Search Results (148)

Açaí (Euterpe oleracea Mart.) is a native fruit of the Amazon, and its production chain is centered in the state of Pará. The processing of açaí fruits generates large amounts of solid waste, which can pose serious risks to the environment if not used and managed properly. The novelty of this research lies in the fact that until this moment, no research had been reported in the literature on the pyrolysis of açaí fibers and the chemical composition of the aqueous phase, making possible a broad set of applications including biogas production. The present research proposes a study of the pyrolysis of açaí seeds and fibers and the physicochemical and compositional characterization of the aqueous phase products. In this way, açaí processing residues were collected in the city of Belém, PA. The seeds and fibers were dried and impregnated with NaOH solutions, and subsequently subjected to pyrolysis on a laboratory scale. The liquid products from pyrolysis were characterized through acidity index analysis, FT-IR, and gas chromatography. The increase in the concentration of the impregnating agent led to an increase in bio-oil yield from both the seeds (ranging from 3.3% to 6.6%) and the fibers (ranging from 1.2% to 3.7%). The yield in the aqueous phase showed an inverse behavior, decreasing as the concentration of NaOH increased, both in the seeds (ranging from 41% to 37.5%) and the fibers (ranging from 33.7% to 21.2%). High acidity levels were found in the liquid products studied, which decreased as the concentration of the impregnating agent increased. The increase in the concentration of the impregnating agent (NaOH) influenced the chemical composition of the obtained liquid products, leading to a decrease in oxygenated compounds and an increase in nitrogenous compounds in both experimental matrices, which was also evidenced by the reduction in acidity. Full article

Radon’s radioactive decay is the main natural source of small air ions near the ground. Its exhalation from soil is affected by meteorological factors, while aerosol pollution reduces air ion concentrations through ion-particle attachment. This study aimed to analyze correlations between radon, ions, and air pollution under varying conditions and to assess potential health impacts. Measurements were taken at two sites: in early autumn at a suburban part of Belgrade with relatively clean air, and in late autumn in central Belgrade under polluted conditions, with low temperatures and high humidity. Parameters measured included radon, small air ions, particle size distribution, PM mass concentration, temperature, humidity, and pressure. Results showed lower radon concentrations in late autumn due to high soil moisture and absence of nocturnal inversions. Radon and air ion concentrations exhibited a strong positive correlation for both polarities under suburban conditions, whereas measurements in the urban setting revealed a weak negative correlation, despite radon concentrations in soil gas being approximately equal at both sites. Small ion levels were also reduced, mainly due to suppressed radon exhalation and increased aerosol concentrations, especially ultrafine particles. A strong negative correlation (r < −0.5) was found between small air ion concentrations and particle number concentrations in the 20–300 nm range, while larger particles (300–1000 nm and >1 µm) showed weak or no correlation due to their lower and more stable concentrations. In contrast, early autumn measurements showed a diurnal cycle of radon, characterized by nighttime maxima and daytime minima, unlike the consistently low values observed in late autumn. Full article

Methane (CH₄) emissions from dairy farming represent a substantial yet under-quantified share of agricultural greenhouse gas emissions. This study provides an in-depth, satellite-based fingerprinting analysis of methane emissions from Canada’s dairy sector, using Sentinel-5P/TROPOMI data. We utilized a robust quasi-experimental design, pairing 14 dairy-intensive zones with eight non-dairy reference regions, to analyze methane emissions from 2019 to 2024. A dynamic, region-specific baseline approach was implemented to remove temporal non-stationarity and isolate dairy-specific methane signals. Dairy regions exhibited consistently higher methane concentrations than reference areas, with an average methane anomaly of 17.4 ppb. However, this concentration gap between dairy and non-dairy regions notably narrowed by 57.23% (from 24.42 ppb in 2019 to 10.44 ppb in 2024), driven primarily by accelerated methane increases in non-dairy landscapes and a pronounced one-year contraction during 2022–2023 (−39.29%). Nationally, atmospheric methane levels rose by 3.83%, revealing significant spatial heterogeneity across provinces. Notably, an inverse relationship between the initial methane concentrations in 2019 and subsequent growth rates emerged, indicating spatial convergence. The seasonal analysis uncovered consistent spring minima and fall–winter maxima across regions, reflecting the combined effects of seasonal livestock management practices, atmospheric transport dynamics, and biogeochemical processes. The diminishing dairy methane anomaly suggests complex interplay of intensifying background methane emissions from climate-driven wetland fluxes, increasing fossil fuel extraction activities, and diffuse agricultural emissions. These findings underscore the emerging challenges in attributing sector-specific methane emissions accurately from satellite observations, highlighting both the capabilities and limitations of current satellite monitoring approaches. Full article

