Calibrating high resolution XRF core scanner data to obtain absolute metal concentrations in highly polluted marine deposits after two case studies off Portmán Bay and Barcelona, Spain

M Cerdà-Domènech; J Frigola; A Sanchez-Vidal; M Canals

doi:10.1016/j.scitotenv.2019.134778

Calibrating high resolution XRF core scanner data to obtain absolute metal concentrations in highly polluted marine deposits after two case studies off Portmán Bay and Barcelona, Spain

Sci Total Environ. 2020 May 15:717:134778. doi: 10.1016/j.scitotenv.2019.134778. Epub 2019 Nov 5.

Authors

M Cerdà-Domènech¹, J Frigola², A Sanchez-Vidal¹, M Canals¹

Affiliations

¹ GRC Geociències Marines, Departament de Dinàmica de la Terra i de l'Oceà, Facultat de Ciències de la Terra, Universitat de Barcelona, Barcelona, Spain.
² GRC Geociències Marines, Departament de Dinàmica de la Terra i de l'Oceà, Facultat de Ciències de la Terra, Universitat de Barcelona, Barcelona, Spain. Electronic address: jfrigola@ub.edu.

PMID: 31843305
DOI: 10.1016/j.scitotenv.2019.134778

Abstract

X-ray fluorescence core scanners (XRF-CS) allow rapid, non-destructive, continuous and high-resolution analyses of the elemental composition of sediment cores, providing large sets of semi-quantitative data. These data can be converted to quantitative data through the linear regression approach using a relatively small number of discrete samples analyzed by techniques providing absolute concentrations. However, a precise characterization of the errors associated with the linear function is required to evaluate the quality of the calibrated element concentrations. Here we present a calibration of high-resolution XRF-CS for six metals (Ti, Mn, Fe, Zn, Pb and As) measured in heavily contaminated marine deposits so that absolute concentrations are obtained. In order to determine the best linear function for conversion of XRF data, we have tested three regression methods: the ordinary least-squares (OLS), which does not consider the standard error in any variable (x and y), the weighted ordinary least-squares (WOLS), which considers the weighted standard error of the vertical variable (y), and the weighted least-squares (WLS), which incorporates the standard error in both x and y variables. We demonstrate that the calibration method presented in this study significantly increases the correlation coefficient, higher than r² = 0.94, and reduces both the data deviation and the errors of the linear function for the three regression methods. Nonetheless, the WLS appears as the best regression method to minimize errors in the calibrated element concentrations. Our results open the door to use calibrated XRF-CS data to evaluate marine sediment pollution according to the levels of the strictest sediment quality guidelines (SQG) with errors lower than 0.4%-2% for Fe, 1%-7% for Zn, 3-14% for Pb and 5%-16% for Mn. They highlight the robustness of the calibration procedure here presented for accurate and precise quantification of element concentrations from XRF-CS semi-quantitative data.

Keywords: Calibration; Contaminated sediment; Sediment quality guidelines; Trace metals; XRF core scanner.