Carbon Monoxide Sensor Research Articles

High-performance amperometric carbon monoxide sensor based on a xerogel-modified PtCr/C microelectrode

An amperometric biosensor based on a xerogel-modified PtCr/C microelectrode was developed for direct carbon monoxide (CO) detection. The effects of elemental Cr on the structural and electronic characteristics of the binary PtCr/C catalyst were characterized using various analytical techniques. Differential pulse voltammetry and amperometric measurements were performed to evaluate the electrocatalytic performance of the fabricated electrodes with respect to CO oxidation. The modified PtCr/C catalyst showed significantly improved electrocatalytic activity for CO oxidation, including a low applied potential of 0.3 V (vs. Ag/AgCl, high sensitivity of 12.5 nA μM−1 (standard deviation [SD] 0.52 nA μM−1)), excellent surface sensitivity of 726.6 nA μM−1 cm−2 (SD 30.4 nA μM−1 cm−2), and sufficiently high CO selectivity in the presence of other common metabolites. Modification of the PtCr/C-alloy catalyst surface with a fluorinated xerogel membrane minimized the effects of interfering species. Under optimal conditions, the xerogel-modified PtCr/C microelectrode exhibited a CO sensitivity of 8.82 nA μM−1 (SD 0.08 nA μM−1) and corresponding selectivity (logKCO,iamp) of < −5, −2.82 (SD 0.38), −3.16 (SD 0.03), − 2.57 (SD 0.05), −0.99 (SD 0.01), −2.02 (SD 0.01), and −1.79 (SD 0.05) for nitrite, ascorbic acid, uric acid, acetaminophen, dopamine, hydrogen peroxide, and nitric oxide. The xerogel-modified PtCr/C sensor was used to measure the CO directly generated on the surface of a living kidney in real time, and a CO concentration of 0.74 μM was estimated. Thus, our sensor can serve as a novel platform for developing high-performance electrochemical sensors suitable for practical applications.

Neonatal resuscitation practices in Italy: a survey of the Italian Society of Neonatology (SIN) and the Union of European Neonatal and Perinatal Societies (UENPS)

BackgroundProviding appropriate care at birth remains a crucial strategy for reducing neonatal mortality and morbidity. We aimed to evaluate the consistency of practice and the adherence to the international guidelines on neonatal resuscitation in level-I and level-II Italian birth hospitals.MethodsThis was a cross-sectional electronic survey. A 91-item questionnaire focusing on current delivery room practices in neonatal resuscitation was sent to the directors of 418 Italian neonatal facilities.ResultsThe response rate was 61.7% (258/418), comprising 95.6% (110/115) from level-II and 49.0% (148/303) from level-I centres. In 2018, approximately 300,000 births occurred at the participating hospitals, with a median of 1664 births/centre in level-II and 737 births/centre in level-I hospitals. Participating level-II hospitals provided nasal-CPAP and/or high-flow nasal cannulae (100%), mechanical ventilation (99.1%), HFOV (71.0%), inhaled nitric oxide (80.0%), therapeutic hypothermia (76.4%), and extracorporeal membrane oxygenation ECMO (8.2%). Nasal-CPAP and/or high-flow nasal cannulae and mechanical ventilation were available in 77.7 and 21.6% of the level-I centres, respectively. Multidisciplinary antenatal counselling was routinely offered to parents at 90.0% (90) of level-II hospitals, and 57.4% (85) of level-I hospitals (p < 0.001). Laryngeal masks were available in more than 90% of participating hospitals while an end-tidal CO2 detector was available in only 20%. Significant differences between level-II and level-I centres were found in the composition of resuscitation teams for high-risk deliveries, team briefings before resuscitation, providers qualified with full resuscitation skills, self-confidence, and use of sodium bicarbonate.ConclusionsThis survey provides insight into neonatal resuscitation practices in a large sample of Italian hospitals. Overall, adherence to international guidelines on neonatal resuscitation was high, but differences in practice between the participating centres and the guidelines exist. Clinicians and stakeholders should consider this information when allocating resources and planning perinatal programs in Italy.

