Indoor Air Quality and Ventilation Energy in University Classrooms: Simplified Model to Predict Trade-Offs and Synergies

Abstract

Students and educators spend significant time in learning spaces on university campuses. Energy efficiency has become a concern among facility managers, given the need to maintain acceptable indoor air quality (IAQ) levels during and after the COVID-19 pandemic. This paper investigates the relationship between control and extraneous variables in a university classroom’s total mechanical ventilation (kWh). The model is built using Grasshopper software on Rhino Version 7. Our methodology encompasses (1) an extensive review of recent trends for studying IAQ and energy, (2) selecting parameters for simulation, (3) model configuration on Grasshopper, and finally, (4) a formulation of a pertinent equation to consolidate the relationship between the studied factors and the total mechanical ventilation energy (kWh). Central to this study are two key research questions: (1) What correlations exist between various parameters related to occupancy and IAQ in educational spaces? And (2) how can we optimize energy efficiency in university classrooms? The main contribution of this research is a generated equation representing the annual mechanical ventilation energy consumption based on selected parameters of classroom height, area, occupancy, window location, and ventilation rate of HVAC systems. We find that occupancy and class volume are the two most influential factors directly affecting mechanical ventilation energy consumption. The equation serves as a valuable estimation tool for facility managers, designers, and campus operations to investigate how fluctuations in occupancy can influence ventilation energy consumption in the physical attributes of a university classroom. This enables proactive decision-making, optimizing energy efficiency and resource allocation in real-time to promote sustainable and cost-effective campus operations.

Enhanced Indoor Air Quality Dashboard Framework and Index for Higher Educational Institutions

“…(3) Third, an equation to estimate energy efficiency was utilized and measured for each selected space. This equation is based on a parametric model simulation of a university classroom in Cairo, Egypt [65]. Finally, the outcome of these collected data was used to assess classroom quality and effectiveness.…”