Remote sensing imaging technology is one of the safest and most effective tools for gas leakage monitoring in chemical parks, as it enables fast and accurate access to detailed information about the gas cloud (e.g., volume, distribution, diffusion, and location) in the case of gas leakage. While multi-spectral imaging systems are commonly used for hazardous gas leakage detection, efforts to realize the three-dimensional reconstruction of gas clouds through data obtained from multi-spectral imaging systems remain scarce. In this study, we propose a method for realizing the three-dimensional reconstruction of gas clouds with only two multi-spectral imaging systems; in particular, the two multi-spectral imaging systems are used to simultaneously observe the three-dimensional space with gas leakage and reconstruct gas cloud images in real time. A geometric method is used for the localization in the monitoring space and the construction of a three-dimensional spatial grid. The non-axisymmetric inverse Abel transform (IAT) is then applied to the extracted gas absorbance images in order to realize the reconstruction of each layer, and these are then stacked to form a 3D gas cloud. Through the above measurement, identification, and reconstruction processes, a 3D gas cloud with geometric information and concentration distribution characteristics is generated. The results of simulation experiments and external field tests prove that gas clouds can be localized under the premise that they are completely covered by the field of view of both scanning systems, and the 3D distribution of the leakage gas cloud can be reconstructed quickly and accurately with the proposed system. Full article

Polychlorinated biphenyls (PCBs) are synthetic organic compounds that were widely used in industrial applications throughout the 20th century. Due to their chemical stability, resistance to degradation and ability to bioaccumulate and biomagnify through food chains, PCBs pose long-term environmental and health risks. Due to these characteristics, PCBs have been globally regulated as persistent organic pollutants (POPs), despite being banned from production in most countries decades ago. This study investigates temporal trends in PCB contamination in urban soils of Bucharest over a 20-year period (2002–2022), focusing on six principal congeners (PCB 28, 52, 101, 138, 153, and 180) sampled from 13 locations, including roadsides and urban parks. Gas chromatography and spatial analysis using inverse distance weighting (IDW) revealed a marked reduction in Σ6PCB concentrations, declining from 0.0159 mg/kg in 2002 to 0.0065 mg/kg in 2022, with statistically significant differences confirmed by Kruskal–Wallis analysis (p < 0.05). This decline is primarily attributed to reduced emissions, source control measures, and natural attenuation. However, the persistence of PCBs in localized hotspots is influenced by secondary dispersion mechanisms, such as atmospheric deposition and surface runoff, which redistribute contaminants rather than eliminate them. Health risk assessments via ingestion, dermal absorption, and inhalation routes confirmed negligible carcinogenic risk for both adults and children. Although measurable progress has been achieved, the persistence of localized contamination underscores the need for targeted remediation strategies and sustained environmental monitoring to protect vulnerable urban areas from recontamination. Full article

This study investigates the hydrothermal gasification (HTG) of apricot tree resin, focusing on the yield and chemical composition of the resulting gas and aqueous phases. K₂CO₃ and KOH were used as catalysts within a temperature range of 300–600 °C, with a constant reaction time of 60 min. The results show that temperature and catalyst choice significantly influence gas yield, liquid composition, and solid residue formation. Higher temperatures increased the gas yield while decreasing aqueous and solid residues. The catalytic effect of K₂CO₃ and KOH enhanced the gaseous product conversion, with KOH achieving the highest gas yield and lowest residue formation at 600 °C. Among the liquid-phase compounds, carboxylic acids and 5-methyl furfural were the most abundant, reaching peak concentrations at 300 °C in the presence of K₂CO₃. The addition of alkali catalysts reduced key acidic intermediates such as glycolic, acetic, and formic acids. The inverse relationship between temperature and liquid/solid product formation underscores the importance of optimizing reaction conditions for efficient biomass conversion. These findings contribute to the growing field of biomass valorization by highlighting the potential of underutilized tree resins in sustainable biofuel production, advancing knowledge in renewable hydrogen production, and supporting the broader development of bio-based energy solutions. Full article

