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Gloves and Dermal Exposure to Chemicals
Published in Robert N. Phalen, Howard I. Maibach, Protective Gloves for Occupational Use, 2023
Stoffenmanager was originally developed as a simple tool to help small companies manage chemical exposure in specific workplaces using a risk (control) banding approach. The basic version of the software tool is available free online (www.stoffenmanager.nl). The tool is designed to use categorical estimates of exposure (in categories from 1 for “negligible” to 6 for “extreme”) and hazard (in categories from A for “low” to E for “extreme”) to provide the final outcome as one of three risk categories, from “low” to “high.” There is no explicit account taken of wearing protective gloves, although the user can choose whether to exclude covered parts of the body, e.g., the hands. This tool has not been validated for dermal exposure assessment.
A harmonized protocol for an international multicenter prospective study of nanotechnology workers: the NanoExplore cohort
Published in Nanotoxicology, 2023
Irina Guseva Canu, Ekaterina Plys, Camille Velarde Crézé, Carlos Fito, Nancy B. Hopf, Athena Progiou, Chiara Riganti, Jean-Jacques Sauvain, Giulia Squillacioti, Guillaume Suarez, Pascal Wild, Enrico Bergamaschi
Importantly, the apparently small minimum sample size of this cohort with 120–160 workers actually corresponds to one of the largest studies of workers exposed to ENMs in the world. For instance, the unique cohort study of ENM workers (the EpiNano cohort) launched in 2012 in France, has included 130 workers so far (Guseva Canu et al. 2016c) while the future US National Institute for Occupational Safety and Health (US-NIOSH) cohort of carbon nanotube and nanofiber workers had 108 participants at baseline (Beard et al. 2018). The Taiwanese national panel study currently includes 206 exposed and 108 unexposed workers recruited at 14 different ENMs producing plants (Wu et al. 2019). It is noteworthy that in the US-NIOSH study, a personal exposure monitoring has been conducted while in the French cohort, the exposure is assessed only qualitatively since the (semi)quantitative exposure assessment has been discontinued (Renaudie et al. 2018). In the Taiwanese study, the exposure is assessed using control banding despite its high bias potential (Guseva Canu, Burstyn, and Richardson 2016b). The assessment of airborne exposure to ENMs based on aerosol sampling analysis should be considered as the minimal requirement pondering between the study feasibility in different occupational settings and the scientific value of its results. Whenever possible, it should be completed with a more thorough individual exposure assessment.
Assessing the risk of main activities of nanotechnology companies by the NanoTool method
Published in International Journal of Occupational Safety and Ergonomics, 2021
Soqrat Omari Shekaftik, Azadeh Ashtarinezhad, Farshad H. Shirazi, AghaFatemeh Hosseini, Rasoul Yarahmadi
Control banding (CB) is one of the most useful qualitative approaches for risk assessment of nanomaterials [14,17,22–24]. CB uses groups or ‘bands’ of health hazards in combination with exposure scenarios or exposure potential to determine optimal controls [25,26]. The tendency toward CB for assessing the risk of activities involving nanomaterials has arisen because of the uncertainties about the data required for risk assessment. These uncertainties greatly diminish the possibility of application of occupational health's traditional approach in risk assessment of activities involving nanomaterials [15]. The use of CB for activities involving nanomaterials was first proposed by Andrew Maynard [17]. After a year, Paik et al. [14] proposed the NanoTool method for prioritizing and managing risks in nanomaterial research environments; afterward, its adapted version (version 2.0) was released by Zalk et al. [24]. After successful use of the NanoTool method in research environments and workplaces, other methods such as Stoffenmanager Nano, NanoSafer, ANSES (French Agency for Environmental and Occupational Health Safety), Precautionary Matrix and Guidance have been released based on the CB approach [27]. Based on the aforementioned, the purpose of this study was to assess the risk of activities involving nanomaterials in nanotechnology companies in Tehran.
Lipid peroxidation metabolites associated with biomarkers of inflammation and oxidation stress in workers handling carbon nanotubes and metal oxide nanoparticles
Published in Nanotoxicology, 2021
Wei-Te Wu, Wei-Ting Jung, Hui-Ling Lee
As part of earlier studies, we conducted extensive exposure characterization in these plants, which included the generation of area-exposure maps in different departments, as well as number concentration, particle size distribution, and mass concentration over a wide range of particle sizes (10–1000 nm) measured by a scanning mobility particle sizer (SMPS) (TSI Inc., MN, USA). However, detailed exposure assessment and chemical analysis for each individual in the field was difficult to perform. Thus, this study used the control banding nanotool risk level matrix proposed by Dr. Paik and colleagues (Liao et al. 2014b; Wu et al. 2014b) to categorize the risk level of each participant as a surrogate marker of exposure. Examples of detailed calculations of severity score, probability score, and risk level have been previously described (Liao et al. 2014b; Wu et al. 2014b). An example elaborated detailed calculation of severity score, probability score and risk level was shown in Supplementary Appendix 2. Briefly, the risk level matrix was calculated based on the probability scores of the exposure and the severity scores of the nanomaterial toxicity. The factors of exposure probability score were based on the questionnaires collected from individual worker exposed to the various nanomaterials. The detailed information of questionnaire used in this study was listed in Supplementary Appendix 1. The cross-table of the severity score (band) and probability score (band) was used to generate the risk levels (1–4) for each individual (Supplementary Appendix 1). The higher the risk levels, the higher the risk of health hazards.