The aim of this study was to assess the environmental impact of socio-cultural practices on the water quality of River Ganga at the foothills of the Garhwal Himalayas in Uttarakhand State, India. The physico-chemical parameters that contributed to the temporal variation and pollution in the river were identified in this study. Principal component analysis (PCA) and Cluster analysis (CA) were used in the identification of anthropogenic factors (industrial, urban sewage, agricultural, land use and mining activities) and natural factors (soil erosion, weathering). The results of this study show that total coliform, fecal coliform, nitrate, sodium, phosphate, sulphate, TDS (Total dissolved solids), temperature, BOD (Biochemical oxygen demand), calcium and chloride are parameters significantly contributing to pollution load.

The development of a surface water evaluation index is a critical factor in the assessment, restoration and protection of stream water quality. Quantifying water pollution in specific grade using dominant parameters is important, as this can explain the current state of water pollution with accuracy. As a result, an integrated multi-parameter water quality index has been developed. It is based on the 10 most prevailing parameters (pH, conductivity, nitrate ions, phosphate ions, Escherichia coli number, cadmium, chromium, lead, copper and manganese) with a scale of 1 to 4, wherein the grades are classified into 1: good; 1.1-1.5: slightly polluted; 1.6-2.0: moderately polluted; 2.1-2.9: heavily polluted and 3.0-4.0: gravely polluted. The measuring stick used was according to the 2011 background values of the World Health Organization (WHO) in which a value of 0.1 was attributed for each, so that the final grade can be calculated. Water quality data were successfully fitted in an integrated multi-parameter water quality index to measure the river water level of pollution, and effectively represented every water bodies. This innovative index is able to quantify pollution with respect to seasons, geography and geomorphology of the respective rivers. Although operative, this index still lacks scientific integrity and as such, more synoptic experiments in the rivers of developing countries are recommended to attain a pragmatic feature.

In this study, we used publicly available GIS layers and statistical tree-based modeling (CART and Random Forest) to predict pathogen indicator counts at a regional scale using 88 spatially explicit landscape predictors and 6657 samples from non-estuarine streams in the Oregon Coast Range. A total of 532 frequently sampled sites were parsed down to 93 pathogen sampling sites to control for spatial and temporal biases. This model's 56.5% explanation of variance, was comparable to other regional models, while still including a large number of variables. Analysis showed the most important predictors on bacteria counts to be: forest and natural riparian zones, cattle related activities, and urban land uses. This research confirmed linkages to anthropogenic activities, with the research prediction mapping showing increased bacteria counts in agricultural and urban land use areas and lower counts with more natural riparian conditions.

Eutrophication is a key water quality issue triggered by increasing nitrogen (N) and phosphorus (P) levels and potentially posing risks to freshwater biota. We predicted the probability that an invertebrate species within a community assemblage becomes absent due to nutrient stress as the ecological risk (ER) for European lakes and streams subjected to N and P pollution from 1985 to 2011. The ER was calculated as a function of species-specific tolerances to NO3− and total P concentrations and water quality monitoring data. Lake and stream ER averaged 50% in the last monitored year (i.e. 2011) and we observed a decrease by 22% and 38% in lake and stream ER (respectively) of river basins since 1985. Additionally, the ER from N stress surpassed that of P in both freshwater systems. The ER can be applied to identify river basins most subjected to eutrophication risks and the main drivers of impacts.

Appalachian surface coal mine overburden affects water quality as drainage percolates through spoil disposal fills. This study evaluated leaching potentials of 15 spoils from south-central Appalachia. Most bulk samples were non acid-forming, all were low in total-S, (≤0.34%), and initial saturated paste specific conductance (SC) ranged from 264 to 3560 μS cm−1. Samples were leached unsaturated (40 cycles) and leachates analyzed for pH, SC, and ion composition. Overall, leachates from unweathered spoils were higher in pH and SC than leachates from weathered spoils. Fine-textured spoils generally produced higher SCs than more coarsely textured spoils. Mean SC for all spoils decreased rapidly from an initial peak of 1468 μS cm−1 (±150) to 247 μS cm−1 (±23). Release patterns for most major ions reflected declining SC. Bicarbonate typically increased with successive leaches, replacing sulfate as the dominant anion. Column SC values were comparable to relevant published field data.

