The first application of compositional data analysis (CoDA) in a multivariate perspective for detection of pollution source in sea sediments: the Pozzuoli Bay (Italy) case study

Year: 2021

Authors: Somma R.; Ebrahimi P.; Troise C.; De Natale G.; Guarino A.; Cicchella D.; Albanese S.

Autors Affiliation: INGV, Osservatorio Vesuviano, 80124 Naples, Italy CNR-IRISS, 80134 Naples, Italy Department of Earth, Environmental and Resources Sciences, University of Naples Federico II, 80126 Naples, Italy CNR-INO, 80078 Pozzuoli, Italy Department of Science and Technology, University of Sannio, 82100 Benevento, Italy

Abstract: In the last decades, investigating geochemistry of sea sediments has been challenging in the eastern sector of Pozzuoli Bay, source of the metal(loid)s has been a matter of debate and the proposed origin of potentially toxic elements (PTEs) has been occasionally inconsistent. In this study, compositional data analysis (CoDA) was used because the results are independent of the measurement unit, the selected subgroup of elements and the order of chemicals in the dataset. The robust variant of principal component analysis (PCA) indicated that Hg, Cd, Cu, Pb and Zn were positively correlated with mud and organic matter in the sediments deposited in front of the former industrial site. Concentrations of these metals decrease along the cores and in the distal zone. Nevertheless, Al, As, V, Fe, Cr, Ni and sand form an association along the coast which strengthens with increasing distance from fumaroles in the proximal zone. It suggests that arsenic was mainly originated from the pyroclastic deposits of Campi Flegrei and some of the seepages with hydrothermal component, supported by low contribution of variables in robust PCA of the sediments from distal zone. Therefore, this pioneering article suggests CoDA as a powerful tool for answering the long-lasting questions over sediment geochemistry in polluted areas.

Journal/Review: CHEMOSPHERE

Volume: 274      Pages from: 129955-1  to: 129955-15

More Information: This study was mainly supported by the ABBaCo project [grant number C62F16000170001] and partially supported by the PONS4E [grant number cod. SCN 00393] and PON-OT4CLIMA [grant number cod. ARS01 00405] projects, all funded by the Italian Ministry for Education, University and Research.
KeyWords: Campi Flegrei, Bagnoli industrial site, symmetric coordinates, isometric log-ratio, robust principal component analysis, fractal analysis
DOI: 10.1016/j.chemosphere.2021.129955