scholarly journals Use of Multiple Low Cost Carbon Dioxide Sensors to Measure Exhaled Breath Distribution with Face Mask Type and Wearing Behaviour

Sensors ◽  
2021 ◽  
Vol 21 (18) ◽  
pp. 6204
Author(s):  
Naveed Salman ◽  
Muhammad Waqas Khan ◽  
Michael Lim ◽  
Amir Khan ◽  
Andrew H. Kemp ◽  
...  
Keyword(s):  
Carbon Dioxide ◽  
Low Cost ◽  
Co2 Concentration ◽  
Face Mask ◽  
Base Station ◽  
Exhaled Breath ◽  
Co2 Sensor ◽  
Improper Use ◽  
The Face ◽  
Carbon Dioxide Co2

The use of cloth face coverings and face masks has become widespread in light of the COVID-19 pandemic. This paper presents a method of using low cost wirelessly connected carbon dioxide (CO2) sensors to measure the effects of properly and improperly worn face masks on the concentration distribution of exhaled breath around the face. Four types of face masks are used in two indoor environment scenarios. CO2 as a proxy for exhaled breath is being measured with the Sensirion SCD30 CO2 sensor, and data are being transferred wirelessly to a base station. The exhaled CO2 is measured in four directions at various distances from the head of the subject, and interpolated to create spatial heat maps of CO2 concentration. Statistical analysis using the Friedman’s analysis of variance (ANOVA) test is carried out to determine the validity of the null hypotheses (i.e., distribution of the CO2 is same) between different experiment conditions. Results suggest CO2 concentrations vary little with the type of mask used; however, improper use of the face mask results in statistically different CO2 spatial distribution of concentration. The use of low cost sensors with a visual interpolation tool could provide an effective method of demonstrating the importance of proper mask wearing to the public.

scholarly journals Correlation of Respiratory Aerosols and Metabolic Carbon Dioxide

2021 ◽  
Vol 13 (21) ◽  
pp. 12203
Author(s):  
Niklas Kappelt ◽  
Hugo Savill Russell ◽  
Szymon Kwiatkowski ◽  
Alireza Afshari ◽  
Matthew Stanley Johnson
Keyword(s):  
Carbon Dioxide ◽  
Oral Fluid ◽  
Low Cost ◽  
Co2 Concentration ◽  
Transmission Route ◽  
Viral Loads ◽  
Co2 Concentrations ◽  
Carbon Dioxide Co2 ◽  
The Individual ◽  
Metabolic Carbon

Respiratory aerosols from breathing and talking are an important transmission route for viruses, including severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Previous studies have found that particles with diameters ranging from 10 nm to 145 μm are produced from different regions in the respiratory system and especially smaller particles can remain airborne for long periods while carrying viral RNA. We present the first study in which respiratory aerosols have been simultaneously measured with carbon dioxide (CO2) to establish the correlation between the two concentrations. CO2 concentrations are easily available through low-cost sensors and could be used to estimate viral exposure through this correlation, whereas source-specific aerosol measurements are complicated and not possible with low-cost sensors. The increase in both respiratory aerosols and CO2 was linear over ten minutes in a 2 m3 chamber for all participants, suggesting a strong correlation. On average, talking released more particles than breathing, with 14,600 ± 16,800 min−1 (one-σ standard deviation) and 6210 ± 5630 min−1 on average, respectively, while CO2 increased with 139 ± 33 ppm min−1 during talking and 143 ± 29 ppm min−1 during breathing. Assuming a typical viral load of 7×106 RNA copies per mL of oral fluid, ten minutes of talking and breathing are estimated to produce 1 and 16 suspended RNA copies, respectively, correlating to a CO2 concentration of around 1800 ppm in a 2 m3 chamber. However, viral loads can vary by several orders of magnitude depending on the stage of the disease and the individual. It was therefore concluded that, by measuring CO2 concentrations, only the number and volume concentrations of released particles can be estimated with reasonable certainty, while the number of suspended RNA copies cannot.

scholarly journals Correlation of Respiratory Aerosols with Metabolic Carbon Dioxide 

