Selective Catalytic Reduction System Research Articles

Techno-Economic Evaluation of Direct Low-Pressure Selective Catalytic Reduction for Boil-Off Gas Treatment Systems of NH3-Fueled Ships

This study proposes a feasible solution for boil-off gas (BOG) treatment to facilitate NH3 fuel use by ocean-going ships, which is currently considered an alternative fuel for ships. Two systems were designed and analyzed for BOG in IMO Type-A NH3 fuel storage tanks for 14,000 TEU container ships. First, BOG lost inside the storage tank minimized economic losses through the onboard re-liquefaction system. The total energy consumed by the system to process NH3 gas generated in the fuel tank at 232.4 kg/h was 51.9 kW, and the specific energy consumption (SEC) was 0.223 kWh/kg. Second, NH3 was supplied to the direct Low-Pressure Selective Catalytic Reduction (LP-SCR) system to treat marine pollutants generated by combustion engines. The feasible design point was determined by calculating the NH3 feed flow rate using three methodologies. The energy consumed by the direct LP-SCR system was 3.89 and 2.39 kW, and the SEC was 0.0144 at 0.0167 kWh/kg at 100% and 25% load, respectively. The feasibility was indicated via economic analysis. Depending on the life cycle cost, the competitiveness of the re-liquefaction system depends on the price of NH3, where a higher price yields a more economical solution. In conclusion, the direct LP-SCR system has a low overall cost because of its low energy consumption when supplying NH3 and its reduced amount of core equipment.

Ammonia coverage ratio control of a novel two-cell SCR-DeNOX system configuration based on IA-ISMC

To respond the China’s “14th Five-Year Plan” on the control of nitrogen oxides (NOX) emission, urea-based selective catalytic reduction (SCR) system has been widely applied to reduce the NOX emission from the diesel engine. NO2 is no longer a factor to be ignored while refining the SCR-DeNOX system model because of the ship diesel engine's long-term low temperature and oxygen-rich condition, which provides abundant conditions for the creation of NO2. Therefore, a refined eight-state two-cell SCR-DeNOX model is established in this paper. Meanwhile, the trade-off between NOX emission and tailpipe ammonia (NH3) slip is one of the major challenges which SCR-DeNOX system is facing. While meeting NOX emission standards, the requirement of limiting NH3 slip to prevent secondary pollution is becoming increasingly urgent, which needs a better structure or controller. Therefore, a two-cell SCR-DeNOX system with a by-pass valve in front of the NH3 injection is designed, integral sliding mode control based on inversion algorithm (IA_ISMC) is proposed for each cell. Based on the FTP-75 test cycle, there are three points of view are presented. Firstly, compared with the traditional six-state model, simulation results from the refined eight-state SCR-DeNOX model are closer to the experimental data. Secondly, the introduction of the by-pass structure has a mild impact on the NOX conversion efficiency, but can largely limit the NH3 slip. Finally, the controller based on IA_ISMC effectively improves the tracking performance of NH3 coverage ratio and reduces the cost of NH3 injection. To sum up, the refined two-cell SCR-DeNOX system with a by-pass valve based on IA_ISMC can enhance SCR performance and lower costs.

Multi-objective optimization of Fe-based SCR catalyst on the NOx conversion efficiency for a diesel engine based on FGRA-ANN/RF

With the development of industrial level and the increasingly strict emission regulations, selective catalytic reduction (SCR) system is one of the important ways to control NOx emissions from diesel engines. In this study, the effects of intake pressure on pressure and NOx conversion efficiency before and after catalyst were investigated at different loads. In order to improve the SCR efficiency, a multi-objective prediction method based on FGRA-ANN/RF was developed for SCR systems, where the predicted output parameters (the front and back section temperatures of the catalyst, the pressure difference, and the instantaneous catalytic efficiency) and the decision variables (the engine operating parameters). Firstly, the sensitivity analysis of the multi-objective inputs obtained from the ETC condition experiments is performed by the fuzzy grey relation method (FGRA) to select the high sensitivity parameters. Then, the prediction was carried out by artificial neural network (ANN) as well as the improved random forest (RF). The experimental results showed that the evaluation index R2 of RF was generally greater than 0.92 and the improved random forest method had high accuracy and robustness. It is valuable for solving SCR industrial simulation and reducing the hysteresis of ammonia injection response.

