Gas Monitoring Research Articles

Active near‐infrared laser heterodyne system based on supercontinuum laser source for gas measurement

AbstractThe performance of an active near‐infrared laser heterodyne system using a supercontinuum light source as the light signal for trace species detection is experimentally demonstrated. The characteristics of the supercontinuum light source and the data processing methods used in heterodyne detection are described. The measurement of methane (CH₄) and carbon dioxide (CO₂) absorption spectra was carried out in the laboratory to evaluate the active laser heterodyne system, and high‐resolution absorption spectra of CO₂ and CH₄ were recorded simultaneously. The stability of the active laser heterodyne system is analyzed using Allan variance analysis of long‐term observation data. The active near‐infrared laser heterodyne detection system demonstrated in this paper has great potential for the development of industrial parks' gas monitoring.

Distribution of air quality data across stratified areas of Port Harcourt metropolis

Distribution of Air Quality Data across seven stratified areas of Port Harcourt Metropolis was carried out. The study utilized a total of 18 parameters from four different air quality datasets obtained from 24 sampling points during field data collection. The sampling points were structured and stratified into residential, industrial, commercial, recreational, transport, dumpsite and abattoir areas. Air quality data were acquired using a multi-digital potable tool, Aerosol Gas Monitor and TESTO Gas Analyser for meteorological data, particulate matters (PM), gaseous emissions and heavy metals. Results showed that the concentrations of air quality data were not evenly distributed across the seven stratified areas, an indication of the influence of location-based activities on the distribution of air quality parameters. The minimum and maximum values of wind speed, temperature and relative humidity were obtained within Residential and Transport Areas, Abattoir and Dumpsite Areas, and, Industrial and Recreational Areas with numerical values of 1.1ms-1 and 3.7ms-1, 27.20C and 350C, and, 67.8% and 923% for wind speed, temperature and relative humidity respectively. The values of TSP, PM2.5 and PM10 ranged from 53 to 255 μg/m3, 13 to 90 μg/m3 and 40 to 169μg/m3 for TSP, PM2.5 and PM10 respectively with the lowest and highest values obtained within Residential and Dumpsite Areas respectively. The concentrations of NO2 and SO2 exceeded the standards of WHO, NAAQS and FMEnv in Industrial, Dumpsite and Abattoir Areas. Lead ( Pb) showed very high values within Dumpsite Area (0.954mg/kg), Industrial Area (0.372mg/kg) and Transport Area (0.077mg/kg).

Selective Identification of Hazardous Gases Using Flexible, Room-Temperature Operable Sensor Array Based on Reduced Graphene Oxide and Metal Oxide Nanoparticles via Machine Learning.

Selective detection and monitoring of hazardous gases with similar properties are highly desirable to ensure human safety. The development of flexible and room-temperature (RT) operable chemiresistive gas sensors provides an excellent opportunity to create wearable devices for detecting hazardous gases surrounding us. However, chemiresistive gas sensors typically suffer from poor selectivity and zero-cross selectivity toward similar types of gases. Herein, a flexible, RT operable chemiresistive gas sensors array is designed, featuring reduced graphene oxide (rGO) and rGO decorated with zinc oxide (ZnO), titanium dioxide (TiO2), and tin dioxide (SnO2) nanoparticles (NPs) on a flexible polyimide (PI) substrate. The sensor array consists of four different sensing layers capable of the selective identification of various hazardous gases such as NO2, NO, and SO2 using machine learning (ML). The gas sensor array exhibits a stable response even when mechanically deformed or exposed to high humidity (up to 60%). Each gas sensor, due to the different metal oxide NPs, shows unique responses in terms of sensitivity, responsiveness, response time, and recovery time to different gases. Consequently, the sensor array generates distinct response patterns that effectively differentiate between the target gases. By leveraging these distinctive recovery patterns and employing a data fusion approach in ML, specific concentrations of target gases can be distinguished. Using ML with fused array sensing data, the training and test accuracies achieved were 98.20 and 97.70%, respectively. This innovative combination of sensor arrays and ML offers significant potential for selective gas detection in environmental monitoring and personal safety applications.

Development of Low-Stress Double-Pass Filter Device for Methane and Ethane Flammable Gas Detection System

To meet the needs of industrial and environmental monitoring of methane and ethane flammable gases, a low-stress filter device for detecting methane and ethane simultaneously is developed based on the absorption spectra of methane and ethane and the thin-film design theory. In order to improve the sensitivity of the detection system and reduce the influence of environmental noise, the information of methane and ethane gas is extracted simultaneously by using a filter with double bandpass and wide cut-off in the middle-infrared and far-infrared bands. The transmittance of the filter is 91.3%, 93.1%, and 93.02% at the wavelengths of 3.31 μm, 6.71 μm, and 7.67 μm, respectively. The cut-off depth in the cut-off interval is above OD3, which meets the system’s requirements.

