Measurement of carbon monoxide in simulated expired breath

Characteristics of the large-scale circulation during episodes with high and low concentrations of carbon dioxide and air pollutants at an arctic monitoring site in winter

This paper describes the design of a portable carbon dioxide detector from low cost hardware and software components. The carbon dioxide molecules absorb light at a specific wavelength of 4.26 µm in the mid-infrared radiation. High concentrations of carbon dioxide molecules absorb more IR light than low concentrations. The design of the system includes a monochromatic infrared source, located in the source housing, and is activated by a constant voltage source obtained from the Switching Regulator Assembly. The infrared energy entering the sample chamber is absorbed at the wavelength specified as a result of the concentration of carbon dioxide being measured. The reflector assembly at the rear of the sample chamber returns the energy onto the IR detector. The detector signal is amplified by a low noise pre-amplifier and directed to the microprocessor. The signal goes into the processor through an ADC circuit. The amplitude of the digital signal is then threshold detected at a predetermined value to detect the amount of carbon dioxide.

The standard industrial process for the purification of natural gas is to remove acid gases, mainly hydrogen sulfide and carbon dioxide, by the absorption and reaction of these gases with alkanolamines, but the lack of reliable and accurate vapor–liquid equilibrium (VLB) data impedes the commercial application of more efficient alkanolamine systems. A novel Fourier‐transform infrared (FTIR) technique was developed to make in‐situ VLE measurements of acid‐gas‐aqueous alkanolamine systems and to improve the accuracy of VLE measurements at low hydrogen sulfide and carbon dioxide concentrations. VLE measurements of low carbon dioxide and hydrogen sulfide concentrations in aqueous mixtures of methyldiethanolamine (MDEA) are reported using the new FTIR technique.

Diffusivity is a strong function of concentration and an important transport property. Diffusion of multiple species is far more frequent than the diffusion of one species. However, there are limited experimental data available on multi-component diffusivity. The objective of this study is to develop an optimal control framework to determine multi-component concentration-dependent diffusivities of two gases in a non-volatile phase such as polymer. In Part 1 of this study, we derived a detailed mass-transfer model of the experimental diffusion process for the non-volatile phase to provide the temporal masses of gases in the polymer. The determination of diffusivities is an inverse problem involving principles of optimal control. Necessary conditions are determined to solve this problem. In Part 2 of this study, we utilized the results of Part 1 to determine the concentration-dependent, multi-component diffusivities of nitrogen and carbon dioxide in polystyrene. To that end, solubility and diffusion experiments are conducted to obtain necessary data. In the ternary system of nitrogen (1), carbon dioxide (2), and polystyrene (3), the diffusivities and D11, D12, D21, and D22 versus the gas mass fractions are two-dimensional surfaces. The diffusivity of carbon dioxide was found to be greater than that of nitrogen. The value of the main diffusion coefficient D11 was found to increase as the concentration of carbon dioxide increased. The highest value of D11 obtained was 2.2 X 10^-8m^2s^-1 for nitrogen mass fraction of 3.14 X10^-4 and for a carbon dioxide mass fraction of 5.67 X 10^-4 . The cross-diffusion coefficient increased as the concentrations of nitrogen and carbon dioxide increased. The diffusivity reached its maximum value when the concentrations of nitrogen and carbon dioxide were at their maximum values. The diffusivity was of the order of 10^-9m^2s^-1. The diffusivity of the cross-diffusion coefficient D21 was found to be increased for the mass The diffusivity of the cross-diffusion coefficient was found to be increased for the mass fractions of carbon dioxide ranging from 0 to 1.70 X 10^-3 . The diffusivity was found to be of the order of . The diffusion coefficient, D22, was found to increase with the concentrations of nitrogen and carbon dioxide, D22 remained high with low concentrations of carbon dioxide. The diffusivity was found to be of the order of 10^-7m^2s^-1

