Search Results (202)

To provide new insights into the integrated management of carbon and heat for sustainable urban development, this study systematically investigates the complex relationship between atmospheric CO₂ concentrations and land surface temperature (LST). Utilizing OCO-2 and OCO-3 satellite observations, combined with meteorological conditions, air pollutants, and spatial characteristics, a high-resolution (0.1° × 0.1°) monthly CO₂ column concentration (XCO₂) dataset for China spanning 2015 to 2022 was generated using the Random Forest algorithm. The study focuses on urban agglomerations, conducting centroid migration and coupling analyses of XCO₂ and LST to elucidate their spatiotemporal distribution patterns and evolution. Results reveal significant seasonal variations in XCO₂, which has exhibited a gradual increase over the years. The spatiotemporal distributions of XCO₂ and LST in urban agglomerations show a high degree of consistency, with centroids either converging or following similar movement trajectories. Additionally, the degree of coupling and coordination between XCO₂ and LST has improved annually, indicating a closer interrelationship. These findings enhance our understanding of climate system dynamics and provide essential scientific evidence and decision-making support for addressing climate change. By clarifying the connection between atmospheric CO₂ and LST, this study contributes to the development of more effective strategies for carbon reduction and urban heat island mitigation, thereby advancing cities towards greener, lower-carbon, and more sustainable development pathways. Full article

Remote sensing has proven to be a vital tool for monitoring and forecasting the quality and yield of crops. The utilization of innovative technologies such as Solar-Induced Fluorescence (SIF) and satellite measurements of column-averaged CO₂ (xCO₂) can enhance these estimations. SIF is a signal emitted by crops during photosynthesis, thus indicating photosynthetic activities. The concentration of atmospheric CO₂ is a critical factor in determining the efficiency of photosynthesis. The aim of this study was to investigate the correlation between satellite-derived Solar-Induced Chlorophyll Fluorescence (SIF), column-averaged CO₂ (xCO₂), and Normalized Difference Vegetation Index (NDVI) and their association with sugarcane yield and sugar content in the field. This study was carried out in south-central Brazil. We used four localities to represent the region: Pradópolis, Araraquara, Iracemápolis, and Quirinópolis. Data were collected from orbital systems during the period spanning from 2015 to 2016. Concurrently, monthly data regarding tons of sugarcane per hectare (TCH) and total recoverable sugars (TRS) were gathered from 24 harvest locations within the studied plots. It was observed that TRS decreased when SIF values ranged between 0.4 W m⁻² sr⁻¹ μm⁻¹ and 0.8 W m⁻² sr⁻¹ μm⁻¹, particularly in conjunction with NDVI values below 0.5. TRS values peaked at 15 kg t⁻¹ with low NDVI and xCO₂ values, alongside SIF values lower than 0.4 W m⁻² sr⁻¹ μm⁻¹ and greater than 1 W m⁻² sr⁻¹ μm⁻¹. These findings underscore the potential of integrating SIF, xCO₂, and NDVI measurements in the monitoring and forecasting of yield and sugar content in sugarcane crops. Full article

The vehicle-routing problem (VRP) is a popular area of research. This popularity springs from its wide application in many real-world problems, such as logistics, network routing, E-commerce, and various other fields. The VRP is simple to formulate, but very difficult to solve and requires a great deal of time. In these cases, researchers use approximate solutions offered by metaheuristics. This work involved the design of a new metaheuristic called Open Competency Optimization (OCO), which was inspired by human behavior during the learning process and based on the competency approach. The aim is the construction of solutions that represent learners’ ideas in the context of an open problem. The candidate solutions in OCO evolve over three steps. Concerning the first step, each learner builds a path of learning (finding the solution to the problem) through self-learning, which depends on their abilities. In the second step, each learner responds positively to the best ideas in their group (the construction of each group is based on the competency of the learners or the neighbor principle). In the last step, the learners interact with the best one in the group and with the leader. For the sake of proving the relevance of the proposed algorithm, OCO was tested in dynamic vehicle-routing problems along with the Generalized Dynamic Benchmark Generator (GDBG). Full article

