Prediction of exhaled carbon dioxide concentration using a computer-simulated person that included alveolar gas exchange

Accurate prediction of inhaled CO₂ concentration and alveolar gas exchange efficiency would improve the prediction of CO₂ concentrations around the human body, which is essential for advanced ventilation design in buildings. We therefore, developed a computer-simulated person (CSP) that included a computational fluid dynamics approach. The CSP simulates metabolic heat production at the skin surface and carbon dioxide (CO₂) gas exchange at the alveoli during the transient breathing cycle. This makes it possible to predict the CO₂ distribution around the human body. The numerical model of the CO₂ gas exchange mechanism includes both the upper and lower airways and makes it possible to calculate the alveolar CO₂ partial pressure; this improves the prediction accuracy. We used the CSP to predict emission rates of metabolically generated CO₂ exhaled by a person and assumed that the tidal volume will be unconsciously reduced as a result of exposure to poor indoor air quality. A reduction in tidal volume resulted in a decrease in CO₂ emission rates of the same magnitude as was observed in our published experimental data. We also observed that the predicted inhaled CO₂ concentration depended on the flow pattern around the human body, as would be expected.