Composite vs. discrete soil sampling in assessing soil pollution of agricultural sites affected by solid waste disposal
Abstract The choice of an appropriate sampling scheme is a crucial step in the process of soil pollution assessment and risk management. In agricultural systems, where soil is mixed by ploughing, the bulking of discrete samples to obtain composite samples improves soil sampling precision, unless strong concentration gradients exist. In this case, the compositing may significantly underestimate the risk posed by the contaminants. In this paper, the degree and spatial variability of soil pollution by potentially toxic elements in three agricultural sites, subjected to unauthorized waste disposal, were assessed applying a soil sampling scheme based on a two level grid resolution. On the first level, a regular low resolution 10 x 10 m grid was defined. On the second level, each grid was subdivided into nine high resolution 3.33 x 3.33 m subplots. Discrete soil samples were taken from each 3.33 x 3.33 m plot. Composite soil samples were made bulking aliquots from the discrete soil samples. Soil samples were collected at 0 30 and 30 60 cm depths to evaluate vertical variations. When statistical analyses were applied to composite data and various pollution indices were calculated, only one site appeared to be slightly polluted by Cu and Zn, with mean contents of 131 and 95 mg kg 1 and peaks of 275 and 174 mg kg 1. When the same analysis and indices were applied to discrete soil data a much worse scenario emerged. The slightly polluted site became highly polluted by Cu (mean and max of 276 and 1707 mg kg 1) and Zn (174 and 972 mg kg 1) and slightly polluted by Sb and As (max of 15 and 30 mg kg 1) Plots classified as unpolluted on the basis of composite data revealed metals above legal limits. Pollution always interested both the 0 30 and 30 60 cm depth soil samples, with the deeper samples showing only in few cases higher values than the surface samples. The adopted two level soil sampling scheme succeeded to show dishomogeneity in soil pollutant spatial distribution, with pollution hot spots emerging only when sampling was done at a very short spatial scale.