2026-04-19T14:06:59Zhttps://riubu.ubu.es/oai/request

oai:riubu.ubu.es:10259/112512026-01-22T01:05:40Zcom_10259_4249com_10259_5086com_10259_2604col_10259_4250

Russo, Raffaele Emanuele 722dc949-ff32-40bb-988a-925fa951f670 600 Fattobene, Martina f835a7f3-495c-4ba6-9688-f5900a8d953c 600 Zamponi, Silvia 793fcac0-d3dd-4570-91b3-c42c2cb4f0a9 600 Conti, Paolo e90b56ef-f7ed-421d-94bf-00aaa236c41a 600 Herrero Gutiérrez, Ana 282 600 0000-0001-6126-1907 Berrettoni, Mario f27b4d89-3740-4e08-ab75-3e18b897073b 600 2026-01-21T07:44:48Z 2026-01-21T07:44:48Z 2026-01 https://hdl.handle.net/10259/11251 10.3390/molecules31020232 1420-3049 Environmental element monitoring is essential for assessing environmental quality, identifying pollution sources, evaluating ecological risks, and understanding long-term contamination trends. Modern monitoring campaigns routinely generate large volumes of complex data that require advanced analytical strategies. This study applied chemometric techniques to analyze elements and BVOCs (biogenic volatile organic compounds) measured from Posidonia oceanica and related environmental matrices (seawater, sediment, and rhizomes) during three sampling campaigns in the Tremiti Islands (Italy). Twenty-two trace elements were quantified, and BVOC profiles were obtained from the leaf samples. The dataset was analyzed using a combination of univariate visualizations, unsupervised and supervised multivariate techniques, and multi-way methods. PCA (Principal Component Analysis) and PLS-DA (Partial Least Squares-Discriminant Analysis) revealed distinct spatial (leaf section) and temporal (sampling period) trends, supported by consistent elemental markers. A low-level data fusion approach integrating BVOC and element data improved group discrimination and interpretability. PARAFAC (PARAllel FACtor analysis) applied to a three-way array successfully separated background trends from meaningful compositional changes, uncovering latent structures across chemical, spatial, and temporal dimensions. This work illustrates the usefulness of chemometrics in environmental monitoring and the effectiveness of combining multivariate tools and data fusion to improve the interpretability of complex environmental datasets. The methodology used in this study is fully generalizable and applicable to other environmental multi-way datasets. he PhD fellowship of M.F. was co-funded by PNRR resources from the European Union (Innovative PhD programs addressing the innovation needs of companies, CUP J11J22001830006) and by Ecotechsystems srl, Ancona (Marche, Italy). application/pdf eng MDPI Molecules. 2026, V. 31, n. 2, p. 232-252 https://doi.org/10.3390/molecules31020232 Atribución 4.0 Internacional http://creativecommons.org/licenses/by/4.0/ info:eu-repo/semantics/openAccess Environmental monitoring Elements BVOCs Posidonia oceanica Sediments Chemometrics N-way techniques PARAFAC Vigilancia ambiental Environmental monitoring Aguas marinas-Contaminación Marine pollution Exploring Environmental Element Monitoring Data Using Chemometric Techniques: A Practical Case Study from the Tremiti Islands (Italy) info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Molecules 31 2 232 252 THUMBNAIL Russo-molecules_2026.pdf.jpg Russo-molecules_2026.pdf.jpg IM Thumbnail image/jpeg 3239 https://riubu.ubu.es/bitstream/10259/11251/4/Russo-molecules_2026.pdf.jpg 37834acfca9d17c295d33199253834b7 MD5 4 LICENSE license.txt license.txt text/plain; charset=utf-8 998 https://riubu.ubu.es/bitstream/10259/11251/3/license.txt aa90105e1c90a1b4fe810649aa967b7d MD5 3 CC-LICENSE license_rdf license_rdf application/rdf+xml; charset=utf-8 908 https://riubu.ubu.es/bitstream/10259/11251/2/license_rdf 0175ea4a2d4caec4bbcc37e300941108 MD5 2 ORIGINAL Russo-molecules_2026.pdf Russo-molecules_2026.pdf application/pdf 3838363 https://riubu.ubu.es/bitstream/10259/11251/1/Russo-molecules_2026.pdf 82bf123ca9425e4277037926f0d08240 MD5 1 10259/11251 oai:riubu.ubu.es:10259/11251 2026-01-22 02:05:40.817 Repositorio Institucional de la Universidad de Burgos bubrep@ubu.es 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