Search Results (1,261)

This paper proposes an intelligent power adaptation framework for Free-Space Optics (FSO) communication systems operating under different weather conditions exploiting a deep learning (DL) analysis of received eye diagram images. The system incorporates two Convolutional Neural Network (CNN) architectures, LeNet and Wide Residual Network (Wide ResNet) algorithms to perform regression tasks that predict received signal quality metrics such as the Quality Factor (Q-factor) and Bit Error Rate (BER) from the received eye diagram. These models are evaluated using Mean Squared Error (MSE) and the coefficient of determination (${\mathrm{R}}^2$ score) to assess prediction accuracy. Additionally, a custom CNN-based classifier is trained to determine whether the BER reading from the eye diagram exceeds a critical threshold of ${10}^{-4}$; this classifier achieves an overall accuracy of 99%, correctly detecting 194/195 “acceptable” and 4/5 “unacceptable” instances. Based on the predicted signal quality, the framework activates a dual-amplifier configuration comprising a pre-channel amplifier with a maximum gain of 25 dB and a post-channel amplifier with a maximum gain of 10 dB. The total gain of the amplifiers is adjusted to support the operation of the FSO system under all-weather conditions. The FSO system uses a 15 dBm laser source at 1550 nm. The DL models are tested on both internal and external datasets to validate their generalization capability. The results show that the regression models achieve strong predictive performance, and the classifier reliably detects degraded signal conditions, enabling the real-time gain control of the amplifiers to achieve the quality of transmission. The proposed solution supports robust FSO communication under challenging atmospheric conditions including dry snow, making it suitable for deployment in regions like Northern Europe, Canada, and Northern Japan. Full article

The Sichuan Basin is a natural-gas-exploiting area with intensive agriculture activities. However, the spatial and temporal distribution of atmospheric methane concentration and the relationships with intensive agriculture and natural gas extraction activities are not well investigated. In this study, a long-term (2003–2021) dataset of column-averaged dry-air mole fraction of methane (XCH₄) over the Sichuan Basin and adjacent regions was built by integrating multi-satellite remote sensing data (SCIAMACHY, GOSAT, Sentinel-5P), which was calibrated using ground station data. The results show a strong correlation and consistency (R = 0.88) between the ground station and satellite observations. The atmospheric CH₄ concentration of the Sichuan Basin showed an overall higher level (around 20 ppb) than that of the whole of China and an increasing trend in the rates, from around 2.27 ppb to 10.44 ppb per year between 2003 and 2021. The atmospheric CH₄ concentration of the Sichuan Basin also exhibits clear seasonal changes (higher in the summer and autumn and lower in the winter and spring) with a clustered geographical distribution. Agricultural activities and natural gas extraction contribute significantly to atmospheric methane concentrations in the study area, which should be considered in carbon emission management. This study provides an effective way to investigate the spatiotemporal distribution of atmospheric CH₄ concentration and related factors at a regional scale with natural and human influences using multi-source satellite remote sensing data. Full article

The prevailing environmental conditions before and during the 28 Large Forest Fires (LFFs) that have occurred in the Canary Islands since 1983 are analyzed. These conditions are often associated with episodes characterized by the advection of continental tropical air masses originating from the Sahara, which frequently result in intense heatwaves. During the onset of the LFFs, the base of the subsidence thermal inversion layer—separating a lower layer of cool, moist air from an upper layer of warm, dry air—is typically located at an altitude of around 350 m above sea level, approximately 600 m below the usual average. Understanding these Saharan air advection events is crucial, as they significantly alter the vertical thermal structure of the atmosphere and create highly conducive conditions for wildfire ignition and spread in the forested mid- and high-altitude zones of the archipelago. Analysis of meteorological records from various weather stations reveals that the average maximum temperature on the first day of fire ignition is 30.3 °C, with mean temperatures of 27.4 °C during the preceding week and 28.9 °C throughout the fire activity period. Relative humidity on the ignition days averages 24.3%, remaining at around 30% during the active phase of the fires. No significant correlation has been found between dry or wet years and the occurrence of LFFs, which have been recorded across years with widely varying precipitation levels. Full article

