Flue Gas Desulfurization Process Research Articles

Investigation of iron oxide supported on activated coke for catalytic reduction of sulfur dioxide by carbon monoxide

In view of the low utilization rate of by-product in limestone-gypsum wet flue gas desulfurization process, a method of catalytic reduction of SO2 to elemental sulfur was proposed. In this work, supported iron catalyst using activated coke as supporter was prepared and characterized. Moreover, the performance of SO2 reduction using CO as reducing agent at various Fe loadings, temperatures, gaseous hourly space velocities and CO/SO2 molar ratios was studied. Research shows that, compared with other metals, the highest catalytic activity is achieved over Fe-based catalyst. The iron sulfide is the main active component during the catalytic reduction reaction, hence the catalyst needs to be presulfided before use. The micropores of activated coke become more abundant after loading Fe, whereas excessive increase of Fe loading may bloke the mesopores and weaken the catalytic activity. Higher reaction temperature, lower GHSV and a stoichiometric molar ratio are conducive to the improvement of SO2 conversion and S yield. The catalytic performance at lower temperatures was further improved by loading Co. When the Co loading is 4 wt%, the SO2 conversion rate reaches 90.9% at 400 °C because loading Co enhances the redox performance of the catalyst surface. The findings are instructive for the development of cost-effective carbon-based catalysts for resource recovery of sulfur.

ZIF-67-derived Co@NC as an efficient catalyst for magnesium sulfite oxidation in the flue gas desulfurization process

Magnesium desulfurization is a wet flue gas desulfurization (WFGD) technology widely used in China, however, the low oxidation rate of magnesium sulfite (MgSO3), a byproduct of WFGD, causes the subsequent oxidation and crystallization process to require amount energy. Here, we prepared a cobalt-based nitrogen-doped porous carbon catalyst (Co@NC) using ZIF-67 as a precursor for the efficient catalytic oxidation of MgSO3 generated during magnesium desulfurization. The performance of Co@NC catalysts obtained at an optimal calcination temperature of 650 °C showed that the catalysts with oxidation rates up to 0.1332 mmol·L−1·s−1 of MgSO3 were considerably better than those previously studied, which outperformed the catalysts described in earlier research by a considerable margin. Further studies revealed that the Co@NC’s exceptional catalytic activity was attributed to both its special porous structure and the exposed active Co sites in the organic skeleton. The uniformly dispersed Co species act as the active sites of the Co@NC that can be fully contacted with the reactant. The presence of 0.5 g·L−1 Co@NC increases the MgSO3 oxidation rate by about 14 times compared to the noncatalytic benchmark. A practical tactic is furnished by this research for energy saving and emission reduction in the WFGD process, especially for the efficient oxidation and resource conversion of the by-product MgSO3.

Atmospheric SO2 pollutant prediction using mutual information based TCNN-GRU model for flue gas desulfurization process

Over the past several years, sulfur dioxide (SO2) has raised growing concern in China owing to its adverse impact on atmosphere and human respiratory system. The major contributor to SO2 emissions is flue gas generated by fossil-fired electricity-generating plants, and as a consequence diverse flue gas desulphurization (FGD) techniques are installed to abate SO2 emissions. However, the FGD is a dynamic process with serious nonlinearity and large time delay, making the FGD process modeling problem a formidable one. In our research study, a novel hybrid deep learning model with temporal convolution neural network (TCNN), gated recurrent unit (GRU) and mutual information (MI) technique is proposed to predict SO2 emissions in an FGD process. Among those technique, MI is applied to select variables that are best suited for SO2 emission prediction, while TCNN and GRU are innovatively integrated to capture dynamics of SO2 emission in the FGD process. A real FGD system in a power plant with a coal-fired unit of 1000 MW is used as a study case for SO2 emission prediction. Experimental results show that the proposed approach offers satisfactory performance in predicting SO2 emissions for the FGD process, and outperforms other contrastive predictive methods in terms of different performance indicators.