Carbon Monoxide Sensor Based on Printed ZnO

This work describes the fabrication of a Carbon monoxide (CO) sensor based on a Zinc oxide (ZnO) Schottky diode that can detect CO at low concentrations as low as one part per million (ppm) at room temperature. Different additive microfabrication techniques are used to fabricate the devices. A precisely controlled fabrication is enabled by employing a microcantilever ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\mu \text{C}$ </tex-math></inline-formula> ) printing system. The fully printed sensor has a high sensitivity of 23.7% towards CO at room temperature. The height of the Schottky barrier significantly influences the response of the device. Furthermore, all sensors specificity was analyzed for some of the gases, and volatile organic compounds (VOCs) found in breath. The fully printed device exhibited a negative temperature coefficient of resistivity for temperatures ranging from 50 to 300 Kelvin. This work aims to develop a proof-of-concept for enhancing room temperature sensing by developing a Schottky sensor.

IoT Based Emergency Button for Women Safety

Abstract: Fundamental to IoT is the instant collaboration that happens between these smart devices. The beauty behind having a network of interconnected devices is that they can all work together to provide real solutions that are much greater than the sum of their parts. IOT based products are always connected and constantly communicating with each other. They regularly exchange information using wired and wireless networks, which helps make our lives easier and safer. When IoT based smart home security systems are used to safeguard our home or possessions, it’s akin to having our favorite reliable friend dutifully watching over our home or pets in our absence. Except it’s actually way better than that, because unlike our well-meaning friend or neighbor, smart home security systems are always present and are ready to instantly alert us of any signs of danger. Smart products, like Nest Lab’s smoke and carbon monoxide alarm, sounds an alert when it detects high levels of CO, and then warns us of the location of the danger. It’s no wonder that Google acquired Nest Labs for a whopping $3.2 billion! Other companies like Canary offer connected smart home security systems that are now a part of a growing trend: using IoT technology to create safety solutions to protect what’s most valuable to us.

Adaptive Air Quality Sensing using Machine Learning

Abstract: Air pollution is a worldwide problem having impacts on both local and global scales. According to the World Health Organization (WHO), air pollution causes 7 million deaths every year, with 4.2 million attributed to exposure to outdoor air pollution. Compared to the reference methods defined in the Air Quality Directive, the use of low-cost air quality sensors for monitoring ambient air pollution would reduce air pollution monitoring costs and would also allow larger spatial coverage especially in remote areas where monitoring with traditional facilities is uneasy. Theses multi-sensors were either calibrated against standard gas mixtures or using artificial neural network under field conditions. The later method resulted in mixed results either satisfactory for short periods or generally weak for longer data series. This project mainly focuses on the adaptive calibration of the low-cost sensors using the trained machine learning model. The performances of several field calibration methods for low-cost sensors, including linear/multi linear regression and supervised learning techniques will be compared. A cluster of ozone, nitrogen dioxide, nitrogen monoxide, carbon monoxide and carbon dioxide sensors will be operated. Subsequently, the accuracy of the predicted values will be evaluated for about a period. These predicted values are fed through the training model and the model will run accordingly and it will adapt all the error situations. This will be useful to the automobile industry in the current situation for smoke emission control and also for many refinery industries in which low-cost sensors can be used with the following modelling for the higher accuracy. This would reduce the cost and also yields more accuracy beyond the varying situation. Keywords: 1) Low-Cost Sensors (LCS) 2) Internet of Things (IoT)

Camping-related carbon monoxide poisoning: Knowledge and risk behaviours among young Saudi campers.

To evaluate the Saudi campers' knowledge and the applied safety practices regarding carbon monoxide poisoning during camping activities. The cross-sectional questionnaire-based study was conducted from December 1, 2018, to February 1, 2019, in Riyadh, Saudi Arabia, and comprised young male campers from recreational camps in the northern parts of the city. Data was collected from the participants regarding socio-demographic characteristics, knowledge regarding carbon monoxide poisoning, the applied safety measures to prevent carbon monoxide poisoning and the dealing with carbon monoxide poisoning during camping activities. Data was analysed using SPSS 22. There were 235 male subjects with mean age 24.47±1.139 years (range: 21-32 years). Of the total, 50(21.3%) participants had received civil defence education or training. Overall, 137(58.3%) participants had a good mean knowledge score, and 157(66.8%) participants had a good mean practice score for applying healthy measures in preventing and managing carbon monoxide poisoning. As a preventive measure against carbon monoxide poisoning, the use of carbon monoxide detectors was valued by 107(45.5%) participants. Having civil defence training, having a monthly income >10,000 Saudi Riyals, and having a good knowledge score were the elements that had significant association with the choice related to carbon monoxide detector usage. The campers had relatively high knowledge regarding carbon monoxide poisoning, but this knowledge was not fully translated into good health practice.