Estimation of anthropogenic carbon dioxide (CO₂) emission sources and natural sinks (i.e., CO₂ fluxes) is essential for the development of climate policies. Satellite observations provide an opportunity for top-down inversion of CO₂ fluxes, which can be used to improve the results of bottom-up estimation. This study proposes to develop a new top-down CO₂ flux estimation method based on deep learning, as well as satellite observations, and an atmospheric chemical transport model. This method utilizes two deep learning models: the concentration correction model and the concentration–flux inversion model. The former optimizes the GEOS-Chem-simulated CO₂ concentration using Orbiting Carbon Observatory-2 (OCO-2) satellite observations, while the latter establishes the complicated relationship between CO₂ concentration and CO₂ flux. Results showed that both deep learning models demonstrated excellent prediction performance, with a mean bias of 0.461 ppm for the concentration correction model and an annual mean correlation coefficient of 0.920 for the concentration–flux inversion model. A posterior CO₂ flux was obtained through a two-step optimization process using these well-trained models. Our findings indicate that the posterior estimations of CO₂ flux sources in eastern China and northern Europe have been significantly reduced compared to the prior estimations. This study provides a new perspective on top-down CO₂ flux inversion using satellite observation. With advancements in deep learning algorithms and increased satellite observations, this method may become an effective approach for CO₂ flux inversion in the future. Full article

In the present work, the corrosion properties and the surface chemistry of a graphene oxide-coated AZ91D alloy were investigated. The coatings were deposited on the substrate specimens by immersion in solutions with GO concentrations of 0.05% and 0.1% (m/v). An intermediate silane layer was firstly obtained to improve adhesion between the GO films and the AZ91D substrate. The electrochemical behavior of the coated specimens was assessed using electrochemical impedance spectroscopy and potentiodynamic polarization curves in 3.5 wt.% NaCl solution. The surface chemistry was assessed using X-ray photoelectron spectroscopy (XPS). The GO films consisted of a mixture of carbon-based bonds (C-C, C-OH, C=O, and O-C=O). The surface morphology of the coated specimens was examined using scanning electron microscopy. The results revealed that the compactness of the GO films was dependent on the deposition conditions. The corrosion resistance was affected by the surface morphology. Full article

In this study, recycled carbon fibers (rCFs) recovered from waste carbon composites were used to manufacture wet-laid nonwoven fabrics. The aim was to improve dispersibility by investigating the changes in the dispersibility of carbon fibers (CFs) based on the content of the dispersant carboxymethyl cellulose (CMC) and the binder polyvinyl alcohol (PVA), and the length and basis weight of the CFs. In addition, the chemical property changes and oxygen functional group mechanisms based on the content of the CMC dispersant and PVA binder were investigated. The nonwoven fabrics made with desized CFs exhibited significantly improved dispersibility. For nonwoven fabrics produced with a fixed binder PVA content of 10%, optimal dispersibility was achieved at a dispersant CMC concentration of 0.4%. When the dispersant CMC concentration was fixed at 0.4% and the binder PVA content at 10%, the best dispersibility was observed at a CF length of 3 mm, while the maximum tensile strength was achieved at a fiber length of 6 mm. Dispersibility remained almost consistent across different basis weights. As the dispersant CMC concentration increased from 0.2% to 0.6%, the oxygen functional groups, such as carbonyl group (C=O), lactone group (O=C-O), and natrium hydroxide (NaOH), also increased. However, hydroxyl group (C-O) decreased. Moreover, the contact angle decreased, while the surface free energy increased. On the other hand, when the dispersant CMC concentration was fixed at 0.4%, the optimal binder PVA content was found to be 3%. As the binder PVA content increased from 0% to 10%, the formation of hydrogen bonds between the CMC dispersant and the PVA binder led to an increase in C=O and O=C-O bonds, while C-O and NaOH decreased. As the amount of oxygen increased, the contact angle decreased and the surface free energy increased. Full article

