Search Results (363)

The overall efficiency of combining denitrification and volatile organic compound (VOC) removal through selective catalytic reduction (SCR) technology is currently mainly limited by the VOC removal aspect. However, existing studies have not studied the microscopic mechanism of the interaction between VOCs and catalysts, failing to provide a theoretical basis for catalysts. Therefore, this work explored the interaction mechanisms between SCR catalysts doped with different additives and typical VOCs (acetone and toluene) in flue gas based on density functional theory (DFT) calculations. The results showed that the VNi-TiO₂ surface exhibited a high adsorption energy of −0.80 eV for acetone and a high adsorption energy of −1.02 eV for toluene on the VMn-TiO₂ surface. Electronic structure analysis revealed the VMn-TiO₂ and VNi-TiO₂ surfaces exhibited more intense orbital hybridization with acetone and toluene, promoting charge transfer between the two and resulting in stronger interactions. The analysis of temperature on adsorption free energy showed that VMn-TiO₂ and VNi-TiO₂ still maintained high activity at high temperatures. This work contributes to clarifying the interaction mechanism between SCR and VOCs and enhancing the VOC removal efficiency. Full article

In response to increasingly stringent emission regulations, low-carbon fuels have received significant attention as sustainable energy sources for internal combustion engines. This study investigates four representative low-carbon fuels, methane, methanol, hydrogen, and ammonia, by systematically summarizing their combustion characteristics and emission profiles, along with a review of existing after-treatment technologies tailored to each fuel type. For methane engines, unburned hydrocarbon (UHC) produced during low-temperature combustion exhibits poor oxidation reactivity, necessitating integration of oxidation strategies such as diesel oxidation catalyst (DOC), particulate oxidation catalyst (POC), ozone-assisted oxidation, and zoned catalyst coatings to improve purification efficiency. Methanol combustion under low-temperature conditions tends to produce formaldehyde and other UHCs. Due to the lack of dedicated after-treatment systems, pollutant control currently relies on general-purpose catalysts such as three-way catalyst (TWC), DOC, and POC. Although hydrogen combustion is carbon-free, its high combustion temperature often leads to elevated nitrogen oxide (NO_x) emissions, requiring a combination of optimized hydrogen supply strategies and selective catalytic reduction (SCR)-based denitrification systems. Similarly, while ammonia offers carbon-free combustion and benefits from easier storage and transportation, its practical application is hindered by several challenges, including low ignitability, high toxicity, and notable NO_x emissions compared to conventional fuels. Current exhaust treatment for ammonia-fueled engines primarily depends on SCR, selective catalytic reduction-coated diesel particulate filter (SDPF). Emerging NO_x purification technologies, such as integrated NO_x reduction via hydrogen or ammonia fuel utilization, still face challenges of stability and narrow effective temperatures. Full article

Denitrification technology in thermal power plants plays a critical role in reducing nitrogen oxide (NOx) emissions, thereby improving air quality and mitigating climate change. This study conducts a numerical simulation of the SCR (Selective Catalytic Reduction) system at the Chizhou Power Plant to optimize its flow field configuration. The original system exhibited severe flow non-uniformity, with local maximum velocities reaching 40 m/s and a velocity deviation coefficient of 28% at the inlet of the first catalyst layer. After optimizing the deflector design, the maximum local velocity was reduced to 21 m/s, and the velocity deviation coefficient decreased to 14.1%. These improvements significantly enhanced flow uniformity, improved catalyst efficiency, and are expected to extend equipment service life. The findings provide a practical reference for the retrofit and performance enhancement of SCR systems in similar coal-fired power plants. Full article

