Search Results (5,251)

We surveyed the air quality conditions in 18 homes with gas stoves for PM_2.5, CO₂, NO₂ and CO using calibrated low-cost sensors. In each home, participants were asked to cook as usual, but to record their cooking activities and mitigation efforts (windows, ventilation fans, etc.). All homes showed enhanced pollutants during, and immediately after, times of cooking or stove use. For each home, we quantified the minutes per day and minutes per minute of cooking over known health thresholds for each pollutant. On average, homes exhibited 38 min per day over one or more of these thresholds, with PM_2.5 and NO₂ being the pollutants of greatest concern. Six homes had much higher occurrences over the health thresholds, averaging 73 min per day. We found an average of 1.0 min over one or more of the health thresholds per minute of cooking when no mitigation was used, whereas when mitigation was used (filtration or vent fan), this value was reduced by 34%. We further investigated several mitigation methods including natural diffusion, a commercial HEPA filter unit, a commercial O₃ scrubber and a ventilation fan. We found that the HEPA unit was highly effective for PM_2.5 but had no impact on any of the gaseous pollutants. The O₃ scrubber was moderately effective for NO₂ but had little impact on the other pollutants. The ventilation fan was highly effective for all pollutants and reduced the average pollutant lifetime significantly. Under controlled test conditions, the pollutant lifetime (or time to reach 37% of the original concentration), was reduced from an average of 45 min (with no ventilation) to 7 min. While no commercial filter showed efficacy for both PM_2.5 and NO₂, the fact that each could be removed individually suggests that a combined filter for both pollutants could be developed, which would significantly reduce health impacts in homes with gas stoves. Full article

Volatile organic compounds (VOCs) are presently posing a rather considerable threat to both human health and environmental sustainability. Among these, n-butanol is commonly identified as bringing potential hazards to environmental integrity and individual health. This study presents the creation of a highly sensitive n-butanol gas sensor utilizing cobalt-doped zinc oxide (ZnO) derived from a metal–organic framework (MOF). A series of x-Co/MOF-ZnO (x = 1, 3, 5, 7 wt%) nanomaterials with varying Co ratios were generated using the homogeneous co-precipitation method and assessed for their gas-sensing performances under a low operating temperature (191 °C) and UV excitation (220 mW/cm²). These findings demonstrated that the 5-Co/MOF-ZnO sensor presented the highest oxygen vacancy (O_v) concentration and the largest specific surface area (SSA), representing the optimal reactivity, selectivity, and durability for n-butanol detection. Regarding the sensor’s response to 100 ppm n-butanol under UV excitation, it achieved a value of 1259.06, 9.80 times greater than that of pure MOF-ZnO (128.56) and 2.07 times higher than that in darkness (608.38). Additionally, under UV illumination, the sensor achieved a rapid response time (11 s) and recovery rate (23 s). As a strategy to transform the functionality of ZnO-based sensors for n-butanol gas detection, this study also investigated potential possible redox reactions occurring during the detection process. Full article

With the development of various new types of instrumental aroma sensing technologies, there is a need for methodologies that help developers and users evaluate the performance of the different devices. This study introduces a simple method that uses standard coffee beverages, reproducible worldwide, thus allowing users to compare aroma sensing devices and technologies globally. Eight different variations of commercial coffee capsules were used to brew espresso coffees (40 mL), consisting of either Arabica coffee or a blend of Robusta and Arabica coffee, covering a wide range of sensory attributes. The AlphaMOS Astree electronic tongue (equipped with sensors based on chemically modified field-effect transistor technology) and the AlphaMOS Heracles NEO and the Volatile Scout3 electronic noses (both using separation technology based on gas chromatography) were used to describe the taste and odor profiles of the freshly brewed coffee samples and also to compare them to the various sensory characteristics declared on the original packaging, such as intensity, roasting, acidity, bitterness, and body. Linear discriminant analysis (LDA) results showed that these technologies were able to classify the samples similarly to the pattern of the coffees based on the human sensory characteristics. In general, the arrangement of the different coffee types in the LDA results—i.e., the similarities and dissimilarities in the types based on their taste or smell—was the same in the case of the Astree electronic tongue and the Heracles electronic nose, while slightly different arrangements were found for the Scout3 electronic nose. The results of the Astree electronic tongue and those of the Heracles electronic nose showed the taste and smell profiles of the decaffeinated coffees to be different from their caffeinated counterparts. The Heracles and Scout3 electronic noses provided high accuracies in classifying the samples based on their odor into the sensory classes presented on the coffee capsules’ packaging. Despite the technological differences in the investigated devices, the introduced coffee test could assess the similarities in the taste and odor profiling capacities of the aroma fingerprinting technologies. Since the coffee capsules used for the test can be purchased all over the world in the same quality, these coffees can be used as global standard samples during the comparison of different devices applying different measurement technologies. The test can be used to evaluate instrumentational and data analytical developments worldwide and to assess the potential of novel, cost-effective, accurate, and rapid solutions for quality assessments in the food and beverage industry. Full article