2021 ◽  
Author(s):  
Niklas Kappelt ◽  
Hugo S. Russell ◽  
Szymon Kwiatkowski ◽  
Alireza Afshari ◽  
Matthew S. Johnson
Keyword(s):  
Carbon Dioxide ◽  
Low Cost ◽  
Co2 Concentration ◽  
Strong Argument ◽  
Wide Acceptance ◽  
Co2 Concentrations ◽  
Chamber Study ◽  
Carbon Dioxide Co2 ◽  
Indoor Spaces ◽  
Metabolic Carbon

Abstract Respiratory Aerosols from breathing and talking have found wide acceptance as a transmission route for viruses such as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Previous studies have found particles with diameters ranging from 10 nm to 145 µm, exhibited from different regions in the respiratory system. We present the first chamber study, in which respiratory aerosols have been simultaneously measured with carbon dioxide (CO2) to establish the correlation between the two concentrations. CO2 concentrations are easily available through low-cost sensors and could be used to estimate viral exposure through this correlation, whereas source-specific aerosol measurements are complicated and not possible with low cost sensors. The increase in both PM10 and CO2 was linear over ten minutes in a 2 m3 chamber for all participants, suggesting a strong correlation. On average, talking released more particles than breathing, with 14,600 ± 16,800 min-1 (one-σ standard deviation) and 6,210 ± 5,630 min-1 on average, respectively, while CO2 increased with 139 ± 33 ppm min-1 during talking and 143 ± 29 ppm min-1 during breathing. Assuming a typical viral load of 7 × 106 RNA copies per ml of oral fluid, ten minutes of talking and breathing are estimated to produce 7 and 16 suspended RNA copies, respectively, correlating to a CO2 concentration of around 1.800 ppm in a 2 m3 chamber. This provides a strong argument for keeping indoor spaces well ventilated and shows how CO2 concentrations, measured with low-cost sensors, could be used as a proxy for viral exposure.

scholarly journals IoT and Deep Learning Based Approach for Rapid Screening and Face Mask Detection for Infection Spread Control of COVID-19

2021 ◽  
Vol 11 (8) ◽  
pp. 3495
Author(s):  
Shabir Hussain ◽  
Yang Yu ◽  
Muhammad Ayoub ◽  
Akmal Khan ◽  
Rukhshanda Rehman ◽  
...  
Keyword(s):  
Deep Learning ◽  
Low Cost ◽  
Face Mask ◽  
World Health ◽  
Rapid Screening ◽  
Screening System ◽  
Source Of Infection ◽  
The Face ◽  
Health Organization ◽  
Vaccine Distribution

The spread of COVID-19 has been taken on pandemic magnitudes and has already spread over 200 countries in a few months. In this time of emergency of COVID-19, especially when there is still a need to follow the precautions and developed vaccines are not available to all the developing countries in the first phase of vaccine distribution, the virus is spreading rapidly through direct and indirect contacts. The World Health Organization (WHO) provides the standard recommendations on preventing the spread of COVID-19 and the importance of face masks for protection from the virus. The excessive use of manual disinfection systems has also become a source of infection. That is why this research aims to design and develop a low-cost, rapid, scalable, and effective virus spread control and screening system to minimize the chances and risk of spread of COVID-19. We proposed an IoT-based Smart Screening and Disinfection Walkthrough Gate (SSDWG) for all public places entrance. The SSDWG is designed to do rapid screening, including temperature measuring using a contact-free sensor and storing the record of the suspected individual for further control and monitoring. Our proposed IoT-based screening system also implemented real-time deep learning models for face mask detection and classification. This module classified individuals who wear the face mask properly, improperly, and without a face mask using VGG-16, MobileNetV2, Inception v3, ResNet-50, and CNN using a transfer learning approach. We achieved the highest accuracy of 99.81% while using VGG-16 and the second highest accuracy of 99.6% using MobileNetV2 in the mask detection and classification module. We also implemented classification to classify the types of face masks worn by the individuals, either N-95 or surgical masks. We also compared the results of our proposed system with state-of-the-art methods, and we highly suggested that our system could be used to prevent the spread of local transmission and reduce the chances of human carriers of COVID-19.

scholarly journals Comparing the Use of High- to Low-Cost Black Carbon and Carbon Dioxide Sensors for Characterizing On-Road Diesel Truck Emissions

