in estimating heavy metal pollution, conductivity, COD, COD and temperature stood out as the most effective parameters for Karasu, Olukdere, Kirandere and Sölöz, respectively. The ANN model emerges as a good prediction tool that can be used effectively in determining the heavy metal pollution in the lake as part of the efforts to protect the water budget of Lake Iznik and to eliminate the existing pollution.

Seasonal variation, spatial distribution and risk assessment of microplastics in surface waters of Periyar River, Kerala, India.

Microplastics, an emerging contaminant, are widespread in oceans around the world, and rivers are the key conveyors of these pollutants into the oceans. There exists a dearth of available data pertaining to seasonal fluctuation, spatial distribution and risk assessment of microplastics in rivers extending from upper reaches to the lower reaches. The collection of such data is of utmost importance for the purpose of formulating beneficial management strategies for riverine microplastics. In order to bridge this research gap, an investigation was made in the Periyar River in Kerala, India, which is exposed to anthropogenic stress and is at risk of microplastic pollution. A total of eighteen sites (six sites each from downstream, midstream and upstream) along the 244 km of the river were investigated across three seasons in a year. The study revealed a discernible pattern in the spatial distribution of microplastic concentrations, wherein there was a rise in abundance from the upstream to midstream and then a sudden increase of abundance along the downstream regions towards the lower reaches. The highest mean microplastic abundance of 124.95 items/L was obtained during the monsoon season followed by post-monsoon season i.e. 123.21 items/L and pre-monsoon i.e. 120.50 items/L. The predominant forms of microplastics were found to be fibres, fragments and filaments. Most prevalent polymer types acquired were polyethylene (PE) and polypropylene (PP). Pollution hazard index (PHI) and pollution load index (PLI) were also evaluated to assess the water quality of this river. The findings of this study conclude that the Periyar River is polluted with microplastics throughout its course and offer significant insights into the detection of microplastic origins in river systems and lend support to the implementation of potential measures aimed at mitigating their impact.

Assessment of water quality and source apportionment of pollution in a tropical river in eastern India: A study utilizing multivariate statistical tools and the APCS-MLR receptor model.

The Mundeswari River, an ecologically distressed river in eastern India, has been subjected to water quality deterioration largely due to anthropogenic activities in its vicinity. This study aimed to comprehensively evaluate the current state of pollution in the river and assess the appropriateness of river water for irrigation, given its extensive use for agricultural purposes. Monthly water quality monitoring was undertaken at four distinct sampling sites (SP1-SP4) over a two-year period (2020-2022), considering seventeen water quality parameters. This research employed principal component analysis/factor analysis (PCA/FA) and absolute principal component score-multiple linear regression (APCS-MLR) receptor modelling. These methodologies were used to discern and quantify potential sources of pollution influencing the water quality of the Mundeswari River. The study revealed that the water quality of the Mundeswari River was most degraded during the pre-monsoon season. Among the four sampling sites, SP3 exhibited the highest level of pollution with mean biochemical oxygen demand (BOD) and chemical oxygen demand (COD) values of 5.36 mg/L and 44.72 mg/L, respectively. According to the one-way analysis of variance (ANOVA), there was considerable spatial and seasonal disparities (P < 0.05) in most water quality parameters. The PCA/FA extracted four latent pollution sources, accounting for 81.5% of the total variance. The primary factors influencing the quality of river water are natural weathering processes, discharge of domestic effluent and waste, and agricultural runoff. The APCS-MLR receptor model further revealed that agricultural drainage factors and the discharge of domestic effluent and waste had a greater impact on the Mundeswari River. The investigation concluded that the mean values of all indicators for irrigation suitability were below the defined threshold limits, indicating that the water of the studied river appears suitable for irrigation. The outcomes of this study may significantly contribute to the formulation of sustainable strategies for the ecological rejuvenation of the Mundeswari River.

Spatiotemporal variations, source identification, and risk assessment of potentially toxic elements in the surface water of Felent Stream impacted by the silver mine.

