Search Results (234)

Transient increments of X-ray radiation and extreme ultraviolet (EUV) during solar flares are strong drivers of thermospheric dynamics on Mars, yet their class-dependent impacts remain poorly measured. This work provides the first direct, side-by-side study of Martian thermospheric reactions to flares X8.2 on 10 September 2017 and M6.0 on 17 September 2017. This study shows nonlinear, class-dependent effects, compositional changes, and recovery processes not recorded in previous investigations. Species-specific responses deviated significantly from irradiance proportionality, even though the soft X-ray flux in the X8.2 flare was 13 times greater. Argon (Ar) concentrations rose 3.28× (compared to 1.13× for M6.0), and radiative cooling led CO₂ heating to approach a halt at ΔT = +40 K (X8.2) against +19 K (M6.0) at exobase altitudes (196–259 km). N₂ showed the largest class difference, where temperatures rose by +126 K (X8.2) instead of +19 K (M6.0), therefore displaying flare-magnitude dependent thermal sensitivity. The 1.95× increase in O concentrations during X8.2 and the subsequent decrease following M6.0 (−39 K cooling) illustrate the contradiction between photochemical production and radiative loss. The O/CO₂ ratio at 225 km dropped 46% during X8.2, revealing compositional gradients boosted by flares. Recovery timeframes varied by class; CO₂ quickly re-equilibrated because of effective cooling, whereas inert species (Ar, N₂) stabilized within 1–2 orbits after M6.0 but needed >10 orbits of the MAVEN satellite after the X8.2 flare. The observations of the X8.2 flare came from the western limb of the Sun, but the M6.0 flare happened on the far side. The CME shock was the primary driver of Mars’ EUV reaction. These findings provide additional information on atmospheric loss and planetary habitability by indicating that Mars’ thermosphere has a saturation threshold where strong flares induce nonlinear energy partitioning that encourages the departure of lighter species. Full article

The introduction of the ”dual carbon” target has increased the need for products that can accurately measure carbon dioxide levels, reflecting the rising demand. Due to challenges in achieving the required spatiotemporal resolution, accuracy, and spatial continuity with current carbon dioxide concentration products, it is essential to explore methods for obtaining carbon dioxide concentration products with completeness in space and time. Based on the 2018 OCO-2 carbon dioxide products and environmental variables such as vegetation coverage (FVC, LAI), net primary productivity (NPP), relative humidity (RH), evapotranspiration (ET), temperature (T) and wind (U, V), this study constructed a multiple regression model to obtain the spatial continuous carbon dioxide concentration products in the provinces of Huai River Basin. Using indicators such as correlation coefficient, root mean square error (RMSE), local variance, and percentage of valid pixels, the performance of model was validated. The validation results are shown as follows: (1) Among the selected environmental variables, the primary factors affecting the spatiotemporal distribution of carbon dioxide concentration are ET, LAI, FVC, NPP, T, U, and RH. (2) Compared with the OCO-2 carbon dioxide products, the percentage of valid pixels of the reconstructed carbon dioxide concentration data increased from less than 1% to over 90%. (3) The local variance in reconstructed data was significantly larger than that of original OCO-2 ${\mathrm{C}\mathrm{O}}_2$ products. (4) The average monthly RMSE is 2.69. Therefore, according to the model developed in this study, we can obtain a carbon dioxide concentration dataset that is spatially complete, meets precision requirements, and is rich in local detail information, which can better reflect the spatial pattern of carbon dioxide concentration and can be used to examine the carbon cycle between the terrestrial environment, biosphere, and atmosphere. Full article

