Chemometric application in classification and assessment of monitoring locations of an urban river system

The study presents the application of selected chemometric techniques: cluster analysis, principal component analysis, factor analysis and discriminant analysis, to classify a river water quality and evaluation of the pollution data. Seventeen stations, monitored for 16 physical and chemical parameters in 4 seasons during the period 1999-2003, located at the Bagmati river basin in Kathmandu Valley, Nepal were selected for the purpose of this study. The results allowed, determining natural clusters of monitoring stations with similar pollution characteristics and identifying main discriminant variables that are important for regional water quality variation and possible pollution sources affecting the river water quality. The analysis enabled to group 17 monitoring sites into 3 regions with 5 major discriminating variables: EC, DO, CL, NO₂N and BOD. Results revealed that some locations were under the high influence of municipal contamination and some others under the influence of minerals. This study demonstrated that chemometric method is effective for river water classification, and for rapid assessment of water qualities, using the representative sites; it could serve to optimize cost and time without losing any significance of the outcome.     

Assessment of river water quality in the South Baltic coast by multivariate techniques

The paper presents an example of using multivariate techniques to interpret a large data set obtained during a 4-year water quality monitoring program in the Gdansk Municipality region, on the southern coast of the Baltic Sea. From 2004 to 2007, 11 physicochemical water parameters were analyzed monthly at 15 sites within eight watercourses. Principal-components analysis and cluster analysis were used to explore the data. Spatio-temporal trends in water quality were evaluated, the variables that determined the data set’s structure and the factors that affected the water’s physicochemical composition identified, with the goal of helping to optimize future monitoring. To reduce the number of analyzed variables, relationships between the analyzed parameters were also identified. The results revealed that the differences in physicochemical water properties among stations were generally smaller than those between the warmer and cooler seasons. It was determined that seasonal intrusions of brackish water from the Gulf of Gdansk can modify the water properties of some watercourses in the study area, but that dissolved oxygen, chemical oxygen demand, and total phosphorus were the main parameters responsible for the overall variation in the observed data. These parameters are related to pollution of anthropogenic origin.     

Assessment of pollution level in a Himalayan Lake,Kashmir, using geomatics approach

Pollution indices aggregate concentrations of several water quality parameters into a single quantity to indicate the general status of pollution in a region. In this study, a variant of the previous water quality index was used to evaluate the pollution status in the Wular Lake, Kashmir, which is a Ramsar site and wetland of international importance. The index termed as water quality status index (WQSI) is considered as a simple pollution indicator to support management actions in the Wular Lake, Kashmir. WQSI is a valuable and unique rating to depict the overall water quality status and pollution level of the waterbody in a spatial context and is also capable of dealing with those water quality parameters which do not have well-developed standard values. In this study, the water quality of the Wular Lake was investigated in June 2013 for 21 sample locations. The index used in this work is composed of 13 measurable physico-chemical parameters – pH, dissolved oxygen, chemical oxygen demand, biological oxygen demand, alkalinity, hardness, chloride, total dissolved solids, ammonia, iron, nitrite, nitrate and fluoride. The generation of WQSI is based on weighted overlay technique, in which interpolated raster maps were generated for all the 13 water quality parameters and weights are assigned to each and every parameter using analytic hierarchy process technique, considering their status as benefit or cost criteria. Based on the value of WQSI, the whole lake was divided into five zones, comprising least polluted zone (23%), moderately polluted zone (20%), high polluted zone (30%), very high polluted zone (22%) and extremely polluted zone (5%). From this study, it has been found that 60 km² (77%) of total lake area constitutes the moderate to extremely polluted zone and only 18 km² (23%) of the total lake area constitutes the least polluted zone, which is in the north-west region of the lake. The study reveals that the world-famous Wular Lake is undergoing the eutrophication process and as a result of which the lake is losing its water holding capacity to deal with the disastrous flood problem in Kashmir region.     