Ammonia, as a toxic and corrosive gas, is widely present in industrial emissions, agricultural activities, and disease biomarkers. Detecting ammonia is of vital importance to environmental safety and human health. Sensors based on MXene have become an effective means for detecting ammonia gas due to their unique hierarchical structure, adjustable surface chemical properties, and excellent electrical conductivity. This study reviews the latest progress in the use of MXene and its composites for the low-temperature detection of ammonia gas. The strategies for designing MXene composites, including heterojunction engineering, surface functionalization, and active sites, are introduced, and their roles in improving sensing performance are clarified. These methods have significantly improved the ability to detect ammonia, offering high selectivity, rapid responses, and ultra-low detection limits within the low-temperature range. Successful applications in fields such as industrial safety, food quality monitoring, medical diagnosis, and agricultural management have demonstrated the multi-functionality of this technology in complex scenarios. The challenges related to the material’s oxidation resistance, humidity interference, and cross-sensitivity are also discussed. This study aims to briefly describe the reasonable design based on MXene sensors, aiming to achieve real-time and energy-saving environmental and health monitoring networks in the future. Full article

The visual colorimetric sensing of total volatile basic nitrogen (TVB-N) allows for convenient dynamic monitoring of animal-derived food freshness to ensure food safety. The agarose hydrogel loaded with the natural dye juglone (Jug@AG) prepared in this study exhibits visible multicolor changes from yellow to grayish-yellow and then to brownish with increasing TVB-N gas concentration, achieving sensitive detection of TVB-N gas at concentrations as low as 0.05 mg/dm³ within 8 min. The minimum observable amounts of TVB-N in spiked pork and fish samples are 8.43 mg/100 g and 8.27 mg/100 g, respectively, indicating that the Jug@AG hydrogel possesses sensitive colorimetric sensing capability in practical applications. The Jug@AG hydrogel also shows significant changes in color difference value (∆C) under both room temperature (25 °C) and cold storage (4 °C) conditions, with the changing trends of ∆C showing consistency with the measured TVB-N and total viable counts (TVC) during the transition of pork and fish samples from freshness to early spoilage and then to spoilage. The results indicate that the Jug@AG hydrogel can be used as a colorimetric sensor to achieve real-time dynamic freshness monitoring of animal-derived food. Full article

