Gas Concentration Research Articles

How does air quality reflect the land cover changes: remote sensing approach using Sentinel data.

Significant environmental challenges, such as urban and industrial expansion, alongside vegetation preservation, directly influence the concentrations of critical air pollutants and greenhouse gases in cities and their surroundings. The urban development and expansion process is aptly captured by classifying land use and land cover (LULC). We aimed to analyze LULC changes in an Andean area, Ecuador, and to reveal the relations of LULC classes with three air pollutants ozone ( ), nitrogen dioxide ( ), and sulfur dioxide ( ), using remote sensing datasets (Sentinel-5P - Sentinel 1 - Sentinel-2) across different periods. Results showed that is not a reliable indicator for assessing its behavior based on LULC classes, as it was difficult to distinguish between different land cover types using this pollutant. For , the analysis showed a moderate distinction among LULC classes, suggesting some variability in its distribution across different land cover classes. On the other hand, analysis shows that all land cover classes are statistically distinguishable, demonstrating that urban, shrubland, green areas, and forest classes influenced ozone distribution. These findings emphasize the importance of accurate land cover classification in understanding air pollutants' spatial distribution and dynamics. This analysis is crucial for understanding the impacts of land use and land cover changes on urban health and well-being and the effects of rapid urban expansion.

A Cone-Like TSV Structured ZnO NO2 Gas Sensor that is Produced Using Room-Temperature Laser Drilling and Radio-Frequency Sputtering

Abstract A typical through-silicon via (TSV) has vertical and high aspect ratio holes, making special equipment required to deposit the film on the vertical hole walls. This study used room-temperature laser drilling to fabricate a cone-like TSV structure so that no special process equipment was required. Radio-frequency sputtering was used to deposit SiNx, ITO, and ZnO films on the cone-like TSV structure to form a ZnO NO2 gas sensor. Scanning electron microscopy and focused ion beam results show that the ZnO film connects the front and back sides of the substrate, enabling sensing on both sides. If the concentration of NO2 gas is increased, the sensor response increases and the average sensor response is 34,7%, with an inaccuracy of <± 1% for five 5 consecutive measurements using a NO2 concentration of 3ppm. Reactions with NH3, CO, CO2, and SO2 gases are almost insignificant, giving the cone-like TSV structure ZnO gas sensor good selectivity, stability, and reproducibility for NO2 gas.

Thermodynamic integration in combined fuel and power plants producing low carbon hydrogen and power with CCUS

Demand for low-carbon sources of hydrogen and power is expected to rise dramatically in the coming years. Individually, steam methane reformers (SMRs) and combined cycle gas power plants (CCGTs), when combined with carbon capture utilisation and storage (CCUS), can produce large quantities of on-demand decarbonised hydrogen and power respectively. The ongoing trend towards the development of CCUS clusters means that both processes may operate in close proximity, taking advantage of a common infrastructure for natural gas supply, electricity grid connection and the CO2 transport and storage network. This work improves on a previously described novel integration process, which utilizes flue gas sequential combustion to incorporate the SMR process into the CCGT cycle in a single “combined fuel and power” (CFP) plant, by increasing the level of thermodynamic integration through the merger of the steam cycles and a redesign of the heat recovery system. This increases the 2nd law thermal efficiency by 2.6% points over un-integrated processes and 1.9% points the previous integration design. Using a conventional 35% wt. monoethanolamine (MEA) CO2 capture process designed to achieve two distinct and previously unexplored CO2 capture fractions; 95% gross and, 100% fossil (CO2 generated is equal to the quantity of CO2 captured). The CFP configuration reduces the overall quantity of flue gas to be processed by 36%–37% and increases the average CO2 concentration of the flue gas to be treated from 9.9% to 14.4% (wet). This decreases the absorber packing volume requirements by 41%–56% and decreases the specific reboiler duty by 5.5% from 3.46–3.67 GJ/tCO2 to 3.27–3.46 GJ/tCO2, further increasing the 2nd law thermal efficiency gains to 3.8%–4.4% points over the un-integrated case. A first of a kind techno economic analysis concludes that the improvements present in a CO2 abated CFP plant results in a 15.1%–17.3% and 7.6%–8.0% decrease in capital and operational expenditure respectively for the CO2 capture cases. This translates to an increase in the internal rate of return over the base hurdle rate of 7.5%–7.8%, highlighting the potential for substantial cost reductions presented by the CFP configuration.