四川温江金马地区地下水化学特征研究

根据温江金马地区地下水水化学分析资料,研究了该区浅层地下水中主要离子组分、微量元素特征及其空间变化规律,初步揭示了地下水化学组分形成原因,为更好的开发利用和保护地下水资源提供一定的参考。     

Factor Analysis for Assigning Sources of Groundwater Pollution

Abstract

Factor Analysis (FA) is applied to tentatively establish either jhe sources of pollution in the groundwater in a delimited zone in Catalonia which has been polluted by permeation with non-controlled wastewaters or the groundwater evolution with time in this area. Three types of chemical analysis were considered: general parameters indicating the chemical quality of water, inorganic micropollutants and organic micropollutants. These analyses were carried out with forty-five samples collected in three different periods, and eleven parameters were considered. From the final solutions of the FA method applied several factors were retained for the different sampling periods and these factors were related to different sources of pollution. FA has proved to be more useful when punctual pollution incidents takes place rather than when groundwater evolution with time is studied.     

Chemometrical Interpretation of Lake Waters after their Chemical Analysis by Using Aas,Flame Photometry and Titrimetric Techniques

This article reports the distribution of trace metals and major ions in lake waters of Sultansazl L < L , a reedfield near Kayseri, Turkey. The determination of elements such as Cr, Ni, Cu, Cd and Pb in lake water samples was performed by AAS after a preconcentration step using a column packed with Amberlite XAD-16 resin. Both flame- and graphite furnace-atomic absorption spectrometry was used to determine these metals in lake water samples. The concentrations of the metals bound to humic substances, and free metal ions were determined after their sorption-elution on the resin, separately. The column method optimized with sodium tetraborate reagent was used in determining the free metal ions. In the determinations of Ca²⁺ and Mg²⁺, K⁺ , and SO2-4 , Cl ^m and total hardness, flame atomic absorption spectrometry, flame photometry, and titrimetry were used, respectively. In order to evaluate the analytical data by multivariate statistical techniques which enable feature reduction and grouping of the pollutant sources in lake waters from their chemical composition, principal component analysis (PCA), cluster analysis (CA) and correlation analysis were used. As a consequence of multivariate statistical evaluation, main anthropogenic sources like traffic, industry and agricultural processes were drawn to be responsible from the pollution in the environment investigated.     

Determination of heavy metals in suspended matter in the storage lake “Bitterfelder Muldestausee”

Dissolved and particulate trace elements have been determined in 400 samples of both the inflow and the outflow waters of the storage lake “Bitterfelder Muldestausse” in order to investigate the sedimentation of 22 elements transported by the highly polluted Mulde River, an affluent of the river Elbe. Inductively coupled plasma mass spectrometry (ICP-MS) has been used to analyse filtered water samples because of its multielemental capabilities, the excellent detection limits, the wide linear calibration range and the high speed of analysis. A special leaching procedure has been employed for the very low amounts of the suspended matter collected from each water sample. The dissolved material has been also analysed by ICP-MS. Testing of the procedure employed by the analysis of a standard reference material (SRM BCR 146) and use of the standard addition method has resulted in both a good precision (1–7%) and accuracy. Despite the wide variation in the composition of the suspended matter samples the concentrations of the heavy metals in sediment samples and in the suspended matter have been found to be comparable. A balance of sedimentation has been calculated based on the mean values of concentrations of all elements investigated in both the water and suspended matter samples of the inflow and outflow. Results from this first study show that the storage lake acts as a sedimentation trap for Zn, Cu, Pb, Ni, Cr, Cd, U and Co.     

Characterizing the origins of bottled water on the South Korean market using chemical and isotopic compositions

We analyzed the major elements and stable isotopes of oxygen, hydrogen, and carbon (dissolved inorganic carbon: DIC) in various types of bottled water (domestic and foreign) commercially available in South Korea to classify the water types and to identify their origins. Only marine waters and some sparkling waters could be discriminated by their physicochemical compositions. Oxygen and hydrogen isotopes made marine waters more distinguishable from other water types. The determination of the carbon isotope composition of DIC was clearly useful for distinguishing between naturally and artificially sparkling waters. In addition, statistical analysis also appeared to aid in the discrimination of bottled water types. Our results indicate that a method that combines chemical and stable isotope composition analysis with statistical analysis is the most useful for discriminating water types and characterizing the origins of bottled water.     

