Assessment of water quality using chemometric tools: a case study of river Cooum, South India

Spatiotemporal Variation Characteristics of Water Pollution and the Cause of Pollution Formation in a Heavily Polluted River in the Upper Hai River

Blackening and odorization of heavily polluted rivers has become a serious concern and threat to ecological and human health. This paper aims to gain a deeper understanding of changes in water pollution and the cause of pollution formation in a heavily polluted river in the upper Hai River. In this study, comprehensive water quality index (CWQI) and multivariate statistical techniques (MSTs) were applied to assess the spatiotemporal variation characteristics of water pollution and to identify potential pollution sources. The seasonal Mann–Kendall (SMK) test and the SMK test of flow-adjusted concentrations were effectively used to explore the temporal variation trends of major pollutants and the causes of their formation. Data of 15 water quality parameters were analyzed during 1980–2018 at 19 monitoring sites in the mainstream and major tributaries of the Xinxiang Section of the Wei River (XSWR). The results showed that the rivers were seriously polluted from 1991 to 2009, but the water quality improved after 2010. Nineteen sampling sites were divided into a low pollution region and a high pollution region. In the flood season, the pollution sources were mainly domestic sewage, industrial wastewater, agricultural runoff, biochemical pollution, and natural sources. In the nonflood season, the pollution sources were mainly domestic sewage and industrial wastewater. In recent years, the water quality of seriously polluted river has generally improved, mainly due to reductions in pollutant discharge from point sources and nonpoint sources.

Plasticizers and bisphenol A in Adyar and Cooum riverine sediments, India: occurrences, sources and risk assessment

Adyar and Cooum, the two rivers intersecting Chennai city, are exposed to serious pollution due to the release of large quantities of dumped waste, untreated wastewater and sewage. Sediments can act as repository for emerging organic contaminants. Hence, we have monitored the occurrence and risk associated with plasticizers [six phthalic acid esters (PAEs), bis(2-ethyl hexyl adipate) (DEHA)] and bisphenol A (BPA) in surface riverine sediments of Adyar and Cooum rivers from residential/commercial, industrial and electronic waste recycling sites. Σ₇plasticizers (PAEs + DEHA) in the Adyar riverine sediment (ARS) and Cooum riverine sediment (CRS) varied between 51.82-1796 and 28.13-856 ng/g, respectively. More than three-fourth of Σ₇plasticizers came from bis(2-ethylhexyl) phthalate (DEHP), in accordance with the high production and usage of this compound. BPA varied between 10.70-2026 and 7.58-1398 ng/g in ARS and CRS, respectively. Average concentrations of plasticizers and BPA were four times higher in electronic waste (e-waste) recycling sites when compared with industrial and residential/commercial sites. BPA and DEHP showed a strong and significant correlation (R² = 0.7; p < 0.01) in the e-waste sites thereby indicating common source types. Sites present at close proximity to raw sewage pumping stations contributed to 70% of the total BPA observed in this study. For the derived pore water concentration of plasticizers and BPA, the ecotoxicological risk has been found to be higher in ARS over CRS. However, sediment concentrations in all the sites of ARS and CRS were much below the recommended serious risk concentration for human (SRC_human) and serious risk concentration for ecotoxicological (SRC_eco).

Assessment of surface water quality status of the Aby Lagoon System in the Western Region of Ghana

The pollution status of the Tendo Lagoon, the upstream section of the Aby Lagoon System, was investigated. The water temperature, pH, turbidity, dissolved oxygen (DO), electrical conductivity (EC), nitrates (NO₃^-), and phosphate (PO₄^3-) levels were evaluated using samples taken during the wet and dry seasons to assess the variabilities in water quality in the area. The water quality data was subjected to paired t-test, One-way ANOVA, Factor Analysis, Cluster analysis (CA) as well as a Water Quality Index (WQI) evaluation using the Canadian Council of Ministers of the Environment (CCME) model. The paired sample t-test confirmed that the surface water quality varies significantly between the wet and dry season samples (p < 0.05) except for phosphate loads which may be contributed largely by year-round municipal waste discharges. The results of the ANOVA showed that the variation of the water quality parameters among sampling stations was not statistically significant except for turbidity which was relatively higher in the upstream sections where the Tano River enters the lagoon. The results of FA indicated that three significant factors–relating to the degradation of organic materials, suspended solids (turbidity) and nutrients- accounted for 73.65% of spatio-temporal variations in the water quality. The CA showed that the eight sampling stations can be grouped into four distinct clusters based on their water quality. The source of pollution in the demarcated sections of the Aby Lagoon was concluded to be largely due to the result of localized anthropogenic inputs of domestic waste and sediments carried from the upstream in the Tano River. An evaluation of the CCME WQI for the sampling stations revealed that all the sampling stations showed marginal water quality relative to the target water quality range recommended by the Water Resources Commission (WRC) of Ghana for domestic use and protection of aquatic life. Monitoring programs were recommended with effective management measures instituted and implemented for the sustainability of the lagoon and the Tano River Basin.

