Search Results (20,340)

Based on the panel data of daily meteorological stations and winter wheat yield in Henan Province from 2000 to 2023, this study comprehensively used the Mann–Kendall trend test, wavelet coherence analysis (WTC), and other methods to reveal the temporal and spatial evolution of extreme precipitation and its multi-scale stress mechanism on grain yield. The results showed the following: (1) Extreme precipitation showed the characteristics of ‘frequent fluctuation-gentle trend-strong spatial heterogeneity’, and the maximum daily precipitation in spring (RX1DAY) showed a significant uplift. The increase in rainstorm events (R95p/R99p) in the southern region during the summer is particularly prominent; at the same time, the number of consecutive drought days (CDDs > 15 d) in the middle of autumn was significantly prolonged. It was also found that 2010 is a significant mutation node. Since then, the synergistic effect of ‘increasing drought days–increasing rainstorm frequency’ has begun to appear, and the short-period coherence of super-strong precipitation (R99p) has risen to more than 0.8. (2) The spatial pattern of winter wheat in Henan is characterized by the three-level differentiation of ‘stable core area, sensitive transition zone and shrinking suburban area’, and the stability of winter wheat has improved but there are still local risks. (3) There is a multi-scale stress mechanism of extreme precipitation on winter wheat yield. The long-period (4–8 years) drought and flood events drive the system risk through a 1–2-year lag effect (short-period (0.5–2 years) medium rainstorm intensity directly impacted the production system). This study proposes a ‘sub-scale governance’ strategy, using a 1–2-year lag window to establish a rainstorm warning mechanism, and optimizing drainage facilities for high-risk areas of floods in the south to improve the climate resilience of the agricultural system against the background of climate change. Full article

This study investigates the production and economic feasibility of biochar for smallholder and family farms in Central Amazonia, with potential implications for other tropical regions. The costs of construction of a prototype mobile kiln and biochar production were evaluated, using small-sized biomass from acai (Euterpe oleracea Mart.) agro-industrial residues as feedstock. The biochar produced was characterised in terms of its liming capacity (calcium carbonate equivalence, CaCO_3eq), nutrient content via organic fertilisation methods, and ash analysis by ICP-OES. Field trials with cowpea assessed economic outcomes, as well scenarios of fractional biochar application and cost comparison between biochar production in the prototype kiln and a traditional earth-brick kiln. The prototype kiln showed production costs of USD 0.87–2.06 kg⁻¹, whereas traditional kiln significantly reduced costs (USD 0.03–0.08 kg⁻¹). Biochar application alone increased cowpea revenue by 34%, while combining biochar and lime raised cowpea revenues by up to 84.6%. Owing to high input costs and the low value of the crop, the control treatment generated greater net revenue compared to treatments using lime alone. Moreover, biochar produced in traditional kilns provided a 94% increase in net revenue compared to liming. The estimated externalities indicated that carbon credits represented the most significant potential source of income (USD 2217 ha⁻¹). Finally, fractional biochar application in ten years can retain over 97% of soil carbon content, demonstrating potential for sustainable agriculture and carbon sequestration and a potential further motivation for farmers if integrated into carbon markets. Public policies and technological adaptations are essential for facilitating biochar adoption by small-scale tropical farmers. Full article

In the casting and rolling production process, surface longitudinal cracks are a typical casting defect. Tracing the causes of longitudinal cracks online and controlling the key parameters leading to their formation in a timely manner can enhance the stability of casting and rolling production. To this end, the influencing factors of longitudinal cracks were analyzed, a data integration storage platform was constructed, and a tracing model was established using empirical rule analysis, statistical analysis, and intelligent analysis methods. During the initial production phase of a casting machine, longitudinal cracks occurred frequently. The tracing results using the LightGBM-SHAP method showed that the relative influence of the narrow left wide inner heat flow ratio of the mold was significant, followed by the heat flow difference on the wide symmetrical face of the mold and the superheat of the molten steel, with weights of 0.135, 0.066, and 0.048, respectively. Based on the tracing results, we implemented online emergency measures. By controlling the cooling intensity of the mold, we effectively reduced the recurrence rate of longitudinal cracks. Root cause analysis revealed that the total hardness of the mold-cooling water exceeded the standard, reaching 24 mg/L, which caused scaling on the mold copper plates and uneven cooling, leading to the frequent occurrence of longitudinal cracks. After strictly controlling the water quality, the issue of longitudinal cracks was brought under control. The online application of the tracing method for the causes of longitudinal cracks has effectively improved efficiency in resolving longitudinal crack problems. Full article

