Buildings account for a substantial portion of energy consumption due to heating, ventilation, and air conditioning (HVAC) contributing to a large portion of energy-related greenhouse gas emissions. Occupant behavior influences this energy usage, particularly HVAC system energy use to meet occupant needs. Thus, knowledge of occupancy and occupancy schedules can assist in more efficient building operations. While many studies examine the link between occupancy, environmental health, and energy efficiency using physics-based modeling, there have been limitations to capturing the relationship between environmental conditions and occupancy trends, and to assess their impact on model predictions and accuracy. Thus, this thesis aims to define the relationship between CO2 concentration and occupancy patterns while capturing the effect of HVAC operations and environmental conditions, in particular air exchange rates associated with changing door conditions, as well as occupancy scenarios.To accomplish this, field data was collected on occupancy, CO2 concentrations, tracer gas testing, door state, and HVAC operations. Data was then modeled using two physics-based models for different occupant and ventilation scenarios. These models were then evaluated for accuracy under varying model assumptions, to assess the relationship between CO2 concentrations and occupancy. The evaluation included the correlation coefficient between the measured and modeled CO2 concentrations. Also, regression models were used to determine the relationship between occupancy and CO2 concentration, assessing fit using the coefficient of determination (r-squared). Findings reflect that physics-based models can accurately determine CO2 concentrations within rooms regardless of environmental conditions and occupant trends. This further validates that physics-based models can be utilized to accurately determine CO2 concentration from occupant sources. However, findings also imply that the application of box modeling to determine occupancy trends for energy efficiency purposes based on CO2 concentration is only applicable during select conditions, limited to high rates of transient occupancy, air exchange, and unknown sources of CO2 from surrounding classrooms and hallways. This indicates that physics-based modeling is a useful tool in modeling concentrations of CO2 within spaces however should be further investigated with other aspects of VAV systems, occupancy conditions, and surrounding sources of CO2 to assist in the outcome of understanding the applicability of this model for energy efficiency purposes.
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