Assessment of elemental contamination in the bottom sediments from a dam reservoir using a sequential extraction technique and chemometric analysis

Abstract

Abstract:© Versita Sp. z o.o. The concentration of elements in sediments is an important aspect of the quality of water ecosystems. The element concentrations in bottom sediments from Goczalkowice Reservoir, Poland, were investigated to determine the levels, accumulation and distribution of elements; to understand the contamination and potential toxicity of elements; and to trace the possible source of pollution. Sediments were collected from 8 sampling points. The functional speciation, mobility and bioavailability of elements were evaluated by means of modified Tessier sequential extraction. The element contents were measured by optical emission spectrometry with inductively coupled plasma. The experimental results were analyzed using chemometric methods such as principal component analysis and cluster analysis to elucidate the metal distributions, correlations and associations. The highest concentrations of most elements were found at the center of the reservoir. The distribution of metals in the individual fractions was varied. To assess the extent of anthropogenic impact indices, contamination factor, degree of contamination, metal pollution index and risk assessment code were applied. The calculated factors showed the highest contamination factor and the ability of chromium to be released from sediments. The degree of contamination showed that the area is characterized by a very high contamination. Strontium and manganese showed high potential ecological risk for sediments. Keywords: Heavy metals • Sediments • Modified Tessier sequential extraction • Principal component analysis • Cluster analysis

Mathematical Modelling as a Tool for the Assessment of Impact of Thermodynamics on the Algal Growth in Dam Reservoirs – Case Study of the Goczalkowice Reservoir

“…It is also a storage reservoir protecting downstream areas from floods and droughts. Additionally, the reservoir being a part of the Natura 2000 system helps to protect a wide range of habitats and species [Dabioch et al 2013; Młynarczyk et al 2013;Polak et al 2011]. The reservoir is included in the national monitoring system and since 2010, extensive research monitoring has been carried out in the framework of the ZiZOZap project [ZiZOZap 2010].…”

“…Both the operational monitoring system and real-time research measurements indicate strong changes in the water quality posing a risk to the water treatment plants and biodiversity dynamics (parameters of concern include: nutrients, sediments, dissolved oxygen and heavy metals). Some of the water quality parameters (e.g., phosphorus, humic acids and heavy metals) were recently analysed in relation to their abilities to be released from sediments [Dabioch et al 2013;Młynarczyk et al 2013;Polak et al 2011]. However, the reservoir hydrodynamics and thermodynamics were not analysed in order to identify their impact on concentrations of chlorophyll a.…”

Variability in different antimony, arsenic and chromium species in waters and bottom sediments of three water reservoirs in Upper Silesia (Poland): a comparative study

“…Among three compared water reservoirs, Goczałkowice was studied best due to its strategic importance as a drinking water source for the Upper Silesia inhabitants. The studies also concentrated on the surface water biomonitoring [22] or speciation of metals from bottom sediments with the modified Tessier's method [23].…”

Impact of River Water and Bottom Sediment Pollution on Accumulation of Metal(loid)s and Arsenic Species in the Coastal Plants Stuckenia pectinata L., Galium aparine L., and Urtica dioica L.: A Chemometric and Environmental Study

“…Methods of chemometric analysis were used to investigate the relationship between metals and metalloids contained in water, bottom sediment, and plants. In the analysis of experimental data, the concepts of (Dis)similarity Analysis using a matrix of distances , Cluster Analysis (CA) (Massart and Kaufman 1983;Smoliński et al 2002;Dabioch et al 2012) and Principal Component Analysis (PCA) (Joliffe 1986;Wold et al 1987;Dabioch et al 2013) were used.…”