Search Results (1,713)

Particulate matter (PM2.5) is a critical indicator of air quality and has significant health implications. This study presents the development and evaluation of a custom-built PM2.5 device, named the P-Tracker, designed to offer an accessible alternative to commercially available air quality monitors. This paper presents the design framework used to address the requirements of a low-cost, accessible device which meets the performance of existing commercial systems. Step-by step build instructions are provided for hardware and software development and connection to the P-tracker open access website which displays the data and interactive map. To demonstrate the performance, the P-Tracker was compared against leading consumer devices, including the AtmoTube Pro by AtmoTech Inc., Flow by Plume Labs, View Plus by Airthings, and the Smart Citizen Kit 2.1 by Fab Lab Barcelona, across four controlled tests. The tests included: (1) a controlled paper combustion test in which all devices were exposed to combustion aerosols in a sealed environment alongside the DustTrak 8530 (TSI Incorporated, Shoreview, MN, USA), used as the gold standard reference, where the P-Tracker achieved a Pearson correlation of 0.99 with DustTrak over the final measurement period; (2) an outdoor test comparing readings with a stationary reference sensor, Osiris (Turnkey Instruments Ltd., Rudheath, UK), where the P-Tracker recorded a mean PM2.5 concentration of 3.08 µg/m³, closely aligning with the Osiris measurement of 3.53 µg/m³ and achieving a Pearson correlation of 0.77; (3) a controlled indoor air quality assessment, where the P-Tracker displayed stable readings with a standard deviation of 0.11 µg/m³, comparable to the AtmoTube Pro; and (4) a real-world kitchen environment test, where the P-Tracker effectively captured fluctuations in PM2.5 levels due to cooking activities, maintaining a consistent response with the DustTrak reference. The results indicate varied degrees of agreement across devices in different conditions, with the P-Tracker demonstrating strong correlation and low error margins in high-pollution and controlled scenarios. This research underscores the potential of open-source, low-cost, custom-built air quality sensors which may be developed and deployed by communities to provide hyperlocal measurements of air pollution. Full article

This study presents a comparative investigation of combustion and emission characteristics in a two-stroke MAN 5S35ME-B9.5 marine diesel engine equipped with a Controllable Pitch Propeller and an Exhaust Gas Recirculation system. Experimental data were obtained from both factory shop tests conducted under the IMO NOx Technical Code 2008 E2 cycle and sea trials performed onboard the T/S Baek-Kyung. Engine performance was evaluated under Tier II-FB, ecoEGR, and Tier III modes, focusing on specific fuel oil consumption, peak cylinder pressure, exhaust gas temperature, and regulated emissions. Results indicate that Tier III achieved the greatest NOx abatement, reducing emissions by up to 76.4% (1464 to 346 ppm), but with penalties of 16.8% higher SFOC and 45.2% higher CO₂ concentration. EcoEGR provided a more favorable compromise, reducing NOx by 52.3% while limiting SFOC increases to ≤15.4% and CO₂ increases to ≤30.9%. Strong correlations were observed between NOx, Pmax, and exhaust gas temperature, reaffirming fundamental trade-offs, while O₂ and CO correlations showed greater variability under sea operation. Despite operational scatter, sea trial results reproduced the key patterns observed in shop tests, confirming robustness across conditions. Overall, this correlation-based analysis provides quantified evidence of performance–emission trade-offs and offers a practical foundation for optimizing CPP-equipped two-stroke engines under varying EGR strategies. Full article

The cement industry accounts for approximately 7–8% of global CO₂ emissions, primarily due to energy-intensive clinker production and limestone calcination. With cement demand continuing to rise, particularly in emerging economies, decarbonization has become an urgent global challenge. The objective of this study is to systematically map and synthesize existing evidence on technological pathways, policy measures, and economic barriers to four core decarbonization strategies: clinker substitution, energy efficiency, alternative fuels, as well as carbon capture, utilization, and storage (CCUS) in the cement sector, with the goal of identifying practical strategies that can align industry practice with long-term climate goals. A scoping review methodology was adopted, drawing on peer-reviewed journal articles, technical reports, and policy documents to ensure a comprehensive perspective. The results demonstrate that each mitigation pathway is technically feasible but faces substantial real-world constraints. Clinker substitution delivers immediate reduction but is limited by SCM availability/quality, durability qualification, and conservative codes; LC₃ is promising where clay logistics allow. Energy-efficiency measures like waste-heat recovery and advanced controls reduce fuel use but face high capital expenditure, downtime, and diminishing returns in modern plants. Alternative fuels can reduce combustion-related emissions but face challenges of supply chains, technical integration challenges, quality, weak waste-management systems, and regulatory acceptance. CCUS, the most considerable long-term potential, addresses process CO₂ and enables deep reductions, but remains commercially unviable due to current economics, high costs, limited policy support, lack of large-scale deployment, and access to transport and storage. Cross-cutting economic challenges, regulatory gaps, skill shortages, and social resistance including NIMBYism further slow adoption, particularly in low-income regions. This study concludes that a single pathway is insufficient. An integrated portfolio supported by modernized standards, targeted policy incentives, expanded access to SCMs and waste fuels, scaled CCUS investment, and international collaboration is essential to bridge the gap between climate ambition and industrial implementation. Key recommendations include modernizing cement standards to support higher clinker replacement, providing incentives for energy-efficient upgrades, scaling CCUS through joint investment and carbon pricing and expanding access to biomass and waste-derived fuels. Full article