Adulteration detection in medicinal plant powders remains a critical challenge in quality control. In this study, we propose a hyperspectral imaging (HSI)-based method combined with deep learning models to quantitatively analyze adulteration levels in Anoectochilus roxburghii powder. After preprocessing the spectral data using raw, first-order, and second-order Savitzky–Golay derivatives, we systematically evaluated the performance of traditional machine learning models (Random Forest, Support Vector Regression, Partial Least Squares Regression) and deep learning architectures. While traditional models achieved reasonable accuracy (R² up to 0.885), their performance was limited by feature extraction and generalization ability. A single-channel convolutional neural network (CNN) utilizing individual spectral representations improved performance marginally (maximum R² = 0.882), but still failed to fully capture the multi-scale spectral features. To overcome this, we developed a multi-channel CNN that simultaneously integrates raw, SG-1, and SG-2 spectra, effectively leveraging complementary spectral information. This architecture achieved a significantly higher prediction accuracy (R² = 0.964, MSE = 0.005), demonstrating superior robustness and generalization. The findings highlight the potential of multi-channel deep learning models in enhancing quantitative adulteration detection and ensuring the authenticity of herbal products. Full article

Accurate estimation of actual evapotranspiration (ET) is critical for understanding hydrothermal cycles and ecosystem functioning in arid regions, where water scarcity governs ecological resilience. To address persistent gaps in ET quantification, this study integrates multi-source remote sensing data, energy balance modeling, and ground-based validation that significantly enhances spatiotemporal ET accuracy in the vulnerable desert steppe ecosystems. The study utilized meteorological data from several national stations and Landsat-8 imagery to process monthly remote sensing images in 2019. The Surface Energy Balance System (SEBS) model, chosen for its ability to estimate ET over large areas, was applied to derive modeled daily ET values, which were validated by a large-weighted lysimeter. It was shown that ET varied seasonally, peaking in July at 6.40 mm/day, and reaching a minimum value in winter with 1.83 mm/day in December. ET was significantly higher in southern regions compared to central and northern areas. SEBS-derived ET showed strong agreement with lysimeter measurements, with a mean relative error of 4.30%, which also consistently outperformed MOD16A2 ET products in accuracy. This spatial heterogeneity was driven by greater vegetation coverage and enhanced precipitation in the southeast. The steppe ET showed a strong positive correlation with surface temperatures and vegetation density. Moreover, the precipitation gradients and land use were primary controllers of spatial ET patterns. The process-based SEBS frameworks demonstrate dual functionality as resource-optimized computational platforms while enabling multi-scale quantification of ET spatiotemporal heterogeneity; it was therefore a reliable tool for ecohydrological assessments in an arid steppe, providing critical insights for water resource management and drought monitoring. Full article

This study aimed to evaluate solid-state fermentation (SSF) as a sustainable approach for the simultaneous detoxification of olive pomace (OP) and the production of industrially relevant enzymes. OP, a semisolid byproduct of olive oil extraction, is rich in lignocellulose and phenolic compounds, which limit its direct reuse due to phytotoxicity. A native strain of Aspergillus sp., isolated from OP, was employed as the biological agent, while grape pomace (GP) was added as a co-substrate to enhance substrate structure. Fermentations were conducted at two scales, Petri dishes (20 g) and a fixed-bed bioreactor (FBR, 2 kg), under controlled conditions (25 °C, 7 days). Key parameters monitored included dry and wet weight loss, pH, color, phenolic content, and enzymatic activity. Significant reductions in color and polyphenol content were achieved, reaching 68% in Petri dishes and 88.1% in the FBR, respectively. In the FBR, simultaneous monitoring of dry and wet weight loss enabled the estimation of fungal biotransformation, revealing a hysteresis phenomenon not previously reported in SSF studies. Enzymes such as xylanase, endopolygalacturonase, cellulase, and tannase exhibited peak activities between 150 and 180 h, with maximum values of 424.6 U·g⁻¹, 153.6 U·g⁻¹, 67.43 U·g⁻¹, and 6.72 U·g⁻¹, respectively. The experimental data for weight loss, enzyme production, and phenolic reduction were accurately described by logistic and first-order models. These findings demonstrate the high metabolic efficiency of the fungal isolate under SSF conditions and support the feasibility of scaling up this process. The proposed strategy offers a low-cost and sustainable solution for OP valorization, aligning with circular economy principles by transforming agro-industrial residues into valuable bioproducts. Full article