Carbon sequestration by ecosystems of cold territories of Transbaikalia

In the Baikal region, the continuous cryolithozone occupies ≈15, the transitional intermittent zone with Talikov islands – 30, the transitional island zone – 45, taliki with a continuous area – 10%. Attention is drawn to the dominance of the transition band, which is characterized by unstable thermodynamic equilibrium. High-temperature permafrost is easily degraded by technoconversion of external heat exchange conditions: removal of ground covers (organogenic layer and snow cover), deforestation, plowing, fires, etc. These circumstances increase the natural hazards and risks in the region. In this regard, the territory of Transbaikalia is of great interest, being in the permafrost zone and near its southern border, on the one hand, and with increased warming rates in recent decades, on the other. The continentality and severity of the climate in Buryatia are much more pronounced than in neighboring single-latitude regions of Russia. The southern boundary of the cryolithozone stretches almost throughout the entire territory of the republic, within which a whole range of landscapes is distinguished – from automorphic forest ecosystems to widespread, due to the high proportion of lakes and swamps, hydromorphic landscapes formed under the active influence of permafrost, as well as dry-steppe. The implementation of the Kyoto Protocol on Stabilization of Greenhouse Gas (GHG) Concentrations in the Atmosphere requires a quantitative assessment of spatiotemporal changes in terrestrial carbon sinks. Identifying areas with high potential and strategies for managing sequestration of atmospheric carbon dioxide by ecosystems is an important task and there is great uncertainty about the actual estimates of carbon reservoirs and how they may be affected by climate change. In the current conditions, we consider the study of the patterns of functioning of the soil and plant carbon reservoir in Transbaikalia to be timely and relevant.

Thermodynamics of Electrochemical Marine Inorganic Carbon Removal.

In recent years, marine carbon removal technologies have gained attention as a means of reducing greenhouse gas concentrations. One family of these technologies is electrochemical systems, which employ Faradaic reactions to drive alkalinity-swings and enable dissolved inorganic carbon (DIC) removal as gaseous CO2 or as solid minerals. In this work, we develop a thermodynamic framework to estimate upper bounds on performance for Faradaic DIC removal systems. To assess the fundamental mass balances of these systems, we first define unit operations in the DIC/total alkalinity (TA) space. By coupling a seawater speciation model to an electrochemical framework, we provide a generalized comparison of gas evolution and mineralization DIC removal routes, focusing on asymmetric charge/discharge systems. We then show how this framework can be extended to other processes, such as those employing dilution schemes. Finally, we provide a minimum energetic assessment of mCDR pathways relative to direct air capture. Overall, this thermodynamic framework aims to guide system and process design and to drive material discovery and engineering for future electrochemical marine DIC removal systems.

AERA-MIP: emission pathways, remaining budgets, and carbon cycle dynamics compatible with 1.5 and 2 °C global warming stabilization

