Search Results (6,900)

In recent years, strong emphasis has been put on decarbonising the transport and mining sectors in an economically viable manner. To this end, ammonia is presented as a fuel, combining a high energy density (when compared to hydrogen) and zero carbon emissions. In this work, conversion of a mining haul truck engine is simulated for its use with an ammonia/diesel dual-fuel system at up to 70% Ammonia Energy Replacement (AER). The numerical setup is partially validated against engine performance data. The simulations suggest a reduction in CO${}_2$ emissions but an increase in N${}_2$O, which increases the carbon-equivalent emissions of the engine. Nevertheless, NO${}_{\mathrm{x}}$ emissions appear to be reduced, suggesting the use of post-treatment is required to deal with the issue of N${}_2$O. Cylinder temperature control is recommended for its reduction, as temperatures are lower when burning ammonia. On the other hand, the simulations suggest that ammonia slip increases with AER if diesel injection phasing is not optimised. Performance-wise, the engine develops a higher indicated mean effective pressure (IMEP) as AER increases, with a maximum at 40% AER, while combustion is delayed progressively into the engine cycle, as CAD50 values increase from −0.6 CAD ATDC at 0% AER to 20.1 CAD ATDC at 70% AER. Opportunities for further research are discussed, including more extensive experimental work to support or reject what is suggested by the simulations. Full article

The common root characteristic of CO₂ and air pollutants in the power industry, both derived from fossil fuel combustion, provides a natural basis for their synergistic emission reduction. However, existing studies suffer from the lack of a multi-pollutant synergistic evaluation system and an imperfect emission reduction technology database, which hinder their ability to support low-cost and high-efficiency emission reduction practices in the industry. Targeting the minimization of synergistic emission reduction costs and the maximization of emission reduction effects, this study integrated the process and economic parameters of 11 power generation technologies and 55 pollutant control technologies to establish a full-chain energy conservation and emission reduction technology database for the power industry, through literature research, industry surveys, and data mining. Based on the definition of pollution equivalent in the Environmental Protection Tax Law, we innovatively developed an air pollutant equivalent normalization evaluation method and constructed a two-dimensional coordinate system comprehensive evaluation system for CO₂ and air pollutants, enabling quantitative analysis and visual evaluation of the synergistic emission reduction effects of various technologies. The results show that new energy power generation technologies such as nuclear power and wind power, as well as O₂/CO₂ cycle combustion, ammonia-based desulfurization, and SNCR-SCR combined reduction technologies, exhibit excellent synergistic emission reduction performance for CO₂ and multiple pollutants. In contrast, some conventional pollutant control technologies, such as the limestone-gypsum method and traditional electrostatic precipitation, have significant CO₂ emission increase antagonistic effects. This study also completed the two-dimensional classification of 66 emission reduction technologies based on “emission reduction efficiency-economic cost”, identified application scenarios for different types of technologies, and proposed optimized paths for synergistic emission reduction adapted to the development of the power industry. The research findings fill the gap in quantitative standards for multi-pollutant synergistic emission reduction, provide theoretical support and detailed technical references for emission reduction technology selection and environmental policy formulation in the power industry, and help the industry achieve the dual development requirements of the “double carbon” goal and air quality improvement. Full article

To achieve synergistic, efficient degradation of volatile, harmful gases in asphalt and to scientifically quantify inhibitor dosage, this study proposes a dosage optimization method that integrates nonlinear regression with a multi-response satisfaction function. Focusing on a proprietary composite volatile gas suppressant, we systematically measured the concentration trends of ammonia, nitrogen oxides, sulfur dioxide, and hydrogen sulfide emitted from three asphalt systems: base asphalt, SBS modified asphalt (Styrene-Butadiene-Styrene modified asphalt), and rubber modified asphalt under different suppressant dosages (0%, 0.02%, 0.04%, 0.06%, 0.08%, and 0.10%). First, high-precision prediction models (R² > 0.95) were established using nonlinear regression to relate different inhibitor dosages to corresponding gas concentrations. Based on a satisfaction function, the multi-objective degradation effects were normalized into a comprehensive satisfaction index, and the optimal dosage was then determined. The results indicate: (1) the constructed models can accurately predict the concentrations of volatile harmful gases at various dosages; (2) the predicted optimal blending ratios vary by asphalt type, specifically 0.082% for base asphalt, 0.079% for SBS modified asphalt, and 0.080% for rubber modified asphalt; and (3) at the optimal blending ratios, all four gases achieve high and balanced degradation levels, resulting in the best overall degradation performance. At the same time, road performance tests confirmed that this blending ratio has no significant negative impact on the high-temperature and low-temperature stability or water stability of the asphalt mixture. Compared with traditional single-factor empirical methods, this approach represents a methodological upgrade from qualitative description to quantitative prediction, and from single-objective comparison to multi-objective synergistic optimization, providing data and theoretical support for the precise, efficient, and engineering-applicable use of asphalt volatile gas inhibitors. Full article

