Assessment of soil heavy metal pollution using stochastic site indicators

Improving the understanding and characterization of spatial soil heavy metal distribution is becoming an important component of risk assessment and environmental policy. In this work, 213 soil samples collected from Daye (Hubei Province, China) were used as the empirical dataset. First, maps of soil heavy metal distributions, including Cd, Co, Cr, Cu, Mn, Ni, Pb and Zn, were obtained using the ordinary Kriging method. Then, the pollution index (PI) and integrated pollution index (IPI) were calculated based on the ordinary Kriging maps to obtain a comprehensive quantitative pollution characterization of the eight heavy metals in the Daye soil. The results showed that 46.1%, 32.1%, and 0.5% of the soil in the study region are moderately, highly and extremely polluted, respectively. Finally, the one- and two-point stochastic site indicators of WI were used to assess quantitatively the uncertainties and risks associated with soil heavy metal distributions in the polluted regions. These results showed that the NI values exceeding a specified threshold increased almost linearly with increasing threshold value, whereas the relative area of excess pollution decreased steadily with increasing threshold. Among the site pairs considered in the study region, about 70% and 26% of them simultaneously experienced moderate and high pollution risk, respectively.