Abstract. While international climate policies now focus on limiting global warming to well below 2 °C or pursuing a 1.5 °C level of global warming, the climate modelling community has not provided an experimental design in which all Earth system models (ESMs) converge and stabilize at the same prescribed global warming levels. This gap hampers accurate estimations based on comprehensive ESMs of the carbon emission pathways and budgets needed to meet such agreed warming levels and of the associated climate impacts under temperature stabilization. Here, we apply the Adaptive Emission Reduction Approach (AERA) with ESMs to provide such simulations in which all models converge at 1.5 and 2.0 °C warming levels by adjusting their emissions over time. These emission-driven simulations provide a wide range of emission pathways and resulting atmospheric CO2 projections for a given warming level, uncovering uncertainty ranges that were previously missing in the traditional Coupled Model Intercomparison Project (CMIP) scenarios with prescribed greenhouse gas concentration pathways. Meeting the 1.5 °C warming level requires a 40 % (full model range: 7 % to 76 %) reduction in multi-model mean CO2-forcing-equivalent (CO2-fe) emissions from 2025 to 2030, a 98 % (57 % to 127 %) reduction from 2025 to 2050, and a stabilization at 1.0 (−1.7 to 2.9) PgC yr−1 from 2100 onward after the 1.5 °C global warming level is reached. Meeting the 2.0 °C warming level requires a 47 % (8 % to 92 %) reduction in multi-model mean CO2-fe emissions until 2050 and a stabilization at 1.7 (−1.5 to 2.7) PgC yr−1 from 2100 onward. The on-average positive emissions under stabilized global temperatures are the result of a decreasing transient climate response to cumulative CO2-fe emissions over time under stabilized global warming. This evolution is consistent with a slightly negative zero emissions commitment – initially assumed to be zero – and leads to an increase in the post-2025 CO2-fe emission budget by a factor of 2.2 (−0.8 to 6.9) by 2150 for the 1.5 °C warming level and a factor of 1.4 (0.9 to 2.4) for the 2.0 °C warming level compared to its first estimate in 2025. The median CO2-only carbon budget by 2150, relative to 2020, is 800 GtCO2 for the 1.5 °C warming level and 2250 GtCO2 for the 2.0 °C warming level. These median values exceed the median IPCC AR6 estimates by 60 % for the 1.5 °C warming level and 67 % for 2.0 °C. Some of the differences may be explained by the choice of the mitigation scenario for non-CO2 radiative agents. Our simulations highlight shifts in carbon uptake dynamics under stabilized temperature, such as a cessation of the carbon sinks in the North Atlantic and in tropical forests. On the other hand, the Southern Ocean remains a carbon sink centuries after temperatures stabilize. Overall, this new type of warming-level-based emission-driven simulation offers a more coherent assessment across climate models and opens up a wide range of possibilities for studying both the carbon cycle and climate impacts, such as extreme events, under climate stabilization.

Revisiting the “East African Paradox”: CMIP6 Models Also Struggle to Reproduce Strong Observed Long Rain Drying Trends

Abstract Societies in much of the Horn of Africa are affected by variability in two distinct rainy seasons: the March–May (MAM) “long” rains and the October–December (OND) “short” rains. A recent five-season, La Niña–forced drought has renewed concerns about possible anthropogenic drying trends in the long rains, which had partially recovered after a multidecadal drying trend in the 1980s through the 2000s. Despite observed drying, previous generations of global climate models (GCMs) have consistently projected long-term wetting due to increased greenhouse gas concentrations, an East African “paradox” which complicates the interpretation of East African rainfall projections. We investigate the paradox in new phase 6 of the Coupled Model Intercomparison Project (CMIP6) and seasonal forecast models, leveraging an improved observational record and large ensembles to better differentiate internal and forced trends. We find observed drying trends are at the limits of the GCM spread during the peak paradox period, though the recent recovery is comfortably within the model spread. We find that the apparent paradox is largely removed by prescribing sea surface temperatures (SSTs) and is likely caused by the GCM difficulties in simulating observed tropical Pacific SST trends in recent decades. In line with arguments that these SST trends are at least partially forced anthropogenically, we recommend users of future rainfall projections in East Africa consider the possibility of long-term MAM drying despite GCM wetting and call for future model simulations that better sample the expected spread of SSTs. Significance Statement Societies in the Horn of Africa depend on the March–May “long” rains and the September–December “short” rains to support agricultural and pastoral practices on rain-fed lands. Recent major droughts have raised worries about possible anthropogenically forced drying trends in the long rains through global climate models (GCMs) project wetting. This East African “paradox” complicates long-term climate adaptation planning. We find the paradox continues in the newest generation of GCMs and seasonal forecast models; though a recent recovery in rainfall is well-captured, the strongest observed drying trends are rare in simulations. The paradox likely arises from known GCM biases in the Pacific Ocean interacting with natural variability. We recommend that researchers and policymakers consider possible long-term drying despite GCM projections of wetting.

