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Inicio  /  Urban Science  /  Vol: 5 Par: 1 (2021)  /  Artículo
ARTÍCULO
TITULO

Effects of Neighboring Units on the Estimation of Particle Penetration Factor in a Modeled Indoor Environment

Yonghang Lai    
Ian A. Ridley and Peter Brimblecombe    

Resumen

Ingress of air from neighboring apartments is an important source of fine particulate matter (PM2.5) in residential multi-story buildings. It affects the measurement and estimation of particle deposition rate and penetration factor. A blower-door method to measure the particle deposition rate and penetration factor has previously been found to be more precise than the traditional decay-rebound method as it reduces variability of PM2.5 ingress from outside. CONTAM is a multi-zone indoor air quality and ventilation analysis computer program to aid the prediction of indoor air quality. It was used in this study to model the indoor PM2.5 concentrations in an apartment under varying PM2.5 emission from neighboring apartments and window opening and closing regimes. The variation of indoor PM2.5 concentration was also modeled for different days to account for typical outdoor variations. The calibrated CONTAM model aimed to simulate environments found during measurement of particle penetration factor, thus identifying the source of error in the estimates. Results show that during simulated measurement of particle penetration factors using the blower-door method for three-hour periods under a constant 4 Pa pressure difference, the indoor PM2.5 concentration increases significantly due to PM2.5 generated from adjacent apartments, having the potential to cause an error of more than 20% in the estimated value of particle penetration factor. The error tends to be lower if the measuring time is extended. Simulated measurement of the decay-rebound method showed that more PM2.5 can penetrate inside if the PM2.5 was generated from apartments below under naturally variable weather conditions. A multiple blower-door fan can be used to reduce the effects of neighboring emission and increase the precision of the penetration estimates.

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