In the eastern region of the Algerian Northern Sahara, the groundwater is the only resource for drinking water supply and irrigation. This study aimed to assess the physical-chemical quality of groundwater with exposition of the fluoride distribution in the eastern region of Algeria taking as case study Ouargla area. The sampling campaign was carried out in such a way to cover the exploited aquifers (Miopliocene and Senonian).  Water temperature, pH, conductivity, hardness, alkalinity, principal ions (Sodium, Potassium Calcium, Magnesium, Bicarbonates, Nitrates, Sulfates, and Chlorides) and the fluoride content in the groundwater were measured and determined. Examination and validation of obtained results were by the use ionic balance method and the hydrochemical analysis by Piper, Stabler and Richards diagrams. The obtained results of our study show that the groundwater of the Ouargla area presents a chlorinated sodium and potassium facies. Moreover, the groundwater quality in the study area is of poor quality; it is hard and characterized by very high mineralization, The Richards' diagram indicates that the groundwater of the study area are unsuitable for irrigation. The spatial distribution of fluoride ions in groundwater of the terminal complex shows that fluoride levels in Ouargla exceed the World Health Organization standard.

Microplastics pollution has become a matter of global concern because of its effects on aquatic life and the ecosystem. This study investigated the abundance and types of microplastics found in an urban canal of Thailand. Water quality and the relationship between microplastics pollutants and the physicochemical properties of water quality were also analyzed to provide evidence for this study. The mean abundance of microplastics was 370 ± 140 particle(p)/m3. The highest number and concentration of microplastics were found on surface water corelated with urbanization. Transparent brown and transparent colors in the form of film and fiber/lines were the predominant morphology. Polypropylene (PP) and polyethylene (PE) were the most abundant polymer type in all surface water samples. Furthermore, water quality was related with microplastic pollution. The physicochemical properties of turbidity (0.99), conductivity (0.97), total solid (0.95) and biological oxygen demand (0.84) were accounted for greatest influences on microplastics distribution. The estimated equation of microplastics was also closely corelated with water quality. These results demonstrate that microplastic pollution has progressed more in poor water quality than good water quality, indicating that the inflow process and sources of microplastics are similar to those of other pollutants. Therefore, this study is expected to encourage and enforce solid waste and wastewater management policies that prevent microplastics pollution in the environment.

In the present investigation, coagulation-flocculation and fenton process in conjunction with phytoremediation by water hyacinth (Eicchornia crassipes) were applied to treat the most frequently occurred contaminants in textile wastewater. The mean values of EC, TDS, turbidity, pH, DO, BOD, COD and TOC in the raw effluents were 2300 μSCm-1, 1260 mgL-1, 48.28 FTU, 10.5, 1.2 mgL-1, 265 mgL-1, 522 mgL-1 and 12.8 mgL-1, respectively whereas the average concentration of Cr, Pb, Mg, Cu, Ni and Zn was 0.86, 1.21, 10.97, 0.47, 2.85 and 0.52 mg/L, correspondingly which evidently indicated that the effluents were highly contaminated compared to Bangladeshi standard. The results demonstrated that the values of EC, TDS, turbidity, pH, BOD, COD and TOC reduced significantly compared to raw effluents by both coagulation-flocculation and fenton processes and meet the standards set by BDS-ECR except BOD and DO. After being treated the COD value reduced to 70 mg/L (86.56%) and 188 mg/L (63.985%) from its initial concentration by coagulation-flocculation and fenton process, respectively on the other hand TOC removal efficiency by coagulation- flocculation process was 97.8125%, significantly greater than fenton methods where removal efficiency was 63.9%. However, the BOD removal efficiency by both treatment processes was ~50% which was not satisfactory compared to local standard. Interestingly, the concentration of DO increased substantially by both coagulation-flocculation (1.2 to 4.4 mg/L) and fenton process (1.2 to 3.85 mg/L). In case of trace elements removal, the combination of coagulation-flocculation-water hyacinth and fenton-water hyacinth show promising results where the removal efficiency of coagulation-flocculation-water hyacinth and fenton-water hyacinth was 24%-76% and 17%-76.36%, respectively. Therefore, it can be concluded that coagulation-flocculation-water hyacinth combination is better than fenton-water hyacinth combination in terms of trace metals removal. Textile effluents treatment and management is considered as one of the most significant issues in Bangladesh herein based on the this study, combination of chemical and phytoremediation technologies could be a promising sustainable low cost alternative for Bangladesh’s textile industrial sector.