Assessing the Spurious Impacts of Ice-Constraining Methods on the Climate Response to Sea Ice Loss Using an Idealized Aquaplanet GCM

Abstract Coupled climate model simulations designed to isolate the effects of Arctic sea ice loss often apply artificial heating, either directly to the ice or through modification of the surface albedo, to constrain sea ice in the absence of other forcings. Recent work has shown that this approach may lead to an overestimation of the climate response to sea ice loss. In this study, we assess the spurious impacts of ice-constraining methods on the climate of an idealized aquaplanet general circulation model (GCM) with thermodynamic sea ice. The true effect of sea ice loss in this model is isolated by inducing ice loss through reduction of the freezing point of water, which does not require additional energy input. We compare the results of freezing point modification experiments with experiments where sea ice loss is induced using traditional ice-constraining methods and confirm the result of previous work that traditional methods induce spurious additional warming. Furthermore, additional warming leads to an overestimation of the circulation response to sea ice loss, which involves a weakening of the zonal wind and storm-track activity in midlatitudes. Our results suggest that coupled model simulations with constrained sea ice should be treated with caution, especially in boreal summer, where the true effect of sea ice loss is weakest, but we find the largest spurious response. Given that our results may be sensitive to the simplicity of the model we use, we suggest that devising methods to quantify the spurious effects of ice-constraining methods in more sophisticated models should be an urgent priority for future work. Significance Statement The potential effects of Arctic sea ice loss on midlatitude weather have been investigated using climate models where sea ice loss is artificially induced, without increasing greenhouse gas concentrations. Recently, this approach has been challenged because the artificial heating used to melt sea ice may also have direct effects on climate, which are not caused by sea ice loss. We run simulations with a simplified climate model that allows us to separate the “spurious” direct effects of the artificial heating from the “true” effect of sea ice loss. In our simulations, the responses of temperature and atmospheric circulation are amplified by spurious effects. Consequently, we argue that previous studies using more complex climate models may overestimate the effect of sea ice loss on climate.

Combined Effects of Drying–Rewetting and Ammonium Addition on Methanotrophs in Agricultural Soil: A Microcosm Study

Oxidation of methane by soil microorganisms is an important mechanism controlling the content of this potent greenhouse gas in the atmosphere. Agricultural soils operate under stressful conditions, and ammonium (N-fertilization) and drying (global warming) may have a significant impact on methane oxidation. In order to investigate how soil methanotrophs respond to drying–rewetting (DW), ammonium addition (100 mg/g) (A), and their combined action (MS), agricultural soil microcosms were incubated over the three months and methane oxidation was measured before and after perturbations, while community composition was monitoring using 16S rRNA gene sequencing. A significant decline in the methane-oxidation activity after perturbations was found, with subsequent restoration, and the combined treatment was more effective than the sum of individual treatments, indicating a synergistic effect. After rewetting, the structure of the bacterial community returned to pre-dry-down levels, but the application of ammonia and combined action lead to irreversible changes in the structure of soil methanotrophic communities. Methanotroph Methylomicrobium were significantly reduced under disturbances, while there was a significant increase in the representation of Methylobacter accompanied by the facultative methylotroph Methylovorus. We concluded that methanotrophic communities in agricultural soil demonstrated flexibility, and even when the abundance of dominant populations drops, ecosystem functions can recover.

Multiscale Qualitative–Quantitative Characterization of the Pore Structure in Coal-Bearing Reservoirs of the Yan’an Formation in the Longdong Area, Ordos Basin

