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The Effect of Particulate Matter Components on the Acidity of Rain in Upper Silesia (Poland)
Authors:Stanislaw Hlawiczka  Katarzyna Korszun
Institution:1. Institute for Ecology of Industrial Areas, Katowice, Poland;2. Department of Environmental Protection and Engineering, Technical University of Czestochowa, Czestochowa, Poland
Abstract:Analysis of data characterizing the chemical composition of atmospheric precipitation was presented, with an emphasis on components responsible for neutralization of rain acidity. For this purpose, chemometric methods were applied. Based on a principal component analysis (PCA) a strong correlation between precipitation pH and potassium and ammonium ions in the heating period (October–March) and potassium and sodium ions in the non‐heating period (April–September) was observed. Additionally, a classification of eight variables, i.e., Na+, K+, Mg2+, Ca2+, equation image , equation image , Cl?, and equation image according to their similarities was made using a cluster analysis. Based on this study, two ions, potassium and ammonium, together with the pH value were classified into one group (cluster) in the heating period while in the non‐heating period ions of potassium and sodium were clustered together with the pH. The results of the cluster analysis indicated that the selected ions contributed the most to the neutralization of the atmospheric precipitation acidity. This relationship was confirmed by a discriminant analysis in which potassium and ammonium ions were selected as components of the highest potential for precipitation classification according to its acidity degree. The relationship between the precipitation pH and the number of non‐precipitation days preceding the precipitation was also analyzed. It was found that although the observed an increase of the pH value was not very high, nevertheless, the effect of the duration of the period preceding the precipitation on the pH value recorded on the day of the precipitation occurrence was quite evident.
Keywords:Acid rain  Cluster analysis  Discriminant analysis  Principal component analysis
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