Hazardous Gases Research Articles

Design of smart nose system for hazardous zone

The sole goal of the project is to develop design along with production of a novel smart nose system capable of accurately sensing and identifying a wide range of chemical gases. This innovative technology will utilize advanced gas sensors, data processing, and machine learning techniques to enable real-time gas detection and identification, with potential applications in various fields, including environmental monitoring, industrial safety, and healthcare. The vital goal is to create a reliable, user-friendly, and versatile device that enhances our ability to detect and respond to hazardous gases in our surroundings, ultimately contributing to safety, environmental preservation, and public health. The system will integrate wireless communication for remote monitoring and control, ensuring convenience and accessibility for end-users. Furthermore, the smart nose will be designed to have low power consumption, making it suitable for deployment in remote and resource-limited settings. Prototyping and rigorous testing will be conducted to validate the system's performance and robustness. The project aims to push the boundaries of current gas sensing technologies, paving the way for future advancements in smart environmental sensing.

The application of PPE at the Juanda meteorological station (BMKG)

The application of Personal Protective Equipment (PPE) at the Meteorology, Climatology, and Geophysics Agency (BMKG) is an important step in maintaining employees’ safety and health in their work environment. Even though BMKG is not involved in heavy industrial activities, there are still potential hazards and risks that need to be addressed in carrying out meteorological, climatological, and geophysical tasks. This study aims to describe the importance of implementing PPE in the BMKG environment, especially the Aviation Meteorological Station, where we took a case study at the Juanda Meteorological Station. First, we identify potential hazards that may be faced by BMKG employees, such as radiation risk, potential for hazardous gas explosions or fires, extreme weather conditions, and risks of physical injury. In the face of these risks, the use of proper PPE can help protect employees from hazardous exposures, and gas explosions and prevent injury. Next, we discuss the factors that need to be considered in implementing PPE at the BMKG. This includes a comprehensive risk assessment, identification of appropriate PPE for specific hazards, training of employees on the use and care of PPE, and regular monitoring and maintenance of the PPE used. Therefore, by implementing the Occupational Health and Safety Management System, in this case, the application of PPE, BMKG can ensure that employees have a safe and healthy work environment, reduce the risk of work accidents, and comply with applicable regulations and standards related to work safety.

Rational design of hybrid sensor arrays combined synergistically with machine learning for rapid response to a hazardous gas leak environment in chemical plants

Combinations of semiconductor metal oxide (SMO) sensors, electrochemical (EC) sensors, and photoionization detection (PID) sensors were used to discriminate chemical hazards on the basis of machine learning. Sensing data inputs were exploited in the form of either numerical or image data formats, and the classification of chemical hazards with high accuracy was achieved in both cases. Even a small amount of gas sensing or purging data (input for ∼30 s) input can be exploited in machine-learning-based gas discrimination. SMO sensors exhibit high performance even in a single-sensor mode, presumably because of the intrinsic cross-sensitivity of metal oxides, which is otherwise considered a major disadvantage of SMO sensors. EC sensors were enhanced through synergistic integration of sensor combinations with machine learning. For precision detection of multiple target analytes, a minimum number of sensors can be proposed for gas detection/discrimination by combining sensors with dissimilar operating principles. The Type I hybrid sensor combines one SMO sensor, one EC sensor, and one PID sensor and is used to identify NH3 gas mixed with sulfur compounds in simulations of NH3 gas leak accidents in chemical plants. The portable remote sensing module made with a Type I hybrid sensor and LTE module can identify mixed NH3 gas with a detection time of 60 s, demonstrating the potential of the proposed system to quickly respond to hazardous gas leak accidents and prevent additional damage to the environment.

