Search Results (1,517)

Under the dual-carbon goals, adopting renewable alternative fuels in transportation is crucial. Alcohol-based fuels, produced via biomass fermentation or green electricity-powered CO₂ hydrogenation, offer benefits like renewability, engine compatibility, and long driving range. Bio-butanol, with an energy density close to gasoline, can power SI engines directly, but its high production costs due to low fermentation efficiency limit its viability. In contrast, IBE (a butanol fermentation intermediate) avoids costly separation steps, making it more competitive than pure butanol. Existing research on IBE in spark ignition engines mainly focuses on fixed-ratio IBE-gasoline blends, restricting real-time fuel adjustment. Building on prior findings that IBE outperforms ABE and butanol, this study examines the combustion and emission characteristics of a gasoline port injection + IBE direct injection engine under varying direct injection timings, IBE ratios, and excess air ratios. Research indicates that early direct injection timings with pure IBE provide optimal performance at stoichiometric conditions. As the excess air ratio rises, an 80% IBE direct injection ratio becomes more advantageous. IBE shows great promise as an alternative fuel, enhancing combustion performance and reducing gaseous and particulate emissions. Full article

In today’s energy landscape, defined by the growing demand for sustainable energy generation technologies and the parallel need to advance internal combustion engine (ICE) architectures toward cleaner and more efficient solutions, the adoption of Free-Piston Linear Generator (FPLG) engines emerges as a highly promising approach. This innovative system enables the direct conversion of combustion-induced piston motion into electrical energy, eliminating the need for traditional crankshaft and connecting rod mechanisms. The FPLG concept facilitates efficient utilization of a broad spectrum of fuels—including methane, ethanol, LPG, gasoline, biodiesel, and hydrogen—by supporting variable compression ratio operation. This feature enhances operational flexibility and fuel adaptability, positioning the technology as a viable candidate for future energy transition scenarios. The absence of rotating mechanical components significantly reduces frictional losses, contributing to an overall increase in system efficiency. To accurately characterize and optimize engine performance, an extensive series of one-dimensional (1D) numerical simulations was performed under both free and controlled operating conditions. The resulting data enabled the development of semi-empirical models capable of predicting the dynamic behavior of the engine across a wide range of working scenarios. Finally, through a detailed parametric analysis, the optimal operating conditions were identified to maximize both net electric efficiency and electrical power output. These findings provide a solid ground for the design and implementation of FPLG engine systems in advanced power generation applications. Full article

Soot and black carbon (BC) are typically regarded as troublesome products of incomplete combustion; however, growing interest in circular economy strategies and sustainable manufacturing highlights their potential as secondary functional carbon materials, including additive manufacturing (AM). This review synthesises the recovery, upgrading, and valorization pathways for soot/BC and recovered carbon black (rCB), with a particular focus on streams captured by mandatory emission-control systems (e.g., diesel/gasoline particulate filters, electrostatic precipitators, baghouse filters, and chimney soot) and the requirements for transforming these heterogeneous residues into reproducible AM feedstocks. A two-stage approach was applied, combining (i) an analysis of the European Union regulatory context (waste classification, end-of-waste routes, and chemical safety obligations, including REACH) with (ii) a structured literature review of studies published in 2017–2026 indexed in the Web of Science and Scopus, culminating in a qualitative synthesis of 152 papers. Evidence indicates that scale-up is primarily constrained by strong compositional variability and contaminant burdens (ash, metals, and PAHs), which affect dispersion, rheology, and property reproducibility, necessitating robust standardisation and risk assessment. This review maps key preparation and upgrading strategies (e.g., classification, ash/metal reduction, and control of organic fractions) and discusses their relevance across AM routes such as FDM/FFF, SLS, DLP, and DIW. Overall, realising credible waste-to-value pathways requires aligning technical performance targets with regulatory compliance and developing consistent characterisation protocols to enable the safe and predictable use of soot/rCB-derived fillers in AM. Full article