Sensors ◽  
2020 ◽  
Vol 20 (23) ◽  
pp. 6714
Author(s):  
Rebecca A. Sugrue ◽  
Chelsea V. Preble ◽  
Thomas W. Kirchstetter
Keyword(s):  
Carbon Dioxide ◽  
Black Carbon ◽  
Emission Factor ◽  
Lower Cost ◽  
Low Cost ◽  
Ambient Air ◽  
Source Characterization ◽  
Ambient Conditions ◽  
Heavy Duty Diesel ◽  
Carbon Dioxide Co2

The exhaust plume capture method is a commonly used approach to measure pollutants emitted by in-use heavy-duty diesel trucks. Lower cost sensors, if used in place of traditional research-grade analyzers, could enable wider application of this method, including use as a monitoring tool to identify high-emitting trucks that may warrant inspection and maintenance. However, low-cost sensors have for the most part only been evaluated under ambient conditions as opposed to source-influenced environments with rapidly changing pollutant concentrations. This study compared black carbon (BC) emission factors determined using different BC and carbon dioxide (CO2) sensors that range in cost from $200 to $20,000. Controlled laboratory experiments show that traditional zero and span steady-state calibration checks are not robust indicators of sensor performance when sampling short duration concentration peaks. Fleet BC emission factor distributions measured at two locations at the Port of Oakland in California with 16 BC/CO2 sensor pairs were similar, but unique sensor pairs identified different high-emitting trucks. At one location, the low-cost PP Systems SBA-5 agreed on the classification of 90% of the high emitters identified by the LI-COR LI-7000 when both were paired with the Magee Scientific AE33. Conversely, lower cost BC sensors when paired with the LI-7000 misclassified more than 50% of high emitters when compared to the AE33/LI-7000. Confidence in emission factor quantification and high-emitter identification improves with larger integrated peak areas of CO2 and especially BC. This work highlights that sensor evaluation should be conducted under application-specific conditions, whether that be for ambient air monitoring or source characterization.

Design, Modeling and Simulation of CMOS-MEMS Piezoresistive Cantilever Based Carbon Dioxide Gas Sensor for Capnometry

2011 ◽  
Vol 403-408 ◽  
pp. 3769-3774 ◽  
Author(s):  
Asif Mirza ◽  
Nor Hisham Hamid ◽  
Mohd Haris Md Khir ◽  
Khalid Ashraf ◽  
M.T. Jan ◽  
...  
Keyword(s):  
Carbon Dioxide ◽  
Modeling And Simulation ◽  
Low Cost ◽  
Cmos Technology ◽  
Simulation Software ◽  
Dynamic Mode ◽  
Fully Differential ◽  
Carbon Dioxide Gas ◽  
Carbon Dioxide Co2 ◽  
Relative Change

This paper reports design, modeling and simulation of MEMS based sensor working in dynamic mode with fully differential piezoresistive sensing for monitoring the concentration of exhaled carbon dioxide (CO2) gas in human breath called capnometer. CO2 being a very important biomarker, it is desirable to extend the scope of its monitoring beyond clinical use to home and ambulatory services. Currently the scope of capnometers and its adaption is limited by high cost, large size and high power consumption of conventional capnometers . In recent years, MEMS based micro resonant sensors have received considerable attention due to their potential as a platform for the development of many novel physical, chemical, and biological sensors with small size, low cost and low power requirements. The sensor is designed using 0.35 micron CMOS technology. CoventorWare and MATLAB have been used as simulation software. According to the developed model and simulation results the resonator has resonant frequency 57393 Hz and mass sensitivity of 3.2 Hz/ng. The results show that the longitudinal relative change of resistance is 0.24%/µm while the transverse relative change of resistance is -0.03%/µm.

