Estimation of Outdoor PM2.5 Infiltration into Multifamily Homes Depending on Building Characteristics Using Regression Models

The purpose of this study was to evaluate outdoor PM2.5 infiltration into multifamily homes according to the building characteristics using regression models. Field test results from 23 multifamily homes were analyzed to investigate the infiltration factor and building characteristics including floo...

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Bibliographic Details
Published in:Sustainability 2021-05, Vol.13 (10), p.5708
Main Authors: Park, Bo Ram, Eom, Ye Seul, Choi, Dong Hee, Kang, Dong Hwa
Format: Article
Language:English
Subjects:
Air flow
Air pollution
Airtightness
Buildings
Correlation analysis
Environmental conditions
Field tests
Housing
Investigations
Particulate matter
Regression analysis
Statistical analysis
Sustainability
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Summary:The purpose of this study was to evaluate outdoor PM2.5 infiltration into multifamily homes according to the building characteristics using regression models. Field test results from 23 multifamily homes were analyzed to investigate the infiltration factor and building characteristics including floor area, volume, outer surface area, building age, and airtightness. Correlation and regression analysis were then conducted to identify the building factor that is most strongly associated with the infiltration of outdoor PM2.5. The field tests revealed that the average PM2.5 infiltration factor was 0.71 (±0.19). The correlation analysis of the building characteristics and PM2.5 infiltration factor revealed that building airtightness metrics (ACH50, ELA/FA, and NL) had a statistically significant (p < 0.05) positive correlation (r = 0.70, 0.69, and 0.68, respectively) with the infiltration factor. Following the correlation analysis, a regression model for predicting PM2.5 infiltration based on the ACH50 airtightness index was proposed. The study confirmed that the outdoor-origin PM2.5 concentration in sufficiently leaky units could be up to 1.59 times higher than that in airtight units.
ISSN:2071-1050
2071-1050
DOI:10.3390/su13105708