Natural gas storage is an effective solution to address the energy supply–demand imbalance, and underground gas storage (UGS) is a primary method for storing natural gas. The overarching goal of this study is to monitor and analyze surface deformation at the Hutubi underground gas storage facility in Xinjiang, China, which is the largest gas storage facility in the country. This research aims to ensure the stable and efficient operation of the facility through long-term monitoring, using remote sensing data and advanced modeling techniques. The study employs the SBAS-InSAR method, leveraging Synthetic Aperture Radar (SAR) data from the TerraSAR and Sentinel-1 sensors to observe displacement time series from 2013 to 2024. The data is processed through wavelet transformation for denoising, followed by the application of a Gray Wolf Optimization (GWO) algorithm combined with Variational Mode Decomposition (VMD) to decompose both surface deformation and gas pressure data. The key focus is the development of a high-precision predictive model using a Gated Recurrent Unit (GRU) network, referred to as GWO-VMD-GRU, to accurately predict surface deformation. The results show periodic surface uplift and subsidence at the facility, with a notable net uplift. During the period from August 2013 to March 2015, the maximum uplift rate was 6 mm/year, while from January 2015 to December 2024, it increased to 12 mm/year. The surface deformation correlates with gas injection and extraction periods, indicating periodic variations. The accuracy of the InSAR-derived displacement data is validated through high-precision GNSS data. The GWO-VMD-GRU model demonstrates strong predictive performance with a coefficient of determination (R²) greater than 0.98 for the gas well test points. This study provides a valuable reference for the future safe operation and management of underground gas storage facilities, demonstrating significant contributions to both scientific understanding and practical applications in underground gas storage management. Full article

There is a lack of an effective approach to measure vacuum conditions inside sealed vacuum electronic devices (VEDs) and other small-space vacuum instruments. In this study, the application performance of an innovative low-pressure gas sensor based on the emission enhancements of multi-walled carbon nanotube (MWCNT) field emitters was investigated, and the in situ vacuum performance of X-ray tubes was studied for the advantages of miniature dimension and having low power consumption, extremely low outgassing, and low thermal disturbance compared to conventional ionization gauges. The MWCNT emitters with high crystallinity presented good pressure sensing performance for nitrogen, hydrogen, and an air mixture in the range of 10⁻⁷ to 10⁻³ Pa. The miniature MWCNT sensor is able to work and remain stable with high-temperature baking, important for VED applications. The sensor monitored the in situ pressures of the sealed X-ray tubes successfully with high-power operations and a long-term storage of over two years. The investigation showed that the vacuum of the sealed X-ray tube is typical at a low 10⁻⁴ Pa level, and pre-sealing degassing treatments are able to make the X-ray tube work under high vacuum levels with less outgassing and keep a stable high vacuum for a long period of time. Full article

To address the difficulty of locating small-hole leaks in buried natural gas pipelines, this study conducted a comprehensive theoretical and numerical analysis of the acoustic characteristics associated with such leakage events. A coupled flow–acoustic simulation framework was developed, integrating gas compressibility via the realizable k-ε and Large Eddy Simulation (LES) turbulence models, the Peng–Robinson equation of state, a broadband noise source model, and the Ffowcs Williams–Hawkings (FW-H) acoustic analogy. The effects of pipeline operating pressure (2–10 MPa), leakage hole diameter (1–6 mm), soil type (sandy, loam, and clay), and leakage orientation on the flow field, acoustic source behavior, and sound field distribution were systematically investigated. The results indicate that the leakage hole size and soil medium exert significant influence on both flow dynamics and acoustic propagation, while the pipeline pressure mainly affects the strength of the acoustic source. The leakage direction was found to have only a minor impact on the overall results. The leakage noise is primarily composed of dipole sources arising from gas–solid interactions and quadrupole sources generated by turbulent flow, with the frequency spectrum concentrated in the low-frequency range of 0–500 Hz. This research elucidates the acoustic characteristics of pipeline leakage under various conditions and provides a theoretical foundation for optimal sensor deployment and accurate localization in buried pipeline leak detection systems. Full article

It is evident that a novel engineering solution is required in order to elevate a greater number of polluting cars into a higher category. There appears to be a paucity of direct interest in upgrading Euro 1, 2, 3, 4, and 5 vehicles to the highest possible level, primarily through software modifications of the parameters determining the performance of the internal combustion engine (ICE). The potential for advancement in this area is evidenced by the presence of systems that enhance environmental efficiency, even in Euro 2 vehicles. These include exhaust gas recirculation, catalytic converter, lambda sensor, electronic control fuel injection, and ignition timing. It is precisely these vehicles that are subject to optimization, a process which would allow the maximum service life of otherwise more reliable but older vehicles to be exploited. Full article

