Search Results (4,412)

Internal combustion engines fueled by fossil fuels are major contributors to greenhouse gas (GHG) emissions. This study analyzes and predicts GHG emissions from hydrogen-enriched compressed natural gas (HCNG)-fueled spark-ignition (SI) engines. Experiments were conducted under stoichiometric conditions, and emissions before and after the three-way catalytic converter (TWC) were analyzed by varying hydrogen fraction (0–50%), EGR ratio (0–23%), engine speed (900 rpm–1500 rpm), engine load (25–75%), and spark timing (8–49 °CA bTDC). Before the TWC, increasing the hydrogen fraction from HCNG0% to HCNG40% at 1500 rpm, 50% load, and 23% EGR reduced total GHG emissions from 184.3 to 65.17 g/kWh. Similarly, for HCNG20% at 900 rpm and 30% load, the TWC reduced the CO₂-equivalent emissions of CO, CH₄, and NOx from 18.531, 8.149, and 9.057 g${\mathrm{C}\mathrm{O}}_{2eq}$/kWh to 7.013, 1.626, and 0.429 g${\mathrm{C}\mathrm{O}}_{2eq}$/kWh, respectively. Pearson correlation analysis revealed strong linear relationships between operating parameters and GHG emissions. Furthermore, emissions were predicted using four Gaussian process regression (GPR) models: Squared, Exponential, Matern 5/2, and Rational. Among these, the Exponential GPR demonstrated the highest predictive accuracy, achieving RMSE values of 0.098, 0.022, and 0.035, with corresponding R² values of 0.999, 0.807, and 0.996 for CO, CH₄, and NOx, respectively. The findings of this study offer valuable insights into GHG emissions and support the development of cleaner, more efficient HCNG engines. Full article

This study developed a nano-TiO₂ modified emulsified asphalt, and the effects of varying dosages of nano-TiO₂ on the performance of emulsified asphalt were systematically investigated. The photocatalytic performance of nano-TiO₂ modified emulsified asphalt was evaluated through NO_x degradation assessment using a self-developed device. Results showed that after adding nano-TiO₂, the high-temperature stability and aging resistance of the modified emulsified asphalt had improved. Specifically, when the TiO₂ content ranged from 4% to 6%, the surface temperature of the photocatalytic fog seal layer decreased by 2.0 °C. At 4% TiO₂ content, the cumulative degradation efficiencies of NO and NO₂ reached 50% and 70%, respectively. When the fog seal layer spraying amount was set at 300 g/m², the pavement performance met the required standards. Overall, nano-TiO₂ photocatalytic materials simultaneously enhance the physical properties of asphalt and its environmental benefits, providing a promising solution for the development of multifunctional pavement materials. Full article

Cruise ships and superyachts have experienced significant global expansion throughout the 21st century. Although the growth in cruise passenger numbers was temporarily disrupted by the COVID-19 pandemic, occupancy rates have since rebounded and even exceeded pre-pandemic levels. This study highlights the significant environmental impact of cruise ships and luxury yachts, particularly in terms of air emissions and marine pollution. Emission levels associated with different fuel types and marine engines are analysed, including the average emissions generated by the Norwegian Cruise Line fleet while docked in ports, as well as the estimated emission reductions achievable through the implementation of onshore power supply systems. To identify environmentally preferable fuel options, a hybrid ANN/MCDM framework is applied. The weighting coefficients of eight evaluation criteria are determined using the Artificial Neural Network/Extreme Learning Machine (ANN/ELM) model, ensuring an objective and data-driven assessment of their relative importance. The ANN/ELM model was trained using emission and fuel-related data collected from the literature and industry reports, and its performance was validated using standard validation procedures, achieving satisfactory predictive accuracy for determining the weighting coefficients. The final ranking of eight fuel alternatives is subsequently performed using the Ranking Alternatives by Weighting of Evaluated Criteria (RAWEC) method. The considered alternatives include conventional and emerging marine fuels currently used in practice or under technological development (A₁–A₈), while the optimization criteria (C₁–C₈) encompass major air pollutants (CO₂, NOx, SOx, CO, PM, CH₄), the fuel cost-to-consumption ratio, and the potential impact on water pollution. The water pollution criterion is assessed qualitatively using the Saaty scale. The integrated ANN/ELM–RAWEC approach enables a systematic comparison of marine fuels and supports the identification of options with the lowest overall environmental impact. Full article

