Gas Concentration Research Articles

A proposed device based on MoSe2-ZnO heterojunctions on rGO for enhanced ethanol gas sensing performances at room temperature

In this research, we report an enhanced sensing response ethanol gas sensing device based on a ternary nanocomposite of molybdenum diselenide-zinc oxide heterojunctions decorated rGO (MoSe2/ZnO/rGO) at room temperature. The sensing performance of the ternary nanocomposite sensing device has been analysed for various concentrations of ethanol gas (1–500 ppm). The gas-sensing results have revealed that for 500 ppm ethanol gas concentration, the sensing device has exhibited an enhanced response value (Rg/Ra) of 50.2. Significantly, the sensing device has displayed a quick response and recovery time of 6.2 and 12.9 s respectively. In addition to this, the sensing device has shown a great prospect for long-term detection of ethanol gas (45 days). The sensing device has demonstrated the ability to detect ethanol at remarkably low concentrations of 1 ppm. The enhanced sensing performance of the ternary nanocomposite sensing device has highlighted the effective synergistic effect between MoSe2 nanosheets, ZnO nanorods, and rGO nanosheets. This has been attributed to the formation of two heterojunctions in the ternary nanocomposite sensor: a p-n heterojunction between MoSe2 and ZnO and a p-p heterojunction between MoSe2 and rGO. The analysis of the results has suggested that the proposed MoSe2/ZnO/rGO nanocomposite sensing device could be considered a promising candidate for the real-time detection of ethanol gas.

Intelligent recognition of coal and gas outburst precursor and potential hazards using YOLOv8 neural network

Fluctuations in gas emission or concentration at working face represent primary indicators of impending coal and gas outbursts, making them essential for monitoring processes. However, the direct use of original signals for predictive purposes may cause false warnings due to the inability to recognize valuable potential information. This can result in decreased prediction accuracy. Additionally, gas emission or concentration is affected by potential hazards such as sensor calibration, borehole spraying, and air duct damage, leading to complexity of their behavior and recognition process. This paper proposes an intelligent recognition method leveraging YOLOv8 neural network to discern coal and gas outburst precursors and potential hazards. By employing continuous wavelet transform (CWT) on the gas concentration signal processed by critical slowing down (CSD) method, a two-dimensional time–frequency representation is generated. This representation is then fed into YOLOv8 model to recognize the outburst precursor characteristics and potential hazards. The research results show that YOLOv8-based intelligent recognition adeptly identifies the relevant precursor characteristics and potential hazards, enhancing both coal mine safety protocols and the accuracy of early outburst warning mechanisms.

Density-Driven CO2 Dissolution in Depleted Gas Reservoirs with Bottom Aquifers

Depleted gas reservoirs with bottom water show significant potential for long-term CO2 storage. The residual gas influences mass-transfer dynamics, further affecting CO2 dissolution and convection in porous media. In this study, we conducted a series of numerical simulations to explore how residual-gas mixtures impact CO2 dissolution trapping. Moreover, we analyzed the CO2 dissolution rate at various stages and delineated the initiation and decline of convection in relation to gas composition, thereby quantifying the influence of residual-gas mixtures. The findings elucidate that the temporal evolution of the Sherwood number observed in the synthetic model incorporating CTZ closely parallels that of the single-phase model, but the order of magnitude is markedly higher. The introduction of CTZ serves to augment gravity-induced convection and expedites the dissolution of CO2, whereas the presence of residual-gas mixtures exerts a deleterious impact on mass transfer. The escalation of residual gas content concomitantly diminishes the partial pressure and solubility of CO2. Consequently, there is an alleviation of the concentration and density differentials between saturated water and fresh water, resulting in the attenuation of the driving force governing CO2 diffusion and convection. This leads to a substantial reduction in the rate of CO2 dissolution, primarily governed by gravity-induced fingering, thereby manifesting as a delay in the onset and decay time of convection, accompanied by a pronounced decrement in the maximum Sherwood number. In the field-scale simulation, the injected CO2 improves the reservoir pressure, further pushing more gas to the producers. However, due to the presence of CH4 in the post-injection process, the capacity for CO2 dissolution is reduced.