The application of satellite-derived sea surface temperature in coastal regions is critical for resolving the dynamics of frontal features and coastal upwelling. Here, we examine and compare sea surface temperature (SST) gradients derived from two satellite products, the Multi-Scale Ultra-High Resolution SST Product (MUR, 0.01° grid scale) and the Operational SST and Ice Analysis (OSTIA, 0.05° grid scale), available through the Group for High Resolution SST (GHRSST). Both products show similar seasonal variability, with maxima occurring in the summer time frame. Additionally, both products show an increasing trend of SST gradients near the coast. However, differences exist between the two products (maximum gradient intensities were around 0.11 and 0.06 °C/km for OSTIA and MUR, respectively). The potential contributions of both cloud cover and the collocation of the MUR SST onto the OSTIA SST grid product to these differences were examined. Spectra and coherences were examined at two specific latitudes along the coast where upwelling can occur. A major conclusion is that future work needs to focus on cloud cover and its impact on the derivation of SST in coastal regions. Future comparisons also need to apply collocation methodologies that maintain, as much as possible, the spatial variability of the high-resolution product. Full article

In this work, lightweight aggregates (LWAs) were prepared from an Italian red clay, pumice scraps, and spent coffee grounds. Chemical and physical characterization was first performed on the raw materials and then on the finished products. By studying the thermal behavior of the materials, the correct firing temperature was evaluated. The obtained aggregates were fired in two different modes: in a rotary kiln and in a static kiln; the influence of the firing processes on the finished products was assessed. This study can be useful for industrially scaling up this process. Firing in a rotary kiln reduced the average diameter of the aggregates (negative expansion index), resulting in a higher compressive strength and dry particle density compared to an aggregate containing only clay. The pH and electrical conductivity values address their use in agronomy without causing problems to crops, while the higher compressive strength, density, and porosity values could allow their use in construction. Full article

The cement industry is a significant contributor to global carbon dioxide emissions, primarily due to the energy demands of its production process and its reliance on clinker, a material formed through the high-temperature calcination of limestone. Strategies to reduce emissions include the adoption of low-carbon fuels, the use of carbon capture and storage (CCS) technologies, and the integration of supplementary cementitious materials (SCMs) to reduce the clinker content. The effectiveness of these measures depends on a complex set of interactions involving technological feasibility, market dynamics, and regulatory frameworks. This study presents a system dynamics model designed to assess how various decarbonization approaches influence long-term emission trends within the cement industry. The model accounts for supply chains, production technologies, market adoption rates, and changes in cement production costs. This study then analyzes a number of scenarios where there is large-scale sustained investment in each of three carbon mitigation strategies. The results show that CCS by itself allows the cement industry to achieve carbon neutrality, but the high capital investment results in a large cost increase for cement. A combined approach using alternative fuels and SCMs was found to achieve a large carbon reduction without a sustained increase in cement prices, highlighting the trade-offs between cost, effectiveness, and system-wide interactions. Full article

This study proposed a mechanochemical activation strategy using ethanol-diisopropanolamine (EDIPA) to improve the grindability and hydration reactivity of basic oxygen furnace slag (BOFS), aiming for its large-scale industrial utilization. The incorporation of EDIPA significantly refined the particle size distribution and reduced the repose angle. As a result, the compressive strength of BOFS paste increased by 25.4 MPa at 28 d with only 0.08 wt.% EDIPA. Conductivity tests demonstrated that EDIPA strongly complexes with Ca²⁺, Al³⁺, and Fe³⁺, facilitating the dissolution of active mineral phases, such as C₁₂A₇ and C₂F, and accelerating hydration reactions. XRD and TG analyses confirmed that the incorporation of EDIPA facilitated the formation of Mc (C₄(A,F)ČH₁₁) and increased the content of C-S-H, both of which contributed to microstructural densification. Microstructural observations further revealed that EDIPA refined Ca(OH)₂ crystals, increasing their specific surface area from 4.7 m²/g to 35.2 m²/g. The combined effect of crystal refinement and enhanced hydration product formation resulted in reduced porosity and improved mechanical properties. Overall, the results demonstrated that EDIPA provided an economical, effective, and scalable means of activating BOFS, thereby promoting its high-value utilization in low-carbon construction materials. Full article

Parabens—specifically methylparaben (MeP), ethylparaben (EtP), propylparaben (PrP), and butylparaben (BuP)—are widely used substances in everyday life, particularly as preservatives in pharmaceutical and food products. However, these compounds are not effectively removed by conventional water and wastewater treatment processes, potentially causing disruptions to human homeostasis and the endocrine system. This study conducted a transport and dimensional analysis through simulation of the adsorption process for these parabens, using zinc chloride-activated carbon derived from spent coffee grounds (ACZnCl₂) as the adsorbent, implemented via Aspen Properties^® and Aspen Adsorption^®. Simulations were performed for two inlet concentrations (50 mg/L and 100 mg/L) and two adsorption column heights (3 m and 4 m), considering a volumetric flow rate representative of a medium-sized city with approximately 100,000 inhabitants. The results showed that both density and surface tension of the parabens varied linearly with increasing temperature, and viscosity exhibited a marked reduction above 30 °C. Among the tested conditions, the configuration with 50 mg∙L⁻¹ inlet concentration and a 4 m column height demonstrated the highest adsorption capacity and better performance under adsorption–desorption equilibrium. These findings indicate that the implementation of adsorption beds on an industrial scale in water and wastewater treatment systems is both environmentally and socially viable. Full article