Simulation study of a planar quadrupole mass filter for MEMS mass spectrometer

Micro-electro-mechanical system (MEMS) based mass spectrometry, MEMS mass spectrometry, emerges a new technique branch of miniature mass spectrometry. One of the main challenges hindering the development of MEMS mass spectrometry is the poor compatibility between the complex electrode structure of traditional ion optics and MEMS processes. This paper proposed a planar quadrupole mass filter utilizing a highly simplified stacked-layer structure and film electrodes, which is easy to fabricate with high precision by MEMS surface micromachining. The ion trajectory simulation model of the MEMS mass spectrometry chip involving all necessary ion optics was elaborated for investigating the preliminary performance of the planar quadrupole mass filter. By optimizing the crucial parameters such as the frequency of radio frequency voltage, the ratio of direct current voltage and radio frequency voltage, pre-pole length, main-pole length, and injection kinetic energy, the preliminary simulation result of planar quadrupole mass filter achieved a 1–2 Da peak width (at 50% of peak height) and 20–80% ion transmission efficiency. Importantly, the planar quadrupole mass filter demonstrated a maximum working pressure of 0.1 Pa (using air as the buffer gas), 100 times higher than that of conventional quadrupole mass filters, while maintaining a 0.7–1.8 Da peak width and ∼5% ion transmission efficiency. Additionally, to modify the theoretical formulas for the non-ideal quadrupolar field of planar quadrupole mass filter, a novel approach based on stability diagrams obtained by simulation was also introduced. The pretty good linearity (R2=1) between ion masses in the range of 10 to 100 Da and the corresponding radio frequency voltages was verified through the simulated mass spectra. Notably, the proportional coefficient of ion mass and radio frequency voltage exhibited a minimal 4% deviation between the simulated value (4.7132 V0P/Da) and the calculated value (4.9036 V0P/Da) through the modified formula. In conclusion, the preliminary simulation results demonstrated that the planar quadrupole mass filter possessed moderate performance, high-pressure tolerance, and excellent theoretical consistency, which proved it a promising technology of MEMS mass spectrometry. It can find applications in the fields of gas detection, including the rapid response to hazardous gas emissions and in situ detection of dissolved gases in the deep sea.

Comprehensive study on incineration-based disposal of hazardous gas and liquid wastes from used lubricating oil refineries

In this study, an incinerator is researched for the disposal of gaseous and liquid hazardous wastes (HWs) from the used lubricating oil refinery by incineration, following the zero-waste principle. Subsequently, combustion characterization of mixed-content HWs from different entrances of the combustion chamber in the incinerator, simultaneously with natural gas without mixing, is investigated experimentally, theoretically, and numerically. The HWs consist of gaseous ones from distillation and hydroprocessing and from the tank farm, and liquid ones resulting from petroleum refining processes. The results show that the combustion gases from HWs and natural gas are maintained at a minimum of 850 °C for at least 2 s in the 1.6 m diameter and 6 m length incinerator. The upper wall exhibits higher temperatures compared to the lower wall due to the heat generated during combustion, emphasizing the significance of material selection and design to withstand thermal stresses. A comprehensive analysis provides insights into the compatibility of the combustion chamber design with chemical processes, further underlining its contributions to environmental sustainability. Thus, this study demonstrates the effectiveness of mathematical and numerical analyses in improving the incineration process, ensuring the thorough combustion of hazardous waste, and minimizing the formation of harmful by-products.

Ruthenium, rhodium decorated perfect and Te-vacancy MoTe2 monolayer for industrial hazardous gases detection and scavenging

With the rapid development of industry and soaring of the global economy, the atmospheric pollution and human poisoning problems turn to a harsh circumstance. Accurate online monitoring and scavenging of industrial hazardous gases have become a bottleneck in recent years. In this paper, the adsorption mechanism and electrical properties of Ruthenium, Rhodium decorated perfect and Te-vacancy MoTe2 monolayer towards hazardous gases (SO2, CO, NH3) were firstly explored based on density functional theory. Comparing the adsorption behavior differences between perfect surface MoTe2 and Te atom vacancy MoTe2 through the analysis of density of states differential charge density and molecular orbital theory. The results show that the dopant reduces the band gap and enhances the surface competence. In addition, the trapping ability of the metal-modified defective MoTe2 to hazardous gases is inferior to that of the perfect MoTe2, and both adsorption types are physico-chemical adsorption. Modified MoTe2 could obtain the ideal recovery time as a NH3 gas sensor. CO are more difficult to detach from the mixture’ surfaces, which is a good proof for the CO adsorbent. The data provides the basis for the design of metal particle decoration based MoTe2 nanomaterials employed in the detection and scavenging of hazardous gases.

