Gas Concentration Research Articles

Chronic and Periodic Effects of Smoke from Crop Residue Combustion on Soil Enzymatic Activity

Wildfires lead to the emission of large volumes of toxic smoke, which is transported hundreds of kilometres away from the fires and can have a negative impact on soil, biota and humans. A series of modelling experiments on pyrogenic fumigation of soil were carried out to assess the effects of gaseous products from wildfires on soil biochemical parameters. The effects of chronic exposure to gaseous substances and periodic, repetitive effects of smoke exposure on soil were determined. The results were compared with a single intensive smoke exposure. It was found that pyrogenic impact significantly affected the change of enzymatic activity of ordinary chernozem. The degree of influence depended on the duration and periodicity of smoke exposure. In all experiments enzymes of oxidoreductase class (catalase, peroxidase, polyphenol oxidase) were more sensitive to fumigation than invertase from hydrolase class. The reason of suppression of enzymatic activity of soils is high concentrations of toxic gases. The following concentrations exceeded the maximum permissible concentrations for atmospheric air: CO 714 times, phenol (hydroxybenzene) 441 times, acetaldehyde 24100 times, formaldehyde 190 times. Accumulation of polycyclic aromatic hydrocarbons (PAHs) in soil after fumigation was revealed, the total content of PAHs was 377 ng/g. The highest values were recorded for naphthalene, where the concentration was 4.4 times higher than the maximum permissible and phenanthrene 2.8 times higher than the maximum permissible. It was found that 60-minute intensive smoke affects the soil to a lesser extent than chronic and periodic. Indicators of enzymatic activity of chernozem after such fumigation decreased by 15-33% depending on the enzyme, in chronic and periodic by 41-84 and 31-78%, respectively. The obtained data indicate a significant effect of smoke on enzymatic activity of soils under chronic and periodic exposure to gaseous products of combustion.

Using the Plasma Jet Method to Create Zinc Nanoparticles and Study Their Structural and Optical Properties as an NH3 Gas Sensor

In this work, zinc nanoparticles were prepared using the low-temperature plasma method at different times 3 min, 5 min, 7 min, 9 min, where the initial reactions of zinc lead to the formation of nanoparticles. The metal interacts with the ionized plasma under different conditions and may turn into an oxide such as exposing the sample to air and raising the temperature of the solution a few degrees as a result of high voltage and within a certain range. The atmospheric pressure plasma system acts as the cathode, while the zinc metal strip acts as the anode. A series of techniques were used, including the use of X-ray diffraction (XRD), ultraviolet-visible spectroscopy and scanning electron microscopy (FESEM). The X-ray diffraction results showed that the samples have polycrystalline structures with hexagonal and cubic structures with a time difference, and the X-ray diffraction results showed the conversion of zinc particles into zinc oxides. FESEM images reveal particle size and shape. The ZnO nanoparticles prepared by the mentioned method seem to form different nanoshapes such as starfish and mushroom nanoparticles. The UV-visible results showed that the samples had an energy gap of about 3.4 eV at a time of 3 min, and this value decreases with increasing reaction time. The appearance of zinc oxides increases gradually with the passage of time. These results provide credibility for the fabrication of ZnO nanostructures for use in future gas sensing applications, despite the inhomogeneity of particle size among ZnO particles, the sensor was also fabricated to detect nitrogen gas (NH3) with different concentrations (17.25 ppm, 46.38 ppm, 78.58 ppm). at room temperature. The ZnO sample showed the highest sensitivity (88.1%) at 7 min. The sensitivity showed different results and increased with reaction time and gas concentration. However, response and recovery time are moderate and decrease as reaction time increases.

Emissions of Polychlorinated Dibenzo-p-Dioxins/Dibenzofurans during Coffee Roasting: Exploring the Influence of Roasting Methods and Formulations

