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Zhu, H., Yuan, X., Zeng, G., Jiang, M., Liang, J., Zhang, C., Yin, J., Huang, H., Liu, Z. and Jiang, H. (2012) Ecological Risk Assessment of Heavy Metals in Sediments of Xiawan Port Based on Modified Potential Ecological Risk Index. Transactions of Nonferrous Metals Society of China, 22, 1470-1477.
http://dx.doi.org/10.1016/S1003-6326(11)61343-5

has been cited by the following article:

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

  AUTHORS: Yovana Todorova, Ivaylo Yotinov, Stilyana Lincheva, Yana Topalova

  KEYWORDS: Risk Identification, Dehydrogenase Activity, Phosphatase Activity Index, Sediments, Co-Contamination

  JOURNAL NAME: Journal of Water Resource and Protection, Vol.7 No.2, January 30, 2015

  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.