In-cylinder pressure is a key parameter for evaluating combustion processes and engine performance in spark-ignition engines. However, acquiring high-resolution pressure data over a wide range of operating conditions, particularly under varying spark advance (SA), is costly and technically challenging, which limits its practical application. To address this issue, this study proposes two artificial neural network (ANN)-based methods for in-cylinder pressure reconstruction using data from a three-cylinder gasoline engine under different spark advance conditions. Both methods employ crank angle and spark advance as input features. The first method (ANN-P) directly predicts the in-cylinder pressure profile, achieving a coefficient of determination (R²) exceeding 0.99 on both training and validation datasets, with a root mean square error (RMSE) below 0.13 bar. The model accurately reproduces the pressure evolution throughout the compression, combustion, and expansion processes and enables reliable estimation of indicated mean effective pressure (IMEP). The second method (ANN-HRR) adopts an indirect strategy by first predicting the heat release rate (HRR) and subsequently reconstructing the pressure trace through thermodynamic integration based on a single-zone model. This approach avoids error amplification associated with numerical differentiation and demonstrates improved accuracy in predicting combustion phasing metrics, such as CA10 and CA50. The results indicate that both methods effectively capture the influence of spark timing on combustion characteristics and peak pressure. While ANN-P provides higher accuracy in pressure reconstruction, ANN-HRR offers superior performance in characterizing combustion features. Overall, this study presents a cost-effective and accurate framework for combustion diagnostics, performance calibration, and control optimization of gasoline engines. Full article

This study aims to show a detailed life cycle assessment (LCA) approach of battery electric vehicles (BEVs) and internal combustion engine vehicles (ICEVs), with an emphasis on determining the electrical carbon intensity at which these vehicles reach life-cycle greenhouse gas (GHG) parity. The analysis was conducted in openLCA v2.0.3 using the Ecoinvent v3.9.1 database under a European use-phase context, with a functional unit of 150,000 km. BEVs were evaluated for two representative lithium-ion battery chemistries (NMC622 and LFP) under three electricity carbon intensity scenarios (50, 400, and 850 g CO₂/kWh), while ICEVs were modeled for both gasoline and diesel pathways. Results show that BEV life-cycle GHG emissions vary between 91 and 221 g CO₂-eq/km across different combinations of electricity mix, battery chemistry, and end-of-life conditions. When isolating electricity carbon intensity as the primary variable under a fixed BEV configuration, emissions increase approximately linearly with grid emission factor. Under average European electricity conditions (400 g CO₂/kWh), BEVs exhibit lower life-cycle GHG emissions than gasoline ICEVs, whereas under coal-intensive electricity conditions (850 g CO₂/kWh) this advantage may be reduced or reversed. The break-even electricity carbon intensity is derived by linear interpolation under a fixed BEV configuration (NMC622, 60 kWh, constant lifetime and EoL conditions), yielding a threshold of approximately 600 g CO₂/kWh. The results further indicate that this threshold is influenced by battery chemistry, production-related emissions, recycling efficiency, and assumed vehicle lifetime. These findings highlight the importance of simultaneous progress in electricity decarbonization and end-of-life recycling to secure the environmental benefits of vehicle electrification, and they provide a threshold-oriented framework for policy-relevant interpretation of comparative vehicle LCA results. Full article

This study presents a technical case study aimed at evaluating the emission performance and regulatory compliance of a low-level ethanol–gasoline blend (E5) produced from cocoa mucilage, applied in a spark-ignition vehicle applied in a spark-ignition vehicle without a catalytic converter, evaluated as a technical case study representative of aging fleet conditions. A controlled within-vehicle experimental design was employed to compare three fuels: Extra gasoline, Super gasoline, and an E5 blend (95% gasoline–5% bioethanol). Exhaust emissions carbon monoxide (CO), hydrocarbons (HC), carbon dioxide (CO₂), oxygen (O₂), and excess air ratio (λ) were quantified under standardized operating conditions (700 and 2500 rpm), following the Ecuadorian standard NTE INEN 2204:2017. Results demonstrate that the E5 blend improves combustion efficiency, reducing CO and HC emissions while increasing CO₂, indicating enhanced carbon oxidation. A systematic shift toward leaner combustion conditions (higher λ and O₂) was also observed, associated with the oxygenated nature of ethanol and improved air–fuel mixture homogeneity. However, regulatory assessment revealed only partial compliance, as all fuels met CO limits but exceeded thresholds for HC, λ, and O₂. Quantitatively, the E5 blend reduced CO emissions by approximately 10–15% compared to Extra gasoline and decreased HC emissions by approximately 15–25%, depending on the operating condition. Additionally, CO₂ emissions showed a slight increase, indicating improved combustion efficiency, while λ and O₂ values reflected a shift toward leaner combustion conditions. Overall, the findings highlight the dominant influence of vehicle mechanical condition on emission performance. Full article