Research on Ozone-Enhanced Oxidation of Industrial Zinc Sulfite from Flue Gas Desulfurization

ABSTRACT This study investigates the air oxidation and ozone-enhanced oxidation of zinc sulfite. Zinc sulfite was prepared by reacting pure or industrial zinc oxide with SO2 in water. The oxidation experiments were conducted under constant temperature conditions, with slurry, oxygen, and ozone concentrations in the ranges of 0.5–4%, 10–60%, and 1100–1920 ppm, respectively. The experiments involved determining the zinc ion concentration, sulfite concentration, dissolved oxygen, ozone concentration in the exhaust gas, and total organic carbon value for analysis of the oxidation process. The findings revealed that the mass transfer rate of O2 and/or O3 determined the reaction rate in the main stage of the oxidation process, while ozone affected the non-mass transfer control stage, resulting in an average enhancement of 15% in the oxidation rate. Furthermore, ozone causes organic matter attached to industrial zinc sulfite particles to fall off into the solution, significantly improving the oxidation ratio of industrial zinc sulfite.

An Innovative Prototype to Measure Carbon Dioxide, Ethylene, and Nitric and Nitrous Oxides in the Soil Air

ABSTRACT Agricultural intensification has increased the consumption of inputs, mainly fertilizers, which may increase emissions of greenhouse gases (GHG). The improvement of our knowledge on GHG dynamics in the soil is mandatory to optimize the use of fertilizers and reduce environmental impacts. We developed an electronic sensor prototype based on Arduino to monitor concentrations of carbon dioxide (CO2), ethylene (C2H4), ammonia (NH3), and nitrogen oxides (N2O/NOx) in the soil air in a greenhouse experiment with soybean (Glycine max L.) under two treatments: single inoculation (Bradyrhizobium spp.) or triple co-inoculation (Bradyrhizobium spp. Azospirillum brasilense and Pseudomonas fluorescens) in a completely randomized design. One-way analysis of variance, as well as correlation between plant traits at 35 days of emergence and the average daily concentration of gases in the soil air were performed. Although not affecting plant growth or yield-related traits, co-inoculation increased CO2, while decreased NOx concentrations compared with single inoculation, whereas C2H4 emission changed with the plant growth stage. Although co-inoculation increased respiration, decreased N losses by denitrification, mitigating the total emissions of GHG. The prototype showed to be efficient for monitoring GHG across the experiment at a low cost and easy use, contributing for monitoring GHG concentrations in the soil air.

Application of uncertainty quantification techniques in the framework of process safety studies: Advanced dispersion simulations

AbstractIn the framework of process safety studies, consequence assessment of accidental scenarios is a crucial step affecting the eventual risk profile associated with the facilities under analysis. Conventional models used for consequence assessment are based on integral models, and may not be adequate to cope with the dynamic evolution of accidental scenarios and their three‐dimensional features. On the other hand, consequence assessment models based on computational fluid dynamics (CFD) approaches are promising to cope with complex scenarios and environments, but setting the simulation introduces relevant uncertainties associated with both the input data, assumptions, and with the modelling of physical effects involved. In the present study, uncertainty quantification (UQ) techniques are applied to support advanced safety studies based on CFD simulations of hazardous gas dispersion. Firstly, the accidental scenarios are characterized by defining release scenarios and conditions and quantifying source terms using integral models. At the same time, input meteorological data are gathered. This enables the development of high‐fidelity CFD simulations of gas dispersion based on different input sets and eventually the implementation of UQ techniques. The generalized polynomial chaos (gPC) expansion is employed to obtain hazardous gas concentration based on the variation of wind direction and speed. The present method is applied for the analysis of a real plant featuring a complex layout. The results show the advantages of the present approach by quantifying the influence of meteorological conditions and providing indications for supporting the development of protection systems and emergency measures.

