X-Ray Core Scanners as an Environmental Forensics Tool: A Case Study of Polluted Harbour Sediment (Augusta Bay, Sicily)

Abstract

A multivariate log-ratio calibration (MLC) model for XRF-core-scanning devices is presented, based on a combination of basic XRF-spectrometry theory and principles of compositional data analysis. The performance of the MLC model is evaluated in comparison with other empirical calibration procedures for XRF core scanner data using two data sets acquired with two different XRF core scanners. The quality of calibration models is assessed by calculating the uncertainties associated with predicted concentrations using cross-validation techniques. Results show that (1) the commonly used direct linear calibration (DLC) methods, which are based on the questionable assumption of a unique linear relation between intensities and con- centrations and do not acknowledge the compositional nature of the calibration prob- lem, give poor results; (2) the univariate log-ratio calibration (ULC) model, which is consistent with the compositional nature of the calibration problem but does not fully incorporate absorption and enhancement effects on intensities, and permits estimation of “relative” concentrations only, is markedly better, and (3) the MLC algorithm intro- duced in this contribution, which incorporates measurement uncertainties, accommo- dates absorption and enhancement effects on intensities, and exploits the covariance between and among intensities and concentrations, is the best by far. The predictive power of the MLC model may be further increased by employing automatic sample selection based on the multivariate geometry of intensity measurements in log-ratio space. The precision attained by MLC in conjunction with automatic sample selection is comparable to that attained by conventional XRF analysis of heterogenous materi- als under laboratory conditions. A solution to the long-standing problem of XRF core scanner calibration implies that high-resolution records of sediment composition with associated uncertainties can now be routinely established, which should increase the range of quantitative applications of XRF-core-scanning devices and strengthen infer- ences based on analysis of geochemical proxies.