Comparison of four low-level carbon monoxide alarms suitable for home use or when traveling

Introduction/Background: Interest in carbon monoxide (CO) alarms that are more sensitive than is required for standard residential CO alarms is growing, as reflected by increased marketing of “low-level” alarms capable of measuring CO levels as low as 10 PPM. At the same time, publicity surrounding CO poisoning events among travelers in lodging facilities has stimulated interest in travel CO alarms. We sought to evaluate four low-level alarms that could be used in the home and especially when traveling. Materials/Methods: Two each of four brands of low-level alarms (CO Experts, Forensics, Kidde, and Sensorcon) were acquired by retail purchase and tested. The eight alarms were simultaneously exposed in an environment with a slowly increasing level of CO from indoor burning of charcoal briquets. CO levels displayed on the alarms were recorded once per minute. Activation of preset alerts on the alarms were noted. Finally, alarms were compared for ease of use and features available. Results: All brands of alarms measured CO similarly over the range from 10-120 PPM. All alarms performed as claimed by their manufacturers, both regarding range of CO reported and preset alert activation. Each alerted at CO levels below that required by the Underwriters Laboratories 2034 Standard. Summary/Conclusions: Since all low-level CO alarms tested measured CO similarly, consumers seeking a low-level CO alarm for use while traveling should base their decision on features desired and price. There are definite differences between the alarms tested, in terms of features, expected durability, ease of operation and price. 10.22462/05.06.2022.4

Severe carbon monoxide poisonings in scuba divers: Asia-Pacific cases and causation

Aim: Reports of fatal incidents in recreational scuba divers from carbon monoxide (CO) poisoning are rare. This study aimed to identify scuba fatalities in the Asia-Pacific region caused by breathing-gas contamination to better understand the likely sources of contamination and reduce such preventable deaths. Methods: A hand search of Project Stickybeak reports, subsequent Australian fatality series reports, and of published New Zealand diving fatality reports and associated data was conducted, as well as key word searches of the National Coronial Information System for scuba fatalities in Australia and New Zealand. Cases identified were matched with the Australasian Diving Safety Foundation diving fatality database. Available reports were examined. Results: Four scuba deaths resulting from CO poisoning were identified from 645 scuba fatalities, including one report from each of Australia, New Zealand, Singapore, and the Maldives. A near-fatal incident was also identified in Indonesia. Two of the fatal incidents and the near-fatal incident involved internal combustion engine exhaust gases from the compressor system or elsewhere entering the air intake. Two deaths likely resulted from combustion within compressor systems. Conclusions: Scuba fatalities from CO poisoning are uncommon, albeit likely under-reported. Sources of CO include exhaust gases entering the compressor and CO production by pyrolysis or gasification within the compressor or its filter system. Preventive measures include proper installation (including positioning of the air intake relative to combustion exhaust), appropriate maintenance, fitting of pressure-maintaining valves and avoidance of overheating. Formal training of compressor operators, improved diver education, mandatory requirements for installation compliance assessments, safety inspections, and the use of carbon monoxide alarms are recommended.

Pediatric Advanced Life Support in a Neonatal Context.

Pediatric Advanced Life Support in a Neonatal Context.

Development of a Fire Smoke Detector that Satisfies the UL 268 (7th Edition) Fire Sensitivity Tests