Did the Glasgow COP26 negotiations meet or miss Article 6 (carbon markets) of the Paris Agreement? A systematic review of the literature

AbstractThe Paris Agreement is an important milestone in international climate policy and the associated negotiations of the United Nations Climate Summit under the United Nations Framework Convention on Climate Change (UNFCCC). Article 6 of the Paris Agreement is a supplementary mechanism—regarding carbon markets—to reduce greenhouse gases and achieve the UNFCCC's main objective of stabilizing greenhouse gas concentrations. The 2021 United Nations Climate Summit in Glasgow (COP26) played a key role in the pursuit of this goal. Via an overview of Article 6 negotiations in past COP summits and a systematic review and qualitative meta‐synthesis of the literature leading up to COP26, I identify three arguments involving Articles 6.2, 6.4, and 6.8 behind the selected literature. I substantiate these arguments based on the meta‐evaluation of the existing literature and propose a three‐stage meta‐evaluation of the arguments on Article 6 (carbon markets) of the Paris Agreement in the context of COP26 to ascertain if the negotiations were successful in leading to requisite agreements on Article 6. I conclude that future qualitative research should focus on Articles 6.4 and 6.8 of the Paris Agreement and examine the outcomes of future climate debates to see how ideas will flow through the negotiations regarding these two articles to pursue the goal of the UNFCCC under the Paris Agreement.Related ArticlesJihyung Joo, Jihyung, Jouni Paavola, and James Van Alstine. 2023. “The Divergence of South Korea's Emissions Trading Scheme (ETS) from the EU ETS: An Institutional Complementarity View.” Politics & Policy 51(6): 1155–73. https://doi.org/10.1111/polp.12566.Nunes Silva, Carlos. 2012. “Policy and Evidence in a Partisan Age: The Great Disconnect—By Paul Gary Wyckoff.” Politics & Policy 40(3): 541–43. https://doi.org/10.1111/j.1747‐1346.2012.00363.x.Robles, Pedro, and Daniel J. Mallinson. 2023. “Catching up with AI: Pushing toward a Cohesive Governance Framework.” Politics & Policy 51(3): 355–72. https://doi.org/10.1111/polp.12529.

Signal enhancement of the gas detection based on quartz-enhanced photothermal spectroscopy technology

This paper presents an improved gas sensor based on the dual-excitation of quartz-enhanced photothermal spectroscopy (QEPTS) using a single quartz tuning fork (QTF) for signal detection. The silver coating on one side of the QTF was chemically etched to increase the laser power interacted with QTF for QEPTS signal excitation. By etching the silver coating on one side of QTF, the reflection structure between the silver coating of the other side of QTF and the external flat mirror was established. The device uses an absorption gas cell with an optical range length of 3 m, making the laser beam interact with the gas more completely and posing more gas concentration information. Acetylene was selected as the target gas to verify the performance of the sensor. The experimental results show that the signal amplitude with a flat mirror was 1.41 times that without a flat mirror, and 2.47 times that of traditional QEPTS sensor. The system has a minimum detection limit (MDL) of 1.10 ppmv, corresponding to a normalized noise equivalent absorption coefficient (NNEA) of 7.14 × 10−9 cm−1·W·Hz−1/2. Allan variance analysis results show that when the integration time is 700 s, the MDL of the system is 0.21 ppmv. The proposed gas sensor can play an important role on detecting trace gas in many fields.

Wavelet Cross-Correlation Signal Processing for Two-Phase Flow Control System in Oil Well Production

