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

Accurate prediction of inhaled CO concentration and alveolar gas exchange efficiency would improve the prediction of CO 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 (CO ) gas exchange at the alveoli during the transient breathing cycle. This makes it possible to predict the CO distribution around the human body. The numerical model of the CO gas exchange mechanism includes both the upper and lower airways and makes it possible to calculate the alveolar CO partial pressure; this improves the prediction accuracy. We used the CSP to predict emission rates of metabolically generated CO 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 CO emission rates of the same magnitude as was observed in our published experimental data. We also observed that the predicted inhaled CO concentration depended on the flow pattern around the human body, as would be expected.