The silver deposits located in the upper basin of the Felent Stream are currently the largest producing mine in the Türkiye. It is also significantly impacted by industrial, agricultural, and thermal spring-related waste in Kütahya Province. The main objectives of this study were to examine the spatiotemporal variations of 12 dissolved potentially toxic elements (PTEs) in the surface water of Felent Stream, to identify their possible sources, and to assess their probable risks. As a result of this study, among investigated PTEs, the highest mean concentrations of 3592-14,388 µg/L for Mg and the lowest of 0.15-0.19 µg/L for Cd were noted in Felent Stream water. The average concentrations of PTEs were found in the order of Mg > Ca > Na > As > Mn > B > Zn > Ni > Cu > Pb > Cr > Cd. Remarkably, during the dry season, there was a conspicuous escalation in the average PTEs contents of water, with an approximately multifold amplification. PTEs in stream water were evaluated for their potential ecotoxicological risks and possible sources. Based on ecological risk assessment indices, the stream exhibited low pollution levels during the wet season but displayed elevated pollution levels during the dry season, indicating a general shift towards heightened pollution conditions. The hazard index (HI) data for As exhibited significant potential noncarcinogenic risks across all monitoring stations. Conversely, the carcinogenic risk (CR) data underscored the imperative nature of addressing the health risks associated with As in the waters of the studied region. Mining activities were identified as the primary origin of PTEs based on principal component analysis (PCA). Moreover, upstream regions, proximal to the mining site, emerged as the most heavily contaminated areas according to cluster analysis (CA).

Water quality and dissolved load in the Chirchik and Akhangaran river basins (Uzbekistan, Central Asia).

Uzbekistan (Central Asia) is experiencing serious water stress as a consequence of altered climate regime, past over-exploitation, and dependence from neighboring countries for water supply. The Chirchik-Akhangaran drainage basin, in the Tashkent province of Uzbekistan, includes watersheds from the Middle Tien Shan Mountains escarpments and the downstream floodplain of the Chirchik and Akhangaran rivers, major tributaries of the Syrdarya river. Water in the Chirchik-Akhangaran basin is facing potential anthropogenic pressure from different sources at the scale of river reaches, from both industrial and agricultural activities. In this study, the major and trace element chemistry of surface water and groundwater from the Chirchik-Akhangaran basin were investigated, with the aim of addressing the geogenic and anthropogenic contributions to the dissolved load. The results indicate that the geochemistry of water from the upstream catchments reflects the weathering of exposed lithologies. A significant increase in Na+, K+, SO42-, Cl-, and NO3- was observed downstream, indicating loadings from fertilizers used in croplands. However, quality parameters suggest that waters are generally suitable for irrigation purposes, even if the total dissolved solid indicates a possible salinity hazard. The concentration of trace elements (including potentially toxic elements) was lower than the thresholds set for water quality by different regulations. However, an exceedingly high concentration of Zn, Mo, Sb, Pb, Ni, U, As, and B compared with the average river water worldwide was observed. Water in a coal fly-ash large pond related to the Angren coal-fired power plants stands out for the high As, Al, B, Mo, and Sb concentration, having a groundwater contamination potential during infiltration. Spring waters used for drinking purposes meet the World Health Organization and the Republic of Uzbekistan quality standards. However, a surveillance of such drinking-water supplies is suggested. The obtained results are indicators for an improved water resource management.

Occurrence of pharmaceuticals in Latin America: case study on hazard assessment and prioritization in Costa Rica.

