Impact of Cognitive Tasks on CO2 and Isoprene Emissions from Humans

Bedroom Concentrations and Emissions of Volatile Organic Compounds during Sleep

Because humans spend about one-third of their time asleep in their bedrooms and are themselves emission sources of volatile organic compounds (VOCs), it is important to specifically characterize the composition of the bedroom air that they experience during sleep. This work uses real-time indoor and outdoor measurements of volatile organic compounds (VOCs) to examine concentration enhancements in bedroom air during sleep and to calculate VOC emission rates associated with sleeping occupants. Gaseous VOCs were measured with proton-transfer reaction time-of-flight mass spectrometry during a multiweek residential monitoring campaign under normal occupancy conditions. Results indicate high emissions of nearly 100 VOCs and other species in the bedroom during sleeping periods as compared to the levels in other rooms of the same residence. Air change rates for the bedroom and, correspondingly, emission rates of sleeping-associated VOCs were determined for two bounding conditions: (1) air exchange between the bedroom and outdoors only and (2) air exchange between the bedroom and other indoor spaces only (as represented by measurements in the kitchen). VOCs from skin oil oxidation and personal care products were present, revealing that many emission pathways can be important occupant-associated emission factors affecting bedroom air composition in addition to direct emissions from building materials and furnishings.

Physiology or Psychology: What Drives Human Emissions of Carbon Dioxide and Ammonia?

Humans are the primary sources of CO2 and NH3 indoors. Their emission rates may be influenced by human physiological and psychological status. This study investigated the impact of physiological and psychological engagements on the human emissions of CO2 and NH3. In a climate chamber, we measured CO2 and NH3 emissions from participants performing physical activities (walking and running at metabolic rates of 2.5 and 5 met, respectively) and psychological stimuli (meditation and cognitive tasks). Participants' physiological responses were recorded, including the skin temperature, electrodermal activity (EDA), and heart rate, and then analyzed for their relationship with CO2 and NH3 emissions. The results showed that physiological engagement considerably elevated per-person CO2 emission rates from 19.6 (seated) to 46.9 (2.5 met) and 115.4 L/h (5 met) and NH3 emission rates from 2.7 to 5.1 and 8.3 mg/h, respectively. CO2 emissions reduced when participants stopped running, whereas NH3 emissions continued to increase owing to their distinct emission mechanisms. Psychological engagement did not significantly alter participants' emissions of CO2 and NH3. Regression analysis revealed that CO2 emissions were predominantly correlated with heart rate, whereas NH3 emissions were mainly associated with skin temperature and EDA. These findings contribute to a deeper understanding of human metabolic emissions of CO2 and NH3.

Achieving better indoor air quality with IoT systems for future buildings: Opportunities and challenges

With the development of IoT technology and low-cost indoor air quality (IAQ) sensors, the IoT-based IAQ monitoring platform has garnered significant research interest and demonstrated its potential in enhancing IAQ management. This study presents a comprehensive review of previous research on the development and application of IoT-based IAQ platforms in different built environments. It offers detailed insights into the design and implementation of recent IoT-based IAQ platforms. The findings indicate that the IoT-based IAQ platforms are able to provide reliable information for IAQ monitoring. To ensure quality control of the IoT-based IAQ platform, it is suggested to replace the sensors every 4-6 months for reliable monitoring. In another aspect, integrating data-driven technology into the platform is crucial for IAQ prediction and efficient control of ventilation systems, leveraging the wealth of data available from the IoT platform. According to recent studies that applied data-driven algorithms for IAQ management, it can be confirmed that the data-driven algorithms are able to prompt IAQ by providing either more information or a control strategy. However, it should be noted that only 9.1 % of the developed platforms integrated data-driven models for IAQ management. Based on our findings, current challenges and further opportunities are discussed. Future studies should focus on integrating data-driven algorithms into IoT-based IAQ platforms and developing digital twins that can be used for real building IAQ management. However, there is obvious tension between controlling ventilation for energy efficiency versus better air quality. It is important to make a balance between energy efficiency and better air quality according to the current situations of specific built environments. Also, the next generation of IoT-based IAQ platforms should include occupants in the loop to create a more occupant-centric IAQ management approach.

Increased CO2 levels in the operating room correlate with the number of healthcare workers present: an imperative for intentional crowd control

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.

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

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.