Kinetic modeling of a Claus reaction furnace and waste heat boiler: Effects of H2S/CO2 and H2S/H2O ratio on the production of hazardous gases in an industrial sulfur recovery unit

In this study, the reaction furnace (RF) and waste heat boiler (WHB) were modeled using a kinetic model developed from key reactions to determine how the input feed in the various acid gas scenarios affects the Sulfur Recovery Unit's (SRU's) thermal stage for industrial application. The modeling results showed that, while keeping other parameters constant, a decrease in the H2S/CO2 and H2S/H2O ratios leads to an increase in the production of hazardous gases such as CO, SO2, and COS in the Waste Heat Boiler (WHB). Consequently, this leads to a decrease in the efficiency of the Sulfur Recovery Unit (SRU). When the temperature profile is altered, the Claus reaction pathway changes unfavorably, consequently affecting the overall efficiency of the Claus process. The accuracy of the kinetic model decreases as the acid gas becomes more dilute, significantly impacting the temperature profile. The accuracy of these results was confirmed through industrial data spanning from typical acid gas to sweet gas, with a Mean Absolute Percentage Error (MAPE) ranging from 26.18 to 47.37.

Effect of heat input on the hazardous gas emissions from galvanized steel during cold metal transfer welding

The impact of heat input on the hazardous gas emissions of cold metal transfer welded zinc-coated steel joints is the main focus of this study. The bulk formation of fumes during the arc-assisted metal joining process not only affects the characteristics of joints but also, affects the welder’s respiratory systems and environment. Hence, in this research work, using a stack-monitoring kit the welding fumes are collected for various heat inputs and characterized to understand the hazardous emission from zinc-coated steel by the Cold Metal Transfer - 400TPSi advanced technique. The experimental work conducted for the heat input of 0.624 kJ/mm showed superior results for fume formation rate, dust emission rate and emission factor when compared to other heat inputs. In addition, the dust emission rate and fume formation rate increased as the heat input increased. Also, Hazardous gas emissions of CO2, SO2, CO, Zinc and the concentration of total dust for the corresponding heat input were found to be within permissible limits. Furthermore, the TEM analysis exhibits that, the particle structure of the fume is agglomerated chains of spherical and faceted morphology. The outcomes prove outstanding results when compared to other welding processes and norms of the NIOSH and ISI 5182 standards.

A novel on design and implementation of hybrid MPPT controllers for solar PV systems under various partial shading conditions

At present, fossil fuel-based power generation systems are reducing drastically because of their less availability in nature. In addition, it produces hazardous gasses and high environmental pollution. So, in this work, the solar natural source is selected for generating the electricity. Due to the nonlinear behavior of PV, achieving maximum voltage from the Photovoltaic (PV) system is a more tough job. In this work, various hybrid optimization controllers are studied for tracing the working power point of the PV under different Partial Shading Conditions. The studied hybrid optimization MPPT methods are equated in terms of oscillations across MPP, output power extraction, settling time of the MPP, dependency on the PV modeling, operating duty value of the converter, error finding accuracy of MPPT, algorithm complexity, tracking speed, periodic tuning required, and the number of sensing parameters utilized. Based on the simulative comparison results, it has been observed that the modified Grey Wolf Optimization based ANFIS hybrid MPPT method provides good results when equated with the other power point tracking techniques. Here, the conventional converter helps increase the PV source voltage from one level to another level. The proposed system is investigated by using the MATLAB/Simulink tool.

Chemical Ecology, Detection and Identification of Subterranean Termites Based on Electronic-Nose Volatile Emissions Analysis

The effective monitoring and identification of existing subterranean termite populations within coarse woody debris and infested wood in service depend on accurate detection. These insects are often concealed within logs, wooden support structures, walls, and floorboards of buildings. In the absence of external mud tubes, termite infestations normally must be discovered through the destructive exploration of wooden structures to reveal the physical presence of these insect pests. Subterranean termite species are difficult to identify due to similarities in morphological features, but they may be readily distinguished by differences in volatile emissions from which they are divided into chemotaxonomic groups. Consequently, a more effective and nondestructive approach for detection and identification is to take advantage of unique species-specific emissions of volatile organic compounds (VOCs) from termite bodies which easily pass through wooden structures, allowing for detection without physical damage to wood and avoiding expensive DNA analysis. Electronic aroma detection analyses were conducted with an Aromascan A32S electronic-nose (e-nose) instrument, fitted with a 32-sensor conducting polymer (CP) sensor array, for discrimination between four common subterranean termite species based on differences in volatile emissions. Principal component analysis (PCA) of whole-body volatiles effectively distinguished between four termite species with the first two principal components accounting for more than 98% of sample variance (p < 0.01). Unique electronic aroma signature patterns (smellprints) were produced from e-nose sensor array outputs that allowed for the effective identification of termite species based on distinct differences in volatile metabolites released from their bodies. The e-nose methods were determined to be an improved means for rapidly detecting and monitoring termite species in wood. The method is cheaper than conventional detection methods and allows for the timelier discovery of species-specific termite infestations necessary for better management. The e-nose capability of detecting the Formosan termite in indoor living spaces was particularly significant due to the production of naphthalene, a volatile hazardous gas causing many adverse human health effects in enclosed environments.