Transition metal oxides show high activity while still facing the challenges of low mineralization and poor durability in the ozone catalytic oxidation (OCO) of volatile organic compounds (VOCs). Improving the oxygen mobility and low-temperature reducibility of transition metal oxides was found to be an effective way to address the above challenges. Here, highly dispersed Ag was added to Mn₃O₄ via the co-precipitation oxalate route, and the obtained Ag/Mn₃O₄ exhibited higher mineralization and stability in benzene catalytic ozonation at room temperature. Compared to Mn₃O₄, the concentration of CO₂ formed from benzene oxidation over Ag/Mn₃O₄ was significantly increased, from 585.4 ppm to 810.9 ppm, while CO generation was greatly suppressed to only one tenth of its original value (194 ppm vs. 19 ppm). In addition, Ag/Mn₃O₄ exhibited higher catalytic stability than Mn₃O₄. The introduction of Ag obviously improved the oxygen mobility and low-temperature reducibility of Mn₃O₄. Moreover, the highly dispersed Ag also promoted the activity of surface oxygen species and the chemisorption of benzene on Mn₃O₄. The above physicochemical properties contributed to the excellent catalytic performance and durability of Ag/Mn₃O₄. This research could shed light on the improvement in VOC mineralization via ozone catalytic oxidation. Full article

A novel method for synthesizing dumbbell-shaped (Gd_1−xTb_x)₂O(CO₃)₂·H₂O (GOC:xTb³⁺) phosphors using sodium carbonate was investigated. An amount of 1 mmol of stable fluorescent powder can be widely prepared using 3–11 mmol of Na₂CO₃ at a pH value of 8.5–10.5 in the reaction solution. The optimal reaction conditions for the phosphors were determined to be 7 mmol for the amount of sodium carbonate and a pH of 9.5 in the solution. Mapping analysis of the elements confirmed uniform distribution of Gd³⁺ and Tb³⁺ elements in GOC:xTb³⁺. The analysis of fluorescence intensity shows that an optimal excitation wavelength of 273 nm is observed when the concentration of Tb³⁺ is between 0.005 and 0.3. The highest emission intensity was observed for GOC:0.05Tb³⁺ with a 57.5% maximum quantum efficiency. The chromaticity coordinates show that the color of GOC:Tb³⁺ is stable and suitable for fluorescence recognition. Latent fingerprint visualization reveals distinctive features like whorls, hooks, and bifurcations. Therefore, the sodium carbonate method offers an effective alternative to traditional urea chemical reaction conditions for preparing GOC:Tb³⁺. Full article

This study aims to study the formation quality of the film of dental silanes. Two dental silanes, 3-methacryloxyproyltrimethoxysilane (MPS) and 3-acryloyloxypropyltrimethoxysilane (ACPS), were deposited on the silica glass-equivalent model surface (i.e., n-type silicon(100) wafer) by varying the deposition time (5 h and 22 h). The film quality was then evaluated by ellipsometry, surface contact angle (CA) and surface free energy (SFE), atomic force microscopy (AFM) and X-ray photoelectron spectroscopy (XPS) in survey and high-resolution modes on Si2p, O1s and C1s. Ellipsometry confirmed that both silanes at the two different deposition times would produce 0.85–1.22 nm thick self-assembled monolayer on the silicon wafer surface. While the water CA of silanized surfaces (60.7–71.5°) was larger than the surface without silane (29.6°), the SFE values of all silanes (40.0–44.5 mN/m) were slightly less than that of the wafer surface (46.3 mN/m). AFM revealed that the MPS with 22 h silanization yielded a significantly higher roughness (0.597 μm) than other groups (0.254–0.297 μm). High-resolution XPS on C1s identified a prominent peak at 288.5 eV, which corresponds to methacrylate O-C*=O, i.e., the silane monolayer is extended fully in the vertical direction, while others are in defect states. This study proves that different dental silanes under various dipping times yield different chemical qualities of the film even if they look thin physically. Full article