Fenton oxidation can contribute to meeting effluent standards for COD in actual wastewater treatment plant effluents. However, Fenton oxidation is prone to produce iron sludge waste. The application of heterogeneous Fenton-like systems based on Fenton iron mud carbon in wastewater treatment plants is essential for Fenton iron mud reduction and recycling. In this study, a Fenton iron mud carbon catalyst/Ferrate salts/H₂O₂ (FSC/Fe(VI)/H₂O₂) system was developed to remove chemical oxygen demand (COD) from secondary effluents at the pilot scale. The results showed that the FSC/Fe(VI)/H₂O₂ system exhibited excellent COD removal performance with a removal rate of 57% under slightly neutral conditions in laboratory experiments. In addition, the effluent COD was stabilized below 40 mg·L⁻¹ for 65 days at the pilot scale. Fe(IV) and ¹O₂ were confirmed to be the main active species in the degradation process through electron paramagnetic resonance (EPR) and quenching experiments. C=O, O-C=O, N sites and Fe⁰ were responsible for the generation of Fe(IV) and ¹O₂ in the FSC/Fe(VI)/H₂O₂ system. Furthermore, the cost per ton of water treated by the pilot-scale FSC/Fe(VI)/H₂O₂ system was calculated to be only 0.6209 USD/t, further confirming the application potential of the FSC/Fe(VI)/H₂O₂ system. This study promotes the engineering application of heterogeneous Fenton-like systems for water treatment. Full article

Cities house more than half of the world’s population and are responsible for more than 70% of the world anthropogenic CO₂ emissions. Therefore, quantifications of emissions from major cities, which are only less than a hundred intense emitting spots across the globe, should allow us to monitor changes in global fossil fuel CO₂ emissions in an independent, objective way. The study adopted a high-spatiotemporal-resolution regional assimilation method using satellite observation data and atmospheric transport model WRF-Chem/DART to assimilate CO₂ concentration and fluxes in Lisbon, a major city in Portugal. It is based on Zhang’s assimilation method, combined OCO-2 XCO₂ retrieval data, ODIAC 1 km anthropogenic CO₂ emissions and Ensemble Adjustment Kalman Filter Assimilation. By employing three two-way nested domains in WRF-Chem, we refined the spatial resolution of the CO₂ concentrations and fluxes over Lisbon to 3 km. The spatiotemporal distribution characteristics and main driving factors of CO₂ concentrations and fluxes in Lisbon and its surrounding cities and countries were analyzed in March 2020, during the period affected by COVID-19 pandemic. The results showed that the monthly average CO₂ and XCO₂ concentrations in Lisbon were 420.66 ppm and 413.88 ppm, respectively, and the total flux was 0.50 Tg CO₂. From a wider perspective, the findings provide a scientific foundation for urban carbon emission management and policy-making. Full article

Air stability caused by the H₂O/CO₂ reaction at the layered oxide NaTMO₂ surface is one of the main obstacles to commercializing sodium-ion batteries (SIBS). The H₂O and CO₂ adsorption properties on the (100) surface of sodium layered transition metal oxide NaTMO₂ (TM = Co, Ni, Mo, Nd) are calculated using the DFT method to study the surface air stability. This study showed that the material bulk phase (symmetry), surface site, element type, and surface termination are all (though not the only) important factors that affect the adsorption strength. Contrary to previous studies, the P phase is not always more air-stable than the O phase; our calculations showed that the NaNiO₂ O phase is more stable than the P phase. The calculated band center and occupation showed a direct relationship with the adsorption energy. The Na site adsorption for CO₂ and H₂O showed the same V-shape trend. However, the TM adsorption for CO₂ and H₂O showed a different trend. With an increased t₂g band center, CO₂ adsorption strength increases. There is no clear trend for H₂O adsorption. Our calculations showed that the electronic structure of the surface atomic of adsorption site plays a decisive role in CO₂ and H₂O adsorption strength. This study demonstrated an effective method for obtaining a stability parameter regarding the electronic structure, which can be used to screen the air-stable layered oxide sodium cathode in the future. Full article

