Using particle dimensionality-based modeling to estimate lung carcinogenicity of 3D printer emissions.
3D printers
QSAR modeling
additive manufacturing
lung cancer
ultrafine particles
Journal
Journal of applied toxicology : JAT
ISSN: 1099-1263
Titre abrégé: J Appl Toxicol
Pays: England
ID NLM: 8109495
Informations de publication
Date de publication:
Apr 2024
Apr 2024
Historique:
revised:
18
10
2023
received:
01
09
2023
accepted:
19
10
2023
pubmed:
11
11
2023
medline:
11
11
2023
entrez:
11
11
2023
Statut:
ppublish
Résumé
The use of 3D printing technologies by industry and consumers is expanding. However, the approaches to assess the risk of lung carcinogenesis from the emissions of 3D printers have not yet been developed. The objective of the study was to demonstrate a methodology for modeling lung cancer risk related to specific exposure levels as derived from an experimental study of 3D printer emissions for various types of filaments (ABS, PLA, and PETG). The emissions of 15 filaments were assessed at varying extrusion temperatures for a total of 23 conditions in a Class 1,000 cleanroom following procedures described by ANSI/CAN/UL 2904. Three approaches were utilized for cancer risk estimation: (a) calculation based on PM2.5 and PM10 concentrations, (b) a proximity assessment based on the pulmonary deposition fraction, and (c) modeling based on the mass-weighted aerodynamic diameter of particles. The combined distribution of emitted particles had the mass median aerodynamic diameter (MMAD) of 0.35 μm, GSD 2.25. The average concentration of PM2.5 was 25.21 μg/m
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
564-581Subventions
Organisme : National Institute of Environmental Health Sciences of the National Institutes of Health
ID : R44ES030650
Organisme : USACE Engineer Research and Development Center Environmental Laboratory
ID : W912HZ21C0061
Organisme : Virginia Tech National Center for Earth and Environmental Nanotechnology Infrastructure (NanoEarth)
Organisme : National Science Foundation (NSF)
ID : ECCS 2025151
Organisme : National Science Foundation (NSF)
ID : ECCS 1542100
Informations de copyright
© 2023 John Wiley & Sons Ltd.
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