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Research Article

Influence of nanofiber window screens on indoor PM2.5 of outdoor origin and ventilation rate: An experimental and modeling study

Tongling Xia1Ye Bian1,2Shanshan Shi3Li Zhang1Chun Chen1,4( )
Department of Mechanical and Automation Engineering, The Chinese University of Hong Kong, Shatin, N.T. 999077, Hong Kong, China
Department of Biomedical Engineering, The Chinese University of Hong Kong, Shatin, N.T. 999077, Hong Kong, China
School of Architecture and Urban Planning, Nanjing University, Nanjing 210093, China
Shenzhen Research Institute, The Chinese University of Hong Kong, Shenzhen 518057, China
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Abstract

When the outdoor PM2.5 pollution is severe, if the windows are open, the occupants tend to be exposed to higher indoor PM2.5 of outdoor origin. However, if the windows are closed, the ventilation rate tends to be insufficient for removing air pollutants generated indoors. Opening windows with the use of nanofiber window screens can be an alternative strategy that can balance between indoor PM2.5 of outdoor origin and ventilation rate. This study fabricated a number of nanofiber window screens and conducted a series of experiments in a laboratory setup to measure the PM2.5 removal efficiency and pressure drop with different window opening angles. A simple model was then developed for predicting the pressure drop, and the measured data was used to validate the model. Finally, the measured data and the validated model were used for two application cases. In the natural ventilation case, the use of nanofiber window screens can effectively reduce indoor PM2.5 of outdoor origin, and the ventilation rate can be improved when compared with infiltration in the house. However, the nanofiber window screens could not reduce the PM2.5 level in the kitchen with a range hood when the cooking PM2.5 emission rate was high.

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Building Simulation
Pages 873-886
Cite this article:
Xia T, Bian Y, Shi S, et al. Influence of nanofiber window screens on indoor PM2.5 of outdoor origin and ventilation rate: An experimental and modeling study. Building Simulation, 2020, 13(4): 873-886. https://doi.org/10.1007/s12273-020-0622-5

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Received: 17 September 2019
Accepted: 15 February 2020
Published: 05 March 2020
© Tsinghua University Press and Springer-Verlag GmbH Germany, part of Springer Nature 2020
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