Vasil Simeonov

Assessment of the surface water quality in Northern Greece

The application of different multivariate statistical approaches for the interpretation of a large and complex data matrix obtained during a monitoring program of surface waters in Northern Greece is presented in this study. The dataset consists of analytical results from a 3-yr survey conducted in the major river systems (Aliakmon, Axios, Gallikos, Loudias and Strymon) as well as streams, tributaries and ditches. Twenty-seven parameters have been monitored on 25 key sampling sites on monthly basis (total of 22,350 observations). The dataset was treated using cluster analysis (CA), principal component analysis and multiple regression analysis on principal components. CA showed four different groups of similarity between the sampling sites reflecting the different physicochemical characteristics and pollution levels of the studied water systems. Six latent factors were identified as responsible for the data structure explaining 90% of the total variance of the dataset and are conditionally named organic, nutrient, physicochemical, weathering, soil-leaching and toxic-anthropogenic factors. A multivariate receptor model was also applied for source apportionment estimating the contribution of identified sources to the concentration of the physicochemical parameters. This study presents the necessity and usefulness of multivariate statistical assessment of large and complex databases in order to get better information about the quality of surface water, the design of sampling and analytical protocols and the effective pollution control/management of the surface waters.

Chemical mass balance source apportionment of PM10 in an industrialized urban area of Northern Greece

Ambient PM10 were sampled at three sites in an industrialized urban area of Northern Greece during June 1997–June 1998 and analyzed for 17 chemical elements, 5 water-soluble ions and 13 polycyclic aromatic hydrocarbons. In addition, chemical source profiles consisting of the same particulate components were obtained for a number of industrial activities (cement, fertilizer and asphalt production, quarry operations, metal electroplating, metal welding and tempering, steel manufacture, lead and bronze smelters, metal scrap incineration), residential oil burning, non-catalyst and catalyst-equipped passenger cars, diesel fuelled taxis and buses, as well as for geological fugitive sources (paved road dust and soil from open lands). Ambient and source data were used in a chemical mass balance (CMB) receptor model for source identification and apportionment. Results of CMB modeling showed that major source of ambient PM10 at all three sites was diesel vehicle exhaust. Significant contribution from industrial oil burning was also evidenced at the site located closest to the industrial area.

Water quality study of the Struma river basin, Bulgaria (1989–1998)

The present paper deals with an estimation of the water quality of the Struma river. Long-term trends, seasonal patterns and data set structures are studied by the use of statistical analysis. Nineteen sampling sites along the main river stream and different tributaries were included in the study. The sites are part of the monitoring net of the region of interest. Seventeen chemical indicators of the surface water have been measured in the period 1989–1998 in monthly intervals. It is shown that the water quality is relatively stable throughout the monitoring period, which is indicated by a lack of statistically significant trends for many of the sites and by chemical variables. Several seasonal patterns are observed at the sampling sites and four latent factors are identified as responsible for the data set structure.

A solvent selection guide based on chemometrics and multicriteria decision analysis

The selection of suitable solvents is a crucially important subject in a wide range of chemical processes. This study presents a solvent selection guide where 151 solvents were assessed, including a significant number of recently reported bio-based solvents. The assessment procedure involves grouping of solvents according to their physicochemical parameters and ranking within clusters according to their toxicological and hazard parameters. Grouping of solvents resulted in the formation of three clusters – nonpolar and volatile (35 solvents), nonpolar and sparingly volatile (35 solvents) and polar ones (81 solvents). The comparison of toxicological and hazard related data indicated that solvents from the third cluster should be preferentially chosen. Within each group, a solvent ranking was performed by means of the TOPSIS procedure based on 15 different criteria. Because of the lack of certain data (especially toxicological), different ranking confidence levels were introduced. The highest confidence rankings were performed only for some solvents but with all the considered criteria. Low confidence rankings were created for all solvents but were based on certain criteria only. The results of our solvent selection guide (SSG) are generally in agreement with the results of others but allow for finer ranking of solvents. The assessment procedure is easy to adapt to individual chemists’ needs and allows including new solvents to the ranking.

Relationship between heavy metal distribution in sediment samples and their ecotoxicity by the use of the Hasse diagram technique

Many studies assessing the quality of sediments and their pollution impact use monitoring data consisting predominantly of chemical indicators. Recently, ecotoxicity estimates have been used as very important parameters of the ecological state of sediment samples. Thus, a more complete sediment risk assessment is achieved and more reliable information on the sediment pollution history is extracted. The data interpretation could be improved if multivariate statistical techniques were applied to data classification, modelling and interpretation. The starting classification of the data was performed using self-organizing maps (SOM) approach in order to reveal specific relationship patterns for objects and for variables. The original element of the present study is the use of the Hasse diagram technique (HDT) for partial ordering in order to explain some specific relations between the chemical indicators analysed (heavy metal content in different sediment compartments) and the ecotoxicity tests for acute and chronic toxicity. In principle, a reliable estimate of the pollution impact of a large environmental object (the Mar Menor lagoon in Spain) is achieved. The specific role of each one of the five heavy metals involved (Zn, Cu, Mn, Pb, and Cd) is interpreted in the context of the additional ecotoxicity tests.