Hybrid materials based on porous organic polymers (POPs) and metal–organic frameworks (MOFs) are increasing attention for advanced separation processes due to the possibility to combine their properties. POPs provide high surface areas, chemical stability, and tunable porosity, while MOFs contribute a high variety of defined crystalline structures and enhanced separation characteristics. The combination (or hybridization) with PIMs gives rise to mixed-matrix membranes (MMMs) with improved permeability, selectivity, and long-term stability. However, interfacial compatibility remains a key limitation, often addressed through polymer functionalization or controlled dispersion of the MOF phase. MOF/COF hybrids are more used as biochemical sensors with elevated sensitivity, catalytic applications, and wastewater remediation. They are also very well known in the gas sorption and separation field, due to their tunable porosity and high electrical conductivity, which also makes them feasible for energy storage applications. Last but not less important, hybrids with other POPs, such as hyper-crosslinked polymers (HCPs), covalent triazine frameworks (CTFs), or conjugated microporous polymers (CMPs), offer enhanced functionality. MOF/HCP hybrids combine ease of synthesis and chemical robustness with tunable porosity. MOF/CTF hybrids provide superior thermal and chemical stability under harsh conditions, while MOF/CMP hybrids introduce π-conjugation for enhanced conductivity and photocatalytic activity. These and other findings confirm the potential of MOF-POP hybrids as next-generation materials for gas separation and carbon capture applications. Full article

The organic volatile compound gases (VOCs) emitted by the rubber running tracks in the park pose a threat to human health. Currently, the challenge lies in how to detect the VOC gas concentration to ensure it is below the level that is harmful to human health. This study developed a low-power acetone gas sensor based on SnO₂/Nb₂C MXene composites, designed for monitoring acetone gas in pocket park rubber tracks at room temperature. Nb₂C MXene was combined with SnO₂ nanoparticles through a hydrothermal method, and the results showed that the SnO₂/Nb₂C MXene composite sensor (SnM-2) exhibited a response value of 146.5% in detecting 1 ppm acetone gas, with a response time of 155 s and a recovery time of 295 s. This performance was significantly better than that of the pure SnO₂ sensor, with a 6-fold increase in response value. Additionally, the sensor exhibits excellent selectivity against VOCs, such as ethanol, formaldehyde, and isopropanol, with good stability (~20 days) and reversibility (~50). It can accurately recognize acetone gas concentrations and has been successfully used to simulate rubber track environments and provide accurate acetone concentration data. This study provides a feasible solution for monitoring VOCs in rubber tracks and the foundation for the development of low-power, high-performance, and 2D MXene gas sensors. Full article

Ammonia (NH₃) is one of the characteristic gases used to detect food spoilage. In this study, the 10 wt% Ag-NiFe₂O₄ nanocomposite was synthesized via the hydrothermal method. Characterization results from SEM, XRD, and XPS analyzed the microstructure, elemental composition, and crystal lattice features of the composite, confirming its successful fabrication. Under the optimal working temperature of 280 °C, the composite exhibited excellent gas-sensing properties towards NH₃. The 10 wt% Ag-NiFe₂O₄ sensor demonstrates rapid response and recovery, as well as high sensitivity, towards 30 ppm NH₃, with response and recovery times of merely 3 s and 9 s, respectively, and a response value of 4.59. The detection limit is as low as 0.1 ppm, meeting the standards for food safety detection. Additionally, the sensor exhibits good short-term repeatability and long-term stability. Additionally, density functional theory (DFT) simulations were conducted to investigate the gas-sensing advantages of the Ag-NiFe₂O₄ composite by analyzing the electron density and density of states, thereby providing theoretical guidance for experimental testing. This study facilitates the rapid detection of food spoilage and promotes the development of portable food safety detection devices. Full article