Hydrogen Sulfide Adsorption Mechanism and Breakthrough Curves of Highly Stable Na-, Na-H-, Ca- and K-Mordenites.

Hydrogen sulfide (H2S) is a hazardous gas found in natural gas and biogas, lethal over 100 ppm. When released into the atmosphere, it can turn into sulfur dioxide. One option to remove H2S is using porous materials such as zeolites. Among them, mordenite stands out due to its channel structure, wide availability, and low cost. In this work, we evaluated the H2S adsorption capacity of mordenite using a volumetric static method. The results show the adsorption capacity of H2S in mordenite varies with the exchanged cation. The highest was measured in Na-mordenite (~4.08 mmol H2S/g mordenite). The experimental breakthrough curves for this zeolite confirmed Langmuir-type adsorption and strong affinity between Na+ cations and H2S. Despite this interaction, the XRD diffractograms of Na-mordenite show that the material retained its crystalline structure. More information about the differences in the amount of H2S adsorbed in the zeolites caused by the change in exchanged cation was obtained by H2S adsorption followed by FTIR spectroscopy. The spectra show differences in the position of the peaks related to the different adsorption modes of H2S caused by a change in the polarizing power of the cations due to their charge and position inside the zeolite pores.

Analysis on occupational dust or harmful gas exposure and protection in people aged 40 and above in China, 2019-2020

Objective: To understand the current status of occupational exposure to dust or harmful gases and occupational protection in people aged ≥40 years in China, and provide data support for the prevention and control of occupational dust or harmful gas exposure. Methods: The data were obtained from the surveillance for chronic obstructive pulmonary disease (COPD) in adults aged ≥40 years selected by multi-stage stratified cluster sampling from 125 surveillance points in 31 provinces (autonomous regions and municipalities) during 2014-2015 and 2019-2020, and relevant information about occupational dust or harmful gas exposure and protection measures were collected through face-to-face interviews. Occupational dust or harmful gas exposure rate and occupational protection rate were estimated by using weighting complex sampling methods, and then the results were compared. Results: From 2014 to 2015 and from 2019 to 2020, a total of 71 061 and 71 023 individuals aged ≥40 years were surveyed, respectively. The rate of occupational exposure to dust or hazardous gas was 33.8% (95%CI: 29.9%-37.7%) during 2019-2020. The occupational exposure rate was higher in men than in women and in rural residents than in urban residents. With the increase of education level, the rate of occupational exposure to dust or harmful gas showed a downward trend. The protection rate against occupational dust or hazardous gas exposure was 47.9% (95%CI: 43.2%-52.6%) during 2019-2020. Compared with 2014-2015, the rate of occupational exposure to dust or hazardous gas decreased by 10.7 percentage points in different gender, area and occupational groups and the occupational protection rate increased by 21.9 percentage points during 2019-2020. The decrease in occupational exposure rate was higher in western China than in eastern and central China, and the increase in occupational protection rate was higher in western China than in eastern and central China. Conclusions: The rate of occupational exposure to dust or harmful gas decreased and the rate of occupational protection against dust or harmful gas exposure increased in China during 2019-2020. However, about one-third of the population still suffer from the occupational exposure, and less than half of them take protection measures. It is necessary to pay more attention to the key populations, such as workers with lower cultural level and rural migrant workers, in occupational health practice.

Optimizing Winter Air Quality in Pig-Fattening Houses: A Plasma Deodorization Approach.