Coupling solar-induced chlorophyll fluorescence (SIF) with gross primary productivity (GPP) for ecological function integration research presents numerous uncertainties, especially in ecologically fragile and climate-sensitive arid regions. Therefore, evaluating the suitability of SIF data for estimating GPP and the feasibility of improving its accuracy in the northern region of Xinjiang is of profound significance for revealing the spatial distribution patterns of GPP and the strong coupling relationship between GPP and SIF in arid regions, achieving the goal of “carbon neutrality” in arid regions. This study is based on multisource SIF satellite data and GPP observation data from sites in three typical ecosystems (cultivated and farmlands, pasture grasslands, and desert vegetation). Two precision improvement methods (canopy and linear) are used to couple multiple indicators to determine the suitability of multisource SIF data for GPP estimation and the operability of accuracy improvement methods in arid regions reveal the spatial characteristics of SIF (GPP). The results indicate the following. (1) The interannual variation of GPP shows an inverted “U” shape, with peaks values in June and July. The cultivated and farmland areas have the highest peak value among the sites (0.35 gC/m²/month). (2) The overall suitability ranking of multisource SIF satellite products for GPP estimation in arid regions is RTSIF > CSIF > SIF_OCO2_005 > GOSIF. RTSIF shows better suitability in the pasture grassland and cultivated and farmland areas (R² values of 0.85 and 0.84, respectively). (3) The canopy method is suitable for areas with a high leaf area proportion (R² improvement range: 0.05–0.06), while the linear method is applicable across different surface types (R² improvement range: 0.01–0.13). However, the improvement effect of the linear method is relatively weaker in areas with high vegetation cover. (4) Combining land use data, the overall improvement of SIF (GPP) is approximately 0.11%, and the peak values of its are mainly distributed in the northern and southern slopes of the Tianshan Mountains, while the low values are primarily found in the Gurbantunggut Desert. The annual mean value of SIF (GPP) is about 0.13 mW/m²/nm/sr. This paper elucidates the applicability of SIF for GPP estimation and the feasibility of improving its accuracy, laying the theoretical foundation for the spatiotemporal coupling study of GPP and SIF in an arid region, and providing practical evidence for achieving carbon neutrality goals. Full article

Plasma treatment of wood surfaces has shown significant effects, but different excitation methods used for different species of wood generally result in varied characteristics of wood surfaces. Secondly, plasma modification greatly enhances the absorption of liquids by wood, but the relationship between liquid absorption and surface wettability is rarely studied. Limited detailed investigation of the modification effects and mechanisms has hindered the large-scale applications of plasma treatment in the wood industry. In this study, two typical plasmas, radio frequency (RF) plasma and gliding arc discharge (GAD) plasma, were employed to treat three species of wood: poplar, black walnut, and sapele. By focusing on changes in the contact angle of the wood surface, an exponential equation fitting method is used to determine the measurement time for contact angles. The research identified that factors contributing to the decrease in contact angle after plasma modification include not only the increase in surface energy but also liquid absorption. SEM and XPS analyses demonstrate that plasma etching accelerated liquid absorption by modifying the surface topography, while the increase in surface energy was due to the addition of oxygen-containing groups. High-valence C=O and O-C=O groups serve as indicators of plasma-induced surface chemical reactions. RF modification primarily features surface etching, whereas GAD significantly increases the active surface groups. Thus, different plasmas, due to their distinct excitation modes, produce diverse modification effects on wood. Considering the various physical and chemical properties of plasma-modified wood surfaces, recommendations for adhesive use on plasma-modified wood are provided. Full article

Aerosol research is important for the protection of the ecological environment, the improvement of air quality, and as a response to climate change. In this study, a random forest (RF) estimation model of aerosol optical depth (AOD) and extinction coefficient vertical profiles was, respectively, established using Orbiting Carbon Observatory-2 (OCO-2) oxygen-A band (O₂ A-band) data from China and its surrounding areas in 2016, combined with geographical information (longitude, latitude, and elevation) and viewing angle data. To address the high number of OCO-2 O₂ A-band channels, principal component analysis (PCA) was employed for dimensionality reduction. The model was then applied to estimate the aerosol extinction coefficients for the region in 2017, and its validity was verified by comparing the estimated values with the Cloud-Aerosol Lidar Infrared Pathfinder Satellite Observations (CALIPSO) Level 2 extinction coefficients. In the comprehensive analysis of overall performance, an AOD model was initially constructed using variables, achieving a correlation coefficient (R) of 0.676. Subsequently, predictions for aerosol extinction coefficients were generated, revealing a satisfactory agreement between the predicted and the actual values in the vertical direction, with an R of 0.535 and a root mean square error (RMSE) of 0.107 km⁻¹. Of the four seasons of the year, the model performs best in autumn (R = 0.557), while its performance was relatively lower in summer (R = 0.442). Height had a significant effect on the model, with both R and RMSE decreasing as height increased. Furthermore, the accuracy of aerosol profile inversion shows a dependence on AOD, with a better accuracy when AOD is less than 0.3 and RMSE can be less than 0.06 km⁻¹. Full article