Study on the equilibrium constants and initial formation temperature of NH4HSO4 and (NH4)2SO4 in coal‐fired flue gas

AbstractWith the development and utilization of high‐sulfur coal, generating ammonium bisulfate (ABS) and ammonium sulfate (AS) during the coal combustion process has garnered increasing attention. This study examined the formation of ABS and AS under varying temperatures and different initial reactant ratios of SO3 and NH3 by establishing a self‐constructed experimental setup. Based on the experimental data, the equilibrium constant change diagram for the ternary reactions leading to ABS and AS formation was derived. The initial temperatures for forming gaseous ABS and AS were estimated to be approximately 416.33°C and 393.56°C, respectively. Consequently, this study fills the data gap of the equilibrium constant of gaseous ABS formed at high temperatures and furnishes the selective catalytic reduction (SCR) system with quantifiable and notably expedient means of technical analysis.

Adaptive time-step unscented kalman filtering (ATS-UKF) based observer design for urea selective catalytic reduction (SCR) performance of diesel engines

To reduce the number of sensors in the SCR catalyst, state feedback and fault diagnosis information are provided. Firstly, a model based on the coupling of flow, heat transfer, and gas-solid phase catalytic reaction in the SCR system is investigated in this paper. The parabolic partial differential equations are simplified by the variable substitution method and the method of lines approach (MOL). The simplified system of equations is solved by backward differentiation formulas (BDF) with adaptive adjustment time step strategy. Meanwhile, the chemical reaction parameters are accurately calibrated per second using the Levenberg-Marquardt method. Secondly, the ATS-UKF is designed in this paper, and to ensure the synchronisation between the ATS-UKF and the SCR model calculations, the time step of solving the BDF by the SCR model is taken as the time step of propagating the sigma points. Two observation scenarios are assumed: (1) no downstream NH3 concentration sensor, ammonia coverage and downstream NH3 concentration are observed by ATS-UKF; (2) no downstream NOx sensor, ammonia coverage and downstream NOx concentration are observed by ATS-UKF. Finally, the paper carries out bench tests. In the first case, the ammonia coverage obtained by the ATS-UKF reached 0.99 with respect to the model-calculated value R². The mean absolute error (MAE) between the observed and experimental values of the ATS-UKF for the downstream NH3 concentration was 2.76 ppm. In the second case, the ammonia coverage obtained by the ATS-UKF reached 0.99 with respect to the model-calculated value R², and the MAE between the observed and experimental values of the ATS-UKF for the downstream NOx concentration was 1.53 ppm. Environmental ImplicationThe Adaptive Time-Step Unscented Kalman Filtering (ATS-UKF) enhances urea Selective Catalytic Reduction (SCR) in diesel engines, improving environmental outcomes. This method minimizes sensor dependence, enabling more precise SCR system management and effective emission reduction. By advancing emission control technologies, ATS-UKF contributes to global air pollution mitigation efforts, supporting cleaner air and environmental sustainability. Its innovative approach in monitoring and predicting SCR performance marks a significant step towards eco-friendly diesel engine operation.

Mechanism-enhanced data-driven method for the joint optimization of boiler combustion and selective catalytic reduction systems considering gas temperature deviations

A novel optimization framework for boiler combustion and selective catalytic reduction systems (BCSCRSs) that accounts for flue gas temperature deviation and integrates prior knowledge is proposed. Initially, single-factor hot-state experiments on the BCSCRSs are conducted to yield samples for model training. By integrating monotonic relationships from the experimental data into the fusion monotony–support vector regression model, more reasonable estimates and trends of the prediction targets (e.g., CO and NOx concentrations, and unburned combustibles) are obtained compared to those of the model without prior knowledge. Based on this model, the inequality-constrained reference vector-guided evolutionary algorithm is employed for multiobjective combustion optimization considering the constraints of gas temperature deviation in the horizontal pass. The corresponding Pareto-frontier solutions that serve as boundary conditions for the second-stage optimization are obtained. The second-stage optimization comprehensively considers the total operating cost of the BCSCRSs, the denitrification fraction in the NOx formation and removal processes, and safety concerns related to steam tube overheating and ammonia slip. Several noteworthy results are derived: the adjustment of the burner tilt angle presents a trade-off between eliminating gas temperature deviation and reducing NOx formation. An optimal point can be identified by comparing the magnitudes and variations of different BCSCRSs objectives.