Atmospheric warming results in increase in temperatures for the mean, the coldest, and the hottest day of the year, season, or month. Global warming leads to a large increase in the atmospheric water vapor content and to changes in the hydrological cycle, which include an intensification of precipitation extremes. Using the GISS-E2.1 climate model, we present the future changes in the coldest and hottest daily temperatures as well as in extreme precipitation indices (under four main Shared Socioeconomic Pathways (SSPs)). The increase in the wet-day precipitation ranges between 6% and 15% per 1 °C global surface temperature warming. Scaling of the 95th percentile versus the total precipitation showed that the sensitivity for the extreme precipitation to the warming is about 10 times stronger than that for the mean total precipitation. For six precipitation extreme indices (Total Precipitation, R95p, RX5day, R10mm, SDII, and CDD), the histograms of probability density functions become flatter, with reduced peaks and increased spread for the global mean compared to the historical period of 1850–2014. The mean values shift to the right end (toward larger precipitation and intensity). The higher the GHG emission of the SSP scenario, the more significant the increase in the index change. We found an intensification of precipitation over the globe but large uncertainties remained regionally and at different scales, especially for extremes. Over land, there is a strong increase in precipitation for the wettest day in all seasons over the mid and high latitudes of the Northern Hemisphere. There is an enlargement of the drying patterns in the subtropics including over large regions around Mediterranean, southern Africa, and western Eurasia. For the continental averages, the reduction in total precipitation was found for South America, Europe, Africa, and Australia, and there is an increase in total precipitation over North America, Asia, and the continental Russian Arctic. Over the continental Russian Arctic, there is an increase in all precipitation extremes and a consistent decrease in CDD for all SSP scenarios, with the maximum increase of more than 90% for R95p and R10 mm observed under SSP5–8.5. Full article

The Latin American and Caribbean (LAC) region faces persistent challenges of inequality, climate change vulnerability, and deteriorating air quality. The Aburrá Valley, where Medellín is located, is a narrow tropical valley with complex topography, strong thermal inversions, and unstable atmospheric conditions, all of which exacerbate the accumulation of pollutants. In Medellín, ${\mathrm{NO}}_2$ concentrations have remained nearly unchanged over the past eight years, consistently approaching critical thresholds, despite the implementation of air quality control strategies. These persistent high concentrations are closely linked to the variability of the atmospheric boundary layer (ABL) and are often intensified by prolonged dry periods. This study focuses on a representative street canyon in Medellín that has undergone recent urban interventions, including the construction of new public spaces and pedestrian areas, without explicitly considering their impact on ${\mathrm{NO}}_x$ dispersion. Using Computational Fluid Dynamics (CFD) simulations, this work evaluates the influence of urban morphology on ${\mathrm{NO}}_x$ accumulation. The results reveal that areas with high Aspect Ratios (AR > 0.65) and dense vegetation exhibit reduced wind speeds at the pedestrian level—up to 40% lower compared to open zones—and higher ${\mathrm{NO}}_2$ concentrations, with maximum simulated values exceeding 50 μg/m³. This study demonstrates that the design of pedestrian corridors in complex urban environments like Medellín can unintentionally create pollutant accumulation zones, underscoring the importance of integrating air quality considerations into urban planning. The findings provide actionable insights for policymakers, emphasizing the need for comprehensive modeling and field validation to ensure healthier urban spaces in cities affected by persistent air quality issues. Full article

The influence of the copper (Cu) content on the corrosion resistance of 3.5%Ni low-carbon weathering steel was investigated using periodic dry–wet cycle accelerated corrosion tests. The mechanical properties of the steels were assessed via tensile and low-temperature impact tests, while corrosion resistance was evaluated based on weight loss measurements. Surface oxide layers were characterized using three-dimensional laser confocal microscopy, X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS), and electrochemical methods. Electron probe microanalysis (EPMA) was employed to examine the cross-sectional morphology of the oxide layer after 72 h of accelerated corrosion tests. The results indicate that the solution state of Cu increased the strength of 3.5%Ni steels but significantly damaged the low-temperature toughness. As the Cu content increased from 0.75% to 1.25%, the corrosion rate decreased from 4.65 to 3.74 g/m² h. However, when there was a further increase in the Cu content to 2.15%, there was little decrease in the corrosion rate. With the increase in the Cu content from 0.75% to 2.15%, the surface roughness of 3.5%Ni weathering steel after corrosion decreased from 5.543 to 5.019 μm, and the corrosion behavior was more uniform. Additionally, the α/γ protective factor of the oxide layer of the surface layer increased from 2.58 to 2.84 with an increase in the Cu content from 0.75% to 1.25%, resulting in the oxide layer of the surface layer being more protective. For 1.25%Cu steel, the corrosion current density of rusted samples is lower (ranging from 1.2609 × 10⁻⁴ A/cm² to 3.7376 × 10⁻⁴ A/cm²), and the corrosion potential is higher (ranging from −0.85544 V to −0.40243 V). Therefore, the rusted samples are more corrosion resistant. The Cu in the oxide layer of the surface layer forms CuO and CuFeO₂, which are helpful for increasing corrosion resistance, which inhibits the penetration of Cl⁻. Full article

