Toxic Gas Monitoring Research Articles

Environmental Monitoring: A Comprehensive Review on Optical Waveguide and Fiber-Based Sensors.

Globally, there is active development of photonic sensors incorporating multidisciplinary research. The ultimate objective is to develop small, low-cost, sensitive, selective, quick, durable, remote-controllable sensors that are resistant to electromagnetic interference. Different photonic sensor designs and advances in photonic frameworks have shown the possibility to realize these capabilities. In this review paper, the latest developments in the field of optical waveguide and fiber-based sensors which can serve for environmental monitoring are discussed. Several important topics such as toxic gas, water quality, indoor environment, and natural disaster monitoring are reviewed.

Internet of Things Information System and Clothing Computer Renderings Digital Art

The Internet of Things (IoT) is developing rapidly and is integrated into all aspects of life. Clothing is an indispensable part of meeting the basic needs of the human body, and its traditional functions include warmth, health care, decoration, and beauty. While as a special type of clothing that integrates multidisciplinary technology, smart clothing has a wider scope of action. With the update and iteration of science and technology, many technologies that originally belonged to nonclothing disciplines have also been applied to the clothing field. Accordingly, for the special clothing category of smart clothing based on embedded system, a set of design process that can be used for this category of smart clothing was proposed. Using this design process, an intelligent fire suit that can be used to protect the personal safety of firefighters and assist firefighters to cooperate was designed and implemented. Starting from the daily working environment and working characteristics of firefighters, this firefighting obedience analyzed the design points from the perspectives of clothing comfort, warning, toxic and harmful gas monitoring, and firefighters’ cooperation. After testing, the test results of the outer layer fabric, waterproof and moisture-permeable layer fabric, and thermal insulation and comfort layer fabric of the fire suit all met the corresponding national standards; the monitoring sensitivity of harmful gases was high; it could achieve a “good” warning effect in a dark environment. Compared with ordinary firefighting suits, it was more comfortable under the subjective and objective test and scored 0.669 higher under the seven-point scale; its interactive performance met the actual needs. The clothing has complete functions and a complete feedback mechanism, which has a positive effect on ensuring the personal safety of firefighters.

Toxic gas detection using 3-channel spark-induced plasma spectroscopy for indoor air quality monitoring

This study explored the toxic gas detection using a set of two spark-induced plasma emission spectroscopy (SIPS) modules as an alternative to conventional chemical sensors. This opens up a new possibility for detecting toxic molecules (formaldehyde, acetaldehyde, acetic acid, toluene, and ammonia) in real-time (<3 s) at relatively high sensitivity (<5 ppm). An optimized electrical controller (Raspberry Pi), manufactured as a compact and economical 3-channel optical measuring device, was developed for handling the high-resolution time-resolved electrical signals from the plasma emissions. Subsequently, the findings of this research elucidate the usability of the 3-channel SIPS device for quantitative monitoring of toxic gases.

IoT-Based Harmful Toxic Gases Monitoring and Fault Detection on the Sensor Dataset Using Deep Learning Techniques

One of the main reasons for accidents among workers is harmful gas leakage. Many people die in chemical industries and their surrounding areas. The present invention is responsible for monitoring and controlling hazardous toxic gases like nitrogen dioxide (NO2), carbon monoxide, ozone (O3), sulfur dioxide (SO2), LPG, hydrocarbon gases, silicones, hydrocarbons, alcohol, CH4, hexane, benzine, as well as environmental conditions, such as temperature and relative humidity to prevent industrial accidents. The Arduino UNO R3 board is used as the central microcontroller. It is connected to the Cloud via AQ3 sensor, Minipid 2 HS PID sensor, IR5500 open path infrared gas detector, DHT11 Temperature and Humidity Sensor, MQ3 sensor, and ESP8266 and WIFI Module, which can store real-time sensor data and send alert messages to the industry’s safety control board. Machine learning and artificial intelligence will be used to make an intelligent prediction (AI). The information gathered will be examined in real-time. The real-time data provided through the sensor can be accessed worldwide. Sensor data quality is critical in the Internet of Things (IoT) applications because poor data quality renders them useless. Error detection in sensor data improves the IoT-based toxic gas monitoring, controlling, and prediction system. Live data from sensors or datasets should be analyzed properly using appropriate techniques. Hence, hybrid hidden Markov and artificial intelligence models are applied as an error detection technique in the sensor dataset. This technique outperformed the dataset gas sensor array under dynamic gas mixtures and lived data. Our method outperformed harmful gas monitoring and error detection in sensor datasets compared to other existing technologies. The hybrid HMM and ANN fault detection methods performed well on the datasets and produced 0.01% false positive rate.

