New Approach to Geochemical Measurement: Estimation of Measurement Uncertainty from Sampling, rather than an Assumption of Representative Sampling

Abstract

It is argued that the current division between field sampling and chemical analysis is counterproductive in terms of ensuring that geochemical measurement results are fit for their intended purpose. An integrated approach to the whole measurement process has many advantages including no dependence on the two assumptions that either the samples are necessarily representative if taken with a correct protocol, or that the measurement results can be assumed to be true values of chemical concentration. The measurement results then require values of measurement uncertainty, including that from sampling as well as from chemical analysis. This enables the user of the measurement results, rather than the producer, to judge their fitness for a specific purpose. Case studies are used to illustrate the practicality and benefits of this new approach, including the use of measurement results with optimal, but relatively high, levels of uncertainty to make reliable decisions. This contrasts with the traditional assumption that pursuit of the lowest possible measurement uncertainty is the best approach.

A review of pXRF (field portable X-ray fluorescence) applications for applied geochemistry

“…Due to its low operating costs, denser data sets can be collected with pXRF, either by more closely spaced measurements, or by repeated measurements over time. This significantly reduces the sampling uncertainty issues related with the selection of small numbers of laboratory samples (Crume, 2000;Ramsey and Ellison, 2007;Ramsey and Boon, 2010).…”

Uncertainty Quantification in Geochemical Mapping: A Review and Recommendations

“…Sampling randomness is usually overlooked or underestimated, presuming that geochemical samples are necessarily representative if a “correct” sampling protocol is devised and implemented (Gy, 1992; Petersen et al., 2005). However, validating such representativeness is challenging, especially retrospectively, as it depends on various factors, including the sampling layout, methodology, sample density, and overall sample size (Ramsey & Boon, 2010; Ramsey & Thompson, 2007).…”

“…In the context of geochemical mapping, the sources of systemic uncertainty associated with the geochemical dispersion process and distribution patterns remain largely underexplored. In contrast, the sources of stochastic uncertainty, such as measurement inaccuracy and imprecision, inconsistent data coverage, and limited data resolution, have been relatively well‐recognized and investigated (e.g., Ramsey, 1998; Ramsey & Boon, 2010).…”

Appropriate Sampling for Optimised Measurement (ASOM), rather than the Theory of Sampling (TOS) Approach, to Ensure Suitable Measurement Quality: A Refutation of Esbensen and Wagner (2014)

“…In order to make reliable decisions that are based on measurement data, it is therefore essential to estimate and report the total measurement uncertainty, including uncertainty that arises from whatever sampling protocol has been used (Ramsey ). Appropriate sampling has been defined as ‘a sampling process in which the samples produced are sufficiently representative to make the measurement results fit for their intended purpose’ (Ramsey and Boon ). Such a measurement can usefully be described as an optimised measurement (OM), hence the overall acronym ASOM (Table for full listing).…”