In situ air change rate estimation from metabolic CO2 measurement. Summer experimental campaign in a single-family test house

Abstract

Night ventilation is one of the most promising approaches for reducing the cooling-energy consumption of buildings while improving the summer thermal comfort of occupants. More accurate measurement of the air change rate (ACR) through window openings may help promote this approach. Indeed this is still an active research topic that requires well-controlled experimental data. This article aims to expand the application scope of the tracer gas methodology for dynamic estimation of ACR in residential buildings. Controlled inputs, such as human metabolic CO2 emissions and various window-opening configurations, are chosen to represent the actual use of a single-family house during the cooling season. The measurement dataset – including weather on site, wind on the walls, indoor air speed, temperature, relative humidity, CO2 concentration at various positions and at a time resolution of 1 min – is processed for sharing. Wind fluctuation on the external wall emphasizes the dynamic nature of ACR. Indoor temperature and CO2 concentration measurements showed a mean spatial heterogeneity of 1.0 °C and 625 ppm, respectively. Indoor CO2 levels are low (<2000 ppm), which is a limitation in the use of the tracer gas equation. Thus, the potential of the dataset for dynamic ACR estimation is discussed by introducing and analyzing two indicators. Finally, the ability of the dataset to compute dynamic ACR is demonstrated through deterministic solving of the tracer gas equation.