Gasification Characteristics of Disposable COVID-19 Masks Using a Bubbling Fluidized Bed: Effect of Gasifying Agents

COVID-19 and mutated viruses have increased global demand for masks, resulting in 490,000 tons of trash masks every month. Waste masks include a virus infection risk and are difficult to recycle due to their multi-component polymer and iron composition. Conventional treatment methods, such as landfilling and incineration, can emit environmental pollutants and cause respiratory diseases. Gasification is a reasonable method for treating multi-component polymers and producing syngas for a variety of applications. The gasification characteristics of disposable COVID-19 masks using a 1kg/h laboratory-scale bubbling fluidized bed gasifier were determined in this study. The experimental operating temperature was set to 1073 K, the fuel feeding rate was set to 6.95 x 10^-5 kg/s, and the minimum fluidization ratio (U_mf/U_g) was set to be 2.5. The characteristics of the waste mask thermochemical conversion process and the influence of activated carbon were investigated depending on the presence or absence of a gasifying agent and the type of gasifying agent (air, steam, carbon dioxide, oxygen/steam). The hydrogen production yield shows maximum under pure oxygen/steam gasification conditions in the presence of activated carbon, and the H₂/CO molar ratio was highest in steam gasification condition. The maximum product gas production was obtained by air gasification, while carbon dioxide gasification was shown to be effective in reducing tar. In the most optimal hydrogen production condition, the gas composition is H₂ 33.4 vol%, CO 13.1 vol%, CH₄ 16.0 vol%, CO₂ 19.1 vol%, and hydrocarbon (C₂-C₃) 18.4 vol%. Activated carbon had the highest tar reduction efficiency of 91%, while CO₂ had the highest tar reduction efficiency of 49% among gasifying agents. These results provided the design parameter for waste mask gasification process, and the product gas can be used as feedstock for chemicals and fuels in the near future.