Study on the Emission Characteristics of Typical City Buses under Actual Road Conditions

Five typical in-use city buses in Tangshan with different emission standards, fuel power types, and emission control technology routes were selected as the research objects. PEMSs (Portable Emissions Measurement Systems) and OBD (On-Board Diagnostic) remote monitoring technologies were used to conduct research on actual road conditions and emission characteristics. The research aimed to analyze the driving characteristics of different power types of bus engines and after-treatment systems, as well as their impact on emissions. The results indicated that the actual road driving is mainly in the urban and suburban areas of the local region. Additionally, the VSP (Vehicle Specific Power) was found to be distributed in the low- and medium-speed range of mode Bin0~Bin24. The emission rates of each pollutant showed an increasing trend with the increase in VSP. THC and NOx emissions of CNG and LNG buses are significantly higher than those of gas–electric hybrid buses. However, the PM emissions are lower. Therefore, it is necessary to strengthen the NOx emission control of CNG and LNG buses. With the improvement in emission standards and the use of hybrid technology, CO2 and NOx emissions of China IV buses can be reduced by 13% and 53.5% compared with China III buses of the same tonnage. The CO2 and NOx emissions of China V buses using natural gas combustion and an electric mixture are 20% and 18.8% lower than those of China V buses of the same tonnage using only natural gas. In the actual operation of the diesel–electric hybrid bus equipped with the SCR (Selective Catalytic Reduction) system, the working time of the engine is about 35.5 ± 5%, and the working time of the SCR system only accounts for 65.5 ± 12%. The low working conditions of the SCR system and the low temperature of SCR system are the reasons for the high NOx concentration at the rear end of the SCR system when the hybrid electric bus is running at low speeds.

Transition metal doped 2D SiC (TM=Ag, Pd and Rh) as a potential candidate for NOx (x = 1,2) and NH3 sensing

To control the nitrogen oxide emissions in large power plants, accurate monitoring NOx and NH3 gases at the outlet of the selective catalytic reduction system is vital to determine the degree of NOx reaction and adjust the amount of injected NH3. In this study, transition-metal (TM) atoms (Ag, Pd and Rh) doped 2D graphene-like SiC monolayers have been designed based on first-principles calculations. The adsorption and detection characteristics of TM-doped 2D SiC monolayers for NOx (x = 1, 2) and NH3 were systematically investigated. It is found that TM-doped 2D SiC monolayers exhibit strong potential in developing chemical sensors capable of detecting NO, NO2 and NH3. With the decoration of TM atoms in SiC monolayers, the adsorption ability of NO, NO2 and NH3 could be enhanced ascribed to the increased adsorption energy and electrical conductivity. In addition, the TM-SiC monolayers exhibit desirable thermostability at 298 K, 498 K and 798 K. By comparing the variations in atom-to-atom distances, plane-averaged charge density differences, charge transfers, density of states, energy gap variation and the recovery times of TM-doped SiC before and after adsorbed NOx and NH3, we found that Pd-SiC, Ag-SiC and Rh-SiC are optimal for the detection and recovery of NO, NO2 and NH3 gases with adsorption energies − 1.82 eV, − 2.17 eV, − 1.10 eV, respectively.

Study on Urea Crystallization Risk Assessment and Influencing Factors in After-Treatment System of Diesel Engines

In order to meet the increasing pollutants discharge standard, the selective catalytic reduction (SCR) module in the diesel engine after-treatment system is an important means to reduce nitrogen oxide (NOx) emissions. SCR systems are prone to urea crystallization at lower temperatures, especially during the cold-start conditions of diesel engines. In this study, we use the diesel engine after-treatment system test bench to obtain the boundary parameter of the simulation modules, and the urea crystallization risk assessment model of the diesel SCR system is established. Comparing the computational fluid dynamics (CFD) results with the test bench results, it is shown that the predicted urea film distribution of the assessment model is in good agreement with the experimental results. In order to clarify the various factors that affect the urea crystallization risk, this paper conducts a simulation analysis on a nozzle and mixer structure and operating parameters. The CFD results indicate that the increase in urea spray time will increase the maximum urea film thickness on the SCR system mixer surface. Exhaust temperature is the most important influencing factor. When the diesel engine exhaust temperature increases from 190 °C to 300 °C, the maximum urea film thickness decreases by 32 and the urea film mass accumulation decreases by 5%. Exhaust flow has a small impact on urea crystallization risk. When the exhaust flow increases from 300 kg/h to 600 kg/h, the maximum urea film thickness decreases by 39% and the urea film mass accumulation decreases by about 1%. In addition, urea spray rate, nozzle numbers, spray angle, and spray cone angle are also factors that affect urea crystallization risk.