An algorithm based on continuous measurement of multiphase flows of oil well production has been designed to improve the efficiency of the technical control of oil production processes in the field. Separation-free, non-contact measurement of multiphase flows of oil well products allows increasing the efficiency of managing oil production processes in the field. Monitoring the current density using radioisotope measuring transducers (RMTs) allows obtaining information about the structure of the flow in the form of the distribution of gas inclusions and the speed of movement of liquid and gas in a two-phase flow. Fluid velocity measurement is based on digital processing of RMT signals, applying a continuous or discrete undecimated wavelet transform to them, and assessing the cross-correlation of wavelet coefficients in individual subspaces of the wavelet decomposition. The cross-correlation coefficients of two RMT signals located at a base distance, calculated in the subspaces of the wavelet decomposition, characterize the speed of movement of gas bubbles of different sizes in a vertical pipe. The measurement assumes that the velocity of the liquid phase of the oil flow in a vertical pipe mainly corresponds to the velocity of small bubbles. This speed should be determined by the maximum cross-correlation of wavelet coefficients in the corresponding decomposition subspace. Computer modeling made it possible to evaluate the characteristics of the algorithm for controlling the speed of liquid movement in the gas–liquid flow of oil well products and determine the mass flow rate of the liquid and the relative value of the gas content. The implementation of the algorithm in a multi-channel version of the device allows monitoring an entire cluster of wells in the field.

Optimizing methane plasma pyrolysis for instant hydrogen and high-quality carbon production

The European Green Deal has set a target for Europe to achieve net-zero greenhouse gas emissions by 2050, necessitating a transition to more sustainable energy sources. Hydrogen gas (H2) has emerged as a promising solution, with methane pyrolysis presenting a viable method for its production. This study explores the optimization of methane plasma pyrolysis for hydrogen and high-quality carbon production. Employing a statistical approach by a design of experiment software, critical process parameters are systematically analyzed to predict their impact within a defined range. Additionally, the paper conducts comprehensive characterization of the solid carbon produced during pyrolysis using imaging, spectroscopic and elemental analysis, and gas sorption analysis methods. The experimental investigation was conducted using a thermal plasma reactor with several settings of influential parameters including methane gas (CH4) content in the plasma gas, electric current, and arc length. The DC-transferred plasma arc is formed using a variable gas mixture of argon gas (Ar) and CH4, with a constant flow rate of 5 Nl/min. Thirteen tests were designed, evaluating responses such as power input, process stability, and H2 yield. The H2 yield indicates the hydrogen produced from CH4, with 100% representing total conversion. While the process exhibited inconstancy, attributed to reactor design constraints, a high H2 yield of 67%–100% was achieved. The results indicate that a higher CH4 content in the plasma gas and extended arc lengths disturb the plasma arc, hence reducing the H2 yield. Increased power input, achieved through higher amperage levels, and a wider reaction zone eased by extending the arc length both led to an improved H2 yield. Scanning electron microscopy (SEM) and energy dispersive X-ray spectroscopy (EDS) revealed microstructural differences, with carbon samples from the filter exhibiting finer textures and carbon samples from the reactor larger sizes and dendritic particles. Raman spectroscopy confirmed crystalline graphitic-like structures with low defect concentrations, a finding supported by X-ray diffraction (XRD) analysis. Inductively coupled plasma mass spectroscopy (ICP-MS) analysis confirmed high-purity carbon with slight impurities from initial filter contamination. Brunauer-Emmett-Teller (BET) specific surface area calculations based on gas sorption analysis showed significant variations, with filter-collected samples exhibiting 40–170 m2/g and reactor-collected ones showing 7–30 m2/g.

A preliminary integrated analysis of regional paleoclimate variations in China over the past ∼ 21 ka