Polychlorinated dibenzo-p-dioxin/dibenzofuran (PCDD/F) emissions during the roasting of green Arabica coffee and coffee formulations containing alcohol, sugar, and honey were investigated in this study. Fast and slow roasting methods, which took 5.62 and 9.65 min to achieve a light roast, respectively, were used to evaluate the emissions. The concentrations in the flue gas during the fast roasting of green coffee (0.0296 ng Nm−3 and 0.00364 ng WHO-TEQ Nm−3) were 13.9% and 70.5% higher than during slow roasting, respectively. However, this was only the trend for some formulations, and no significant differences in concentrations were found between the methods at p = 0.05. Thus, the slow roasting method might not necessarily reduce formation when additives are included. The emission factors were 2.86 ng kg−1 and 0.352 ng WHO-TEQ kg−1, and 4.17 ng kg−1 and 0.176 ng WHO-TEQ kg−1 for the fast and slow roasting of green coffee, respectively. Further investigations are warranted to understand the formation mechanism, assess potential health risks, and explore mitigation strategies. These findings have implications for both coffee processing industries and regulatory bodies, as understanding the impact of roasting methods and additives could inform the development of cleaner production practices and targeted emission reduction policies.

The Effect of CO on the Exothermic Characteristics of Low-Temperature Oxidation in Coal

ABSTRACT In recent years, abnormally high concentrations of CO gas have often been detected in goaf areas of coal mines in China, which have posed a serious threat to safe production in coal mines and the life and safety of underground personnel. The effect of CO on the exothermic characteristics of low-temperature oxidation in coal was studied by analyzing the exothermic characteristics, heat release, oxidation stages, and activation energy of coal at different CO concentrations using a C600 microcalorimeter. The experimental results indicated that CO promoted the coal oxidation at low temperature, but inhibited it after reaching 144°C. When the CO concentration is 30%, the exothermic characteristics of coal in low-temperature oxidation adsorption stage were significantly affected, with the heat flow value decreased by 27.0% and the initial exothermic temperature point moved forward by 3.9 K. In the later stage of the oxidation reaction, the heat release of coal was linearly negatively correlated with CO concentration. The higher the concentration, the lower the heat release. These findings contribute to understanding the combustion mechanism of coal in high-concentration CO atmosphere and provide valuable insights for designing and optimizing coal utilization technologies.

Investigating the Relationship between Urbanization and Air Pollution Using Google Earth Engine Platform: A Case Study of Istanbul

Rapid population growth in megacities such as Istanbul has led to various effects, such as industrialization, urbanization, loss of green areas, increasing vehicle traffic, and higher consumption of fossil fuels. These reasons, along with many other environmental factors, contribute to the rise of air pollution in urban life. This study aimed to examine the relationship between urbanization and air pollution in Istanbul. For this purpose, land cover maps covering Istanbul province were produced using Landsat-5 (TM), Landsat-8 (OLI), and Sentinel-2 (MSI) images for the years 1996 to 2021 at three-year intervals on the Google Earth Engine platform. Land cover for classification purposes was divided into five different classes: forest, water surface, urban area, and bare land, and classified using a random forest machine learning algorithm. To examine the impact of this urban area growth on air pollution, in the second step of the study, the column number density values of Sentinel 5P (TROPOMI) data for SO2, NO2, CO, and O3 gases for 2019, 2020, and 2021 were analyzed. The averages of the data from 39 air pollution monitoring stations across Istanbul were also examined. According to this classification, the urban area expanded from 491 km2 in 1996 to 1222 km2 by 2021. Considering the total surface area of Istanbul province, the urban area, which was 9% in 1996, reached 23% by 2021. The TROPOMI values were calculated as follows: the average column number density values for SO2, NO2, CO, and O3 were 0.0003538 mol/m², 0.0339514 mol/m², 0.0000984 mol/m², and 0.1453515 mol/m², respectively. Similarly, the gas concentrations of SO2, NO2, CO, and O3 measured from the ground stations were calculated as 6.603 µ/m3, 786,815 µ/m3, 43.763 µ/m3 and 45.773 µ/m3, respectively. Correlations between urbanization and TROPOMI values revealed a positive correlation of 0.39, 0.02, and 0.80 for SO2, NO2, and CO gases, while a negative correlation of 0.25 was found for O3 gas. The study also examined correlations between TROPOMI and ground station measurements, resulting in positive correlations of 0.55, 0.66, and 0.16 for SO2, NO2, and CO gases, respectively, while a negative correlation of 0.05 was found for O3 gas. Based on these findings, among the air pollutants studied both through TROPOMI and ground station data, the highest correlation was observed for CO gas.