Water Quality of Inflows to the Everglades National Park over Three Decades (1985⁻2014) Analyzed by Multivariate Statistical Methods

The Everglades, a vast subtropical wetland, dominates the landscape of south Florida and is widely recognized as an ecosystem of great ecological importance. Data from seven inflow sites to the Everglades National Park (ENP) were analyzed over three decades (1985–2014) for temporal trends by the STL (integrated seasonal-trend decomposition using LOESS) method. A cluster analysis (CA) and principal component analysis (PCA) were applied for the evaluation of spatial variation. The results indicate that the water quality change trend is closely associated with rainfall. Increasing rainfall results in increasing flow and thus, decreasing concentrations of nitrogen and phosphorus. Based on 10 variables, the seven sampling stations were classified by CA into four distinct clusters: A, B, C, and D. The PCA analysis indicated that total nitrogen (TN) and total phosphorus (TP) are the main pollution factors, especially TN. The results suggest that non-point sources are the main pollution sources and best management practices (BMPs) effectively reduce organic nitrogen. However, TN and TP control is still the focus of future work in this area. Increasing the transfer water quantity can improve the water quality temporarily and planting submersed macrophytes can absorb nitrogen and phosphorus and increase the dissolved oxygen (DO) concentration in water, continuously improving the water quality.

Fluoride contamination in groundwater sources in Southwestern Nigeria: Assessment using multivariate statistical approach and human health risk

The present study investigated the ionic and fluoride concentrations in tap water and its associated health risk to local dwellers of Ogun State (Abeokuta south), Nigeria. 63 samples were collected from twenty-one different locations. Results obtained revealed the mean concentration of fluoride (F^-) as 1.23 mg/L. Other water quality parameters such as total dissolved solids (TDS), electrical conductivity (EC), F^-, Fe^2+, and SO₄^2- surpassed the WHO guidance for drinking water. Strong positive correlation was observed between F^- and TDS; F^- and pH; TDS and EC; TDS and Mg²⁺; TDS and SO₄^2-; TDS and HCO₃^-; EC and HCO₃^-; EC and SO₄^2-; Na⁺ and Cl^-; SO₄^2- and Cl^-. In addition, Empirical Bayesian Kriging (EBK) model was employed to spatially distribute the concentration of the analyzed elements within the study region. The chronic daily dose (CDD) and hazard quotient (HQ) were also used to evaluate the health risk associated with F^-, considering dermal and ingestion as pathways. The results revealed that the associated HQ for infants between the age range of 6-12months within about 91% of the study region surpassed the accepted HQ limit. However, the HQ for age categories 11-16years; >65years; 18-21years; 21years; 16-18years within 95.2%, 90.5%, 80.95% and 100% of the study location were less than 1. Conclusively, the HQ values obtained in this study should serve as a baseline information for water management authorities, policymakers and the society at large towards addressing these pollution issues.