Combining multivariate analysis and geochemical approaches for assessing heavy metal level in sediments from Sudanese harbors along the Red Sea coast

Multivariate statistical analysis and geochemical approaches were exploited for the assessment of the level of some heavy metals (Mn, Fe, Ni, Cu, Zn and Pb) in sediments from Sudanese harbors along the Red Sea coast. Principal component analysis, as a multivariate statistical analysis approach, was applied to identify contribution sources by heavy metals in sediments. While a single source (crustal) was recorded in the bulk sediments and coarse sediment grains (grain-size 1000-500 µm), two sources (crustal and anthropogenic) were recorded in fine sediment grains (grain-size < 500 µm). Furthermore, enrichment factor (EF), as a geochemical approach, appointed polluted sites by heavy metals in the study area. Based upon a previous study addressed the interpretation of EF values, minor to moderate anthropogenic enrichment were recorded in sediments from some sites in the study area. The main anthropogenic activities that believed to be the major sources of pollution by heavy metals in the study area are discharges from oil refinery, industry, shipping activity and domestic waste. Hierarchical cluster analysis (HCA), as another multivariate statistical analysis approach, was applied for the concentrations of heavy metals in bulk sediments to group sediments according to their mineralogical composition. The output of HCA is that sediments from the Port-Sudan harbor can be divided mainly into three areas — east, west and south. For the Sawakin harbor, no apparent trend for the spatial distribution of heavy metals in sediments was recorded.     

Environmetrical Treatment of Water Quality Survey Data from Yantra River, Bulgaria

 The environmetrical analysis carried out has indicated that the short-term water quality survey may give a very important information on the latent factors influencing the water quality of Yantra river basin. The principal components analysis carried out reveals that at least four principal components are necessary for multivariate statistical modeling of the water quality – combination of natural and anthropogenic influences (“mixed” factor) reflecting parameters such as water hardness, marine influence, organic pollution; typical anthropogenic influences (“anthropogenic” factor) explaining the metal contamination of the river water; everyday wastes, usually N-containing pollutants such as nitrates, nitrites or ammonia, form the “N-containing wastes” factor and a “temperature” factor formed by typical physical parameters such as water and air temperature. The formation of these special features of the river waters from Yantra basin is also confirmed by the results of cluster analysis (variable clustering) where the content of the significant clusters of the variables is the same as the content of the principal components modeling over 75% of the total variance of the system. Additionally, the cluster analysis of the objects has proved that the water quality during both sampling traverses is very stable and reproducible. Few exceptions are observed due to momentary local pollution in an industrial area along the river stream. Comparison with standard requirements for water quality has indicated that the Yantra river waters are of high quality and could be used after minor pretreatment as potable water sources. The environmetrical approaches applied reveal a specific information concerning the river water quality. In this way the ecological problem treated has not a local importance but suggests a strategy for estimation of similar ecosystems in global sense. Received July 30, 1998. Revision June 1, 1999.     

Water migration of elements in Ornithogenic ecosystems of the North Pacific islands

Specific features of the chemical composition of surface water and water migration of elements in North Pacific islands with large population of marine colonial birds were analyzed. Ornithogenic factor was found to be determining in the composition of surface water in such ecosystems. The concentrations of nutrients (N, P, S, K) are informative hydrochemical parameters reflecting the effect of birds on the intensity of their migration in water. Spacious areas subjected to biogeochemical impact are formed around the islands populated by seabird colonies.     