Most air pollution research in India has predominantly focused on the Indo-Gangetic Plain (IGP) owing to its high pollution levels and dense populations, leaving peninsular India comparatively undercharacterized. In contrast, South India remains underexplored because of its relatively limited long-term monitoring and more favorable meteorology. This geographical imbalance restricts a comprehensive national understanding of particulate matter (PM) dynamics. Addressing this gap, the present study delivers a multi-scale (hourly to interannual) spatiotemporal assessments of PM_2.5 across eight monitoring stations in Andhra Pradesh, a South Indian State, for the period 2020–2024. The analysis reveals pronounced seasonal variability, with persistent winter and post-monsoon maxima. Although overall concentrations are low compared to northern India, urban–industrial centers such as Visakhapatnam and Rajahmahendravaram frequently exceeded both the National Ambient Air Quality Standards (NAAQS) and World Health Organization (WHO) guidelines. Notably, Amaravati, a non-industrial and low-lying inland site, exhibited anomalously moderate PM_2.5 levels, with ~11.58% of hourly values surpassing 60 µg m⁻³. The COVID-19 lockdown period further offered a natural experiment, revealing substantial reductions (30–65%) in PM_2.5 and PM₁₀ at major urban sites while concurrent ozone enhancements (up to ~50%) at Tirupati and Rajahmundry exposed complex photochemical sensitivity under reduced NO_x conditions. Satellite-based MERRA-2 estimates corroborated inter-annual variability and the short-lived improvement in air quality. This study demonstrates that air quality dynamics in the state of Andhra Pradesh are governed by region-specific meteorological controls, episodic processes, and localized emission characteristics, necessitating expanded long-term monitoring infrastructure and improved satellite–ground calibration frameworks. Full article

The use of hydrogen direct injection (DI) plays a crucial role in decarbonizing internal combustion engine (ICE) technology. However, a suitable characterization of the injection process is required to control the mixture preparation before combustion, especially in the case of late injection timing. CFD modeling represents a useful tool to support experiments in addressing this goal. This study presents a numerical investigation of hydrogen DI using a swirled-type injector, seated in a constant-volume vessel. First, the selected numerical setup is validated against optical measurements of the jet penetration, demonstrating the reliability of the approach. Then, the analysis compares swirling and non-swirling configurations under different nozzle pressure ratios (nPRs) to evaluate the interaction between swirl-induced mixing and under-expanded jet structures. Results show that at lower nPR, swirl significantly alters the momentum distribution, reducing axial penetration. Instead, at higher nPR, where the H2 jets exhibit strong shock structures, the effects of swirl become negligible, with penetration and plume morphology nearly identical to non-swirling conditions. Analysis of the scalar dissipation rate showed the presence of a redistribution of mixing characteristics at low nPR due to swirl, while shock structures dominate at high nPR. This could have a significant impact on combustion and NO_x emissions in ICE operated with late injection strategies, where lower nPR are found. Full article

This paper addresses the problem of nonparametric regression for functional time series, a setting complicated by the infinite-dimensional nature of the covariates, temporal dependence, and potential for outliers. We propose a new robust estimator that combines three powerful ideas: (i) k-nearest neighbors (kNN) for adaptive localization in the functional space; (ii) local linear smoothing to reduce bias; and (iii) $\mathcal{M}$-estimation to ensure resilience against atypical observations. The key theoretical contribution establishes the almost-complete convergence of the proposed estimator under mild conditions that account for the functional geometry, weak dependence (via quasi-association), and robustness constraints. The obtained rate of convergence explicitly reveals the interplay between the functional concentration, dependence strength, and local smoothness of the model. A simulation study demonstrates that this method offers superior stability and predictive accuracy compared to classical alternatives, particularly under heavy-tailed errors and data contamination. The practical relevance of the approach is further illustrated through a one-step-ahead prediction application to a real-world environmental dataset of hourly NOx measurements. Full article

Oxidative stress is one of the few defined causes of male infertility affecting at least one third of patients attending infertility clinics. Human spermatozoa are vulnerable to this form of attack because their stripped-down architecture means that they possess limited antioxidant protection and little capacity for biochemical repair. They also compound their vulnerability by being active generators of reactive oxygen species (ROS) and possessing multiple substrates for oxidative damage. The major sources of ROS in these cells are their mitochondria, an L-amino acid oxidase (IL4I1) and a calcium-dependent NADPH oxidase (NOX5). Spermatozoa tolerate the risks associated with ROS generation because their biology is heavily dependent on redox regulation. ROS are important mediators of sperm capacitation, stimulating the generation of cAMP and prostaglandins, inhibiting protein phosphatases and encouraging removal of cholesterol from the plasma membrane. Furthermore, during fertilization, the ability of ROS to activate metalloproteinases facilitates penetration of the zona pellucida and sperm–oocyte fusion. While ROS are physiologically important for sperm function, the over-production of these metabolites can impair sperm function. Antioxidants have therefore assumed some importance as a possible therapy for the infertile male. However, before this potential can be realized, we need to optimize the composition and dose of reagents used in such formulations and develop improved methods of diagnosing oxidative stress within the patient population. Full article