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 study was conducted to assess surface water quality in Ca Mau peninsula using multivariate statistical analysis. Fifty-one water samples with the parameters of pH, dissolved oxygen (DO), total suspended solids (TSS), biochemical oxygen demand (BOD5), chemical oxygen demand (COD), ammonium (N-NH4+), orthophosphate (P-PO43-) and total coliform were used in the evaluation. Water quality is assessed using national standard and water quality index (WQI). The methods of cluster (CA), discriminant (DA), principal component analysis (PCA) were used to analyze the variation patterns of water quality. The surface water was contaminated with organic matters, suspended solids, nutrients, and microorganisms. DA revealed that DO, TSS, BOD5 and pH contributed 76.91% to the seasonal variation of water quality. Water quality is classified from bad to heavily polluted. CA grouped water quality into 7 clusters and DO, TSS, BOD5, COD and coliform of the clusters 1-3 were significantly higher than those of the clusters 4-7. PCA presented that PC1-PC3 was the main sources affecting water quality, explaining 85.45% of the variation in water quality. The sources of pollution can be human (domestic wastewater, waste from agriculture, fisheries, industry, landfills), natural (hydrological regime, rainwater overflow, river bank erosion). pH, DO, BOD5, COD, TSS, N-NH4+, P-PO43- and coliform have an impact on water quality and need to be continuously monitored. However, for the multivariate statistical method to be more effective, an initial data set with several water quality parameters sampling locations is needed. The current results provide scientific information and support local water quality monitoring activities.

The purpose of this study was to evaluate the concentrations of potentially toxic elements in the Suches river using standardized geochemical indices and to identify the main sources of contamination in the section from the Suches lagoon up to 33.8 km downstream of the effluent river, in the district of Cojata, Puno, Peru. The concentration of Al, Ba, Co, Fe, M, Ni, P, V and Zn in sediments of the Suches river was determined by means of mass spectrometry from October 2019 to February 2020. The values of Co, Fe, Mn, Ni, P and Zn exceeded the base values of contamination according to the general geological references while Al, Ba and V, did not surpass them. The contamination factor showed that the elements Co and Ni revealed a very high level of contamination, while the Zn, a considerable level. The area has an average pollution load index value of 2.24, indicating moderate general pollution. The elements Co, Ni, Al and Zn were within the moderate and extreme classification according to the pollution index. The Spearman's correlation analysis allowed determining the association between Al, Fe, Mn, P and V, which share a natural origin and the accumulation of these elements is due to the effects of weathering and soil erosion. The evaluation of the contamination indices and the correlation confirm that Cobalt, Nickel and Zinc are toxic elements associated with gold mining and agricultural activities.

The changes in diatom assemblages along an urban-to-rural gradient were characterized to assess the ecological status of the Sai Gon River, Vietnam. Diatoms and physico-chemical variables were measured at 10 stations during dry and rainy season. One-way ANOVA showed that diatom metrics and physicochemical variables were significantly different (p < 0.05) between the upper course sites and both the middle- and the lower sites. However, no significant differences were observed between the middle course sites and the lower course sites. Achnanthidium minutissimum and A. exigua were potential indicators of low nutrient in the upper course sites; Melosira granulata and Navicula viridula were preferred moderately eutrophic water in the middle course sites; while Navicula cryptocephala and Nitzschia palea were tolerant to very heavy pollution and dominant in the lower course sites. Canonical correlation analysis (CCA) results showed that concentration of TSS, TN, TP, BOD5 and COD were the most important factors in structuring benthic diatom communities in the Sai Gon River. The results of this study indicated that diatom community was sensitive to changes in urban condition and could be used as an indicator of urbanization.

One of the main aims of water resource planners and managers is to estimate and predict the parameters of groundwater quality so that they can make managerial decisions. In this regard, there have many models developed, proposing better management in order to maintain water quality. Most of these models require input parameters that are either hardly available or time-consuming and expensive to measure. Among them, the Artificial Neural Network (ANN) Models, inspired from human brain, are a better choice. The present study has simulated the groundwater quality parameters of Ramhormoz Plain, including Sodium Adsorption Ratio (SAR), Electrical Conductivity (EC), and Total Dissolved Solids (TDS), via ANN and ANN+ Particle Swarm Optimization (PSO) Models and at the end has compared their results with the measured data. The input data for TDS quality parameter is consisted of EC, SAR, pH, SO4, Ca, Mg, and Na, while for SAR, it includes TDS, pH, Na, and Hco3, and as for EC, it involves So4, Ca, Mg, SAR, and pH; all of them, gathered from 2009 to 2015. Results indicate that the highest prediction accuracy for SAR, EC, and TDS is related to the ANN + PSO model with the tangent sigmoid activation function so that both MAE and RMSE statistics have the minimum and R2 the maximum value for the model. Also the highest prediction accuracy is respectively related to EC, TDS, and SAR parameters. Considering the high efficiency of artificial neural network model, by training the PSO algorithm, it can be used in order to make managerial decisions and ensure monitoring and cost reduction results.

