Supplement: Application of ICP-MS and various computational methods for drinking water quality assessment from the Silesian District (Southern Poland)

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1 Cent. Eur. J. Chem. 10(1) 2012 S1-S6 DOI: /s y Central European Journal of Chemistry Supplement: Application of ICP-MS and various computational methods for drinking water quality assessment from the Silesian District (Southern Poland) Supplementary Information Robert Skorek 1*, Magdalena Jablonska 2, Marzena Polowniak 1, Andrzej Kita 1, Piotr Janoska 3, Franciszek Buhl 1 1 Department of Analytical Chemistry, Institute of Chemistry, University of Silesia, Katowice, Poland 2 Institute of Environmental Engineering of the Polish Academy of Science, Zabrze, Poland 3 Department of Probability Theory, Institute of Mathematics, University of Silesia, Katowice, Poland Supplementary Table 1. The results - mean, standard deviation, median, kurtosis and skewness for all 12 groups of samples. cond* (μs cm -1 ) alk* (mmol H + L -1 ) * (mg CaCO 3 L -1 ) Co sub-region 1 mean (southern) SD SW (springs) median n = 23 kurtosis skewness sub-region 2 mean (Bedzin poviat) SD SW (Czarna Przemsza river) median n = 6 kurtosis skewness sub-region 3 mean (Bedzin poviat) SD GW (groundwater) median n = 14 kurtosis skewness sub-region 4 mean (Dabrowa) SD GW (groundwater) median n = 10 kurtosis skewness sub-region 5 mean (Central: Goczalkowice) SD SW (reservoirs) median n = 18 kurtosis skewness S1 * robert.skorek@us.edu.pl

2 R. Skorek et al. Supplementary Table 1. The results - mean, standard deviation, median, kurtosis and skewness for all 12 groups of samples. cond* (μs cm -1 ) alk* (mmol H + L -1 ) * (mg CaCO 3 L -1 ) Co sub-region 6 mean (Central: Go-Cza - Murcki) SD SW (reservoirs) median n = 40 kurtosis skewness sub-region 7 mean (Central: Go-Cza - Mikolow) SD SW (reservoirs) median n = 16 kurtosis skewness sub-region 8 mean (Maczki) SD mix (ala Przemsza river) median n = 16 kurtosis skewness sub-region 9 mean (biela+kozlowa Gora) SD mix (reservoir + groundwater) median n = 27 kurtosis skewness sub-region 10 mean (northern - Jura) SD GW (groundwater) median n = 18 kurtosis skewness sub-region 11 mean (western - Miedary) SD GW (groundwater) median n = 7 kurtosis skewness sub-region 12 mean (western - own supplies) SD GW (groundwater) median n = 6 kurtosis skewness * cond conductivity, alk alkalinity, - ness Rb Te Tl V sub-region 1 mean (southern) SD surface - springs median n = 23 kurtosis skewness sub-region 2 mean (Bedzin poviat) SD surface - Czarna Przemsza median S2

3 Supplement: Application of ICP-MS and various computational methods for drinking water quality assessment from the Silesian District (Southern Poland) Supplementary Table 1. The results - mean, standard deviation, median, kurtosis and skewness for all 12 groups of samples. Rb Te Tl V n = 6 kurtosis skewness sub-region 3 mean (Bedzin poviat) SD groundwater median n = 14 kurtosis skewness sub-region 4 mean (Dabrowa) SD groundwater median n = 10 kurtosis skewness sub-region 5 mean (Central: Goczalkowice) SD surface - reservoirs median n = 18 kurtosis skewness sub-region 6 mean (Central: Go-Cza - Murcki) SD surface - reservoirs median n = 40 kurtosis skewness sub-region 7 mean (Central: Go-Cza - Mikolow) SD surface - reservoirs median n = 16 kurtosis skewness sub-region 8 mean (Maczki) SD surface - ala Przemsza median n = 16 kurtosis skewness sub-region 9 mean (biela+kozlowa Gora) SD ground+surface water median n = 27 kurtosis skewness sub-region 10 mean (northern - Jura) SD groundwater median n = 18 kurtosis skewness sub-region 11 mean (western - Miedary) SD groundwater median n = 7 kurtosis skewness sub-region 12 mean (western - own supplies) SD groundwater median n = 6 kurtosis skewness S3

4 R. Skorek et al. Supplemetary Table 2. Pearson correlation coefficients for all sub-regions. * s-r 1 s-r 2 s-r 3 s-r 4 s-r 5 s-r 6 s-r 7 s-r 8 s-r 9 s-r10 s-r11 s-r12 V Tl Te cond ** alk Co Rb Te Tl cond alk Co Rb Te cond alk Co Rb cond alk S4 S4

5 Supplement: Application of ICP-MS and various computational methods for drinking water quality assessment from the Silesian District (Southern Poland) Supplemetary Table 2. Pearson correlation coefficients for all sub-regions. * s-r 1 s-r 2 s-r 3 s-r 4 s-r 5 s-r 6 s-r 7 s-r 8 s-r 9 s-r10 s-r11 s-r12 Rb Co Rb cond alk Co Rb cond alk Co cond 0.76 alk Co cond alk Co S5 S5

6 R. Skorek et al. Supplemetary Table 2. Pearson correlation coefficients for all sub-regions. Co * s-r 1 s-r 2 s-r 3 s-r 4 s-r 5 s-r 6 s-r 7 s-r 8 s-r 9 s-r10 s-r11 s-r12 cond alk Co cond alk Co cond alk cond 0.74 alk cond alk cond 0.84 alk *s-r sub-region. ness. cond conductivity. alk - alkalinity ** - all values below 0.65 were omitted S6

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