Accurate characterization of coal reservoir micro- and nanopores is crucial in evaluating coalbed methane storage and gas production capacity. In this work, 12 coal-bearing rock samples from the Jurassic Yan’an Formation, Longdong area, Ordos Basin were taken as research objects, and micro- and nanopore structures were characterized via scanning electron microscopy, high-pressure mercury pressure, low-temperature N2 adsorption and low-pressure CO2 adsorption experiments. The main factors controlling coal pore structure development and the influence of pore development on the gas content were studied by combining the reflectivity of specular samples from the research area, the pore microscopic composition and the pore gas content determined through industrial analyses and isothermal absorption experiments. The results show that the coal strata of the Yan’an coal mine are a very important gas source, and that the coal strata of the Yan’an Formation in the study area exhibit remarkable organic and clay mineral pore development accompanied by clear microfractures and clay mineral interlayer joints, which together optimize the coal gas storage conditions and form efficient microseepage pathways for gas. Coalstone, carbonaceous mudstone and mudstone show differential distributions in pore volume and specific surface area. The general trend is that coal rock is the best, carbonaceous mudstone is the second best, and mudstone is the weakest. The coal samples’ microporous properties are positively correlated with the coal sample composition for the specular group, whereas there is no clear correlation for the inert group. An increase in the moisture content of the air-dried matrix promotes adsorption pore development, leading to increases in the microporous volume and specific surface area. CH4 adsorption in coal rock increases with increasing pressure, and the average maximum adsorption is approximately 8.13 m3/t. The limit of the amount of methane adsorbed by the coal samples, VL, is positively correlated with the pore volume and specific surface area, indicating that the larger the pore volume is, the greater the amount of gas that can be adsorbed by the coal samples, and the larger the specific surface area is, the greater the amount of methane that can be adsorbed by the coal samples. The PL value, pore volume and specific surface area are not correlated, indicating that there is no direct mathematical relationship between them.

Study on Fire Characteristics of Flame-Retardant Polycarbonate Under Low Pressure

This work presents experimental and numerical research on the pyrolysis and combustion characteristics of flame-retardant polycarbonate under low ambient pressure. A novel experimental low-pressure combustion platform was constructed to determine the heat release rate, a key combustion parameter of polycarbonate. The ignition process of polycarbonate under external radiation was analyzed, and an ignition time prediction model was developed. In addition, theoretical calculations of the main gas components and concentrations during the pyrolysis stage of polycarbonate and estimations of the calorific values of the combustible gas components produced during pyrolysis were carried out, providing a new explanation for the phenomenon of advancing ignition time in low-pressure environments.

Proposal of a new method for interpreting the concentrations of gases dissolved in mineral transformer oil

Proposal of a new method for interpreting the concentrations of gases dissolved in mineral transformer oil

Study on the influence of gas transmission characteristics of positive pressure beam tube system under graded pressurization

The positive pressure beam tube system addresses issues related to gas composition distortion, concentration variations, and long transmission delays observed in traditional negative pressure systems. It has increasingly become the primary system for early monitoring and warning of coal spontaneous combustion in goaf areas. Nevertheless, there remains a deficiency in comprehensive research concerning critical aspects like gas transmission characteristics and transmission lag time in the positive pressure beam tube system. This study aims to construct an experimental platform for the positive pressure beam tube monitoring system and systematically investigate how the choice of pressurization device, pipe length, pipe diameter, and driving pressure in the transmission pipeline affect gas transmission characteristics. The findings indicate that the most effective pressurization occurs under conditions of two-stage high positive pressure transport, with a driving gas pressure of 0.65 MPa. The optimal diameter for positive pressure gas transmission is 7 mm. Long-distance negative pressure pipelines result in decreased transmission efficiency, necessitating increased output pressure with the lengthening of positive pressure pipelines to maintain efficiency.

Multi-model effective radiative forcing of the 2020 sulfur cap for shipping

Abstract. New regulations of sulfur emissions from shipping were introduced in 2020, reducing emissions of SO2 from international shipping by ∼ 80 %. As SO2 is an aerosol precursor, this drop in emissions over the ocean will weaken the total aerosol effective radiative forcing (ERF) that has historically masked an uncertain fraction of the warming due to the increased concentration of greenhouse gases in the atmosphere. Here, we use four global climate models and a chemical transport model to calculate the ERF resulting from an 80 % reduction in SO2 emissions from international shipping relative to 2019 emission estimates. The individual model means range from 0.06 to 0.09 W m−2, corresponding to the ERF resulting from the increase in CO2 concentration over the last 2 to 3 years. The full uncertainty in the ERF due to the new regulation is not quantified but will very likely be high considering the contribution of uncertainties in shipping SO2 emissions, the sulfur cycle, the modelling of cloud adjustments and the impact of interannual variability on the method for calculating radiative forcing.