The Orbiting Carbon Observatory-3 (OCO-3) mission provides a new perspective for studying atmospheric carbon dioxide (CO₂). Here we assess the potentiality of OCO-3 satellite acquisitions to analyse and monitor the CO₂ emissions from Mt. Etna volcano. While OCO-3 data are well-suited for gas analysis on a regional spatial scale, they have not yet been widely utilised for studying volcanic carbon dioxide emissions. The Snapshot Area Map (SAM) acquisition mode enables the capture of targeted snapshots over volcanic regions, allowing for the measurement of CO₂ concentrations in the vicinity of volcanic structures. In this work, we analyse 62 OCO-3 images acquired between 2020 and 2023, focusing on measurements within a 20 km radius of Mt. Etna’s summit, where the main craters are located. Atmospheric CO₂ concentrations are examined as a function of distance from the summit, and assuming a linear decreasing trend, the angular coefficient is computed. Lower angular coefficient values may indicate a stronger volcanic CO₂ contribution. Considering both the number of sampled pixels in each OCO-3 snapshot and the associated uncertainties in the angular coefficient calculation, we identify five days with potentially significant CO₂ emissions from Mt. Etna, likely associated with specific volcanic activity phases. The eruptive activity on these five days is further investigated, revealing a possible correlation between elevated gas emissions and intense volcanic phenomena, such as lava fountains. This assessment is supported by thermal activity analyses using SEVIRI, MODIS, and VIIRS satellite data. Full article

The increase in the carbon dioxide (CO₂) concentration is a major driver of global warming, presenting significant challenges to ecosystems and human societies. Satellite remote sensing technology can monitor the continuous spatial variation of the atmospheric CO₂ column concentration (XCO₂), but its global application is limited by the narrow observational swath. To address this, this study effectively integrates XCO₂ data retrieved from the GOSAT and OCO-2 satellites using atmospheric profile adjustment and spatial grid integration techniques. Based on this, a multi-machine learning ensemble algorithm (MLE) was developed, which successfully estimated the spatially continuous XCO₂ concentration in China from 2010 to 2022 (ChinaXCO₂-MLE). The results indicate that, compared to individual satellite observations, the integration of multi-source satellite XCO₂ data significantly improves the spatiotemporal coverage. The overall R² of the MLE model was 0.97, with an RMSE of 0.87 ppmv, outperforming single machine learning models. The ChinaXCO₂-MLE shows good consistency with the observational records from two background stations in China, with R² values of 0.93 and 0.78, and corresponding RMSEs of 1.00 ppmv and 1.32 ppmv. This study also reveals the seasonal and regional variations in China’s XCO₂ concentration: the highest concentration occurs in spring, the lowest concentration occurs in northern regions during summer, and the lowest concentration occurs in southern regions during autumn. From 2010 to 2022, the XCO₂ concentration continued to rise, but the growth rate has slowed due to the implementation of air pollution prevention and energy conservation policies. The spatially continuous XCO₂ data provide a more comprehensive understanding of carbon variation and offer a valuable reference for achieving China’s carbon neutrality goals. Full article

