Article ; Online: Dry Heat as a Potential Decontamination Method on the Filtration Efficiency of Filtering Facepiece Respirators
International Journal of Environmental Research and Public Health, Vol 19, Iss 7167, p
2022 Volume 7167
Abstract: Filtering facepiece respirators have been widely used in the fields of occupational health and public hygiene, especially during the COVID-19 pandemic. In particular, disposable respirators have been in high demand, and the waste generated from these ... ...
| Abstract | Filtering facepiece respirators have been widely used in the fields of occupational health and public hygiene, especially during the COVID-19 pandemic. In particular, disposable respirators have been in high demand, and the waste generated from these disposable products poses a problem for the environment. Here, we aimed to test a practical decontamination method to allow for the reuse of KN95 respirators. In this study, three types of KN95 respirators were heated at 80 °C and 90 °C for different durations (15 min, 30 min, 45 min, 1 h, 2 h, 3 h, 4 h, 6 h, 8 h, 10 h, and 24 h). The filtration efficiencies of the tested KN95 respirators before and after heating were measured, and the changes in microstructure were imaged with a scanning electron microscope (SEM). In addition, a neural network model based on the nonlinear autoregressive with external input (NARX) to predict the filtration efficiency of the KN95 respirator was established. The results show that the temperature and time of dry heating affected particle prevention. The higher the temperature and the longer the heating time, the more obvious the decline in the filtration efficiency of the respirators. When the heating temperature reached 100 °C, the respirator may be no longer suitable for reuse. These results show that a dry heat temperature between 70 °C and 90 °C, and a heating time between 30 min and 2 h is assumed to be a suitable and effective decontamination method for respirators. |
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| Keywords | filtering facepiece respirators ; heat treatment ; filtration efficiency ; neural network ; Medicine ; R |
| Subject code | 620 |
| Language | English |
| Publishing date | 2022-06-01T00:00:00Z |
| Publisher | MDPI AG |
| Document type | Article ; Online |
| Database | BASE - Bielefeld Academic Search Engine (life sciences selection) |
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