This study aimed to evaluate the effect of two circulation modes of a plasma deodorization unit on the air environment of pig-fattening houses in winter. Two pig-fattening houses were selected, one of which was installed with a plasma deodorizing device with two modes of operation, alternating internal and external circulation on a day-by-day basis. The other house did not have any form of treatment and was used as the control house. Upon installing the system, this study revealed that in the internal circulation mode, indoor temperature and humidity were sustained at elevated levels, with the NH3 and H2S concentrations decreasing by 63.87% and 100%, respectively, in comparison to the control house. Conversely, in the external circulation mode, the indoor temperature and humidity remained subdued, accompanied by a 16.43% reduction in CO2 concentration. The adept interchange between these two operational modes facilitates the regulation of indoor air quality within a secure environment. This not only effectively diminishes deleterious gases in the pig-fattening house but also achieves the remote automation of environmental monitoring and hazardous gas management; thereby, it mitigates the likelihood of diseases and minimizes breeding risks.

Theoretical Investigation of TiSiO4 Monolayer Membranes for Highly Selective H2S Detection from Hazardous Gas Mixtures

Theoretical Investigation of TiSiO₄ Monolayer Membranes for Highly Selective H₂S Detection from Hazardous Gas Mixtures

Multifunctional polylactic acid sensing fabric based on biomass flame retardants for intelligent fire early-warning

Today, building materials emit many hazardous gases in the event of a fire, causing great harm to human health and the environment. Therefore, it is of great significance to develop bio-based flame retardant materials and to realize preventive measures to reduce fires or their damage. In this work, we fabricated a novel multifunctional fire early-warning polylactic acid-based fabric (MFR-PBF) by coating MXene nanosheet, phytic acid @ furfurylamine (PA@FA) and ammonium polyphosphate (APP) via an eco-friendly layer-by-layer assembly method. MFR-PBF showed outstanding flame retardancy including a limiting oxygen index value of 35 % and better char formation capacity. More importantly, MFR-PBF exhibited sensitive fire early-warning capability (∼1 s) and excellent cyclic alarm stability (>15 cycles) due to the excellent semiconductor responsiveness (light and heat) and the significant catalytic char formation effect. Moreover, MFR-PBF is comfortable, flexible and strong enough to sew onto firefighter uniform to detect a variety of human motions, which can be monitored in the internet by using a LoRa emitter and a gateway. In addition, the controllable heating performance rendered MFR-PBF as a potential portable heater. This work provides new insights into the preparation and application of intelligent fire early-warning fabrics in the smart fire protection and Internet of Things.

EFFICIENT PLANT GAS LEAKAGE DETECTION AND MONITORING SYSTEM BASED ON IOT INTEGRATION

In industrial areas, fire breakouts often stem from gas leaks within the surrounding environment. These leaks could be caused by faulty apparatus, inadequate maintenance, or human mistake either during handling or storage of flammable gases. The presence of combustible gases poses a significant risk, as they can ignite easily and escalate into large-scale fires, endangering both personnel and property within the industrial site. This research employs a compact detection device capable of identifying combustible gases like propane, LPG Gas, Carbon Monoxide, butane, and other hazardous gases. The device is designed to identify these gases quickly and accurately, aiding in ensuring safety in various environments such as industrial sites, homes, and workplaces. The leakage detector includes NODEMCU, gas sensors, buzzer, and LCD system. When harmful gases surpass acceptable thresholds, the micro-controller initiates a alerting SMS using Blynk server. The prototype emits a sound alert and illuminates LCDs to indicate the leaking gas. Gas concentration datais sent to Thinkspeak server for easy monitoring by plant personnel.

MILITARY SURVEILLANCE BOT

This research describes a cutting-edge method for border and distant surveillance using multipurpose robots that are based on the most recent 3G technology used in defense and military applications. This autonomous vehicle has the capacity to conduct surveillance in border regions in place of soldiers. Using the internet as a communication tool, the robotic vehicle may be operated both manually and autonomously. This multimodal robot is employed in distant and combat zones to detect fire, explosives, hazardous gasses, and people. Traditional wireless security robots are rendered obsolete by their constrained human control and frequency range. The use of 3G technology, which has an infinite range, allows one to overcome these restrictions. By using solar panels, this system further improves the usage of renewable energy sources. Infrared and ultrasonic sensors are used to operate autonomously. The DTMF decoder controls the manual operation, and mobile phones are employed as video cameras by initiating 3G video calls and modifying the robot's course based on surrounding real-time information. The experimental findings of the solar panel's tilt angle selection and power consumption in both automated and manual modes are also shown in this study. Under certain conditions, this robotic vehicle may be used for both surveillance and reconnaissance.

