Application of Chemometric Analysis to the Study of Snow at the Sudety Mountains, Poland

Abstract

Snow samples were collected during winter 2011/2012 in three posts in the Western Sudety Mountains (Poland) in 3 consecutive phases of snow cover development, i.e. stabilisation (Feb 1st), growth (Mar 15th) and its ablation (Mar 27th). To maintain a fixed number of samples, each snow profile has been divided into six layers, but hydrochemical indications were made for each 10 cm section of core. The complete data set was subjected in the first run of chemometric data interpretation to Cluster Analysis as well as Principal Components Analysis. Further, Self-Organizing Maps, type of neutral network described by Kohonen were used for visualization and interpretation of large high-dimensional data sets. For each site the hierarchical Ward's method of linkage, squared Euclidean distance as similarity measure, standardized raw data, cluster significance test according to Sneath's criterion clustering of the chemical variables was done. Afterwards this grouping of the chemical variables was confirmed by the results from Principal Components Analysis. The major conclusion is that the whole system of three sampling sites four patterns of variable groupings are observed: the first one is related to the mineral salt impact; the second one -with the impact of secondary emissions and organic pollutants; next one -with dissolved matter effect and the last one -with oxidative influence, again with relation to anthropogenic activities like smog, coal burning, traffic etc. It might be also concluded that specificity of the samples is determined by the factors responsible for the data set structure and not by particular individual or time factors.

Using an Urban Snow Cover Composition-Based Cluster Analysis to Zone Krasnoyarsk Town (Russia) by Pollution Level

“…The latter clustering type is detailed in Blas et al [25], where they discuss variable grouping patterns coming from mineral salt impact, impact of secondary emissions and organic pollutants, dissolve matter effects, and human-caused oxidative influences. Shevchenko [39] used the same approach to analyzing snow cover chemical composition and its influence on surface water hydrochemistry in little-studied West Siberian Lowland.…”

“…Similar studies were done in Baikal Region [11,12], for Severonikel Industrial Complex, the Kola Peninsula, NW Russia [13], Tomsk Town [14,15], Tumen Town [16] and for many other industrial towns with stable snow cover. Studying snow cover to estimate pollution, particularly traffic impacts, in urban areas attracts nowadays much interest in Scandinavia [17,18], East European countries [19][20][21][22][23][24][25], the USA [26], and China [27].…”

Metals in Plant Functional Types of Ombrotrophic Peatlands in the Sudetes (SW Poland)

“…; thus it is more exposed to the prevailing western air masses, which facilitates effective transport of airborne contaminants within long-range deposition. Pollution control improved the situation in the former Black Triangle but some contamination is still produced by power plants and chemical industry (Kosior et al 2010;Błaś et al 2016;Wojtuń et al 2017;Kazienko et al 2020). Additionally, metals released to the environment decades ago may persist in the ecosystems for many years (Kabata-Pendias 2001b).…”

“…This is all the more important that this type of peat bogs in the Sudetes is contaminated by long-range transport from the former Black Triangle Region (Fig. 1) with mining of lignite, chemical industry, and electric power plants that affect the environment in the region (Błaś et al 2016;Wojtuń et al 2017). Peat bogs, especially those located at higher elevations, are an effective barrier for the retention of contaminants deposited by atmospheric fallout (orographic barriers).…”