Formalin, a commercial aqueous solution typically containing 37% formaldehyde, often includes a few percent methanol to inhibit polymerization. Nevertheless, formaldehyde readily forms polymerization products such as glycols, dimethoxy (acetal), and methoxyalcohol (hemiacetal) derivatives, making their analysis important. In this work, we employ ion mobility spectrometry (IMS) for qualitative and quantitative detection of these species and demonstrate that analysis is not feasible using the standard IMS reactant ion, H₃O⁺(H₂O)_n. Protonation by H₃O⁺(H₂O)_n induces loss of water or methanol, preventing stable detection of the intact derivatives. Hence, ammonia was introduced as a dopant to replace H₃O⁺(H₂O)_n with NH₄⁺(H₂O)_n in the ionization region, thereby shifting the ionization mechanism from proton transfer to ammonium attachment. A high-temperature injection port was also designed to enable the analysis of both liquid samples and their corresponding headspace. Using the developed method, we identified both acetal and hemiacetal derivatives in commercial formaldehyde solution, while only the more volatile acetal species were detected in the headspace. Quantitative analysis yielded a limit of detection (LOD) of 1.9 ppm and a linear range of 5.5–120 ppm for solution measurements. Importantly, the method provides reliable detection in the presence of substantial humidity, an environment in which many polymer-based sensors fail due to severe moisture interference. Overall, ammonia-doped IMS offers a robust and humidity-tolerant platform for characterizing formaldehyde polymerization products in both the gas and liquid phases. Full article

Ammonia decomposition represents a promising route for CO₂-free hydrogen production; however, the development of efficient and stable catalysts remains a critical challenge. In this work, a series of Al-based mixed-oxide catalysts (AlM, where M = Ni, Co, Ce) were synthesized via co-precipitation and systematically investigated to elucidate the relationship between physicochemical properties and catalytic performance in ammonia decomposition. Comprehensive characterization by X-ray diffraction (XRD), N₂ physisorption (BET), scanning electron microscopy with energy-dispersive X-ray spectroscopy (SEM–EDX), X-ray photoelectron spectroscopy (XPS), thermogravimetric analysis (TGA), and pyridine-adsorbed Fourier transform infrared spectroscopy (FTIR-Py) revealed significant variations in surface area, morphology, dispersion, and acidity as a function of the incorporated metal. Among the investigated catalysts, the AlNi system exhibited superior activity, achieving the highest ammonia conversion over the studied temperature range. This enhanced performance is attributed to its high specific surface area, homogeneous mesoporous structure, and a balanced distribution of Lewis/Brønsted acid sites, which promote effective ammonia adsorption, activation and decomposition. Kinetic analysis further confirmed the favorable reaction pathway on AlNi, as evidenced by its lower apparent activation energy and higher pre-exponential factor compared to the other materials. The results demonstrate a clear correlation between surface acidity, textural properties, and catalytic performance, highlighting the pivotal role of AlM interactions in governing ammonia decomposition. These findings provide valuable insights for the rational design of efficient catalysts for hydrogen production from ammonia. Full article

Chocolate spot, caused by the ascomycete fungus Botrytis fabae, is a devastating foliar disease and a major constraint on the quality and yield of faba beans (Vicia faba). Monoterpenes, such as carvone, cineole, and linalool, are often considered natural-identical alternatives to synthetic chemicals. Therefore, this study was carried out to assess the antifungal activity of some eco-friendly control agents (carvone, cineole, and linalool) against B. fabae, the causative agent of chocolate spot disease in faba beans, through growth inhibition assays in vitro. Furthermore, the efficacy of the tested monoterpenes for reducing the severity of chocolate spot disease in faba beans was evaluated under field conditions. Moreover, these eco-friendly control agents activate plant defense enzymes (phenylalanine ammonia-lyase, polyphenol oxidase, and peroxidase) as a self-defense mechanism against pathogen attacks of faba bean plants were investigated. Moreover, the impact of the tested monoterpenes on growth and yield characters of faba bean was evaluated. The results indicated a significant decrease in B. fabae growth following a treatment with the tested compounds compared to untreated controls. In field trials, treated faba bean plants exhibited a notable reduction in disease severity. Additionally, the application of monoterpenes enhanced the activity of defense enzymes (phenylalanine ammonia-lyase, polyphenol oxidase, and peroxidase), which are integral to plant defense mechanisms. Treatments also resulted in significant improvement growth and yield characters of faba bean. These findings suggest that the tested monoterpenes could serve as a control strategy for managing B. fabae, offering an environmentally sustainable alternative to conventional fungicides. Full article