Assessment of geospatial and hydrochemical interactions of groundwater quality, southwestern Nigeria

Groundwater pollution resulting from anthropogenic activities and poor effluent management is on the rise in Nigeria. Hence, groundwater used for domestic purposes is questionable and therefore calls for scientific scrutiny. Investigation of hydrochemical interactions and quality of groundwater resource is essential in order to monitor and identify sources of water pollutants. As a result, groundwater samples were collected from 21 locations in Abeokuta South, Nigeria and analyzed for physicochemical parameters using standard methods. Results obtained were subjected to hydrochemical and geospatial analyses. Water quality parameters investigated exhibited wide variations from location to location. Fe²⁺, Mg²⁺, SO₄^2-, Cl^-, total hardness (TH), Mn, Na⁺, NO₃^-, SiO₂, and alkalinity exhibited the highest levels of variation with coefficients of variation of 131.3, 92.8, 83.9, 76.7, 65.9, 64.3, 57.6, 57.2, 57.0, and 52.5, respectively. The average pH value was 6.76 with 71% of the water samples being slightly acidic. Na²⁺, Mg²⁺, Fe²⁺, and EC contents exhibited the most violation of drinking water standards with percent violations of 100, 52.4, 47.6, and 47.6%, respectively. Parameters, such as Mn, Ca²⁺, NO₃^-, and CO₃^2-, were within the WHO guideline values for drinking water in all the samples. The highest level of significant correlation was found to exist between Na⁺ and Cl^- (r = 0.84, α = 0.01). Six principal components, which explained 83.5% of the variation in water quality, were extracted with the first (34.1%) and second components (15.7%) representing the influence of mineral dissolution and anthropogenic practices, respectively, on the hydrochemistry of the area. Four hydrochemical clusters were identified with distinctly partitioned water quality. Further analysis revealed that 38, 29, 24, and 9% of the samples were the Na-K-HCO₃, Na-K-Cl-SO₄, Ca-Mg-HCO₃, and Ca-Mg-Cl-SO₄ types, respectively. Anthropogenic activities are increasing threat to groundwater quality in the study location and therefore call for urgent attention. There is also a need for routine monitoring of groundwater in Abeokuta.

Modelling spatio-temporal heterogeneities in groundwater quality in Ghana: a multivariate chemometric approach

Chemometric techniques were applied to evaluate the spatial and temporal heterogeneities in groundwater quality data for approximately 740 goldmining and agriculture-intensive locations in Ghana. The strongest linear and monotonic relationships occurred between Mn and Fe. Sixty-nine per cent of total variance in the dataset was explained by four variance factors: physicochemical properties, bacteriological quality, natural geologic attributes and anthropogenic factors (artisanal goldmining). There was evidence of significant differences in means of all trace metals and physicochemical parameters (p < 0.001) between goldmining and non-goldmining locations. Arsenic and turbidity produced very high value F's demonstrating that 'physical properties and chalcophilic elements' was the function that most discriminated between non-goldmining and goldmining locations. Variations in Escherichia coli and total coliforms were observed between the dry and wet seasons. The overall predictive accuracy of the discriminant function showed that non-goldmining locations were classified with slightly better accuracy (89%) than goldmining areas (69.6%). There were significant differences between the underlying distributions of Cd, Mn and Pb in the wet and dry seasons. This study emphasizes the practicality of chemometrics in the assessment and elucidation of complex water quality datasets to promote effective management of groundwater resources for sustaining human health.

Microbial, physical and chemical properties of irrigation water in rice fields of Southern Brazil

This paper presents the results of the statistical analysis of microbiological, physical and chemical parameters related to the quality of the water used in rice fields in Southern Brazil. Data were collected during three consecutive crop years, within structure of a comprehensive monitoring program. The indicators used were: potential hydrogen, electrical conductivity, turbidity, nitrogen, phosphorus, potassium, calcium, total and fecal coliforms. Principal Component and Discriminant Analysis showed consistent differences between the water irrigation and drainage, as the temporal variation demonstrated a clear reduction in the concentration of most of the variables analyzed. The pattern of this reduction is not the same in the two regions - that is, the importance of each of the different variables in the observed differentiation is modified in two locations. These results suggested that the variations in the water quality utilized for rice irrigation was influenced by certain specific aspects of each rice region in South Brazilian - such as anthropic action or soil/climate conditions in each hydrographic basin.

