Uncertainty quantification: For an IAQ and energy performance assessment method for smart ventilation strategies

Abstract

In new low-energy buildings or buildings after thermal refurbishment, the envelope high airtightness could have an impact on air renewal and could decrease the indoor air quality (IAQ). In this context smart-ventilation systems with variable airflows could play a role in providing better IAQ without compromising the energy performance.

However, smart-ventilation strategies are quite recent, and their benefits need to be clearly quantified. This article, proposes to quantify the uncertainty of a recent multi-criteria performance assessment method, using global RBD-FAST sensitivity analysis. The impact of the pollutant emissions scenarios, model input parameters and ventilation strategies is assessed.

Five ventilation systems were studied: two constant airflow, one humidity-controlled and two humidity/CO2 controlled, applied on a French low-energy house. 2500 simulations were performed to calculate 504 sensitivity indices across 12 input variables and 9 output performance indicators. The sensitivity analysis shows that occupant bio-effluent, formaldehyde and PM2.5 emissions rates are responsible for 11 %–87 % of the uncertainty for the IAQ performance indicators. The PM2.5 deposition velocity parameter is responsible for 50 % of the uncertainty on the PM2.5 indicator, which was an unknown impact. In addition, the benefits of humidity-controlled ventilation were highlighted regarding energy performance, with, in average, 20 % lower heat-loss compared to constant airflow ventilation. Moreover, smart-ventilation provides clear IAQ benefits without drastically increasing the energy demand. This work demonstrates the potential of the proposed evaluation method for ventilation performance assessment.