Combustion processes in compression ignition engines lead to the inevitable generation of nitrogen oxides, which cannot be limited to the currently desired levels just by optimising the in-cylinder processes. Therefore, simulation-based engine development needs to include all engine-related aspects which contribute to tailpipe emissions. Among them, the SCR (selective catalytic reduction) aftertreatment-related processes, such as urea–water solution injection, urea decomposition, mixing, NOx catalytic reduction, and deposits’ formation, are the most challenging, and require as much attention as the processes taking place inside the cylinder. Over the last decade, the urea-SCR aftertreatment systems have evolved from underfloor designs to close-coupled (to the engine) architecture, characterised by the short mixing length. Therefore, they need to be tailor-made for each application. This study presents the CFD-based development of a multi-platform SCR system with a short mixing length for mobile non-road applications, compliant with Stage V NRE-v/c-5 emission standard. It combines multiphase dispersed flow, including wall wetting and urea decomposition kinetic reaction modelling to account for the critical aspects of the SCR system operation. The baseline system’s design was characterised by the severe deposit formation near the mixer’s outlet, which was attributed to the intensive cooling in the mounting area. Moreover, as the simulations suggested, the spray was not appropriately mixed with the surrounding gas in its primary zone. The proposed measures to reduce the wall film formation needed to account for the multi-platform application (ranging from 56 to 130 kW) and large-scale production capability. The performed simulations led to the system design, providing excellent UWS–exhaust gas mixing without a solid deposit formation. The developed system was designed to be manufactured and implemented in large-scale series production. Full article

Based on engine bench testing, this study investigated the effect of diesel oxidation catalytic converter (DOC) formulations on the gaseous emissions performance of diesel engines equipped with a DOC+ catalyzed diesel particulate filter (CDPF)+selective catalytic reduction (SCR) system after the treatment system. The experimental results indicate that changes in DOC formulations have no significant effect on engine fuel economy. As the precious metal loading increases and the Pt/Pd ratio decreases, the T₅₀ for CO and HC decreases, and the low-temperature conversion rates (<300 °C) for CO and HC increase. However, as the temperature continues to rise, the beneficial effect of increased precious metal loading or Pd on CO and HC conversion rates gradually weakens. The average conversion rates in the high-temperature range (≥300 °C) show little difference. The NO conversion rate increases with increasing precious metal loading. The NO conversion rate is more sensitive to Pt content, with higher Pt content formulations promoting NO oxidation, contrary to the trends observed for CO and HC conversion rates. When the SCR inlet temperature is low, high NO₂ concentrations are beneficial for improving the SCR’s NOx conversion efficiency. When the SCR inlet temperature is high, the SCR’s NOx conversion efficiency exceeds 90% with no significant differences. No significant impact of DOC formulation changes on CDPF pressure drop under external conditions was observed. Full article

Progressive research on reducing engine emissions is highly valued due to the emissions’ significant environmental and health impacts. This comprehensive comparative study examines the catalytic efficiency of manganese (Mn) and cerium silica (Ce-Si) synthesis catalyst-based molds in a diesel engine using a selective catalytic reduction (SCR) technique with diesel and diesel–plastic oil blend (DPB) (B50). In addition to Fourier transform infrared spectroscopy (FTIR) studies, X-ray diffraction (XRD), scanning electron microscopy (SEM), and the Brunauer–Emmett–Teller (BET) method are utilized to characterize the produced molds before and after exhaust gas passes. The Ce-Si-based mold demonstrates superior redox capacity, better adsorption capacity, and better thermal stability, attributed to enhanced oxygen storage and structural integrity compared to the Mn-based mold. Under minimum load conditions, nitrogen oxide (NO) reduction efficiency peaks at 80.70% for the Ce-Si-based mold in the SCR treatment with DPB fuel. Additionally, significant reductions of 86.84%, 65.75%, and 88.88% in hydrocarbon (HC), carbon monoxide (CO), and smoke emissions, respectively, are achieved in the SCR treatment under optimized conditions. Despite a wide temperature range, Ce-Si-based mold promotes high surface area and superior gas diffusion properties. Overall, the Ce-Si-based mold provides efficient emission control in diesel engines, which paves a path for developing better environmental sustainability. The outcomes contribute to advancing environmental sustainability by supporting the achievement of SDGs 7, 11, and 13. Full article