Differentiating the Spatiotemporal Distribution of Natural and Anthropogenic Processes on River Water-Quality Variation Using a Self-Organizing Map With Factor Analysis

To elucidate the historical improvement and advanced measure of river water quality in the Taipei metropolitan area, this study applied the self-organizing map (SOM) technique with factor analysis (FA) to differentiate the spatiotemporal distribution of natural and anthropogenic processes on river water-quality variation spanning two decades. The SOM clustered river water quality into five groups: very low pollution, low pollution, moderate pollution, high pollution, and very high pollution. FA was then used to extract four latent factors that dominated water quality from 1991 to 2011 including three anthropogenic process factors (organic, industrial, and copper pollution) and one natural process factor [suspended solids (SS) pollution]. The SOM revealed that the water quality improved substantially over time. However, the downstream river water quality was still classified as high pollution because of an increase in anthropogenic activity. FA showed the spatiotemporal pattern of each factor score decreasing over time, but the organic pollution factor downstream of the Tamsui River, as well as the SS factor scores in the upstream major tributary (the Dahan Stream), remained within the high pollution level. Therefore, we suggest that public sewage-treatment plants should be upgraded from their current secondary biological processing to advanced treatment processing. The conservation of water and soil must also be reinforced to decrease the SS loading of the Dahan Stream from natural erosion processes in the future.

Long-term evolution of the composition of surface water from the River Gharasoo, Iran: a case study using multivariate statistical techniques

We report an assessment of the quality of surface water from the River Gharasoo, Iran, with rainfall data. EC, pH, HCO(3)(-), Cl(-), SO(4), Ca(2+), Mg(2+), Na(+), %Na, and sodium adsorption ratio results, monitored monthly by two sampling stations over a period of 40 years, were held by the Hydraulic Works Organization in Kermanshah City. Principal-components analysis of the data revealed three factors for each station explaining 90.36 and 79.52 % of the total variance in the respective water-quality data. The first factor was chemical components resulting from point and non-point source pollution, especially industrial and domestic waste, and agricultural runoff, as a result of anthropogenic activity. Rainfall had significant negative correlation with bicarbonate only, at a level of 0.05, at station 1. Box-plot analysis revealed that, except for pH, the other studied characteristics were indicative of high pollution at station 1. Among the sources of pollution at station 1, Mg(2+) and Cl(-) data deviated most from normal distribution and included outliers and extremes. Hierarchical cluster analysis showed EC was substantially affected by rainfall. It is thus essential to treat industrial wastewater and municipal sewage from point sources by adoption of the best management practices to control diffuse pollutants and improve water quality of the Gharasoo River basin.

Use of multivariate statistical techniques for the evaluation of temporal and spatial variations in water quality of the Kaduna River, Nigeria

Multivariate statistical techniques, such as cluster analysis (CA) and principal component analysis/factor analysis (PCA/FA), were used to investigate the temporal and spatial variations and to interpret large and complex water quality data sets collected from the Kaduna River. Kaduna River is the main tributary of Niger River in Nigeria and represents the common situation of most natural rivers including spatial patterns of pollutants. The water samples were collected monthly for 5 years (2008-2012) from eight sampling stations located along the river. In all samples, 17 parameters of water quality were determined: total dissolved solids (TDS), pH, Thard, dissolved oxygen (DO), 5-day biochemical oxygen demand (BOD5), chemical oxygen demand (COD), NH4-N, Cl, SO4, Ca, Mg, total coliform (TColi), turbidity, electrical conductivity (EC), HCO3 (-), NO3 (-), and temperature (T). Hierarchical CA grouped 12 months into two seasons (dry and wet seasons) and classified eight sampling stations into two groups (low- and high-pollution regions) based on seasonal differences and different levels of pollution, respectively. PCA/FA for each group formed by CA helped to identify spatiotemporal dynamics of water quality in Kaduna River. CA illustrated that water quality progressively deteriorated from headwater to downstream areas. The results of PCA/FA determined that 78.7 % of the total variance in low pollution region was explained by five factor, that is, natural and organic, mineral, microbial, organic, and nutrient, and 87.6 % of total variance in high pollution region was explained by six factors, that is, microbial, organic, mineral, natural, nutrient, and organic. Varifactors obtained from FA indicated that the parameters responsible for water quality variations are resulted from agricultural runoff, natural pollution, domestic, municipal, and industrial wastewater. Mann-Whitney U test results revealed that TDS, pH, DO, T, EC, TColi, turbidity, total hardness (THard), Mg, Ca, NO3 (-), COD, and BOD were identified as significant variables affecting temporal variation in river water, and TDS, EC, and TColi were identified as significant variables affecting spatial variation. In addition, box-whisker plots facilitated and supported multivariate analysis results. This study illustrates the usefulness of multivariate statistical techniques for classification and processing of large and complex data sets of water quality parameters, identification of latent pollution factors/sources and their spatial-temporal variations, and determination of the corresponding significant parameters in river water quality.