In this study, we developed a multi-sensor fire detector that satisfies the revised requirements of the cooking nuisance test, polyurethane foam fire test, and polyurethane foam smoldering smoke test of UL 268, and the special program, UL 268 (7th edition), at the Underwriters Laboratories (UL) headquarters in Northbrook, Illinois, United States. The fire detection algorithm was confirmed using the "Research Preliminary Test" program. Our fire detector was evaluated in a dark room with a smoke detector consisting of photoelectric, carbon monoxide, and ionization sensors, and was mounted on a board. In addition, the upper case of the detector is designed to have sufficient space on its top and side surfaces to allow the flow of air and combustion gases. As a result, in the polyurethane foam fire test, the detector triggered an alarm (within 3 min) before the smoke concentration reached 5%/ft (after 3-4 min); thus, satisfying the requirements of the UL 268 polyurethane foam fire test. In the polyurethane foam smoldering smoke test, the detector was operated for 22-26 min before the smoke concentration reached 12%/ft (after 26 min), thus satisfying the requirements of the UL 268 polyurethane foam smoldering smoke test. Lastly, in the cooking nuisance test, the detector was operated for 16-18 min before the smoke concentration reached 1.5%/ft (after 16 min), thus satisfying the requirements of the UL 268 cooking nuisance test. It can be concluded that the results of this study will be useful for the developers of similar products who want to obtain UL certification in the future.

Design of a Surface Plasmon Resonance CO Sensor.

Carbon monoxide (CO) is a highly toxic gas, which can cause death if it is inhaled in small quantities for a long time or in large quantities for a short time. Since this gas can be lethal, it is essential to detect it from minute to large concentrations. Our study consists of the design of a superficial plasmonic resonance (SPR) CO sensor of tiny dimensions which is capable of giving an immediate response at different concentrations. It is designed to work at different heights above sea level since the refractive index of this gas depends on a mixture with air and the air pressure. Due to its low weight and tiny dimensions, it is ideal for space travel or on airplanes. The results show a high resolution and sensitivity (~10−5 RIU of resolution and a sensitivity of 13.51–81.26 RIU−1).

Highly Sensitive Carbon Monoxide Sensor Element with Wide-Range Humidity Resistance by Loading Pd Nanoparticles on SnO2 Surface

To develop a highly sensitive carbon monoxide (CO) sensor with a wide range of humidity resistance, we focused on the Pd loading method on SnO2 nanoparticles and the thickness of the sensing layer. The Pd nanoparticles were loaded on the SnO2 surface using the surface immobilization method (SI-Pd/SnO2) and the colloidal protection method (CP-Pd/SnO2). The XPS analysis indicated that the Pd nanoparticles were a composite of PdO and Pd, regardless of the loading method. According to the evaluation of the electrical properties at 350 °C, the CO response in a humid atmosphere and the resistance toward humidity change using CP-Pd/SnO2 were higher than those using SI-Pd/SnO2, even though the Pd loading amount of SI-Pd/SnO2 was slightly larger than that of CP-Pd/SnO2. In addition, Pd/SnO2 prepared via the CP method with a thinner sensing layer showed a higher sensor response and greater stability to humidity changes at 300 °C, even though the humidity change influenced the CO response at 250 and 350 °C. Thus, the overall design of the surface Pd, including size, dispersity, and oxidation state, and the sensor fabrication, that is, the thickness of the sensing layer, offer a high-performance semiconductor-type CO gas sensor with a wide range of humidity resistance.

Evaluating the Performance of Using Low-Cost Sensors to Calibrate for Cross-Sensitivities in a Multipollutant Network.

As part of our low-cost sensor network, we colocated multipollutant monitors containing sensors for particulate matter, carbon monoxide, ozone, nitrogen dioxide, and nitrogen monoxide at a reference field site in Baltimore, MD, for 1 year. The first 6 months were used for training multiple regression models, and the second 6 months were used to evaluate the models. The models produced accurate hourly concentrations for all sensors except ozone, which likely requires nonlinear methods to capture peak summer concentrations. The models for all five pollutants produced high Pearson correlation coefficients (r > 0.85), and the hourly averaged calibrated sensor and reference concentrations from the evaluation period were within 3-12%. Each sensor required a distinct set of predictors to achieve the lowest possible root-mean-square error (RMSE). All five sensors responded to environmental factors, and three sensors exhibited cross-sensitives to another air pollutant. We compared the RMSE from models (NO2, O3, and NO) that used colocated regulatory instruments and colocated sensors as predictors to address the cross-sensitivities to another gas, and the corresponding model RMSEs for the three gas models were all within 0.5 ppb. This indicates that low-cost sensor networks can yield useable data if the monitoring package is designed to comeasure key predictors. This is key for the utilization of low-cost sensors by diverse audiences since this does not require continual access to regulatory grade instruments.

