- Evaluation of Geostatistical Approaches for better Estimation of Polluted Soil Volume with Uncertainty Evaluation
- Kim, Ho-Rim;Kim, Kyoung-Ho;Yun, Seong-Taek;Hwang, Sang-Il;Kim, Hyeong-Don;Lee, Gun-Taek;Kim, Young-Ju;
- KU-KIST Green School (Graduate School of Energy and Environment) and Department of Earth and Environmental Sciences, Korea University;KU-KIST Green School (Graduate School of Energy and Environment) and Department of Earth and Environmental Sciences, Korea University;KU-KIST Green School (Graduate School of Energy and Environment) and Department of Earth and Environmental Sciences, Korea University;Korea Environment Institute (KEI);National Instrumentation Center for Environmental Management College of Agriculture and Life Sciences, Seoul National University;National Instrumentation Center for Environmental Management College of Agriculture and Life Sciences, Seoul National University;Korea Environment Institute (KEI);
- 지구통계 기법을 활용한 토양 오염범위 산정 및 불확실성 평가
- 김호림;김경호;윤성택;황상일;김형돈;이군택;김영주;
- 고려대학교 그린스쿨대학원(KU-KIST) 및 지구환경과학과;고려대학교 그린스쿨대학원(KU-KIST) 및 지구환경과학과;고려대학교 그린스쿨대학원(KU-KIST) 및 지구환경과학과;한국환경정책.평가연구원;서울대학교 농생명과학공동기기원(NICEM);서울대학교 농생명과학공동기기원(NICEM);한국환경정책.평가연구원;
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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