Flue Gas Desulfurization Products Use on Agricultural Land Use Systems

The Flue gas desulfurization (FGD) process is a set of technology that is used to remove the sulphur dioxide (SO2) present in the flue gas, which is exhausted from the thermal power plant during electricity generation. In FGD equipment, high calcium-containing sorbent materials are sprayed, which will react with the SO2 present in the flue gas and result in the formation of calcium sulphite and FGD gypsum etc. these formed waste materials are known as FGD products. The FGD products can be used in agricultural land for the amelioration of the soil acidity, salinity and alkalinity, it improves the soil’s physical property, reduce the runoff rate etc. Now a day around two per cent of generated FGD products is used in the agricultural field. As some of the FGD products may contain heavy metals, their direct use in the agriculture field may cause environmental hazards. To avoid environmental pollution before its direct use the chemical properties of the product have to be thoroughly checked. So by the use of these materials in the agricultural field, we can effectively convert waste material into useful products.

Modeling based on machine learning to investigate flue gas desulfurization performance by calcium silicate absorbent in a sand bed reactor

Flue gas desulfurization (FGD) is a critical process for reducing sulfur dioxide (SO2) emissions from industrial sources, particularly power plants. This research uses calcium silicate absorbent in combination with machine learning (ML) to predict SO2 concentration within an FGD process. The collected dataset encompasses four input parameters, specifically relative humidity, absorbent weight, temperature, and time, and incorporates one output parameter, which pertains to the concentration of SO2. Six ML models were developed to estimate the output parameters. Statistical metrics such as the coefficient of determination (R2) and mean squared error (MSE) were employed to identify the most suitable model and assess its fitting effectiveness. The random forest (RF) model emerged as the top-performing model, boasting an R2 of 0.9902 and an MSE of 0.0008. The model's predictions aligned closely with experimental results, confirming its high accuracy. The most suitable hyperparameter values for RF model were found to be 74 for n_estimators, 41 for max_depth, false for bootstrap, sqrt for max_features, 1 for min_samples_leaf, absolute_error for criterion, and 3 for min_samples_split. Three-dimensional surface plots were generated to explore the impact of input variables on SO2 concentration. Global sensitivity analysis (GSA) revealed absorbent weight and time significantly influence SO2 concentration. The integration of ML into FGD modeling offers a novel approach to optimizing the efficiency and effectiveness of this environmentally crucial process.

Fabrication of Pillar-Cage Fluorinated Anion Pillared Metal-Organic Frameworks via a Pillar Embedding Strategy and Efficient Separation of SO2 through Multi-Site Trapping.

Flue gas desulfurization is crucial for both human health and ecological environments. However, developing efficient SO2 adsorbents that can break the trade-off between adsorption capacity and selectivity is still challenging. In this work, a new type of fluorinated anion-pillared metal-organic frameworks (APMOFs) with a pillar-cage structure is fabricated through pillar-embedding into a highly porous and robust framework. This type of APMOFs comprises smaller tetrahedral cages and larger icosahedral cages interconnected by embedded [NbOF5]2- and [TaOF5]2- anions acting as pillars. The APMOFs exhibits high porosity and density of fluorinated anions, ensuring exceptional SO2 adsorption capacity and ultrahigh selectivity for SO2/CO2 and SO2/N2 gas mixtures. Furthermore, these two structures demonstrate excellent stability towards water, acid/alkali, and SO2 adsorption. Cycle dynamic breakthrough experiments confirm the excellent separation performance of SO2/CO2 gas mixtures and their cyclic stability. SO2-loaded single-crystal X-ray diffraction, Grand canonical Monte Carlo (GCMC) simulations combined with density functional theory (DFT) calculations reveal the preferred adsorption domains for SO2 molecules. The multiple-site host-guest and guest-guest interactions facilitate selective recognition and dense packing of SO2 in this hybrid porous material. This work will be instructive for designing porous materials for flue gas desulfurization and other gas-purification processes.

