The world of nanotechnology remains one of the most dynamic and innovative sectors today. As companies continue to harness the unique properties of nanomaterials to enhance products across a plethora of industries, ensuring the safety of workers who handle these substances has become paramount. A recent study published in NanoImpact has introduced a novel approach that significantly improves the prediction and management of occupational exposures to nanomaterials.
The study conducted by Carla C. Ribalta and her colleagues at The National Research Center for Work Environment (NRCWE) and associated institutions, outlines an advanced modelling technique that combines the Dustiness Index (DI) and a derived Handling Energy factor (H), offering occupational hygienists a robust tool for workplace exposure assessment.
In this extensive review, we will delve into the implications of this research, shedding light on how the combined use of DI and H factors could revolutionize the management of nanomaterial exposures in occupational settings.
The research paper, titled “Use of the dustiness index in combination with the handling energy factor for exposure modelling of nanomaterials,” presents insights from modelling occupational exposure concentrations in 13 different case scenarios.
Researchers utilized a two-box model along with three nano-specific tools – Stoffenmanager Nano, NanoSafer, and GUIDEnano – to simulate workplace exposure conditions. The main goal was to assess whether incorporating the handling energy factor could enhance the prediction accuracy of exposure levels when handling nanomaterial powders.
The study’s findings were telling. By incorporating quartile-3 H factors derived from real-world handling scenarios, the researchers observed a significant improvement in modelling outcomes:
1. When using the derived H factors, Pearson correlations increased from 0.52 to 0.88, highlighting a substantial boost in the predictability of actual exposure concentrations.
2. The ratio of modelled to measured concentrations fell between 0.9 to 10 in 75% of cases, compared to only 16.7% when H factors were not integrated into the models.
However, it was also noted that particle number concentrations were typically underpredicted, suggesting that the conservative use of H values could still lead to underestimation of potential exposures.
Implications for Occupational Safety
This novel approach addresses a critical limitation in current exposure modelling – the accurate characterization of emission sources during powder handling of nanomaterials. By improving exposure prediction, occupational hygienists can refine risk assessments, tailor protective measures more precisely, and ensure regulatory compliance. Moreover, it helps in aligning workplace safety practices with the rapid advancements in nanotechnology.
The conventional methods used for exposure assessment have long grappled with the unpredictability of nanomaterial behaviors. With the introduction of the handling energy factor, this research signifies a leap forward in our ability to ascertain and mitigate risks associated with nanomaterials in the workplace.
The study also raises important questions about the extensibility of these findings to other nanomaterial handling scenarios and encourages further research to validate and enhance the two-box model and the nano-specific tools.
Considering the rapid evolution of nanotechnology, continuous updates to safety protocols and modelling techniques are necessary to protect workers from potential health risks. This research represents a crucial step towards achieving that objective.
The article explicitly notes that all rights reserved by Elsevier B.V., and it details affiliations and potential conflicts of interest among the researchers involved.
The integration of the dustiness index with a handling energy factor has been demonstrated to considerably enhance the accuracy of occupational exposure predictions to nanomaterials. This methodological breakthrough ushered in by Ribalta and her team provides critical insights that can transform exposure modelling and management practices for nanomaterials in workplaces worldwide.
As the nanotechnology industry continues to expand, vigorously enforcing and constantly improving safety measures is indispensable. Studies like this one lay the groundwork for safer, more controlled environments, benefiting not just the workforce but the industry as a whole.
Keywords
1. Nanomaterials exposure modelling
2. Workplace safety nanotechnology
3. Dustiness index nanomaterials
4. Occupational hygiene nanomaterials
5. Handling energy factor nanoparticles
References
Ribalta, Carla C., Jensen, Alexander C. Ø., Shandilya, Neeraj, Delpivo, Camilla, Jensen, Keld A., and Fonseca, Ana Sofia. (2024). Use of the dustiness index in combination with the handling energy factor for exposure modelling of nanomaterials. NanoImpact, 33, 100493.
DOI: 10.1016/j.impact.2024.100493
Five References:
1. Maynard, A. D., & Kuempel, E. D. (2005). Airborne nanostructured particles and occupational health. Journal of Nanoparticle Research, 7(6), 587–614.
2. Asbach, C., Alexander, C., Clavaguera, S., Dahmann, D., Dozol, H., Faure, B., Fissan, H., Jiménez, A. S., Kaminski, H., Monz, C., & Mülhopt, S. (2017). Review of measurement techniques and methods for assessing personal exposure to airborne nanomaterials in workplaces. Science of the Total Environment, 603, 793–806.
3. Brouwer, D. (2010). Exposure to manufactured nanoparticles in different workplaces. Toxicology, 269(2-3), 120–127.
4. Schneider, T., Brouwer, D. H., Koponen, I. K., Jensen, K. A., Fransman, W., Van Duuren-Stuurman, B., Kromhout, H., & Tielemans, E. (2011). Conceptual model for assessment of inhalation exposure to manufactured nanoparticles. Journal of Exposure Science & Environmental Epidemiology, 21(5), 450–463.
5. Eastlake, A., Beaucham, C., Martinez, K. F., Dahm, M. M., Sparks, C., Hodson, L. L., & Geraci, C. L. (2016). Refinement of the nanoparticle emission assessment technique into the nanomaterial exposure assessment technique (NEAT 2.0). Journal of Occupational and Environmental Hygiene, 13(9), 708–717.