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https://hdl.handle.net/10216/165093| Author(s): | Moreno-Martín, V López, M Bou, D Fraga, S Teixeira, JP López-Lilao, A Sanfélix, V Monfort, E Viana, M |
| Title: | Incidental nanoparticle characterisation in industrial settings to support risk assessment modelling |
| Publisher: | Elsevier |
| Issue Date: | 2025 |
| Abstract: | Research on nanoparticle (NP) release and potential exposure can be assessed through experimental field campaigns, laboratory simulations, and prediction models. However, risk assessment models are typically designed for manufactured NP (MNP) and have not been adapted for incidental NP (INP) properties. A notable research gap is identifying NP sources and their chemical, physical, and toxicological properties, especially in real-world settings. This work aims to provide insights into the release and physico-chemical properties of INP while contributing to improving models for INP release. INP release was evaluated through a case study in a ceramic tile firing facility, where aerosol (10 nm - 10 μm) properties were determined. The Control Banding (CB) Nanotool model was applied to test outputs based on provided input parameters. Results: demonstrate the constant generation and release of INP during tile firing, with NP concentrations up to 68711/cm³ and mean diameters of 37 nm, with 95% smaller than 100 nm. Particle morphology was mostly spherical, suggesting nucleation from precursor gases as the main formation mechanism. INP chemical composition was driven by primary ceramic components, while trace elements like Ni and Ti exhibited size-dependent patterns. In vitro cell viability tests indicated low to medium cytotoxicity of PM2 aerosols, decreasing human alveolar epithelial cell viability in a concentration-dependent manner. Applying the risk model with varying input parameters revealed that the risk level (RL) based on severity scores decreased when aerosol size distribution data were used, illustrating the model's sensitivity to input variables. We conclude on the need for comprehensive experimental datasets to support risk assessment models and achieve effective risk management strategies in real-world scenarios. © 2025 |
| DOI: | 10.1016/j.ijheh.2025.114523 |
| URI: | https://hdl.handle.net/10216/165093 |
| Source: | Int J Hyg Environ Health. 2025 Mar:264:114523. doi: 10.1016/j.ijheh.2025.114523. Epub 2025 Jan 25. |
| Related Information: | info:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB/04750/2020/PT info:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/LA/P/0064/2020/PT |
| Document Type: | Artigo em Revista Científica Internacional |
| Rights: | restrictedAccess |
| Appears in Collections: | ISPUP - Artigo em Revista Científica Internacional |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| morenomartin2025.pdf Restricted Access | 3.62 MB | Adobe PDF | View/Open |
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