Spatially Resolved Distribution Models of POP Concentrations in Soil: A Stochastic Approach Using Regression Trees

KUBOŠOVÁ, Klára, Jiří KOMPRDA, Jiří JARKOVSKÝ, Milan SÁŇKA, Ondřej HÁJEK, Ladislav DUŠEK, Ivan HOLOUBEK and Jana KLÁNOVÁ. Spatially Resolved Distribution Models of POP Concentrations in Soil: A Stochastic Approach Using Regression Trees. Environmental Science & Technology. USA, 2009, vol. 43, No 24, p. 9230–9236. ISSN 0013-936X.

Basic information

• Original name: Spatially Resolved Distribution Models of POP Concentrations in Soil: A Stochastic Approach Using Regression Trees
• Authors: KUBOŠOVÁ, Klára (203 Czech Republic, guarantor), Jiří KOMPRDA (203 Czech Republic), Jiří JARKOVSKÝ (203 Czech Republic), Milan SÁŇKA (203 Czech Republic), Ondřej HÁJEK (203 Czech Republic), Ladislav DUŠEK (203 Czech Republic), Ivan HOLOUBEK (203 Czech Republic) and Jana KLÁNOVÁ (203 Czech Republic).
• Edition: Environmental Science & Technology, USA, 2009, 0013-936X.

Other information

• Original language: English
• Type of outcome: Article in a journal
• Field of Study: 30304 Public and environmental health
• Country of publisher: United States of America
• Confidentiality degree: is not subject to a state or trade secret
• Impact factor: Impact factor: 4.630
• RIV identification code: RIV/00216224:14310/09:00039152
• Organization unit: Faculty of Science
• UT WoS: 000272462500032
• Keywords in English: POP concentration spatial model soil
• Tags: International impact, Reviewed

Abstract

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.

Links

• MSM0021622412, plan (intention): Name: Interakce mezi chemickými látkami, prostředím a biologickými systémy a jejich důsledky na globální, regionální a lokální úrovni (INCHEMBIOL) (Acronym: INCHEMBIOL)

Investor: Ministry of Education, Youth and Sports of the CR, Interactions among the chemicals, environment and biological systems and their consequences on the global, regional and local scales (INCHEMBIOL)