Microplastics quantification in sewage sludge: A rapid and cost-effective approach
| dc.contributor.author | Santos López, Aurora | |
| dc.contributor.author | Cotillas Soriano, Salvador | |
| dc.contributor.author | Domínguez Torre, Carmen María | |
| dc.contributor.author | Pérez López, Alejandro | |
| dc.contributor.author | Navarro Úbeda, Mario | |
| dc.date.accessioned | 2025-10-27T09:12:34Z | |
| dc.date.available | 2025-10-27T09:12:34Z | |
| dc.date.issued | 2025-08-13 | |
| dc.description.abstract | The growing concern regarding microplastic (MP) accumulation in sewage sludge highlights the urgent need for practical, reliable and cost-effective quantification methods to support sludge valorization and environmental risk assessment. In this study, a novel image-based methodology that combines digital photography with opensource ImageJ analysis to estimate MP particle number and mass in complex sludge matrices is presented. The method was developed and validated using polyethylene terephthalate (PET) microplastics across multiple size ranges (0.15–5 mm), yielding strong area-to-mass correlations (R2 > 0.99) and high repeatability (CV < 3.2 %). It requires no specialized instrumentation or intensive sample preparation and enables rapid analysis (2–5 min per sample). The method’s robustness was confirmed through testing with different real-world sludge types, demonstrating consistent accuracy despite variations in matrix composition. While the approach is readily applicable to PET, its extension to other polymers may require specific calibration or correction models to account for differences in particle density, thickness, and three-dimensional morphology. Overall, this accessible and non-destructive tool is particularly well suited to support the development, optimization, and validation of microplastic separation technologies in sewage sludge treatment. | |
| dc.description.department | Depto. de Ingeniería Química y de Materiales | |
| dc.description.faculty | Fac. de Ciencias Químicas | |
| dc.description.refereed | TRUE | |
| dc.description.sponsorship | Ministerio de Ciencia, Innovación y Universidades | |
| dc.description.sponsorship | Agencia Estatal de Investigación | |
| dc.description.sponsorship | European Union NextGeneration | |
| dc.description.sponsorship | Comunidad de Madrid | |
| dc.description.status | pub | |
| dc.identifier.citation | Alejandro Pérez-López, Mario Navarro-Úbeda, Aurora Santos, Salvador Cotillas, Carmen M. Domínguez, Microplastics quantification in sewage sludge: A rapid and cost-effective approach, Journal of Environmental Chemical Engineering, Volume 13, Issue 5, 2025, 118554, ISSN 2213-3437, https://doi.org/10.1016/j.jece.2025.118554. (https://www.sciencedirect.com/science/article/pii/S2213343725032506) | |
| dc.identifier.doi | 10.1016/j.jece.2025.118554 | |
| dc.identifier.officialurl | https://doi.org/10.1016/j.jece.2025.118554 | |
| dc.identifier.relatedurl | https://www.sciencedirect.com/science/article/pii/S2213343725032506 | |
| dc.identifier.uri | https://hdl.handle.net/20.500.14352/125380 | |
| dc.issue.number | 118554 | |
| dc.journal.title | Journal of Environmental Chemical Engineering | |
| dc.language.iso | eng | |
| dc.publisher | Elsevier | |
| dc.relation.projectID | TED2021-131380A-C22 | |
| dc.relation.projectID | TEC-2024/ECO-69 | |
| dc.rights.accessRights | open access | |
| dc.subject.cdu | 54 | |
| dc.subject.keyword | Microplastics | |
| dc.subject.keyword | PET | |
| dc.subject.keyword | Emerging contaminants | |
| dc.subject.keyword | Sewage sludge | |
| dc.subject.keyword | Wastewater treatment | |
| dc.subject.keyword | Environmental monitoring | |
| dc.subject.keyword | Sludge valorization | |
| dc.subject.ucm | Química | |
| dc.subject.unesco | 23 Química | |
| dc.title | Microplastics quantification in sewage sludge: A rapid and cost-effective approach | |
| dc.type | journal article | |
| dc.type.hasVersion | VoR | |
| dc.volume.number | 13 | |
| dspace.entity.type | Publication | |
| relation.isAuthorOfPublication | c9d0900f-4c0e-4a20-867d-8103d0ac678a | |
| relation.isAuthorOfPublication | ed898263-c6e6-435b-b688-e2b115651b2b | |
| relation.isAuthorOfPublication | ed6e75ce-3c05-40f4-9238-3e4743fe1385 | |
| relation.isAuthorOfPublication.latestForDiscovery | c9d0900f-4c0e-4a20-867d-8103d0ac678a |
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