The insufficient octane ratings of commercial fuels limit the efficiency of spark-ignition (SI) engines and worsens emissions due to knock. One alternative approach to mitigate this phenomenon is the Octane-on-Demand (OOD) concept, which adjusts fuel properties onboard the vehicle. Although implementing this advanced technology can contribute to greenhouse-gas (GHG) emission reductions, few studies have examined its impact on combustion characteristics. Accordingly, the objective of this study was to conduct a comprehensive investigation combining fuel characterization and engine testing to evaluate the effectiveness of the OOD strategy in directly suppressing knock in an SI engine, an aspect not previously reported in the literature. The present study was divided into two parts. In the fuel study, optimal conditions for obtaining a candidate fuel—high-octane fractions (HOF)—from gasoline were determined based on chromatographic (GC–MS) analyses. During engine testing, commercial gasoline and blends containing HOF in several proportions were evaluated in a dual-fuel operation under knocking conditions. The maximum amplitude of pressure oscillations (MAPO) was used as the knock indicator. The results demonstrate that temporary fuel enrichment using only gasoline-derived fractions, without additional octane boosters, can effectively suppress knocking combustion. These findings highlight the influence of the OOD concept on the combustion process and provide guidance for optimizing fueling strategy design under knock-limited operation. The study contributes to the growing body of knowledge regarding OOD applications and underscores the need for comprehensive testing under real-world engine operating conditions. Full article

As part of efforts to support the transition toward a zero-carbon future, this research evaluates how the use of natural gas and liquefied petroleum gas under lean burn conditions affects the energy efficiency and environmental outcomes of a diesel engine that has been retrofitted to operate with spark ignition. The assessment of the ecological potential of these low-carbon gaseous fuels was performed at the engine test bed at optimum spark advance set from the condition of achieving maximum brake thermal efficiency (i.e., lowest carbon dioxide emission, CO₂). The results found with lean mixtures are compared to those obtained under stoichiometric conditions, as well as to those from a commercial gasoline engine of comparable size, equally operated at stoichiometry. With lean burning, a clear improvement is observed for all operating points in terms of brake thermal efficiency with respect to the stoichiometric operation. The results highlight a slightly greater improvement when operating with natural gas lean mixtures: between (1.35 and 2.35) percentage points gained in this case, compared to (1.15–2.10) percentage points gained in the case of liquefied petroleum gas. As for CO₂, a maximum 28% reduction when using natural gas is achieved with lean operation with respect to the commercial gasoline engine. Using lean mixtures also brings an important reduction in the engine-out pollutants (carbon monoxide, nitric oxides and particulate number). However, with respect to stoichiometric operation, cyclic variability of the prototype degrades with lean burning but remains lower than one of the baseline commercial gasoline engines. Full article

Data on wildfires (burned area ≥ 100 ha) in South Korea were compiled for 2000–2025 and analyzed together with the national geospatial inventories of hazardous fuel facilities to characterize wildfire-triggered Natech exposure and potential consequence distances. In total, 47 large wildfire events were identified, burning approximately 139,800 ha, with all events occurring during the late winter–spring window (February–May). The spatial overlays of wildfire footprints with facility locations identified 805 gasoline/diesel stations and 227 LPG filling stations located within wildfire-affected districts, corresponding to 14.1% of gas stations and 11.5% of LPG stations in the nationwide facility dataset. Facility exposure was geographically clustered, with the highest concentrations occurring in the eastern and southeastern wildfire hotspots. To quantify potential technological impact extents under wildfire escalation, ALOHA simulations were conducted for a wildfire-induced BLEVE/fireball scenario involving a 10,000 L mobile tank with representative fuels (propane for LPG, n-octane for gasoline, and n-dodecane for diesel). The modeled thermal radiation threat zone radii (10, 5, and 2 kW·m⁻²) were 228/322/502 m for propane, 250/353/550 m for n-octane, and 254/358/559 m for n-dodecane. Together, the event-based wildfire dataset, facility overlay results, and scenario-based impact distances provide an integrated, quantitative basis for assessing wildfire-triggered Natech conditions at the wildland–urban/industrial interface in South Korea. Full article