Modelling and Simulation of a Wet Scrubber System

Shipping is a relatively clean transport method with low emissions per ton-mile compared with road transport. However, harmful emissions emitted in coastal areas are a concern, as these affect local air quality and health. To reduce sulphur oxide (SOX ) emissions, the International Maritime Organization (IMO) implemented a global sulphur cap of 0.5 wt% and the 0.1 wt% limit in emission control areas (ECAs). Ship owners can opt for either low sulphur fuels or wet scrubber systems. Wet scrubber systems are a reliable method for reducing SOX emissions with capture rates of up to 98%. These systems may use seawater alkalinity or caustic soda (e.g. closed-loop systems) to neutralise the SOX emissions. However, the dynamic loading of engines can cause large fluctuations in the exhaust flow conditions, and it is unknown how these affect the effectiveness of the scrubber. This study explores the impact of dynamic loads on the SOX removal efficiency of closed-loop wet scrubbers. A dynamic model of a closed-loop wet scrubber utilising fresh water and caustic soda is developed and verified using publicly available data. The model applies the two-film theory to model the gas-liquid interface. Billet and Schultes liquid hold-up theory is used to model the liquid film thickness in the packed bed. Maintaining scrubber efficiency with large load fluctuations or high-frequency fluctuations requires an increased liquid flow. The scrubber control system used a set-point of 75% of the equivalent compliance limit to ensure compliance with the 0.1% ECA limit during load fluctuations. The model and results can be used to develop a more advanced control system for improved scrubber operation and integration with a selective catalytic reduction (SCR) system to demonstrate compliance with the IMO NOX Tier III limit when using high-sulphur heavy fuel oil (HFO).

A MAXIMUM ENTROPY PRINCIPLE MODEL FOR THE INITIALIZATION OF EULERIAN–LAGRANGIAN SPRAY SIMULATIONS

NOx emission regulations have become more and more restrictive for internal combustion engine-powered vehicles, especially for road transport applications. To minimize emissions and comply with regulations, selective catalytic reduction (SCR) systems are the most efficient deNOx technology thanks to the injection of a urea-water solution (UWS). State-of-the-art computational fluid dynamics (CFD) techniques employ Eulerian-Lagrangian frameworks to deal with the two phases of such problems. Still, the associated low velocities of UWS applications make it difficult to use standard breakup models (Kelvin-Helmholtz, Rayleigh-Taylor, Taylor analogy breakup) to generate initial drop size distributions. Hence, these specific studies end up needing experimentally characterized drop size distributions to initialize the CFD simulations or using expensive Eulerian-Eulerian simulations to obtain the outcomes of the primary breakup of the liquid jet. The maximum entropy principle (MEP) allows generating a droplet size-velocity probability distribution function (PDF) from initial injection conditions and injector characteristics while satisfying conservation equations. The most probable PDF curve is determined by the distribution that maximizes the entropy of the problem. A critical Weber number has been proposed to select which droplets will break up subsequently after the initial droplet break up. The model has been validated against experimental results obtained by high-resolution laser backlight imaging. Comparable results have been found and realistic tendencies were achieved, decreasing the expected droplet size with increasing injection pressures. The proposed model could help with introducing alternative breakup models for low-velocity applications without the need for prior droplet size knowledge.

Numerical Study on Compact Design in Marine Urea-SCR Systems for Small Ship Applications

With increasingly stringent emissions legislation, such as that stipulated by the International Maritime Organization, for nitrogen oxide emission reduction in marine diesel engines, the imperative of curtailing nitrogen oxide emissions from marine diesel engines is intensifying. Consequently, the significance of aftertreatment technologies, including diesel particulate filters (DPFs) and selective catalytic reduction (SCR), is poised to grow substantially. In particular, a redesign is required to reduce the size of DPF and SCR systems for application in small ships. In this study, we varied the shape of the filters in DPF and SCR systems, aiming to achieve a distinct flow pattern and enable overall miniaturization. The performance metrics, including the nitric oxide (NO) reduction rate, NH3 slip rate, and pressure drop, of the redesigned models were compared with those of the conventional model. Computational fluid dynamics simulations were used to compare the performance of the redesigned model with that of the conventional model in terms of NO reduction and pressure drop. The redesigned system achieved a NO reduction rate of 6.9% below that of the conventional system, offering additional noteworthy benefits such as a 50% reduction in both pressure and overall length.

