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

J 2009

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 et. al.

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

Language

English

Type of outcome

Článek v odborném periodiku

Field of Study

30304 Public and environmental health

Country of publisher

United States of America

Confidentiality degree

není předmětem státního či obchodního tajemství

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

Abstract

V originále

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)

Citovat

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.

@article{874049,
   author = {Kubošová, Klára and Komprda, Jiří and Jarkovský, Jiří and Sáňka, Milan and Hájek, Ondřej and Dušek, Ladislav and Holoubek, Ivan and Klánová, Jana},
   article_location = {USA},
   article_number = {24},
   keywords = {POP concentration spatial model soil},
   language = {eng},
   issn = {0013-936X},
   journal = {Environmental Science & Technology},
   title = {Spatially Resolved Distribution Models of POP Concentrations in Soil: A Stochastic Approach Using Regression Trees},
   volume = {43},
   year = {2009}
}

TY  - JOUR
ID  - 874049
AU  - Kubošová, Klára - Komprda, Jiří - Jarkovský, Jiří - Sáňka, Milan - Hájek, Ondřej - Dušek, Ladislav - Holoubek, Ivan - Klánová, Jana
PY  - 2009
TI  - Spatially Resolved Distribution Models of POP Concentrations in Soil: A Stochastic Approach Using Regression Trees
JF  - Environmental Science & Technology
VL  - 43
IS  - 24
SP  - 9230–9236
EP  - 9230–9236
SN  - 0013936X
KW  - POP concentration spatial model soil
N2  - 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.
ER  -

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. \textit{Environmental Science \&{} Technology}. USA, 2009, vol.~43, No~24, p.~9230–9236. ISSN~0013-936X.

Detailed Information on Publication Record