A novel methodology for estimating space air change rates and occupant CO2 generation rates from measurements in mechanically-ventilated buildings

It is useful to know ventilation rates and carbon dioxide (CO₂) generation rates for evaluating indoor air quality and ventilation efficiency in mechanically-ventilated buildings. A strong limitation of the current models is either they focus solely on a whole building or they are too complicated for practical use in studies of individual spaces. This paper develops a new method for accurately quantifying ventilation rates (i.e. space air change rate) and CO₂ generation rates from measured CO₂ concentrations for individual spaces. The proposed method firstly determined space air change rate using Maximum Likelihood Estimation (MLE). Additionally, a novel coupled-method was initiated for further estimating CO₂ generation rates. Both simulated and experimental data were used to validate the model. Experiments were conducted in a school office by measuring indoor CO₂ concentrations and pressure differences between the return air vent and space. Excellent agreement was obtained. At least 0.998 R² values were obtained for fitting measured CO₂ concentrations when conducting MLE for estimating space air change rate, and the corresponding residual plots showed no pattern and trend. The estimated numbers of occupants were same as the actual ones. Furthermore, the predicted space air change rates showed great consistencies with those from CO₂ equilibrium analysis. The model is simple, handy and effective for practical use. Moreover, the model is also capable for dealing with time-varying space air change rates.