Diffusivity is a strong function of concentration and an important transport property. Diffusion of multiple species is far more frequent than the diffusion of one species. However, there are limited experimental data available on multi-component diffusivity. The objective of this study is to develop an optimal control framework to determine multi-component concentration-dependent diffusivities of two gases in a non-volatile phase such as polymer. In Part 1 of this study, we derived a detailed mass-transfer model of the experimental diffusion process for the non-volatile phase to provide the temporal masses of gases in the polymer. The determination of diffusivities is an inverse problem involving principles of optimal control. Necessary conditions are determined to solve this problem. In Part 2 of this study, we utilized the results of Part 1 to determine the concentration-dependent, multi-component diffusivities of nitrogen and carbon dioxide in polystyrene. To that end, solubility and diffusion experiments are conducted to obtain necessary data. In the ternary system of nitrogen (1), carbon dioxide (2), and polystyrene (3), the diffusivities and D11, D12, D21, and D22 versus the gas mass fractions are two-dimensional surfaces. The diffusivity of carbon dioxide was found to be greater than that of nitrogen. The value of the main diffusion coefficient D11 was found to increase as the concentration of carbon dioxide increased. The highest value of D11 obtained was 2.2 X 10^-8m^2s^-1 for nitrogen mass fraction of 3.14 X10^-4 and for a carbon dioxide mass fraction of 5.67 X 10^-4 . The cross-diffusion coefficient increased as the concentrations of nitrogen and carbon dioxide increased. The diffusivity reached its maximum value when the concentrations of nitrogen and carbon dioxide were at their maximum values. The diffusivity was of the order of 10^-9m^2s^-1. The diffusivity of the cross-diffusion coefficient D21 was found to be increased for the mass The diffusivity of the cross-diffusion coefficient was found to be increased for the mass fractions of carbon dioxide ranging from 0 to 1.70 X 10^-3 . The diffusivity was found to be of the order of . The diffusion coefficient, D22, was found to increase with the concentrations of nitrogen and carbon dioxide, D22 remained high with low concentrations of carbon dioxide. The diffusivity was found to be of the order of 10^-7m^2s^-1

Lactic acid, carbon dioxide and human sweat stimuli were presented singly and in combination to femaleAedes aegypti(Linnaeus) within a wind-tunnel system. The take-off, flight, landing and probing responses of the mosquitoes were recorded using direct observation and video techniques. The analyses determined the nature of the response to different stimuli and the concentration ranges within which specific behaviours occurred. A threshold carbon dioxide concentration for taking-off of approximately 0.03% above ambient was detected. Lactic acid and human sweat samples did not elicit take-off when presented alone, however, when they were combined with elevated carbon dioxide, take-off rate was enhanced in most of the combinations tested. Flight activity was positively correlated with carbon dioxide level and some evidence for synergism with lactic acid was found within a narrow window of blend concentrations. The factors eliciting landing were more subtle. There was a positive correlation between landing rate and carbon dioxide concentration. At the lowest carbon dioxide concentration tested, landing occurred only in the presence of lactic acid. Within a window of low to intermediate concentrations, landing rate was enhanced by this combination. At the highest carbon dioxide concentration, landing was however inhibited by the presence of lactic acid. The sweat extract elicited landings in the absence of elevated carbon dioxide. This indicated the presence of chemical stimuli, other than lactic acid, active in the short range. Probing occurred only at low carbon dioxide concentrations and there was no probing when lactic acid alone was tested. There was however probing in the presence of combined stimuli, the level of response seemed to be positively correlated with the ratio of carbon dioxide and lactic acid concentrations.

For the design of high oxygen modified atmosphere packages, knowledge and modelling of respiration rates at both low and super‐atmospheric oxygen levels is required. Fresh‐cut butterhead lettuce was stored in glass jars at three different temperatures (1 °C, 5 °C and 9 °C), three carbon dioxide levels (0, 10 and 20 kPa) and eight different levels of oxygen partial pressures (0, 2, 5, 10, 20, 50, 70 and 100 kPa). Oxygen consumption and carbon dioxide production rates were measured. The respiration rates were significantly reduced by low temperatures and elevated carbon dioxide concentrations up to 10 kPa. At carbon dioxide concentrations of 20 kPa the respiration rates were comparable to those at 0 kPa CO2 probably due to an injury response. Oxygen concentrations had to be below 2 kPa to significantly reduce the respiration rates compared to air conditions. Respiration rates were also slightly lower under super‐atmospheric (50, 70 and 100 kPa) oxygen partial pressures than at air conditions. Additionally, a Michaelis–Menten based model to describe the respiration rates as a function of oxygen, carbon dioxide and temperature was constructed. Models that include respiration rates at super‐atmospheric oxygen levels have not previously been described. The inhibitive effects of carbon dioxide and high oxygen concentrations were incorporated by an uncompetitive and a non‐competitive inhibition term respectively. Temperature effects were described using Arrhenius' law. The model gave a good description (R2adj = 0.82) of the oxygen consumption and carbon dioxide production rates over the temperature, oxygen and carbon dioxide range tested. Copyright © 2006 Society of Chemical Industry

