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| Titel |
Heavy metal contaminants on the Elbe River floodplains - chances and limits to prediction of topsoil qualities |
| VerfasserIn |
F. Krüger, B. Urban |
| Konferenz |
EGU General Assembly 2009
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| Medientyp |
Artikel
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| Sprache |
Englisch
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| Digitales Dokument |
PDF |
| Erschienen |
In: GRA - Volume 11 (2009) |
| Datensatznummer |
250030343
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| Zusammenfassung |
| For decades to centuries the Elbe river lands have been highly polluted by heavy metals and
organic micro pollutants due to uncontrolled and unlimited sewage disposal from settlements,
industries, agriculture and contaminated sites.
During high flood events polluted sediments are transported downstream and spread over the
floodplains where they have caused severe large scale contamination. Recent sustainable
agriculture on Elbe river grasslands requires site specific management, adapted to the degree
of contamination. Due to different sedimentation rates and different historical contamination
loads of pollutants, the status of soil contamination varies over time and between
sites.
As part of the RAMWASS project (Risk Assessment and Management of the
Water-Sediment-Soil System, 6th EU research frame programme), a topsoil monitoring
strategy was applied to the Lower-Saxony section of the Elbe River (Germany) which
incorporates different flooding situations. In 2007, 66 topsoils were sampled along 21 cross
sections within 11 meander loops. Up- and downstream, bankside and distant flooding
environments
were considered as well as different flooding frequences of sites. Measured soil parameters
were heavy metals (Cd, Cr, Cu, Hg, Ni, Pb, Zn) arsenic, organic carbon, nitrogen, pH and
grain size. Measured site parameters were elevation (flooding frequency) and distance to the
Elbe from pollution source. Findings included arsenic values ranging from 17-165 mg/kg;
cadmium, 0,5-11 mg/kg; and mercury, 0,1-20 mg/kg. More than 90 % of all investigated sites
exceed legally allowed “threshold values” for mercury of 2 mg/kg for grassland
use.
The described monitoring strategy enables an assessment of large scale pollution.
Multi-regression analyses were performed with selected parameters correlated to
sedimentation processes to predict contamination status without heavy metal analysis, but
with the help of easy assignable parameters as elevation, distance to the river from
pollution source, pH, Carbon, C/N and grainsize. The results are e. g. for mercury
equations:
Hgcalculated = -10,9 + (-0,87*ELEVATION [m] + 0,001*DISTANCE [m] + 0,15*PH +
1,43*CARBON [%] + 0,529*C/N + 0,08*GRAINSIZE [ |
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