| Full text | |
| Author(s): |
Ferreira, Anderson Targino da Silva
;
Oliveira, Regina Celia de
;
Siegle, Eduardo
;
Ribeiro, Maria Carolina Hernandez
;
Esteves, Luciana Slomp
;
Kuznetsova, Maria
;
Dipold, Jessica
;
Freitas, Anderson Zanardi de
;
Wetter, Niklaus Ursus
Total Authors: 9
|
| Document type: | Journal article |
| Source: | MICROPLASTICS; v. 4, n. 1, p. 21-pg., 2025-03-05. |
| Abstract | |
This study focuses on the deposition of microplastics (MPs) on urban beaches along the central S & atilde;o Paulo coastline, utilizing advanced methodologies such as remote sensing, GNSS altimetric surveys, mu -Raman spectroscopy, and machine learning (ML) models. MP concentrations ranged from 6 to 35 MPs/m2, with the highest densities observed near the Port of Santos, attributed to industrial and port activities. The predominant MP types identified were foams (48.7%), fragments (27.7%), and pellets (23.2%), while fibers were rare (0.4%). Beach slope and orientation were found to facilitate the concentration of MP deposition, particularly for foams and pellets. The study's ML models showed high predictive accuracy, with Random Forest and Gradient Boosting performing exceptionally well for specific MP categories (pellet, fragment, fiber, foam, and film). Polymer characterization revealed the prevalence of polyethylene, polypropylene, and polystyrene, reflecting sources such as disposable packaging and industrial raw materials. The findings emphasize the need for improved waste management and targeted urban beach cleanups, which currently fail to address smaller MPs effectively. This research highlights the critical role of combining in situ data with predictive models to understand MP dynamics in coastal environments. It provides actionable insights for mitigation strategies and contributes to global efforts aligned with the Sustainable Development Goals, particularly SDG 14, aimed at conserving marine ecosystems and reducing pollution. (AU) | |
| FAPESP's process: | 18/19240-5 - Multi-user equipment approved in grant 2017-50332-0: STM-AFM Raman SNOM analysis system |
| Grantee: | Anderson Zanardi de Freitas |
| Support Opportunities: | Multi-user Equipment Program |
| FAPESP's process: | 20/12050-6 - Microplastic's geochronology in coastal sediment: analysis based on optically stimulated luminescence (LOE), stable isotopes (13C), thermal analysis, and GNSS positioning |
| Grantee: | ANDERSON TARGINO DA SILVA FERREIRA |
| Support Opportunities: | Regular Research Grants |