Review and Extension of CO₂-Based Methods to Determine Ventilation Rates with Application to School Classrooms

Abstract

The ventilation rate (VR) is a key parameter affecting indoor environmental quality (IEQ) and the energy consumption of buildings. This paper reviews the use of CO₂ as a "natural" tracer gas for estimating VRs, focusing on applications in school classrooms. It provides details and guidance for the steady-state, build-up, decay and transient mass balance methods. An extension to the build-up method and an analysis of the post-exercise recovery period that can increase CO₂ generation rates are presented. Measurements in four mechanically-ventilated school buildings demonstrate the methods and highlight issues affecting their applicability. VRs during the school day fell below recommended minimum levels, and VRs during evening and early morning were on the order of 0.1 h^-1, reflecting shutdown of the ventilation systems. The transient mass balance method was the most flexible and advantageous method given the low air change rates and dynamic occupancy patterns observed in the classrooms. While the extension to the build-up method improved stability and consistency, the accuracy of this and the steady-state method may be limited. Decay-based methods did not reflect the VR during the school day due to heating, ventilation and air conditioning (HVAC) system shutdown. Since the number of occupants in classrooms changes over the day, the VR expressed on a per person basis (e.g., L·s^-1·person^-1) depends on the occupancy metric. If occupancy measurements can be obtained, then the transient mass balance method likely will provide the most consistent and accurate results among the CO₂-based methods. Improved VR measurements can benefit many applications, including research examining the linkage between ventilation and health.

Keywords: air change rate; carbon dioxide (CO2); classrooms; indoor air quality; schools; ventilation.

Figure 1

Observed and simulated CO₂ concentration trends over 24-h periods in classrooms in two conventional school buildings (A,B) and two EnergyStar school buildings (C,D). Red circles show observed (15-min) levels; colored areas show predicted CO₂ levels using simulated air change rate estimates fitted for the school day (blue), evening (green), and early morning (yellow) periods. Time axis shows hour of day (starting at 07:00).

Figure 2

Effect of post-exercise recovery on CO₂ generation and metabolic activity rates, expressed as relative bias for periods of 0 to 3 h, compared to classroom activity of 1.4 MET. Assumes children undergoing light to moderate exercise (2.9 to 4.6 MET) prior to entering the classroom. Three cases shown: Case 1 uses nominal parameters; Case 2 uses “maximal effect” parameters; Case 3 uses “minimal effect” parameters.