Estimating and Optimising Analytical and Sampling Uncertainty in Environmental Investigations: Application and Evaluation

Abstract

Measurements taken to characterise environmental contamination contain uncertainty, which is generated by both field sampling and chemical analyses. Recently devised techniques have been applied for the first time to estimate this uncertainty in the commercial monitoring and assessment of contaminated land. The uncertainty reduces the reliability of the classification of the land that is made following a site investigation. The possible misclassification of areas of land, as a result of measurement uncertainty, can lead to substantial financial penalties, resulting from litigation or unnecessary remediation. Previous studies have developed methods for the estimation and financial optimisation of measurement uncertainty. These methods have now been applied to a series of six contrasting site investigations, which were conducted by various commercial organisations. The previous uses of these sites included a gas works, a tin mine and railway sidings. The measurement uncertainty was successfully estimated for each of the six investigations, showing its applicability to a wide range of different sampling methods, such as trial pits, window sampling and augering. The measurement uncertainty ranged widely between sites from 25% to 158%, indicating that investigations can differ widely in their reliability. The field sampling tended to generate the largest component of the measurement uncertainty when compared to the contribution from the chemical analysis. The Optimised Contaminated Land Investigation (OCLI) method was applied to each site, with the initial aim of estimating the financial losses that could be incurred as a result of misclassifying the land, due to the uncertainty. It showed that the expectation of loss value per sampling location ranged from only £58 at one site to over £ 11 000 at another. The optimal level of uncertainty that produced the minimal financial loss was then calculated for each site. It provided a reduction in the expectation of loss for the whole site of over £ 10 000 at two of the sites and over £90 000 at two others. These findings demonstrate that implementing concepts of uncertainty can have practical benefits in environmental monitoring, and can enable improvements to be made in the quality of sampling and hence of measurements in general.

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