DOI: 10.3303/CET2188089 Paper Received: 12 June 2021; Revised: 27 July 2021; Accepted: 6 October 2021 Please cite this article as: Weiß B.D., Fuchs W., Harasek M., 2021, Finding Optimized Process Conditions to Minimize Precipitations in an SO2 Absorption Process Using Thermodynamic Process Simulation, Chemical Engineering Transactions, 88, 535-540 DOI:10.3303/CET2188089 CHEMICAL ENGINEERING TRANSACTIONS VOL. 88, 2021 A publication of The Italian Association of Chemical Engineering Online at www.cetjournal.it Guest Editors: Petar S. Varbanov, Yee Van Fan, Jiří J. Klemeš Copyright © 2021, AIDIC Servizi S.r.l. ISBN 978-88-95608-86-0; ISSN 2283-9216 Finding Optimized Process Conditions to Minimize Precipitations in an SO2 Absorption Process Using Thermodynamic Process Simulation Barbara D. Weißa*, Wolfgang Fuchsb, Michael Haraseka a Thermal Process Engineering - Computational Fluid Dynamics, Institute of Chemical, Environmental & Bioscience Engineering, TU Wien, Getreidemarkt 9, 1060 Vienna, Austria b Sappi Austria Produktions-GmbH & Co. KG, Sappi Europe, Brucker Strasse 21, 8101 Gratkorn, Austria barbara.weiss@tuwien.ac.at A process model to describe SO2 absorption from exhaust gas using an absorptive magnesium-based slurry was developed in Aspen Plus® V10. The model includes the thermodynamic description of the electrolyte system MgO-CaO-SO2-H2O-O2-CO2, including precipitation reactions in the system. The property method electrolyte- NRTL with an asymmetric reference state was chosen as the thermodynamic method. The model was evaluated using plant data for pH value, HSO3- and SO3-- content of the liquid phase from an industrial SO2 absorption venturi system of the pulp and paper industry. The model shows good accuracy in describing the pH value and the combined HSO3- and SO3-- content. Sensitivity analyses were performed to identify key parameters that influence unwanted precipitation reactions in the system and to support the optimization of the SO2 absorption process. Temperature and the Mg(OH)2/SO2 ratio in the system were identified as key parameters influencing the formation and precipitation of sulfites. The pH value was identified as a key parameter affecting the precipitation of magnesium hydroxide. The model predicts the precipitation of Mg(OH)2 at a pH value of higher than 8 and the precipitation of MgSO3 trihydrate at a temperature higher than 78 °C or a slurry/SO2 ratio higher than around 4. The performed analyses can support optimized process design decisions for SO2 absorption processes to avoid limiting precipitation issues. 1. Introduction The chemisorption of SO2 is a well-established technology to reduce SO2 emissions from SO2 containing exhaust gas from different industries such as coal-firing plants, sintering plants, or pulp production. Besides the traditionally used absorptive slurry based on limestone (Ozyuguran and Ersoy-Mericboyu 2010), a magnesium based slurry is widely used as an absorbent with the advantage of better recyclability and higher SO2 removal efficiencies (Liu et al. 2020). Magnesium hydroxide as an absorptive slurry gained increased attention due to the possibility of removing the pollutants SO2 and NOx simultaneously (Zou et al. 2019). In the pulp production industry, magnesium hydroxide is used as slurry to control SO2 emissions and simultaneously recover the cooking liquor. Eqs(1) – (3) summarize the main reactions of the chemical recovery for magnesium-based systems: MgO + H2O → Mg(OH)2 (1) Mg(OH)2 + SO2 → MgSO3 + H2O (2) MgSO3 + SO2 +H2O → Mg(HSO3)2 (3) After the combustion of black liquor, magnesium oxide is recovered from the ash and hydrated to serve as absorbent for the SO2 removal in the absorption venturi system. There, SO2 reacts with the slurry to form magnesium bisulfite, which serves again as cooking liquor for pulp production. 