Background and Aims Critically ill acute kidney injury (AKI) patients may require treatment by extracorporeal carbon dioxide removal (ECCO2R) devices to allow protective or ultraprotective mechanical ventilation and avoid hypercapnic acidosis. Continuous venovenous hemofiltration (CVVH) and ECCO2R devices can be arranged in series to form a single extracorporeal circuit; such a circuit has been proposed to be optimal, based carbon dioxide removal efficacy, if the ECCO2R device is placed proximal to the CVVH device (Allardet-Servent et al, Crit Care Med 43:2570-2581, 2015). Method We developed a mathematical model of whole-body, acid-base balance during extracorporeal therapy using in-series ECCO2R and CVVH devices for treatment of mechanically ventilated AKI patients. Equilibrium acid-base chemistry in blood was assumed as reported previously (Rees and Andreassen, Crit Rev Biomed Eng 33:209-264, 2005). Published clinical data from Allardet-Servent et al of mechanically ventilated (6 mL/kg predicted body weight or PBW) AKI patients treated by CVVH without ECCO2R were used to adjust model parameters to fit plasma levels of arterial partial pressure of carbon dioxide (PaCO2) and arterial plasma bicarbonate concentration ([HCO3]). The effects of applying ECCO2R at an unchanged tidal volume and a reduced tidal volume (4 mL/kg PBW) on PaCO2 and [HCO3] were then simulated assuming carbon dioxide removal rates from the ECCO2R device measured in the clinical study (91 mL of CO2/min when ECCO2R was proximal and 72 mL of CO2/min when CVVH was proximal). Results Agreement of model predictions with the clinical data was good, and model predictions were relatively independent of the in-series position of the devices (see Table). Total carbon dioxide removal from the CVVH device via ultrafiltration predicted by the model was lower after applying ECCO2R at both the unchanged tidal volume (25 mL of CO2/min when ECCO2R was proximal and 39 mL of CO2/min when CVVH was proximal) and the reduced tidal volume (30 mL of CO2/min when ECCO2R was proximal and 44 mL of CO2/min when CVVH was proximal). The reduced removal of total carbon dioxide via ultrafiltration when ECCO2R was proximal resulted from the lower total carbon dioxide concentration in blood entering the CVVH device. Thus, independent of the in-series position of the devices, the magnitude of this difference in total carbon dioxide removal by the CVVH device (14 mL of CO2/min) approximately cancels out the relative greater efficacy of the ECCO2R device (19 mL of CO2/min). Conclusion The described mathematical model has quantitative accuracy. It suggests that overall acid-base balance when using ECCO2R and CVVH devices in a single, combined extracorporeal circuit will be similar, independent of their in-series position.

