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Statements

Subject Item
n2:RIV%2F00216224%3A14310%2F09%3A00039152%21RIV10-MSM-14310___
rdf:type
skos:Concept n16:Vysledek
dcterms:description
Background concentrations of selected persistent organic pollutants (PCBs, HCB, p,p-DDT including metabolites and PAHs) in soils of the Czech Republic were predicted in this study, and the main factors affecting their geographical distribution were identified. A database containing POP concentrations in 534 soil samples and the set of specific environmental predictors were used for development of a model based on regression trees. Selected predictors addressed specific conditions affecting a behavior of the individual groups of pollutants: a presence of primary and secondary sources, density of human settlement, geographical characteristics and climatic conditions, land use, land cover, and soil properties. The model explained a high portion of variability in relationship between the soil concentrations of selected organic pollutants and available predictors. The validation results confirmed that the model is stable, general and useful for prediction. Background concentrations of selected persistent organic pollutants (PCBs, HCB, p,p-DDT including metabolites and PAHs) in soils of the Czech Republic were predicted in this study, and the main factors affecting their geographical distribution were identified. A database containing POP concentrations in 534 soil samples and the set of specific environmental predictors were used for development of a model based on regression trees. Selected predictors addressed specific conditions affecting a behavior of the individual groups of pollutants: a presence of primary and secondary sources, density of human settlement, geographical characteristics and climatic conditions, land use, land cover, and soil properties. The model explained a high portion of variability in relationship between the soil concentrations of selected organic pollutants and available predictors. The validation results confirmed that the model is stable, general and useful for prediction.
dcterms:title
Spatially Resolved Distribution Models of POP Concentrations in Soil: A Stochastic Approach Using Regression Trees Spatially Resolved Distribution Models of POP Concentrations in Soil: A Stochastic Approach Using Regression Trees
skos:prefLabel
Spatially Resolved Distribution Models of POP Concentrations in Soil: A Stochastic Approach Using Regression Trees Spatially Resolved Distribution Models of POP Concentrations in Soil: A Stochastic Approach Using Regression Trees
skos:notation
RIV/00216224:14310/09:00039152!RIV10-MSM-14310___
n3:aktivita
n7:Z
n3:aktivity
Z(MSM0021622412)
n3:cisloPeriodika
24
n3:dodaniDat
n5:2010
n3:domaciTvurceVysledku
n8:7314949 n8:9478426 n8:4504135 n8:1799320 n8:6120393 n8:9008888 n8:8953244 n8:3635872
n3:druhVysledku
n10:J
n3:duvernostUdaju
n6:S
n3:entitaPredkladatele
n15:predkladatel
n3:idSjednocenehoVysledku
342752
n3:idVysledku
RIV/00216224:14310/09:00039152
n3:jazykVysledku
n14:eng
n3:klicovaSlova
POP concentration spatial model soil
n3:klicoveSlovo
n17:POP%20concentration%20spatial%20model%20soil
n3:kodStatuVydavatele
US - Spojené státy americké
n3:kontrolniKodProRIV
[7A8A8AB3F9B7]
n3:nazevZdroje
Environmental Science & Technology
n3:obor
n11:DN
n3:pocetDomacichTvurcuVysledku
8
n3:pocetTvurcuVysledku
8
n3:rokUplatneniVysledku
n5:2009
n3:svazekPeriodika
43
n3:tvurceVysledku
Dušek, Ladislav Holoubek, Ivan Jarkovský, Jiří Sáňka, Milan Komprda, Jiří Hájek, Ondřej Kubošová, Klára Klánová, Jana
n3:zamer
n18:MSM0021622412
s:issn
0013-936X
s:numberOfPages
7
n13:organizacniJednotka
14310