Features of Temporal Variability of the Concentrations of Gaseous Trace Pollutants in the Air of the Urban and Rural Areas in the Southern Baikal Region (East Siberia, Russia)

This article presents the results of the automatic monitoring of the concentrations of gaseous impurities of sulfur and nitrogen oxides in the ground-level atmosphere of the urban and rural areas in the Southern Baikal region (East Siberia, Russia). The study was conducted from 2020 to 2023 at the urban Irkutsk station and the rural Listvyanka station located at a distance of 70 km from each other. We calculated the main statistical characteristics of the variations in the concentrations of nitrogen oxides and sulfur dioxide in the ground-level atmosphere and determined a nature of variability in their concentrations on various time scales: annual, weekly, and daily. Annual variabilities of gaseous pollutants in the ground-level atmosphere above the Irkutsk city and the Listvyanka settlement were similar and showed the highest values in winter and the lowest in summer. The daily and weekly dynamics of the nitrogen oxide concentrations in the urban area clearly depended on the increase in the road traffic during rush hours (morning and evening). In the rural area, there was no such dependence. In this area, the daily and weekly variability in the concentrations of nitrogen oxides and sulfur dioxide mainly depended on natural meteorological processes. The work systematizes the meteorological parameters at which the largest amount of anthropogenic impurities enters the air basin of Lake Baikal. The maximum values of acid-forming gas concentrations were observed when the air masses were transferred from the northwest direction, which corresponds to the location of sources in the territory of the Irkutsk–Cheremkhovo industrial hub—the largest concentration of anthropogenic objects in the Irkutsk region.

Effective methods for the decontamination of healthcare waste: Ozone and UV-C radiation process

ABSTRACT Human-generated waste, including infectious healthcare waste, poses significant risks to public health and the environment. The COVID-19 pandemic has increased the global production of infectious waste, emphasizing the need for safe and sustainable waste management practices. While autoclaves are commonly used for on-site disposal, alternative methods like ozone gas and UV-C radiation offer environmentally friendly options that effectively eliminate pathogens without leaving toxic residues. Inadequate waste management can contribute to disease transmission, while open burning releases harmful pollutants. This study investigated the effectiveness of different disinfection agents – ozone gas and UV-C radiation – on infectious solid waste contaminated with bacteria. The bacterial indicators examined were Staphylococcus aureus, Bacillus subtilis, and Pseudomonas aeruginosa. The experimental methods included operating each ozone and UV-C radiation individually and simultaneously using ozone gas and UV-C radiation. The study also investigated exposure times and various concentrations of ozone gas. The findings demonstrated that the simultaneous application of ozone gas and UV-C radiation was the most effective method for decontaminating infectious solid waste and targeting the selected bacteria. The concentration of ozone gas ranged from 165 to 5000 ppm, depending on generation time and treatment chamber volume, while exposure times varied from 1 to 180 minutes. In applying UV-C rays, complete elimination of S. aureus was observed after 60 minutes up to 6-log, while the reduction of B. subtilis and P. aeruginosa were 2-log and 3-log, respectively. Ozone gas had the ability to inactivate all strains, but when ozone gas and UV-C rays were used simultaneously, this process was accelerated and improved. The total reduction in the bacterial load was 8-log. Considering the increase in population and the subsequent increase in waste generation, adopting an environmentally friendly waste management method can be very advantageous. Implications: This study highlights the effectiveness of simultaneously applying ozone gas and UV-C radiation for decontaminating infectious solid waste, offering an environmentally friendly alternative to traditional thermal treatments like autoclave and incineration. By optimizing ozone concentrations and exposure times, this method reduces disease transmission risks and minimizes environmental impact. These findings are crucial, especially during outbreaks such as the COVID-19 pandemic, providing scalable, sustainable waste management solutions for healthcare facilities. Implementing these techniques can protect public health and the environment, setting a new standard for safe infectious waste disposal worldwide, mitigating hazardous pollutants, and reduce the exposure risk of bio-hazardous residues.

Research on Gas Extraction Effect of High Gas Mines Based on Stereoscopic Cross Directional Drilling Technology

Based on the advantages of three-dimensional cross drilling technology and directional drilling technology, a gas extraction technology of "three-dimensional cross + directional" drilling is proposed. The advantages, applicability, and key influencing factors of this technology are analyzed, and on-site gas extraction experiments are conducted at the 2210 working face of the No. 2 coal seam in a certain coal mine. The research results show that after adopting the stereoscopic cross directional drilling technology and extraction technology, the gas extraction effect of the 2210 working face has been significantly improved compared to using ordinary extraction drilling, and the stereoscopic cross directional drilling technology can effectively increase the gas extraction volume and concentration. This technology has obvious advantages in improving gas extraction rate and ensuring operational safety, providing a certain reference for solving gas control problems in high gas mines.

