Geostatistical conditional simulation for the assessment of contaminated land by abandoned heavy metal mining

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dc.authorid0000-0003-2213-6155
dc.contributor.authorErsoy, Adem
dc.contributor.authorYunsel, Tayfun Yusuf
dc.contributor.authorAtici, Uemit
dc.date.accessioned2019-08-01T13:38:39Z
dc.date.available2019-08-01T13:38:39Z
dc.date.issued2008
dc.departmentNiğde ÖHÜ
dc.description.abstractAbandoned mine workings can undoubtedly cause varying degrees of contamination of soil with heavy metals such as lead and zinc has occurred on a global scale. Exposure to these elements may cause to harm human health and environment. In the study, a total of 269 soil samples were collected at 1, 5, and 10 m regular grid intervals of 100 X 100 m area of Carsington Pasture in the UK. Cell declustering technique was applied to the data set due to no statistical representativity. Directional experimental semivariograms of the elements for the transformed data showed that both geometric and zonal anisotropy exists in the data. The most evident spatial dependence structure of the continuity for the directional experimental semivariogram, characterized by spherical and exponential models of Pb and Zn were obtained. This study reports the spatial distribution and uncertainty of Pb and Zn concentrations in soil at the study site using a probabilistic approach. The approach was based on geostatistical sequential Gaussian simulation (SGS), which is used to yield a series of conditional images characterized by equally probable spatial distributions of the heavy elements concentrations across the area. Postprocessing of many simulations allowed the mapping of contaminated and uncontaminated areas, and provided a model for the uncertainty in the spatial distribution of element concentrations. Maps of the simulated Pb and Zn concentrations revealed the extent and severity of contamination. SGS was validated by statistics, histogram, variogram reproduction, and simulation errors. The maps of the elements might be used in the remediation studies, help decision-makers and others involved in the abandoned heavy metal mining site in the world. (C) 2008 Wiley Periodicals, Inc.
dc.identifier.doi10.1002/tox.20314
dc.identifier.endpage109
dc.identifier.issn1520-4081
dc.identifier.issue1
dc.identifier.pmid18214925
dc.identifier.scopus2-s2.0-39449094552
dc.identifier.scopusqualityQ2
dc.identifier.startpage96
dc.identifier.urihttps://dx.doi.org/10.1002/tox.20314
dc.identifier.urihttps://hdl.handle.net/11480/5278
dc.identifier.volume23
dc.identifier.wosWOS:000253183100012
dc.identifier.wosqualityQ1
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.indekslendigikaynakPubMed
dc.institutionauthor[0-Belirlenecek]
dc.language.isoen
dc.publisherWILEY-BLACKWELL
dc.relation.ispartofENVIRONMENTAL TOXICOLOGY
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/openAccess
dc.subjectgeostatistical simulation
dc.subjectcontaminated land assessment
dc.subjectabandoned mine
dc.subjectsite characterization
dc.subjectheavy metals
dc.subjectprobability map
dc.titleGeostatistical conditional simulation for the assessment of contaminated land by abandoned heavy metal mining
dc.typeArticle

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