New sensor measures biological activity in soil at field scale in real time

Providing for increasing global energy needs while managing carbon dioxide emissions is the dual energy challenge the modern world faces. In order to meet this challenge, reliable and dispatchable low carbon energy sources are a likely component. For many scenarios, this suggests that cost effective carbon dioxide capture will be a key technology.[1] Carbon capture with carbonate fuel cells (CFCs) may be one such technology option.[2]Carbonate fuel cells concentrate carbon dioxide from the cathode to the anode as part of their normal operation, effectively doing both carbon capture and low carbon power generation in a single process. (see Figure 1) When generating power, typical carbon dioxide concentrations fed to the CFC cathode tend to be higher than carbon dioxide emissions of many industrial processes. This means that if we want to capture that carbon dioxide, we need the fuel cell to operate at lower carbon dioxide concentrations than it typically does. For carbon capture operations, cathode inlet carbon dioxide concentrations could be as low as 4%. Additionally, under typical power generation operations, CFCs only capture a fraction of the carbon dioxide (<50%) fed to the cathode, where for carbon capture rates may be as high as 90%. Together these two constraints (low initial concentration and higher capture) results in very low carbon dioxide concentrations in the cell, particularly at the cathode outlet. This may impact the fundamental chemistry of the process. Carbon dioxide capture at 4% and lower was tested in a fuel cell, specifically designed to minimize mass transport effects external to the active cell components. Carbon capture was demonstrated at a range of carbon dioxide concentrations ranging from standard operation for power generation (>10%) to <1%. Additionally, oxygen concentrations and current densities were varied over likely operational ranges. We demonstrate that under most circumstances, operations under carbon capture conditions proceed via a similar mechanism to those under power generation conditions. However, in harsh or extreme conditions, where carbon dioxide concentrations are low (<0.5%) and/or current densities high, alternative mechanisms appear. We demonstrate how the CFC performs when these alternative mechanisms are present. Additionally, our findings suggest that they appear to utilize water in place of carbon dioxide and allow the cell to operate at conditions beyond theoretical complete carbon capture. [1] IEA World Energy Outlook 2018; Bloomberg New Energy Finance, New Energy Outlook 2018 [2] Ghezel-Ayagh H., Jolly S., Patel D., Hunt J., Steen W., Richardson C., Marina O., (2013) A Novel System for Carbon Dioxide Capture Utilizing Electrochemical Membrane Technology ECS Transaction Vol 51 (1) 265-272 Figure 1

Electrodes for blood pO2 and pCO2 determination.

Carbon dioxide sensors used for monitoring and control applications in buildings are known to be sensitive to long term drift and can be affected by variations in temperature, humidity, other gas interferents, pressure and other factors that cannot be corrected through the typical auto-calibration methods often embedded in the sensor electronics. This investigation was part of the Category D defined in the ARPA-E Saving Energy Nationwide in Structures With Occupancy Recognition (SENSOR) Financial Assistance Funding Opportunity Announcement No. DE-FOA-0001737, FFDA No. 81.135, January 18, 2017. The FOA defined target criteria for the evaluation of the Category C commercial CO2 sensors selected for review and development through the ARPA-E SENSOR program and charged the Iowa State Category D team with developing an evaluation methodology for Category C sensors in accordance with these criteria. As part of the work, the Iowa State team chose to engage the standards community in the development of the evaluation methodology. Standard development work in the D22.05 Indoor Air and D22.03 Ambient Atmospheres and Source Emissions subcommittees of ASTM International Committee D22 on Air Quality on the evaluation of low cost sensors and provision of guidance for using indoor carbon dioxide concentrations to evaluate indoor air quality and ventilation is of particular relevance to the Category D efforts. To date, three draft standards with specific input by the Iowa State Category D team have passed the subcommittee balloting stage and are being balloted in December 2022 and January 2023 in the main D22 committee. In addition to the aforementioned standards to which the PI was a contributing author, intellectual property developed in this project pertaining to “An Automated System for Evaluation of the Long Term Performance of Carbon Dioxide Sensors” and “An Automated Ground Truth System for Real-Time Reliability Assessment, Capture of Control Decisions and Energy Savings Measurements for Occupancy Recognition Systems and Other Applications” are the other major deliverables of the project. These standards and the developed intellectual property are expected to benefit the public in a number of ways stemming from their provision of means to benchmark the performance of carbon dioxide and other sensor systems. In particular, there is high interest in techniques to demonstrate the performance of low-cost carbon dioxide sensors which can be used for typical HVAC applications (e.g., demand controlled ventilation, outdoor and indoor air monitoring, estimation of occupancy, etc.).