Electrochemical gas sensing module combined with Unmanned Aerial Vehicles for air quality monitoring

The issue of air pollution and the monitoring of air quality is a very serious problem in today's society. This problem is basically caused by human in activities related to industry, construction, transport, etc. High pollution values have become an important risk factor for the health of citizens. Measuring pollution for air quality control is not an easy task, as it requires highly specialized equipment, working under special conditions, which makes reference systems bulky and costly installations. To this must be added the disadvantages of measuring in areas with little or no accessibility. The aim of this work is to develop an unmanned aerial vehicle (UAV) equipped with low-cost sensors to monitor air quality both on the move and stationary in a position that is difficult to access. It is equipped with sensors for carbon monoxide (CO), ozone (O3), nitrogen monoxide (NO) and nitrogen dioxide (NO2) measurement. The electronic instrumentation has been developed in the laboratory for this application and it is optimized to minimize interference between the different devices. It also incorporates a pneumatic pump and a tube for air sampling outside the influence of the propellers. In this study, a series of measurements of the UAV were carried out at a stationary location next to a reference station in order to perform the calibration of the sensors. Once calibrated, a series of measurements have been made in motion. The experimental results show the accuracy of the measurements of the proposed prototype as well as its robustness in-flight measurements.

Research on multi-functional intelligent ventilator based on UC/OS-III operating system for gas concentration detection

In order to change the traditional gas concentration inspection and exhaust device, the system through the gas concentration to control the rotation of the fan, to achieve real-time gas concentration monitoring, alarm control and GPS global positioning. In this study, STM32F4ZGT6 with ARM Coretex-M4 as the core controller is combined with embedded system design, and MDK is used to develop software programming. Through the ADC MQ-9 carbon monoxide sensor detection module and infrared NDIR carbon dioxide sensor detection module of the output of the analog conversion to digital quantity acquisition and processing, when the gas concentration exceeds the pre-set threshold, triggering a buzzer alarm, timer and the energy conservation and exhaust fan work, implementation is beyond the rapid circulation of the gas and gas concentration inside and outside the display of the time.Through bluetooth and mobile phone connection, real-time check of gas concentration, using the upper computer to control the operation mode of exhaust fan and change the gas concentration threshold. Modular programming is adopted in this study to improve the maintainability and facilitate debugging and modification in the later stage of the study. Through practical verification, the system can realize the detection of carbon monoxide and carbon dioxide concentration, real-time alarm monitoring, GPS positioning and change exhaust fan working mode and other functions, with real time, practicality and reliability.

Fatal Unintentional Non-Fire Related Carbon Monoxide Poisoning: Data from Narrative Verdicts in England and Wales, 1998-2019.

Unintentional non-fire related (UNFR) carbon monoxide (CO) poisoning continues to cause fatalities. The narrative verdicts from coroners concerning fatal UNFR CO poisoning in England and Wales, 1998–2019, were collated by the Office for National Statistics. Search terms related to CO exposure were used to obtain information regarding the circumstances of death. Findings were grouped by the location of death, the source of CO, and the reason or behaviour underlying the exposure. There were 750 deaths (77% male). The annual number of deaths decreased over the period studied. Two thirds (68%) of the deaths occurred in the autumn or winter. From the records with information, 59% of deaths occurred within a dwelling (67% male). Males also predominated deaths within vehicles (91%) and garages or outbuildings (95%). From the deaths with information, domestic piped gas was the most common source of CO (36%) and the most frequent underlying factor was inadequate ventilation of exhaust gases (39%, 91% male). Despite the decrease in the annual number of deaths over the study period, there remains a clear need for measures that raise awareness of the dangers of CO poisoning, especially amongst men working alone in garages or outbuildings. Education campaigns and fitting and maintaining CO alarms in high-risk areas should be encouraged.