S. I. Engine Pollution Control Using Low-Cost Palletized Catalytic Converter

Volume 2 ◽  
2004 ◽  
Author(s):  
Madhuri Jakkaraju ◽  
Vasudha Patri
Keyword(s):  
Carbon Dioxide ◽  
Carbon Monoxide ◽  
Pollution Control ◽  
Noble Metals ◽  
Fossil Fuel ◽  
Catalytic Converter ◽  
Low Cost ◽  
Hydrocarbon Emissions ◽  
Oxides Of Nitrogen ◽  
Carbon Dioxide Co2

I. C. Engines consume large amounts of fossil fuel emitting harmful pollutants like carbon monoxide (CO), unburnt hydrocarbons (UBHC), and oxides of nitrogen (NOx). By using a catalytic converter (CC), the carbon monoxide, hydrocarbon emissions can be transformed into less harmful carbon dioxide (CO2) & water vapor (H2O). Currently available CC’s are using costly noble metals like platinum (pt), palladium (pd), rhodium (rh) etc., hence making them expensive. This paper deals with the use of low-cost palletized silver coated alumina as the catalyst element in a CC. In this study, alumina and silver were used in the ratio of 10:1. All tests have been conducted on a stationary S.I. Engine at a constant speed of 1500 r.p.m with and without CC. Also, the performance of the palletized CC in combination with promoters like Bismuth, Cerium and Lanthanum was tested which have shown better results than silver alone as the coating element. It has been experimentally determined that the CO emissions have dropped from 7.25 (% vol) to 3.03(% vol) and the HC values have reduced from 350 ppm to 190 ppm.

Plasma Decomposition of Carbon Dioxide: Simulations and Experiments

2019 ◽  
Author(s):  
Kamau Wright ◽  
Robert Galvez
Keyword(s):  
Carbon Dioxide ◽  
Co2 Concentration ◽  
Plasma Discharges ◽  
Electrical Parameters ◽  
Plasma System ◽  
Process Gas ◽  
Plasma Decomposition ◽  
Carbon Dioxide Co2 ◽  
Co2 Decomposition ◽  
Over Time

Abstract Simulations and experiments are conducted to model, simulate, test and demonstrate the effect of plasma discharges on decomposition of carbon dioxide (CO2). A pin-to-plane discharge is employed in gas samples containing CO2. A high voltage plasma system is used which was previously shown to be able to decrease CO2 concentration in gas samples. The discharge is modeled and described, including monitoring electrical parameters such as current and voltage. The present study investigated plasma decomposition of carbon dioxide experimentally, and through simulation. A plasma micro-discharge was utilized to better understand plasma-CO2 interactions. Enhancements are suggested to help increase the efficiency and yield of the plasma-CO2 decomposition process. Gas samples are analyzed over time using a CO2 meter.

scholarly journals Six years of atmospheric CO<sub>2</sub> observations at Mt. Fuji recorded with a battery-powered measurement system

2017 ◽  
Vol 10 (2) ◽  
pp. 667-680 ◽  
Author(s):  
Shohei Nomura ◽  
Hitoshi Mukai ◽  
Yukio Terao ◽  
Toshinobu Machida ◽  
Yukihiro Nojiri
Keyword(s):  
Carbon Dioxide ◽  
Measurement System ◽  
Measurement Data ◽  
Co2 Concentration ◽  
Measurement Unit ◽  
Sources And Sinks ◽  
Charging System ◽  
Carbon Dioxide Co2 ◽  
Stability And Accuracy ◽  
Working Standards

Abstract. We developed a battery-powered carbon dioxide (CO2) measurement system for monitoring at the summit of Mt. Fuji (3776 m a.s.l.), which experiences very low temperatures (below −20 °C) and severe environmental conditions without access to gridded electricity for 10 months (from September to June). Our measurement system used 100 batteries to run the measurement unit during these months. These batteries were charged during the 2-month summer season when gridded electricity was available, using a specially designed automatic battery-charging system. We installed this system in summer 2009 at the Mt. Fuji weather station; observations of atmospheric CO2 concentration were taken through December 2015. Measurements were never interrupted by a lack of battery power except for two cases in which lightning damaged a control board. Thus we obtained CO2 data during about 94 % of the 6-year period. Analytical performances (stability and accuracy) were better than 0.1 ppm, as tested by checking working standards and comparisons with flask sampling.Observational results showed that CO2 mole fractions at Mt. Fuji demonstrated clear seasonal variation. The trend and the variability of the CO2 growth rate observed at Mt. Fuji were very similar to those of the Mauna Loa Observatory (MLO). Seasonally, the concentration at Mt. Fuji was 2–10 ppm lower in summer and 2–12 ppm higher in winter than those at MLO. The lower concentrations at Mt. Fuji in summer are mainly attributed to episodes of air mass transport from Siberia or China, where CO2 is taken up by the terrestrial biosphere. On the other hand, the relatively higher concentrations in winter seem to reflect the high percentage of air masses originating from China or Southeast Asia during this period, which carry increased anthropogenic carbon dioxide. These results show that Mt. Fuji is not very influenced by local sources but rather by the sources and sinks over a very large region.Thus we conclude that, as this system could provide stable measurement data with relatively easy operation for 6 years at Mt. Fuji, it could be a useful monitoring technique for remote background sites elsewhere.