In this study, we employ biological, geochemical and mineral, and physical proxies to quantitatively and semi-quantitatively reconstruct regional paleoclimate variations in China over the past ∼21 thousand years (ka). We have constructed state-of-the-art transfer functions between proxies and climatic variables in East Asia, revealing substantial paleoclimate variability, and demonstrate significant diversity of paleoclimate variations in regions of China over the past ∼21 ka. Compared with observational data between 1961 and 1990, averaged mean annual temperature (MAT) was ∼5 °C (3–8 °C) lower during the Last Glacial Maximum (LGM, ∼21 ± 3 ka), and ∼ 2 °C (1–3 °C) higher during Holocene Optimum (HO, ±9 ka) in China; while averaged mean annual precipitation (MAP) and averaged summer precipitation varied between 30 and 150%, with enhanced seasonality during the warmer Holocene (8–5 ka). Our quantitative and semi-quantitative paleoclimate reconstructions reveal both similarities and contrasts with previous studies of regional temperature and precipitation variability. The most remarkable paleoclimate variability is recorded in the transitional zone between the humid monsoon and arid desert regions of central and northern China. We conducted a dynamic downscaling paleoclimate simulation with a regional climate model (RegCM4), using the output from the fully-forced transient simulation of the global climate (TraCE-21 K) as the prescribed boundary conditions, to simulate regional climate changes at high spatial resolution in China over the past ∼21 ka. The results improve paleoclimate simulations at regional scales, but reveal differences in comparison with TraCE-21 K, thereby highlighting uncertainties in the simulation modeling. Moreover, we compare proxy-based paleoclimate reconstructions and the output of TraCE-21 K to identify inconsistencies in relation to regional paleoclimate variations, and confirm a generally consistent warming trend in MAT from the LGM to the HO followed by a cooling trend during the late Holocene. An overall increase in both annual and summer precipitation is observed from LGM to Holocene. This general paleoclimate pattern is likely to have been driven by northern hemisphere ice volume and atmospheric greenhouse gas concentrations (GHGs) during the last deglaciation, and boreal summer insolation during the Holocene. This study represents the first attempt to use multi sources and large datasets of proxy reconstructions and numerical simulations to evaluate regional paleoclimate variability in China since the LGM. Our research provides a comprehensive overview of climate change over the past 21 ka and underscores the critical importance of conducting high-resolution simulations and quantitative paleoclimate studies. This approach is essential for deciphering patterns of paleoclimate change that are currently poorly defined.

Thermal and Combustion Properties of Biomass-Based Flame-Retardant Polyurethane Foams Containing P and N

Biomass has been widely used due to its environmental friendliness, sustainability, and low toxicity. In this study, aminophosphorylated cellulose (PNC), a biomass flame retardant containing phosphorus and nitrogen, was synthesized by esterification from cellulose and introduced into polyurethane to prepare flame-retardant rigid polyurethane foam. The combustion properties of the PU and PU/PNC composites were studied using the limiting oxygen index (LOI), UL-94, and cone calorimeter (CCT) methods. The thermal degradation behavior of the PU and PU/PNC composites was analyzed by thermogravimetric analysis (TGA) and thermogravimetric infrared spectroscopy (TG-IR). The char layer after combustion was characterized using SEM, Raman, and XPS. The experimental results showed that the introduction of PNC significantly improved the flame-retardant effect and safety of PU/PNC composites. Adding 15 wt% PNC to PU resulted in a vertical burning grade of V-0 and a limiting oxygen index of 23.5%. Compared to the pure sample, the residual char content of PU/PNC15 in a nitrogen atmosphere increased by 181%, and the total heat release (THR) decreased by 56.3%. A Raman analysis of the char layer after CCT combustion revealed that the ID/IG ratio of PU/PNC15 decreased from 4.11 to 3.61, indicating that the flame retardant could increase the stability of the char layer. The TG-IR results showed that PNC diluted the concentration of O2 and combustible gases by releasing inert gases such as CO2. These findings suggest that the developed PU/PNC composites have significant potential for real-world applications, particularly in industries requiring enhanced fire safety, such as construction, transportation, and electronics. The use of PNC provides an eco-friendly alternative to traditional flame retardants. This research paves the way for the development of safer, more sustainable, and environmentally friendly fire-resistant materials for a wide range of applications.