Poly(N-methyl pyrrole) decorated rGO nanocomposite: A novel ultrasensitive and selective carbon monoxide sensor

An ultrasensitive and selective carbon monoxide (CO) sensor based on poly(N-methyl pyrrole)/reduced graphene oxide (P(NMP)/rGO) nanocomposites working at room temperature (RT) has been presented. A unique three-step approach has been introduced to ensure the preparation of a highly conductive and water-soluble rGO. P(NMP)/rGO nanocomposite was materialized through the inexpensive and straightforward self-assembled micellar soft-template polymerization route in the presence of rGO. The P(NMP)/rGO based sensor demonstrates outstanding response upon exposure to a broad concentration of CO ranging from 10 ppm to 275 ppm. The experimental results revealed that incorporation of rGO with P(NMP) nanosphere improved the sensor response (231.5 % to 75 ppm), leading to fast response and recovery characteristics (40 s / 36 s) and excellent selectivity at RT. The lowest detection limit of P(NMP)/rGO nanocomposite-based sensor for CO is calculated to be 1.042 ppm. Based on the outcomes of this investigation, it is believed that the proposed sensor, with its inexpensive and simple construction method, along with its remarkable performance towards CO, might be a wonderful option for real-time detection of CO.

Air Pollution Monitoring System Using Wireless Sensor Networks and Cloud Computing

Air pollution is the availability of pollutants and other particles in the air which affect its quality. The common sources of air pollution include vehicle and industrial emissions, bushfire and volatile organic compounds. Over 80% of the urban dwellers are exposed to air pollution especially in low and middle-income countries. With most African countries embracing industrialization coupled with rapid urbanization, air pollution is swiftly becoming a serious concern due to the associated health risks. Globally, about 4.2 million people die annually from diseases attributed to air pollution. This paper presents a mechanism of using sensors to remotely monitor air pollution. The monitored data are then sent to the cloud database in real time using an internet connection. The materials used include an Arduino Uno, ESP8266 module, carbon monoxide and smoke sensors. The approach involves connecting an ESP8266 wireless module, smoke and carbon monoxide sensors to the Arduino board using jumpers. Results revealed that data is collected by the sensors, processed by Arduino and sent to the cloud for storage and analysis. The cloud service visualizes the received data in a graphical format for easy analysis whereas a spreadsheet document can also be extracted for offline analysis. In conclusion, a system capable of monitoring smoke and carbon monoxide pollutants has been proposed. This system is effective in sending the monitored data to a cloud database in real time. Policy makers, governments, and different stakeholders such as environment authorities should embrace such systems and also sensitize the citizens on the dangers of air pollution.

Sensitivity enhanced NIR photoacoustic CO detection with SF6 promoting vibrational to translational relaxation process

A challenge for slowly relaxing carbon monoxide (CO) molecules detection using photoacoustic spectroscopy (PAS) is to promote the vibration-translation (V-T) relaxation process. Addressing this challenge, a sensitivity enhanced photoacoustic CO sensor with sulfur hexafluoride (SF6) as the promotor is investigated and demonstrated. A 1568 nm near-infrared (NIR) laser diode and a customized optical amplifier are used as the excitation source to generate the photoacoustic signal. A differential photoacoustic cell is simulated and designed to obtain identical laminar flow distribution in the resonant cell to suppress the flow noise. The modulation frequency and added SF6 volume ratio are optimized experimentally to achieve optimal sensitivity. Feasibility and performance of the CO sensor with a small amount of SF6 as promotor is discussed and evaluated, obtaining a ~ 2 times improvement of signal value compared to the one with pure N2 background and resulting in a minimum detection limit of 467.5 ppb for CO detection.

Distributed Sensors for Wildfire Early Warnings

Wildfires cause immense damage and loss of life. They are exacerbated by climate change effects and will be getting worse each year for some time to come. One way to deal with them is to have better means of early detection. Fires produce significant changes in the physical and chemical makeup of the local atmosphere that, in practice, can be detected by air quality monitors. This paper describes a sensor array that measures trace levels of fire produced emissions that is coupled to computation and communication equipment that is low power and low cost. The emission arrays are calibrated and deployed in controlled fire detection situations. Evaluations illustrate some important characteristics of detecting fire emissions including: 1] sensing CO and Particulates together reduce ambiguity of signals; and 2] fire emission signatures for relatively close fires produce rapid spikes in concentrations of emissions. Most importantly, the details of this work indicate that an individual sensor node consisting of only a CO and particle detector can provide an early indication of a wildfire. Additionally, the low-cost CO and particle sensors used in this study show a correlation of greater than 0.9 R2 with FRM reference monitors. The results are encouraging that very low-cost arrays could substantially contribute to an early warning system for detection of wildland fires thereby improving response times for mitigation measures.