Pharmaceuticals are considered as contaminants of emerging concern, and their occurrence in diverse environmental matrices has been described during the last 25 years. Nonetheless, pharmaceutical occurrence has not been evenly described worldwide, and reports from some geographical areas such as most parts of Latin America are scarce. This work aims to address the situation of water pollution due to pharmaceuticals in Latin America by means of two main goals: i. First, reviewing the monitoring studies performed in Latin America on this topic (period 2009-2024), which were conducted in Brazil, Mexico, Colombia, Ecuador, Peru and Argentina, to highlight the most frequently detected compounds from each therapeutic group in the region. ii. Second, analyzing the case of Costa Rica through the hazard assessment and prioritization of pharmaceuticals based on the monitoring performed in this country (years 2011; 2018-2019). The monitoring in Costa Rica comprised a total of 163 sampling points: wastewater treatment plants (WWTPs) (14 urban WWTPs plus two landfill WWTPs; total samples n = 44 influents and n = 34 effluents), nine hospital effluents (n = 32), wastewater from livestock farms (six swine farms and seven dairy farms; n = 23 influents and n = 37 effluents), 64 continental surface water sampling points (n = 137), and 61 coastal seawater sampling points (n = 61). Risk assessment of detected concentrations by the hazard quotient (HQ) approach (period 2018-2019) revealed a total of 25 medium or high-hazard compounds (out of 37 detected compounds). The prioritization approach (which included the Frequency of Appearance (FoA), the Frequency of PNEC exceedance (FoE), and the Extent of predicted no-effect concentration (PNEC) exceedance (EoE)), showed a critical list of nine pharmaceuticals: caffeine, diphenhydramine, acetaminophen, lovastatin, gemfibrozil, ciprofloxacin, ibuprofen, doxycycline and norfloxacin. These compounds should be taken into account as a first concern during the implementation of environmental policies related to pharmaceutical products in the region.

Microplastic pollution in the surface waters of the zuari river, goa, india.

Limited research has been conducted on microplastic (MP) contamination in the rivers of Goa. To address this gap, this study examines the levels of MP contamination in the surface water of the Zuari River, Goa. We investigate the abundance, characteristics (size, shape, colour, and polymer composition), and risk assessment of MPs. MPs were detected at all sampling stations in the Zuari River, with concentrations varying from 0.01 particles/L (S3) to 1.38 particles/L (S13). The average abundance of MPs in the water samples was 0.28 ± 0.35 particles/L. MPs were more common in the 0.3-1 mm size range (51.70%) than in the 1-5 mm range (48.30%). The most common MP shapes observed were fibers (37.88%) and fragments (29.66%). FTIR analysis confirmed the presence of polyethylene terephthalate, high-density polyethylene, polypropylene, and polyacrylamide carboxyl-modified MPs. The Pollution Load Index (PLI) showed an average value of 3.8, indicating significant contamination (PLI > 1). Scanning electron microscopy (SEM) revealed various degradation features such as pits, scratches, grooves, and cracks on the MPs surfaces, while energy dispersive X-ray spectroscopy (EDS) detected metals on the MP's surfaces. This study provides key insights into MP pollution in the Zuari River's surface water and lays the groundwork for future research and management strategies in the region.

Examining contaminant transport hotspots and their predictability across contrasted watersheds.

Hydrobiogeochemical processes governing water quantity and quality are highly variable in space and time. Focusing on thirty river locations in Québec, Canada, three water quality hotness indices were used to classify watersheds as contaminant transport hotspots. Concentration and load data for suspended solids (SS), total nitrogen (TN), and total phosphorous (TP) were used to identify transport hotspots, and results were compared across hotness indices with different data requirements. The role of hydroclimatic and physiographic characteristics on the occurrence and temporal persistence of transport hotspots was examined. Results show that the identification of transport hotspots was dependent on both the type of data and the hotness index used. Relationships between temporal and spatial predictors, however, were generally consistent. Annual transport hotspot occurrence was found to be related to temporal characteristics such as the number of dry days, potential evapotranspiration, and snow water equivalent, while hotspot temporal persistence was correlated to landcover characteristics. Stark differences in the identification of SS, TN, and TP transport hotspots were attributed to differences in mobilization processes and provided insights into dominant water and nutrient flowpaths in the studied watersheds. This study highlighted the importance of comparing contaminant dynamics across watersheds even when high-frequency water quality data or discharge data are not available. Characterizing hotspot occurrence and persistence, among hotness indices and water quality parameters, could be useful for watershed managers when identifying problematic watersheds, exploring legacy effects, and establishing a prioritization framework for areas that would benefit from enhanced routine monitoring or targeted mitigation strategies.