Kinetic modeling of methane dehydroaromatization over Mo/ZSM-5 catalysts

We propose a novel kinetic model for the methane dehydroaromatization (MDA) reaction over the Mo/ZSM-5 catalyst to express the practical behavior of the catalytic reaction. Unlike existing MDA kinetic models, we introduced a deactivation model involving carbon deposit formation to simulate the more realistic behavior of the MDA reaction. The proposed kinetic model integrated the “apparent kinetic model,” which focuses on detectable components, and the “micro-kinetic model,” which incorporates the acidic properties and active sites of the catalyst. To validate this model, we conducted fixed-bed experiments across a wide range of operating conditions, including temperature, gas velocity, and metal loading. Compared with experimental data, our model predictions exhibited a remarkable error of 5 %. Specifically, by leveraging the relationship between the deactivation behavior and carbon deposit formation, the model accurately predicted the CH4 conversion rates, component yields, and coke production throughout the reaction. This model sheds light on catalytic behavior during carbon deposit generation under diverse operating conditions, contributing to a comprehensive understanding of the MDA reaction mechanism. The developed kinetic model can be applied to estimate reactor performance across various scenarios. By providing a kinetic model that incorporates information regarding the catalytic properties of Mo/ZSM-5 and the apparent gas concentration, our study offers a potent tool for estimating practical reactor performance and advancing MDA catalyst development.

A large-dynamic range conductivity-modulated PANI online analysis and sensing platform for ammonia gas detection using coupled optical probing mode

Due to the large-dynamic range and reversible conductivity modulation capability, polyaniline (PANI) shows promising prospects for diverse applications, such as supercapacitors, rechargeable batteries, and electrochromic materials. However, online characterization of the optical properties of the conductive polymer in the infrared band throughout the synthesis and redox state changing processes poses a challenge. Here, we propose and demonstrate an analysis and sensing platform for real-time evaluation of both thickness and the complex refractive index of PANI nanofilm, and employed for ammonia gas concentration sensing. The coupled optical probing mode of tilted fiber Bragg grating (TFBG) as a robust and portable permittivity perception tool is utilized for online perceiving the large-dynamic-range conductivity change of PANI nanofilm. By reproducing the spectral evolution of the probing cladding mode resonance, we introduce a simulation method for analyzing the optical properties of polymer nanofilms within the infrared band. For ammonia gas detection, the sensing platform exhibited continuous and reliable detection within a concentration range of 25–500 ppm, with an optimal film thickness of 156 nm. A good linear response was observed with a sensitivity of up to 5.2 × 10−3 dB/ppm, and a linearity (R2 = 0.9876) with a detection limit of 10 ppm. Our proposed low-cost and large dynamic range conductivity-modulated PANI-TFBG platform for optical properties online analysis and sensing shows potential in environmental monitoring, healthcare, and the biochemical field.

The low primordial heavy noble gas and 244Pu-derived Xe contents of Earth's convecting mantle

Clues to unraveling the origin and history of terrestrial volatiles lie in the noble gas record of Earth's mantle. However, the low abundance of heavy noble gases (Ar-Kr-Xe) in mantle-derived rocks presents a major analytical challenge that limits our understanding of mantle volatile evolution. Here, we employ a new technique of ultrahigh precision dynamic mass spectrometry to measure Ar-Kr-Xe isotopes in mantle-derived gas collected from Mt. Etna (Italy) and Eifel (Germany), which both tap depleted convecting mantle reservoirs. We find that the fractions of primordial Kr-Xe from accretionary sources (≤ 7 % of non-radiogenic, non-fissiogenic isotopes) and 244Pu-derived 136Xe (≤ 9.8 ± 9.3 % of total fissiogenic Xe) are both markedly lower than previously estimated. For Mt. Etna, we find an apparent lack of detectable primordial Xe, which could reflect an additional contribution from recycled atmospheric volatiles from nearby subduction. In addition, slight excesses of 238U-derived fissiogenic Xe relative to the upper mantle composition may reflect the contribution of a crustal component related to the occurrence of a HIMU (“high μ” where μ = 238U/204Pb)-type source in Mt. Etna volcanic products. The low primordial heavy noble gas and 244Pu-derived Xe contents of Earth's convecting mantle, as derived from these new data, requires extensive volatile loss during terrestrial accretion, followed by long-term degassing and pervasive overprinting of primordial heavy noble gases by subduction recycling. In addition, we suggest that quantitative incompatible element (including Pu, U) extraction to the Hadean crust and subsequent reintroduction of U via subduction could have contributed to lowering the ultimate fraction of 244Pu-derived 136Xe in the upper mantle. The differences observed between this study and other upper mantle Xe studies may reflect mantle source heterogeneities (e.g. due to the heterogeneous overprinting of mantle volatiles by subduction) but could also result from analytical inconsistencies and/or subsurface isotope fractionation in natural systems. Future studies are crucial to gain insight into the origin of these different results.