Commodity and carbon markets are central to natural resource allocation, energy security, and the effectiveness of carbon-pricing policies, yet their risk linkages can intensify sharply during crises. This study examines nonlinear, tail-dependent volatility spillovers across strategically important resource markets using a Quantile-on-Quantile connectedness framework. We employ weekly observed data from 3 January 2010 to 27 April 2025 for eleven futures markets spanning metals (copper, silver, gold), energy (WTI crude oil, heating oil, natural gas, gasoline), agricultural commodities (sugar, coffee, corn), and carbon emissions. Volatility is measured using GARCH-based estimates and embedded in quantile VAR dynamics to map state-contingent shock transmission across the distribution. The results indicate strong asymmetries: connectedness rises markedly in tail regimes and attains its highest levels during the COVID-19 pandemic and the Russia–Ukraine war, relative to the 2015–2016 energy market adjustment. Heating oil, gold, and natural gas frequently act as key volatility transmitters, while the carbon market shifts from a peripheral receiver to a more integrated and sometimes systemic node within the broader commodity risk network. The findings indicate that carbon-price risk propagates through resource markets in a regime-dependent manner, with implications for stress testing, tail-sensitive hedging, and the coordination of resource and climate policy under turbulent market states. Full article

Modern oil refining is faced with the need to maximize raw material processing in the face of fierce competition and environmental requirements. Therefore, the fluid catalytic cracking (FCC) process, key to the production of high-octane gasoline, requires special attention to automation efficiency. Maintaining optimal reactor temperature is a complex scientific and technical challenge, the solution to which directly impacts the yield of target products and the service life of the catalyst. Existing automatic control systems often fail to cope with process transients, nonlinearities, and time delays, making the search for new control approaches highly relevant. The scientific significance of this study lies in the system analysis and quantitative comparison of the effectiveness of classical control laws (P, PI, PID) applied to a plant with a delay. For the first time, a rigorous comparative analysis of tuning methods—analytical (based on phase margin specifications) and automated (using the PID Tuner tool in MATLAB Simulink R2024b)—is performed for a plant characterized as a second-order system with time delay, formed by the series connection of two first-order lag elements with transport delay. The results contribute to automatic control theory by clearly demonstrating the limitations of the proportional controller and the insufficient speed of the integral controller, as well as confirming the hypothesis that a PID law is necessary to achieve a balance between accuracy and response speed under inertia conditions. The practical significance of the work is confirmed by the development of an optimized automatic temperature control system. Using the PID Tuner tool, we achieved critical industrial performance indicators: zero static error, minimal control time (44 s), and acceptable overshoot (9.6%). The system’s robustness (maintaining stability with changes in plant parameters by 30–40%) and its invariance to the main disturbance (catalyst temperature fluctuations), confirmed during simulation, guarantee the viability of the proposed solution under real-world production conditions. Implementation of such a controller will minimize deviations from the process conditions, leading to increased yield of light petroleum products and an extended service life of the expensive catalyst, providing direct economic benefits. Full article

Industrial volatile organic compound (VOC) emissions from large-scale petroleum storage represent a persistent environmental challenge, particularly in agricultural perimeters where atmospheric “breathing” cycles drive localized soil loading. This study investigates the thermodynamic and spatial relationship between gasoline storage emissions and chemical contamination in the Constanta South terminal area using a multi-layered analytical approach. By integrating gas chromatography (GC-MS) headspace analysis with an artificial intelligence (AI) framework utilizing high-order polynomial regression, we quantified the source–path–receptor dynamics across a thermal gradient (12 °C to 70 °C). The results reveal a non-linear surge in VOC emissions at temperatures exceeding 37 °C, characterized by a shift toward medium-weight hydrocarbons (C4–C6) that act as carriers for heavier aromatics. The AI risk model identified a significant spatial gradient, identifying a 500 m “critical zone” where the Hazard Quotient (HQ) is elevated, necessitating technological upgrades like Vapor Recovery Units (VRUs) to mitigate ecological risks. Full article