Seasonal variation in water quality of Anchar Lake was evaluated using multivariate statistical techniques- principal component analysis (PCA) and cluster analysis (CA). Water quality data collected during 4 seasons was analyzed for 13 parameters. ANOVA showed significant variation in pH (F3 = 10.86, P < 0.05), temperature (F3 = 65, P <0.05), Electrical conductivity (F3 = 32.72, P <0.05), Calcium (F3 = 36.84, P <0.05), Magnesium (F3 = 16.52, P <0.05), nitrate-nitrogenSeasonal variation in water quality of Anchar Lake has been evaluated, using two multivariate statistical techniques, namely Principal Component Analysis (PCA) and Cluster Analysis (CA). Water quality data, collected during four seasons, have been analyzed for 13 parameters and ANOVA has shown that pH (F3= 10.86, P < 0.05), temperature (F3 = 65, P < 0.05), electrical conductivity (F3= 32.72, P < 0.05), Calcium (F3= 36.84, P < 0.05), Magnesium (F3= 16.52, P < 0.05), nitrate-nitrogen (F3= 48.06, P < 0.05), ammonical nitrogen (F3 =198.75, P < 0.05), and dissolved oxygen (F3= 4.96, P < 0.05) varied by season, whereas the substantial variations of sodium (F2= 7.18, P <0.05), phosphate-phosphorous (F2= 25.31, P < 0.05), biological oxygen demand (F2= 11.02, P < 0.05), and chemical oxygen demand (F2=37.73, P < 0.05) were based on different sites. CA has grouped the three sampling sites throughout the four seasons into three clusters of similar water quality as relatively Less-Polluted (LP), Medium-Polluted (MP), and Highly-Polluted (HP). In addition, PCA has been applied on the extract to recognize the factors, responsible for water quality variations in four seasons of the year, resulting in four principal components for winter, summer, and autumn, five ones for spring, accounting for 79.58%, 89.07%, 83.34%, and 93.13% of total variance respectively. Thus the factors, responsible for water quality variation, are mainly related to domestic wastewaters, seasonal variation, agricultural runoff, and catchment geology. These results will help decision-makers better understand the influence of various factors on water quality and manage pollution/eutrophication adaptively in Anchar Lake.

The present study has been conducted to assess the surface water quality of Halda River from September 2015 to March 2016. DO, BOD5, COD, pH, EC, Chloride, Alkalinity, and Hardness concentrations in water samples have been found to range within 0.93-5.15 mg/L, 30-545 mg/L, 43-983 mg/L, 6.3-7.3, 110-524 uS/cm, 12-56 mg/L, 35-67 mg/L, and 38-121 mg/L, respectively. Multivariate statistical analyses, such as Principal Component Analysis (PCA) as well as Correlation Matrix (CM) have revealed significant anthropogenic pollutant intrusions in water. Cluster Analysis (CA) has indicated decent results of rendering three different groups of resemblance between the two sampling sites, reflecting the different water quality indicators of the river system. A very strong positive linear relation has been found between COD and BOD (1.000), hardness and EC (0.993), pH and DO (0.979), hardness and COD (0.929), hardness and BOD (0.924), EC and COD (0.922), and EC and BOD (0.916) at a significance level of 0.01, proving their common origin entirely from industrial effluents, municipal wastes, and agricultural activities. River Pollution Index (RPI) has indicated that the water from rivers at Kalurghat and Modhunaghat varied from low to high pollution, which is due to the former area's being mostly industrial zone with some domestic sewage, while the latter underwent less industrial activities. On the contrary, lots of agricultural activities have been found in Modhunaghat. Use of river water can pose serious problems to human health and aquatic ecosystem via biological food chain. The present research suggests special preference for proper management of the river with eco-friendly automation along with development of the country's sustainable economic.