Intensive short-term sampling with long-term consequences: characterizing pollutant transport with implications for developing monitoring.

Riverine sampling of pollutants is commonly used to understand pollutants' transport pathways, relationships with hydrology, and overall presence in a waterbody. However, temporal gaps between sample collection introduce errors to these efforts, and guidance prescribing sampling frequency remains sparse. The magnitude of error often depends on a contaminant's transport mechanisms and local hydrologic conditions, making the creation of comprehensive sampling guidance difficult. This study analyzed a unique dataset that measured 18 analytes, including pesticides, nutrients, and pathogens, in three Iowa rivers for 90 consecutive days (May 4-August 1, 2000). This dataset provided a novel opportunity to relate pollutants to local hydrology and quantify errors associated with recurring sampling. Pesticide concentrations followed the spring flush phenomenon, where values were greatest during high streamflow in May and June but often depleted by July. Fecal coliform and total phosphorus (TP) also coincided with high flow, but unlike pesticides, their concentrations never diminished. Nitrate exhibited more complex behavior; concentrations were diluted during high flows and then increased as streamflow receded. Autocorrelations were significant for nitrate and atrazine in larger rivers but negligible for fecal coliform and TP. Loads were calculated for four pollutants with minimal non-detects (atrazine, fecal coliform, nitrate, and TP). We simulated intermittent sampling by selecting evenly spaced subsets of measured values to estimate loads, which were compared to the loads calculated using every daily sample to quantify error. This method typically overestimated nitrate loads but underestimated other pollutants, and errors often decreased in larger watersheds. Nitrate generally had the lowest error, while fecal coliform had the highest. We used these results to approximate the sampling frequency needed to bind errors within a certain threshold.

Water quality assessment and its pollution source analysis from spatial and temporal perspectives in small watershed of Sichuan Province, China.

Rapid socio-economic development has led to many water environmental issues in small watersheds such as non-compliance with water quality standards, complex pollution sources, and difficulties in water environment management. To achieve a quantitative evaluation of water quality, identify pollution sources, and implement refined management in small watersheds, this study collected monthly seven water quality indexes of four monitoring points from 2010 to 2023, and ten water quality indexes of 23 sampling points in the Shiting River and Mianyuan River which are tributaries of the Tuojiang River Basin. Then, water quality evaluation and pollution source analysis were conducted from both temporal and spatial perspectives using the Water Quality Index (WQI) method, the Absolute Principal Component Scores/Multiple Linear Regression (APCS-MLR) method, and the Positive Matrix Factorization (PMF) receptor modeling technique. The results indicated that except for total nitrogen (TN), the concentrations of other water quality indexes exhibited a decreasing trend, and all were divided into two obvious stages before and after 2016. Furthermore, the proportion of water quality grade of Good and above increased from 73.96 to 84.94% from 2010-2015 to 2016-2023, and the water quality grade of Good and above from upstream to downstream dropped from 100 to 23.33%. From the temporal scale, four and five pollution sources were identified in the first and second stages, respectively. The distinct TN pollutant is mainly affected by agricultural non-point sources (NPS), whose impact is enhanced from 17.76 to 78.31%. Total phosphorus (TP) was affected by the phosphorus chemical industry, whose contribution gradually weakened from 50.8 to 24.9%. From a spatial perspective, four and five pollution sources were identified in the upstream and downstream, respectively. Therefore, even though there are some limitations due to the data availability of water monitory and hydrology data, the proposed research framework of this study can be applied to the water environmental management of other similar watersheds.

Pollution, spatial distribution, and health risks assessment of nutrient concentration in surface water resources of Maroon-Jarahi Basin in southwestern Iran.

