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Estimation of air change rate by CO2 sensor network in workplace with COVID-19 outbreak
Shinji Yokogawa1, Yo Ishigaki2, Hiroko Kitamura3
1Info-Powered Energy System Research Center (i-PERC), University of Electro-communications, Tokyo, Japan.
Objectives:
This study aimed to measure the air change per hour (ACH) in a workplace that spanned 880 m2 and had a ceiling height of 3 m. This workplace experienced clusters of coronavirus disease (COVID-19) cases, and the study measured ACH before and after remediation. The objective was to provide a quantitative estimate of ACH in various compartments.
Methods:
A network of CO2 sensors was set up in the workplace. The data from the sensors were analyzed using a generalized linear mixed model and dynamic time distortion to estimate the ACH in each area.
Results:
During the cluster outbreak, the ACH was in the range of 0.408 to 1.178/hour (p<.001), which was relatively low and likely contributed to the outbreak. Additionally, the room's ventilation was imbalanced due to partitioning. However, the ACH improved significantly from 1.835 to 2.551/hour (p<.001) by simply opening the windows and allowing natural ventilation.
Conclusions:
Based on the evidence that the transmission of COVID-19 was contained following the enhancement of ventilation, an ACH rate of below 2/hour was the primary factor in developing COVID-19 clusters within the facility under investigation.
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