Enhanced n-butanol sensing performance of SnO2/ZnO nanoflowers fabricated via a facile solvothermal method

High-performance gas sensors have important application prospects in the detection and monitoring of toxic and harmful gases that exist in the environment and workshop. Herein, SnO2/ZnO nanoflowers with core-shell like structure were successfully fabricated by a two-step solvothermal method. Morphology and mineral phase characterizations demonstrate that the nanoflowers, composed of a SnO2 flower core in a diameter of about 50 nm and ZnO nanoparticles embedded in the interstice of SnO2 petals, has a novel mesoporous hierarchical structure with pore size distributed in about 3 nm and 30 nm and a specific surface area of 36.474 m2/g, benefitting to gas-sensing. The results reveal that, compared to pure SnO2 nanoflowers, the optimal SnO2/ZnO (Zn/Sn is 5%) based gas sensor shows 2.7-fold sensing enhancement, fast response (3 s), long-term stability toward n-butanol. It has an outstanding selectivity to n-butanol rather than other gas, its response toward 100 ppm n-butanol at 200 °C is up to 13, 34, 15 and 32 times of that to acetone, xylene, ammonia and carbon monoxide respectively. Hence, SnO2/ZnO nanoflowers can be considered as a practical sensing material for n-butanol detection.

Sensing Performance of a ZnO-based Ammonia Sensor

Monitoring and remediation of toxic and flammable gases have become a critical task for the development of a clean society. Among various types of metal oxide semiconductors (MOS), zinc oxide (ZnO) is considered a potential material for gas sensing application because of its high sensitivity, easy synthesis, and high thermal stability behaviours. This research aimed to gain an in-depth understanding of the sensing task of a very stable and porous thin film of spin coated ZnO for detecting toxic ammonia vapour at room temperature. As-prepared ZnO films were characterised by x-ray diffraction (XRD), scanning electron microscopy (SEM), and ultraviolet-visible (UV-vis) analyses. XRD and SEM results revealed the polycrystalline wurtzite ZnO phase with grainy surface morphology. Optical calculations quantify the direct band gap of ZnO as 3.2 eV. The sensitivity measurements showed a good response ratio of 38.5 ± 0.6 with an exposure of 400 ppm of ammonia vapour. The results on sensitivity measurement of several cycles illustrated its stability and sensing performance better than other reported similar works. These findings will be useful to develop a low cost and efficient room temperature MOS gas sensor that can efficiently detect extremely low concentrations as 20 ppm of ammonia vapour which is below the Occupational Safety and Health Administration (OSHA) recommended value.

Advanced polymeric/inorganic nanohybrids: An integrated platform for gas sensing applications

Rapid industrial development, vehicles, domestic activities and mishandling of garbage are the main sources of pollutants, which are destroying the atmosphere. There is a need to continuously monitor these pollutants for the safety of the environment and human beings. Conventional instruments for monitoring of toxic gases are expensive, bigger in size and time-consuming. Hybrid materials containing organic and inorganic components are considered potential candidates for diverse applications, including gas sensing. Gas sensors convert the information regarding the analyte into signals. Various polymeric/inorganic nanohybrids have been used for the sensing of toxic gases. Composites of different polymeric materials like polyaniline (PANI), poly (4-styrene sulfonate) (PSS), poly (3,4-ethylene dioxythiophene) (PEDOT), etc. with various metal/metal oxide nanoparticles have been reported as sensing materials for gas sensors because of their unique redox features, conductivity and facile operation at room temperature. Polymeric nanohybrids showed better performance because of the larger surface area of nanohybrids and the synergistic effect between polymeric and inorganic materials. This review article focuses on the recent developments of emerging polymeric/inorganic nanohybrids for sensing various toxic gases including ammonia, hydrogen, nitrogen dioxide, carbon oxides and liquefied petroleum gas. Advantages, disadvantages, operating conditions and prospects of hybrid composites have also been discussed.