Mercury (Hg) poses a significant threat to human health and ecosystems, garnering increased attention in environmental studies. This paper evaluates the dynamics of Hg accumulation in various common tree leaves, specifically white poplar, linden, and cherry plum, throughout their growing season. The findings offer valuable insights into air quality and the ability of urban vegetation to mitigate mercury pollution in urban areas. A case study was conducted in Turda, a town in northwestern Romania, where a former chlor-alkali plant operated throughout the last century. Although the plant ceased its electrolysis activities over 25 years ago, the surrounding soil remains contaminated with mercury (Hg) due to the significant amounts released during its operation. The results indicated that the Hg concentration varied between 2.4 and 7.3 mg kg⁻¹ dry weight (dw), exceeding the intervention threshold for soil of 2.0 mg kg⁻¹. Additionally, the Hg content in the leaf samples consistently increased over time, influenced by leaf age and tree species. The Hg content increased in the following order: cherry plum < white poplar < linden. On average, white poplar leaves accumulated 72 ng Hg g⁻¹ dw, linden leaves 128 ng Hg g⁻¹ dw, and cherry plum leaves 47 ng Hg g⁻¹ dw during the six-month monitored period from April to September. The results obtained can be used to evaluate the potential of different tree species for mitigating atmospheric Hg contamination and to elaborate on the suitable management of fallen leaves in the autumn. Full article

Several strains of the genus Serratia isolated from the rhizosphere of crops are plant growth-promoting bacteria (PGPB) that may possess various traits associated with nitrogen metabolism, auxin production, and other characteristics. The objective of the present study was to investigate the in vitro and in vivo characteristics of the growth-promoting activity of S. liquefaciens UNJFSC 002 in potato plants. This strain was inoculated into potato varieties (Solanum tuberosum) under laboratory and greenhouse conditions to determine the bacterial strain’s ability to promote growth under controlled conditions. It was found that the S. liquefaciens strain UNJFSC 002 had a significantly greater effect on the fresh and dry weight of the foliage and induced a higher tuber weight per plant and larger tuber diameter compared to the uninoculated potato plants (p < 0.05). Additionally, in vitro, the strain demonstrated the ability to fix atmospheric nitrogen and produce indole-3-acetic acid (IAA), as well as the capacity to solubilise tricalcium phosphate in the laboratory. This research reveals the potential of S. liquefaciens UNJFSC 002 as an inoculant to improve potato production, demonstrating its ability to promote the growth and productivity of potato varieties suitable for direct consumption and processing under controlled conditions. Full article

Expansive soils, characterized by the presence of surface and subsurface cracks, over-consolidation, and swell-shrink properties, present significant challenges to slope stability in geotechnical engineering. Despite extensive research, preventing geohazards associated with expansive soils remains unresolved. This study investigates shallow sliding failures in slopes of highly expansive soils induced by rainfall, using model tests to explore deformation and mechanical behavior under cyclic wetting and drying conditions, focusing on the interaction between soil properties and environmental factors. Model tests were conducted in a wedge-shaped box filled with Nanyang expansive clay from Henan, China, which is classified as high-plasticity clay (CH) according to the Unified Soil Classification System (USCS). The soil was compacted in four layers to maintain a 1:2 slope ratio (i.e., 1 vertical to 2 horizontal), which reflects typical expansive soil slope configurations observed in the field. Monitoring devices, including moisture sensors, pressure transducers, and displacement sensors, recorded changes in soil moisture, stress, and deformation. A static treatment phase allowed natural crack development to simulate real-world conditions. Key findings revealed that shear failure propagated along pre-existing cracks and weak structural discontinuities, supporting the progressive failure theory in shallow sliding. Cracks significantly influenced water infiltration, creating localized stress concentrations and deformation. Atmospheric conditions and wet-dry cycles were crucial, as increased moisture content reduced soil suction and weakened the slope’s strength. These results enhance understanding of expansive soil slope failure mechanisms and provide a theoretical foundation for developing improved stabilization techniques. Full article