Electrocatalytic nitrate reduction to ammonia (NH₃) offers a sustainable alternative to the Haber–Bosch process while enabling remediation of nitrate-contaminated water. However, the mechanistic origin of performance differences among bimetallic catalysts remains poorly understood, particularly regarding the metal-dependent evolution of reaction intermediates. Here, we construct a series of phase-pure tandem Cu–M catalysts (M = Co, Ni, Fe, Sn) by physically integrating commercial nanoparticles to examine the role of the secondary metal. In this architecture, Cu governs nitrate adsorption and its initial reduction to nitrite, whereas M dictates downstream hydrogenation toward NH₃. Operando ATR–FTIR spectroscopy reveals that NH₃ FE is determined by the hydrogenation kinetics of nitrite-derived intermediates rather than nitrate activation itself. Among the examined systems, Cu–Co achieves optimal kinetic matching, enabling rapid nitrite consumption and continuous hydrogenation, delivering an ammonia Faradaic efficiency of 91.2% with minimal nitrite accumulation (~1.0%) and a yield rate of 0.86 mmol h⁻¹ cm⁻² at −0.5 V vs. RHE. In contrast, Ni and Fe exhibit sluggish hydrogenation, while Sn induces pronounced intermediate buildup. These findings identify nitrite hydrogenation as the selectivity-determining step in tandem nitrate reduction and establish the chemical nature of the secondary metal as a decisive descriptor for rational catalyst design. Full article

High litter moisture content (LMC) in poultry houses is a primary driver of footpad dermatitis, elevated ammonia emissions, and bacterial proliferation. These conditions directly compromise broiler welfare and productivity. Existing monitoring methods, including oven-drying, contact-based sensors, and near-infrared spectroscopy, suffer from invasiveness, single-point limitation, or surface-only measurement. This study investigates ultra-wideband (UWB) impulse radar as a non-contact sensing modality for estimating the LMC of cedar wood shaving bedding under controlled laboratory conditions. A four-phase experimental program was conducted. Phases 1–3 characterized signal–moisture relationships across 0–50% LMC, manure simulant contamination, and bedding structural changes (loose, compacted, caked). Phase 4 tested whether UWB radar can estimate litter LMC when a stationary broiler body obstructs the beam under combined contamination and structural conditions. A progressive feature engineering approach and an SVC-gated mixture-of-experts regression architecture were used to address each confounding factor. Full technical details are provided in the Methods Section. Under clean conditions, the baseline model achieved $R^2=0.97$ and RMSE = 2.48% LMC. Under combined realistic conditions (manure contamination, caked bedding, centered carcass), the full pipeline achieved $R^2=0.91$ and RMSE = 4.53% LMC, with 98.8% bird detection accuracy from the radar signal alone. These laboratory findings suggest that the UWB radar can sense litter moisture through a stationary broiler body. The results support its potential as the sensing core of a non-contact monitoring system for precision poultry farming. Full article

Ammonia (NH₃) from intensive agriculture is a primary precursor for secondary fine particulate matter (PM_2.5), necessitating mitigation under the EU National Emission Ceilings (NEC) Directive. This study evaluated a novel feed-based intervention assessed under real-scale commercial conditions in weaning and growing pig units. Indoor NH₃ concentrations were monitored at high frequency (2 h resolution), and treatment effects were analyzed using a Circular Block Bootstrap (CBB) approach to account for diurnal cyclicity and temporal autocorrelation. In the weaning unit, where pits were fully emptied before the trial, the mean indoor NH₃ concentration decreased from 7.51 ppm to 1.37 ppm, representing an 81.7% reduction. In the growing unit, which operated under pre-existing slurry and an overflow system, a significant reduction of 20.9% was observed (from 5.45 ppm to 4.31 ppm). These results demonstrate the intervention’s efficacy in preventing NH₃ release from fresh excreta and suggest that its impact in systems managed under slurry overflow can be further optimized by initially activating pre-existing material. This infrastructure-free solution offers a scalable, economically sustainable pathway to align livestock production with zero-pollution targets while supporting multiple Sustainable Development Goals related to human health, worker welfare, and environmental protection. Full article