Sensing Performance of a ZnO-based Ammonia Sensor

Monitoring and remediation of toxic and flammable gases have become a critical task for the development of a clean society. Among various types of metal oxide semiconductors (MOS), zinc oxide (ZnO) is considered a potential material for gas sensing application because of its high sensitivity, easy synthesis, and high thermal stability behaviours. This research aimed to gain an in-depth understanding of the sensing task of a very stable and porous thin film of spin coated ZnO for detecting toxic ammonia vapour at room temperature. As-prepared ZnO films were characterised by x-ray diffraction (XRD), scanning electron microscopy (SEM), and ultraviolet-visible (UV-vis) analyses. XRD and SEM results revealed the polycrystalline wurtzite ZnO phase with grainy surface morphology. Optical calculations quantify the direct band gap of ZnO as 3.2 eV. The sensitivity measurements showed a good response ratio of 38.5 ± 0.6 with an exposure of 400 ppm of ammonia vapour. The results on sensitivity measurement of several cycles illustrated its stability and sensing performance better than other reported similar works. These findings will be useful to develop a low cost and efficient room temperature MOS gas sensor that can efficiently detect extremely low concentrations as 20 ppm of ammonia vapour which is below the Occupational Safety and Health Administration (OSHA) recommended value.

FA-LSTM: A Novel Toxic Gas Concentration Prediction Model in Pollutant Environment

Real-time monitoring and accurate prediction of toxic gas concentration in the future are of great significance for emergency capability assessment and rescue work. At present, the method of gas concentration prediction based on artificial intelligence still has problems of low accuracy, slow convergence speed and equal feature importance. This paper proposes a feature-aware LSTM model to predict pollutant gas concentration. First of all, we design a set of multi-component toxic gas monitoring equipment that applies in pollution environment, which can at the same time monitor CO, NO₂, NH₃, HCN, H₂S and SO₂, six common pollutants; To accurate estimate the toxic gas concentration, we combine the collected the gas data and the environmental parameters and regard them as the input features, and then we obtain toxic gas data based on the sampling policy and the environmental data as our data-set. Finally, we train a FA-LSTM gas concentration prediction model on these data-set. We test the proposed model and compared with ARIMA, ETS and BP network on the same test set. Experimental results show that the proposed model outperforms traditional concentration prediction model. Also, it is better than other state-of-the-art models in predicting accuracy.

Design of Toxic Environment Monitoring System for Industrial Sites Based on Wireless Sensor Networks

In view of the actual demand of toxic gas monitoring in the production, storage and use field environment of chemical enterprises, considering the large amount of monitoring data and the difficulty of real-time transmission of information, a toxic gas environment monitoring system is designed. The system based on low-power microcontroller chip CC2530 by using wireless sensor intelligent information processing and data communication technology, which evaluates and improves the ambient air conditions and provides theoretical basis and technical support. The sensor node collects the concentration data of CO, formaldehyde, ozone, SO2 and other toxic gases in real time, processes them and sends them to the receiving end. According to the stored data, the receiver monitors the air quality of the industrial production and storage environment in real time, and effectively solves the problems of complex wiring and maintenance difficulties of traditional cable sensors to reduce the risk of accidents or early warning and reduce the hazards of accidents. The test results show that the system has stable performance, can effectively detect industrial toxic environmental parameters, and can be widely used in various fields, especially in unattended or inaccessible environment for monitoring tasks.

Bifunctional Metal Meshes Acting as a Semipermeable Membrane and Electrode for Sensitive Electrochemical Determination of Volatile Compounds.

