CO2 emission rates from sedentary subjects under controlled laboratory conditions

Sakamoto, Mitsuharu; Li, Mengze; Kuga, Kazuki; Ito, Kazuhide; Bekö, Gabriel; Williams, Jonathan; Wargocki, Paweł

doi:10.1016/j.buildenv.2021.108735

Cited by 21 publications

(13 citation statements)

References 25 publications

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“…This range based on the data sheet shown in Figure 2, which meets the experiment requirements that switched at a low frequency. IR source is electrical modulated frequency with frequency changes in a range from (0.5 to 3 Hz) [2].…”

Section: Methodsmentioning

confidence: 99%

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Development of NDIR CO2 Gas Sensing System Based on U-Shaped Optical Cavity

Mahdi

Azzawi

Mohammed

2022

Al-Mustansiriyah Journal of Science

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In this paper, a proposed carbon dioxide Gas Sensing System of high precision, rapid reaction, compact size and low power consumption rate is presented based on the non-dispersive infrared (NDIR) measurement. This system used to determine CO2 gas concentration in air; it consists of the single broadband light source, U-shape tube optical path cavity as gas cell, thermopile detector, and microcontroller circuit. This study investigates the efficiency of the U-tube optical path cavity at CO2 gas concentrations ranging from (0-5000) ppm. The obtained results show that it has the better thermal response compare to the linear tube and exhibits high sensitivity by change the transmitted light intensity into analog voltage. The proposed system design can be used as an environmental monitoring sensor.

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Section: Methodsmentioning

confidence: 99%

“…Carbon dioxide (CO2) measurement has recently been a hot topic in the harsh environment due to CO2's impact on air quality [1], global warming [2] and respiratory diseases [3]. Non-dispersive infrared gas sensors (NDIR) and contact type gas sensors such as Semiconductor Metal Oxide and Electrochemical have been employed in CO2 monitoring.…”

Section: Introductionmentioning

confidence: 99%

Development of NDIR CO2 Gas Sensing System Based on U-Shaped Optical Cavity

Mahdi

Azzawi

Mohammed

2022

Al-Mustansiriyah Journal of Science

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“…CO 2 emissions from individuals under various activity levels and environmental conditions is an active area of research. Recent studies have investigated the effect of various conditions including sedentary vs active behavior, indoor pollutants, ambient CO 2 levels, stressed vs relaxed cognitive activities, metabolic rate, temperature, gender and age [14][15][16][17][18][19][20][21]. Measurement of CO 2 concentration has previously been suggested as a tool for estimating airborne infection transmission risk [22].…”

Section: Introductionmentioning

confidence: 99%

Increasing Occupancy Levels in an Operating Room Environment Increases Detectable Ambient CO 2 Concentrations

Carroll

Kirschman

Mammana

2022

Preprint

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The air in an operating room becomes more contaminated as the occupancy of the room increases. Individuals residing in a room can potentially emit infectious agents. In order to inhibit and better understand the epidemiology of surgical site infections, it is important to develop procedures to track room occupancy level and respiration. Exhaled CO2 provides a respiratory byproduct that can be tracked with IR light and is associated with human occupancy. Exhaled CO2 can also be used as an indirect measure of the potential release and level of infectious airborne agents. We show that non-dispersive infrared CO2 sensors can be used to detect CO2 in operating room air flow conditions of 20 air changes per hour and a positive pressure of 0.03 in. H2O. The CO2 concentration increased consecutively for occupation levels of one to four individuals, from approximately 65 ppm above the background level when one individual occupied the operating room for twenty minutes to approximately 300 ppm above the background when four individuals were present for twenty minutes. The amount of CO2 detected increases as the number of occupants increase, the activity level increases, the residency time increases and when the ventilation level is reduced.

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“…The CO 2 emission rate is usually predicted on the basis of physical activity, body size, gender, and age. 1,2 Their impact on the CO 2 emission rates has been investigated experimentally in previous studies examining the effects of physical activity, [3][4][5][6][7][8][9] age, 8,10 and gender. 4,8,9,11 It has recently been shown that CO 2 emission rates can vary depending on other factors, including air temperature, 10,[12][13][14] the concentration of CO 2 and other pollutants in the inhaled air, 14,15 and psychological effects.…”

Section: Introductionmentioning

confidence: 99%

“…1,2 Their impact on the CO 2 emission rates has been investigated experimentally in previous studies examining the effects of physical activity, [3][4][5][6][7][8][9] age, 8,10 and gender. 4,8,9,11 It has recently been shown that CO 2 emission rates can vary depending on other factors, including air temperature, 10,[12][13][14] the concentration of CO 2 and other pollutants in the inhaled air, 14,15 and psychological effects. 16,17 In a previous study, 14 we measured the CO 2 emission rates of six male volunteers who were seated, and therefore, at a low activity level and found that when elevated ambient CO 2 concentration (between 800 and 3000 ppm) was obtained either by restricting ventilation or dosing pure CO 2 from a gas cylinder, the CO 2 emission rate decreased.…”

Section: Introductionmentioning

confidence: 99%

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

et al. 2022

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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.

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CO2 emission rates from sedentary subjects under controlled laboratory conditions

Cited by 21 publications

References 25 publications

Development of NDIR CO2 Gas Sensing System Based on U-Shaped Optical Cavity

Development of NDIR CO2 Gas Sensing System Based on U-Shaped Optical Cavity

Increasing Occupancy Levels in an Operating Room Environment Increases Detectable Ambient CO 2 Concentrations

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

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