The Cuyu gold deposit in central Jilin Province in Northeast China is located in the eastern segment of the northern margin of the North China Craton (NCC), as well as the eastern segment of the Xing’an–Mongolian Orogenic Belt (XMOB). Gold ore-bodies are controlled by NW-trending faults and mainly occur in late Hercynian granodiorite. The mineralization process in the Cuyu deposit can be divided into three stages: quartz + coarse grained arsenopyrite + pyrite (stage I), quartz + sericite + pyrite + arsenopyrite + electrum + chalcopyrite + sphalerite (stage II), and quartz + calcite ± pyrite (stage III). Stage II is the most important for gold mineralization. We conducted analyses including petrography, microthermometry, laser Raman spectroscopy of fluid inclusions, and H–O–S–Pb isotopic analysis to elucidate the mineralization processes in the Cuyu deposit. Five types of primary fluid inclusions (FIs) are present in the hydrothermal quartz and calcite grains of the ore: liquid-rich two-phase aqueous fluid inclusions (L-type), vapor-rich two-phase aqueous fluid inclusions (V-type), CO₂-bearing two- or three-phase inclusions (C1-type), CO₂-rich two- or three-phase inclusions (C2-type), and pure CO₂ mono-phase inclusions (C3-type). From stages I to III, the fluid inclusion assemblages changed from L-, C2-, and C3-types to L-, V-, C1-, C2-, and C3-types and, finally, to L-types only. The corresponding homogenization temperatures for stages I to III were 242–326 °C, 202–298 °C, and 106–188 °C, and the salinities were 4.69–9.73, 1.63–7.30, and 1.39–3.53 wt.% NaCl equiv., respectively. The ore-forming fluid system evolved from a NaCl-H₂O-CO₂ ± CH₄ ± H₂S fluid system in stage I and II with immiscible characteristics to a homogeneous NaC-H₂O fluid system in stage III. Microthermometric data for stages I to III show a decreasing trend in homogenization temperatures and salinities. The mineral assemblages, fluid inclusions, and H–O–S–Pb isotopes indicate that the initial ore-forming fluids of stage I were exsolved from diorite porphyrite and characterized by a high temperature and low salinity. The addition of meteoric water in large quantities led to decreases in temperature and pressure, resulting in a NaCl-H₂O-CO₂ ± CH₄ ± H₂S fluid system with significant immiscibility in stage II, facilitating the deposition of gold and associated polymetallic sulfides. The Cuyu gold deposit has a similar ore genesis to those of gold deposits in the Jiapigou–Haigou gold belt (JHGB) of southeastern Jilin Province indicating potential for gold prospecting in the northwest-trending seam of the JHGB. Full article

To comparatively study the effects of cold plasma activation and chemical treatment on the adsorption capacities of biomass carbon nanofiber membranes (BCNMs), microcrystalline cellulose (MCC) and chitosan (CS) were used to fabricate porous BCNMs by electrospinning and carbonization. Two modification methods, including oxygen (O₂) plasma activation and chemical treatment using nitric acid (HNO₃), sulfuric acid (H₂SO₄), hydrogen peroxide (H₂O₂), and urea, were further employed to enhance their adsorption performance. Various carbonyl group (C=O), ether bond (C-O), carboxyl group (O-C=O) and pyridinic nitrogen (N), pyrrolic N, and quaternary N functional groups were successfully introduced onto the surface of the BCNMs by the two methods. The BCNM-O₂ showed optimal formaldehyde absorption capacity (120.67 mg g⁻¹), corresponding to its highest contents of N, O-containing functional groups, and intact network structure. However, chemical treatment in strong acid or oxidative solutions destructed the microporous structures and changed the size uniformity of fibers in the BCNMs, resulting in a decline in formaldehyde adsorption capacity. A synergistically physical–chemical adsorption took place during formaldehyde adsorption by the modified biomass nanofiber membranes, due to the coexistence of suitable functional groups and porous structures in the membranes. Full article

In this study, a microwave-assisted sulfuric acid recovery method is proposed for the efficient recovery of high-value carbon fibers at 100–140 °C. The recycled carbon fibers (RCF) were characterized, and recycled carbon fiber-reinforced plastics (RCFRP) were fabricated using their fibers. The recycling process preserved the surface morphology of the carbon fibers, with the RCF maintaining the axial groove structure on the surface of the virgin carbon fiber (VCF). X-ray diffraction (XRD) and Raman spectroscopy analyses confirmed that the degree of graphitization and crystalline structure of the RCF remained largely unchanged compared to the original carbon fibers. Surface oxidation occurred during the recycling process, leading to an increase in O–C=O content on the surface of the RCF compared to that of the VCF, which facilitated interfacial chemical bonding with the resin and enhanced the wettability. Compared to virgin carbon fiber-reinforced plastics (VCFRP), RCFRP retained up to 95.25% of the tensile strength, 97.47% of the shear strength, and 96.76% of the bending stress, demonstrating excellent mechanical properties. This study provides a simple and effective approach for the low-temperature and high-efficiency recycling of carbon fiber composites. Full article

