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(1) Background: Monitoring effluent in water treatment plants has a key role in identifying potential pollutants that might be released into the environment. A non-target analysis approach can be used for identifying unknown substances and source-specific multipollutant signatures. (2) Methods: Urban and industrial wastewater effluent were analyzed by HPLC-HRMS for non-target analysis. The anomalous infiltration of industrial wastewater into urban wastewater was investigated by analyzing the mass spectra data of "unknown common" compounds using principal component analysis (PCA) and the Self-Organizing Map (SOM) AI tool. The outcomes of the models were compared. (3) Results: The outlier detection was more straightforward in the SOM model than in the PCA one. The differences among the samples could not be completely perceived in the PCA model. Moreover, since PCA involves the calculation of new variables based on the original experimental ones, it is not possible to reconstruct a chromatogram that displays the recurring patterns in the urban WTP samples. This can be achieved using the SOM outcomes. (4) Conclusions: When comparing a large number of samples, the SOM AI tool is highly efficient in terms of calculation, visualization, and identifying outliers. Interpreting PCA visualization and outlier detection becomes challenging when dealing with a large sample size. [ABSTRACT FROM AUTHOR]

The geochemical composition of bedrock is the key feature determining elemental concentrations in soil, followed by anthropogenic factors that have less impact. Concerning the latter, harmful effects on the trophic chain are increasingly affecting people living in and around urban areas. In the study area of the present survey, the municipalities of Cosenza and Rende (Calabria, southern Italy), topsoil were collected and analysed for 25 elements by inductively coupled plasma mass spectrometry (ICP-MS) in order to discriminate the different possible sources of elemental concentrations and define soil quality status. Statistical and geostatistical methods were applied to monitoring the concentrations of major oxides and minor elements, while the Self-Organizing Maps (SOM) algorithm was used for unsupervised grouping. Results show that seven clusters were identified—(I) Cr, Co, Fe, V, Ti, Al; (II) Ni, Na; (III) Y, Zr, Rb; (IV) Si, Mg, Ba; (V) Nb, Ce, La; (VI) Sr, P, Ca; (VII) As, Zn, Pb—according to soil elemental associations, which are controlled by chemical and mineralogical factors of the study area parent material and by soil-forming processes, but with some exceptions linked to anthropogenic input. [ABSTRACT FROM AUTHOR]

The present study deals with the application of the self-organizing map (SOM) technique in the exploration of spatiotemporal dynamics of spring and stream water samples collected in the Chochołowski Stream Basin located in the Tatra Mountains (Poland). The SOM-based classification helped to uncover relationships between physical and chemical parameters of water samples and factors determining the quality of water in the studied high-mountain area. In the upper part of the Chochołowski Stream Basin, located on the top of the crystalline core of the Tatras, concentrations of the majority of ionic substances were the lowest due to limited leaching. Significantly higher concentration of ionic substances was detected in spring and stream samples draining sedimentary rocks. The influence of karst-type springs on the quality of stream water was also demonstrated. [Copyright &y& Elsevier]

This study deals with the exploration of oospores morphometric variability according to various types of water reservoirs of Poland by the self-organizing maps (SOM). The SOM integrates morphometrical features in order to distinguish genera and species and to explore their natural environmental habitats. The data set covered 575 oospores collected in Poland and contained measurements of largest polar axis (LPA), largest equatorial diameter (LED), isopolarity index, number of ridges and width of fossa (WF) of 15 Chara and Nitella species. Biometric analysis of oospores revealed that Chara and Nitella genera could be easily distinguished by the SOM. LPA and LED of C. contraria oospores collected from lakes were higher than in case of those found in peat bogs. LPA, LED and WF of C. globularis that were found in lakes were higher than the ones of charophytes from ponds and ditches. The most taxonomically useful morphometrical features for oospores identification are LPA, LED and WF. The advantages of SOM algorithm in the form of exceptional visualization, dimension reduction and exploration abilities are stressed. [ABSTRACT FROM AUTHOR]

The aim of this study was to offer an efficient and unsupervised strategy for medical data exploration to find relationships between clinical tests and major as well as concomitant syndromes of a specific disease. A large data set consisting of a group of 100 patients suffering diabetes mellitus type 2 disease characterized by more than 30 clinical parameters was explored using self-organizing maps (SOM) and classified by the use of non-hierarchical K-means algorithm implemented in the SOM. An attempt was made to correlate the classification results with the parameters of the metabolic syndrome. The classification result revealed 4 specific patterns of patients, each presented by respective discriminating parameters: (i) patients with well-controlled state of the disease, (ii) patients with disturbed kidney function, (iii) patients who do not keep the required medical treatment regime, and (iv) patients who neglect the disease. All patterns included respective number of patients with different clinical status and attitude to the health problem. Patients with a well-controlled state of the disease, although being chronic for a long period of time were characterized by very low density proteins and triglycerides levels as well as by the lowest levels for hemoglobin A1c, total protein and creatine phosphokinase. Patients with disturbed kidney function were characterized by the highest averages of the uric acid, albumin, total protein and creatinine, and relatively low values for glucose. Patients who do not keep the required regime possessed the highest level of glucose along with maximal values for cholesterol and trombocytes. Patients who neglect the disease were characterized by high values of cholesterol and relatively high level of glucose, although the duration of the disease was the shortest as compared to the other groups of patients. [ABSTRACT FROM AUTHOR]

