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http://dx.doi.org/10.7857/JSGE.2012.17.6.069

Evaluation of Geostatistical Approaches for better Estimation of Polluted Soil Volume with Uncertainty Evaluation  

Kim, Ho-Rim (KU-KIST Green School (Graduate School of Energy and Environment) and Department of Earth and Environmental Sciences, Korea University)
Kim, Kyoung-Ho (KU-KIST Green School (Graduate School of Energy and Environment) and Department of Earth and Environmental Sciences, Korea University)
Yun, Seong-Taek (KU-KIST Green School (Graduate School of Energy and Environment) and Department of Earth and Environmental Sciences, Korea University)
Hwang, Sang-Il (Korea Environment Institute (KEI))
Kim, Hyeong-Don (National Instrumentation Center for Environmental Management College of Agriculture and Life Sciences, Seoul National University)
Lee, Gun-Taek (National Instrumentation Center for Environmental Management College of Agriculture and Life Sciences, Seoul National University)
Kim, Young-Ju (Korea Environment Institute (KEI))
Publication Information
Journal of Soil and Groundwater Environment / v.17, no.6, 2012 , pp. 69-81 More about this Journal
Abstract
Diverse geostatistical tools such as kriging have been used to estimate the volume and spatial coverage of contaminated soil needed for remediation. However, many approaches frequently yield estimation errors, due to inherent geostatistical uncertainties. Such errors may yield over- or under-estimation of the amounts of polluted soils, which cause an over-estimation of remediation cost as well as an incomplete clean-up of a contaminated land. Therefore, it is very important to use a better estimation tool considering uncertainties arising from incomplete field investigation (i.e., contamination survey) and mathematical spatial estimation. In the current work, as better estimation tools we propose stochastic simulation approaches which allow the remediation volume to be assessed more accurately along with uncertainty estimation. To test the efficiency of proposed methods, heavy metals (esp., Pb) contaminated soil of a shooting range area was selected. In addition, we suggest a quantitative method to delineate the confident interval of estimated volume (and spatial extent) of polluted soil based on the spatial aspect of uncertainty. The methods proposed in this work can improve a better decision making on soil remediation.
Keywords
Remediation of polluted soils; Heavy metals; Geostatistical approaches; Estimation of spatial extent and volume of polluted soil; Uncertainty estimation;
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Times Cited By KSCI : 1  (Citation Analysis)
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