title: [Spatial distribution prediction of surface soil Pb in a battery contaminated site].
abstract: In order to enhance the reliability of risk estimation and to improve the accuracy of pollution scope determination in a battery contaminated site with the soil characteristic pollutant Pb, four spatial interpolation models, including Combination Prediction Model (OK(LG) + TIN), kriging model (OK(BC)), Inverse Distance Weighting model (IDW), and Spline model were employed to compare their effects on the spatial distribution and pollution assessment of soil Pb. The results showed that Pb concentration varied significantly and the data was severely skewed. The variation coefficient of the site was higher in the local region. OK(LG) + TIN was found to be more accurate than the other three models in predicting the actual pollution situations of the contaminated site. The prediction accuracy of other models was lower, due to the effect of the principle of different models and datum feature. The interpolation results of OK(BC), IDW and Spline could not reflect the detailed characteristics of seriously contaminated areas, and were not suitable for mapping and spatial distribution prediction of soil Pb in this site. This study gives great contributions and provides useful references for defining the remediation boundary and making remediation decision of contaminated sites.
authors.forename: Geng
authors.initials: G
authors.lastname: Liu
authors.forename: Jun-Jie
authors.initials: JJ
authors.lastname: Niu
authors.forename: Chao
authors.initials: C
authors.lastname: Zhang
authors.forename: Xin
authors.initials: X
authors.lastname: Zhao
authors.forename: Guan-Lin
authors.initials: GL
authors.lastname: Guo
mesh_terms: D004784:Environmental Monitoring; D007854:Lead / Q000032:analysis*; D008962:Models, Theoretical; D015203:Reproducibility of Results; D012987:Soil / Q000737:chemistry*; D012989:Soil Pollutants / Q000032:analysis*; D062206:Spatial Analysis
chemical_list: D012987:Soil; D012989:Soil Pollutants; D007854:Lead