期刊
GEOSTANDARDS AND GEOANALYTICAL RESEARCH
卷 40, 期 4, 页码 571-581出版社
WILEY
DOI: 10.1111/ggr.12121
关键词
measurement uncertainty; sampling theory; fitness-for-purpose; appropriate sampling; representative sampling
The 'Appropriate Sampling for Optimised Measurement' (ASOM) approach considers measurement to be the focus of the sampling process, and sampling to be only the first part of the measurement process. To achieve ASOM, the uncertainty of measurements, including its contribution from sampling, needs to be estimated and optimised in order to achieve fitness-for-purpose. Such samples are then 'sufficiently' representative. The 'Theory of Sampling' (TOS) focuses on the processes of primary sampling and sample preparation and assumes that samples are 'representative' if they are correctly prepared by nominally 'correct' protocols. It defines around ten sampling 'errors', which are either modelled or minimised to improve sampling quality. It is argued that the ASOM approach is more effective in achieving appropriate measurement quality than in applying TOS to just the first part of the measurement process. The comparison is made less effective by the different objectives, scopes, terminology and assumptions of the two approaches. ASOM can be applied to in situ materials that are too variable to be modelled accurately, or where sources of uncertainty are unsuspected. The proposed integration of ASOM with TOS (Esbensen and Wagner 2014, Trends in Analytical Chemistry, 57, 93-106) is therefore effectively impossible. However, some TOS procedures can be useful within the ASOM approach.
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