TY - JOUR
T1 - Optimization of gasification process parameters for COVID-19 medical masks using response surface methodology
AU - Chalermsinsuwan, Benjapon
AU - Li, Yueh Heng
AU - Manatura, Kanit
N1 - Funding Information:
This research was supported by a grant from the Kasetsart University Research and Development Institute (KURDI), Bangkok Thailand (R-M 21.61) and the Faculty of Engineering at Kamphaeng Saen, Kasetsart University, Thailand.
Publisher Copyright:
© 2022 THE AUTHORS
PY - 2023/1
Y1 - 2023/1
N2 - Due to the COVID-19 pandemic, large amounts of medical wastes have been produced and their disposal has resulted in environmental and human health problems. This medical waste may include face masks, gloves, face shields, goggles, coverall suits, and other related wastes, such as hand sanitizer and disinfectant containers. To address this issue, the effect was investigated of gasification process parameters (type of COVID-19 medical mask based on the polypropylene ratio, pressure, steam ratio, and temperature) on hydrogen syngas and cold gas efficiency. The gasification model was developed using process modeling based on the Aspen Plus software. Response surface methodology with a 3k statistical factorial design was used to optimize the process aiming for the highest hydrogen yield and cold gas efficiency. Analysis of variance showed that both the steam ratio and temperature were significant parameters regarding the hydrogen yield and cold gas efficiency. Proposed models were constructed with very high accuracy based on their coefficient of determination (R2) values being greater than 0.97. The optimum conditions were: 65 % polypropylene in the mixture, a pressure of 1 bar, a steam ratio of 0.38, and a temperature of 900 °C, producing a maximum hydrogen yield of 40.61 % and cold gas efficiency of 81.43 %. These results supported the efficacy of the primary design for steam gasification using a mixture of plastic wastes as feedstock. The hydrogen could be utilized in chemical applications, whereas the efficiency could be used as a basis for further development of the process.
AB - Due to the COVID-19 pandemic, large amounts of medical wastes have been produced and their disposal has resulted in environmental and human health problems. This medical waste may include face masks, gloves, face shields, goggles, coverall suits, and other related wastes, such as hand sanitizer and disinfectant containers. To address this issue, the effect was investigated of gasification process parameters (type of COVID-19 medical mask based on the polypropylene ratio, pressure, steam ratio, and temperature) on hydrogen syngas and cold gas efficiency. The gasification model was developed using process modeling based on the Aspen Plus software. Response surface methodology with a 3k statistical factorial design was used to optimize the process aiming for the highest hydrogen yield and cold gas efficiency. Analysis of variance showed that both the steam ratio and temperature were significant parameters regarding the hydrogen yield and cold gas efficiency. Proposed models were constructed with very high accuracy based on their coefficient of determination (R2) values being greater than 0.97. The optimum conditions were: 65 % polypropylene in the mixture, a pressure of 1 bar, a steam ratio of 0.38, and a temperature of 900 °C, producing a maximum hydrogen yield of 40.61 % and cold gas efficiency of 81.43 %. These results supported the efficacy of the primary design for steam gasification using a mixture of plastic wastes as feedstock. The hydrogen could be utilized in chemical applications, whereas the efficiency could be used as a basis for further development of the process.
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U2 - 10.1016/j.aej.2022.07.037
DO - 10.1016/j.aej.2022.07.037
M3 - Article
AN - SCOPUS:85135146346
SN - 1110-0168
VL - 62
SP - 335
EP - 347
JO - AEJ - Alexandria Engineering Journal
JF - AEJ - Alexandria Engineering Journal
ER -