Metal–organic frameworks (MOFs) are a novel type of porous crystalline materials assembled from metal ions and organic linkers. Their derivatives can inherit characteristics such as high specific surface area, tunable porosity, and unique topological structures, which make MOF-derived metal oxides ideal catalysts for the selective catalytic reduction (SCR) of NO_x. This review focuses on the synthetic strategies of MOF-derived metal oxides and the latest progress of oxides derived from various typical MOFs materials (including MILs, ZIFs, UiO, BTC series, MOF-74, MOF-5, and Prussian blue analogs, etc.) in the catalytic reduction in NO_x, and analyzes the mechanisms for the enhanced catalytic performance. In addition, the challenges and prospects of MOF derivatives in catalytic applications are discussed. It is hoped that this review will help researchers understand the latest research progress of MOF-derived metal oxide materials in the catalytic removal of NO_x pollution. Full article

The combustion of biomass fuels releases alkali metals, which induce severe catalyst deactivation due to alkali metal (K) poisoning in low-temperature ammonia selective catalytic reduction (NH₃-SCR) systems. To address this issue, this study developed a series of heteropoly acid (HPA)-modified Ce/AC catalysts prepared via incipient wetness impregnation. The low-temperature NH₃-SCR performance (80–200 °C) of these catalysts was systematically evaluated, with particular emphasis on their denitrification activity and K-poisoning resistance. The silicotungstic-acid (TSiA)-modified Ce/Ac (TSiA-Ce/AC) catalyst showed an improvement (>20%) in NO conversion activity under the K poisoning condition. The superior K-poisoning resistance of the TSiA-Ce/AC catalyst was attributed to the high density of Brønsted acidic sites and the strong K binding affinity of TSiA, which together protected active sites and preserved the standard SCR reaction pathway under K contaminations. This study proposes a novel strategy for enhancing catalyst K resistance in low-temperature NH₃-SCR systems. Full article

This study proposes a data-driven optimization framework to enhance emission control performance in diesel engine selective catalytic reduction (SCR) systems under transient operating conditions. A one-dimensional SCR model was constructed in GT-Power, and simulation datasets were generated using experimentally measured inputs from the World Harmonized Transient Cycle (WHTC), with representative emission responses obtained by varying fixed ammonia-to-NOx (A/N) ratios. Building on these datasets, a hybrid prediction model combining Long Short-Term Memory (LSTM) networks and multi-head attention mechanisms was developed to accurately forecast SCR outlet NH₃ leakage and NOx emissions. The model exhibited high predictive accuracy, achieving R² values exceeding 0.977 and low RMSE across training, validation, and test sets. Based on the model predictions, a constrained dynamic multi-objective optimization strategy was implemented to adaptively adjust ammonia dosing, aiming to simultaneously minimize NH₃ leakage and NOx emissions. The optimized NH₃ injection profiles were validated through reapplication in the GT-Power simulation environment. Compared to the baseline fixed-ratio control strategy, the proposed approach reduced NH₃ leakage and NOx emissions by 34.40% and 11.15%, respectively, as determined for the transient segment of the WHTC cycle. These results demonstrate the effectiveness of integrating physics-based simulation, deep learning prediction, and dynamic optimization for improving aftertreatment adaptability and emission compliance in real-world diesel engine applications. All reported values are based on a single simulated WHTC cycle without statistical uncertainty analysis. Full article