Research and design of multiple gas mixing system in modified atmosphere packaging

Despite the abundant production of fruits and vegetables in Xinjiang, there is an increasing trend in waste rates. Gas-controlled packaging techniques are employed post-harvest to enhance freshness and extend shelf life. However, the multi-gas mixing system at the core of this equipment often encounters challenges such as insufficient stability, limited precision, high costs, and inadequate intelligence. In this context, we have developed and designed a multi-gas mixing system for gas-conditioned packaging. The system integrates Internet of Things technology, uses a programmable controller as the core, proposes a ternary gas distribution model based on the ideal gas equation and Dalton’s law of partial pressures, and utilizes RS-485 bus, TCP/IP protocol, among others. This ensures communication between the equipment and data transmission with the cloud server while enabling remote control of the gas mixing and blending process via a mobile phone terminal. The system runs stably through testing, with the average relative deviations of CO2 and O2 gas concentrations being 0.86% and 0.72%, respectively. This fulfills the technical prerequisites for achieving a gas concentration precision of less than 1%, addressing challenges related to inadequate precision in gas blending, unstable performance, and limited visual representation. Moreover, it significantly reduces equipment costs and operational complexities while serving as a valuable reference for advancing multivariate gas mixing and blending technology in Xinjiang’s fruit and vegetable gas-conditioned packaging.

Ammonia and ethanol detection via an electronic nose utilizing a bionic chamber and a sparrow search algorithm-optimized backpropagation neural network.

Ammonia is widely acknowledged to be a stressor and one of the most detrimental gases in animal enclosures. In livestock- and poultry-breeding facilities, a precise, rapid, and affordable method for detecting ammonia concentrations is essential. We design and develop an electronic nose system containing a bionic chamber that imitates the nasal-cavity structure of humans and canines. The sensors are positioned based on fluid simulation results. Response data for ammonia and ethanol gases and the response/ recovery times of an ammonia sensor under three concentrations are collected using the electronic nose system. Response data are classified and regressed using a sparrow search algorithm (SSA)-optimized backpropagation neural network (BPNN). The results show that the sensor has a relative mean deviation of 1.45%. The ammonia sensor's output voltage is 1.3-2.05 V when the ammonia concentration ranges from 15 to 300 ppm. The ethanol gas sensor's output voltage is 1.89-3.15 V when the ethanol gas concentration ranges from 8 to 200 ppm. The average response time of the ammonia sensor in the chamber is 13 s slower than that of the sensor directly exposed to the gas being measured, while the average recovery time is 19 s faster. In tests comparing the performance of the SSA-BPNN, support vector machine (SVM), and random forest (RF) models, the SSA-BPNN achieves a 99.1% classification accuracy, better than the SVM and RF models. It also outperforms the other models at regression prediction, with smaller absolute, mean absolute, and root mean square errors. Its coefficient of determination (R2) is greater than 0.99, surpassing those of the SVM and RF models. The theoretical and experimental results both indicate that the proposed electronic nose system containing a bionic chamber, when used with the SSA-BPNN, offers a promising approach for detecting ammonia in livestock- and poultry-breeding facilities.

Methane Gas Sensor using Graphene Nanoflakes at Room Operating Temperature

Methane gas is commonly produced and used in various industries, including agriculture, coal mining, manure management, landfills, natural gas, and petroleum systems. This gas is colorless and odorless. High concentrations of methane gas can have detrimental effects on human health, such as causing headaches, visual issues, and memory loss. Moreover, prolonged exposure to higher concentrations may lead to respiratory and heart rate fluctuations, balance problems, and even unconsciousness. In order to address these concerns, a thick film gas sensor based on graphene nanoflakes is proposed in this work to detect different levels of methane gas at room operating temperature. The gas sensor was fabricated using screen-printing technology on a Kapton film. Graphene nanoflakes were mixed with a binder to create the sensing film. Scanning electron microscopy (SEM) was used to characterize the morphology and X-ray diffraction (XRD) for structural components of the sensing film. Two graphene gas sensors (PF-1 and PF-2) were fabricated using screen-printing to compare their performance to methane at room operating temperature with gas concentrations ranging from 300 to 1000 ppm. The results showed that both gas sensors responded robustly to changing concentrations of methane gas at room operating temperature within 20 s. PF-2 outperforms PF-1, with the result of sensitivity being approximately 0.0000353, 0.0000288, and 0.0000262 for the first, second, and third exposures to methane gas. Both gas sensors also exhibited excellent repeatability characteristics with similar patterns each time exposed to the methane.