Multi-gas pollutant detection based on sparrow search algorithm optimized ALSTM-FCN.

It is critical to identify and detect hazardous, flammable, explosive, and poisonous gases in the realms of industrial production and medical diagnostics. To detect and categorize a range of common hazardous gasses, we propose an attention-based Long Short term memory Full Convolutional network (ALSTM-FCN) in this paper. We adjust the network parameters of ALSTM-FCN using the Sparrow search algorithm (SSA) based on this, by comparison, SSA outperforms Particle Swarm Optimization (PSO) Algorithm, Genetic Algorithm (GA), Gray Wolf Optimization (GWO) Algorithm, Cuckoo Search (CS) Algorithm and other traditional optimization algorithms. We evaluate the model using University of California-Irvine (UCI) datasets and compare it with LSTM and FCN. The findings indicate that the ALSTM-FCN hybrid model has a better reliability test accuracy of 99.461% than both LSTM (89.471%) and FCN (96.083%). Furthermore, AdaBoost, logistic regression (LR), extra tree (ET), decision tree (DT), random forest (RF), K-nearest neighbor (KNN) and other models were trained. The suggested approach outperforms the conventional machine learning model in terms of gas categorization accuracy, according to experimental data. The findings indicate a potential for a broad range of polluting gas detection using the suggested ALSTM-FCN model, which is based on SSA optimization.

Концентрационные пределы распространения пламени сжиженного природного газа

Concentration limits of flame propagation are the fundamental indicator in determining fire and explosion hazard of combustible gases. Correct determination of this parameter allows to assess the possibility of ignition of gas-air mixture. The issues of determining the concentration limits of flame propagation are represented by a large number of experimental and theoretical studies. Despite this, in the literature these indicators for the same combustible mixture differ markedly from each other. This fact is explained by different experimental conditions, as well as different approaches to analyzing the research results. Inaccuracies may arise due to the exclusively thermal approach to determining ignition limits. Although the chain-thermal theory of flame propagation is currently developed. In addition, when determining the concentration limits of flame propagation for mixed compositions, the effect of the mixture components on each other cannot be neglected. In practice, the mixture of hydrocarbons is the liquefied natural gas. Its intensive development in Russia requires a qualitative assessment of the explosion and fire hazard, in particular, the flammability limits indicators. Currently, the concentration limits of flame propagation of the liquefied natural gas vapors are determined by methane. Therefore, the application of the existing approach introduces significant errors in the determination of these indicators. On the basis of the conducted experiments, the legitimacy of applying Le Chatelier's rule for technical calculations of the concentration limits of flame propagation of a mixture of the liquefied natural gas vapors with air was established. This allows to use a differentiated approach in calculations for different compositions of the liquefied natural gas.

Emerging trends in metal oxide-based electronic noses for healthcare applications: a review.

An electronic nose (E-nose) is a technology fundamentally inspired by the human nose, designed to detect, recognize, and differentiate specific odors or volatile components in complex and chaotic environments. Comprising an array of sensors with meticulously designed nanostructured architectures, E-noses translate the chemical information captured by these sensors into useful metrics using complex pattern recognition algorithms. E-noses can significantly enhance the quality of life by offering preventive point-of-care devices for medical diagnostics through breath analysis, and by monitoring and tracking hazardous and toxic gases in the environment. They are increasingly being used in defense and surveillance, medical diagnostics, agriculture, environmental monitoring, and product validation and authentication. The major challenge in developing a reliable E-nose involves miniaturization and low power consumption. Various sensing materials are employed to address these issues. This review presents the key advancements over the last decade in E-nose technology, specifically focusing on chemiresistive metal oxide sensing materials. It discusses their sensing mechanisms, integration into portable E-noses, and various data analysis techniques. Additionally, we review the primary metal oxide-based E-noses for disease detection through breath analysis. Finally, we address the major challenges and issues in developing and implementing a portable metal oxide-based E-nose.