Efficient search procedures for extreme pollutant values

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Abstract
Extreme pollutant values are of great interest in water quality monitoring because of their frequent toxicological significance. The principal barrier to the detection of these values, however, is the cost of extensive and comprehensive monitoring. This paper demonstrates an efficient method to determine the maximum sample measurement from a finite set of sequential samples without explicitly testing them all. It is assumed that the process of sample measurement is distinct from collection and has higher costs. It is further assumed that the measurements have high positive autocorrelation. A methodology is presented based on a common industrial testing procedure referred to as composite sampling—the physical pooling or compositing of a set of sequential samples before measurement. A method known as primary first order compositing (PFOC) was found to be superior to the traditional technique of random sampling, particularly if small composite sizes are utilized.

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