A mathematical model for predicting indoor PM2.5 concentration under different ventilation methods in residential buildings
Author(s): |
Wei Xie
Yuesheng Fan Xin Zhang Guoji Tian Pengfei Si |
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Medium: | journal article |
Language(s): | English |
Published in: | Building Services Engineering Research and Technology, October 2020, n. 6, v. 41 |
Page(s): | 694-708 |
DOI: | 10.1177/0143624420905102 |
Abstract: |
Experiments and theoretical analyses are conducted in a residential building in Changzhou to study indoor PM2.5concentrations by establishing a combined parameter model. An alternative method for predicting the particle deposition rate and penetration coefficient is proposed, and its accuracy is tested and verified by experiments using time-dependent concentrations and air exchange rate measurements. The predicted PM2.5penetration coefficient increased from 0.70 to 0.88 when the air exchange rates were varied from 0.2 h−1to 0.5 h−1. In addition, outdoor sources of PM2.5dominantly contributed approximately 90% to 98% to the indoor concentrations for both mechanically and naturally ventilated structures. Finally, a mathematical model for predicting the indoor concentration is presented using a mass balance equation, which estimates the parameter values in the building. The indoor PM2.5concentrations ranged from 40 to 46 µg/m³ by using a fresh air system with 82% filtration efficiency, while those by using open windows for natural ventilation ranged from 105 to 118 µg/m³ when the outdoor PM2.5concentration ranged from 115 to 137 µg/m³. The results of this study can be used to estimate the indoor particle level. Practical application: By applying the ventilation criteria for acceptable indoor air quality in ASHRAE Standard 62.1, the indoor PM2.5monitoring results show serious pollution in dwellings in 2018. More dwellings are expected to maintain a clean indoor environment in the future. Thus, it is crucial to consider the indoor PM2.5pollution risk in the building design to prevent the possible consequences of unsafe high indoor concentrations. The use of this prediction model, as discussed in this article, will provide further information on the influence of the particle deposition rate ( K) and penetration coefficient ( P) on indoor PM2.5concentrations. |
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data sheet - Reference-ID
10477091 - Published on:
18/11/2020 - Last updated on:
18/11/2020