Short courses
Representative sampling – the critical success-factor for geo-science analysis
Presented by
Kim H. Esbensen, research professor
Geological Survey of Denmark and Greenland
Aalborg University, campus Esbjerg, Denmark
Telemark University College, Porsgrunn, Norway
The Total Sampling Error (TSE) is by far the dominating contribution to analytical error budgets, typically 10-25-50 times larger than the Total Analytical Error (TAE), depending on material heterogeneity. The critical determinant for reliable analysis is therefore that sampling is representative in the entire chain: field-to-laboratory. The Theory of Sampling (TOS) provides a comprehensive description of all errors involved in sampling of heterogeneous processes, products and materials as well as all necessary tools for their evaluation, elimination or minimization. A set of ten Sampling Unit Operations (SUOs) cover all practical aspects of sampling and provides a practical toolbox for geo-science samplers, engineers, laboratory and scientific personnel. After the critical primary sampling step, only unbiased laboratory mass reduction procedures (sub-sampling, splitting and sample preparation procedures) will ensure a representative, and therefore reliable, analytical result. TOS provides a unique definition of the concept of "sampling correctness" and of the Fundamental Sampling Principle (FSP), as attributes of the sampling process (it is not possible to ascertain whether a specific sample is representative or not by inspection of the sample alone). It is essential to induct some level of TOS competence into the scientific, engineering, analytical and technological professions in order to secure the necessary reliability of: samples (- representative, from primary sampling throughout the laboratory), analysis (- does not mean anything outside the miniscule analytical volume without documented representativity) as well as subsequent data analysis ("data" do not exist in isolation of their provenance). TOS also contains a complete coverage of process sampling, which has important consequences for Process Analytical Technologies (PAT).
It is occasionally claimed that Measurement Uncertainty (MU) covers all determinants for reliable analysis – this is unfortunately not correct. This short course introduces all principles and procedures for representative sampling, which includes the relationship between measurement Uncertainty (MU) and TOS. Participants will acquire professional first order competence regarding representative sampling under all conditions. Course documentation/literature include (additional literature may be added on the course):
(1) Petersen, L, Minkkinen, P. & Kim H. Esbensen (2005). Representative Sampling: Theory of Sampling. Chemometrics and intelligent laboratory systems, vol. 77, issue 1-2, p. 261-277
(2) Petersen, L, C. Dahl, K.H. Esbensen (2004). Representative mass reduction in sampling – a critical survey of techniques and hardware. in Special Issue: 50 years of Pierre Gy's Theory of Sampling. Proceedings: First World Conference on Sampling and Blending (WCSB1). Esbensen & Minkkinen (Eds). Chemometrics and Intelligent Laboratory Systems, vol. 74, Issue 1, p. 95-114
(3) Petersen L. & K. H. Esbensen (2005). Representative Process Sampling – a Tutorial. Journal of Chemometrics, vol. 19, Issue 11-12. p. 625-647
(4) Esbensen, K.H, H.H.Friis-Petersen, L. Petersen, J.B. Holm-Nielsen & P.P.Mortensen (2006). Representative process sampling – in practise: Variographic analysis and estimation of Total Sampling Errors (TSE). Proceedings 5.th Winter Symposium of Chemometrics (WSC-5), Samara 2006. Chemometrics and Intelligent Laboratory Systems, Special Issue, vol. 88, No.1, 41-49 (2007).
(5) Esbensen, K.H. & Mortensen, P. (2010). Process Sampling (Theory of Sampling, TOS) – the Missing Link in Process Analytical Technology (PAT). in Bakeev, K. A. (Ed.) Process Analytical Technology. 2. Edition. Blackwell Publishing.
(6) Esbensen, K.H. & Julius, L.P. (2009). Representative sampling, data quality, validation – a necessary trinity in chemometrics. in Brown, S, Tauler, R, Walczak,R (Eds.) ComprehensiveChemometrics, Wiley Major Reference Works, vol. 4, pp.1-20. Oxford: Elsevier