The monitoring of toxic inorganic gases and volatile organic compounds has brought the development of field-deployable, sensitive, and scalable sensors into focus. Here, we attempted to meet these requirements by using concurrently microhole-structured meshes as (i) a membrane for the gas diffusion extraction of an analyte from a donor sample and (ii) an electrode for the sensitive electrochemical determination of this target with the receptor electrolyte at rest. We used two types of meshes with complementary benefits, i.e., Ni mesh fabricated by robust, scalable, and well-established methods for manufacturing specific designs and stainless steel wire mesh (SSWM), which is commercially available at a low cost. The diffusion of gas (from a donor) was conducted in headspace mode, thus minimizing issues related to mesh fouling. When compared with the conventional polytetrafluoroethylene (PTFE) membrane, both the meshes (40 μm hole diameter) led to a higher amount of vapor collected into the electrolyte for subsequent detection. This inedited fashion produced a kind of reverse diffusion of the analyte dissolved into the electrolyte (receptor), i.e., from the electrode to bulk, which further enabled highly sensitive analyses. Using Ni mesh coated with Ni(OH)2 nanoparticles, the limit of detection reached for ethanol was 24-fold lower than the data attained by a platform with a PTFE membrane and placement of the electrode into electrolyte bulk. This system was applied in the determination of ethanol in complex samples related to the production of ethanol biofuel. It is noteworthy that a simple equation fitted by machine learning was able to provide accurate assays (accuracies from 97 to 102%) by overcoming matrix effect-related interferences on detection performance. Furthermore, preliminary measurements demonstrated the successful coating of the meshes with gold films as an alternative raw electrode material and the monitoring of HCl utilizing Au-coated SSWMs. These strategies extend the applicability of the platform that may help to develop valuable volatile sensing solutions.

Acidic and alkaline gas sensitive and self-healing chitosan aerogel based on electrostatic interaction

Gas pollution is a serious problem. More attention has been paid to the detection and monitoring of toxic and harmful gases, and it is urgently needed for a sensor that could simultaneously identify and distinguish between acid and base gases. Based on the electrostatic interaction resulting from amidogen of chitosan (CS) and carboxylic groups of itaconic acid (IA), we successfully prepared a series of biomass aerogels (CS-IA aerogels) that could respond to acidic and alkaline gases with different concentrations. The acidic and alkaline gases could be easily detected and distinguished by changing the content of IA in CS-IA aerogels. Moreover, the electrostatic interactions could also endowed CS-IA aerogels with self-healing ability in the breaks at room temperature. After self-healing, CS-IA aerogels still sensitively answered to acidic and alkaline gases. CS-IA aerogels with sensitivity to acid-base gas and self-healing performance has been suggested to be promising candidates as application of multi-functional aerogels.

Wearable NO2 sensing and wireless application based on ZnS nanoparticles/nitrogen-doped reduced graphene oxide

Wearable electronics consists of mechanically flexible sensor networks and the corresponding circuit system can provide real-time monitoring and recording of toxic gases. In this work, we present a convenient watch-type wearable nitrogen dioxide (NO2) sensor based on ZnS nanoparticles/nitrogen-doped reduced graphene oxide (ZnS NPs/N-rGO) as a flexible device. The power consumption of the flexible sensor is as low as 0.52 μW. The response value of the device for 10 ppm NO2 is 2.2; while the recovery time is 724 s, with a low theoretical limit of detection at 69 ppb, with the device maintaining stable mechanical durability. By reading and analyzing the signal data through wireless bluetooth transmission, the device can provide timely monitoring and early warning for NO2 leakage. Furthermore, the impressive room-temperature sensing performance of ZnS NPs/N-rGO is attributed to factors of geometrical and electronic effects. More specifically, ZnS NP uniformly dispersed on rGO greatly expands the effective contact area with the target gas molecules, and the built-in electric field formed by the strong charge interaction between them also effectively improves the detection sensitivity. The successful development of this type of wireless wearable sensor provides an effective reference for the future application and development of high-performance, low-power, and lightweight sensing equipment.

Enhanced NO2 sensing performance of ZnO@ZnS core-shell structure fabricated using a solution chemical method

Semiconductor metal oxide core-shell based sensor promises an important perspective in toxic and harmful gas detection and monitoring field. However, NO2 sensor is not only required for more excellent selectivity and sensitivity, but also a ppb level detection limit, which remains a key technological challenge. Herein, a novel mesoporous ZnO@ZnS (ZS) core-shell heterojunction was successfully fabricated using a simple solution chemical method. The results show that the as-prepared ZS has a mesoporous construction with pore dimension of 3.6 nm and a thin shell (about 4 nm in thickness) that composed of numerous ZnS nanoparticles. The ZS sensor exhibits excellent NO2 detecting properties in the range of 10 ppb–3 ppm at a relatively low temperature of 130 °C and an extremely low detection threshold of 10 ppb. The response to 1 ppm NO2 is 41.12, which is almost 6 times that of the pure ZnO. The enhanced gas-sensing performance of the ZS was achieved by the combination effect of the Schottky barrier and its mesoporous structure. It has a significant practical application prospect in NO2 detection and monitoring field.

