Popular statistical techniques, such as Spearman's rank correlation matrix, principal component analysis (PCA) and multiple linear regression analysis were applied to analyze a large set of water quality data of the Rybnik Reservoir generated during semiannual monitoring. Water samples collected at 9 sampling sites located along the main axis of the reservoir were tested for 14 selected parameters: concentrations of co-occurring elements, ions and physicochemical parameters. The aim of this study was to estimate the impact of those parameters on inorganic arsenic occurrence in Rybnik Reservoir water by means of multivariate statistical methods. The spatial distribution of arsenic in Rybnik Power Station reservoir was also included. Inorganic arsenic As(III), As(V) concentrations were determined by hydride generation method (HG-AAS) using SpectrAA 880 spectrophotometer (Varian) coupled with a VGA-77 system for hydride generation and ECT-60 electrothermal furnace. Spearman's rank correlation matrix was used in order to find existing correlations between total inorganic arsenic (AsTot) and other parameters. The results of this analysis suggest that As was positively correlated with PO43-; Fe and TDS. PCA confirmed these observations. Principal component analysis resulted in three PC's explaining 57% of the total variance. Loading values for each component indicate that the processes responsible for As release and distribution in Rybnik Reservoir water were: leaching from bottom sediments together with other elements like Cu, Cd, Cr, Pb, Zn, Ni, Ca (PC1) and co-precipitation with PO43-, Fe and Mn (PC3) regulated by physicochemical properties like T and pH (PC2). Finally, multiple linear regression model has been developed. This model incorporates only 8 (T, pH, PO43-, Fe, Mn, Cr, Cu, TDS) out of initial 14 variables, as the independent predictors of total As contamination level. This study illustrates the usefulness of multivariate statistical techniques for analysis and interpretation of complex environmental data sets.
The presented results describe the effect of severe plastic deformation on the structure and mechanical properties of AA5083 and AA5754 alloys. Both materials were subjected to single hydrostatic extrusion (HE) and cumulative hydrostatic extrusion in the case of AA5083 and a combination of plastic deformation by equal-channel angular pressing (ECAP) with the next HE for AA5754. After the deformation, both alloys featured a homogeneous and finely divided microstructure with average grain size deq = 140 nm and 125 nm for AA5083 and AA5754, respectively. The selection of plastic forming parameters enabled a significant increase in the UTS tensile strength and YS yield stress in both alloys – UTS = 510 MPa and YS = 500 MPa for alloy AA5083 after cumulative HE, and 450 MPa and 440 MPa for alloy AA5754 after the combination of ECAP and HE, respectively. It has been shown on the example of AA5083 alloy that after the deformation the threads of the fasteners made of this material are more accurate and workable at lower cutting speeds, which saves the cutting tools. The resultant properties of AA5083 and AA5754 alloys match the minimum requirements for the strongest Al-Zn alloys of the 7xxx series, which, however, due to the considerably lower corrosion resistance, can be replaced in many responsible structures by the AA5xxx series Al-Mg alloys presented in this paper.