Recycling flue gas desulfurization ash in enhancing the comprehensive moisture susceptibility of asphalt mixtures

Moisture susceptibility of asphalt mixtures is a major concern in areas with heavy rainfall or humid climates, as it can lead to premature pavement failures. As a typical industrial by-product during the flue gas desulfurization process of coal-fired, flue gas desulfurization ash (FGDA) with alkali mineral can facilitate the water damage resistance of asphalt mixtures. However, low density and high hydrophilic coefficient of FGDA limit its improvement effect. Hence, the comprehensive moisture susceptibility of asphalt mixtures with FGDA deserves systematic investigation. In this study, the properties indexes of FGDA and FGDA-limestone filler (LF) composite fillers were characterized. And the moisture susceptibility of asphalt mixtures containing six dosages of FGDA-LF fillers under hydrostatic damage and moisture induced sensitivity tester (MIST) hydrodynamic damage conditions were determined. The comprehensive assessment index of FLAM was explored based on radar chart assessment mean. The results indicate that FGDA with high alkali minerals and flocculent sphere morphology promotes the improvement of dispersivity and compatibility and the generation of homogeneous integral structure. Incorporating FGDA in FGDA-LF composite filler degrades its apparent density and elevates fineness and hydrophilic coefficient. Under MIST hydrodynamic damage, FLAM demonstrates the larger RMS and TSR than asphalt mixture with LF, accompanied by smaller attenuation compared to hydrostatic treatment. FLAM with F3 reveals the lowest rutting depth of 8.65 mm and creep slope of 1.92 × 10−4 and the largest comprehensive assessment index of 0.9998, indicating its optimal comprehensive moisture susceptibility. It is suggested that 30% FGDA might be an appropriate substitution amount for LF in FLAM.

Effect of selected green corrosion inhibitors on SO2 removal during carbon steel corrosion in aqueous solutions of ammonia and histidine

To understand the feasibility of using carbon steel in the flue gas desulfurization process, the corrosion protection of carbon steel was investigated by adding four green corrosion inhibitors (12-aminolauric acid; 4-carboxyphenylboronic acid; 1,2,3-benzotriazole; and L-methionine) to an ammonia solution containing histidine as the SO2 absorbent. The effects of the corrosion inhibitors on the corrosion rates of carbon steel and SO2 absorption performance were investigated. We observed that 1,2,3-benzotriazole was the most effective corrosion inhibitor, reducing the corrosion rate by 73 % and increasing the SO2 absorption loading by 8.3 % compared to other corrosion inhibitors. Scanning electron microscopy/energy dispersive X-ray spectroscopy and X-ray diffraction studies were conducted to understand the corrosion inhibition behavior of 1,2,3-benzotriazole. The formation of the Fen-(SO2-BTA)m complex and its subsequent adsorption on the carbon steel surface blocked active sites and inhibited corrosion. This study demonstrated the feasibility of effectively using carbon steel under harsh environmental conditions such as in desulfurization.

Physicochemical and radiological characterization of flue gas desulfuration waste samples from Brazilian coal-fired power plants

Flue gas desulfurization (FGD) waste is an industrial by-product generated during the flue gas desulfurization process in coal-fired power plants. This by-product contain trace quantities of naturally occurring radionuclides and elements such as As, Ba, Co, Cr, Zn. The characteristics of FGD waste are important for its reuse and are mainly depend on the desulfurization process. In this work, two types of FGD materials collected from three coal-fired power plants using semi-dry and wet processes were characterized by X-Ray Diffraction (XRD), Scanning Electron Microscope (SEM), X-ray fluorescence (XFR) and particle size analysis. The radioactive content of 238U, 232Th, 228Th, 226Ra, 228Ra, 210Pb and 40K and trace elements were also determined using Neutron activation analysis and Gamma-ray spectrometry. The major constituents for all samples were Ca, Si, S, Al and Fe. Wet FGD by-product presented also high magnesium content. The wastes contain mainly semi-hydrate calcium sulfite and calcium sulfate. The particle size of FGD from semi-dry process was lower than that from the wet process. The average activity concentration of 238U, 232Th, 226Ra, 210Pb, 228Ra, 228Th and 40K varied between were 50-71, 33-42, 28-52, 113-150, 26-33, 33-39, 161-390 Bq kg-1, respectively. According to the results of leaching and solubilization tests, FGD samples were classified as non-hazardous and non-inert. The obtained data are useful for evaluation of possible applications of FGD by-products.

