Formy výskytu rizikových prvků v kanalizační síti v Ostravě.

Abstract

The dissertation thesis focuses on the study of behavior of risk elements and their occurrence forms in urban wastewater in combined sewer systems in Ostrava. Stricter regulatory requirements on the quality of treated wastewater and the content of pollutants in sewage sludge require identification of pollution sources contribution. To determine possible sources of risk elements the information about the contents of risk elements in wastewater during dry water periods (point sources and domestic wastewater) as well as during wet water periods (influence of non-point sources) was demonstrated. To determine variability in the contents of risk elements in combined sewer systems the research contents of risk elements from 14 sampling points (altogether 448 samples were obtained) was used. Statistically significant variability in the contents of As, Cr, Cd, Cu, Zn, Mn and Fe was demonstrated. To determine background concentrations of risk elements in combined sewer systems the geochemical principle was applied – calculation of geochemical background. For risk elements the geochemical background values are: 2,3 μg/l for As, 8,5 μg/l for Cr, 0,2 μg/l for Cd, 35,0 μg/l for Cu, 11,5 μg/l for Ni, 28,0 μg/l for Pb, 0,3 μg/l for Hg, 210,0 μg/l for Zn, 161,5 μg/l for Mn and 1305,0 μg/l for Fe. To estimate the daily production of risk elements per capita, which is captured in domestic wastewater, 10 sampling sites for 6 months was sampled. The amounts of the risk elements produced per person and day were estimated to As 361,52 μg/day, Cr 601,82 μg/day, Cu 9004,4 μg/day, Ni 2233,1 μg/day, Pb 5402,4 μg/day, Zn 43,8 mg/day, Mn 41,8 mg/day, Fe 155,2 mg/day. These values were used to calculate the contribution municipal wastewater pollution produced by households. Households are involved in the overall loads of municipal wastewater in the combined sewer systems in Ostrava in the range from 8 % (Fe) to 63 % (Cu). Emphasis was placed on the correct statistical data analysis the analytical results. The exploratory data analysis and statistical analysis for descriptive statistics using a series of statistical tests and graphical diagnostics were performed. To identify significant sources of pollution the multivariate statistical analysis were performed. It was found that runoff from roofs and roads are significant non-point sources for Cu, Zn, Cr, Cd, Pb a Ni.