Carbonization and Gasification of Cow‐Dung and Fe3O4 Nanoparticles at Different Operating Conditions for Hydrogen Production

AbstractCow dung is an abundant agricultural by‐product that poses disposal challenges. Converting this waste into a valuable energy resource aligns with sustainable waste management practices and contributes to a circular economy. This research aims at Cow dung disposal by carbonization and gasification for hydrogen generation and maximizes it by optimizing the process parameters. In the pyrolysis‐carbonization process, the influence of temperature on cow dung and its biochar characteristics was initially investigated. On the cow dung feedstock, different operating temperatures at about 400, 500, and 600 °C and response times of about 30, 60, and 120 min were tested. With CD450 as the feedstock, the gas concentrations and hydrogen yield were around 62 vol% and 0.69 m3 kg−1, respectively, for longer reaction times. Similar to this, the gas concentration and yield value for hydrogen at 600 °C gasification temperature is around 64 vol% and 0.91 m3 kg−1. Cow dung is evidently acceptable for larger hydrogen production at higher gasification temperatures and reaction times when the carbonization temperature is 450 °C. In addition, when compared to feedstock without adding nanoparticles, including Fe3O4 nanoparticles may increase the hydrogen concentration and yield by around 13.5 % and 4.21 %, respectively.

Large-scale data-driven uniformity analysis and sensory prediction of commercial banana ripening process

Artificial intelligence (AI) and machine learning (ML) have found prominent yet mostly academic applications in the food supply chain specifically to preserve and optimize the quality of fresh produce and achieve uniformity across the various stages of the cold chain. Nevertheless, the practical use of AI/ML for predictive analytics within real and large-scale commercial food processes, such as banana ripening, is sparse. This study proposes a novel data-driven approach tested and validated on two new large-scale datasets to automate and optimize the banana ripening process in refrigerated marine containers by successfully employing ML in uniformity analysis of the peel color and the pulp temperature of bananas based on atmospheric conditions. The results demonstrate high correlations between the gas concentrations and the uniformity of the process, suggesting that the uniformity of the peel color and the pulp temperature of fruit can be achieved by controlling the concentrations of the CO2 and O2 gas levels. Furthermore, this study, for the first time, achieves accurate algorithmic predictions of oxygen levels from other atmospheric variables to provide an alternative approach for continuous, improved and more cost-effective monitoring of the atmospheric conditions during ripening. A wide-range of predictive models are tested and validated where the Long Short Term Memory regression provides the lowest root-mean-square-errors (0.033 and 0.202) with robust R-squared values (0.999 and 0.959) for two datasets.

Spectroscopic Measurement of Electron Concentration in Shock-Heated Gas

Spectroscopic Measurement of Electron Concentration in Shock-Heated Gas

Expanding forest carbon sinks to mitigate climate change in Africa

Forests significantly contribute to climate change mitigation by acting as carbon sinks, sequestering atmospheric carbon dioxide, and keeping it in soil and biomass. Covering 22 % of its land, African forests offer numerous benefits to millions of people. Nevertheless, they face threats from human activities like deforestation and degradation. A holistic approach encompassing social, economic, and environmental factors is necessary to sustain forests as carbon sinks for maximum carbon sequestration potential. This study used carbon dioxide emissions, forest loss and gain, and land use change to investigate the level of carbon dioxide emissions and their relationship to forest loss and climate change in Africa from 1992 to 2020. Using ArcGIS, land use change was reclassified, InVEST model calculated carbon storage and sequestration, and annual changes in forest cover were assessed using the K and S indices. In the last two decades, 77.36 % of African countries had greater forest losses than gains, leading to 32 × 103 kha net loss, resulting in 15.73 Pg C of carbon dioxide emissions. Annual forest loss rate is 1.6 × 103 kha, equivalent to 0.786 Pg C, and that of carbon storage and sequestration decreased to −0.69 and −1.37, respectively. Results indicate that deforestation, particularly in the Democratic Republic of the Congo, significantly contributes to carbon emissions, and persistent tropical deforestation will affect future greenhouse gas concentrations. This research provides a detailed spatiotemporal analysis, highlighting areas experiencing severe forest cover change and carbon loss, underscoring the importance of forest conservation in mitigating climate change, and promoting effective land management policies.