To advance the design of novel clean coal-fired boilers, this study integrates artificial intelligence with numerical simulations to optimize a 130 MW conceptual boiler based on Moderate or Intense Low-oxygen Dilution (MILD) and oxy-coal combustion technologies. First, mathematical models for pulverized-coal MILD-oxy combustion are validated using experimental data from a 0.58 MW pilot-scale boiler and then applied to the full-scale 130 MW boiler. An orthogonal experimental design with four factors and five levels is employed to generate 25 simulation cases, evaluating the effects of burner nozzle configuration and furnace geometry on boiler performance. Based on the simulation dataset, mutual information analysis is conducted to identify key influencing features, guiding nine additional simulations to refine samples in critical design areas. Finally, using the complete 34 simulation data, an optimal boiler structure is identified using support vector machine and multi-objective optimization algorithms. The results indicate that both the burner circumferential diameter and the O₂/CO₂ inlet diameter are positively correlated with nitrogen oxide (NOx) emissions, whereas the former is negatively correlated with the wall thermal non-uniformity. After optimization, the average char burnout rate increased by 1.4%, NOx emissions decreased by 4%, and wall heat non-uniformity coefficient reduced by 1.1%, demonstrating the effectiveness of the proposed approach. Full article

Background: Acute lung injury (ALI) is a major complication of sepsis, driven by oxidative stress, inflammation, and apoptosis. Paeoniflorin, a monoterpenoid glycoside, has demonstrated notable antioxidant and anti-inflammatory properties, suggesting potential therapeutic value in ALI. Methods: Sepsis-induced ALI was established in mice using the cecal ligation and puncture (CLP) model. The protective effects of paeoniflorin were evaluated by measuring oxidative stress markers (SOD, GSH, and MDA) and pro-inflammatory cytokines (TNF-α, IL-6, and IL-1β) using biochemical assays and RT-PCR. Histopathological examination and apoptosis assessment (Bax and Bcl-2 expression) were performed. Western blot analysis was conducted to investigate the involvement of the JAK2/STAT3 signaling pathway. Network pharmacology analysis was used to identify potential molecular targets, and molecular docking was performed to explore binding interactions. Results: CLP-induced ALI resulted in increased oxidative stress and inflammatory responses, as evidenced by elevated MDA and cytokine levels, along with reduced SOD and GSH levels. Paeoniflorin treatment significantly ameliorated these alterations. Histological damage and apoptosis were markedly reduced, accompanied by the downregulation of Bax and upregulation of Bcl-2. Additionally, paeoniflorin inhibited activation of the JAK2/STAT3 pathway. Network pharmacology identified key ALI-related targets, including IL6, TNF, IL1B, HIF1A, STAT3, NFKB1, CCL2, CYBB, CXCL8, and NOX4. Molecular docking revealed strong binding affinity of paeoniflorin toward HIF-1 and JUN, and moderate interactions with IL-1β, TNF-α, and Bax. Conclusions: Paeoniflorin exerts protective effects against sepsis-induced ALI by attenuating oxidative stress, inflammation, and apoptosis, partly through inhibition of the JAK2/STAT3 signaling pathway. These findings highlight its potential as a promising therapeutic candidate for ALI management. Full article