Biodiesel derived from waste cooking oil (WCO) and animal fats is a promising alternative to fossil fuels, offering environmental benefits and renewable energy potential. However, a detailed understanding of its combustion characteristics at the droplet scale is essential for optimizing its practical application. This study investigates the combustion behavior of biodiesel–diesel blends (B5, B10, B15, B20, B25, B50, B75) and neat fuels (B0 and B100) by analyzing combustion rates, pre-ignition time, burning time, droplet morphology, and puffing characteristics. The results demonstrate that biodiesel concentration strongly influences combustion dynamics. Higher blends (B50, B75) exhibit enhanced steady combustion rates due to increased oxygen availability, while lower blends (B5–B25) experience stronger puffing events, leading to greater secondary droplet formation. The global combustion rate follows a non-linear trend, peaking at B10, decreasing at B25, and rising again at B50 and B75. Pre-ignition time increases with biodiesel content, while burning time exhibits an inverse relationship with combustion rate. Four distinct puffing mechanisms were identified, with lower blends producing finer secondary droplets and higher blends forming larger droplets. Puffing characteristics were evaluated based on puffing occurrences, intensity, and effectiveness, revealing that puffing peaks at B25 in occurrence and at B10 in intensity, while higher blends (B50, B75) exhibit notable puffing effectiveness. This study addresses a critical research gap in droplet-scale combustion of WCO and animal fat-derived biodiesel across a wide range of blend ratios (B5–B75). The findings provide key insights for optimizing biodiesel formulations to improve fuel spray atomization, ignition stability, and combustion efficiency in spray-based combustion systems, such as diesel engines, gas turbines, and industrial burners, bridging fundamental research with real-world applications. Full article

Monitoring and early warning systems for cross-fault buried pipelines are critical measures to ensure the safe operation of oil and gas pipelines. Accurately acquiring pipeline strain response serves as the fundamental basis for achieving this objective. This study proposes a comprehensive analytical methodology combining finite element analysis (FEA) and experimental verification to investigate strain responses in cross-fault buried pipelines. Firstly, a finite element modeling approach with equivalent-spring boundaries was established for cross-fault pipeline systems. Secondly, based on the similarity ratio theory, an experimental platform was designed using Φ89 mm X42 steel pipes and in situ soil materials. Subsequently, the finite element model of the experimental conditions was constructed using the proposed FEA. Guided by simulation results, strain sensors were strategically deployed on test pipelines to capture strain response data under mechanical loading. Finally, prototype-scale strain responses were obtained through similarity ratio inverse modeling, and a comparative analysis with full-scale FEA results was performed. The results demonstrate that strike-slip fault displacement induces characteristic “S”-shaped antisymmetric deformation in pipelines, with maximum strain concentrations occurring near the fault plane. Both the magnitude and location of maximum strain derived from similarity ratio inverse modeling show close agreement with FEA predictions, with relative discrepancies within 18%. This consistency validates the reliability of the experimental design and confirms the accuracy of the finite element model. The proposed methodology provides valuable technical guidance for implementing strain-based monitoring and early warning systems in cross-fault buried pipeline applications. Full article

As mining depths increase, the highly metamorphosed anthracite in Southwest China progressively develops into a complex dynamic disaster influenced by both in situ stress and gas pressure. By utilizing characteristic indicators of mining-induced stress and gas dynamic emissions, a grading evaluation method for coal and gas dynamic disasters (CGDDs) based on fuzzy mathematics l theory is proposed and validated at the No. 1 Well of the Yuwang Coal Mine. The results indicate that the acceleration of microseismic wave velocity and the increase in the wave velocity anomaly coefficient are indicative of a more pronounced stress concentration. The working face exhibits distinct gradations of stress concentrations, categorized as weak, moderate, and strong. Moreover, the increase in microseismic wave velocity and the anomaly coefficient further confirm the intensity of the stress concentrations. Gas dynamic emissions show a clear correlation with the drill cuttings gas desorption indicator ($K_1$ value) and drill cuttings volume ($S$ value). Characteristic indicators A, B, and D are suitable for assessing the risk of CGDDs in the working face. For the application of individual indicators for classifying the CGDD risk at different distances from the crosscut (128 m, 247.5 m, 299.4 m, and 435 m) in the 1010201-working face, contradictory classification results were observed. However, the classification results derived from the fuzzy mathematics method were consistent with the findings of field investigations. As the working face advanced through the pre-concentrated stress zone, significant changes were observed in both the source wave velocity and wave velocity anomaly coefficient. Concurrently, gas emissions displayed a distinct pattern of fluctuation characterized by increases and decreases. The consistency between the periodic weighting of the working face, the gas emission, the drill cuttings gas desorption indicator, and the stress field inversion result further validates the classification outcomes. These research results can provide theoretical support for the monitoring of CGDDs. Full article

