Monitoring of Particulate Matter Emissions from 3D Printing Activity in the Home Setting

Real-Time Exposure to 3D-Printing Emissions Elicits Metabolic and Pro-Inflammatory Responses in Human Airway Epithelial Cells

Three-dimensional (3D) printer usage in household and school settings has raised health concerns regarding chemical and particle emission exposures during operation. Although the composition of 3D printer emissions varies depending on printer settings and materials, little is known about the impact that emissions from different filament types may have on respiratory health and underlying cellular mechanisms. In this study, we used an in vitro exposure chamber system to deliver emissions from two popular 3D-printing filament types, acrylonitrile butadiene styrene (ABS) and polylactic acid (PLA), directly to human small airway epithelial cells (SAEC) cultured in an air-liquid interface during 3D printer operation. Using a scanning mobility particle sizer (SMPS) and an optical particle sizer (OPS), we monitored 3D printer particulate matter (PM) emissions in terms of their particle size distribution, concentrations, and calculated deposited doses. Elemental composition of ABS and PLA emissions was assessed using scanning electron microscopy coupled with energy dispersive X-ray spectroscopy (SEM-EDX). Finally, we compared the effects of emission exposure on cell viability, inflammation, and metabolism in SAEC. Our results reveal that, although ABS filaments emitted a higher total concentration of particles and PLA filaments emitted a higher concentration of smaller particles, SAEC were exposed to similar deposited doses of particles for each filament type. Conversely, ABS and PLA emissions had distinct elemental compositions, which were likely responsible for differential effects on SAEC viability, oxidative stress, release of inflammatory mediators, and changes in cellular metabolism. Specifically, while ABS- and PLA-emitted particles both reduced cellular viability and total glutathione levels in SAEC, ABS emissions had a significantly greater effect on glutathione relative to PLA emissions. Additionally, pro-inflammatory cytokines including IL-1β, MMP-9, and RANTES were significantly increased due to ABS emissions exposure. While IL-6 and IL-8 were stimulated in both exposure scenarios, VEGF was exclusively increased due to PLA emissions exposures. Notably, ABS emissions induced metabolic perturbation on amino acids and energy metabolism, as well as redox-regulated pathways including arginine, methionine, cysteine, and vitamin B3 metabolism, whereas PLA emissions exposures caused fatty acid and carnitine dysregulation. Taken together, these results advance our mechanistic understanding of 3D-printer-emissions-induced respiratory toxicity and highlight the role that filament emission properties may play in mediating different respiratory outcomes.

Characterization of Volatile and Particulate Emissions from Desktop 3D Printers

The rapid expansion of 3D printing technologies has led to increased utilization in various industries and has also become pervasive in the home environment. Although the benefits are well acknowledged, concerns have arisen regarding potential health and safety hazards associated with emissions of volatile organic compounds (VOCs) and particulates during the 3D printing process. The home environment is particularly hazardous given the lack of health and safety awareness of the typical home user. This study aims to assess the safety aspects of 3D printing of PLA and ABS filaments by investigating emissions of VOCs and particulates, characterizing their chemical and physical profiles, and evaluating potential health risks. Gas chromatography-mass spectrometry (GC-MS) was employed to profile VOC emissions, while a particle analyzer (WIBS) was used to quantify and characterize particulate emissions. Our research highlights that 3D printing processes release a wide range of VOCs, including straight and branched alkanes, benzenes, and aldehydes. Emission profiles depend on filament type but also, importantly, the brand of filament. The size, shape, and fluorescent characteristics of particle emissions were characterized for PLA-based printing emissions and found to vary depending on the filament employed. This is the first 3D printing study employing WIBS for particulate characterization, and distinct sizes and shape profiles that differ from other ambient WIBS studies were observed. The findings emphasize the importance of implementing safety measures in all 3D printing environments, including the home, such as improved ventilation, thermoplastic material, and brand selection. Additionally, our research highlights the need for further regulatory guidelines to ensure the safe use of 3D printing technologies, particularly in the home setting.

Identification of effective control technologies for additive manufacturing

Additive manufacturing (AM) refers to several types of processes that join materials to build objects, often layer-by-layer, from a computer-aided design file. Many AM processes release potentially hazardous particles and gases during printing and associated tasks. There is limited understanding of the efficacy of controls including elimination, substitution, administrative, and personal protective technologies to reduce or remove emissions, which is an impediment to implementation of risk mitigation strategies. The Medline, Embase, Environmental Science Collection, CINAHL, Scopus, and Web of Science databases and other resources were used to identify 42 articles that met the inclusion criteria for this review. Key findings were as follows: 1) engineering controls for material extrusion-type fused filament fabrication (FFF) 3-D printers and material jetting printers that included local exhaust ventilation generally exhibited higher efficacy to decrease particle and gas levels compared with isolation alone, and 2) engineering controls for particle emissions from FFF 3-D printers displayed higher efficacy for ultrafine particles compared with fine particles and in test chambers compared with real-world settings. Critical knowledge gaps identified included a need for data: 1) on efficacy of controls for all AM process types, 2) better understanding approaches to control particles over a range of sizes and gas-phase emissions, 3) obtained using a standardized collection approach to facilitate inter-comparison of study results, 4) approaches that go beyond the inhalation exposure pathway to include controls to minimize dermal exposures, and 5) to evaluate not just the engineering tier, but also the prevention-through-design and other tiers of the hierarchy of controls.