The dry conversion of CO₂ into CO and O₂ provides an attractive path for CO₂ utilization which allows for the use of the CO produced for the synthesis of valuable hydrocarbons. In the following work, the CO₂ conversion is driven by an arc discharge at atmospheric pressure, producing hot plasma. This study presents a series of experiments aiming to optimize the process. The results obtained include the energy efficiency and the conversion rate of the process, as well as the electrical parameters of the discharge (current and voltage signals). In addition, optical emission spectroscopy diagnostics based on an analysis of C₂’s Swan bands are used to determine the gas temperature in the discharge. The data is analyzed according to several aspects—an analysis of the arc’s motion based on the electrical signals; an analysis of the effect of the gas flow and the discharge current on the discharge performance for CO₂ conversion; and an analysis of the vibrational and rotational temperatures of the arc channel. The results show significant improvements over previous studies. Relatively high gas conversion and energy efficiency are achieved due to the arc acceleration caused by the Lorentz force. The rotational (gas) temperatures are in the order of 5500–6000 K. Full article

This study examines the complex interactions among soil moisture, evaporation, extreme weather events, and lightning, and their influence on fire activity across the extratropical and Pan-Arctic regions. Leveraging reanalysis and remote-sensing datasets from 2000 to 2020, we applied cross-correlation analysis, a modified Mann–Kendall trend test, and assessments of interannual variability to key variables including soil moisture, fire frequency and risk, evaporation, and lightning. Results indicate a significant increase in dry days (up to 40%) and heatwave events across Central Eurasia and Siberia (up to 50%) and Alaska (25%), when compared to the 1980–2000 baseline. Upward trends have been detected in evaporation across most of North America, consistent with soil moisture trends, while much of Eurasia exhibits declining soil moisture. Fire danger shows a strong positive correlation with evaporation north of 60° N (r ≈ 0.7, p ≤ 0.005), but a negative correlation in regions south of this latitude. These findings suggest that in mid-latitude ecosystems, fire activity is not solely driven by water stress or atmospheric dryness, highlighting the importance of region-specific surface–atmosphere interactions in shaping fire regimes. In North America, most fires occur in temperate grasslands, savannas, and shrublands (47%), whereas in Eurasia, approximately 55% of fires are concentrated in forests/taiga and temperate open biomes. The analysis also highlights that lightning-related fires are more prevalent in Eastern Europe and Southeastern Asia. In contrast, Western North America exhibits high fire incidence in temperate conifer forests despite relatively low lightning activity, indicating a dominant role of anthropogenic ignition. These findings underscore the importance of understanding land–atmosphere interactions in assessing fire risk. Integrating surface conditions, climate extremes, and ignition sources into fire prediction models is crucial for developing more effective wildfire prevention and management strategies. Full article

The conversion of CO₂ into CH₄ through the Sabatier reaction is one of the key processes that can reduce CO₂ emissions into the atmosphere. This work aims to develop Ni-Al aerogel-based thermo-photocatalysts with large specific surface areas prepared using a sol–gel method and subsequent supercritical drying in CO₂. Different Al/Ni molar ratios were selected for the development of the catalysts, characterized using ICP-OES, N₂ adsorption–desorption isotherms, XRD, H₂-TPR, TEM, UV-Vis DRS, and XPS techniques. Thermo-photocatalytic activity tests were performed in a photoreactor with two different light sources (λ = 365 nm, λ = 470 nm) at a temperature range from 300 °C to 450 °C and a pressure of 10 bar. The catalyst with the highest Ni loading (AG 1/3) produced the best catalytic results, reaching CO₂ conversion and CH₄ selectivity levels of 82% and 100%, respectively, under visible light at 450 °C. In contrast, the catalysts with the lowest nickel loading produced the lowest results, most likely due to their low amounts of active Ni. These results suggest that supercritical drying is an efficient method for developing active thermo-photocatalysts with high Ni dispersion, suitable for Sabatier reactions under mild reaction conditions. Full article

