Improving the measurement of air change rates using the decay method: Quantifying the uncertainty of the well-mixed assumption and identifying the required sampling locations

Improving building ventilation has emerged as a vital imperative in today’s post-Covid-19 era, while accurately estimating air change rates continues to present a considerable challenge. For more than fifty years, the decay method has been employed for this purpose, assuming the well-mixed condition that rarely occurs. However, existing mixing models (e.g., K or Ez) are limited in addressing this gap since their reported data are subjective and inconsistent across different standards (ASHRAE and AIHA). Therefore, we developed a novel modified decay method that includes two proposed factors: the uniformity index (Ui) and the sampling factor (Sf). These two factors help to quantify the well-mixed assumption’s uncertainty and identify the minimum required sampling locations for tracer measurements. The modified decay method is tested in a classroom, measuring the spatial variations of CO2 using automated data acquisition. The proposed method significantly reduced the error caused by the well-mixing assumption of estimated air change rates from 26% to 3%. The sampling locations are identified as a function of the zone’s geometry. The findings of this study can be used to improve the ventilation performance of buildings.

Publication Details

Journal
Springer Link (Chiba Institute of Technology)
Published
2025-12-05
DOI
https://doi.org/10.1051/e3sconf/202567207038/pdf
Primary Topic
Building Energy and Comfort Optimization
Type
article
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article

Improving the measurement of air change rates using the decay method: Quantifying the uncertainty of the well-mixed assumption and identifying the required sampling locations

Springer Link (Chiba Institute of Technology)
Building Energy and Comfort Optimization
article

Improving the measurement of air change rates using the decay method: Quantifying the uncertainty of the well-mixed assumption and identifying the required sampling locations

article en

Abstract

Improving building ventilation has emerged as a vital imperative in today’s post-Covid-19 era, while accurately estimating air change rates continues to present a considerable challenge. For more than fifty years, the decay method has been employed for this purpose, assuming the well-mixed condition that rarely occurs. However, existing mixing models (e.g., K or Ez) are limited in addressing this gap since their reported data are subjective and inconsistent across different standards (ASHRAE and AIHA). Therefore, we developed a novel modified decay method that includes two proposed factors: the uniformity index (Ui) and the sampling factor (Sf). These two factors help to quantify the well-mixed assumption’s uncertainty and identify the minimum required sampling locations for tracer measurements. The modified decay method is tested in a classroom, measuring the spatial variations of CO2 using automated data acquisition. The proposed method significantly reduced the error caused by the well-mixing assumption of estimated air change rates from 26% to 3%. The sampling locations are identified as a function of the zone’s geometry. The findings of this study can be used to improve the ventilation performance of buildings.

Springer Link (Chiba Institute of Technology)
Sustainable cities and communities
Openalex Percentile: Top 43%
Building Energy and Comfort Optimization
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