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2 Open Chemistry

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Application of chemometrics to identifying solid fuels and their origin

100%

Sajdak M.

Open Chemistry

2013

tom 11

nr 2

151-159

The aim of this work was to implement a chemometric analysis to detect the relationships between the analysed variables in samples of solid fuels. Efforts are being made to apply chemometrics methods in environmental issues by developing methods for the rapid assessment of solid fuels and their compliance with the required emission characteristics regulations. In the present investigation, two clustering techniques-hierarchical clustering analysis (HCA) and principal components analysis (PCA)-are used to obtain the linkage between solid fuel properties and the type of sample. These analyses allowed us to detect the relationships between the studied parameters of the investigated solid fuels. Furthermore, the usefulness of chemometrics methods for identification of the origin of biofuels is shown. These methods will enable control of the degree of contamination. [...]

Assessment of the impact of a phosphatic fertilizer plant on the adjacent environment using fuzzy logic

100%

Szczepaniak K. , Sârbu C. , Astel A. , Raińska1 E. , Biziuk M. , Culicov O. , Frontasyeva M. V. , Bode P.

Open Chemistry

2006

tom 4

nr 1

29-55

The impact of a phosphatic fertilizer plant on the adjacent environment was examined. Selected rare earth elements, heavy metals and metalloids were determined in substrates and products, waste by-product, and grass and soil samples. Concentration gradients of elements in grass and soil samples along the southerly and easterly directions were examined and compared with the content of interior soil and grass samples, substrates, and products. Results were compared with available data on soil permissible element concentration levels. Two fuzzy principal component analysis (FPCA) methods for robust estimation of principal components were applied and compared with classical PCA. The efficiency of the new algorithms is illustrated. The investigation explored the impact of the plant on the adjacent environment. The most reliable results, in good agreement with types of samples, were produced using the FPCA-O algorithm