To address the bottleneck of poor biological nitrogen removal efficiency caused by the extremely low carbon-to-nitrogen (C/N) ratio of domestic sewage in alpine plateau regions, this study used Hordeum vulgare var. coeleste L., a characteristic crop endemic to the Qinghai–Tibet Plateau, as raw material and adopted pretreated highland barley straw as an external carbon source. Three parallel experiments were carried out using the anaerobic–aerobic–anoxic sequencing batch reactor (AOA-SBR) process to investigate the nitrogen removal performance and functional succession of the microbial community in the AOA-SBR system under three C/N ratio ranges: 5~7, 7~9, and 9~11. The results showed that the addition of an external carbon source significantly improved nitrogen removal efficiency. The optimal C/N ratio range for nitrogen removal in this study was determined to be 7~9. A weakly alkaline environment was conducive to denitrification. The fermentation broth prepared by alkali pretreatment contained a large amount of readily biodegradable organic matter with low toxicity, and achieved excellent nitrogen removal performance, helping to realize cost reduction and efficiency improvement in wastewater treatment. At the optimal C/N ratio of 7~9, the average removal efficiencies of ammonia nitrogen (NH₄⁺-N) and total nitrogen (TN) reached 94.46% and 61.32%, respectively, which were significantly improved compared with the blank control group without external carbon addition. During the experimental period, no obvious changes were observed in microbial abundance at the phylum level, whereas the community structure at the genus level responded significantly to the addition of a straw carbon source. Among them, genera with specific degradation capabilities for straw hydrolysates, such as norank_f__Chitinophagaceae and unclassified_f__Comamonadaceae, were highly sensitive to variations in the C/N ratio. These genera could partially replace the nitrification and denitrification functions of other microorganisms and played a key role in the nitrogen removal process. In contrast, Thauera, a typical conventional heterotrophic denitrifier, showed no significant response to changes in the C/N ratio, indicating that the straw-based external carbon source mainly affected microbial genera with specific hydrolysate-degrading functions. Full article

Although grazing is a key driver of nitrogen cycling in alpine meadow soils, a systematic understanding of how different grazing intensities shape the structure and functional potential of soil nitrogen-cycling microbial communities remains lacking. In this study, soil samples were collected under five grazing intensities (no grazing, light grazing, moderate grazing, heavy grazing, and extreme grazing) and metagenomic sequencing was employed to analyze variations in nitrogen-cycling microbial communities and functional genes. The results showed that bacteria were the dominant group in nitrogen-cycling communities (relative abundance: 93.99–98.98%), with significant community differentiation across grazing intensities. Light grazing maintained relatively high microbial diversity, whereas moderate and heavy grazing led to more pronounced differences in community composition. Functional gene analysis identified 41 nitrogen-cycling-related genes, primarily involved in denitrification, nitrate reduction, and ammonia assimilation. Light grazing enhanced nitrate reduction and glutamate synthesis; moderate grazing exhibited the strongest ammonia assimilation potential; heavy grazing significantly increased denitrification activity, indicating an elevated risk of nitrogen loss; and under extreme grazing, both the number and abundance of nitrogen-cycling functional genes declined markedly, with functional composition becoming simplified. Collectively, light grazing is more conducive to maintaining the balance between soil microbial diversity and nitrogen-cycling function in alpine meadows, whereas overgrazing disrupts the equilibrium between microbial communities and nitrogen metabolism. This study provides a microbiological basis for the restoration of degraded alpine meadows and sustainable grazing management. Full article

Plasma-assisted ammonia (NH₃) decomposition is a promising strategy for hydrogen production. However, reactor geometry remains a key factor limiting its hydrogen yield per energy input (${\mathrm{Y}}_{{\mathrm{H}}_2}$). This study systematically investigates H₂ production in outer-dielectric (OD), inner-dielectric (ID), and double-dielectric (DD) coaxial DBD reactors. The results show that the ammonia decomposition performance of OD- and ID-coaxial DBDs is significantly higher than that of the DD-coaxial DBD. OD- and ID-coaxial DBDs generate abundant micro-discharge pulses, enabling effective discharge energy deposition at lower peak voltages. Consequently, the reduced electric fields E/N are maintained within the optimal kinetic window for NH₃ dissociation and H₂ production. Moreover, by balancing residence time and energy density, the 8 cm length electrode achieves a peak ${\mathrm{Y}}_{{\mathrm{H}}_2}$ of 1.22–1.24 gH₂/kWh in the OD-coaxial DBD. For the ID-coaxial DBD, a 1 mm dielectric thickness yields a maximum capacitance of 86 pF, achieving a peak ${\mathrm{Y}}_{{\mathrm{H}}_2}$ of ~1.35 gH₂/kWh at the optimum E/N. In contrast, the DD-coaxial DBD exhibits the lowest ${\mathrm{Y}}_{{\mathrm{H}}_2}$ (≤0.82 gH₂/kWh) with minimal temperature rise. This is caused by the reduced current pulse numbers and the deviation of E/N from the optimal range with elevated operating voltages. This work provides guidance for the optimization of DBD reactors in plasma-assisted NH₃ decomposition for efficient H₂ production. Full article