A Review of the Increasing Global Impact of Climate Change on Human Health and Approaches to Medical Preparedness.

At the end of 2023, the World Health Organization (WHO) identified climate change as the greatest threat to human health. Global climate change is due to rising atmospheric concentrations of greenhouse gasses, primarily due to the burning of fossil fuels, mainly by populations in developed and developing countries. In 2022, the world experienced the highest temperatures for over 100,000 years. However, in 2022, global investment in fossil fuels increased by 10% and reached more than USD 1 trillion. The 2023 Lancet Commission report concluded that there has been little progress in protecting individuals from the adverse health effects of climate change. It is clear that global action against climate change needs to move more quickly, and the inequalities in the effects of climate change, including the impact on health, are increasing. This article aims to review the ongoing global impact of climate change on human health at individual and population levels, including recent initiatives and medical approaches to prepare for this increasing challenge.

Measurement of inward leakage of full-face masks in EN and ISO standards: comparison of gas and aerosol test agents.

In Europe, respiratory protective devices must be certified before they can be marketed. Among the parameters of interest, inward leakage (IL) characterizes the tightness between the face seal and the face, to verify that the device is well-designed. European standard EN 13274-1 (2001) and International Organization for Standardization (ISO) standard ISO 16900-1 (2019) specify that IL should be measured using sodium chloride (NaCl) aerosol or sulfur hexafluoride (SF6) gas. For reusable masks made of nonporous materials, both test agents are considered equally acceptable. However, the few studies that have compared IL values measured with various aerosols and gases have come to divergent conclusions. This work then aimed to measure IL with the test agents recommended by the standards to determine whether they are really equivalent. Since krypton (Kr) is an interesting candidate for replacing SF6 in standard tests, IL was assessed with SF6 and Kr simultaneously, and with NaCl aerosol using various calculation methods. Tests were carried out on 5 models of full-face masks donned on a headform connected to a breathing machine simulating 3 sinusoidal breathing rates of various intensities. The respirator fit on the headform was evaluated using a controlled negative pressure method to determine a manikin fit factor. Four scenarios were then tested to represent very poor, bad, good, and excellent fit. Gas concentration was measured using a mass spectrometer, and IL was calculated for SF6 and Kr. A combination of 3 devices allowed the determination of the number-based concentration of particles with diameters between 20nm and 2 µm, and IL was calculated for each of the 33 channels, as well as using a cumulative number concentration. In addition, to comply with standards, a conversion was carried out to calculate IL using a cumulative mass concentration. The results of this work evidenced that the IL values measured with NaCl were systematically lower than those determined with gases. IL was also shown to vary with particle size, with a maximum value exceeding that calculated with cumulative concentrations (in number or mass). As part of the revision of the standards, protocols for measuring inward leakage should be redefined. On the one hand, acceptability thresholds should be re-evaluated according to the nature of the test agent (gas or aerosol), as it is clear that the 2 options do not give the same results for a given configuration. On the other hand, the aerosol leakage measurement protocol needs to be reworked to enable the measurement of a well-defined, robust, and reproducible inward leakage value.

Reconstruction of the Chemical Gas Concentration Distribution Using Partial Convolution-Based Image Inpainting

