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

Abstract

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.