期刊
SCIENCE OF THE TOTAL ENVIRONMENT
卷 912, 期 -, 页码 -出版社
ELSEVIER
DOI: 10.1016/j.scitotenv.2023.168803
关键词
Bioaerosol transport; Computational fluid dynamics (CFD); Far-UVC disinfection; Airborne infectious diseases control; Fast computational model
This study developed a fast prediction approach based on the Markov chain model to optimize the installation locations of far-UVC lamps for enhancing the effectiveness of bioaerosol disinfection in indoor environments. Experimental results validated the accuracy of the proposed method and showed that optimizing the installation location significantly increased the disinfection efficiency.
Far-ultraviolet C (far-UVC) light is an effective and safe disinfection method for bioaerosol control in occupied indoor environments. The installation location of a far-UVC lamp strongly influences the spatial distribution of far-UVC irradiance, and thus the effectiveness of bioaerosol disinfection. To assist the design process, this study developed a fast prediction approach based on the Markov chain model for optimizing the installation locations of far-UVC lamps in order to enhance the disinfection effectiveness for indoor bioaerosol control. Experiments were conducted in an environmental chamber to validate the proposed simulation-based optimization approach. The results show that the proposed method can correctly predict the disinfection efficiency when compared with experimental data, and optimizing the installation location of the far-UVC lamp increased the disinfection efficiency by 54 % compared with the worst location. As an application, the validated method was then used to design the installation location of a far-UVC lamp in a real conference room. The results show that installing the far-UVC lamp in the optimal location can increase the disinfection efficiency by 48 % compared with the worst installation location. Therefore, optimizing the far-UVC lamp location using the proposed Markov chain model can enhance the effectiveness of bioaerosol disinfection in indoor environments.
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