A Large-Scale Identification of Sediment-Associated Risks of Contamination with Heavy Metals and Organics: Indicators and Algorithms

DOI: 10.4236/jwarp.2015.72008   PDF   HTML   XML   2,554 Downloads   3,074 Views   Citations


As mediators in key biotransformation processes, the complex enzyme activities (measured as a total of extracellular and intracellular activity on sub-organism, organism and supra-organism level) have a high potential to be used as reliable indicators for risk identification in co-contaminated sediments with organics and heavy metals. Two enzyme activities—dehydrogenase activity (TTC-DHA) and phosphatase activity index (PAI) were measured by use of methods with tetrazolium chloride and p-nitrophenyl phosphate in polluted sediments of Middle Iskar River part, Bulgaria. The environmental state of river sector has been strongly influenced by the organics, nutrients, xenobiotics pollutants and by the intensive hydrotechnical activity for construction of 9 micro-hydro power plants. The change of hydrological regime was a factor for intensive sediment accumulation and concentration of pollutants in the area of the cascade. Data for total activities of dehydrogenases and phosphatases in sediments were compared with total count of culturable sediment bacteria and pollutants concentrations. The results showed that the enzyme activities correlated positively with bacterial abundance in sediments and organics content in sediments and negatively with concentrations of xenobiotic pollutants (heavy metals). This approves a high potential of enzyme indicators for regulation of ecosystem self-purification capacity and for early assessment of sediment-associated risks of co-contamination. The correlative relations allow dividing the mathematical algorithms for control and management of processes in technologically influenced hydroecosystem.

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Todorova, Y. , Yotinov, I. , Lincheva, S. and Topalova, Y. (2015) A Large-Scale Identification of Sediment-Associated Risks of Contamination with Heavy Metals and Organics: Indicators and Algorithms. Journal of Water Resource and Protection, 7, 101-110. doi: 10.4236/jwarp.2015.72008.

Conflicts of Interest

The authors declare no conflicts of interest.


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