A Large-Scale Identification of Sediment-Associated Risks of Contamination with Heavy Metals and Organics: Indicators and Algorithms
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http://www.scirp.org/journal/PaperInformation.aspx?PaperID=53695#.VM85jizQrzE
ABSTRACT
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.
KEYWORDS
Risk Identification, Dehydrogenase Activity, Phosphatase Activity Index, Sediments, Co-Contamination
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References
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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.
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