scholarly journals Towards Low Cost and Low Temperature Capacitive CO2 Sensors Based on Amine Functionalized Silica Nanoparticles

Nanomaterials ◽  
2019 ◽  
Vol 9 (8) ◽  
pp. 1097 ◽  
Author(s):  
Jamila Boudaden ◽  
Armin Klumpp ◽  
Hanns-Erik Endres ◽  
Ignaz Eisele
Keyword(s):  
Silica Nanoparticles ◽  
Low Cost ◽  
Inorganic Materials ◽  
Organic Polymer ◽  
Impregnation Method ◽  
Inorganic Particles ◽  
Co2 Sensor ◽  
Sensing Material ◽  
Carbon Dioxide Co2 ◽  
Thermal Stability Of

Hybrid materials based on inorganic particles and an organic polymer were developed and used as an efficient sensing material for carbon dioxide (CO2). The sensing material consists of fumed silica that is functionalized with an organic polymer, polyethylenimine, by means of the impregnation method. The organic polymer is effectively immobilized around the silica nanoparticles and confirmed by infrared spectroscopy. Thermogravimetric analysis proves the thermal stability of the sensing material. CO2 capacitive sensors operating at temperatures lower than 70 °C were fabricated by depositing a thin layer of hybrid sensing material on interdigitated gold electrodes. Impedance spectroscopy explored the sensing capability of the hybrid organic–inorganic material towards CO2 in the presence of different relative humidity levels, as well as its stability and reversibility. This strategy to couple organic and inorganic materials as a sensing layer for CO2 paves the way for the design of a low-cost CO2 sensor.

scholarly journals Determination of Dissolved CO2 Concentration in Culture Media: Evaluation of pH Value and Mathematical Data

Processes ◽  
2020 ◽  
Vol 8 (11) ◽  
pp. 1373
Author(s):  
Amir Izzuddin Adnan ◽  
Mei Yin Ong ◽  
Saifuddin Nomanbhay ◽  
Pau Loke Show
Keyword(s):  
Carbon Dioxide ◽  
Ph Value ◽  
Culture Media ◽  
Co2 Concentration ◽  
Co2 Solubility ◽  
Greenhouse Gasses ◽  
Dipotassium Phosphate ◽  
The Difference ◽  
Carbon Dioxide Co2

Carbon dioxide is the most influential gas in greenhouse gasses and its amount in the atmosphere reached 412 µmol/mol in August 2020, which increased rapidly, by 48%, from preindustrial levels. A brand-new chemical industry, namely organic chemistry and catalysis science, must be developed with carbon dioxide (CO2) as the source of carbon. Nowadays, many techniques are available for controlling and removing carbon dioxide in different chemical processes. Since the utilization of CO2 as feedstock for a chemical commodity is of relevance today, this study will focus on how to increase CO2 solubility in culture media used for growing microbes. In this work, the CO2 solubility in a different medium was investigated. Sodium hydroxide (NaOH) and monoethanolamine (MEA) were added to the culture media (3.0 g/L dipotassium phosphate (K2HPO4), 0.2 g/L magnesium chloride (MgCl2), 0.2 g/L calcium chloride (CaCl2), and 1.0 g/L sodium chloride (NaCl)) for growing microbes in order to observe the difference in CO2 solubility. Factors of temperature and pressure were also studied. The determination of CO2 concentration in the solution was measured by gas analyzer. The result obtained from optimization revealed a maximum CO2 concentration of 19.029 mol/L in the culture media with MEA, at a pressure of 136.728 kPa, operating at 20.483 °C.

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