DETERMINING THE OPTIMAL CLEAN-UP UNIT FOR CONTAMINATED SOIL BASED ON DISPERSION VARIANCE

摘要

The spatial distribution of a pollutant in contaminated soil is usually highly skewed. Therefore, in practice, it is necessary that the entire contaminated site is subdivided into smaller clean-up blocks for selective remediation. An observed value of pollutant concentration, measured as the average over a certain soil volume, is called the sample support. However, the scale of sample support is usually much smaller than the unit for clean-up. In addition, there is not sampling support in some subdivided clean-up blocks. Thus the dispersion variances representing the variation of pollutant concentration within or between clean-up blocks should be taken into account for assessing the uncertainty of estimation of pollutant concentration in clean-up blocks when setting up a remediation plan. Since the dispersion variance varies with the size of subdivided clean-up blocks, how to determine the optimum size of clean-up blocks in order to reduce the estimation variance of pollutant concentrations in the entire contaminated site is important for applying separate clean-up actions on each clean-up blocks. In this study, an approach of calculating dispersion variances according to the Krige's additivity relationship was proposed and an uncertainty function representing the average value of estimation variances for the pollutant concentration of entire contaminated site was established. The value of the uncertainty function was proposed as a criterion to determine the proper block size for clean-up plan. The subdivided block size corresponding to the minimum value of the uncertainty function was selected as the optimal clean-up units for the contaminated site. A real data set of heavy metal concentrations in a contaminated site located in Taiwan was employed for illustrating this proposed approach.