Abstract: Modelling spatial variation of total trihalomethanes (TTHMs) based on the quality of drinking water and parameters of distribution network showed three intervals (low, moderate, and high) for TTHMs abundance in various governorates in Kuwait. The majority of differences in TTHMs spreading were found between samples collected at Ahmadi, Jahra and Capital Governorate, as well as at Hawalli and Jahra. Spatiotemporal variations of TTHMs in household drinking water carried out by the self-organizing map (SOM) approach indicated that discontinuously sampled locations could be analyzed in a multivariate way in order to reveal the factors controlling the quality of water. In the group of analyzed variables, several mutual correlations were discovered; however, the highest relative abundance of TTHMs, and hence the correlation, was associated with dibromochloromethane (DBCM) and bromoform (BFM). The SOM-based classification helped to uncover the relationship between the THMs level and the distance from the supplying water treatment plant, and hence an indirect relation to its operational efficiency. The products of the Az-Zoor and the Shuaiba plants were of the best quality and contained the lowest levels of each of the four THMs as well as TTHMs. [Copyright &y& Elsevier]

The level of pollution with various mercury species (organomercury, water- and acid-soluble mercury, mercury bound to humic matter and to sulphides) of the floodplain soils and sediments from middle part of the Warta River has been assessed using self-organizing maps (SOM). Chemometric evaluation allowed identification of moderately (median 173–187 ng g−1, range 54–375 ng g−1 in soil and 130 ng g−1, range 47–310 ng g−1 in sediment) and heavily polluted samples (662 ng g−1, range 426–884 ng g−1). Heavily polluted were located mainly below and in the area of the Poznań city. Statistical comparison of mercury species distribution in floodplain soils of the Warta River shows different patterns for moderately and heavily polluted samples. In heavily polluted soils the contribution of mobile mercury (sum of organomercury species, water- and acid soluble species) is lower (4.2%) than in moderately polluted soils (6.1%). Higher contribution of mobile mercury was observed in sediments of the Warta River (12%). In case of moderately polluted samples, statistical differences in the contribution of mercury species are relatively low and thus the environmental risk from mercury deposited in aquatic system of the Warta River is relatively low. However, higher water levels and heavy floods may incite remobilisation of some organomercuries (2.2–2.9 ng g−1 in soil and 10 ng g−1 in sediment) and acid-soluble species of mercury (2.6–2.9 ng g−1 in soil and 0.5 ng g−1 in sediment). [ABSTRACT FROM AUTHOR]

A self-organizing map (SOM) algorithm was applied to evaluate the geochemical and environmental impact of 26th December 2004 tsunami, based on interelemental and intersite relations of sediment chemistry. The study was carried out based on data sets, including contents of salts (K, Na, Ca, Mg, Cl and SO4) leached with deionized water, heavy metals (Cd, Cr, Cu, Ni, Pb and Zn) in acid leachable fraction, metalloids (As, Sb and Se) in exchangeable fraction, as well as both total Hg and mercury in the form of various species (organomercury, water-soluble, acid-soluble, bound to humic matter and bound to sulfides) in sediment samples. SOM-supported exploration were performed for two separate data sets. The first run was applied for analytical results concerning sediments taken less than 50 days after tsunami event while the second one concerned results obtained for samples collected in the same location one year later, after rainy season. In the case of the “2005-run”, based on mutual linkage, complete set of variables could be conditionally divided into general groups showing of their patterns related to their major source as “salt” and “wastewater.” Classification results revealed natural clusters of sediment samples in relation to their location and to the magnitude of the impact of tsunami wave. Numerous clusters reflect general chemical composition of tsunami sediments while clusters containing isolated sampling locations reflect “site-specific” conditions, partially related to anthropogenic impact. The cleaning effect of the rainy season in Thailand was observed, based on “2006-run” exploaration results. The chemical composition of tsunami sediments was unified for 93% of samples. General patterns related to major source of analytes were analogous compared to the “2005-run.” These studies demonstrate that SOM has the potential to successfully assist the assessment of the environmental impacts of a tsunami disaster and the role of a tsunami sediments as potential carriers of pollution. [ABSTRACT FROM AUTHOR]

Abstract: The present study deals with the application of self-organizing maps (SOM) in order to model, classify and interpret seasonal and spatial variability of 210Po, 238U and 239+240Pu levels in the Vistula river basin. The data set represents concentration values for 3 alpha emitters (210Po, 238U and 239+240Pu) measured in surface water samples collected at 19 different sampling locations (8 in major Vistula stream while 11 in right or left Vistula tributaries) during four seasons (winter, spring, summer and autumn) in the framework of a one-year quality monitoring study. The advantages of an SOM algorithm, its classification and visualization ability for environmental data sets, are stressed. The neural-network based classification made it possible to reveal specific patterns related to both seasonal and spatial variability. In the middle and upper part of Vistula catchment as well as in the right-shore tributaries, concentrations of 210Po and 238U during summer and winter are the lowest. Concentrations of 210Po and 238U increase significantly during spring and autumn in the Vistula river catchment, especially in the delta of Vistula river. High concentration of anthropogenic originated 239+240Pu indicates “site-specific” character of pollution in two large left-shore tributaries located in the middle part of the Vistula drainage area. Efficient classification of sampling locations could lead to an optimization of river radiochemical sampling networks and to a better tracing of natural and anthropogenic changes along Vistula river stream. [Copyright &y& Elsevier]