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Due to relatively cold climate and an abundance of soils rich in organic carbon, the concentration of natural organic matter (NOM) in raw water of Boreal region is high and its removal during conventional water treatment is complicated. This thesis show possibility to determine the NOM removal efficacy during humic rich raw water treatment using inexpensive chemical methods, which allow detection of specific organic compounds removal efficiency during each water treatment stage. During monitoring of the water treatment process the correction necessary to optimize the coagulation process of…mehr

Produktbeschreibung
Due to relatively cold climate and an abundance of soils rich in organic carbon, the concentration of natural organic matter (NOM) in raw water of Boreal region is high and its removal during conventional water treatment is complicated. This thesis show possibility to determine the NOM removal efficacy during humic rich raw water treatment using inexpensive chemical methods, which allow detection of specific organic compounds removal efficiency during each water treatment stage. During monitoring of the water treatment process the correction necessary to optimize the coagulation process of humic rich water was determined. In this research the degradation rate of biodegradable dissolved organic carbon in different type of water produced from humic rich raw waters was determined and factors affecting biodegradation rate were evaluated. Results indicate that NOM significantly affects water quality in water distribution network, where the NOM accumulation in loose deposits of water supply system and biological degradation processes as a result of inefficient operation of biological filter takes place.
Autorenporträt
Kristina Tihomirova received her MChem at the University of Latvia in 2000. Currently she is a researcher in Riga Technical University Department of Water Engineering and Technology and received her PhD in 2011. Main research interests are water treatment and quality, optimization of treatment processes, rapid detection of contaminants in network.