Document type

Article

Version

Published version

Publication date

Publication license

cc-by (c) Miriello, Domenico et al., 2018
Please use this identifier to cite or link to this item: https://hdl.handle.net/2445/191337

Non-Destructive Multi-Analytical Approach to Study the Pigments of Wall Painting Fragments Reused in Mortars from the Archaeological Site of Pompeii (Italy)

Journal Title

Director/Tutor

Additional contribution

Journal ISSN

Volume Title

Abstract

During the excavations carried out in Via di Mercurio (Regio VI, 9, 3) in Pompeii, in 2015, some red, green, black, and brown wall painting fragments were found in the preparatory layer of an ancient pavement which was probably built after the 62 AD earthquake. These fragments, derived from the rubble, were used as coarse aggregate to prepare the mortar for building the pavement. The wall painting fragments are exceptionally well preserved, which is an uncommon occurrence in the city of Pompeii. However, as they were enclosed in the mortar, the wall painting fragments were protected from the high temperatures (probably ranging between 180 ◦C and 380 ◦C) produced by the eruption in 79 AD. The pigmented outer surface of each sample was analyzed using a non-destructive multi-analytical approach, by combining spectrophotometric colorimetry and portable X-ray fluorescence with micro-Raman spectroscopy. The compositional characterization of the samples revealed the presence of cuprorivaite, goethite, and celadonite in the green pigments; hematite in the red pigments; goethite in the brown pigment; and charcoal in the black pigment. These data probably provide us with the most "faithful picture" of the various red, green, black, and brown pigments used in Pompeii prior to the 79 AD eruption

Citation

Citation

MIRIELLO, Domenico, et al. Non-Destructive Multi-Analytical Approach to Study the Pigments of Wall Painting Fragments Reused in Mortars from the Archaeological Site of Pompeii (Italy). Minerals. 2018. Vol. 8, num. 4. ISSN 2075-163X. [consulted: 5 of October of 2026]. Available at: https://hdl.handle.net/2445/191337

Export metadata

JSON - METS

Share record