This study addresses the abnormal emission of pressure-relieved methane under high-intensity mining conditions by integrating geostatistical inversion, FLAC^3D-COMSOL coupled numerical simulations, and stable carbon–hydrogen isotopic tracing. Focusing on the 12023 working face at Wangxingzhuang Coal Mine, we established a heterogeneous methane reservoir model to analyze the mechanical responses of surrounding rock, permeability evolution, and gas migration patterns under mining intensities of 2–6 m/d. Key findings include the following: (1) When the working face advanced 180 m, vertical stress in concentration zones increased significantly with mining intensity, peaking at 12.89% higher under 6 m/d compared to 2 m/d. (2) Higher mining intensities exacerbated plastic failure in floor strata, with a maximum depth of 47.9 m at 6 m/d, enhancing permeability to 223 times the original coal seam. (3) Isotopic fingerprinting and multi-method validation identified adjacent seams as the dominant gas source, contributing 77.88% of total emissions. (4) Implementing targeted long directional drainage boreholes in floor strata achieved pressure-relief gas extraction efficiencies of 34.80–40.95%, reducing ventilation air methane by ≥61.79% and maintaining return airflow methane concentration below 0.45%. This research provides theoretical and technical foundations for adaptive gas control in rapidly advancing faces through stress–permeability coupling optimization, enabling the efficient interception and resource utilization of pressure-relieved methane. The outcomes support safe, sustainable coal mining practices and advance China’s Carbon Peak and Neutrality goals. Full article

The short-wave infrared (SWIR) grating imaging spectrometer based on indium gallium arsenide (InGaAs) material inverts the atmospheric methane concentration by measuring the scattered light signals in the sky. This study proposes spectral and radiometric calibration methods for the characteristics of the spectrometer, such as the small-area array, high signal-to-noise ratio, and high spectral resolution. Four spectral response function models, namely, the Gauss, Lorentz, Voigt and super-Gaussian models, were compared during spectral calibration. With a fitting residual of 0.032, the Gauss model was found to be the most suitable spectral response function for the spectrometer. Based on the spectral response function, the spectral range and spectral resolution of the spectrometer were determined to be 1592.4–1677.2 and 0.1867 nm, respectively. In addition, radiometric calibration of the spectrometer was achieved by combining an integrating sphere and linear measuring instrument. Moreover, absolute and relative radiometric calibrations of the spectrometer were performed. The low signal response problem caused by the quantum efficiency of the detector at long wavelength was corrected, and the uncertainty and non-stability uncertainty of absolute radiometric calibration were calculated to be less than 0.2%. Finally, the calibrated spectrometer was used to accurately measure the solar scattering spectrum in the SWIR band, and the solar spectrum was simulated by the radiative transfer model for verification; the measurement error was found to be 5%. Concurrently, a methane sample gas experiment was performed using the integrating-sphere light source, and the measurement error was less than 4%. This fully proves the effectiveness of the spectral and radiometric calibrations of the SWIR spectrometer and strongly guarantees a subsequent, rapid and accurate inversion of atmospheric methane concentration. Full article

The accurate monitoring of greenhouse gas (GHG) concentrations is crucial in mitigating global warming. The imaging Fourier transform spectrometer (IFTS) is an effective tool for measuring GHG concentrations, offering high throughput and a wide spectral measurement range. In order to address the issue of spectral inconsistency during the detection process of the target gas, which is influenced by external environmental factors, making it difficult to achieve high-precision gas concentration inversion, this paper proposes a multi-scale feature attention (MDISE) model. The model uses a multi-scale dilated convolution (MD) module to retain both global and local shallow features of the spectra; introduces the one-dimensional Inception (1D Inception) module to further extract multi-scale deep features; and incorporates the channel attention mechanism (SE) module to enhance attention to important spectral wavelengths, suppressing redundant and interfering information. A target gas detection system was built in the laboratory, and the proposed model was tested on gas samples collected by two channels of a short and medium-wavelength infrared imaging Fourier transform spectrometer (SMWIR-IFTS). The experimental results show that the MDISE model reduces the root mean square error (RMSE) in both channels by 79.14%, 76.59%, and 69.80%, and 81.45%, 82.65%, and 74.01%, respectively, compared to the partial least squares regression (PLSR), support vector regression (SVR), and conventional one-dimensional convolutional neural network (1D-CNN) models. Additionally, the MDISE model achieved average coefficient of determination (R²) values of 0.997 and 0.995 for the concentration intervals in both channels. The MDISE model demonstrates excellent performance and significantly improves the accuracy of GHG concentration inversion. Full article