The selective catalytic reduction of NO_x with CH₄ (CH₄-SCR) holds the potential to simultaneously abate harmful NO_x and CH₄ greenhouse gases. In this study, a series of bimetallic M-In/H-SSZ-39 catalysts (where M represents Cr, Co, Ce, and Fe) were prepared via an ion exchange method and subsequently evaluated for their CH₄-SCR activity. The influences of the preparation parameters, including the metal ion concentration and calcination temperature, as well as the operating conditions, such as the CH₄/NO ratio, O₂ concentration, water vapor content, and gas hourly space velocity (GHSV), on the catalytic activity of the optimal Cr-In/H-SSZ-39 catalyst were meticulously examined. The results revealed that the Cr-In/H-SSZ-39 catalyst exhibited peak CH₄-SCR catalytic performance when the Cr(NO₃)₃ concentration was 0.0075 M, the In(NO₃)₃ concentration was 0.066 M, and the calcination temperature was 500 °C. Under optimal operating conditions, namely GHSV of 10,000 h⁻¹, 400 ppm NO, 800 ppm CH₄, 15 vol% O₂, and 6 vol% H₂O, the NO_x conversion rate reached 93.4%. To shed light on the excellent performance of Cr-In/H-SSZ-39 under humid conditions, a comparative analysis of the crystalline phase, chemical composition, pore structure, surface chemical state, surface acidity, and redox properties of Cr-In/H-SSZ-39 and In/H-SSZ-39 was conducted. The characterization results indicated that the incorporation of Cr into In/H-SSZ-39 enhanced its acidity and also facilitated the generation of InO⁺ active species, which promoted the oxidation of NO and the activation of CH₄, respectively. A synergistic effect was observed between Cr and In species, which significantly improved the redox properties of the catalyst. Consequently, the activated CH₄ could further interact with InO⁺ to produce carbon-containing intermediates such as HCOO⁻, which ultimately reacted with nitrate-based intermediates to yield N₂, CO₂, and H₂O. Full article

Platinum was supported on ZSM5 at loadings from 0.1 to 1 wt% and tested for the Selective Catalytic Reduction of NO with H₂ under excess O₂ in a fixed bed reactor to address the issue of NO_x emission abatement from H₂-fueled internal combustion engines avoiding the additional devices for urea storage and injection. To reduce the undesired NO oxidation to NO₂, which is activated by platinum at T > 200 °C, the 0.1%Pt/ZSM5 catalyst was further promoted with sodium. 5 wt% loading of Na strongly inhibited the NO oxidation while giving only a limited impact on the H₂-SCR activity. Unpromoted and Na-promoted catalysts were characterized by XRD, SEM/EDX, N₂ physisorption, and NH₃-TPD to investigate the morphological, structural, and acid properties; H₂ pulse chemisorption and DRIFTS of CO chemisorption were used to investigate the nature of Pt active species. Steady-state and transient operando DRIFTS experiments under NO+H₂+O₂ flow were employed to identify the adsorbed NO_x species interacting with H₂, and reaction intermediates as a function of the reaction conditions. The formation of ammonium intermediates via the reduction of surface nitrate species, playing a key role in H₂-SCR catalyzed by 0.1Pt/ZSM5, was preserved at low Na load whilst NO₂ formation was largely inhibited. Full article

The selective catalytic reduction (SCR) of NO_x emissions by hydrocarbons (HCs) using a silver (Ag)-based catalyst offers significant advantages over conventional SCR systems that rely on ammonia reductants and vanadium-based catalysts. However, the conversion rate of SCR is influenced by several factors, among which catalyst poisoning is a major concern. Toxic metals such as sodium (Na), potassium (K), magnesium (Mg), and calcium (Ca) can degrade catalyst activity and lead to deactivation. Poisoned catalysts suffer from reduced conversion rates and premature deactivation before reaching their intended operational lifespan. In particular, calcium poisoning results in the formation of CaO (calcium oxide), which reacts to produce a CaWO₄ compound that severely impairs SCR performance. This study investigates the role of antimony (Sb) in mitigating Ca-induced deactivation in HC-SCR of NO_x. Five catalysts with varying Sb loadings were prepared and tested to evaluate Sb’s effect on NO_x conversion rate at a space velocity of 30,000 h⁻¹. The results demonstrate that Sb effectively suppresses Ca deactivation, enhancing the conversion rate across all engine test conditions. The highest NO_x conversion rate (95.88%) was achieved using a catalyst with 3% Sb. Full article

