Using indicator kriging to delineate and map the spatial patterns of zinc soil pollution

Mapping heavy metal pollution in soil is essential for environmental monitoring. Kriging is often used to characterize the spatial variability of heavy metal. However, due to its smooth effects, it is incapable of detecting the uncertainty of estimates. In this study, the indicator kriging was used to map the uncertainty of the estimate, and to provide the probability of pollution risk. Eight hundred and thirty nine samples were analyzed, according to the accumulating pollution index and the background value. Three thresholds which classified Zn pollution risk into safe, low, moderate and high levels were adopted. The result showed that there is high Zn content in the soil of the study area. Its mean reached 86.7 mg/kg, larger than the background value (80.3 mg/kg), which mainly resulted from the nearby Zn mine. The probability map indicated that the pollution risk were chiefly low and moderate levels, and the closer the distance to Zn mine, the greater the probability values.

[1]  A. Journel.  Nonparametric estimation of spatial distributions , 1983 .

[2]  R. Lark,et al.  Geostatistics for Environmental Scientists , 2001 .

[3]  Michael Edward Hohn,et al.  An Introduction to Applied Geostatistics: by Edward H. Isaaks and R. Mohan Srivastava, 1989, Oxford University Press, New York, 561 p., ISBN 0-19-505012-6, ISBN 0-19-505013-4 (paperback), $55.00 cloth, $35.00 paper (US) , 1991 .

[4]  B. Devkotaa,et al.  Accumulation of heavy metals in food plants and grasshoppers from the Taigetos Mountains , Greece , 2000 .

[5]  Freek D. van der Meer,et al.  Indicator kriging applied to absorption band analysis in hyperspectral imagery: A case study from the Rodalquilar epithermal gold mining area, SE Spain , 2006 .

[6]  Yunfeng Xie,et al.  Spatial distribution of soil heavy metal pollution estimated by different interpolation methods: accuracy and uncertainty analysis. , 2011, Chemosphere.

[7]  H. Wackernagle,et al.  Multivariate geostatistics: an introduction with applications , 1998 .

[8]  Lorentz Jäntschi,et al.  Analysis of Soil Heavy Metal Pollution and Pattern in Central Transylvania , 2008, International journal of molecular sciences.

[9]  E. Paoletti,et al.  Adaptation of forest ecosystems to air pollution and climate change: a global assessment on research priorities , 2011 .

[10]  Pierre Goovaerts,et al.  Evaluating the probability of exceeding a site-specific soil cadmium contamination threshold , 2001 .

[11]  P. K. Govil,et al.  Assessment of heavy metal contamination in soils at Jajmau (Kanpur) and Unnao industrial areas of the Ganga Plain, Uttar Pradesh, India. , 2010, Journal of hazardous materials.

[12]  B. Gorte,et al.  Probabilistic image classification using geological map units applied to land-cover change detection , 2000 .

[13]  R. Olea.  Geostatistics for Natural Resources Evaluation By Pierre Goovaerts, Oxford University Press, Applied Geostatistics Series, 1997, 483 p., hardcover, $65 (U.S.), ISBN 0-19-511538-4 , 1999 .

[14]  Clayton V. Deutsch,et al.  GSLIB: Geostatistical Software Library and User's Guide , 1993 .

[15]  K. T. Klasson,et al.  Influence of pyrolysis temperature on biochar property and function as a heavy metal sorbent in soil. , 2011, Journal of agricultural and food chemistry.

[16]  Alireza Mesdaghinia,et al.  Effect of fertilizer application on soil heavy metal concentration , 2010, Environmental monitoring and assessment.

[17]  A. C. S. Costa,et al.  Assessment of trace metals contamination in estuarine sediments using a sequential extraction technique and principal component analysis , 2010 .