Heat-dependent properties of methane diffusion in coal: an experimental study and mechanistic analysis.

Coalbed methane thermodynamic extraction, as an emerging ECBM recovery method, can effectively improve gas recovery rates. And clarifying methane diffusion and migration law in coal under thermal stimulation is crucial for the selection of its process parameters. Based on laboratory methane adsorption-release experiments, the evolution law of methane diffusion characteristics with temperature and pressure was studied, and the control mechanism of heat-dependent methane diffusion behavior was explored. The results show that both thermal stimulation and high adsorption pressure accelerated the methane diffusion rate in coal. Adsorption pressure had little effect on methane diffusion percentage, but thermal stimulation promoted a significant increase in diffusion percentage and improved the net methane yield. The influence mechanisms of adsorption pressure and thermal stimulation on methane diffusion characteristics are elucidated in relation to the amount and proportion of methane-activated molecules in the diffusion process. The constant diffusion coefficient of methane is heat-dependent, based on which a diffusion model is derived to accurately predict the methane release process in coal. Additionally, temperature has a more important effect on transient diffusion coefficient than pressure. Thermal stimulation leads to a net increase rather than a decrease in diffusion coefficient in the early diffusion stages and can also accelerate the attenuation of diffusion coefficient, with this intensifying effect becoming more pronounced at higher temperatures. The research results can provide some reference for the determination of coal seam gas content and the selection of heat injection process parameters.

Research and Application of Sealed coring Technology in In-situ Coal Seam of Directional Long borehole in Coal mine

In order to accurately obtain the gas content of in-situ coal seams in coal mines, a sealed coring technology for in-situ coal seams in coal mines has been proposed. By utilizing the pressure difference generated by high-pressure water at both ends of the piston, the piston is driven to cut off the positioning pin, which in turn drives the ball valve in the coring device to rotate, achieving the goal of cutting off and sealing the in-situ coal core. Performance tests were conducted on the sealing pressure of the coring device by opening the amount of water holes on the piston and using suspension pins of different materials, verifying the working parameters of the piston opening amount and suspension pins of different materials, providing basic data for subsequent industrial underground tests. Finally, during the industrial test underground, it was found that the gas content in the coal seam measured by closed sampling was 1.9-2.5 times higher than that of the coal seam sampled by the hole, which verified the successful design of the closed sampling device.

Calculation of Radon Gas Concentrations and Effective Dose of Al-Hindia, Euphrates River in Karbala Governorate Using RAD7

Calculation of Radon Gas Concentrations and Effective Dose of Al-Hindia, Euphrates River in Karbala Governorate Using RAD7

Calculating the Spontaneous Combustion Temperature of Coal Based on Measured Gas concentration: A Case Study in the Huangshan Mine, China

ABSTRACT The actual coal temperature of “spontaneous combustion zone” is not convenient to obtain, which causes a lot of inconvenience to the prevention and control of coal spontaneous combustion fire. The traditional temperature measurement method does not consider the influence of gas flow in the goaf, so the measured coal temperature cannot directly reflect the actual state of coal spontaneous combustion. This paper presents a method to predict the coal temperature in the “spontaneous combustion zone” based on the theoretical data obtained in the laboratory, combined with the actual coal temperature in the “dissipation zone,” and applies it to the B4 layer coal mine in Huangshan, Jiangxi Province. The results show that the method is objective and effective, and can be used for the prediction of CSC (coal spontaneous combustion) in the goaf of coal mines.

Drivers of the ECMWF SEAS5 seasonal forecast for the hot and dry European summer of 2022