The suppression and CO elimination performance of Co3O4 dust cloud for methane-air mixture explosion

This paper experimentally studied the effect of Co3O4 dust clouds on the methane-air mixture explosion characteristics and post-explosion CO concentration, aiming to propose a novel method for simultaneously suppressing explosion and eliminating CO product. The Co3O4 catalyst was synthesized utilizing the co-precipitation method. We varied the methane concentration and Co3O4 dust cloud concentration to investigate their effects on the flame propagation behavior, maximum explosion overpressure (Pm), flame combustion time (tc), and the gaseous product concentration. The hazard of the gaseous product was evaluated by the effective escape time (te) based on the Fraction Effective Dose (FED) mathematical model. The results demonstrated that the Co3O4 dust cloud could significantly reduce the explosion severity and CO concentration. Furthermore, the higher the concentration of Co3O4 dust clouds, the more significant the explosion suppression and CO elimination performance, which was as a result of the significant increase in the contact area and collision probability between the Co3O4 particles and the reaction components increased. Compared to traditional inhibitors that only reduce the severity of an explosion, Co₃O₄ could not only significantly reduce the explosion severity, but also quickly eliminate post-detonation CO. The method proposed in this paper could effectively reduce the hazard of methane-air mixture explosion, which was of great practical significance for ensuring the safety of personnel involved in the risk.

Design and Development of a Smart Trash Bin to Minimize Odor from Household Waste Based on the Internet of Things

The problem that occurs is that household waste continues to increase along with the development of population and the number of increasingly dense settlements. The existence of this household waste is of concern to the community and the government because it can cause various negative impacts. Based on the results of observations of the existing trash cans, the accumulation of household waste is the source of this unpleasant odor. Smell is connoted as something that tends to disturb comfort, and gives the impression of being unclean and the like, such as fishy, rotten, urine, rancid, and so on. The smell of burning garbage is also dangerous because it contains H2 which reduces the amount of oxygen in the air. This study aims to prevent the occurrence of unpleasant odors from garbage. The tool will be designed using the NodeMCU microcontroller with website-based monitoring and Whatsapp notifications automatically when the trash can is full and automatic deodorizing powder spraying according to the concentration of gas released by the stench. This study uses the Experimental and Comparative Testing method in designing an IoT-based Smart Trash Bin tool and conducting tests on the built system and comparing the test results with the expected system. The results of this study indicate that the Smart Trash Bin tool can work and function as expected, namely being able to minimize the unpleasant odor emitted by the trash can and being able to monitor the sprinkling of deodorizing powder, the status of the height of the trash can and can provide notifications both automatically and manual to officers through the website.

The Prediction of Coalbed Methane Layer in Multiple Coal Seam Groups Based on an Optimized XGBoost Model

The prediction of the optimal coalbed methane (CBM) layer plays a significant role in the efficient development of CBM in multiple coal seam groups. In this article, the XGBoost model optimized by the tree-structured Parzen estimator (TPE) algorithm was established to automatically predict the optimal CBM layer in complex multi-coal seams of the Dahebian block in Guizhou Province, China. The research results indicate that the TPE XGBoost model has higher evaluation metrics than traditional machine learning models, with higher accuracy and generalization ability. The optimal coalbed methane layer predicted by the model for the Dacong 1–3 well is the 11th coal seam. In addition, the interpretation results of the model indicate that sonic (AC) and caliper logging (CAL) are relatively important in determining the optimal CBM layer. The favorable layers for coalbed methane development are distributed in coal seams with developed fractures and high gas content. The TPE-XGBoost model can help us objectively analyze the significance of different types of logging, quickly predict the optimal layer in complex multiple coal seam groups, and greatly reduce costs and subjective impact. It provides a new approach to predict the best CBM layer in multiple coal seam groups in the Guizhou Province in the southwest of China.