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Optimum Allocation for Soil Contamination Investigations in Hsinchu, Taiwan, by Double Sampling
Author(s) -
Chang Ya-Chi,
Yeh Hund-Der
Publication year - 2007
Publication title -
soil science society of america journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.836
H-Index - 168
eISSN - 1435-0661
pISSN - 0361-5995
DOI - 10.2136/sssaj2006.0130
Subject(s) - sampling (signal processing) , contamination , soil test , mathematics , sample (material) , environmental science , chemistry , analytical chemistry (journal) , soil water , soil science , environmental chemistry , physics , chromatography , ecology , biology , detector , optics
The double sampling (DS) scheme is a cost‐effective sampling method that combines an expensive measurement procedure with an inexpensive but less accurate one. Double sampling works when the true correlation of determination (ρ 2 ) between two techniques is known in advance, but that is hardly ever the case. By assuming a ρ 2 < 0.9, a three‐stage procedure (TSP) in DS selects a preliminary pool of samples and estimates ρ 2 , from which the optimal allocation of samples is determined. There may be excessive and unnecessary sampling during a TSP when ρ 2 > 0.9. The main objective of this study was to extend the TSP and determine the optimum allocation of the samples under a fixed budget condition for the case ρ 2 > 0.9. A soil from Hsinchu, Taiwan, contaminated with heavy metals Zn, Cu, Pb, Ni, Cr, and Cd was sampled at 0.15, 0.3, 0.45, and 0.6 m deep at 36 sites (144 samples). All samples were analyzed with field‐portable x‐ray fluorescence and a subset of 40 samples was selected for analyses of Zn, Cu, and Pb with standard methods in the laboratory. Results from both measurements were linearly correlated with estimated ρ 2 values of 0.96, 0.95, and 0.97 for Zn, Cu, and Pb, respectively. Considering a ρ 2 = 0.99, the optimum subsample and sample sizes were 5 out of 167, 4 out of 173, and 5 out of 167 for Zn, Cu, and Pb, respectively. The extended TSP analyses reduced the number of superfluous samples to only two or three, which was less than obtained by TSP (9–16).

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