Faculty of Engineering Sciences, Kyushu University, Kasuga, Japan.
Interdisciplinary Graduate School of Engineering Sciences, Kyushu University, Kasuga-shi, Japan.
Indoor Air. 2022 Aug;32(8):e13079. doi: 10.1111/ina.13079.
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.
准确预测吸入的 CO 浓度和肺泡气体交换效率将提高对人体周围 CO 浓度的预测能力，这对于建筑物中先进的通风设计至关重要。因此，我们开发了一个包含计算流体动力学方法的计算机模拟人（CSP）。CSP 模拟皮肤表面的代谢产热和肺泡中的二氧化碳（CO）气体交换在瞬态呼吸周期中。这使得预测人体周围的 CO 分布成为可能。CO 气体交换机制的数值模型包括上呼吸道和下呼吸道，并且能够计算肺泡 CO 分压；这提高了预测精度。我们使用 CSP 预测人体代谢产生的 CO 的排放率，并假设由于暴露于不良室内空气质量，潮气量会无意识地减少。潮气量的减少导致 CO 排放率降低，与我们发表的实验数据观察到的结果相同。我们还观察到，吸入的 CO 浓度取决于人体周围的流动模式，这是意料之中的。
