Experimental study of environmental factors affecting particle infiltration in buildings

被引:0
|
作者
Qiu, Jiayi [1 ]
Liu, Yilin [1 ]
Luo, Xilian [1 ]
Jin, Liwen [1 ]
机构
[1] Xi An Jiao Tong Univ, Sch Human Settlements & Civil Engn, Xian 710049, Shaanxi, Peoples R China
来源
基金
中国博士后科学基金; 中国国家自然科学基金;
关键词
Particle infiltration; Indoor air quality; Relative humidity; Particle size distribution; Hygroscopicity and coagulation; FINE PARTICULATE MATTER; OUTDOOR RELATIONSHIPS; AEROSOL-PARTICLES; INDOOR; SIZE; PENETRATION; NUMBER; DEPOSITION; HOMES;
D O I
10.1016/j.jobe.2025.112408
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
Ambient particles infiltrate indoor environments through cracks in the building envelope, deteriorating indoor air quality and posing risks to human health. This study investigates the factors influencing particle infiltration in controlled laboratory settings, utilizing an orthogonal experimental design. The effects of outdoor particle concentration (Cout), crack structure factor (q), indoor temperature (Tin), and indoor relative humidity (RHin) on indoor particle concentration (Cin) and infiltration factor (Finf) are quantified using multivariate regression analysis. Particle mass and number concentrations were measured in sixteen experimental scenarios to characterize infiltration behavior and particle size distribution. Results demonstrate that Cin increases predominantly with Cout, such that a 1 mu g m-3 increase in Cout leads to a 0.382 mu g m-3 increase in Cin, assuming all other factors remain constant. Regression modeling identifies optimal conditions for Cin at Cout = 50 mu g m-3, RHin = 30 %, and U-shaped cracks. Meanwhile, Finf rises with q and RHin but decreases with increasing Tin, achieving its minimum at RHin = 30 %, Tin = 30 degrees C, and Ushaped cracks. Size-resolved analysis shows infiltration peaks for 0.4-0.5 mu m particles at RHin = 90 %, suggesting that particles smaller than 0.5 mu m undergo hygroscopic growth and coagulate into this range. By incorporating temperature and humidity variables, this study establishes predictive models for particle infiltration, providing actionable strategies for optimizing indoor air quality management while balancing energy efficiency. These findings advance the understanding of particle infiltration in buildings and inform the formulation of targeted design codes.
引用
收藏
页数:17
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