Advances in Gas Detection of Pattern Recognition Algorithms for Chemiresistive Gas Sensor

Gas detection and monitoring are critical to protect human health and safeguard the environment and ecosystems. Chemiresistive sensors are widely used in gas monitoring due to their ease of fabrication, high customizability, mechanical flexibility, and fast response time. However, with the rapid development of industrialization and technology, the main challenges faced by chemiresistive gas sensors are poor selectivity and insufficient anti-interference stability in complex application environments. In order to overcome these shortcomings of chemiresistive gas sensors, the pattern recognition method is emerging and is having a great impact in the field of sensing. In this review, we focus systematically on the advancements in the field of data processing methods for feature extraction, such as the methods of determining the characteristics of the original response curve, the curve fitting parameters, and the transform domain. Additionally, we emphasized the developments of traditional recognition algorithms and neural network algorithm in gas discrimination and analyzed the advantages through an extensive literature review. Lastly, we summarized the research on chemiresistive gas sensors and provided prospects for future development.

Miniaturized Electrochemical Gas Sensor with a Functional Nanocomposite and Thin Ionic Liquid Interface for Highly Sensitive and Rapid Detection of Hydrogen.

Hydrogen has been widely used in industrial and commercial applications as a carbon-free, efficient energy source. Due to the high flammability and explosion risk of hydrogen-air mixtures, it is vital to develop sensors featuring fast-responding and high sensitivity for hydrogen leakage detection. This paper presents a miniaturized electrochemical gas sensor by elaborately establishing a nanocomposite and thin ionic liquid interface for highly sensitive and rapid electrochemical detection of hydrogen, in which a remarkable response time and recovery time of approximately 6 s was achieved at room temperature. A screen-printed carbon electrode was modified with a reduced graphene oxide-carbon nanotube (rGO-CNT) hybrid and platinum-palladium (Pt-Pd) bimetallic nanoparticles to realize high sensitivity. To achieve miniaturization and high stability of the sensor, a thin-film room-temperature ionic liquid (RTIL) was employed as the electrolyte with a significantly decreased response time. The fast-responding hydrogen sensor demonstrates excellent performance with high sensitivity, linearity, and repeatability at concentrations below the lower explosive limit of 4 vol %. The engineered high-performance interface and gas sensor provide a promising and effective strategy for gas sensor design and rapid hazardous gas monitoring.

Age of Stratospheric Air: Progress on Processes, Observations, and Long‐Term Trends

AbstractAge of stratospheric air is a well established metric for the stratospheric transport circulation. Rooted in a robust theoretical framework, this approach offers the benefit of being deducible from observations of trace gases. Given potential climate‐induced changes, observational constraints on stratospheric circulation are crucial. In the past two decades, scientific progress has been made in three main areas: (a) Enhanced process understanding and the development of process diagnostics led to better quantification of individual transport processes from observations and to a better understanding of model deficits. (b) The global age of air climatology is now well constrained by observations thanks to improved quality and quantity of data, including global satellite data, and through improved and consistent age calculation methods. (c) It is well established and understood that global models predict a decrease in age, that is, an accelerating stratospheric circulation, in response to forcing by greenhouse gases and ozone depleting substances. Observational records now confirm long‐term forced trends in mean age in the lower stratosphere. However, in the mid‐stratosphere, uncertainties in observational records are too large to confirm or disprove the model predictions. Continuous monitoring of stratospheric trace gases and further improved methods to derive age from those tracers will be crucial to better constrain variability and long‐term trends from observations. Future work on mean age as a metric for stratospheric transport will be important due to its potential to enhance the understanding of stratospheric composition changes, address climate model biases, and assess the impacts of proposed climate geoengineering methods.

Network of artificial olfactory receptors for spatiotemporal monitoring of toxic gas.

Excessive human exposure to toxic gases can lead to chronic lung and cardiovascular diseases. Thus, precise in situ monitoring of toxic gases in the atmosphere is crucial. Here, we present an artificial olfactory system for spatiotemporal recognition of NO2 gas flow by integrating a network of chemical receptors with a near-sensor computing. The artificial olfactory receptor features nano-islands of metal-based catalysts that cover the graphene surface on the heterostructure of an AlGaN/GaN two-dimensional electron gas (2DEG) channel. Catalytically dissociated NO2 molecules bind to graphene, thereby modulating the conductivity of the 2DEG channel. For the energy/resource-efficient gas flow monitoring, trust-region Bayesian optimization algorithm allocates many sensors optimally in a complex space. Integrated artificial neural networks on a compact microprocessor with a network of sensors provide in situ gas flow predictions. This system enhances protective measures against toxic environments through spatiotemporal monitoring of toxic gases.

