Spatially Resolved Distribution Models of POP Concentrations in Soil: A Stochastic Approach Using Regression Trees
Identifikátory výsledku
Kód výsledku v IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14310%2F09%3A00039152" target="_blank" >RIV/00216224:14310/09:00039152 - isvavai.cz</a>
Výsledek na webu
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DOI - Digital Object Identifier
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Alternativní jazyky
Jazyk výsledku
angličtina
Název v původním jazyce
Spatially Resolved Distribution Models of POP Concentrations in Soil: A Stochastic Approach Using Regression Trees
Popis výsledku v původním jazyce
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 ofthe 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.
Název v anglickém jazyce
Spatially Resolved Distribution Models of POP Concentrations in Soil: A Stochastic Approach Using Regression Trees
Popis výsledku anglicky
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 ofthe 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.
Klasifikace
Druh
J<sub>x</sub> - Nezařazeno - Článek v odborném periodiku (Jimp, Jsc a Jost)
CEP obor
DN - Vliv životního prostředí na zdraví
OECD FORD obor
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Návaznosti výsledku
Projekt
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Návaznosti
Z - Vyzkumny zamer (s odkazem do CEZ)
Ostatní
Rok uplatnění
2009
Kód důvěrnosti údajů
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Údaje specifické pro druh výsledku
Název periodika
Environmental Science & Technology
ISSN
0013-936X
e-ISSN
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Svazek periodika
43
Číslo periodika v rámci svazku
24
Stát vydavatele periodika
US - Spojené státy americké
Počet stran výsledku
7
Strana od-do
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Kód UT WoS článku
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EID výsledku v databázi Scopus
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