Journal of Hazardous Materials, Journal Year: 2025, Volume and Issue: 494, P. 138508 - 138508
Published: May 8, 2025
Language: Английский
Journal of Hazardous Materials, Journal Year: 2025, Volume and Issue: 494, P. 138508 - 138508
Published: May 8, 2025
Language: Английский
Toxics, Journal Year: 2025, Volume and Issue: 13(2), P. 137 - 137
Published: Feb. 14, 2025
The evaluation of air pollution is a critical concern due to its potential severe impacts on human health. Currently, vast quantities data are collected at high frequencies, and researchers must navigate multiannual, multisite datasets trying identify possible pollutant sources while addressing the presence noise sparse missing data. To address this challenge, multivariate analysis widely used with an increasing interest in neural networks deep learning along well-established chemometrics methods receptor models. Here, we report combined approach involving Self-Organizing Map (SOM) algorithm, Hierarchical Clustering Analysis (HCA), Positive Matrix Factorization (PMF) disentangle single elaboration without previously separating sites years. proved be valid, allowing us detect site peculiarities terms sources, variation profiles during years outliers, affording reliable interpretation.
Language: Английский
Citations
0Marine Pollution Bulletin, Journal Year: 2025, Volume and Issue: 213, P. 117682 - 117682
Published: Feb. 17, 2025
Language: Английский
Citations
0Journal of Environmental Sciences, Journal Year: 2025, Volume and Issue: unknown
Published: March 1, 2025
Language: Английский
Citations
0Journal of Hazardous Materials, Journal Year: 2025, Volume and Issue: 494, P. 138508 - 138508
Published: May 8, 2025
Language: Английский
Citations
0