Nowadays, the introduction of nutrients caused by human activities is considered an environmental issue and a significant problem in river basins and coastal ecosystems. In this study, the concentration of nutrients ( NO 3 - and PO 4 3 - ) in the surface water sources of the Maroon-Jarahi watershed in the southwest of Iran was determined, and the pollution status and health risk assessment were done. The average concentration of nitrate and phosphate in Ludab, Maroon, Zard, Allah, Jarahi rivers, and Shadegan wetland were obtained at 2.25-0.59, 4.59-1.84, 4.07-2.02, 5.40-2.81, 11.51-4.67, 21.63 and 6.20 (mg/l), respectively. A comparison of the results with the World Health Organization (WHO) limit showed that nitrate was lower than in all stations, but phosphate was higher than the limit in some stations of the Maroon, Allah, Jarahi rivers, and Shadegan wetland. Calculation of linear regression analysis showed significant positive relationships between nitrate and phosphate in all surface water sources (except Ludab) and based on the N/P ratio, nitrogen was estimated as the limiting factor in phytoplankton growth (N/P < 16). The evaluation of the status of the Nutrient pollution index (NPI) was observed as: Shadegan > Jarahi > Allah > Maroon > Zard > Ludab that the Jarahi River and Shadegan wetland were in the medium pollution class (1 < NPI ≤ 3) and other waterbodies were in the non-polluted to low pollution state (NPI < 1). Calculation of the chronic daily intake (CDI) showed that water body nutrients cause more non-carcinogenic health risks through the oral route than dermal exposure, and according to HI, children's health is more at risk than adults. Findings showed that surface water resources especially downstream of the Maroon-Jarahi watershed are at eutrophication risk, and to control the nearby human activities and as a result increase the nutrients in these water resources, measures should be taken.

Assessment of the surface water quality and primary health risk in urban wastewater and its receiving river Kathajodi, Cuttack of eastern India.

Kathajodi, the principal southern distributary of the Mahanadi River, is the vital source of irrigation and domestic water use for densely populated Cuttack city which receives anthropogenic wastes abundantly. This study assesses the contamination level and primary health status of urban wastewater, and its receiving river Kathajodi based on the physicochemical quality indices employing inductively coupled plasma mass spectroscopy and aligning with guidelines from the United States Environmental Protection Agency (USEPA) and WHO. The high WQI, HPI, and HEI in the catchment area (KJ2, KJ3, and KJ4) indicate poor water quality due to the influx of domestic waste through the primary drainage system and effluents of healthcare units. A high BOD (4.33-19.66 mg L-1) in the catchment indicates high organic matter, animal waste, bacteriological contamination, and low DO, resulting in deterioration of water quality. CR values beyond limits (1.00E - 06 to 1.00E - 04) in three locations of catchment due to higher Cd, Pb, and As indicate significant carcinogenic risk, while high Mn, Cu, and Al content is responsible for several non-carcinogenic ailments and arsenic-induced physiological disorders. The elevated heavy metals Cd, Cu, Fe, Mn, Ni, and Zn, in Kathajodi, could be due to heavy coal combustion, vehicle exhaust, and industrial waste. On the other hand, Cu, Fe, K, and Al could be from agricultural practices, weathered rocks, and crustal materials. Positive significant (p ≤ 0.05) Pearson correlations between physicochemical parameters indicate their common anthropogenic origin and similar chemical characteristics. A strong correlation of PCA between elements and physiological parameters indicates their role in water quality deterioration. Assessing the surface water quality and heavy metal contents from this study will offer critical data to policymakers for monitoring and managing public health concerns.

Water quality dynamics and underlying controls in the Halton Region, Ontario.