Source apportionment of wastewater pollutants using multivariate analyses

A faster and cost-effective methodology has been developed to estimate the spatial and seasonal variations in wastewater quality and apportion the influencing sources through multivariate statistical techniques, cluster analysis and principal component analysis (PCA). Partially treated or untreated wastewater is released into the river from various industrial and domestic sources, which poses a serious threat to human health. Wastewater samples were collected from five stations along the river bank. PCA performed on overall wastewater samples revealed that in present study all the five sampling stations were influenced by sewage and industrial effluents mixed together. However, the pollutant levels were significantly different in the three groups of wastewater samples, which were confirmed by univariate analysis of principal component (PC) scores. Based on wastewater similarities, cluster analysis identified three groups (central, upstream and downstream) of sampling stations, which further confirmed univariate analysis of PCs scores. Spatial variations in wastewater quality reveled that the highest pollutant concentration was noted for group 1 and lowest for group 2. Seasonal variations in the wastewater quality revealed that highest values of pollutants were observed in low flow and lowest in high flow. Results of the present study obtained through multivariate analyses may be used to classify wastewater and identify the influencing sources of pollutants. The present study may be useful in reducing 11 % of the cost in future investigations. Thus, in future quality estimation of the representative wastewater samples would be faster as well as cost-effective approach.

An integrated assessment of seawater intrusion in a small tropical island using geophysical, geochemical, and geostatistical techniques

In this study, geophysics, geochemistry, and geostatistical techniques were integrated to assess seawater intrusion in Kapas Island due to its geological complexity and multiple contamination sources. Five resistivity profiles were measured using an electric resistivity technique. The results reveal very low resistivity <1 Ωm, suggesting either marine clay deposit or seawater intrusion or both along the majority of the resistivity images. As a result, geochemistry was further employed to verify the resistivity evidence. The Chadha and Stiff diagrams classify the island groundwater into Ca-HCO3, Ca-Na-HCO3, Na-HCO3, and Na-Cl water types, with Ca-HCO3 as the dominant. The Mg(2+)/Mg(2+)+Ca(2+), HCO3 (-)/anion, Cl(-)/HCO3 (-), Na(+)/Cl(-), and SO4 (2-)/Cl(-) ratios show that some sampling sites are affected by seawater intrusion; these sampling sites fall within the same areas that show low-resistivity values. The resulting ratios and resistivity values were then used in the geographical information system (GIS) environment to create the geostatistical map of individual indicators. These maps were then overlaid to create the final map showing seawater-affected areas. The final map successfully delineates the area that is actually undergoing seawater intrusion. The proposed technique is not area specific, and hence, it can work in any place with similar completed characteristics or under the influence of multiple contaminants so as to distinguish the area that is truly affected by any targeted pollutants from the rest. This information would provide managers and policy makers with the knowledge of the current situation and will serve as a guide and standard in water research for sustainable management plan.

An assessment of temporal variations in physicochemical and microbiological properties of barmouths and lagoons in Chennai (Southeast coast of India)

Two estuary and two coastal lagoon stations along Chennai, Southeast coast of India were monitored for 1year to study both physicochemical and microbiological properties of the water. Influence of the marine environment over the systems was evident by elevated salinity levels. Considerable concentrations of total heterotrophic bacterial count and fecal bacteria such as total coliforms, fecal coliforms and fecal streptococci were observed throughout the study period which evinced a pattern of anthropogenic activities. Principle component analysis was employed for assessing the overall pattern of variation within the data sets. Climatic variation was highly correlated with changes in water quality, i.e. the Northeast monsoon and Summer had influenced considerably the microbial occurrence as well as the physicochemical parameters such as total suspended solids, chloride, sulphate and salinity. However, the effect of the Southwest monsoon was less prominent than the Northeast monsoon with its heavy rains. As both estuaries revealed elevated concentrations of polluted water, these stations can be used as indicators or alerts for the water quality along the coastal zone of Chennai.

