Estimation of measurement uncertainty arising from sampling

Foreword Uncertainty of measurement is the most important single parameter that describes the quality of measurements. This is because uncertainty fundamentally affects the decisions that can be made that are based upon the measurement value. Significant progress has been made in devising procedures to estimate the uncertainty that originates in the analytical portion of the measurement, and guidance on these procedures is available [1]. However, a measurement almost invariably involves the process of taking a sample. This is because it is usually impossible to analyse the entire bulk of the material to be characterised (the " sampling target "). If the objective of the measurement is to estimate the value of the analyte concentration in a sampling target, then the uncertainty associated with the sampling process must inevitably contribute to the uncertainty associated with the reported result. It has become increasingly apparent that sampling is often the most important contribution to uncertainty and requires equally careful management and control. The uncertainty arising from the sampling process must therefore be evaluated. While existing guidance identifies sampling as a possible contribution to the uncertainty in a result, procedures for estimating the resulting uncertainty are not well developed and further, specific, guidance is required. Historically, measurement scientists have been primarily concerned with measurements made within laboratories, and the process of sampling has been conducted by, and the responsibility of, different people who are often in separate organisations. The measurement scientist's knowledge of the sampling process is then very limited. Conversely, the advent of in situ analytical techniques has enabled the measurement scientist to make measurements at the sampling site and in contact with the material to be sampled. Examples of this situation are process analysis within industrial production, and in situ measurements on contaminated land. The placing of the analytical sensor in these situations then constitutes the taking of a sample, and the measurement scientist becomes not only aware of, but responsible for, all stages of the measurement process, including the sampling. An awareness of the whole process is important, irrespective of the division of effort. Since analytical and sampling processes contribute to the uncertainty in the result, the uncertainty can only be estimated if there is an understanding of the complete process. Further, optimisation of the relative effort in sampling and analysis is only possible where sampling and analytical processes are both understood. If the different stages are the responsibility of different …