Читать книгу Global Approaches to Environmental Management on Military Training Ranges - Tracey Temple - Страница 43

Table 2.2 illustrates the effect that controlling for various error sources has on the root mean square (RMS) global estimation error (GEE) of the final estimation of the mean concentration of a contaminant in a DU. Sampling error obviously has the greatest effect on the GEE until the maximum feasible sampling error reduction is achieved, at which point sample preparation error begins to dominate. Error reduction effects are illustrated in figure 2.1. Note that there will always be error associated with every step of the characterization process, and that sampling error is likely to be the largest source, even when all steps of the process are controlled to the greatest extent feasible (figure 2.2). The exception is if no effort is put into reducing sample preparation error, which is unlikely in an ideal world as it is much easier to reduce this error than sampling error. The problem with this assumption is if the sample preparation is done separately from the sample collection, as often happens as different contractors typically handle these two processes. The effort put into minimizing sampling error should not be perceived as excessive, but sample preparation is also critical to achieving reproducible data.

Table 2.2. Effect of controlling for maximum error on global estimation error (GEE).

Case	Error Source	GEE	Error fromsampling
Sampling	Sample prep	Analytical
1	1000%	300%	20%	1044%	92%
2	1000%	300%	3%	1044%	92%
3	1000%	5%	20%	1000%	>99%
4	1000%	5%	3%	1000%	>99%
5	25%	300%	20%	302%	1%
6	25%	5%	20%	32%	61%
7	25%	5%	3%	26%	95%

Figure 2.1. Graphical representation of results for sample error reduction efforts.

Figure 2.2. Total error distribution when error sources are controlled to currently achievable levels. Global estimation error (GEE) is 26% (Case 7, table 2.2).