New index and model of transient CO2 diffusion for personal air quality and demand-controlled ventilation in heating and cooling systems

Evaluation metrics and prediction methods for carbon dioxide (CO₂) concentration play a critical role in Demand–Controlled Ventilation (DCV) optimization. However, the non–uniform impact of pollution sources on transient CO₂ distribution in personal air quality (PAQ) is frequently overlooked. This study aims to propose a new equivalent CO₂ index (E_CO₂) and a computational CO₂ concentration (C_CO₂) model to investigate transient CO₂ diffusion. This method defines uniformly mixed reference concentration per unit time, background index for pinpointing the most disadvantaged breathing-zone with excessive CO₂ accumulation, and the correction factor for exhaled CO₂ at different heights; the model consists of air changes per hour (ACH), characteristics of occupant, temperature, pressure gradients, CO₂ exhaled rates, pollutant diffusion duration, and correction factor for varying breathing–zone heights. Transient CO₂ diffusion patterns for various ceiling and sidewall terminals of heating and cooling systems were investigated through analyzing experimental and computational fluid dynamics (CFD) simulation results. Transient CFD simulation and the computation model were validated for effective prediction of CO₂ concentrations at varying breathing–zone heights. Under the unstable dynamic airflow system, CO₂ distribution was primarily governed by vertical convection/thermal plumes. The ceiling cooling has the smallest CO₂ concentration difference at different heights, which has a higher average E_CO₂ value. Under the stable thermally stratified system, the ceiling heating promoted horizontal pollutant diffusion. Moreover, the average positive E_CO₂ had increased by 4.9 % by optimizing the design scheme based on individual demand. This investigation quantifies non-uniform CO₂ distributions from pollution sources, enabling PAQ-based prediction and ventilation optimization.