535 The goal of such chemical recovery system is the full reuse of required chemicals to target a closed-loop process control. However, unwanted precipitation reactions in the system can challenge this goal. Uncontrolled precipitation can lead to blockage of pipes, shortens maintenance intervals, and increases the chemical demand. Therefore, it is essential to understand the reaction system leading to precipitations when designing wet flue gas desulfurization systems. While most studies focus on removal efficiency, the issue of precipitation is often overlooked, leading to a lack of studies targeting that issue in literature. In a previous work, potential salts and their solubility data from literature were studied (Weiß and Harasek 2021). In literature, a solid database for the solubility of potential salts in water is available. However, potential precipitations are dependent on the complex present electrolyte system. A rigorous thermodynamic model can provide a tool to analyze the effect of different parameters on the precipitation by including all necessary electrolyte reactions. The MgO- H2O-SO2 system was previously modeled by Zidar et al. using the Rudzinsky+Pitzer-Ion activity coefficient model (Zidar et al. 1997). Steindl et al. described the same system using the electrolyte NRTL method (Steindl et al. 2008). The newer study of Si et al. applies the electrolyte NRTL method on an SO2 absorption system based on calcium (Si et al. 2019). This study investigates the effect of temperature, pH value, SO2, and Mg(OH)2 in the system on precipitation calculated by the electrolyte NRTL method. The flowsheet and input data are based on an industrial absorption plant of the chemical recovery in the pulp industry. 2. Methods The system was modeled as a steady-state process in thermodynamic equilibrium. The thermodynamic framework, the reaction system, and the flowsheet calculations were set and performed using the sequential modular simulation tool Aspen Plus® V10. The following summarizes the applied methodology. 2.1 Thermodynamic framework The system was rigorously modeled using the built-in elecNRTL property method in Aspen Plus® V10. This method uses the electrolyte NRTL activity coefficient model as proposed by Chen and Evans and extended by Mock et al. The vapor phase properties were calculated using the Redlich-Kwong equation of state. As for every activity coefficient model, the activity coefficient expresses the deviation of a solution from ideality. The reference state of the system defines which state is referred to as ideal. For ions, the reference state of infinite dilution in the actual mixed solvent present was chosen (asymmetric reference state). For all other components, the reference state is that of a pure compound. The reference state for supercritical, dissolved gases, defined as Henry components in Aspen Plus®, is at infinite dilution (asymmetric reference state) at system temperature and pressure. In the studied system, SO2, O2, and CO2 were defined as Henry components. All pure component and binary interaction parameters were retrieved from the standard implemented data banks in Aspen Plus® V10. 2.2 Chemical system Aspen Plus® V10 allows the description of electrolyte systems using the true component approach. The true component approach, unlike the apparent component approach, means that all true components of the electrolyte system, including ions, salts, and molecular species, are reported. The chemical equilibrium is calculated using built-in or user-supplied parameters to describe the equilibrium constants Keq as a function of temperature. If no equilibrium constants are given, the equilibrium is calculated from the reference state Gibbs free energies of the participating components. Table 1 summarizes all considered reactions and how the chemical equilibrium was calculated. Table 1: Considered electrolyte system Reaction Type Calculation of chemical equilibrium 2 H2O ↔ OH- + H3O+ Equilibrium built-in coefficients for Keq 2 H2O + SO2 ↔ H3O+ + HSO3- Equilibrium built-in coefficients for Keq H2O + HSO3- ↔ H3O+ + SO3-- Equilibrium built-in coefficients for Keq H2O + HCl ↔ Cl- + H3O+ Equilibrium Gibbs free energy calculation H2SO4 + H2O ↔ H3O+ + HSO4- Equilibrium Gibbs free energy calculation H2O + HSO4- ↔ H3O+ + SO4-- Equilibrium Gibbs free energy calculation MgOH+ ↔ OH- + Mg++ Equilibrium Gibbs free energy calculation CaOH+ ↔ OH- + Ca++ Equilibrium Gibbs free energy calculation 2 H2O + CO2 ↔ H3O+ + HCO3- Equilibrium built-in coefficients for Keq H2O + HCO3- ↔ H3O+ + CO3-- Equilibrium built-in coefficients for Keq Mg(OH)2 → OH- + MgOH+ Dissociation - Ca(OH)2 → OH- + CaOH+ Dissociation - 536 Table 1: Considered electrolyte system, continued Reaction Type Calculation of chemical equilibrium 2 H2O + CO2 ↔ H3O+ + HCO3- Equilibrium built-in coefficients for Keq H2O + HCO3- ↔ H3O+ + CO3-- Equilibrium built-in coefficients for Keq Mg(OH)2 → OH- + MgOH+ Dissociation - Ca(OH)2 → OH- + CaOH+ Dissociation - MgSO4 → Mg++ + SO4-- Dissociation - MgSO3 → Mg++ + SO3-- Dissociation - CaSO4 → Ca++ + SO4-- Dissociation - CaSO3 → Ca++ + SO3-- Dissociation - MgCO3 → Mg++ + CO3-- Dissociation - CaCO3 → Ca++ + CO3-- Dissociation - Mg(OH)2 (s) ↔ OH- + MgOH+ Salt precipitation Gibbs free energy calculation Ca(OH)2 (s) ↔ OH- + CaOH+ Salt precipitation Gibbs free energy calculation MgSO3 * 6 H2O ↔ Mg++ + SO3-- + 6 H2O Salt precipitation built-in coefficients for Keq MgSO3 * 3 H2O ↔ Mg++ + SO3-- + 3 H2O Salt precipitation built-in coefficients for Keq CaSO3 * ½ H2O ↔ Ca++ + SO3-- + ½ H2O Salt precipitation Gibbs free energy calculation MgSO4 * H2O ↔ Mg++ + SO4-- + 1 H2O Salt precipitation built-in coefficients for Keq MgSO4 * 7 H2O ↔ Mg++ + SO4-- + 7 H2O Salt precipitation built-in coefficients for Keq CaSO4 * 2 H2O ↔ Ca++ + SO4-- + 2 H2O Salt precipitation built-in coefficients for Keq CaSO4 ↔ Ca++ + SO4-- Salt precipitation Gibbs free energy calculation 2.3 Flowsheet and input data The developed flowsheet was based on an industrial absorption unit (Figure 1). Figure 1: Flowsheet of SO2 absorption venturi system in Aspen Plus® V10 It consists of a flash unit “VENTURI”, which calculates the chemical and phase equilibrium at atmospheric pressure of 1.013 bar and without any heat duty. In an industrial venturi system, the physical solubility of SO2 is considered as the limiting process preventing the system to be in equilibrium (Marocco 2010). To adapt the equilibrium model to the real process, a gas bypass allows adjusting the venturi efficiency. The reactor “HYDRA” covers the hydration of MgO and CaO to Mg(OH)2 and Ca(OH)2 respectively, resulting in the input stream “SLURRY”. The hydration reactor was implemented as a stoichiometric reactor with a hydration rate of 90 %. The stoichiometric reactor “OXID” covers the oxidation of SO3-- to SO4-- in the liquid outlet of the venturi. Several studies describe the kinetics of the oxidation of SO2 in the liquid phase. Due to the complex nature and fast kinetics of the reaction (Hudson et al. 1979), it was assumed that the total O2 in the liquid phase reacts with SO3--. The initial composition of the exhaust gas “G0” is summarized in Table 2. Table 2: Gas composition G0 in vol% (standard conditions, dry) N2 SO2 O2 CO2 NO 78.43 0.41 5.94 13.52 1.71 In industrial SO2 absorption processes, the exhaust gas usually passes several absorption units in series, and the liquid outlet of an absorption unit is recycled counter current into the previous unit. The stream “RECYCLE” 537 represents this liquid recycle stream. The composition of the input streams “RECYCLE” and “MGO+H2O” are summarized in Table 3. Table 3: Composition of input streams RECYCLE and MGO+H2O in mass-% H2O Mg(HSO3)2 MgSO3 MgSO4 CaSO3 CaSO4 MgCO3 MgO CaO N2 Others RECYCLE 97.20 1.66 0.82 0.04 0.07 0.03 0.08 0.06 0.05 MGO+H2O 90.95 0.34 0.04 7.84 0.35 0.48 On the presented flowsheet, sensitivity analyses were performed to study the effect of temperature, pH value and the input ratio of slurry and SO2. 3. Results and discussion In the following the model is validated using industrial plant data. Furthermore, results of the performed sensitivity analyses are presented and discussed. 3.1 Validation of model with plant data Table 4 compares the calculated values of the liquid product stream with measured plant data at process conditions. Table 4: Comparison of calculated values with data of industrial plant (with σ = standard deviation) in product (T=68 °C; ṁGas0= 374,000 kg/h, ṁRecycle= 83,000 kg/h, ṁSlurry=3,840 kg/h, venturi efficiency = 0.55) Units Calculated Plant data pH 5.47 5.18 σ = 0.07 SO3-- + HSO3- mass-% SO2 2.94 3.04 σ = 0.22 SO3-- mass-% SO2 0.13 0.39 σ = 0.09 The calculated amount of SO2, which is present as SO3-- and HSO3- in the liquid product, is in very good agreement with the measured value. The pH value shows only a small deviation of 0.22 pH units, considering the standard deviation of the measurement. Compared to measurements, the model underestimates the amount of SO2, which is present as SO3--. 