Study on the Effect of Niobium on the High Temperature Oxidation Resistance of Ferritic Stainless Steel

More and more cars are installing urea selective catalytic reduction (SCR) systems to solve the problem of exhaust emissions, which often operates at high temperatures in the exhaust system and is prone to failure of the exhaust pipe due to high-temperature oxidation. And niobium containing ferritic stainless steel has been widely used in the manufacturing of automotive exhaust pipes. In order to extend the service life of ferrite stainless steel exhaust pipes, niobium plays a crucial role as an added alloying element. The solid solution and precipitation of niobium in ferritic stainless steel will give ferritic stainless steel more excellent high temperature resistance. The precipitation of Nb can change the organizational structure in steel and refine the grains. However, if the content is not properly controlled, large particles of (Nb, Ti) C will precipitate, which will reduce the high temperature oxidation resistance. In this paper, the high temperature oxidation behavior of two kinds of ferritic stainless steels with different Nb content at 700 °C, 800 °C and 900 °C was studied. The microstructure of the oxide film on the surface of the material, the thickness of the oxide layer on the cross section, the distribution of chemical composition, the existence form and distribution of Nb element were analyzed by SEM, EDS, XRD and TEM. The results show that the higher the niobium content, the better the high temperature oxidation resistance, and the higher the temperature, the more obvious the high temperature oxidation resistance of niobium. This is because the high Nb content steel is easy to precipitate NbN and other Nb-containing precipitates at the grain boundary, which is helpful to the high temperature resistance. In the case of less Nb content, its ability to generate (Nb, Ti) C precipitates and coarsen at high temperatures reduces its high-temperature resistance.

Efficient optimization design of flue deflectors through parametric surrogate modeling with physics-informed neural networks

In engineering applications, deflectors play a vital role in regulating the uniformity of flow field distribution in the selective catalytic reduction (SCR) system, and their optimal design is a topic of great concern. However, traditional optimal design methods often suffer from insufficient prediction accuracy or too high computational cost. This paper develops and verifies an efficient and robust parametric surrogate model for SCR systems based on the physics-informed neural networks (PINNs) framework. This study comprises three progressive steps. (1) We predicted the flow field distribution in the original flue based on the PINNs framework and compared the results qualitatively and quantitatively with the traditional computational fluid dynamics (CFD) method. The results show that the maximum relative error of velocity is 12.6%, and the relative error is within 5% in most areas. (2) For the optimal design of the deflector in the SCR system, a parametric surrogate model based on the PINNs framework is developed, and the model inputs include not only the coordinate variables but also the position parameters of the deflector. The accuracy and efficiency of this parametric surrogate model are also compared with the traditional CFD method. (3) Based on the parametric surrogate model developed above, the deflector optimal position for the research object of this study is found through two quantitative indicators (uniformity coefficient and flue gas energy loss). The results demonstrate that the parameterized model based on PINNs can reduce the computational time to about 14% compared to traditional methods. Finally, the sensitivity analysis of the deflector position parameters is carried out. Overall, the results of this study demonstrate that the parametric surrogate model based on the PINNs framework is an efficient and robust tool for system optimization, design, and autonomous control.

NOx emissions prediction in diesel engines: a deep neural network approach.

