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Relationship of Metal Contaminants with Acid-Volatile Sulphides (AVS) in Tropical Estuarine Sediments: Potential Influence on Metal Distribution and Bioavailability

  • M. F. Carvalho
  • W. Machado
  • R. E. Santelli
  • J. E. L. Maddock
Chapter
Part of the Environmental Science book series (ESE)

Abstract

The river transport of anthropogenic trace metals to coastal areas and the extent to which these elements are trapped within coastal systems are issues of great interest (Salomons and Förstner 1984). Many studies have investigated the input of metals transported by estuarine waters to coastal areas and the ability of sediments to scavenge and retain them (e.g. Bricker 1993; Lacerda et al.1993; Puig et al.1999; Rozan and Benoit 1999). Besides the evident influence of fluctuating metal loading and hydrodynamic conditions, it has been widely demonstrated that the metal biogeochemistry in the water column and underlying sediments is critical in determining the efficiency of metal removal from waters by sediments. For example, changes in sediment chemistry can occur in conjunction with changes in overlying water redox conditions that may lead to the remobilisation of accumulated metals (Cooper and Morse 1996). However, remobilised elements may again be removed from the water column after being released from the sediments (Warnken et al. 2001). As the presence of geochemically reactive phases of trace metals may occur at elevated levels under a wide range of sedimentary conditions (e.g. due to variable redox conditions, differentiated organic matter supply and anthropogenic disturbances), research on the factors regulating the diagenetic behaviour of metals within sediments is essential to understanding the pathways of accumulation and transfer of these elements, their removal from the overlying waters and their potential bioavailability in each particular environmental condition.

Keywords

Metal Contaminant Environ Toxicol Simultaneously Extract Metal Organic Matter Supply Sediment Accretion Rate 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • M. F. Carvalho
  • W. Machado
  • R. E. Santelli
  • J. E. L. Maddock

There are no affiliations available

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