Mercury in the sediments of selected peatlands in Małopolska region

Abstract

Czerwonem in the Orawa-Nowy Targ Basin) was determined to a depth of 100 cm at a resolution of 1-2 cm. Geochemical background and level of anthropogenic mercury enrichment were determined for each peat bog. To establish the interdependence between mercury concentration, mineral matter content and selected metals, geochemical diagrams and models of the system were drawn up representing the correlational relationships between the selected geochemical variables for three of the peat bogs in the Orawa--Nowy Targ Basin (Otrębowskie Brzegi, Przybojec and Bór na Czerwonem). It was found that, comparing against other European raised bogs, the range of mercury concentrations in the peat layer down to 50 cm in the peatlands of Małopolska is similar to those in Norway, Sweden, Denmark and Spain, and decidedly lower than in the peatlands in Scotland, Belgium and Czechia. Furthermore, the sites in the Orawa-Nowy Targ Basin were clearly lower, the lower the altitude of the peat bog surface, which is probably associated with local topoclimatic conditions.

Geochemical characteristics of Late Glacial and Holocene biogenic sediments in central Poland and implications for reconstructing the palaeoenvironment

“…In the first case, however, these are usually single ecosystems, in which the geochemical topics discussed refer chronostratigraphic differences or differences between individual accumulation zones (Wojciechowski 1990;Bojakowska, Sokołowska 1997;Aleksander-Kwaterczak, Kostka 2011;Pawłowski et al 2014;Adumitroaei et al 2018;Adamek et al 2021;Juśkiewicz, Gierszewski 2022); the sediments of several biogenic accumulation reservoirs within one morphogenetic or landscape zone have been compared less often (e.g., Wicik 1984;Borówka 1992;Owsianny et al 2011;Kłapyta et al 2016). In cases of statistical description, the most commonly used measures are averages, dispersion and asymmetry (Bojakowska, Lech 2008;Borówka et al 2022). On the other hand, statistical inferencing to detect interdependencies between individual elements of the chemical composition of sediments and environmental factors is most effective for stations with long measurement series (e.g., Boryczka, Wicik 1983;Walanus 2000;Zander et al 2021;Płóciennik et al 2022), or for larger areas covered by detailed monitoring (Marszelewski 2005;Sojka et al 2022).…”