With the increasing emphasis on environmental protection and sustainable development, improving air pollution control technology has become imperative. In this study, Ce-based catalysts are used as research objects to explore the effects of hydrothermal aging on their performance in oxidizing PM. Different Mn, Na, Pt and Zr-doped Ce-based catalysts were prepared based on the impregnation method and the PM oxidation performance of Ce-based catalysts before and after hydrothermal aging was investigated using thermogravimetric experiments, and the catalytic activity change pattern of fresh/hydrothermal aging Ce-based catalysts was analyzed by comparing the comprehensive combustion index S and combustion stability index Rw, revealing the PM oxidation process. The conclusion showed that the cerium-based catalyst significantly enhanced the oxidation efficiency of PM compared with PU. By comparing the performance of different metal-modified catalysts, it was found that the order of activity was: Pt > Na > Mn > Zr. With the metal doping increased, only the comprehensive combustion index S and combustion stability index Rw of Na/CeO₂ catalysts decreased. After hydrothermal aging treatment, the Zr/CeO₂ catalysts showed the best hydrothermal aging resistance, and the comprehensive combustion index S and combustion stability index Rw remained stable (<5%). Ce-based catalysts have the strongest to weakest hydrothermal aging resistance in the following order: Zr > Mn > Pt > Na. This study not only provides an important scientific reference for the application of Ce-based catalysts in the field of environmental purification but also contributes new ideas and methods to promote the green and sustainable development of air pollution control technology. Full article

Small-scale thermal treatment systems can provide environmentally improved sewage sludge treatment due to processing sludge locally, which lowers transport costs and emissions. However, the combined effect of confined volume and complex sludge properties makes achieving strict regulations on flue gas emissions and end-ash composition challenging. System development thus requires the use of advanced, 3D CFD simulation supported studies. An important step forward regarding these is the application of combustion models which introduce tailored surrogate fuels and apply detailed chemical kinetics to achieve a high-fidelity combustion description in confined volumes. In relation to this, the paper presents an innovative computationally efficient sewage sludge surrogate-based combustion model capable of defining surrogates, tailored to sewage sludge, and capable of providing detailed insight into reaction zone evolution in small-scale sludge incineration systems. The validity of the proposed model and surrogates is confirmed via simulated temperatures differing from measurements in the small-scale system for less than 30 K. The validated model of a small-scale system is used in the parametric analysis of variable air–fuel ratios, higher fuel moisture presence, varying bed temperature, and varying thermal power to enable unprecedentedly accurate and efficient definition of design features of small-scale systems and to provide key guidelines for operation optimization. Full article

In this study, the decarburization behavior in basic oxygen furnace (BOF) steelmaking was investigated based on the multi-zone reaction mechanism. The contributions of the main reaction zones to decarburization were clarified, and the effects of key factors—including the effective reaction amount in the main reaction zones, the post combustion ratio (PCR) in auxiliary reaction zones, and the carbon content of scrap steel—on decarburization behavior were quantitatively analyzed. The results indicate that decarburization predominantly occurs in the jet impact reaction zone (approximately 76% of the total decarburization), followed by the emulsion and metal droplet reaction zone (approximately 14%) and the bulk metal and slag reaction zone (approximately 10%). Variations in the effective reaction amount for the main reaction zones significantly affect both the decarburization rate and the endpoint carbon content, with the direct oxidation decarburization reaction in the jet impact reaction zone being the dominant factor. In addition, the PCR in the gas homogenization zone of the auxiliary reaction zones determines the distribution ratio of effective reaction oxygen, while the melting behavior of scrap steel in the metal homogenization zone plays a critical role in the precise control of the endpoint carbon content. This study provides a quantitative elucidation of the effects of different reaction zones on decarburization behavior, offering a foundation for the precise control of endpoint carbon content in BOF steelmaking. Full article