Adsorption and Sensing Properties of Ni-Modified InSe Monolayer Towards Toxic Gases: A DFT Study

The emission of toxic gases from industrial production has intensified issues related to atmospheric pollution and human health. Consequently, the effective real-time monitoring and removal of these harmful gases have emerged as significant challenges. In this work, the density functional theory (DFT) method was utilized to examine the adsorption behaviors and electronic properties of the Ni-decorated InSe (Ni-InSe) monolayer when interacting with twelve gases (CO, NO, NO2, NH3, SO2, H2S, H2O, CO2, CH4, H2, O2, and N2). A comparative assessment of adsorption strength and sensing properties was performed through analyses of the electronic structure, work function, and recovery time. The results show that Ni doping enhances the electrical conductivity of the InSe monolayer and improves the adsorption capabilities for six toxic gases (CO, NO, NO2, NH3, SO2, and H2S). Furthermore, the adsorption of these gases on the Ni-InSe surface is characterized as chemisorption, as indicated by the analysis of the adsorption energy, density of states, and charge density difference. Additionally, the adsorption of CO, NO, NO2, and SO2 results in significant alterations to the bandgap of Ni-InSe, with changes of 18.65%, 11.37%, 10.62%, and −31.77%, respectively, underscoring its exceptional sensitivity. Moreover, the Ni-InSe monolayer exhibits a moderate recovery time of 3.24 s at 298 K for the SO2. Consequently, the Ni-InSe is regarded as a promising gas sensor for detecting SO2 at room temperature. This research establishes a foundation for the development of an Ni-InSe-based gas sensor for detecting and mitigating harmful gas emissions.

A Novel Mechanism Based on Oxygen Vacancies to Describe Isobutylene and Ammonia Sensing of p-Type Cr2O3 and Ti-Doped Cr2O3 Thin Films

Gas sensors based on metal oxide semiconductors (MOS) have been widely used for the detection and monitoring of flammable and toxic gases. In this paper, p-type Cr2O3 and Ti-doped Cr2O3 (CTO) thin films were synthesized using an aerosol-assisted chemical vapor deposition (AACVD) method. Detailed analysis of the thin films deposited, including structural information, their elemental composition, oxidation state, and morphology, was investigated using XRD, Raman analysis, SEM, and XPS. All the gas sensors based on pristine Cr2O3 and CTO exhibited a reversible response and good sensitivity to isobutylene (C4H8) and ammonia (NH3) gases. Doping Ti into the Cr2O3 lattice improves the response of the CTO-based sensors to C4H8 and NH3. We describe a novel mechanism for the gas sensitivity of p-type metal oxides based on variations in the oxygen vacancy concentration.

Radiocarbon as a tracer of the fossil fraction of regional carbon monoxide emissions

Abstract Carbon monoxide (CO) is an atmospheric pollutant with a positive net warming effect on the climate. The magnitude of CO sources and the fraction of fossil vs biogenic sources are still uncertain and vary across emissions inventories. Measurements of radiocarbon (14C) in CO could potentially be used to investigate the sources of CO on a regional scale because fossil sources lack 14C and reduce the 14C/C ratio (Δ14C) of atmospheric CO more than biogenic sources. We use regional Lagrangian model simulations to investigate the utility of Δ14CO measurements for estimating the fossil fraction of CO emissions and evaluating bottom-up emissions estimates (United Kingdom Greenhouse Gas, UKGHG, and TNO Copernicus Atmosphere Monitoring Service, TNO) in London, UK. Due to the high Δ14CO in atmospheric CO from cosmogenic production, both fossil and biogenic CO emissions cause large reductions in Δ14CO regionally, with larger reductions for fossil than biogenic CO per ppb added. There is a strong seasonal variation in Δ14CO in background air and in the sensitivity of Δ14CO to fossil and biogenic emissions of CO. In the UK, the CO emissions estimate from TNO has a higher fraction from fossil fuels than UKGHG (72\% vs 67\%). This results in larger simulated decreases in Δ14C per ppb CO for TNO emissions. The simulated differences between UKGHG and TNO are likely to be easily detectable by current measurement precision, suggesting that Δ14CO measurements could be an effective tool to understand regional CO sources and assess bottom-up emissions estimates.