Dynamic Modeling of Flue Gas Desulfurization Process via Bivariate EMD-Based Temporal Convolutional Network

Sulfur dioxide (SO2) can cause detrimental impacts on the ecosystem. It is well known that coal-fired power plants play a dominant role in SO2 emissions, and consequently industrial flue gas desulfurization (IFGD) systems are widely used in coal-fired power plants. To remove SO2 effectively such that ultra-low emission standard can be satisfied, IFGD modeling has become urgently necessary. IFGD is a chemical process with long-term dependencies between time steps, and it typically exhibits strong non-linear behavior. Furthermore, the process is rendered non-stationary due to frequent changes in boiler loads. The above-mentioned properties make IFGD process modeling a truly formidable problem, since the chosen model should have the capability of learning long-term dependencies, non-linear dynamics and non-stationary processes simultaneously. Previous research in this area fails to take all the above points into account at a time, and this calls for a novel modeling approach so that satisfactory modeling performance can be achieved. In this work, a novel bivariate empirical mode decomposition (BEMD)-based temporal convolutional network (TCN) approach is proposed. In our approach, BEMD is employed to generate relatively stationary processes, while TCN, which possesses long-term memory ability and uses dilated causal convolutions, serves to model each subprocess. Our method was validated using the operating data from the desulfurization system of a coal-fired power station in China. Simulation results show that our approach yields desirable performance, which demonstrates its effectiveness in the IFGD dynamic modeling problem.

CFD analysis of the spray droplet parameters effect on gas-droplet flow and evaporation characteristics in circulating fluidized bed desulfurization tower

The circulating fluidized bed flue gas desulfurization (CFB-FGD) process is a promising semi-dry flue gas desulfurization technology. The gas-droplet flow characteristics and droplets evaporation characteristics are critical to improving the desulfurization efficiency of the FGD tower. The effects of droplet parameters, including spray droplet diameter, spray droplet velocity, spray droplet mass flow rate and spray angle are investigated. Two evaluation indices, the coefficient of variation of droplet concentration (CV) and droplet mass-weighted life, are adopted to evaluate mixing degree of gas-droplet and droplet evaporation time, respectively. Results show that as the spray droplet diameter increases from 40 µm to 80 µm, the amount of water droplets trapped by tower wall increases from 3% to 21%. Increasing the spray droplet velocity and spray droplet mass flow rate could effectively increase the turbulent kinetic energy, which could improve the turbulent mixing ability. Moreover, droplet with smaller diameter and high velocity are beneficial to improving the temperature distribution uniformity. When the spray droplet mass flow rate exceeds 2.7 kg/s, the temperature in the tower would be lower than the dew point temperature, resulting in corrosion of the tower wall. Furthermore, the evaporation rate of droplets decreases with the increase of droplet diameter, spray droplet velocity and spray mass flow rate, while increases with the increase in the spray angle. This study would provide a better reference for the optimum operating scheme in practical applications.

Multiple field synergy mechanism of the desulfurization process in the intensified spouted beds

The semi-dry flue gas desulfurization process in the conventional spouted bed (CSB), integral multi-jet spouted bed (IMJSFB), spouted bed with longitudinal vortex generator (SB with LVG) and swirl blade nozzle (SB with SBN) was simulated using the multi fluid model. Meanwhile, the multiphase reaction system of intensified spouted beds was explored based on the field synergy theory. The analysis of the synergy angle among three fields of the gas phase velocity, temperature, and pressure in the spouted bed shows that adding intensification structures can effectively enhance the gas heat transfer and reduce the gas drag and pressure drop. The intensified spouted beds also had better synergy among the multiphase field of velocity, velocity gradient, and temperature gradient. The desulfurization efficiencies in the CSB, SB with LVG, IMJSFB, and SB with SBN were 77.75 %, 80.85 %, 87.97 %, and 88.81 %, respectively, and the promotion effects in descending order of SBN > multi-jets > LVG.