Past work demonstrating an association between indoor air quality and cognitive performance brought attention to the benefits of increasing outdoor air ventilation rates beyond code minimums. These code minimums were scrutinized during the COVID-19 pandemic for insufficient ventilation and filtration specifications. As higher outdoor air ventilation was recommended in response, questions arose about potential benefits of enhanced ventilation beyond infection risk reduction. This was investigated by examining associations between indoor carbon dioxide concentrations, reflective of ventilation and building occupancy, and cognitive test scores among graduate students attending lectures in university classrooms with infection risk management strategies, namely increased ventilation. Post-class cognitive performance tests (Stroop, assessing inhibitory control and selective attention; Arithmetic, assessing cognitive speed and working memory) were administered through a smartphone application to participating students (54 included in analysis) over the 2022-2023 academic year in classrooms equipped with continuous indoor environmental quality monitors that provided real-time measurements of classroom carbon dioxide concentrations. Temporally and spatially paired exposure and outcome data was used to construct mixed effects statistical models that examined different carbon dioxide exposure metrics and cognitive test scores. Model estimates show directionally consistent evidence that higher central and peak classroom carbon dioxide concentrations, indicative of ventilation and occupancy, are associated with lower cognitive test scores over the measured range included in analysis ( ~ 440-1630 ppm). The effect estimates are strongest for 95th percentile class carbon dioxide concentrations, representing peak class carbon dioxide exposures. As the COVID-19 pandemic eased, questions emerged on the benefits of increased outdoor air ventilation beyond infection reduction. This work assesses associations between carbon dioxide concentrations, indicative of ventilation and occupancy, and cognitive test scores among students in university classrooms with increased outdoor air ventilation. Although not causal, models show statistically significant evidence of associations between lower carbon dioxide concentrations and higher cognitive test scores over the low range of carbon dioxide exposures in these classrooms. While the underlying mechanisms remain unknown, higher outdoor air ventilation appears to provide additional benefits by reducing indoor air exposure and supporting student performance.

To assess the efficacy of added carbon dioxide as adjunctive therapy to positive airway pressure-refractory mixed obstructive and central sleep-disordered breathing, using a prototype device-the positive airway pressure gas modulator. Open-label evaluation of low concentrations of carbon dioxide added to a positive airway pressure circuit. Physician-attended polysomnographic titration in a free-standing sleep laboratory with end-tidal and transcutaneous carbon-dioxide monitoring. Six adult men (age 54 +/- 5.7 years) with severe poorly controlled mixed sleep-disordered breathing in the absence of renal or heart failure. Flow-independent addition of incremental concentrations of carbon dioxide during sleep. The respiratory disturbance index before treatment was 66 +/- 14.5 events per hour of sleep, with a nocturnal desaturation low of 84.6% +/- 10.1%. Residual respiratory disturbance index on best treatment was 43 +/- 9 events per hour of sleep. There was an immediate (<1 minute) response to the addition of 0.5% to 1% carbon dioxide, and minimal changes were required to be made across the night. There was no discomfort, shortness of breath, palpitations, headache, or significant increase in respiratory or heart rate. The residual respiratory disturbance index on carbon dioxide, scored irrespective of desaturations, was in the normal range (< 5 / hour of sleep). Two subjects had a second night at the concentration of carbon dioxide determined to be efficacious, with no required concentration change. No adverse effects on overall sleep architecture were noted. Low concentrations of carbon dioxide added to conventional positive airway pressure effectively control severe treatment-resistant mixed obstructive and central sleep-disordered breathing.

The ocean is one of the most extensive ecosystems on Earth and can absorb large amounts of carbon dioxide. Changes in seawater carbon dioxide concentrations are one of the most important factors affecting marine ecosystems. Excess carbon dioxide can lead to ocean acidification, threatening the stability of marine ecosystems and species diversity. Dissolved carbon dioxide detection in seawater has great scientific significance. Conducting online monitoring of seawater carbon dioxide can help to understand the health status of marine ecosystems and to protect marine ecosystems. Current seawater detection equipment is large and costly. This study designed a low-cost infrared carbon dioxide detection system based on molecular theory. Using the HITRAN database, the absorption spectra and coefficients of carbon dioxide molecules under different conditions were calculated and derived, and a wavelength of 2361 cm-1 was selected as the measurement channel for carbon dioxide. In addition, considering the interference effect of direct light, an infrared post-splitting method was proposed to eliminate the interference of light and improve the detection accuracy of the system. The system was designed for the online monitoring of carbon dioxide in seawater, including a peristaltic pump to accelerate gas-liquid separation, an optical path structure, and carbon dioxide concentration inversion. The experimental results showed that the standard deviation of the gas test is 3.05, the standard deviation of the seawater test is 6.04, and the error range is within 20 ppm. The system can be flexibly deployed and has good stability and portability, which can meet the needs of the online monitoring of seawater carbon dioxide concentration.