The Mongolian Plateau plays a crucial role in global carbon cycling, but the spatiotemporal characteristics of XCO₂ concentration and its driving mechanism remain insufficiently explored. To solve this scientific issue, the synergistic methodology of mathematical statistics—the Pearson correlation and random forest model—was established using the main source of Orbiting Carbon Observatory 2 (OCO-2) satellite data. Results indicate the following: (1) Average XCO₂ concentration of the Mongolian Plateau was 412 ppm, with an annual growth rate of 2.29 ppm/a from 2018 to 2022, along with higher values in the south and lower values in the north. The seasonal change displayed a clear temporal feature, in the order of spring (414.83 ppm) > winter (413.4 ppm) > autumn (411.3 ppm) > summer (409.12 ppm). The spatial distributions in spring, autumn, and winter were relatively consistent, all showing higher XCO₂ concentrations in the east and lower concentrations in the west, whereas summer exhibited the opposite pattern. (2) From the perspective of the natural environment, XCO₂ change was negatively correlated with the normalized difference vegetation index (NDVI), precipitation (PRE), and temperature (TEMP). Temporal analysis further revealed that this negative correlation was most pronounced in the eastern region, in which these three elements were all relatively high. (3) According to the random forest model, the influence of both single and interactive factors on the plateau’s XCO₂ varied significantly. A comparison of driving factors revealed that the NDVI had the highest contribution rate (0.35), followed by fossil fuel combustion emissions (ODIAC), wind direction (WD), and wind speed (WS). As for interaction effects, the combination of NDVI and ODIAC showed the highest contribution rate (over 0.25), indicating a strong joint influence on XCO₂. Other important interactions included WS and WD, ODIAC and WS, and NDVI and WS (all above 0.05). These findings provide valuable insights into the driving mechanisms of XCO₂ on the Mongolian Plateau, offering a reference for regional carbon emission reduction policies. Full article

Climate change poses a global threat, affecting both biodiversity and human populations. To implement efficient mitigating strategies, the consistency and accuracy of our monitoring of greenhouse gases at the local level must be improved. We can achieve this with more advanced monitoring instruments or an enhancement of our processing techniques, which will in turn improve data attributes such as spatial or temporal resolutions and accuracy. This paper presents a daily high spatial resolution XCO₂ dataset aiming to help monitor atmospheric CO₂ concentration on a global scale at a greater level of detail compared with existing datasets. Using a super resolution deep learning model, we increase the resolution of the OCO-2-derived dataset from 0.5° × 0.625° to 0.03° × 0.04° and show that our product maintains the quality of the original dataset while consistently improving the detail of the atmospheric pollution field. We conduct a benchmark that highlights how our dataset outperforms similar products and present a use case of CO₂ monitoring at the regional level. In conclusion, this work provides a complementary approach to the area of global continuous dataset reconstruction and focuses on the adjacent problem of improving specific features of existing datasets. Full article