Few studies have assessed social inequalities in exposure to drinking water contaminants. This study explores this issue in 593 rural municipalities of Québec, Canada. Quartiles of an ecological composite deprivation index were used as a proxy of socioeconomic status. Total trihalomethanes (TTHMs) and lead were chosen as proxies of chemical drinking water quality. The results show that the majority of deprived rural municipalities apply no treatment to their water (26%) or use a basic treatment (51%), whereas a relative majority of the wealthiest municipalities (40%) use advanced treatment. The proportion of municipalities having important lead (>5 μg/L) levels is highest in most deprived municipalities. Moreover, most deprived municipalities have a higher risk of high tap lead levels (RR = 1.33; 95%CI: 1.30, 1.36). Conversely, most deprived municipalities have a lower risk of high TTHMs levels (RR = 0.78; 95%CI: 0.69, 0.86). These findings suggest an environmental inequality in drinking water contaminants distribution in rural municipalities.

For twenty-five world lakes and three engineered nanoparticles (ENP), lake retention was calculated using a uniformly mixed lake mass balance model. This follows similar approaches traditionally used in water quality management. Lakes were selected such that lake residence times, depths and areal hydraulic loadings covered the widest possible range among existing lakes. Sedimentation accounted for natural colloid as well as suspended solid settling regimes. An ENP-specific mixed sedimentation regime is proposed. This regime combines ENP sedimentation through slow settling with natural colloids from the water column, with faster settling with suspended solids from a selected part of the water column. Although sedimentation data and hydrodynamic concepts as such were not new, their first time combination for application to ENPs shows in which cases lake retention is important for these particles. In combination with ENP emission data, lake retention translates directly into potential risks of ENPs for lake benthic communities.

California's Stream Pollution Trends program (SPoT) assesses long-term water quality trends, using 100 base-of-the-watershed sampling sites. Annual statewide sediment surveys from 2008 to 2012 identified consistent levels of statewide toxicity (19%), using the freshwater amphipod Hyalella azteca. Significant contaminant trends included a decrease in PCBs, stable concentrations of metals and PAHs, and a statewide increase in detections and concentrations of pyrethroid pesticides. The pyrethroid pesticide bifenthrin was detected in 69% of samples (n = 410). Detection of toxicity increased in a subset of samples tested at a more environmentally relevant test temperature (15 °C), and the magnitude of toxicity was much greater, indicating pyrethroid pesticides as a probable cause. Pyrethroid toxicity thresholds (LC50) were exceeded in 83% of samples with high toxicity. Principal components analysis related pyrethroids, metals and total organic carbon to urban land use.

Present study deals with the river Ganga water quality and its impact on metal speciation in its sediments. Concentration of physico-chemical parameters was highest in summer season followed by winter and lowest in rainy season. Metal speciation study in river sediments revealed that exchangeable, reducible and oxidizable fractions were dominant in all the studied metals (Cr, Ni, Cu, Zn, Cd, Pb) except Mn and Fe. High pollution load index (1.64–3.89) recommends urgent need of mitigation measures. Self-organizing Map-Artificial Neural Network (SOM-ANN) was applied to the data set for the prediction of major point sources of pollution in the river Ganga.

In reverse osmosis, a frequently used technology in water desalination processes, wastewater (RO concentrate) is generated containing the retained solutes as well as so-called antiscalants (AS), i.e. chemical substances that are commonly applied to prevent membrane-blocking. In this study, a risk assessment of a possible discharge of concentrate into a small stream was conducted. The acute toxicity of two concentrates containing two different ASs and of concentrate without AS to the amphipods Gammarus pulex and Gammarus roeseli was studied. Mortality of gammarids exposed to the concentrate without AS was not different to the control, whereas concentrates including ASs caused mortality rates up to 100% at the highest test concentrations after 168 h. Resulting EC50-values were 36.2–39.4% (v/v) after 96 h and 26.6–58.0% (v/v) after 168 h. These results suggest that the ecotoxicological relevance of antiscalants is greater than currently assumed.