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Evaluation of the performance and limitations of empirical partition-relations and process based multisurface models to predict trace element solubility in soils
- Source :
- Environmental Pollution 166 (2012), Environmental Pollution, 166, 98-107
- Publication Year :
- 2012
- Publisher :
- Elsevier BV, 2012.
-
Abstract
- Here we evaluate the performance and limitations of two frequently used model-types to predict trace element solubility in soils: regression based "partition-relations" and thermodynamically based "multisurface models", for a large set of elements. For this purpose partition-relations were derived for As, Ba, Cd, Co, Cr, Cu, Mo, Ni, Pb, Sb, Se, V, Zn. The multi-surface model included aqueous speciation, mineral equilibria, sorption to organic matter, Fe/Al-(hydr)oxides and clay. Both approaches were evaluated by their application to independent data for a wide variety of conditions. We conclude that Freundlich-based partition-relations are robust predictors for most cations and can be used for independent soils, but within the environmental conditions of the data used for their derivation. The multisurface model is shown to be able to successfully predict solution concentrations over a wide range of conditions. Predicted trends for oxy-anions agree well for both approaches but with larger (random) deviations than for cations.
- Subjects :
- Cation binding
Bodemscheikunde en Chemische Bodemkwaliteit
Health, Toxicology and Mutagenesis
Statistics as Topic
contaminated soils
Mineralogy
Thermodynamics
complexation models
Toxicology
Soil
Soil Pollutants
heavy-metals
Partition (number theory)
cation-binding
Organic matter
Duurzaam Bodemgebruik
Solubility
natural organic-matter
Sustainable Soil Use
chemistry.chemical_classification
humic substances
Trace element
assemblage model
Sorption
General Medicine
Pollution
Trace Elements
Models, Chemical
chemistry
Soil water
zn
agricultural soils
metal-ion binding
Soil Chemistry and Chemical Soil Quality
Aqueous speciation
Environmental Monitoring
Subjects
Details
- ISSN :
- 02697491
- Volume :
- 166
- Database :
- OpenAIRE
- Journal :
- Environmental Pollution
- Accession number :
- edsair.doi.dedup.....aa7469ad08bf1c8203eebb8c0f6de383
- Full Text :
- https://doi.org/10.1016/j.envpol.2012.03.011