Assessment of Bhatiari Lake water quality: Pollution indices,hydrochemical signatures and hydro-statistical analysis

This study aimed at evaluating the water quality of Bhatiari Lake (BL) for the first time based on water quality parameters, pollution indices, hydrochemical signatures and hydro-statistical analysis. Lake water samples were collected from the lake during April–May 2019 and wide ranges of parameters were considered for the investigation. Except for COD and Fe, all the parameters were within the permissible limit. COD crossed Bangladesh standards and testing institution (BSTI) and United States environmental protection agency (USEPA) standards. In contrast, Fe crossed World health organization (WHO), Bureau of Indian Standards (BIS) and USEPA standards. Hydrochemical analysis indicated the water as soft-fresh where near neutral low-metal was noticed from the Ficklin-Caboi diagram. Ca²⁺-Mg²⁺-HCO₃^- type water was confirmed from Piper and Chadha diagram, whereas Durov and Schoeller's diagram were indicated the influence of Mg²⁺-HCO₃^-. The trend of cations and anions were Ca²⁺> Mg²⁺> Na⁺>K⁺ and HCO₃^? > Cl^? > NO₃^? > SO₄^2? > PO₄^3? as stated by pie chart. Most precipitation dominant water was confirmed from the Gibbs diagram. Principal component analysis (PCA), Cluster analysis (CA) and Correlation matrix (CM) indicated the co-existence of geogenic and anthropogenic sources for pollution. Good water quality was observed via an integrated approach namely degree of contamination (C_d), Single-Factor Pollution Index (SPI), Comprehensive pollution index (CPI), Heavy metal evaluation index (HEI), Heavy metal pollution index (HPI), Nemerow's pollution index (NPI) and Ecological risk index (ERI). In addition, water quality index (WQI) remarked the water is excellent. Taken collectively, the present study indicates the BL water can be considered pollution-free.     

Multivariate statistical analysis approach to assess groundwater quality in two selected mandals of Vizianagaram district,Andhra Pradesh,India

Groundwater quality is the major concern all over the world. Natural processes and manmade activities are the prime reasons for the contamination of available water resources. It is crucial to assess the quality of groundwater in areas surrounded by various industries. The present study was carried out to assess the groundwater quality during pre-monsoon and post monsoon seasons of 2016, in two mandals of Vizianagaram district of Andhra Pradesh via multivariate statistical analysis and water quality index method. The present work gains importance in light of the construction of proposed international airport at Bhohapuram and the existence of various industries in Pusapatirega mandal. A total of thirty-seven villages, eighteen from Bhogapuram mandal and seventeen from Pusapatirega mandal were selected for the present study. Factor analysis, linear regression analysis, correlation matrix analysis and cluster analysis tools were used to emphasize the parameters influencing quality of water in the chosen study area. From the analysis reports, it was found that the groundwater of the two mandals under investigation was strongly influenced by EC, TDS, total hardness(TH), Ca⁺², Mg⁺² and K⁺. During the two seasons under study, the water quality index value was found to be greater than 100 indicating that the water is unfit for human consumption. Concentration of Ca⁺², Mg⁺² and K⁺ were found to be beyond the permissible limits prescribed by BIS (2012). Dissolution of calcium and magnesium bearing minerals, mixing of industrial and household wastes may be the reasons for elevated concentration levels of these parameters.     

Chemometric analysis of groundwater quality data of alluvial aquifer of Gangetic plain, North India

Water quality data set from the alluvial region in the Gangetic plain in northern India, which is known for high fluoride levels in soil and groundwater, has been analysed by chemometric techniques, such as principal component analysis (PCA), discriminant analysis (DA) and partial least squares (PLS) in order to investigate the compositional differences between surface and groundwater samples, spatial variations in groundwater composition and influence of natural and anthropogenic factors. Trilinear plots of major ions showed that the groundwater in this region is mainly of Na/K-bicarbonate type. PCA performed on complete data matrix yielded six significant PCs explaining 65% of the data variance. Although, PCA rendered considerable data reduction, it could not clearly group and distinguish the sample types (dug well, hand-pump and surface water). However, a visible differentiation between the water samples pertaining to two watersheds (Khar and Loni) was obtained. DA identified six discriminating variables between surface and groundwater and also between different types of samples (dug well, hand pump and surface water). Distinct grouping of the surface and groundwater samples was achieved using the PLS technique. It further showed that the groundwater samples are dominated by variables having origin both in natural and anthropogenic sources in the region, whereas, variables of industrial origin dominate the surface water samples. It also suggested that the groundwater sources are contaminated with various industrial contaminants in the region.     

