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Temporal variations and bioaccumulation of heavy metals in different Suaeda salsa marshes of the Yellow River estuary, China.

  • Song, Hongli
  • Sun, Zhigao
Published Article
Environmental Science and Pollution Research
Springer Nature
Publication Date
Dec 01, 2014
DOI: 10.1007/s11356-014-3296-7
PMID: 25056745


To understand the temporal variations and bioaccumulation of heavy metals in the coastal marshes, the concentrations of heavy metals (Cr, Ni, Pb, and Cu) in the two Suaeda salsa marshes [middle S. salsa marsh (MM) and low S. salsa marsh (LM)] of the Yellow River estuary were determined from May to November in 2008 by in situ sampling and inductively coupled plasma mass spectrometry (ICP-MS) analysis. Results showed that heavy metal concentrations in S. salsa of MM and LM were generally in the order of Cu > Cr > Pb > Ni, while those in sediments fell in the order of Cr > Ni > Cu > Pb. Heavy metal concentrations of S. salsa in MM and LM were different, and significant differences were observed in stems (F = 4.797, p = 0.046) and litters (F = 6.799, p = 0.026) for Ni. Litter was the main stock of heavy metals, and the allocations of Cr, Ni, and Pb reached 31.25-51.31, 28.49-42.58, and 29.55-66.79 % (in MM) and 36.73-48.60, 41.70-57.87, and 33.30-60.64 % (in LM), respectively. The ratios of roots/leaves (R/L) and roots/stems (R/S) for Cr and Ni in MM were mostly greater than 1, while those ratios in LM were mostly less than 1, indicating that Cr and Ni in S. salsa at LM had greater mobility compared with those at MM. Moreover, the [accumulation factor, AF]plant of Cr, Ni, Cu, and Pb in LM, especially [AF]root and [AF]stem of Cr and [AF]litter of Ni, was also higher than that in MM. These indicated that S. salsa grown in LM was more suitable for potential biomonitor or phytoremediation of Cr, Ni, Cu, and Pb if intertidal sediments were seriously contaminated with an increase of pollutant loading (especially heavy metals) in the Yellow River estuary. The use of biomonitor (S. salsa) living and growing in LM could yield valuable information not only on the presence of anthropogenic stressors, but, more importantly, on the adverse influence the stressors are having on the environment.

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