Sensor placement optimization for fenceline monitoring of toxic gases considering spatiotemporal risk of the plant-urban interface

Toxic gas leak accidents can lead to significant casualties. The damage from a leak accident will be greater if toxic gas spreads to places where population density is high or vulnerable facilities with people who have difficulty evacuating. And the damage from leak accidents will also be greater if there is no evacuation warning from the plant despite the significant leak. Therefore, it is necessary to design the fenceline monitoring system through sensor placement optimization that reduces the risk toward the community. In this study, a mixed-integer linear programming formulation is proposed for sensor placement minimizing the risk by reflecting the characteristics of nearby areas. In order to quantitatively estimate the risk toward the community, the risk is calculated using dispersion data from computational fluid dynamics simulations and evacuation vulnerability and population density that define characteristics of a community. A case study is conducted to validate the efficiency of the proposed method. Exposed area and residual risk fraction are compared according to sensor placements from different conditions. Top-3 risk leak scenarios are analyzed quantitatively to manage the worst leak accident. It is validated that the proposed method is more efficient especially for the community that has uneven characteristics distribution.

First-Principles Insight into Pd-Doped C3N Monolayer as a Promising Scavenger for NO, NO2 and SO2.

The adsorption and sensing behavior of three typical industrial toxic gases NO, NO2 and SO2 by the Pd modified C3N monolayer were studied in this work on the basic first principles theory. Meanwhile, the feasibility of using the Pd doped C3N monolayer (Pd-C3N) as a sensor and adsorbent for industrial toxic gases was discussed. First, the binding energies of two doping systems were compared when Pd was doped in the N-vacancy and C-vacancy sites of C3N to choose the more stable doping structure. The result shows that the doping system is more stable when Pd is doped in the N-vacancy site. Then, on the basis of the more stable doping model, the adsorption process of NO, NO2 and SO2 by the Pd-C3N monolayer was simulated. Observing the three gases adsorption systems, it can be found that the gas molecules are all deformed, the adsorption energy (Ead) and charge transfer (QT) of three adsorption systems are relatively large, especially in the NO2 adsorption system. This result suggests that the adsorption of the three gases on Pd-C3N belongs to chemisorption. The above conclusions can be further confirmed by subsequent deformable charge density (DCD) and density of state (DOS) analysis. Besides, through analyzing the band structure, the change in electrical conductivity of Pd-C3N after gas adsorption was studied, and the sensing mechanism of the resistive Pd-C3N toxic gas sensor was obtained. The favorable adsorption properties and sensing mechanism indicate that the toxic gas sensor and adsorbent prepared by Pd-C3N have great application potential. Our work may provide some guidance for the application of a new resistive sensor and gas adsorbent Pd-C3N in the field of toxic gas monitoring and adsorption.

Detection of the organic solvent vapors by the optical gas sensors based on polyaminoarenes

The important problem to ensure the safety of life is the development of effective methods for monitoring of toxic gases in the atmosphere and industrial premises. To ensure such control, various gas sensors are developed that work on the effects of changes in electrical resistance, optical absorption or radiation in a certain spectral range. Most known gas sensors have high operating temperatures, which creates some difficulties in their operation, so more and more attention is paid to sensors based on conjugated electrically conductive polymers, in particular, polyaminoarenes. In result of absorption of inorganic polar gases such as ammonia, nitrogen oxide, hydrogen chloride and others the significant changes in conductivity, optical absorption and morphology of polyaminoarene films are observed. However influence of organic solvent vapors on the optical spectra of polyaminoarene films for today is poorly studied. In the present work the functional polymer films of polyanisidine (PoA) and polytoluidine (PoTI) are proposed as sensitive elements of optical sensors operating at room temperatures. The sensitive films on the transparent SnO2 surface were prepared by electrodeposition. The influence of vapors of organic solvents (dimethylformamide, tetrahydrofuran, chloroform, nitrobenzene, toluene) on the optical characteristics of PoTi and PoA films was established. The optical absorption spectra investigated PoA film was characterized by two band with maximum near 360–410 nm (π–π* transition) and broad band in the range of 620–950 nm which is a superposition of the second and third bands. Influence of organic vapors causes the changes in films coloration. The maximum of sensitivity to the organic vapors for PoTI films in all cases is observed at λ &gt; 550 nm and extends to near-infra-red area indicating a formation of free charge carriers of polaron type. Nonpolar solvent vapors insignificantly affect the optical properties of polyaminoarene films responсes to spectral changes in the visible and NIR range of spectrum. A highest gas sensitivity of optical signal was observed under influence of dimethylformamide and tetrahydrofuran vapors. The time to establish the steady-state value of the optical response is 30–60 s for PoTi, while for PoA reaches 120–180 s depending on the nature of organic vapors.