Per-Person and Whole-Building VOC Emission Factors in an Occupied School with Gas-Phase Air Cleaning

Using real-time measurements of CO₂ and volatile organic compounds (VOCs) in the air handler of an occupied middle school, we quantified source strengths for 249 VOCs and apportioned the source to the building, occupants and their activities, outdoor air, or recirculation air. For VOCs quantified in this study, there is a source to the outdoors of 8.6 ± 1.8 g/h in building exhaust air, of which 5.9 ± 1.7 g/h can be attributed to indoor sources (the building and occupants and their activities). The corresponding whole-building area emission factor from indoor sources is 1020 ± 300 μg/(m² h), including reactive VOCs like isoprene and monoterpenes (33 ± 5.1 and 29 ± 5.7 μg/(m² h), respectively). Per-person emission factors are calculated for compounds associated with occupants and their activities, e.g., monoterpenes are emitted at a rate of 280 ± 80 μg/(person h). The air handler included carbon scrubbing, reducing supply air concentrations of 125 compounds by 38 ± 19% (mean ± std. dev.) with a net removal of 2.4 ± 0.4 g/h of organic compounds from the building. This carbon scrubber reduces steady-state indoor concentrations of organics by 65 μg/m³ and the contribution of indoor sources of VOCs to the outdoor environment by ∼40%. These data inform the design and operation of buildings to reduce human exposure to VOCs inside buildings. These data indicate the potential for gas-phase air cleaning to improve both indoor air quality and reduce VOC emissions from buildings to the outdoor environment.

A Smart System for the Contactless Measurement of Energy Expenditure

Energy Expenditure (EE) (kcal/day), a key element to guide obesity treatment, is measured from CO₂ production, VCO₂ (mL/min), and/or O₂ consumption, VO₂ (mL/min). Current technologies are limited due to the requirement of wearable facial accessories. A novel system, the Smart Pad, which measures EE via VCO₂ from a room’s ambient CO₂ concentration transients was evaluated. Resting EE (REE) and exercise VCO₂ measurements were recorded using Smart Pad and a reference instrument to study measurement duration’s influence on accuracy. The Smart Pad displayed 90% accuracy (±1 SD) for 14–19 min of REE measurement and for 4.8–7.0 min of exercise, using known room’s air exchange rate. Additionally, the Smart Pad was validated measuring subjects with a wide range of body mass indexes (BMI = 18.8 to 31.4 kg/m²), successfully validating the system accuracy across REE’s measures of ~1200 to ~3000 kcal/day. Furthermore, high correlation between subjects’ VCO₂ and λ for CO₂ accumulation was observed (p < 0.00001, R = 0.785) in a 14.0 m³ sized room. This finding led to development of a new model for REE measurement from ambient CO₂ without λ calibration using a reference instrument. The model correlated in nearly 100% agreement with reference instrument measures (y = 1.06x, R = 0.937) using an independent dataset (N = 56).

Low Level Carbon Dioxide Indoors—A Pollution Indicator or a Pollutant? A Health-Based Perspective

With modern populations in developed countries spending approximately 90% of their time indoors, and with carbon dioxide (CO2) concentrations inside being able to accumulate to much greater concentrations than outdoors, it is important to identify the health effects associated with the exposure to low-level CO2 concentrations (<5000 ppm) typically seen in indoor environments in buildings (non-industrial environments). Although other reviews have summarised the effects of CO2 exposure on health, none have considered the individual study designs of investigations and factored that into the level of confidence with which CO2 and health effects can be associated, nor commented on how the reported health effects of exposure correspond to existing guideline concentrations. This investigation aimed to (a) evaluate the reported health effects and physiological responses associated with exposure to less than 5000 parts per million (ppm) of CO2 and (b) to assess the CO2 guideline and limit concentrations in the context of (a). Of the 51 human investigations assessed, many did not account for confounding factors, the prior health of participants or cross-over effects. Although there is some evidence linking CO2 exposures with health outcomes, such as reductions in cognitive performance or sick building syndrome (SBS) symptoms, much of the evidence is conflicting. Therefore, given the shortcomings in study designs and conflicting results, it is difficult to say with confidence whether low-level CO2 exposures indoors can be linked to health outcomes. To improve the epidemiological value of future investigations linking CO2 with health, studies should aim to control or measure confounding variables, collect comprehensive accounts of participants’ prior health and avoid cross-over effects. Although it is difficult to link CO2 itself with health effects at exposures less than 5000 ppm, the existing guideline concentrations (usually reported for 8 h, for schools and offices), which suggest that CO2 levels <1000 ppm represent good indoor air quality and <1500 ppm are acceptable for the general population, appear consistent with the current research.

The effects of warmth and CO2 concentration, with and without bioeffluents, on the emission of CO2 by occupants and physiological responses

The emission rate of carbon dioxide (CO₂ ) depends on many factors but mainly on the activity level (metabolic rate) of occupants. In this study, we examined two other factors that may influence the CO₂ emission rate, namely the background CO₂ concentration and the indoor temperature. Six male volunteers sat one by one in a 1.7 m³ chamber for 2.5 h and performed light office-type work under five different conditions with two temperature levels (23 vs. 28°C) and three background concentrations of CO₂ (800 vs. 1400 vs. 3000 ppm). Background CO₂ levels were increased either by dosing CO₂ from a cylinder or by reducing the outdoor air supply rate. Physiological responses to warmth, added CO₂ , and bioeffluents were monitored. The rate of CO₂ emission was estimated using a mass-balance equation. The results indicate a higher CO₂ emission rate at the higher temperature, at which the subjects were warm, and a lower emission rate in all conditions in which the background CO₂ concentration increased. Physiological measurements partially explained the present results but more measurements are needed.