Global warming caused by the increase in the atmospheric CO₂ content has become a focal environmental issue of common concern to the international community. As a key resource support for achieving the “dual carbon” goals in Western China, Sichuan Province requires a deep analysis of its carbon sources, carbon sinks, and its characteristics in terms of atmospheric environmental capacity, which is of great significance for formulating effective regional sustainable development strategies and responding to global climate change. In view of the unique geographical and climatic conditions in Sichuan Province and the current situation of a low and uneven distribution of atmospheric environmental capacity, this paper uses three forms of multi-source satellite data, OCO-2, OCO-3, and GOSAT, combined with other auxiliary data, to generate a daily XCO₂ concentration dataset with a spatial resolution of a 1km grid in Sichuan Province from 2015 to 2022. Based on the Optuna optimization method with 10-fold cross-validation, the optimal hyperparameter configuration of the four base learners of Stacking, random forest, gradient boosting decision tree, extreme gradient boosting, and the K nearest neighbor algorithm is searched for; finally, the logistic regression algorithm is used as the second-layer meta-learner to effectively improve the prediction accuracy and generalization ability of the Stacking ensemble learning model. According to the comparison of the performance of each model by cross-validation and TCCON site verification, the Stacking model significantly improved in accuracy, with an R², RMSE, and MAE of 0.983, 0.87 ppm and 0.19 ppm, respectively, which is better than those of traditional models such as RF, KNN, XGBoost, and GBRT. The accuracy verification of the atmospheric XCO₂ data estimated by the model based on the observation data of the two TCCON stations in Xianghe and Hefei showed that the correlation coefficients were 0.96 and 0.98, and the MAEs were 0.657 ppm and 0.639 ppm, respectively, further verifying the high accuracy and reliability of the model. At the same time, the fusion of multi-source satellite data significantly improved the spatial coverage of XCO₂ concentration data in Sichuan Province, effectively filling the gap in single satellite observation data. Based on the reconstructed XCO₂ dataset of Sichuan Province, the study revealed that there are significant regional and seasonal differences in the XCO₂ concentrations in the region, showing seasonal variation characteristics of being higher in spring and winter and lower in summer and autumn; in terms of the spatial distribution, the overall spatial distribution characteristics are high in the east and low in the west. This study helps to deepen our understanding of the carbon cycle and climate change, and can provide a scientific basis and risk assessment methods for policy formulation, effect evaluation, and international cooperation. Full article

In the present research, laser circle welding (LCW) was proposed to join dual-phase steel (DP980) and carbon fiber-reinforced plastic (CFRP). The welding appearance, cross-section of the welded joint and fracture surfaces were subjected to multi-scale characterizations. Joining strength was evaluated by the single-lap shear test. Moreover, a numerical model was established based on the in-house finite element (FE) code JWRIAN-Hybrid to reproduce the thermal process of LCW. The results showed that successful bonding was achieved with a laser power higher than 300 W. The largest joining strength increased to about 1353.2 N (12.2 MPa) with 450 W laser power and then decreased under higher heat input. While the welded joint always presented brittle fracture, the joining zone could be divided into a squeezed zone (SZ), molten zone (MZ) and decomposition zone (DZ). The morphology of CFRP and chemical bonding information were distinct in each subregion. The chemical reaction between the O-C=O bond on the CFRP surface and the -OH bond on the DP980 sheet provided the joining force between dissimilar materials. Additionally, the developed FE model was effective in predicting the interfacial maximum temperature distribution of LCW. The influence of laser power on the joining strength of LCW joints was dualistic in character. The joining strength variation reflected the competitive result between joining zone expansion and local bonding quality change. Full article

The development of carbonaceous materials such as biochar has triggered a hot spot in materials application. In this study, a new type of char carbon was developed from raw cigarette filter rods (CFRs) via a carbonization process under moderate conditions (T = 550 °C; t_res = 1 h) (CFR char carbon). The produced char was characterized by ATR-FTIR (Attenuated total reflectance—Fourier-transform infrared) spectroscopy, XRD (X-ray diffraction) analysis, GC-MS (Gas Chromatography–Mass Spectrometry), FESEM-EDS (Field-Emission Scanning Electron Microscopy—Energy-dispersive X-ray spectroscopy) technique, XPS (X-ray photoelectron spectroscopy), and N₂ adsorption/desorption (BET) measurements. The obtained carbon material is rich in oxygen-containing functional groups (i.e., C=O, C–O, –C(=O)–CH₃, C–O–C, C–OH, and O=C–O, with chemisorbed oxygen), containing significant amounts of calcium (that originates from CaCO₃) and silicon (Si), generated by reduction of SiO₂. It was found that the formation of char(C)/n-alkane composite material makes that CFR char have a high compressive strength improvement. Moderate carbonization has contributed to the creation of such material that has a fairly high specific surface area (320.93 m²/g), exhibiting a complex hierarchical structure that was characterized by composite Type I/IV(a) isotherm, associated with micro-/mesoporous carbon material. In addition, more directional extensions of this research for future work were proposed, including the implementation of electrochemical research. Full article