Highly Sensitive Ammonia Gas Detection at Room Temperature by Integratable Silicon Nanowire Field-Effect Sensors.

Toxic gas monitoring at room temperature (RT) is of great concern to public health and safety, where ultrathin silicon nanowires (SiNWs), with diameter <80 nm, are ideal one-dimensional candidates to achieve high-performance field-effect sensing. However, a precise integration of the tiny SiNWs as active gas sensor channels has not been possible except for the use of expensive and inefficient electron beam lithography and etching. In this work, we demonstrate an integratable fabrication of field-effect sensors based on orderly SiNW arrays, produced via step-guided in-plane solid-liquid-solid growth. The back-gated SiNW sensors can be tuned into suitable subthreshold detection regime to achieve an outstanding field-effect sensitivity (75.8% @ 100 ppm NH3), low detection limit (100 ppb), and excellent selectivity to NH3 gas at RT, with fast response/recovery time scales (Tres/Trec) of 20 s (at 100 ppb NH3) and excellent repeatability and high stability over 180 days. These outstanding sensing performances can be attributed to the fast charge transfer between adsorbed NH3 molecules and the exposed SiNW channels, indicating a convenient strategy to fabricate and deploy high-performance gas detectors that are widely needed in the booming marketplace of wearable or portable electronics.

Towards a low cost fully integrated IGZO TFT NO2 detection and quantification: A solution-processed approach

Abstract Semiconducting metal oxide gas sensors that are inexpensive, room temperature operable are imperative for toxic gas and air pollution monitoring. The heating or continuous light activation requirements are unavoidable for these types of gas sensors. This paper reports for the first time a room temperature operable solution-processed In-Ga-Zn-O thin-film transistor (TFT) gas sensor to detect NO2 without continuous light activation. The TFT sensor exhibits promising sensing and selectivity towards NO2. The devices are re-generable and require light activation only to recover after exposure to the gas. Kelvin probe force microscopy characterization studies are performed to understand in detail the sensing mechanism of the solution-processed TFT device. A novel solution-processed TFT based gas-sensitive digital indicators that yield digital output quantifying the NO2 concentration are demonstrated. One of the integrated gas-sensitive digital indicators is developed using only two InGaZnO TFTs incorporating a signal conditioning circuit and analog to digital converter. Furthermore, it paves the way for portable, compact, and inexpensive systems for various gas sensing applications, including smart cities and sustainable ecosystems.

Hydrogen sulfide gas sensor based on TiO2–ZnO composite sensing membrane-coated no-core fiber

A novel hydrogen sulfide (H2S) gas sensor based on multimode interference is proposed and presented. The sensor is constructed by a 30 mm no-core fiber (NCF) and two 30 mm thin-core fibers (TCFs). The first part of the TCF is excited by the high-order modes, in the second part of TCF, the basic core and high-order modes are coupled to the last single-mode fiber, which can induce inter-mode interference. Titanium dioxide–zinc oxide (TiO2–ZnO) composite film is coated on the outside surface of the NCF by the dip-coating method. The experimental results indicate that there is a good linear relationship between the wavelength shift and the different H2S gas concentrations. The sensor has a sensitivity of 21.26 pm ppm−1 in the gas range of 0–50 ppm H2S. In addition, the TiO2–ZnO composite sensing membrane has good selectivity for H2S gas. The response and recovery times are about 90 s and 115 s, respectively. The sensor has the advantages of simple structure, high sensitivity, easy manufacture and could be used in toxic H2S gas monitoring.