Data‐based learning control for optimization of nonlinear systems

Data‐based learning control for optimization of nonlinear systems

Numerical study on the effect of longitudinal vortex generator on semi-dry desulfurization process in 3D spouted beds

A longitudinal vortex generator was introduced into spouted beds to improve the heat and mass transfer rates in a semi-dry desulfurization process. The flue gas desulfurization processes in a 3D conventional spouted bed (CSB) and a spouted bed with a longitudinal vortex (LVSB) were simulated and verified experimentally. The simulation results show that the generator can strengthen the gas-particle-slurry contact in the spouting and annular areas. The average interphase slip velocities of the gas-particle and gas–liquid in the LVSB were 26.6 and 26.5 % higher than that in the CSB. The generator also increased the liquid temperature and interphase mass transfer rates in the spouted beds. The simulated desulfurization efficiencies of the CSB and LVSB were 77.75 and 80.85 %, respectively, which indicate the addition of a generator is beneficial for promoting the semi-dry desulfurization process.

Effect of swirling spouting intensification structure on semi-dry desulfurization process in 3D spouted beds

The swirling blade nozzle structure was introduced at the inlet of flue gas in the spouted bed to enhance interphase mixing and improve the desulfurization efficiency. The computational fluid dynamics (CFD) and experimental methods were used to study the gas–solid two-phase flow, water vaporization and semi-dry flue gas desulfurization processes in a spouted bed with an integral swirling blade nozzle (SB with an ISBN). It is found that the introduction of the swirling blade can significantly intensify heat and mass transfer process in spouted beds, the gas–liquid-solid temperature in the SB with an ISBN is higher than that of the conventional SB. During the desulfurization process, the desulfurization efficiency of spouted bed with an ISBN is about 85.42 %, while that of conventional SB is 76.14 %, and the desulfurization efficiency is increased by 12.2 %.

Numerical study of multi-jet structure impact on flue gas desulfurization process in 3D spouted beds

Multiple jets were added in the cone area of spouted beds to form an integral multi-jet spouted-fluidized bed (IMJSFB) to improve the flue gas desulfurization efficiency. The flue gas desulfurization process in the conventional spouted bed (CSB) and IMJSFB was simulated, and the accuracy of the adjusted mesoscale drag model and desulfurization prediction model was verified experimentally. The simulation results show that the spouting gas of CSB would skew after adding the slurry, while the spouting morphology of IMJSFB was less affected by slurry adding. The multi-jet structure can significantly enhance the flow field uniformity and interphase heat and mass transfer in spouted beds, especially in the cone area. The outlet gas moisture content in IMJSFB was 41 % higher than that of CSB. The desulfurization efficiency of CSB and IMJSFB was 77.75 % and 87.97 %, respectively, and the desulfurization efficiency was increased by 10.22 % by using the multi-jet structure.

Improving the quality of ammonium sulfate produced from the flue gas desulfurization process by using ammonium persulfate

Yellow ammonium sulfate, a by-product of flue gas desulfurization, has a lower product quality due to its chromaticity not meeting the chromaticity requirements for ammonium sulfate fertilizer. In this work, sulfur impurity was revealed to be the reason for the yellowing of ammonium sulfate products by studying the effects of organic pollutants, metal impurities, and sulfur-containing impurities on the chromaticity of ammonium sulfate products. A sulfur impurity was found to be generated when ammonium thiosulfate in the unqualified absorption mother liquor reacted with concentrated sulfuric acid, an oxidant in the ammonia desulfurization process. Subsequently, ammonium persulfate was proposed to replace concentrated sulfuric acid as an oxidant to solve the problem of abnormal chromaticity of ammonium sulfate. The experimental results show that under the optimized process conditions, the removal rates of thiosulfate and sulfite in the desulfurization mother liquor are as high as 90.1 % and 93.4 %, respectively, with ammonium persulfate as an oxidant. The ammonium sulfate product obtained is white with uniform particles. In addition, the effect degree of different oxidation components is S2O82−>SO4−∼OH in the oxidation process of ammonium persulfate to the absorption of the mother liquor. The ammonium persulfate oxidation technique provides benefits over the conventional ammonia acid process, including increased oxidation efficiency, decreased sulfur generation, and enhanced ammonium sulfate product quality.