The regional differences in carbon dioxide (CO₂) variations from the Orbiting Carbon Observatory-2 (OCO-2) over the Beijing-Tianjin-Hebei (Jing-Jin-Ji) region from 2015 to 2021 are analyzed in this study. This study shows an annual increase and a seasonal cycle; the CO₂ annual growth rate was about 2.63 ppm year⁻¹, with the highest value being in spring and the lowest in summer. The spatial distribution is unbalanced, regional differences are prominent, and the CO₂ concentration is lower in the north of the Jing-Jin-Ji region (like Zhangjiakou, Chengde, and Qinhuangdao). Land-type structures and population economy distributions are the key factors affecting CO₂ concentration. By analyzing the land-type structures over Jing-Jin-Ji in 2020, we find that cropland, woodland, and grassland (CWG) are the main land cover types in Jing-Jin-Ji; the proportion of these three types is about 83.3%. The woodland areas in Zhangjiakou, Chengde, and Qinhuangdao account for about 65% of the total woodland areas in Jing-Jin-Ji; meanwhile, the grassland areas in these three regions account for 62% of the total grassland areas in Jing-Jin-Ji. CO₂ concentration variation shows a high negative correlation with CWG land areas (coefficient of determination (R²) > 0.76). The regions with lower population and GDP secondary industry (SI) density also have lower CO₂ concentration (like Zhangjiakou, Chengde, and Qinhuangdao), and the regions with higher population and GDP SI density also have higher CO₂ concentration (like the southeast of Jing-Jin-Jin). Full article

The spatial and temporal variations in the atmospheric CO₂ concentrations evidently respond to anthropogenic CO₂ emission activities. NO₂, a pollutant gas emitted from fossil fuel combustion, comes from the same emission sources as CO₂. Exploiting the simultaneous emissions characteristics of NO₂ and CO₂, we proposed an XCO₂ prediction approach to reconstruct XCO₂ data based on the data-driven machine learning algorithm using multiple predictors, including satellite observation of atmospheric NO₂, to resolve the issue of data gaps in satellite observation of XCO₂. The prediction model showed good predictive performance in revealing CO₂ concentrations in space and time, with a total deviation of 0.17 ± 1.17 ppm in the cross-validation and 1.03 ± 1.15 ppm compared to ground-based XCO₂ measurements. As a result, the introduction of NO₂ obtained better improvements in the CO₂ concentration responding to the anthropogenic emissions in space. The reconstructed XCO₂ data not only filled the gaps but also enhanced the signals of anthropogenic CO₂ emissions by using NO₂ data, as NO₂ strongly responds to anthropogenic CO₂ emissions (R² = 0.92). Moreover, the predicted XCO₂ data preferred to correct the abnormally low XCO₂ retrievals at satellite observing footprints, where the XCO₂_uncertainity field in the OCO-2 and OCO-3 products indicated a larger uncertainty in the inversion algorithm. Full article

Photoisomerizable molecules in liquid crystals (LCs) allow for photoinduced phase transitions, facilitating applications in a wide variety of photoresponsive materials. In contrast to the widely investigated azobenzene structure, research on the photoinduced phase-transition behavior of imine-based LCs is considerably limited. We herein report the thermal and photoinduced phase-transition behaviors of photoisomerizable imine-based LC dimers with twist–bend nematic (N_TB) phases. We synthesize two homologous series of ester- and thioether-linked N-(4-cyanobenzylidene)aniline-based bent-shaped LC dimers with an even number of carbon atoms (n = 2, 4, 6, 8, and 10) in the central alkylene spacers, namely, CBCOOnSBA(CN) and CBOCOnSBA(CN), possessing oppositely directed ester linkages, C=OO and OC=O, respectively. Their thermal phase-transition behavior is examined using polarizing optical microscopy and differential scanning calorimetry. All dimers form a monotropic N_TB phase below the temperature of the conventional nematic (N) phase upon cooling. Remarkably, the N_TB phases of CBCOOnSBA(CN) (n = 2, 4, 6, and 8) and CBOCOnSBA(CN) (n = 6 and 8) supercool to room temperature and vitrify without crystallization. In addition, the phase-transition temperatures and entropy changes of CBCOOnSBA(CN) are lower than those of CBOCOnSBA(CN) at the same n. Under UV light irradiation, the N_TB and N phases transition to the N and isotropic phases, respectively, and reversibly return to their initial LC phases when the UV light is turned off. Full article