We assessed the hydrochemistry of 15 watersheds in the Halton Region, southern Ontario, in high resolution (n > 500 samples across n > 40 streams) to characterize water quality dynamics and governing controls on major and trace element concentrations in this rapidly urbanizing region. In 2022, major water quality parameters were generally in line with historic monitoring data yet significantly different across catchments, e.g., in specific conductance, turbidity, phosphate and chloride, and trace element concentrations. Distinct hydrochemical signatures were observed between urban and rural creeks, with urban stream sections and sites near the river mouths close to Lake Ontario having consistently higher chloride (up to 700 mg/L) and occasional enrichment in nutrients levels (up to 8 and 20 mg/L phosphate and nitrate, respectively). Particularly upper reaches exhibited hydrochemical signatures that were reflective of the catchment surface lithologies, for instance through higher dissolved Ca to Mg ratios. Unlike for chloride and phosphate, provincial water quality guidelines for trace elements and heavy metals were seldom surpassed (on < 10 occasions for copper, zinc, cadmium, and uranium). Concentrations of other trace elements (e.g., platinum group elements or rare earth elements) were expectedly low (< 0.3 µg/L) but showed spatiotemporal concentration patterns and concentration-discharge dynamics different from those of the major water quality parameters. Our results help improve the understanding of surface water conditions within Halton's regional Natural Heritage Systems and demonstrate how enhanced environmental monitoring can deliver actionable information for watershed decision-making.

Spatio-temporal variation in water quality due to the anthropogenic impact in Rudrasagar Lake, a Ramsar site in India.

Rudrasagar Lake, a vital habitat for diverse flora and fauna, supports over 2000 households to sustain their daily livelihoods. The current study attempts to examine the impact of human activities on spatio-temporal variation in the water quality of the study area. The study integrates extensive field surveys, sample processing, and statistical analysis to assess the recent status of wetland health. Latin Square Matrix (LSM) was employed to select the sampling sites while the Inverse Distance Weighting (IDW) interpolation technique was used for spatial variation mapping. Modified Weighted Arithmetic Water Quality Index (MWAWQI) and Comprehensive Pollution Index (CPI) were utilized for assessing seasonal variation water quality and pollution loads, respectively. The results showed that dissolved oxygen (DO) was strongly influenced by the tributaries, and recreational activities have substantially influenced the highest concentrations of biochemical oxygen demand (BOD), and total suspended solids (TSS). The central portion of the lake is particularly susceptible to pollution from extensive fishing and recreational activities while peripheral sites are strongly influenced by agricultural run-offs, seepages from brick industries, and municipal wastes characterized by high concentrations of pH, total hardness (TH), oxidation-reduction potential (ORP). The findings reveal remarkable spatio-temporal fluctuations and highlight the areas within the lake susceptible to anthropogenic activities. The study proposed a sustainable management model to ameliorate anthropogenic threats. Moreover, the study contributes to the scientific understanding of the challenges and ensures the long-term viability of wetland health as a vital ecological and socio-economic resource.

Spatio-temporal characteristics and multi-scale risk identification of pollution load based on sensitivity analysis in small watersheds located in Tuojiang River Basin, China.

High-quality development of water resources supports high-quality socio-economic development. High-quality development connects high-quality life, and clarifying the key management contents of small watersheds plays an important role in building ecologically clean small watersheds and promoting regional production and life. Previous research on pollution loads has focused on examining the impact of various external drivers on pollution loads but still lacks research on the impact of changes in pollution sources themselves on pollution loads. In this study, sensitivity analysis was used to determine the impact of changes from different sources on the total pollution loads, which can recognize the critical pollution sources. We first employed the pollutant discharge coefficient method to quantify non-point source pollution loads in the small watershed in the upstream Tuojiang River basin from 2010 to 2021. Then, combination sensitivity analysis with Getis-Ord Gi* was used to identify the critical sources and their crucial areas at the global, districts (counties), and towns (streets) scales, respectively. The results indicate: (1) The pollution loads of COD, NH3-N, TN, and TP all show a decreasing trend, reducing by 18.3%, 16.2%, 18.6%, and 28.1% from 2010 to 2021, respectively; (2) Livestock and poultry breeding pollution source is the most critical source for majority areas across watershed; (3) High-risk areas are mainly concentrated in Jingyang district and its subordinate towns (streets). There is a trend of low-pollution risk areas transitioning to high-pollution risk areas, with high-risk areas predominantly concentrated in the southeast and exhibiting a noticeable phenomenon of pollution load spilling around. This study can promote other similar small watersheds, holding significant importance for non-point source pollution control in small watersheds.