In this work, a detailed study of Monte Arci obsidian sub-sources using the increasingly accessible technique of pXRF is presented based upon a large dataset of 68 geological samples, for the development of X-ray fluorescence-based analytical standardless procedure. In addition, a non-conventional (for obsidian provenance study) direct application of multivariate analysis on XRF spectra (continuous variables), rather than absolute concentrations or intensity ratios (discrete variables) is proposed. Results from different softwares and data analysis approaches (bi-/trivariate multivariate) were compared. In a blind test, the bi-/trivariate approach led to the correct assignment for the main SA, SB, and SC sub-sources, taking into account averaged values of intensity ratios with their standard deviation obtained from three independent measurements. A high intra-source variability for the SB subgroups was detected (almost 13% of error in the assignment, 9 samples out of 68). A non-conventional application of multivariate analysis was carried out directly on the XRF spectra and correct assignments were obtained for SA, SB1, SC groups, while 71% of the SB2 samples were correctly identified. The non-destructive analysis on 14 archaeological samples from Su Carroppu (Carbonia, southwestern Sardinia) rockshelter and from the Middle Neolithic (MN) 422 structure of the open-air dwelling site at Cuccuru is Arrius (Cabras, central-western Sardinia) permitted to test the method and hypothesise their provenance. The comparison with visual characterization or previous analyses by Particle Induced X-Ray Emission (PIXE) permitted to verify the correct provenance assignment of all artifacts for the bi-/trivariate method, and for 12/14 samples in the case of the multivariate one. The standardless analytical approach proposed in this work can represent a more general method exploitable for other obsidian sources, other glassy materials, besides other materials of archaeological interest.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10006479PMC
http://dx.doi.org/10.1016/j.heliyon.2023.e13958DOI Listing

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