Abstract
Background: Occupational exposure to manufactured nanomaterials (MNMs) and its potential health impacts are of scientific and practical interest, as previous epidemiological studies associate exposure to nanoparticles with health effects, including increased morbidity of the respiratory and the circulatory system.
Objectives: To estimate the occupational exposure and effective internal doses in a real production facility of TiO2 MNMs during hypothetical scenarios of accidental release.
Methods: Commercial software for geometry and mesh generation, as well as fluid flow and particle dispersion calculation, were used to estimate occupational exposure to MNMs. The results were introduced to in-house software to calculate internal doses in the human respiratory tract by inhalation.
Results: Depending on the accidental scenario, different areas of the production facility were affected by the released MNMs, with a higher dose exposure among individuals closer to the particles source.
Conclusions: Granted that the study of the accidental release of particles can only be performed by chance, this numerical approach provides valuable information regarding occupational exposure and contributes to better protection of personnel. The methodology can be used to identify occupational settings where the exposure to MNMs would be high during accidents, providing insight to health and safety officials.
Original language | English |
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Pages (from-to) | 249-258 |
Number of pages | 10 |
Journal | International Journal of Occupational and Environmental Health |
Volume | 22 |
Issue number | 3 |
DOIs | |
Publication status | Published - 2 Jul 2016 |
Keywords
- Manufactured nanomaterials
- Particles dispersion
- CFD modeling
- Occupational exposure
- Internal doses
- Accidental release
Project and Funding Information
- Project ID
- info:eu-repo/grantAgreement/EC/FP7/280535/EU/Innovative strategies, methods and tools for occupational risks management of manufactured nanomaterials (MNMs) in the construction industry/SCAFFOLD
- Funding Info
- This work was supported by project SCAFFOLD [project_x000D_ number NMP4-SL-2012-280535] of the European_x000D_ Commission (FP7).