You are here:
GY SAMPLING THEORY IN ENVIRONMENTAL STUDIES 1: ASSESSING SOIL SPLITTING PROTOCOLS
Gerlach, R. W., J M. Nocerino, D. E. Dobb, AND G. A. Raab. GY SAMPLING THEORY IN ENVIRONMENTAL STUDIES 1: ASSESSING SOIL SPLITTING PROTOCOLS. JOURNAL OF CHEMOMETRICS 16(7):321-328, (2002).
The overall objective of the chemometrics and environmetrics program and this task is to examine and evaluate the statistical procedures and methods used in the measurement or experimentation process and to improve those procedures and methods (if deemed inadequate) by investigating, developing, and evaluating statistical methods, algorithms, and software to reduce data uncertainty. The measurement or experimentation process encompasses: decision objectives and design, sampling design, sampling, experimental design, quality control, data collection, signal processing and data manipulation, data analysis, validation, and decision analysis. Other general objectives of the program are to: evaluate certain existing, developed, or potential performance measurements for information content, relevancy, and cost-effectiveness. The objectives of the sampling research area are to provide the Agency with improved state-of-the-science guidance, strategies, and techniques to more accurately and effectively collect solid particulate field and laboratory subsamples that best represent the extent and degree of contamination at a given site.
Five soil sample splitting methods (riffle splitting, paper cone riffle splitting, fractional shoveling, coning and quartering, and grab sampling) were evaluated with synthetic samples to verify Pierre Gy sampling theory expectations. Individually prepared samples consisting of layers of sand, NaCl, and magnetite were left layered until splitting to simulate stratification from transport or density effects. Riffle splitting performed the best with approximate 99% confidence levels of less than 2%, followed by paper cone riffle splitting. Coning and quartering and fractional shoveling were associated with significantly higher variability, and also took much longer to perform. Common grab sampling was the poorest performer, with approximate 99% confidence levels of I00 to I5O% and biases of 15 to 20%. Method performance rankings were in qualitative agreement with expectations from Pierre Gy sampling theory. Precision results depended on the number of increments, the type of increment, and other factors influencing the probability of selecting a particle at random, and were all much higher than Pierre Gy's
fundamental error estimate of I%. A critical factor associated with good performance for these
methods is a low conditional probability of sampling adjacent particles. Accuracy levels were
dominated by the sampling process rather than by the analytical method. Sampling accuracy was at least two orders of magnitude worse than the accuracy of the analytical method.