Given the urgent need to decarbonize the global energy system, green hydrogen has emerged as a key alternative in the transition to renewables. However, its production via electrolysis demands high water quality and raises environmental concerns, particularly regarding reject water discharge. This study employs an experimental and analytical approach to define optimal water characteristics for electrolysis, focusing on conductivity as a key parameter. A pilot water treatment plant with reverse osmosis and electrodeionization (EDI) was designed to simulate industrial-scale pretreatment. Twenty water samples from diverse natural sources (surface and groundwater) were tested, selected for geographical and geological variability. A predictive algorithm was developed and validated to estimate useful versus reject water based on input quality. Three conductivity-based categories were defined: optimal (0–410 µS/cm), moderate (411–900 µS/cm), and restricted (>900 µS/cm). Results show that water quality significantly affects process efficiency, energy use, waste generation, and operating costs. This work offers a technical and regulatory framework for assessing potential sites for green hydrogen plants, recommending avoidance of high-conductivity sources. It also underscores the current regulatory gap regarding reject water treatment, stressing the need for clear environmental guidelines to ensure project sustainability. Full article

The growing concern over environmental sustainability has intensified the focus on consumers’ perceptions of eco-friendly food packaging, especially among younger generations. This study aims to investigate the attitudes, preferences, and barriers faced by Greek university students regarding sustainable food packaging, a demographic considered pivotal for driving future consumption trends. An online questionnaire assessing perceptions, preferences, and behaviours related to sustainable packaging was administered to students, with responses measured on a five-point Likert scale. Three hundred and sixty-four students took part in this survey, with the majority (60%) of them being female. Principal component analysis was employed to identify underlying factors influencing perceptions, and k-means cluster analysis revealed two consumer segments: “Innovatives”, including one hundred and ninety-eight participants (54%), who demonstrate strong environmental awareness and willingness to adopt sustainable behaviours, and “Sceptics”, including one hundred sixty-six participants (46%), who show moderate engagement and remain cautious in their choices. Convenience, affordability, and clear product communication emerged as significant factors shaping student preferences. The findings suggest that targeted educational campaigns and transparent information are essential to converting positive attitudes into consistent purchasing behaviours. This research provides valuable insights for policymakers and marketers looking to design effective sustainability strategies tailored to the student population. Full article

Micronutrients play a prominent role in plant growth and development, and their bioavailability is a growing global concern. Zinc is one of the most important micronutrients in the plant life cycle, acting as a metallic cofactor for numerous biochemical reactions within plant cells. Zinc deficiency in plants leads to various physiological abnormalities, ultimately affecting nutritional quality and posing challenges to food security. Biofortification methods have been adopted by agronomists to increase Zn concentrations in crops through optimal foliar and soil applications. Changing climatic conditions and conventional agricultural practices alter edaphic factors, reducing zinc bioavailability in soils due to abrupt weather changes. Precision agriculture emphasizes need-based and site-specific technologies to address these nutritional deficiencies. Nanoscience, a multidimensional approach, reduces particle size to the nanometer (nm) scale to enhance their efficiency in precise amounts. Nanoscale forms of Zn⁺² and their broad applications across crops are gaining attention in agriculture under varied application methods. This review focuses on the significance of Zn oxide (ZnO) nanoparticles (ZnONPs) and their extensive application in crop production. We also discuss optimum dosage levels, ZnONPs synthesis, application methods, toxicity, and promising future strategies in this field. Full article

Subcooling-based ice slurry production faces challenges in terms of energy efficiency and operational stability, which limit its applications for large-scale cold energy storage. A thermodynamic model is established to investigate the effects of key control parameters, including evaporation temperature, condensation temperature, subcooling degree, water flow rate, type of refrigerant, and adiabatic compression efficiency. The results show that using the refrigerant R161 achieves the highest energy efficiency, indicating that R161 is the optimal refrigerant in this research. When the evaporation and condensation temperatures are −10 °C and 30 °C, respectively, the system achieves the maximum comprehensive performance coefficient of 2.43. Moreover, under a flow velocity of 0.8 m/s and a temperature of 0.5 °C, the system achieves a peak ice production rate of 45.28 kg/h. A high water temperature and high flow velocity would significantly degrade the system’s ice production capacity. This research provides useful guidance for the design, optimization, and application of ice slurry-based cold energy storage systems. Full article