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Humans emit carbon dioxide (CO2) as a product of their metabolism. Its concentration in buildings is used as a marker of ventilation rate (VR) and degree of mixing of supply air, and indoor air quality (IAQ). The CO2 emission rate (CER) may be used to estimate the ventilation rate. Many studies have measured CERs from subjects who were awake but little data are available from sleeping subjects and the present publication was intended to reduce this gap in knowledge. Seven females (29 ± 5 years old; BMI: 22.2 ± 0.8 kg/m2) and four males (27 ± 1 years old; BMI: 20.5 ± 1.5 kg/m2) slept for four consecutive nights in a specially constructed capsule at two temperatures (24 and 28°C) and two VRs that maintained CO2 levels at ca. 800 ppm and 1700 ppm simulating sleeping conditions reported in the literature. The order of exposure was balanced, and the first night was for adaptation. Their physiological responses, including heart rate, pNN50, core body temperature, and skin temperature, were measured as well as sleep quality, and subjective responses were collected each evening and morning. Measured steady‐state CO2 concentrations during sleep were used to estimate CERs with a mass‐balance equation. The average CER was 11.0 ± 1.4 L/h per person and was 8% higher for males than for females (P < 0.05). Increasing the temperature or decreasing IAQ by decreasing VR had no effects on measured CERs and caused no observable differences in physiological responses. We also calculated CERs for sleeping subjects using the published data on sleep energy expenditure (SEE) and Respiratory Quotient (RQ), and our measured CERs confirmed both these calculations and the CERs predicted using the equations provided by ASHRAE Standard 62.1, ASHRAE Handbook, and ASTM D6245‐18. The present results provide a valuable and helpful reference for the design and control of bedroom ventilation but require confirmation and extension to other age groups and populations.

Accurate prediction of inhaled CO 2 concentration and alveolar gas exchange efficiency would improve the prediction of CO 2 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 2 ) gas exchange at the alveoli during the transient breathing cycle. This makes it possible to predict the CO 2 distribution around the human body. The numerical model of the CO 2 gas exchange mechanism includes both the upper and lower airways and makes it possible to calculate the alveolar CO 2 partial pressure; this improves the prediction accuracy. We used the CSP to predict emission rates of metabolically generated CO 2 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 2 emission rates of the same magnitude as was observed in our published experimental data. We also observed that the predicted inhaled CO 2 concentration depended on the flow pattern around the human body, as would be expected.