AbstractThe European summer (June–August) 2022 was characterised by warm and dry anomalies across much of the continent, likely influenced by a northward‐shifted jet stream. These general features were well predicted by European Centre for Medium‐Range Weather Forecasts' system 5 seasonal forecast, initialised on May 1. Such successful predictions for European summers are relatively uncommon, particularly for atmospheric circulation. In this study, a set of hindcast experiments is employed to investigate the role that initialisation of the ocean, atmosphere, and land surface played in the 2022 forecast. We find that the trend from external forcing was the strongest contributor to the forecast near‐surface temperature anomalies, with atmospheric circulation and land‐surface interactions playing a secondary role. On the other hand, atmospheric circulation made a strong contribution to precipitation anomalies. Modelled Euro‐Atlantic circulation anomalies in 2022 were consistent with a La Niña‐forced teleconnection from the tropical Pacific. However, a northward jet trend in the model hindcasts with increasing greenhouse gas concentrations also contributed to the predicted circulation anomalies in 2022. In contrast, the observed linear trend in the jet over the past four decades was a southward shift, though it is unclear whether this trend was driven by external forcings or natural variability. Nevertheless, this case study demonstrates that important features of at least some European summers are predictable at the seasonal time‐scale.

Study on Safety Tunneling Technology of Secondary Outburst Elimination by CO2 Gas Fracturing in High-Outburst Coal Seam

The No. 3 coal seam in the Yuxi Coal Mine has a measured maximum gas content of 25.59 m3/t, along with a maximum gas pressure of 2.9 MPa, indicating its high risk to gas and outbursts. To mitigate outburst risks of the coal seam, the 1301 working face has been implemented with gas pre-drainage measures by grid boreholes from underlying roadways. After one year of extraction, it was confirmed that the gas content at all 33 test sites was below 8 m3/t, meeting the outburst prevention standards. However, during subsequent coal tunnel excavation, the gas desorption index K1 value frequently exceeded the standard, resulting in numerous occurrences of abnormal gas emission or small-scale outbursts. To tackle the challenges associated with safe excavation following the first-round regional outburst prevention measures, a research and industrial trial of CO2 gas fracturing (CO2-Frac) technology for secondary outburst prevention and rapid excavation was completed. The results show that the dual-hole and high-pressure (185 MPa) CO2-Frac considerably contributes to outburst prevention. K1 exceedances per hundred meters of tunnel excavations were from an average of 2.54 without CO2-Frac to an average of 0.28 after the new technology was implemented, leading to an eight-fold reduction. Additionally, the monthly excavation footage increased from an average of 81.64 m without CO2-Frac to an average of 162.42 m with CO2-Frac, resulting in a two-fold improvement. The dual-hole and high-pressure CO2-Frac is an advanced technology for safe and efficient excavation for secondary outburst elimination in highly outburst-prone coal seams in the Yuxi Coal Mine, with potential for widespread application in similar coal seam conditions.

Influence of entrainment on residual content of pollutants after absorber with sieve trays and wire demister

Entrainment is an important negative process that affects the efficiency of column units with a sieve trays. In sieve trays absorbers, entrainment leads to secondary contamination of the gas being purified by the reflux liquid. The sizes of entrainment droplets range widely from microns to millimeters and are the determining factor affecting the efficiency of demister. A review of studies on the flow rate and dispersion characteristics of entrainment removal from sieve trays is carried out, the research results are summarized in the form of a methodology for calculating the residual liquid content in gas after an absorber with a wire demister. In an absorber with cross-flow foam trays and a wire demister, there is an irreducible residual content of the reflux liquid, about several mg/m3, which practically does not change up to gas velocities of 1–1.5 m/s.

Improving the short-term prediction of dissolved carbon monoxide using a combination of Light GBM and meta-heuristic algorithms

In this study, the prediction of carbon monoxide pollutants on a short-term scale has been investigated according to some input data sources, comprising gas concentrations related to air quality and weather features. Utilizing a hybrid modeling approach that integrates the Light Gradient Boosting Machine with several meta-heuristic optimization algorithms such as Chaos Game Optimization, Aquila Optimizer, and others, we aimed to optimize the hyperparameters of the Light GBM to enhance predictive accuracy. The application of a K-fold cross-validation technique with K=5 helped in preventing overfitting. By conducting a case study on a real dataset collected from a gas multi-sensor device, it was found that the hybrid model combining the Light Gradient Boosting Machine with Chaos Game Optimization demonstrated superior performance compared to other models. The values of the coefficient of determination, Root Mean Square Error, Mean Absolute Error, and Mean Absolute Percentage Error for this model based on test data are 0.99, 0.0393, 0.0301, and 0.0052, respectively. These results underscore the effectiveness of the hybridization approach in providing highly accurate predictions for short-term carbon monoxide concentrations, offering a valuable tool for environmental monitoring and enhancing public health safeguards.