Surface water quality assessment by the use of combination of multivariate statistical classification and expert information

The present study deals with the assessment of surface water quality from an industrial-urban region located in northern Poland near to the city of Gdansk. Concentrations of thirteen chemicals including total polycyclic aromatic hydrocarbons (PAHs), halogenated volatile organic compounds (HVOCs) and major ions in the samples collected at five sampling points during six campaigns were used as variables throughout the study. The originality in the monitoring data treatment and interpretation was the combination of a traditional classification approach (self-organizing maps of Kohonen) with PAH diagnostic ratios expertise to achieve a reliable pollution source identification. Thus, sampling points affected by pollution from traffic (petroleum combustion products), from crude oil processing (petroleum release related compounds), and from phosphogypsum disposal site were properly discriminated. Additionally, it is shown that this original assessment approach can be useful in finding specific pollution source tracers.

An in situ derivatization – dispersive liquid–liquid microextraction combined with gas-chromatography – mass spectrometry for determining biogenic amines in home-made fermented alcoholic drinks

A novel dispersive liquid-liquid microextraction (DLLME) gas chromatography mass-spectrometry (GC-MS) method was developed for the determination of 13 biogenic amines in home-made wine samples. The method allows to simultaneous extraction and derivatization of the amines providing a simple and fast mode of extract enrichment. During the study, two different procedures were examined. Statistical analysis was performed to choose better procedure, as well as the conditions of derivatization reaction. At least, a mixture of methanol (dispersive solvent; 215μL), chloroform (extractive solvent; 400μL), and isobutyl choloroformate (derivatizing reagent; 90μL) was used as extractive/derivatizing reagent, added to 5mL of sample. The addition of mixture of pyridine and HCl was necessary to eliminate the by-products. The proposed method showed good linearity (correlation coefficients >0.9961), good recoveries (from 77 to 105%), and good intra-day precision (below 13%) and inter-day precision (below 10%). Moreover, detection limits were never over 4.1μg/L. The developed method was successfully applied to the analysis of 17 home-made wine samples not regulated by law. All of the biogenic amines analyzed were found in most of the wines.

Application of multivariate statistics in assessment of green analytical chemistry parameters of analytical methodologies

The study offers a multivariate statistical analysis of a dataset, including the major metrological, “greenness” and methodological parameters of 43 analytical methodologies applied for aldrin determination (a frequently analyzed organic compound) in water samples. The variables (parameters) chosen were as follows: metrological (LOD, recovery, RSD), describing the “greenness” (amount of the solvent used, amount of waste generated) and general methodological parameters (sample volume, time of analysis, injection volume) and scores of greenness assessment with NEMI and eco-scale. The results of the study show that all analytical methodologies have been grouped into three clusters. The first one consisted of “non-green” LLE and SPE methodologies and the other two consisted of solventless or virtually solventless methodologies. The NEMI and eco-scale scores are well correlated, which indicates the similarity between these two assessment scales. A self-organizing maps technique is not feasible for easy and quick labeling of analytical methodologies in terms of their greenness. However, the multivariate analysis of analytical methodologies can give information about clustering of methodologies to “green” or “non-green” groups and some extra information about relations between objects inside clusters of interest.

Multivariate statistical assessment of polluted soils

This study deals with the application of several multivariate statistical methods (cluster analysis, principal components analysis, multiple regression on absolute principal components scores) for assessment of soil pollution by heavy metals. The sampling was performed in a heavily polluted region and the chemometric analysis revealed four latent factors, which describe 84.5 % of the total variance of the system, responsible for the data structure. These factors, whose identity was proved also by cluster analysis, were conditionally named “ore specific”, “metal industrial”, “cement industrial”, and “steel production” factors. Further, the contribution of each identified factor to the total pollution of the soil by each metal pollutant in consideration was determined.

Hasse diagram technique as a tool for water quality assessment

The management of the quality large water catchments is a complex problem which requires intelligent data analysis on various levels - analytical, spatial, and temporal. Recently, a successful approach is developed combining advanced multivariate data treatment approaches like self-organizing maps of Kohonen (SOM) and Hasse diagram technique (HDT). In the first step of the environmetric analysis the monitoring data were subject to pre-processing using SOMs to reduce the number of objects and/or water quality parameters. In the next step HDT for partial ranking (both in spatial and temporal aspect) was applied according to the pre-selected set of the water quality parameters. The use of the water quality norms issued by the Bulgarian environmental authorities revealed important details in assessing the Maritsa River water quality. Thus, the relations between different water quality patterns and sampling stations could be used by water management authorities during the period of observation.