Satellite-based monitoring of atmospheric column-averaged dry-air mole fraction (XCH₄) is essential for quantifying methane (CH₄) emissions, yet uncharacterized spatially varying biases in XCH₄ observations can cause misattribution in flux estimates. This study assesses the potential of the upcoming TanSat-2 satellite mission to estimate China’s CH₄ emission using a series of Observing System Simulation Experiments (OSSEs) based on an Ensemble Kalman Filter (EnKF) inversion framework coupled with GEOS-Chem on a 0.5° × 0.625° grid, alongside an evaluation of current TROPOMI-based products against Total Carbon Column Observing Network (TCCON) observations. Assuming a target precision of 8 ppb, TanSat-2 could achieve an annual national emission estimate accuracy of 2.9% ± 4.2%, reducing prior uncertainty by 84%, with regional deviations below 5.0% across Northeast, Central, East, and Southwest China. In contrast, limited coverage in South China due to persistent cloud cover leads to a 26.1% discrepancy—also evident in pseudo TROPOMI OSSEs—highlighting the need for complementary ground-based monitoring strategies. Sensitivity analyses show that satellite retrieval biases strongly affect inversion robustness, reducing the accuracy in China’s total emission estimates by 5.8% for every 1 ppb increase in bias level across scenarios, particularly in Northeast, Central and East China. We recommend expanding ground-based XCH₄ observations in these regions to support the correction of satellite-derived biases and improve the reliability of satellite-constrained inversion results. Full article

This study investigated the enhancement in lipid accumulation in Chlorella sp. using non-thermal atmospheric pressure plasma as a pretreatment strategy for the production of value-added products. The plasma treatment was optimized by varying discharge times (0–16 min) using argon gas at a flow rate of 4 L/min. Lipid productivity was assessed through gravimetric analysis and profiling of fatty acid methyl ester using gas chromatography−mass spectrometry (GC-MS). The growth rate and pH of the treated cells were monitored. The findings demonstrated that the 4-min plasma exposure maximized the efficiency of lipid recovery, achieving a 35% of the dry cell weight and a 34.6% increase over untreated control. However, longer plasma treatment times resulted in a comparative decrease in lipid yield, as the decline is possibly due to oxidative degradation. The findings highlight the role of plasma treatment, which significantly boosts lipid yield and gives complementary optimization of downstream processes to improve biodiesel production. The accumulation of lipids in terms of size and volume in the algal cells was assessed by confocal laser scanning microscopy. The GC–MS results of the control revealed that lipids comprised primarily mixed esters such as 2H Pyran 2 carboxylic acid ethyl esters, accounting for 50.97% and 20.52% of the total peak area. In contrast, the 4-min treated sample shifted to saturated triacylglycerols (dodecanoic acid, 2,3 propanetriyl ester), comprising 85% of the total lipid content, which efficiently produced biodiesel. Thus, the non-thermal plasma-based enhancement of lipids in the algal cells has been achieved. Full article

The world’s energy demand increases daily, fostering the search for renewable fuels to reconcile production needs with environmental sustainability. To prevent the severe atmospheric impact of fossil fuels, reducing greenhouse gas emissions is both essential and urgent, reinforcing the necessity of developing and adopting renewable fuel alternatives. Therefore, this work aimed to produce bio-oil through sugarcane bagasse fast pyrolysis. The methodology is based on fast pyrolysis operation in a fluidized bed reactor (pilot plant) as a thermochemical method for bio-oil production. This research required the conditioning of the raw material for system feeding, along with optimizing key variables, operating temperature, airflow, and sugarcane bagasse feed rate, to achieve improved yields compared to previous studies conducted in this pilot plant. The sugarcane bagasse was conditioned through drying and milling, followed by characterization using various analytical methods, including calorific value, thermogravimetric analysis (TGA), particle size analysis by laser diffraction (Mastersizer—MS), and ultimate analysis (determining carbon, hydrogen, nitrogen, sulfur, and oxygen by difference). The bio-oil produced showed promising yield results, with a maximum estimated value of 61.64%. Fourier Transform Infrared Spectroscopy (FT-IR) analysis confirmed the presence of aromatic compounds, as well as ester, ether, carboxylic acid, ketone, and alcohol functional groups. Full article