Source inversion optimization using sensor observations is a key method for rapidly and accurately identifying unknown source parameters (source strength and location) in abrupt hazardous gas leaks. Sensor number and location distribution both play important roles in source inversion; however, their combined impacts on source inversion optimization remain poorly understood. In our study, the optimization inversion method is established based on the Gaussian plume model and the generation algorithm. A research strategy combining random sampling and coefficient of variation methods was proposed to simultaneously quantify their combined impacts in the case of a single emission source. The sensor layout impact difference was analyzed under varying atmospheric conditions (unstable, neutral, and stable) and source location information (known or unknown) using the Prairie Grass experiments. The results indicated that adding sensors improved the source strength estimation accuracy more when the source location was known than when it was unknown. The impacts of sensor location distribution were strongly negatively correlated (r ≤ −0.985) with the number of sensors across scenarios. For source strength estimation, the impacts of the sensor location distribution difference decreased non-linearly with more sensors for known locations but linearly for unknown ones. The impacts of sensor number and location distribution on source strength estimation were amplified under stable atmospheric conditions compared to unstable and neutral conditions. The minimum number of randomly scattered sensors required for stable source strength inversion accuracy was 11, 12, and 17 for known locations under unstable, neutral, and stable atmospheric conditions, respectively, and 24, 9, and 21 for unknown locations. The multi-layer arc distribution outperformed rectangular, single-layer arc, and downwind-axis distributions in source strength estimation. This study enhances the understanding of factors influencing source inversion optimization and provides valuable insights for optimizing sensor layouts. Full article

Highly sensitive real-time detection of hydrogen sulfide (H₂S) is important for human health and environmental protection due to its highly toxic properties. The development of high-performance H₂S sensors remains challenging for poor selectivity, high limit detection and slow recovery from irreversible sulfidation. To solve these problems, we strategically prepared a layered structure of CuO-sensitized WO₃ flower-like hollow spheres with CuO as the sensitizing component. A 15 wt% CuO/WO₃ exhibits an ultra-high response (R_a/R_g = 571) to 10 ppm H₂S (131-times of pure WO₃), excellent selectivity (97-times higher than 100 ppm interference gas), and a low detection limit (100 ppb). Notably, its fast response (4 s) is accompanied by full recovery within 236 s. After 30 days of continuous testing, the response of 15 wt% CuO/WO₃ decreased slightly but maintained the initial response of 90.5%. The improved performance is attributed to (1) the p-n heterojunction formed between CuO and WO₃ optimizes the energy band structure and enriches the chemisorption sites for H₂S; (2) the reaction of H₂S with CuO generates highly conductive CuS, which significantly reduces the interfacial resistance; and (3) the hierarchical flowery hollow microsphere structure, heterojunction, and oxygen vacancy synergistically promote the desorption. This work provides a high-performance H₂S gas sensor that balances response, selectivity, and response/recovery kinetics. Full article

Hydrogen sulfide (H₂S) is a highly toxic and corrosive gas generated in numerous industrial and environmental processes; rapid, sensitive detection at low ppm levels is therefore crucial for ensuring occupational safety and protecting public health. This work explores the effect of grafting various loadings of pendant aniline tetramer pendants (PEDA) onto electroactive poly(amic acid) (EPAA) films and evaluates their performance as H₂S gas sensors. Comprehensive characterization including ion trap mass spectrometry (Ion trap MS), Fourier-transform infrared spectroscopy (FTIR), cyclic voltammetry (CV), and four-probe conductivity measurements, confirmed successful PEDA incorporation and revealed enhanced electrical conductivity with increasing PEDA content. Gas sensing tests revealed that EPAA3 (3 wt% PEDA) achieved the best overall performance toward 10 ppm H₂S, producing a 591% response with a rapid 108 s response time. Selectivity studies showed that the response of EPAA3 to H₂S exceeded those for SO₂, NO₂, NH₃, and CO by factors of five to twelve, underscoring its excellent discrimination against common interferents. Repeatability tests over five successive cycles gave a relative standard deviation of just 7.4% for EPAA3, and long-term stability measurements over 16 days in ambient air demonstrated that EPAA3 retained over 80%. These findings establish that PEDA-grafted PAA films combine the processability of poly(amic acid) with the sharp, reversible redox behavior of pendant aniline tetramers, delivering reproducible, selective, and stable H₂S sensing. EPAA3, in particular, represents a balanced composition that maximizes sensitivity and durability, offering a promising platform for practical environmental monitoring and industrial safety applications. Full article