Accurate values of thermophysical transport properties of particle beds are necessary to accurately model heat and mass transfer processes in particle beds that under-go preferred processes and changes. The objective of this study is to use a proven analytical/numerical methodology to estimate the unknown transport properties within test cells filled with silicagel particles and compare the results with the previously published data. An experimental test cell was designed and constructed to carry out transient heat transfer tests for both step change conduction and convection heat transfer within a packed bed of silicagel particles. For a known step change in the test cell temperature boundary condition, the temporal temperature distribution within the bed during heat conduction depends only on the effective heat conduction coefficient and the thermal capacity of the particle bed. The central problem is to, using only the boundary conditions and a few time-varying temperature sensors in the test cell of particles, determine the effective thermal conductivity of the test bed and specify the resulting measurement uncertainty. A similar problem occurs when the heat convection coefficient is sought after a step change in the airflow inlet temperature for the test cell. These types of problems are known as inverse heat transfer problems (IHTP). In this thesis, IHTP method was used to estimate the convective heat transfer coefficient. Good agreement was seen in experimental and numerical temperature profiles, which were modeled by using the estimated convective heat transfer coefficient. The same methodology was used to estimate the effective thermal conductivity of the particle bed. Comparison between the experimental temperature distribution and numerical temperature distribution, which was modeled by using the estimated effective conductivity, illustrated good agreement. On the other side, applying the effective thermal conductivity, obtained from a direct steady state measurement, in the numerical simulation could not present agreement between the numerical and experimental results. It was concluded that the IHTP methodology was a successful approach to find the thermophysical properties of the particle beds, which were hard to measure directly.

In this work a new simplified procedure for isolation and determination of PAH in smoked meat products was developed. This procedure is using ASE as selective extraction technique. Its principle is addition of silicagel activated during 18 hours at 140 °C directly to the extraction cell in ratio 10 g to 1 g of homogenized sample. In the next step the sample is extracted by n-hexane at 100 °C and 10 MPa for three 10 minutes static extraction cycles. The flush volume is 60 % and the purge time 120 sec. During the extraction silicagel adsorb koextracted lipids and thus the obtained extract is suitable for immediate HPLC-FLD analysis. On the contrary, the classical extraction procedures with nonpolar solvent require difficult purification of extract for removal of unwanted lipids. Mostly applied techniques here are GPC and SPE. The new procedure was validated for determination of B[a]P as well as for determination of 4 PAH (B[a]A, CHR, B[b]F, B[a]P) in smoked sausages. It meets all requirements to be set by Regulation (EC) No 333/2007, respective by new Regulation (EC) No 836/2011. After the method validation, the content of 4 PAH was investigated in twelve samples of various smoked sausages manufactured in Slovakia. Two analyzed products showed high PAH levels exceeding maximum legislation limits set for B[a]P as well as for sum of 4 PAH by Regulation (EC) No 835/2011.

The work has been focused on the preconcentration techniques for determination of 9Be, 51V, 59Co, 60Ni, 89Y, 111Cd, 208Pb, 232Th and 238U on the modified sorbents, all measurements were performed on ICP-MS. The instrument setup was optimized. The solution of internal standard (200 µg•l-1) was used during all measurements. The internal standard were chosen as follows: 6Li for 9Be, 45Sc (51V), 72Ge (59Co, 60Ni, 89Y), 103Rh (111Cd), 209Bi (206Pb, 207Pb, 208Pb, 232Th and 238U). Another parameters such as influence of mineral acids (HCl, HNO3), surfactant (Septonex®, Zephyramin, Ajatin, Brij 35 and Sodium dodecyl sulphate) and organic reagents (Ammonium pyrrolidinedithiocarbamate, 8-Hydroxyquinoline-5-sulphonic acid, 1,2-Dihydroxyanthraquinone-3-sulphonic acid and 4-(2-Pyridylazo)resorcinol) and the effect of some matrix components on intensity of instrument signal determination was investigated. For preconcentration polar Silicagel and modified nonpolar Silicagels (Silicagel-C18, C8 nad Phenyl) were used. Another experimantal part was dedicated to preconcentration on nonpolar Amberlite XAD-16 and Strata SDB-L and intermediately polar sorbent Amberlite XAD-7. Recoveries of sorption process were observed in the presence of all testing types of surfactants in certified concentration 5•10-4 mol•l-1. Surfactants were always applied in the conditioning step. The suitable combinations of surfactant and organic reagent were tested for increasing of recoveries of analytes. Testing organic reagents were added in five times mass excess againts concentration of analytes, the concentration of the organic reagents was 900 µg•l-1. The organic reagent was always added to the solution for preconcentration before this solution was led on the sorbent. The composition and a necessary volume of elution mixture for quantitative elution were tested, too. Only one sorbent was chosen from each group of sorbents with similar properties. The chosen sorbent showed the best recoveries in majority of target analytes. The highest recoveries from silica-group was reached for Silicagel-C18, from nonpolar Amberlite was chosen Strata SDB-L and intermediately polar Amberlite XAD-7. The influence of some matrix components (anionts and cations) on recoveries of analytes was investigated for chosen sorbent. The optimized process was applied on real samples of nature water and industry water. In experimental part all analytes are marked as specific izotopes, which were measured by ICP-MS. Of course, all izotopes of analytes undergo preconcentration techniques.