occupancy

A Canadian provincial government has initiated a collaboration with the Indoor Air Quality (IAQ) team of the National Research Council of Canada (NRC) to conduct a controlled intervention study to determine the effectiveness of portable air cleaners (PACs) in reducing indoor air contaminants in 2 schools.

Data from mechanical extract ventilation units of Renson Ventilation nv installed in Belgium is utilized to detect space occupancy through machine learning. Challenges with the detection of occupancy using data captured by these smart devices are (1) absence of labelled data for training a machine learning model, and (2) occupant’s CO2 generation rate and building layouts influence the measured CO2 concentrations, which prevents simple rule-based models to be used for data labelling.

Indoor air quality is a major area of concern in northern housing and could be influenced by ventilation. The required ventilation rate set by North American ventilation standards (ASHRAE 62.2, CSA-F326) is calculated on the basis of fixed floor area and number of bedrooms or people. The heat/energy recovery ventilators (HRV/ERV) on the market offer constant airflows and are selected to meet the required ventilation.

Measuring ventilation rates in occupied dwellings is challenging but represents the conditions that occupants experience. This paper explores the constraints of existing methods when measuring the ventilation rate of occupied buildings and proposes a new method addressing some of them.  

Traditionally, occupancy-based ventilation controls have only ventilated when occupants are present – usually based on measurements of CO2 and/or humidity.  These indictors may be fine for pollutants released directly by occupants, such as bioeffluents, or by their activities, such as cooking and cleaning. However, they do not account for pollutants not associated with occupancy, such as formaldehyde from building materials and furnishings.

Although theoretical studies show that energy use for ventilation purposes can be reduced by more than 50% with DCV compared to CAV, evaluation of real energy use demonstrates that this potential is seldom met. DCV-based ventilation systems must become more reliable to close the gap between theoretical and real energy-performance.