Solar-electric propulsion offers a practical way to lengthen the endurance of small fixed-wing unmanned aerial vehicles while removing the noise, emissions, and upkeep that come with combustion engines. This work describes and tests a lightweight platform that couples a flexible thin-film photovoltaic array, a high-efficiency power-tracking controller, and a lithium–polymer battery to an electric brushless drivetrain. A ground-based flight emulator reproducing steady cruise allows continuous logging of the electrical flows between panel, battery, and motor. The results show that the solar subsystem can sustain most of the cruise demand, so the battery is called on only sparingly and is even able to recharge when sunlight is higher than a specific threshold. This balance translates into a clear endurance gain without upsetting the aircraft’s weight or handling. Full article

Fuel cell trucks are a promising solution to reduce the disproportionately high greenhouse gas emissions of heavy-duty long-haul transportation. However, unlike conventional diesel vehicles, they lack combustion engine waste heat for cabin heating. As a result, electric heaters are often employed, which increase auxiliary energy consumption and reduce driving range. To address this challenge, advanced control strategies are needed to improve heating efficiency while maintaining passenger comfort. This study proposes and validates a methodology for implementing Model Predictive Control (MPC) in the cabin heating system of a fuel cell truck. Vehicle experiments were conducted to characterize dynamic heating behavior, passenger comfort indices, and to provide validation data for the mathematical models. Based on these models, an MPC strategy was developed in a Model-in-the-Loop simulation environment. The proposed approach achieves energy savings of up to 8.1% compared with conventional control using purely electric heating, and up to 21.7% when cabin heating is coupled with the medium-temperature cooling circuit. At the same time, passenger comfort is maintained within the desired range (PMV within ±0.5 under typical winter conditions). The results demonstrate the potential of MPC to enhance the energy efficiency of fuel cell trucks. The methodology presented provides a validated foundation for the further development of predictive thermal management strategies in heavy-duty zero-emission vehicles. Full article

This study explores the combustion behavior of three biomass pellet types—wood (W), sunflower husk (SH), and a mixture of wood and sunflower husks (W/SH)—in a residential hot water boiler. Experiments were carried out under two air supply regimes (40%/60% and 60%/40% primary to secondary air) to measure flue gas concentrations of oxygen (O₂), carbon monoxide (CO), and nitrogen oxides (NO_x). The results indicate that SH pellets generate the highest emissions (CO: 1095.3 mg/m³, NO_x: 679.3 mg/m³), while W pellets achieve the lowest (CO: 0.3 mg/m³, NO_x: 194.1 mg/m³). The mixed W/SH pellets produce intermediate values (CO: 148.7 mg/m³, NO_x: 201.8 mg/m³). Overall boiler efficiency for all tested fuels ranged from 90.3% to 91.4%. Numerical simulations using ANSYS CFX (2024 R2 (24.2)) were performed to analyze temperature distribution, flue gas composition, and flow fields, showing good agreement with experimental outlet temperature and emission trends. These findings emphasize that both pellet composition and air distribution significantly influence efficiency and emissions, offering guidance for optimizing small-scale biomass boiler operation. Full article

The increasing share of renewable energy sources in power grids demands greater load flexibility from thermal power plants. Circulating Fluidized Bed (CFB) combustion systems, while offering fuel flexibility and high thermal inertia, face challenges in maintaining hydrodynamic and thermal stability during load transitions. This study investigates partial flue gas recirculation (FGR) as a strategy to enhance short-term load flexibility in a 1 MW_th CFB pilot plant fired exclusively with solid recovered fuel. Two experimental test series were conducted. Under conventional operation, where fuel and fluidization air are reduced proportionally, load reductions to 86% and 80% led to operating regime shift. Particle entrainment from the riser to the freeboard and loop seal decreased, circulation weakened, and the temperature difference between bed and freeboard zone increased by 71 K. Grace diagram analysis confirmed that the system approached the boundary of the circulating regime. In contrast, the partial FGR strategy maintained total fluidization rates by replacing part of the combustion air with recirculated flue gas. This stabilized pressure conditions, sustained particle circulation, and limited the increase in the temperature difference to just 7 K. Heat extraction in the freeboard remained constant or improved, despite slightly lower flue gas temperatures. While partial FGR introduces a minor efficiency loss due to the reheating of recirculated gases, it significantly enhances combustion stability and enables low-load operation without compromising fluidization quality. These findings demonstrate the potential of partial FGR as a control strategy for flexible, waste-fueled CFB systems and supports its application in future low-carbon energy systems. Full article

The paper presents the application of high-speed flame imaging combined with convolutional neural networks (CNNs) for determining different states of biomass–coal co-combustion in terms of thermal power and excess air coefficient. The experimental setup and methodology used in a laboratory-scale co-combustion system are described, highlighting tests conducted across nine defined operational variants. The performance of several state-of-the-art CNN architectures was examined, focusing particularly on those achieving the highest classification metrics and exploring the dependence of input image resolution and applying a transfer learning paradigm. By benchmarking various CNNs on a large, diverse image dataset without preprocessing, the research advances intelligent, automated control systems for improved stability, efficiency, and emissions control, bridging advanced visual diagnostics with real-time industrial applications. The summary includes recommendations and potential directions for further research related to the use of image data and machine learning techniques in industry. Full article