Accurate, high-resolution emission inventories are essential for air quality modeling and policy evaluation, yet national-scale inventories for Thailand remain limited in spatial and temporal detail. This study develops a comprehensive national emission inventory for Thailand in 2019 (EI–TH 2019), covering 12 major air pollutants and greenhouse gases across key sectors, including energy, transport, industry, agriculture, waste, and residential activities. The inventory is constructed using country-specific activity data from official statistics and sectoral surveys, combined with GAINS-consistent emission factors and control assumptions. Emissions are resolved at 1 × 1 km spatial resolution and monthly temporal resolution to capture Thailand-specific emission dynamics. The results show that emissions across major pollutants are dominated by a limited number of source groups, with biomass burning and residential solid-fuel use driving particulate matter, transport dominating NO_x and CO emissions, large-scale combustion and industry controlling SO₂ emissions, and agriculture contributing the majority of NH₃ emissions. Strong seasonal variability is observed in PM_2.5, CO, and NH₃, primarily driven by dry-season biomass burning, whereas NO_x and SO₂ exhibit relatively stable temporal patterns. The reliability of EI–TH 2019 is supported by a multi-dimensional evaluation framework. Temporal consistency is demonstrated through strong agreement between modeled PM_2.5 emissions and ground-based observations, as well as between NO_x emissions and satellite-derived TROPOMI NO₂ (r = 0.93; ρ = 0.96). Biomass burning timing is further validated using satellite fire activity (VIIRS), showing consistent seasonal patterns. Comparisons with global inventories (EDGAR v8.1, HTAP v3.2, and GFED5.1) reveal systematic differences in sectoral contributions, temporal profiles, and emission magnitudes, particularly for biomass burning, reflecting the importance of country-specific data and assumptions. Overall, EI–TH 2019 provides a robust, high-resolution, and policy-relevant emission dataset that improves the representation of emission processes in Thailand. The results highlight key priority sectors—biomass burning, transport, industry, and agriculture—for targeted emission-reduction strategies and support applications in chemical transport modeling, exposure assessment, and integrated air-quality and climate-policy analysis. Full article

The Variable Cycle Engine (VCE) is a key enabling technology for addressing the economic and environmental challenges of next-generation supersonic civil aircraft. This paper presents a multidisciplinary design analysis and optimization (MDAO) approach to quantitatively assess the potential benefits of Variable Cycle Engines (VCE) in the conceptual design of supersonic civil aircraft. In this approach, component-level models of a conventional Mixed-Flow Turbofan (MFTF) and a double-bypass VCE with a Core Driven Fan Stage (CDFS) are integrated into the MDAO process. Employing a multi-point optimization strategy, the engine design parameters and off-design control schedules are first determined. Subsequently, for each given engine design (MFTF and CDFS VCE), the airframe geometry parameters are optimized to minimize the aircraft Maximum Take-off Weight (MTOW). The application of this approach is illustrated through a case study of a medium-sized supersonic civil transport. The results indicate that, under the assumption of identical weights for the VCE and the MFTF, the design with the VCE reduces the MTOW by 2.8%, block fuel consumption by 5.7%, and total mission Nitrogen Oxides (NOx) emissions by 24.2% compared to the design with the MFTF. Additionally, lateral noise and flyover noise during the take-off phase are decreased by 2.2 EPNdB and 1.9 EPNdB, respectively. To account for the potential weight increase caused by the structural complexity of the VCE, a parametric weight sensitivity analysis is conducted. Results show that the VCE retains its advantages in MTOW, fuel efficiency, noise, and emissions for weight penalty factors up to 1.15. Full article

Glioblastoma (GBM) is characterized by hypoxia-driven metabolic adaptation and profound therapeutic resistance. Ferroptosis, an iron-dependent lipid peroxidation-related cell death process, has emerged as a potential vulnerability; however, its relationship with hypoxia signaling remains incompletely defined. In this study, we performed integrative transcriptomic and single-cell RNA sequencing analyses to investigate the relationship between hypoxia signaling and ferroptosis-related gene signatures in GBM. Intersection analysis of hypoxia-associated differentially expressed genes and curated ferroptosis-related gene sets identified 29 core candidate genes. FerroScore stratification revealed that tumors with higher ferroptosis-related transcriptional signatures were significantly associated with poor overall survival. Among these genes, HILPDA emerged as a hypoxia-associated gene consistently linked to ferroptosis-related gene expression patterns and immune-related transcriptional programs. HILPDA expression showed significant correlations with iron-ROS axis components, including HMOX1, NOX4, and STEAP3, and was associated with immune microenvironment changes characterized by T cell depletion and inflammatory infiltration. Single-cell RNA-seq analysis further supported the cellular-level association between HILPDA expression and hypoxia-related transcriptional states. Structural equation modeling suggested that the relationship between HILPDA expression and ferroptosis-related gene signatures may be mediated through hypoxia-related pathways. Collectively, these findings indicate a transcriptomic association between hypoxia signaling and ferroptosis-related gene signatures in GBM and identify HILPDA as a candidate gene associated with this axis. Full article