Chemometric characterization of river water quality

Various industrial facilities in the city of Varanasi discharge their effluent mixed with municipal sewage into the River Ganges at different discharge points. In this study, chemometric tools such as cluster analysis and box-whisker plots were applied to interpret data obtained during examination of River Ganges water quality. Specifically, we investigated the temperature (T), pH, total alkalinity, total acidity, electrical conductivity (EC), biochemical oxygen demand (BOD), chemical oxygen demand (COD), dissolved oxygen (DO), nitrate nitrogen (N), phosphate (PO 4(2-) ), copper (Cu), cadmium (Cd), chromium (Cr), nickel (Ni), iron (Fe), lead (Pb), and zinc (Zn) in water samples collected from six sampling stations. Hierarchical agglomerative cluster analysis was conducted using Ward's method. Proximity distance between EC and Cr was the smallest revealing a relationship between these parameters, which was confirmed by Pearson's correlation. Based on proximity distances, EC, Cr, Ni, Fe, N, COD, temperature, BOD, and total acidity comprised one group; Zn, Pb, Cd, total alkalinity, Cu, and phosphate (PO 4(2-) ) were in another group; and DO and pH formed a separate group. These groups were confirmed by Pearson's correlation (r) values that indicated significant and positive correlation between variables in the same group. Box-whisker plots revealed that as we go downstream, the pollutant concentration increases and maximum at the downstream station Raj Ghat and minimum at the upstream station Samane Ghat. Seasonal variations in water quality parameters signified that total alkalinity, total acidity, DO, BOD, COD, N, phosphate (PO 4(2-) ), Cu, Cd, Cr, Ni, Fe, Pb, and Zn were the highest in summer (March-June) and the lowest during monsoon season (July-October). Temperature was the highest in summer and the lowest in winter (November-February). DO was the highest in winter and the lowest in summer season. pH was observed to be the highest in monsoon and the lowest in summer season.

Application of physicochemical data for water-quality assessment of watercourses in the Gdansk Municipality (South Baltic coast)

The paper presents water-quality evaluation based on an 8-year monitoring programme in the Gdansk Municipality region, on the Southern coast of the Baltic Sea. The studies were carried out from 2000 to 2007 by surface water analysis at 15 various sites within eight watercourses. Sampling sites included rather urbanized or developed lands, farming fields and non-polluted city recreational areas such as parks and forests. Most of the watercourses were sampled monthly at two locations, one within the upper course of the watercourse and the other near its mouth. In all samples, eight parameters of water quality were determined: total suspended solids, dissolved oxygen, water temperature, oxygen saturation, 5-day biochemical oxygen demand, chemical oxygen demand, total phosphorus and total nitrogen concentration. Interpretation of the obtained results revealed that examination of those basic physicochemical parameters permits to discriminate initially watercourses with respect to level of water contamination. During the research, a large dataset was obtained and it was described by both basic statistical parameters and chemometric method of cluster analysis. The paper presents relations between analysed parameters and influence of land exploitation mode on water quality and describes variation of the results both in space and time.

Spatial-temporal variation of surface water quality in the downstream region of the Jakara River, north-western Nigeria: A statistical approach

The pollution status of the downstream section of the Jakara River was investigated. Dissolved oxygen (DO), 5-day biochemical oxygen demand (BOD(5)), chemical oxygen demand (COD), suspended solids (SS), pH, conductivity, salinity, temperature, nitrogen in the form of ammonia (NH(3)), turbidity, dissolved solids (DS), total solids (TS), nitrates (NO(3)), chloride (Cl) and phosphates (PO(3-)(4)) were evaluated, using both dry and wet season samples, as a measure of variation in surface water quality in the area. The results obtained from the analyses were correlated using Pearson's correlation matrix, principal component analysis (PCA) and paired sample t-tests. Positive correlations were observed for BOD(5), NH(3), COD, and SS, turbidity, conductivity, salinity, DS, TS for dry and wet seasons, respectively. PCA was used to investigate the origin of each water quality parameter, and yielded 5 varimax factors for each of dry and wet seasons, with 70.7 % and 83.1 % total variance, respectively. A paired sample t-test confirmed that the surface water quality varies significantly between dry and wet season samples (P < 0.01). The source of pollution in the area was concluded to be of anthropogenic origin in the dry season and natural origins in the wet season.