Hybrid systems have recently become widespread in motorsports due to advantages such as increased power through the use of electric motors and reduced fuel consumption thanks to regenerative braking. Achieving high performance from a hybrid powertrain requires a highly efficient control system for managing power flows between the internal combustion engine (ICE) and the electric motor. The goal of this study is to develop a control algorithm for a hybrid powertrain aimed at minimizing lap times compared to traditional vehicles equipped with an ICE. To achieve this objective, a mathematical vehicle model based on the tractive balance equation was used. Lap time simulations were conducted for both a traditional ICE vehicle and a hybrid system. The results showed that the hybrid vehicle has a significant advantage in lap time; however, the energy from a fully charged battery would only be sufficient for two laps. To address this issue, a hybrid system control algorithm is proposed, which maintains the energy balance of the battery throughout the entire lap while still providing better lap times compared to a vehicle equipped with a traditional ICE. Full article

Excessive exhaust backpressure (EBP) in modern diesel engines disrupts gas exchange, increases residual gas fraction (RGF), and reduces combustion efficiency. Traditional experimental approaches, including simulations and bench testing, are often time-consuming and costly, which has driven growing interest in artificial neural networks (ANNs) for accurately modelling complex engine behavior. This research introduces an ANN model designed to predict the impact of EBP on the performance and emissions of a diesel engine across varying compression ratio (CR) of 12, 14, 16, and 18 and engine load (25%, 50%, 75%, and 100%) conditions. The ANN model was developed and optimised using genetic algorithms (GA) and particle swarm optimisation (PSO). It was then trained using data from an experimentally validated one-dimensional computational fluid dynamics (1D-CFD) model developed through GT-Power GT-ISE v2024, simulating engine responses under variation CR, load, and EBP conditions. The optimised ANN architecture, featuring an optimal (3-14-10) configuration, was trained using the Levenberg–Marquardt back propagation algorithm. The performance of the model was assessed using statistical criteria, including the coefficient of determination (R²), root mean square error (RMSE), and k-fold cross-validation, by comparing its predictions with both experimental and simulated data. Results indicate that the optimised ANN model outperformed the baseline ANN and other machine learning (ML) models, attaining an R² of 0.991 and an RMSE of 0.011. It reliably predicts engine performance and emissions under varying EBP conditions while offering insights for engine control, optimisation, diagnostics, and thermodynamic mechanisms. The overall prediction error ranged from 1.911% to 2.972%, confirming the model’s robustness in capturing performance and emission outcomes. Full article

This paper investigates the combustion characteristics of promising decarbonized fuel mixtures—methane/hydrogen (CH₄/H₂) and ammonia/hydrogen (NH₃/H₂)—with a focus on how they interact with external electric fields. The key findings are that these flames possess significant electrochemical properties, allowing for non-intrusive control over their stabilization, shape, and structure using relatively weak electric fields. The research combines experimental techniques like volt-ampere characteristic (VAC) measurement and advanced Hilbert visualization to analyze flame deformation, temperature distribution, and species concentration. Two orientations of the electric field were considered: transverse and longitudinal. For the transverse field, an assessment of the degree of flame deformation was made, indicating the preservation of the laminar combustion regime. In the longitudinal electric field, a change in the combustion stabilization mode was observed, which was detected through visualization and current-voltage characteristics (CVC). Full article

The escalating global demand for primary energy—still predominantly met by conventional carbon-based fuels—has led to increased atmospheric pollution. This underscores the urgent need for alternative energy strategies capable of reducing carbon emissions while meeting global energy requirements. Hydrogen, as a clean combustible fuel, offers a promising alternative to hydrocarbons, producing neither soot, CO₂, nor unburned hydrocarbons. Although nitrogen oxides (NO_x) are the primary combustion by-products, their formation can be mitigated by controlling flame temperature. This study investigates the viability of hydrogen as a clean energy vector by simulating an unsteady, turbulent, non-premixed hydrogen jet flame interacting with an air co-flow. The numerical simulations employ the Unsteady Reynolds-Averaged Navier–Stokes (URANS) framework for efficient and accurate prediction of transient flow behavior. Turbulence is modeled using the Shear Stress Transport (SST k-ω) model, which enhances accuracy in high Reynolds number reactive flows. The combustion process is described using a presumed Probability Density Function (PDF) model, allowing for a statistical representation of turbulent mixing and chemical reaction. The simulation results are validated by comparison with experimental temperature and mixture fraction data, demonstrating the reliability and predictive capability of the proposed numerical approach. Full article