Land-Based Classification of Herb's Origin Based on Supervised and Unsupervised Pattern Recognition of Plant and Soil Chemical Profiling

In this work, a series of supervised and unsupervised pattern recognition techniques are assessed for the first time as a tool in order to elaborate a common approach able to classify different plant species based on a common pattern determined by their geographical origin. For this reason, soil samples and extracts from various parts of 7 self-sown indigenous Greek plants were collected in nature from two regions (highlands and insular) in NW Greece. Based on the chemical profiling of each species and the respective soil matrix composition, the identification of similarities and dissimilarities on a regional basis were pursued. The results indicate that hierarchical cluster classification and discriminant analysis using the chemical profile of inorganic elements and soil matrix composition provide the basis for the provision of an area-specific geographic marker that enables the classification of different herbs based on their origin with high discrimination efficiency.     

Archaeometric characterization of ancient glazed pottery sherds from Khirbet Faris, Jordan by inductively coupled plasma mass spectrometry (ICP-MS)

Multielement analysis of sixteen Ayyubid–Mamluk glazed pottery sherds was done for determination of chemical composition in order to study their provenance. The sherds tested in the present research come from the historical site of Khirbet Faris on the Karak Plateau in Jordan. The chemical analysis was carried out by inductively coupled plasma mass spectroscopy (ICP-MS). Mg, Al, Ti, V, Cr, Mn, Ni, Cu, Mo, Bi and U have been determined in the studied samples. The data were analyzed by using principal component analysis PCA and hierarchical cluster analysis with Bray-Curtis in order to define grouping of different glazed potteries by obtaining information about their similarity and clustering. The results of chemical analysis provided persuasive evidence that the Khirbet Faris pottery sherds have at least three different sources of provenance.     

Understanding the groundwater dynamics in the Southern Rift Valley Lakes Basin (Ethiopia): multivariate statistical analysis method, oxygen (δ 18O) and deuterium (δ 2H)

Multivariate statistical analysis is very important to classify waters of different hydrochemical groups. Statistical techniques, such as cluster analysis, can provide a powerful tool for analyzing water chemistry data. This method is used to test water quality data and determine if samples can be grouped into distinct populations that may be significant in the geologic context, as well as from a statistical point of view. Multivariate statistical analysis method is applied to the geochemical data in combination with δ ¹⁸O and δ ²H isotopes with the objective to understand the dynamics of groundwater using hierarchical clustering and isotope analyses. The geochemical and isotope data of the central and southern rift valley lakes have been collected and analyzed from different works. Isotope analysis shows that most springs and boreholes are recharged by July and August rainfalls. The different hydrochemical groups that resulted from the multivariate analysis are described and correlated with the geology of the area and whether it has any interaction with a system or not.     

Characterization of Metals in Surface Sediments from Xiaoyang River,Jiangsu, China

Some metal species and fractions have high affinity to anthropogenic activities, making it feasible to characterize the spatiotemporal characteristics of human-induced degradation of ecosystems. The accumulation of Fe, Mg, Mn, Zn, Cu, Cr, Ni, and Pb, their fractions, physiochemical parameters, and nutrients was evaluated in the surface sediments at 11 sites on the Xiaoyang River in urban and suburban locations in Jiangsu, China for the assessment of pollution. The sediment quality was evaluated based on sediment quality guidelines, enrichment factors, geoaccumulation index, potential ecological risk index, and risk assessment code. Principal component analysis and cluster analysis were used to identify the sources of the metals. The total concentrations of metals, enrichment factors, and geoaccumulation indices demonstrated that all sites were significantly polluted with Zn and significantly to moderately polluted by Cu, Pb, and Ni. Moreover, higher metal enrichment was present downstream through downtown Sheyang due to extensive human activities. However, the potential ecological risk indices and risk assessment codes revealed high bioavailability and toxicity of Pb in this region. These results indicated that the metal fraction showed higher susceptibility. The accuracy of the ecological risk assessment was evaluated in the river, indicating a heavy anthropogenic impact.