This study presents a comprehensive comparative analysis of the performance, combustion, and emission characteristics of a single-cylinder, four-stroke spark-ignition engine fueled by commercial gasoline and raw biogas enhanced with cerium oxide (CeO₂) nanoparticles. Raw biogas containing 58% methane was tested without carbon dioxide removal to reflect practical rural applications, while CeO₂ nanoparticles were ultrasonically dispersed in the fuel to promote homogeneous suspension and catalytic activity. Experiments were conducted under wide-open and part-throttle conditions across a range of engine speeds, with simultaneous measurement of brake thermal efficiency, brake-specific fuel consumption, volumetric efficiency, in-cylinder pressure, heat release rate, combustion phasing, and regulated emissions. The results showed that while gasoline consistently outperformed biogas in torque and power due to its higher heating value and flame speed, the addition of CeO₂ significantly reduced the performance gap. For the biogas mode, CeO₂ addition increased brake thermal efficiency by up to 5%, lowered brake-specific fuel consumption by up to 8%, and shifted the start of main combustion to earlier crank angles, indicating faster and more complete combustion, particularly at high loads where higher temperatures activate CeO₂’s catalytic behavior. Emission analysis revealed that CeO₂-blended biogas reduced carbon monoxide emissions by approximately 25% and unburned hydrocarbons by up to 55% compared with gasoline, while nitrogen oxide emissions were consistently 15–22% lower. These reductions were observed across both wide-open and part-throttle conditions, confirming improved combustion completeness and lower peak flame temperatures. These improvements are attributed to CeO₂’s oxygen-storage capability, catalytic oxidation activity, and enhanced thermal conductivity, which collectively strengthen combustion completeness and cyclic stability. The findings demonstrate that nanoparticle-enhanced biogas can substantially improve the environmental and operational viability of spark-ignition engines, offering a practical pathway for integrating renewable gaseous fuels into existing transportation systems. Full article

Road transportation is a major contributor to global CO₂ emissions, yet the influence of road geometry on vehicular emissions remains insufficiently quantified under real-world conditions. This study investigates the effects of horizontal and vertical alignments on CO₂ emissions of a light-duty gasoline passenger vehicle using Portable Emissions Measurement System (PEMS) data collected along a 62.4 km highway section. Six geometric parameters longitudinal grade, cross slope, horizontal curve radius, horizontal curve length, vertical curve radius, and vertical curve length were analyzed in combination with second-by-second vehicle dynamics. The results indicate that transient CO₂ emissions exhibit substantial variability, with instantaneous emission rates exceeding 7.0 g/s under high-load conditions. Longitudinal slope gradient shows the strongest linear association with emission rate (r = 0.63), while speed and acceleration exhibit weaker but statistically significant correlations (r = 0.21 and r = 0.28, respectively). Vehicle Specific Power (VSP), representing integrated tractive power demand, demonstrates stronger association with instantaneous CO₂ emissions than individual kinematic variables. In contrast, cross slope and horizontal curvature parameters display minimal direct correlations under the tested highway conditions. A nonlinear polynomial regression model modestly improves explanatory performance relative to a linear formulation (R² = 0.21 versus 0.15; RMSE approximately 56 g/km), although a substantial portion of variability remains unexplained, reflecting the complexity of transient real-world processes. Overall, vertical alignment and transient driving conditions dominate CO₂ emission variability, while horizontal parameters play supplementary roles. These findings provide empirical evidence for refining emission models and highlight the importance of incorporating vertical alignment into sustainable roadway design and carbon reduction strategies. Full article

In this study, the effect of boron carbide (B₄C), hexagonal boron nitride (hBN), holy super graphene (HSG), and hybrid (B₄C + hBN + HSG) nano-additives on the tribological performance of SAE 5W-30 gasoline engine oil was investigated on Al-Si-based samples (Al 4032) prepared by cutting from a single-cylinder gasoline engine block. The addition of nano-additives regularly increased the kinematic viscosity; the 63.80 mm²/s (BO) value rose to 68.90 mm²/s at the highest level of B₄C and to 70.50 mm²/s in the hybrid oil (≈10.5% increase). The lowest and most stable friction performance was found in the hybrid 0.025 g/25 mL nano-additive oil, which remained between 0.03 and 0.05 during the entire COF test. The EDS mapping and line scan results confirmed the formation of tribofilm by identifying the additive elements (B for B₄C, B and N for hBN, C for HSG) in the wear scar, and the presence of increased O elements showed the restricted formation of tribo-oxidation. The results show that hybrid nano-additive oils provide the most effective friction and wear improvement, especially at low concentrations, while at high additive levels, performance does not show a consistent increase due to particle accumulation and third-body effects. Full article