Low excess noise and high quantum efficiency avalanche photodiodes for beyond 2 µm wavelength detection

The rising concentration of greenhouse gases, especially methane and carbon dioxide, is driving global temperature increases and exacerbating the climate crisis. Monitoring these gases requires detectors that operate in the extended short-wavelength infrared range (~2.4 µm), covering methane (1.65 µm) and carbon dioxide (2.05 µm) wavelengths. Here, we present a high-performance linear mode avalanche photodetector (APD) with an InGaAs/GaAsSb type-II superlattice absorber and an AlGaAsSb multiplier, matched to InP substrates. This APD achieves a room temperature gain of 178, an external quantum efficiency of 3560% at 2 µm, low excess noise (less than 2 at gains below 20), and a small temperature coefficient of breakdown (7.58 mV/K·µm). These results indicate that a manufacturable semiconductor material-based APD could significantly advance high-sensitivity receivers for greenhouse gas monitoring, potentially enabling their commercial production and widespread use.

High‐Performance Flexible Gas Sensor Using Natural Rubber/MXene Composite for Selective and Stable VOC Detection

AbstractFlexible gas sensors are gaining interest for real‐time volatile gas monitoring. A natural rubber (NR)/MXene nanocomposite sensor is developed. Among the six selected target volatile gases, the composite sensor exhibited a strong response value (82% toward 100 ppm NH3) with the fastest response/recovery time (12.3 s/15.5 s) to NH3. The sensitivity showed a clear dependence of gases, suggesting a good selectivity to varying gases. Ti3C2Tx MXene gas sensors exhibited a very low limit of detection of 50–100 ppb for volatile organic compounds (VOCs) at room temperature. In addition, the NR/MXene sensor allows detection of the mixture of ammonia (NH3), dimethyl sulfoxide (DMSO), and acetone (C3H6O) and it shows good response depending on the total concentration of VOC gases. Furthermore, the flexible nanocomposite sensor exhibits stable sensing performance at different bending states (0‐120°) and shows 20‐day atmospheric stability. This sensor's ability extends to alcohol breath analysis, useful for drunk driving detection. This work paves the way to the possibility of using robust MXene‐based toward practical realization of electronic devices.

Wool powder assisted colorimetric sensing yarn with high sensitivity for NH3 monitoring

Colorimetric sensors have applications in gas monitoring due to their simple and quick detection through visible color changes. However, it remains challenging to prepare colorimetric sensors with high sensitivity. Herein, this work fabricated a biomass-based colorimetric sensing yarn with high sensitivity using anthocyanins as the colorimetric dye and wool powder as an effective ammonia (NH3) adsorbent. The sensitivity of the prepared yarns was evaluated for detection limit and response time. Surprisingly, the addition of 3% wool powder greatly improved the sensitivity of the prepared yarns, with a reduction of both detection limit and responsive time from 100 ppm to 20 ppm, and 2 min to 20 s, respectively when exposed in 150 ppm NH3. The prepared yarns also showed good selectivity and reusability. An example of the practical use of colorimetric yarns was presented. This work provides a facile strategy for fabricating wearable devices for toxic gas monitoring with visual output.

Compound disaster characteristics of rock burst and coal spontaneous combustion in island mining face: A case study

The island mining face in coal mines often encounters stress concentration and significant air leakage, elevating the risk of rock burst and spontaneous combustion of residual coal in the goaf. This study centers on the investigation of the 9305 island mining face within a mine situated in Shandong Province, China. Leveraging the features of coal spontaneous combustion and data from microseismic and gas monitoring throughout the mining process, a novel method for calculating safe mining speeds under compound disasters is introduced. The safe mining speed of the 9305 island mining face is stratified, and a prevention and control technology integrating long distance directional drilling for impact-spontaneous combustion compound disasters is proposed. Findings suggest that to mitigate spontaneous combustion of residual coal, considering the seam's spontaneous combustion tendency, the safe mining speed should exceed 3.7 m per day. Accounting for the distribution of microseismic events during coal seam extraction, the safe mining speed is maintained below 4.8 m per day in the unprotected mining area and capped at 8 m per day in the protected zone. Through a comprehensive analysis considering coal seam spontaneous combustion tendency, impact tendency, and time to coal seam oxidation to critical temperature, the safe mining speed for the island mining face ranges from 3.7 m per day to 4.8 m per day in the unprotected area and from 5.14 m per day to 8 m per day in the protected area. The proposed long distance directional drilling 'one hole, multiple purposes' scheme enables an integrated approach encompassing pressure relief before coal seam extraction, water injection during mining, and grouting post-mining. This method effectively prevents and controls the compound disasters of rock burst and coal spontaneous combustion, presenting innovative technical solutions for the safe extraction of coal resources.