An interpolation method, which estimates unknown values with constrained information, is based on mathematical calculations. In this study, we addressed interpolation from an image-based perspective and expanded the use of image inpainting to estimate values at unknown points. When chemical gas is dispersed through a chemical attack or terrorism, it is possible to determine the concentration of the gas at each location by utilizing the deployed sensors. By interpolating the concentrations, we can obtain the contours of gas concentration. Accurately distinguishing the contours of a contaminated region from a map enables the optimal response to minimize damage. However, areas with an insufficient number of sensors have less accurate contours than other areas. In order to achieve more accurate contour data, an image inpainting-based method is proposed to enhance reliability by erasing and reconstructing low-accuracy areas in the contour. Partial convolution is used as the machine learning approach for image-inpainting, with the modified loss function for optimization. In order to train the model, we developed a gas diffusion simulation model and generated a gas concentration contour dataset comprising 100,000 contour images. The results of the model were compared to those of Kriging interpolation, one of the conventional spatial interpolation methods, finally demonstrating 13.21% higher accuracy. This suggests that interpolation from an image-based perspective can achieve higher accuracy than numerical interpolation on well-trained data. The proposed method was validated using gas concentration contour data from the verified gas dispersion modeling software Nuclear Biological Chemical Reporting And Modeling System (NBC_RAMS), which was developed by the Agency for Defense Development, South Korea.

Measurement of inward leakage of full-face masks in EN and ISO standards: comparison of gas and aerosol test agents.

In Europe, respiratory protective devices must be certified before they can be marketed. Among the parameters of interest, inward leakage (IL) characterizes the tightness between the face seal and the face, to verify that the device is well-designed. European standard EN 13274-1 (2001) and International Organization for Standardization (ISO) standard ISO 16900-1 (2019) specify that IL should be measured using sodium chloride (NaCl) aerosol or sulfur hexafluoride (SF6) gas. For reusable masks made of nonporous materials, both test agents are considered equally acceptable. However, the few studies that have compared IL values measured with various aerosols and gases have come to divergent conclusions. This work then aimed to measure IL with the test agents recommended by the standards to determine whether they are really equivalent. Since krypton (Kr) is an interesting candidate for replacing SF6 in standard tests, IL was assessed with SF6 and Kr simultaneously, and with NaCl aerosol using various calculation methods. Tests were carried out on 5 models of full-face masks donned on a headform connected to a breathing machine simulating 3 sinusoidal breathing rates of various intensities. The respirator fit on the headform was evaluated using a controlled negative pressure method to determine a manikin fit factor. Four scenarios were then tested to represent very poor, bad, good, and excellent fit. Gas concentration was measured using a mass spectrometer, and IL was calculated for SF6 and Kr. A combination of 3 devices allowed the determination of the number-based concentration of particles with diameters between 20nm and 2 µm, and IL was calculated for each of the 33 channels, as well as using a cumulative number concentration. In addition, to comply with standards, a conversion was carried out to calculate IL using a cumulative mass concentration. The results of this work evidenced that the IL values measured with NaCl were systematically lower than those determined with gases. IL was also shown to vary with particle size, with a maximum value exceeding that calculated with cumulative concentrations (in number or mass). As part of the revision of the standards, protocols for measuring inward leakage should be redefined. On the one hand, acceptability thresholds should be re-evaluated according to the nature of the test agent (gas or aerosol), as it is clear that the 2 options do not give the same results for a given configuration. On the other hand, the aerosol leakage measurement protocol needs to be reworked to enable the measurement of a well-defined, robust, and reproducible inward leakage value.

Detection of ethanol gas at room temperature by In2O3-based screen-printed films fabricated through particle-free aqueous solution combustible inks

Abstract The current work investigates the room temperature ethanol gas detection capabilities of pristine, Sn doped, Zn doped, Sn & Zn co-doped In2O3-based screen-printed films that are developed using particle-free aqueous solution combustible inks. The fabricated films were pure, polycrystalline with cubic bixbyite crystal structure, porous, and transparent (~75 to 95 % in the visible range). High surface roughness was detected in pristine film than in doped films. Ethanol gas of 50 to 100 ppm concentration was traced by all the films at room temperature. Among all, the pristine film showed a greater gas response at all concentrations of ethanol gas, and it was because of high oxygen vacancy concentration (OV/OL) and more relative area fraction of adsorbed oxygen (% of OA). Diminished amounts of OV/OL and % of OA caused a relatively low gas response in the doped films. The maximum ethanol gas response was discerned to be 17.3 at 100 ppm by the pristine film. The demonstrated film was also highly selective towards ethanol gas.