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Regionale und substratabhängige Verteilung von Schwermetallen in oberflächennahen Sedimenten des Inner Kingston Basin, Ontariosee / Spatial and Substrate Associated Distribution of Heavy Metals in Surficial Sediments from Inner Kingston Basin, Lake Ontario

The sequential extraction scheme BCR 701 has been applied to the upper 2 cm layer of 39 sediment samples from Inner Kingston Basin, Ontario. The samples were also been characterized by water content, loss on ignition at 550°C and 950°C and by particle size distribution. Methodological problems occurred during particle size analysis, caused by agglomerating effects, mainly driven by organic matter, which is fairly resistant against oxidation by hydrogen peroxide due to natural manganese dioxide particles in the sediments. This leads to an overestimation of the clay content. For the same reason, the digestion in step 3 of the sequential extraction was insufficient, so that typical organic bound metals were found in the residual fraction. From factor and cluster analysis of all data three main substrate element associations were derived: The carbonate group contains Ca, Sr, LOI 950°C from calcite, and in step 2 additional Mg extracted from dolomite. Secondly, the organic associations include LOI 550°C, water content and clay content, and finally the metals (except from carbonate bound metals) which are more or less linked to the organic associations. Regionalized maps using inverse distance weighting or ordinary Kriging have been judged to be less precise and informative than point data maps using a classification following equal standard deviation distances and additional statistical information, box plots and histograms. Compared to the geogenic background, all samples show a significant metal enrichment in the mobile fractions, so that they could easily be remobilized during changing environmental conditions. Higher enrichment rates have been detected around the city of Kingston, mainly the harbour region, and close to the outlet of Kingston s sewage treatment plant. Generally, local contamination can easily be detected and differentiated according to their origin from sequential extraction data.

Identiferoai:union.ndltd.org:uni-osnabrueck.de/oai:repositorium.ub.uni-osnabrueck.de:urn:nbn:de:gbv:700-2004110917
Date09 November 2004
CreatorsDöpke, Gisbert
ContributorsProf. Dr. J. W. Härtling, Prof. Dr. H. Meuser
Source SetsUniversität Osnabrück
LanguageGerman
Detected LanguageEnglish
Typedoc-type:doctoralThesis
Formatapplication/zip, application/pdf
Rightshttp://rightsstatements.org/vocab/InC/1.0/

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