Hollow CuO/Cu2O octahedrons for selective and stable detection of acetone gas

Acetone (C3H6O) is key member of the volatile organic compound family, which can cause health as well as environmental issues. The identification and sensing of acetone gas are important in many applications such as air quality control and biomarker-based diagnosis. Here, we synthesized hollow CuO/Cu2O octahedrons heterostructure composite through coprecipitation and subsequent heat treatment. The sensor manifested a response of 3.52 to 50 ppm acetone gas at 350 °C. Besides, it showed excellent stability in a 150-day test and excellent repeatability, with a response of 4.15. Also, exhaled gas sensing was carried out using standard method to estimate the acetone concentration in breath. The high sensing capability of the sensor was ascribed to the formation of p-p heterojunctions, the hollow morphology of octahedrons, and the presence of structural defects. The hollow CuO/Cu2O octahedron sensor with good performance may be employed for the detection and monitoring of acetone gas in real situations.

Regulation of receptor function in NiCo2O4-SnO2 heterojunction for H2S detection at room temperature

In recent years, the World Health Organization has increasingly emphasized air quality in production environments, leading to heightened societal demands for monitoring of pollutant gases at room temperature. Traditional semiconductor gas-sensitive materials, such as tin oxide (SnO2), have their gas-sensing performance largely limited by their receptor functions, resulting in common issues like low response and poor recovery at room temperature. Spinel-type bimetallic oxides, such as nickel cobaltate (NiCo2O4), offer a unique solution due to their rich adsorption sites on the surface, which provide distinctive receptor functions for detecting toxic gases at room temperature. Herein, NiCo2O4 is synthesized via a one-step hydrothermal method, with a porous spherical cluster structure, and combined with SnO2 to form a heterojunction. The NiCo2O4-SnO2 heterojunction film gas sensor exhibits excellent gas-sensing performance for H2S at room temperature, including high response, short response time, good repeatability, and selectivity. Additionally, the unique receptor functions of the NiCo2O4 were analyzed through first-principles calculations, revealing a semiconductor p-n conversion phenomenon in the presence of H2S gas. The composite also demonstrates a conversion from p-n heterojunction to n-n homojunction during the sensing process, enhancing its gas-sensing performance. This work not only addresses the receptor function limitations of traditional gas-sensitive semiconductor but also provides a feasible approach for controlling carrier types in semiconductors.

Gas, Temperature, and Humidity Sensors-Based Onion Quality Monitoring System

Gas, Temperature, and Humidity Sensors-Based Onion Quality Monitoring System

Concentration calculation model for calibration of non-dispersive infrared gas detection system

Non-dispersive infrared (NDIR) gas detection systems have been extensively used for gas monitoring because they are considered the simplest approach with moderate sensitivity and fast response. Concentration calculation models for calibration are particularly important in NDIR gas detection systems because of the nonlinear relationship between the output voltage ratio and concentration. We propose a concentration calculation model with two fitting parameters for non-dispersive infrared gas detection systems, accounting for the fact that not all IR radiation that impinges upon the detector is absorbed by the gas and for the saturation effects in absorption peaks leading to the nonlinear relationship. Despite the small number of fitting parameters of the proposed concentration calculation model, it presents high quality curve fitting to experimental data. The performance of the proposed model is compared to that of other concentration calculation models.

Characterization and Ambient Temperature Hydrogen Sulfide Sensing of Annealed NiO-MnO₂ Thin Films Prepared via Jet Nebulizer Spray Pyrolysis

A jet nebulizer spray pyrolysis technique to synthesize NiO-MnO2 thin films was demonstrated. These nanosheets were annealed at 350, 450 and 550 °C for 2 hours. The thin films surface morphology and structure were characterized using scanning electron microscopy, XRD, and UV spectroscopy. Subsequently, utilized as gas sensors for the detection of hydrogen sulphide gas. The introduction of NiO into MnO2 nanosheets significantly improved the gas-sensing performance. Notably, the gas-sensing response of the NiO-MnO2 nanosheet sensor surpassed that of both NiO and MnO2 alone, reaching a notable value of 165 when detecting 100 ppm hydrogen sulfide gas with the NiO-MnO2 thin film sensor. A remarkable feature of the NiO-MnO2 thin film sensor is its accelerated response time, registering at 10 seconds when exposed to 100 ppm of hydrogen sulfide gas. The mechanism underlying gas sensing and the factors contributing to the enhanced gas response of NiO-MnO2 thin film is thoroughly discussed. From a broader perspective, these developed sensors present a novel platform for the identification and monitoring of hydrogen sulfide gas, showcasing significant advancements in gas-sensing technology.