The reduction of various nitrogen oxide (NOx) emissions from diesel engines is an important environmental issue due to their negative impact on air quality and public health. Selective catalytic reduction (SCR) has emerged as an effective technology to mitigate NOx emissions, but predicting the performance of SCR systems remains a challenge due to the complex chemistry involved. In this study, we propose using DNN models to predict NOx emission reductions in SCR systems. Four types of datasets were created; each consisted of five variables as inputs. We evaluated the models using experimental data collected from a diesel engine equipped with an SCR system. Our results indicated that the deep neural network (DNN) model produces precise estimates for exhaust gas temperature, NOx concentration, and De-NOx efficiency. Moreover, inclusion of additional input features, such as engine speed and temperature, improved the prediction accuracy of the DNN model. The mean absolute error (MAE) values for these parameters were 3.1°C, 3.04ppm, and 3.65%, respectively. Furthermore, the R-squared coefficient of determination values for the estimates were 0.912, 0.983, and 0.905, respectively. Overall, this study demonstrates the potential of using DNNs to accurately predict NOx emissions from diesel engines and provides insights into the impact of input features on the performance of the model.

Efficiency of limiting nitrogen oxides emissions by exhaust gas recirculation systems of marine internal combustion engines

The subject of this study is systems for ensuring environmental safety of marine internal combustion engines, in particular, technologies for limiting emissions of nitrogen oxides (NOx). The regulatory requirements for reducing emissions are presented in the paper. The main theoretical aspects of the problem of nitrogen oxides formation during combustion in a diesel engine are considered. On the basis of these theoretical aspects the effectiveness of using various methods to achieve the requirements for the permissible level of NOx concentration in the exhaust gases is assessed. Exhaust gas recirculation (EGR) systems and selective catalytic reduction (SCR) systems are considered as the main technologies; they allow achieving the highest indicators of nitrogen oxide emissions control in accordance with the requirements of the Tier 3 standard. Taking into account the peculiarities of the requirements for the design and layout of systems as part of a ship power plant, as well as operational and investment costs, the main attention in the work is paid to systems of indirect influence on the engine in-cylinder processes, which include exhaust gas recirculation systems. Based on the comparison of high and low pressure EGR, the advantages and disadvantages of the designs are determined. It is noted that high-pressure exhaust gas recirculation systems have a number of advantages, which primarily include the compactness and high speed of the system response to changes in operational conditions. On the example of the leading manufacturers developments, the potential capabilities of the high-pressure EGR system and the engine characteristics confirming the effectiveness of its use are demonstrated. Based on the results of the work, a conclusion about the high efficiency and expediency of using exhaust gas recirculation systems to meet the requirements of the current environmental safety standards of ship power plants is made.

Diesel Particle Filter Requirements for Euro 7 Technology Continuously Regenerating Heavy-Duty Applications

The upcoming Euro 7 regulation for Heavy-Duty (HD) vehicles is calling for a further tightening of the Solid Particle Number (SPN) emissions by means of both lowering the applicable limits and shifting the lowest detectable size from 23 nm (SPN23) to 10 nm (SPN10). A late-technology diesel HD truck was tested on a chassis dynamometer in order to assess the necessary particle filtration requirements for a continuously regenerating system. The study showed that passive regeneration under real-world operating conditions can lead to a significant release of SPN10 particles from the current technology Diesel Particulate Filter (DPF) when soot-loaded, even exceeding the currently applicable emission limits. The actual emissions during passive regeneration and following the clean-up of the DPF exceeded the proposed Euro 7 limits by more than an order of magnitude. A prototype DPF, exhibiting a 99% filtration efficiency when clean, was shown to effectively control SPN10 emissions under both operating conditions. The shift to SPN10 also necessitates control of nanoparticles forming inside the Selective Catalytic Reduction (SCR) system, which for the tested truck exceeded the proposed (hot) limit by up to 56%. A dedicated particle filter specifically designed to capture these particles was also evaluated, showing a better than 60% efficiency. The key message of this study is that SPN emissions can be kept at low levels under all conditions.

Design and evaluation of novel static mixers for SCR application

Static mixers are widely used in selective catalytic reduction (SCR) systems to improve the conversion efficiency and service life of the catalyst by better mixing ammonia and the exhaust stream. However, the structure of the mixer needs to be designed carefully to minimise the loss of the system pressure caused by its installation. In this work, experiments and simulations are conducted to evaluate the mixing performance of the static mixers and the system pressure loss. The simulations and experimental results have good agreement. Four novel static mixers are designed and compared with a commercial static mixer to demonstrate their performance. The results show that the box mixer can accomplish less pressure loss (690 Pa) and more homogenous mixing (CoV = 5.4%), and it can thus be used to improve the mixing of ammonia and the exhaust stream in SCR systems.

