A comparison of methods for the derivation of classroom ventilation rates from CO2 measurements

• Comparison of three CO 2 -based methods for estimating classroom ventilation rates • First study to assess CO 2 methods’ performance under diverse ventilation conditions • Monte Carlo sampling quantifies effects of uncertain occupancy and emission rates • Steady-state daily mean CO 2 method agrees within ±10 % of transient mean method • Proposed method supports ventilation rate compliance and infection risk assessments Reliable estimation of classroom ventilation rates is essential for maintaining indoor air quality and verifying compliance with ventilation standards. However, CO₂-based estimation methods are often applied inconsistently across studies, and their comparative performance—especially under varying ventilation strategies—remains insufficiently understood. This study, conducted following the ImpAQS project, provides an empirical comparison of three methods for deriving daily ventilation rates based on indoor CO 2 measurements: (i) a steady-state method using the daily 95 th percentile CO 2 concentrations, (ii) a steady-state method using daily mean CO 2 concentrations, and (iii) a transient mass balance method. The analysis is based on measurements from one mechanically and one naturally ventilated classroom over three representative school days. It identifies how each methods captures the dynamic ventilation patterns associated with mechanical ventilation and user-driven window ventilation. Results show that the steady-state method using the daily mean CO 2 concentration is closely aligned with the transient mass balance method. Relative percentage differences within 10 % indicate that dynamic ventilation patterns can be approximated reliably with a steady-state approach. This highlights the practicality of the steady-state method using the daily mean CO 2 concentration for large monitoring datasets, where transient models require numerical solutions to the mass-balance equation and are therefore computationally more demanding. The uncertainty analysis further indicates that variability in occupant numbers and CO₂ generation rates introduce an uncertainty of approximately ± 40 % of the daily mean ventilation rate, underlining the need to quantify input-related variability when interpreting CO₂-based ventilation estimates.