Influence of ventilation rate on the potential for indoor particulate matter exposure
File(s)
Published version (pre-proof)
Author(s)
Wood, Samuel GA
Handy, Alice EE
Burridge, Henry C
Type
Journal Article
Abstract
Increased ventilation is widely recommended for improving indoor air quality, yet ventilation can also act as a pathway for outdoor particulate matter to enter indoor spaces. We investigate the mechanisms and extent by which ventilation may increase the potential for particulate matter exposure using both physical and statistical modelling. The physical model explores the dynamics of an idealised room over differing exposure-durations, exploring the duration-averaged particulate matter concentration as an indicator of the potential for exposure. This indicates that whilst duration-averaged indoor concentrations exhibit a simple linear increase with increasing outdoor concentrations, increasing the ventilation rate can either increase or decrease the potential for exposure indoors. Moreover, the physical model identifies two conditions under which increased ventilation can reduce duration-averaged indoor PM
2.5: transient removal from initially elevated indoor concentrations, and cases where indoor sources dominate over ingress from outdoors. We further exploit the large-scale ‘SAMHE’ dataset of air quality measurements made in UK schools. Using generalised additive modelling regression, we show that outdoor particulate matter concentration is the strongest predictor of the potential for particulate matter exposure, although its interaction with ventilation reveals a more complex non-linear relationship. Over the two school years of data examined, the statistical modelling suggests that increasing ventilation by 5 L s
−1p−1 would, on average, increase daily mean indoor PM
2.5 by approximately 0.74 μgm−3, with around 99% of schools predicted to experience increases, particularly those with higher outdoor pollution and lower baseline ventilation. However, these predictions were sensitive to the ventilation rates being achieved and the outdoor particulate matter concentrations. While increases in the ventilation rates associated with these schools would likely result in relatively small increases in the particulate matter concentrations therein, the reverse would be expected for spaces with larger indoor sources such as homes, dependent upon outdoor conditions.
2.5: transient removal from initially elevated indoor concentrations, and cases where indoor sources dominate over ingress from outdoors. We further exploit the large-scale ‘SAMHE’ dataset of air quality measurements made in UK schools. Using generalised additive modelling regression, we show that outdoor particulate matter concentration is the strongest predictor of the potential for particulate matter exposure, although its interaction with ventilation reveals a more complex non-linear relationship. Over the two school years of data examined, the statistical modelling suggests that increasing ventilation by 5 L s
−1p−1 would, on average, increase daily mean indoor PM
2.5 by approximately 0.74 μgm−3, with around 99% of schools predicted to experience increases, particularly those with higher outdoor pollution and lower baseline ventilation. However, these predictions were sensitive to the ventilation rates being achieved and the outdoor particulate matter concentrations. While increases in the ventilation rates associated with these schools would likely result in relatively small increases in the particulate matter concentrations therein, the reverse would be expected for spaces with larger indoor sources such as homes, dependent upon outdoor conditions.
Date Issued
2026-08-31
Date Acceptance
2026-08-21
Citation
Indoor Environments, 2026
ISSN
2950-3620
Publisher
Elsevier BV
Journal / Book Title
Indoor Environments
Copyright Statement
©2026 Published by Elsevier Inc. on behalf of International Society of Indoor Air Quality and Climate. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Publication Status
Published online
Article Number
100191
Date Publish Online
2026-08-31