Enabling direct H2O2 electrosynthesis of 100 % selectivity at 100 mA cm−2 using a continuous flow sulfite/air fuel cell

Direct electrosynthesis of hydrogen peroxide from the air is a promising alternative to the complex and energy-intensive anthraquinone process but generally suffers a low productivity and high energy consumption now. Here we provide a direct synthesis strategy using a continuous flow sulfite/air fuel cell, where the traditional oxygen evolution anode is replaced by a sulfite depolarized anode. By optimizing the carbon catalyst and cell parameters for hydrogen peroxide electrosynthesis, the prototype cell can achieve 100 % selectivity at a current density of up to 100 mA cm−2 and retain the selectivity for > 50 h. Up to 23.12 g/L HO2–, the cell can be operated continuously at remarkable productivity of 1.86 mmol cm−2 h−1, where the energy consumption is only 1.96 kWh kg−1 HO2–. The maximum electrosynthesis HO2– concentration was 35.02 g L−1. As a win–win strategy, we apply the desulfurization solution from the ammonia flue gas desulfurization process as the anolyte, which not only enhances the direct electrosynthesis of hydrogen peroxide from the air but also recovers sulfur from flue gas to (NH4)2SO4 fertilizer.

Difference of flue gas desulfurization performance and desulfurization mechanism of steel slag obtained under various cooling methods

Steel slag has excellent desulfurization capacity due to its high content of alkaline. However, the current researches mainly focus on the desulfurization rate, and there is no report on the desulfurization capacity of steel slag and influence of steel slag cooling methods on desulfurization. In this paper, the difference of flue gas desulfurization performance of steel slag under three cooling methods (chilling, natural-cooling and low-cooling) were discussed through the variation patterns of pH, desulfurization rate and sulfur capacity in the desulfurization process. The order of desulfurization efficiency of steel slag with different cooling methods was chilling > natural-cooling > low-cooling. Subsequently, the desulfurization mechanism was investigated by comparing the elemental distribution and phase composition of raw materials and desulfurization products, as well as the cation analysis of the desulfurization solution. The alkaline elements Ca, Mg, Mn, and Fe in the chilled steel slag were located in the glass phase, and of them dissociated during the process of flue gas desulfurization, which was the fundamental reason for the efficient flue gas desulfurization capacity. Finally, the flue gas desulfurization performance of chilled steel slag and widely used CaO and CaCO3 were compared, and the flue gas desulfurization capacity of sharply chilled steel slag was slightly higher than that of CaCO3. Therefore, the steel slag obtained by chilling method can replace limestone, which is more friendly to the environment.

Investigation on SO3/sulfuric acid mist conversion in WFGD process

SO3 and sulfuric acid mist generated in coal-fired boilers and wet flue gas desulfurization (WFGD) processes can adversely affect boiler facilities, while detection and absorption is an important issue. Factors affecting the conversion of SO3 to sulfuric acid mist (SO3/sulfuric acid mist) during wet desulfurization were studied and evaluated in a simulated experimental system, including the effects of flue gas composition, temperature and humidity on the SO3/sulfuric acid mist conversion rate. The certain concentrations of SO3, water vapor, SO2, NO, NH3, O2 and N2 were mixed thoroughly to simulate the flue gas of WFGD under the special temperature conditions in this experiment. The sulfuric acid droplets, sulfuric acid vapor and sulfuric acid aerosol in the simulated flue gas were absorbed and intercepted by NaCl and quartz wool, gaseous SO3 was absorbed by isopropanol solution, and thorium-barium titration method was used to measure SO42− concentration. The results showed that the increase of temperature significantly decreased the SO3/sulfuric acid mist conversion rate, the increase of humidity significantly increased the SO3/sulfuric acid mist conversion rate, and O2 concentration had little effect on the SO3/sulfuric acid mist conversion rate. In addition, the increase concentration of NH3, NO and SO2 also improved the conversion rate of SO3/sulfuric acid mist to some extent.