Monitoring ammonia slip from large-scale selective catalytic reduction (SCR) systems in combined heat and power generation applications with field effect gas sensors

Abstract. Following tightened regulations, selective catalytic reduction (SCR) of nitrogen oxides (NOx) by ammonia (NH3) has over the last couple of decades found wider adoption as a means of reducing NOx emissions from e.g. power production and district heating plants. As in the SCR process NH3 injected into the flue gas reacts with and reduces NOx to nitrogen (N2) and water (H2O) on the surface of a specific catalyst, the NH3 injection has to be dynamically adjusted to match both instant and long-term variations in flue gas nitrogen oxide concentration in order to minimize NOx and NH3 emissions. One possibility of realizing such NH3 dosing control would be the real-time monitoring and feedback of downstream flue gas NOx and NH3 concentrations to the NH3 injection control unit. In this study the sensing characteristics and performance of SiC-based Metal Oxide Semiconductor Field Effect Transistor (MOSFET) sensors with a structurally tailored gas-sensitive gate contact of iridium (Ir) for in situ NH3 monitoring downstream from the SCR catalyst in a combined heat and power (CHP) plant have therefore been investigated and evaluated. The sensor's NH3 sensitivity and selectivity as well as the cross-sensitivity to common flue gas components – oxygen (O2), water vapour (H2O), nitric oxide (NO), nitrogen dioxide (NO2), carbon monoxide (CO), and a model hydrocarbon, ethene (C2H4) – were thereby investigated for relevant concentration ranges under controlled conditions in the laboratory. While, at the prescribed sensor operation temperature of 300 ∘C, the influence of H2O, CO, and C2H4 on the sensor's NH3 concentration reading could be regarded as practically insignificant, a moderate cross-sensitivity was observed between NH3 and NO2 and, to a lesser extent, between NH3 / NO and NH3 / O2. As the NOx concentration downstream from the SCR catalyst under normal SCR and power plant operation is expected to be considerably smaller than the NH3 concentration whenever any appreciable ammonia slip occurs, the observed NH3 / NOx cross-sensitivities may, however, be of less practical significance for ammonia monitoring in real flue gases downstream from the SCR catalyst. Furthermore, if required, the small influence of O2 concentration variations on the sensor reading may also be compensated for by utilizing the signal from a commercially available oxygen sensor. Judging from in situ measurements performed in a combined heat and power plant, the structurally tailored Ir gate field effect sensors also exhibit good NH3 sensitivity over the relevant 0–40 ppm range when directly exposed to real flue gases, offering an accuracy of ±3 ppm as well as low sensor signal drift, the latter most likely to further improve with regular zero-point calibration and thereby make the Ir gate MOSFET ammonia sensor a promising alternative for cost-efficient real-time ammonia slip monitoring or SCR system control in heat and/or power production plants.

Study on Rates of NH3 Adsorption and Desorption in SCR on Various Engine Operation Conditions

Aging diesel engines on the road require the development of an after-treatment system to meet current emission regulations, and a reduction in NOx (Nitrogen Oxide) is significant. The SCR (Selective Catalytic Reduction) system is the after-treatment system for removing NOx from exhaust gas in diesel engines using NH3 (Ammonia) gas. However, the mixing and conversion process between NH3 and NOx in SCR has not been entirely clarified. That process produces NH3 slip in the catalyst surface; the NH3 slip will make the after-treatment performance worse. This study informs how the UWS (Urea Water Solution) injection controlling method can minimize the NH3 slip in the after-treatment system. For this, the NH3 adsorption and desorption rates are important factors for determining the quantity of UWS injection in the system. The NH3 adsorption rate and desorption rate in the SCR are not significantly affected by engine speed, i.e., the exhaust gas flow rate. However, as the exhaust gas temperature increased, the adsorption rate and desorption rate of NH3 in the SCR increased. Through this, the exhaust gas temperature dramatically affects the NH3 adsorption rate and desorption rate in the SCR. Therefore, if the urea water is injected based on this knowledge that the NH3 adsorption amount in the SCR decreases as the exhaust gas flow rate increases, NH3 slip can be suppressed and a high NOx reduction rate can be achieved. Therefore, if the SCR adsorption and desorption mechanisms are analyzed according to the exhaust temperature and the exhaust flow rate in this paper, it can be used as a reference for selecting an appropriate SCR when retrofitting an old diesel engine car.