Applying the CO2 concentration decay tracer gas method in long-term monitoring campaigns in occupied homes: Identifying appropriate unoccupied periods and decay periods

Purpose: Ventilation is driven by weather conditions, occupant actions and mechanical ventilation, and so can be highly variable. This paper reports on the development of two analysis algorithms designed to facilitate investigation of ventilation in occupied homes over time. Design/methodology/approach: These algorithms facilitate application of the CO2 concentration decay tracer gas technique. The first algorithm identifies occupied periods. The second identifies periods of decaying CO2 concentration which can be assumed to meet the assumptions required for analysis. Findings: The algorithms were successfully applied in four occupied dwellings, giving over 100 ventilation measurements during a six-month period for three flats. The specific implementation of the decay identification algorithm had important ramifications for the ventilation rates measured, highlighting the importance of interrogating the way that appropriate periods for analysis are identified. Practical implications: The analysis algorithms provide robust, reliable and repeatable identification of CO2 decay periods appropriate for ventilation rate analysis. The algorithms were coded in Python, and these have been made available via GitHub. As well as supporting future CO2 tracer gas experiments, the algorithms could be adapted to different purposes, including the use of other tracer gases or exploring occupant exposure to indoor air pollution. Originality/value: Empirical investigations of ventilation in occupied dwellings rarely aim to investigate the variability of ventilation. This paper reports on analysis methods which can be used to address this gap in the empirical evidence.