Cooking-related emissions represent a major contributor to indoor air pollution in residential kitchens, producing complex mixtures of volatile organic compounds (VOCs), odor-causing gases, oil vapors, particulate matter (PM_2.5), and combustion-related pollutants (CO and NO_x). In this study, a controlled ozone-assisted oxidation approach was integrated into a recirculating (ductless) domestic kitchen hood equipped with a confined reaction chamber and experimentally evaluated under closed-loop operating conditions where treated air was returned to the indoor environment after post-treatment. A multivariate Response Surface Methodology (RSM) framework based on the Box–Behnken design was employed to quantify and optimize the coupled effects of temperature (20–30 °C), relative humidity (40–60%), ozone dosage (1–3 ppm within the confined reaction zone), and airflow rate (150–250 m³/h) on multi-pollutant removal performance. The results demonstrate that ozone assistance substantially improves the abatement of oxidation-sensitive pollutants, particularly VOCs and odor, while airflow rate strongly governs transport-dominated pollutants such as PM_2.5 and oil vapors. In contrast, CO and NO_x exhibited limited improvement, indicating that ozone-assisted oxidation alone is insufficient for comprehensive control of combustion-related gases under short-residence-time recirculating hood conditions. The main contribution of this work is the implementation of a demand-driven ozone management strategy, supported by dual ozone sensing for reaction-zone control and outlet safety verification, where ozone generation is activated only in the presence of reactive gaseous pollutants and automatically reduced or terminated once pollutant concentrations fall below predefined thresholds, minimizing unnecessary oxidant release. Residual ozone downstream of the reaction stage was continuously monitored to prevent excess ozone return to the occupied zone. Overall, the proposed closed-loop, feedback-controlled ozone-assisted recirculating range hood concept demonstrated device-level reductions in measured VOC/odor signals under controlled conditions, while also highlighting the need for complementary post-treatment components for particle- and combustion-related pollutants. However, the potential formation of secondary oxidation byproducts was not characterized in this study, and therefore the results should be interpreted with respect to device-level pollutant removal rather than comprehensive indoor air quality improvement. Full article

Ground-level ozone (GLO₃) poses a critical threat to public health and the success of the Saudi Green Initiative, yet its long-term spatiotemporal evolution across the Arabian Peninsula remains poorly constrained. Utilizing CAMS-derived mixing ratios (1000–850 hPa) from 2003 to 2024, this study identifies a major systemic regime shift occurring in 2016–2017, marking a transition toward a more O₃-enriched atmospheric state across Saudi Arabia. While the early study period was characterized by pronounced spatial heterogeneity, post-2017 diagnostics reveal a synchronized intensification of GLO₃, particularly within the urban industrial belts of the Eastern and Western Provinces. Statistical trend metrics, including Mann–Kendall and regime-shift detection, show a persistent upward trend in GLO₃ concentrations, most significantly during winter and over the southwestern highlands. These trends are robustly coupled with increasing boundary-layer height, temperature, and UV-B radiation, alongside shifting precursor stoichiometry (CO, VOCs, NO_x) that separates titration-dominated from production-dominated regimes. Our results suggest that this mid-decade intensification reflects a convergence of anthropogenic forcing under Saudi Vision 2030 and shifting regional climatic drivers. By uncovering the transition from localized variability to kingdom-wide synchronization, this research provides a process-based foundation for targeted air quality management and the safeguarding of regional sustainability frameworks. Full article

Tumor oxygenation is a key determinant of cancer biology and treatment response, correlating with angiogenesis, recurrence, and malignant progression. Hypoxia is a defining feature of glioblastoma (GBM) and adult diffuse gliomas, generating low-oxygen niches that promote invasion, stem-like states, immune suppression, and resistance to radiotherapy and temozolomide, contributing to poor outcomes. Measuring tissue partial pressure of oxygen (pO₂) and mapping its spatial heterogeneity can, therefore, inform mechanistic understanding and therapeutic development, including hypoxia-activated prodrugs, hypoxia-responsive gene therapy, and optimized radiotherapy planning. Although direct pO₂ assessment is challenging, invasive probes and multimodal imaging can characterize regional hypoxia pre-operatively, support patient stratification, monitor treatment effects, and improve outcome prediction. This review summarizes oxygen dynamics in GBM; analyzes causes of hypoxia (rapid growth outpacing supply, diffusion-limited hypoxia, and abnormal/chaotic vasculature); compares methods to quantify oxygenation from direct measurements to noninvasive imaging surrogates; and evaluates preclinical and clinical strategies that target hypoxia to enhance standard therapy, including barriers to translation. We further integrate oxygenation with cell signaling and redox biology: oxygen gradients are transduced via hypoxia-inducible factor programs and redox-sensitive pathways (NRF2/KEAP1, NOX-derived ROS, nitric oxide/S-nitrosylation, and sulfur metabolic routes), shaping mesenchymal-like transitions and cell-death programs such as ferroptosis. Framing oxygenation as both a microenvironmental and redox-signaling variable positions oxygen imaging as an entry point to biomarker-guided therapies that exploit oxidative vulnerabilities. Full article