Using particle dimensionality-based modeling to estimate lung carcinogenicity of 3D printer emissions.

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/m3 . The spline-based function of aerodynamic diameter allowed us to reconstruct the carcinogenic potential of seven types of fine and ultrafine particles (crystalline silica, fine TiO2 , ultrafine TiO2 , ambient PM2.5 and PM10, diesel particulates, and carbon nanotubes) with a correlation of 0.999, P < 0.00001. The central tendency estimation of lung cancer risk for 3D printer emissions was found at the level of 14.74 cases per 10,000 workers in a typical exposure scenario (average cumulative exposure of 0.3 mg/m3 - years), with the lowest risks for PLA filaments, and the highest for PETG type.

Additives influence 3D printer emission profiles: Implications for working safely with polymer filament composites.

It is critical to thoroughly investigate, characterize, and understand the unique emission profiles of common and novel polymer feedstocks used in fused filament fabrication (FFF) 3D printers as these products become increasingly ubiquitous in consumer and industrial environments. This work contributes unique insights regarding the effects of polymer composite feedstocks with metal, ceramic, or carbonaceous particle additives on particulate emissions in a variety of filaments under various print conditions, including print temperature. In addition to active characterization of particulate size and concentration following the ANSI/CAN/UL 2904 method, particulate sampling and subsequent analysis by scanning electron microscopy revealed agglomeration behavior that may have important health implications. Specifically, fine particles (0.3-2.5 µm) generated by certain filaments including acrylonitrile butadiene styrene (ABS) and glycol-modified poly(ethylene terephthalate) (PETG) are shown to be formed via agglomeration of emitted ultrafine particles rather than composed of coherent primary particles; accordingly, transport and behavior of these particulates after inhalation may not follow expected patterns for micrometer-sized particles. Structures resembling carbonaceous additives (e.g., graphene and nanotubes) were also captured by airborne sampling during printing of filaments containing carbonaceous advanced materials.

An Emergency Powered Air-Purifying Respirator From Local Materials and its Efficacy Against Aerosolized Nanoparticles.

We describe an approach used by a rural healthcare provider to convert surgical helmets into emergency powered air-purifying respirators (PAPRs) at the onset of the COVID-19 pandemic. The approach uses common materials and efficacy was demonstrated against aerosols measuring 7 nm to 25 µm in diameter.

Prevention through design: insights from computational fluid dynamics modeling to predict exposure to ultrafine particles from 3D printing.

Fused filament fabrication (FFF) 3D printers are increasingly used in industrial, academic, military, and residential sectors, yet their emissions and associated user exposure scenarios are not fully described. Characterization of potential user exposure and environmental releases requires robust investigation. During operation, common FFF 3D printers emit varying amounts of ultrafine particles (UFPs) depending upon feedstock material and operation procedures. Volatile organic compounds associated with these emissions exhibit distinct odors; however, the UFP portion is largely imperceptible by humans. This investigation presents straightforward computational modeling as well as experimental validation to provide actionable insights for the proactive design of lower exposure spaces where 3D printers may be used. Specifically, data suggest that forced clean airflows may create lower exposure spaces, and that computational modeling might be employed to predict these spaces with reasonable accuracy to assist with room design. The configuration and positioning of room air ventilation diffusers may be a key factor in identifying lower exposure spaces. A workflow of measuring emissions during a printing process in an ANSI/CAN/UL 2904 environmental chamber was used to provide data for computational fluid dynamics (CFD) modeling of a 6 m2 room. Measurements of the particle concentrations in a Class 1000 clean room of identical geometry were found to pass the Hanna test for agreement between model and experimental data, validating the findings.

Testing of Commercial Masks and Respirators and Cotton Mask Insert Materials using SARS-CoV-2 Virion-Sized Particulates: Comparison of Ideal Aerosol Filtration Efficiency versus Fitted Filtration Efficiency.

Shortages in the availability of personal protective face masks during the COVID-19 pandemic required many to fabricate masks and filter inserts from available materials. While the base filtration efficiency of a material is of primary importance when a perfect seal is possible, ideal fit is not likely to be achieved by the average person preparing to enter a public space or even a healthcare worker without fit-testing before each shift. Our findings suggest that parameters including permeability and pliability can play a strong role in the filtration efficiency of a mask fabricated with various filter media, and that the filtration efficiency of loosely fitting masks/respirators against ultrafine particulates can drop by more than 60% when worn compared to the ideal filtration efficiency of the base material. Further, a test method using SARS-CoV-2 virion-sized silica nanoaerosols is demonstrated to assess the filtration efficiency against nanoparticulates that follow air currents associated with mask leakage.