Platinum- and/or palladium-containing silica-based supports were applied for the selective catalytic reduction of NO_x with hydrogen (H₂-SCR-DeNO_x). To obtain enhanced activity and N₂ selectivity below 150 °C, we varied the type and loading of noble metals (Pt and Pd both individually and paired, 0.1–1.0 wt.-%), silica-containing supports (ZrO₂/SiO₂, ZrO₂/SiO₂/Al₂O₃, Al₂O₃/SiO₂/TiO₂), as well as the H₂ concentration in the feed (2000–4000 ppm). All of these contributed to enhancing N₂ selectivity during H₂-SCR-DeNO_x over the (0.5 wt.-%)Pt/Pd/ZrO₂/SiO₂ catalyst in the presence of 10 vol.-% of O₂. H₂ was completely consumed at 150 °C. A comparison of the catalytic results obtained during H₂-SCR-DeNO_x,(H₂-)NH₃-SCR-DeNO_x, as well as stop-flow H₂-SCR-DeNO_x and temperature-programmed studies, revealed that in the temperature range between 150 and 250 °C, the continuously coupled or overlaying mechanism of NO reduction by hydrogen and ammonia based on NH₃ formation at lower temperatures, which is temporarily stored at the acid sites of the support and desorbed in this temperature range, could be postulated. Full article

As a major emission pollutant from diesel engines, NOx is extremely harmful to the environment and human health. In order to reduce NOx emissions, countries around the world have been implementing increasingly stringent emissions regulations. The urea injection strategies of the Selective Catalytic Reduction (SCR) system are the main factors affecting NOx emissions and NH₃ slips of diesel engines. In this study, test data were obtained from an engine test stand and a Support Vector Machine (SVM) was developed using the test data to predict NOx conversion efficiency and NH₃ slip. The SVM model was optimized using the Crested Porcupine Optimizer (CPO) to improve its prediction accuracy and was made to replace the mathematical model to save computational time. Finally, the Nondominated Sorting Genetic Algorithm II (NSGA-II) was used to optimize the urea injection volume for all conditions. The optimized urea injection volume maximizes the NOx conversion efficiency of the SCR system while controlling the NH₃ slip within 10 ppm. In addition, based on this method, the urea injection pulse spectrum under full operating conditions was obtained, and the optimized urea injection amount can effectively reduce the NOx accumulation of the WHTC cycle by about 7.5%, as shown through bench testing. Full article

To enhance the management of NOx emissions from hybrid electric buses, this paper develops an instantaneous NOx emission prediction model for hybrid electric buses based on a two-layer stacking ensemble learning method. Seventeen parameters, including operational characteristic parameters of hybrid electric buses, engine operating parameters, and emission after-treatment device operating parameters are selected as input features for the model. The correlation analysis results indicate that the Pearson correlation coefficients of engine coolant temperature and selective catalytic reduction (SCR) after-treatment device temperature show a significant linear negative correlation with instantaneous NOx emission mass. The Mutual Information (MI) analysis reveals that engine intake air volume, SCR after-treatment device temperature and engine fuel consumption have strong nonlinear relationships with instantaneous NOx emission mass. The two-layer stacking ensemble learning model selects eXtreme Gradient Boosting (XGBoost), Random Forest (RF), and an optimized BP neural network as base learners, with a linear regression model as the meta-learner, effectively predicting the instantaneous NOx emission mass of hybrid electric buses. The evaluation metrics of the proposed model—mean absolute error, root mean square error, and coefficient of determination—are 0.0068, 0.0283, and 0.9559, respectively, demonstrating a significant advantage compared to other benchmark models. Full article