This study aims to investigate the characteristics of ash accumulation and slagging in boilers during low- and medium-load operation and to analyse the migration pattern of alkali metals in high-alkali coal. In this paper, the ash accumulation characteristics and slagging trend of the furnace interior under a 500 MW load were investigated using numerical simulation by comparing the ash accumulation and slagging characteristics under two different burner configurations, and analysing the slagging trend of the furnace with upper burner arrangement and lower burner arrangement by taking the deposition location on the furnace wall and the deposition rate and the temperature of the furnace wall as the indices. The existing formation of sodium in Jundong coal at different temperatures was investigated using computational methods; SiO₂, Al₂O₃, and kaolin were doped separately; and the migration and transformation characteristics of their different additives on the sodium-based compounds in Jundong coal were explored. The results showed that, under a 500 MW load, the size of the tangent circle formed in the furnace by commissioning the upper burner condition was larger than the lower burner, and the main combustion zone was larger than the lower burner. The ash accumulation of coal ash particles in the boiler was mainly concentrated in the hearth region, and the deposition rate was higher at the height regions of 10 m and 25 m in the hearth. The solid-phase NaCl transition temperature was reduced to 350 °C after the doping of SiO₂ in Jundong coal, and the doping of Al₂O₃ inhibited the transition of solid-phase NaCl, promoted the generation of gas-phase NaCl, and had certain inhibitory effects on the generation of sodium-based silica–aluminium compounds, the content of which at all temperatures was inversely proportional to the proportion of doping. The doping of kaolin promotes the transformation of solid-phase NaCl and inhibits the generation of gas-phase NaCl. Full article

A promising approach for carbon dioxide (CO₂) valorization and storing excess electricity is the biological methanation of hydrogen and carbon dioxide to methane. The primary challenge here is to supply sufficient quantities of dissolved hydrogen. The newly developed Inverse Membrane Reactor (IMR) allows for the spatial separation of the required reactant gases, hydrogen (H₂) and carbon dioxide (CO₂), and the degassing area for methane (CH₄) output through commercially available ultrafiltration membranes, enabling a reactor design as a closed circuit for continuous methane production. In addition, the Inverse Membrane Reactor (IMR) facilitates the utilization of hydraulic pressure to enhance hydrogen (H₂) input. One of the process’s advantages is the potential to utilize both carbon dioxide (CO₂) from conventional biogas and CO₂-rich industrial waste gas streams. An outstanding result from investigating the IMR revealed that, employing the membrane gassing concept, methane concentrations of over 90 vol.% could be consistently achieved through flexible gas input over a one-year test series. Following startup, only three supplemental nutrient additions were required in addition to hydrogen (H₂) and carbon dioxide (CO₂), which served as energy and carbon sources, respectively. The maximum achieved methane formation rate specific to membrane area was 87.7 L_N of methane per m² of membrane area per day at a product gas composition of 94 vol.% methane, 2 vol.% H₂, and 4 vol.% CO₂. Full article

As a promising candidate for More Moore technology, InGaAs-based n-channel metal-oxide-semiconductor field-effect transistors (nMOSFETs) have attracted growing research interest, especially with InGaAs-on-insulator (InGaAs-OI) configurations aimed at alleviating the short channel effects. Correspondingly, the fabrication of an ultrathin InGaAs body becomes necessary for the full depletion of the channel, while the deteriorated semiconductor–insulator interface-related scattering could severely limit carrier mobility. This work focuses on the exploration of carrier mobility enhancement strategies for 8 nm body-based InGaAs-OI nMOSFETs. With the introduction of a bottom gate bias on the substrate side, the conduction band structure in the channel was modified, relocating the carrier wave function from the InGaAs/Al₂O₃ interface into the body. Resultantly, the channel mobility with an inversion layer carrier concentration of 1 × 10¹³ cm⁻² was increased by 62%, which benefits InGaAs-OI device application in monolithic 3D integration. The influence of the dual-gate bias from front gate and bottom gate on gate stability was also investigated, where it has been unveiled that the introduction of the positive bottom gate bias is also beneficial for gate stability with an alleviated orthogonal electric field. Full article