As a carbon-free fuel, ammonia can substantially reduce the carbon footprint of internal combustion engines. However, its slow flame propagation speed and high ignition temperature present combustion challenges. A dual-fuel engine combining ammonia with diesel can effectively address these issues and enhance combustion performance. This study investigates the effects of diesel split ratio (DSR), start of diesel pre-injection (SODI-pre), and start of diesel main-injection (SODI-main). The results indicate that, compared to single diesel injection, segmented diesel injection significantly improves mixture distribution and reactivity, leading to enhanced flame propagation. With a pre-injection ratio of 10% and SODI-pre advanced to −62 °CA, the indicated thermal efficiency increases from 45.35% to 47.61%. Meanwhile, NH₃ emissions decrease from 1707 ppm to 689 ppm, and greenhouse gas N₂O concentration drops from 370 ppm to 251 ppm. Nevertheless, elevated NO_x emissions remain a significant challenge. Full article

Cardiac positron emission tomography (PET) has undergone substantial development in recent years, moving beyond conventional perfusion imaging toward a multiparametric and increasingly quantitative assessment of cardiovascular disease. This article provides a critical narrative overview of the recent cardiac PET literature, with particular emphasis on studies published over the last five years, and discusses both established tracers and emerging radiopharmaceuticals in contemporary cardiology. Among established applications, 18F-FDG remains relevant for myocardial viability assessment and selected inflammatory indications, although its prognostic and therapeutic implications are less uniform than earlier narratives suggested. For myocardial perfusion imaging, 13N-ammonia and 82Rb PET provide robust assessment of myocardial blood flow and myocardial flow reserve, but their clinical interpretation remains strongly influenced by acquisition protocols, software reproducibility, and methodological standardization. The review also addresses newer tracers, including 68Ga-FAPI for fibroblast activation, 18F-flurpiridaz for high-performance perfusion imaging, 18F-FDOPA for cardiac sympathetic dysfunction, and amyloid-binding PET radiopharmaceuticals for cardiac amyloidosis. Overall, recent evidence supports cardiac PET as a powerful platform for physiologic and molecular imaging, but not as a uniform or methodologically neutral technology. Its current value lies in selective, question-driven clinical use, whereas broader implementation will depend on tracer-specific validation, harmonized quantitative workflows, and clear demonstration of incremental benefit over existing imaging strategies. Full article

This study aimed to investigate the effects of dietary bile acids (BA) supplementation on serum antioxidant capacity, fecal fermentation characteristics, microbial diversity, and community composition in culled ewes. Twenty 5-year-old culled Hu ewes with similar body weights (42.95 ± 1.07 kg) were randomly allocated to two groups (n = 10 per group). The control group (CON) received a basal diet, while the treatment group (BA400) was fed the same basal diet supplemented with 400 mg/kg BA. Compared with the CON group, the BA400 group showed enhanced serum activities of total antioxidant capacity, superoxide dismutase, and glutathione peroxidase, while also showing reduced concentrations of cortisol, malondialdehyde, and reactive oxygen species (p < 0.05). Fecal pH, ammonia nitrogen, total volatile fatty acids, and the concentrations and proportions of individual volatile fatty acids remained unaffected by BA supplementation (p > 0.05). Microbial analysis revealed that the BA400 group exhibited higher fecal bacterial richness and diversity than the CON group (p < 0.05). Analysis of similarities revealed significant differences between the CON and BA400 groups (R = 1.000, p = 0.007). Specifically, BA supplementation increased the relative abundances of beneficial taxa, including Verrucomicrobiota and Akkermansia, while decreasing potentially pathogenic bacteria such as Campylobacterota and Proteobacteria. These findings indicate that dietary BA supplementation improves serum antioxidant capacity and modulates fecal microbial diversity and community structure in culled ewes, suggesting that hindgut microbiota may contribute to the health benefits of BA supplementation in ruminant production. Full article