3.2 Effect of temperature on solid precipitation Figure 2a and b show the precipitation as a function of temperature, while all other input parameters were unchanged. a) b) Figure 2: Precipitation in product as a function of temperature; (a) total precipitation mapped in linear scale; (b) precipitation of MgSO3* 3 H2O and CaSO3* ½ H2O mapped in logarithmic scale (ṁGas0= 374,000 kg/h, ṁRecycle= 83,000 kg/h, ṁSlurry=3,840 kg/h, venturi efficiency = 0.55) The process model reports precipitation of CaSO3 hemihydrate (CaSO3* ½ H2O) over the whole considered temperature range. CaSO3 hemihydrate has the lowest solubility in water compared to the other considered sulfates and sulfites (Weiß and Harasek 2021). Its solubility decreases with temperature, which corresponds to the increase of CaSO3* ½ H2O in the product with temperature. However, due to the small amount of calcium 538 present in the system, the effect of its precipitation in the product stream is small and makes up only around 0.1 mass-% in the product. At temperatures higher than 78 °C, the model also reports MgSO3 trihydrate (MgSO3* 3 H2O) as precipitated solid. This can be explained by the shift in the vapor-liquid phase equilibrium with increasing temperature. The total liquid product flow decreases with increasing temperature. As a consequence, the concentration of MgSO3 in the liquid product exceeds the solubility limit leading to the precipitation of MgSO3*3 H2O. Another factor is that at higher temperatures, the less soluble MgSO3*3 H2O is the dominantly occurring form, while at lower temperatures, the more soluble MgSO3*6 H2O is the stable form (Steindl et al. 2005). The transition from hexahydrate to trihydrate as stable form can explain the precipitation of MgSO3 at higher temperatures. 3.3 Effect of pH value on solid precipitation Figure 3 shows the effect of the pH value in the system on solid precipitation. Figure 3: Precipitation in product as a function of pH value adjusted by adding HCl and NaOH (T = 68 °C, ṁGas0= 374,000 kg/h, ṁRecycle= 83,000 kg/h, ṁSlurry=3,840 kg/h, venturi efficiency = 0.55) The pH value was adjusted by adding HCl and NaOH to the system. HCl and NaOH were chosen as they are not part of other reactions in the electrolyte system other than their dissociation. The analyses show that Mg(OH)2 precipitates when a pH value of 8 is exceeded. This corresponds to the studies by Scholz and Kahlert (Scholz and Kahlert 2015). 3.4 Effect of slurry/SO2 ratio on solid precipitation Figure 4a and b show the effect of the mass flow ratio of slurry and SO2 into the venturi flash on the precipitation. a) b) Figure 4: Precipitation in product as a function of the mass flow ratio Slurry/SO2; (a) Varying of SO2 input; (b) Varying of slurry input (T = 68 °C, ṁGas0= 374,000 kg/h, ṁRecycle= 83,000 kg/h, venturi efficiency = 0.55) The ratio was varied once by changing the SO2 input and once by changing the slurry input. Following the Eqs(2) and (3), excess Mg(OH)2 in the system leads to an increased formation of MgSO3. The model reports that at a ratio higher than 4, the solubility limit is exceeded and MgSO3 precipitates as trihydrate. The start of the precipitation can also be recognized by the inflection point of the slope of pH value in the product. This point is at a pH value of around 5.7 to 6. 539 4. Conclusions The simulation showed promising results when compared with industrial measurement data. The performed analyses showed the importance to not only consider removal efficiency but also potential solid precipitation when designing wet flue gas desulfurization systems. The model reports CaSO3 hemihydrate as precipitated solid in the product under the analyzed conditions. The precipitation of MgSO3 trihydrate was reported when exceeding a temperature of 78 °C or a slurry/SO2 ratio of higher than around 4. Mg(OH)2 was reported when exceeding a pH value of 8 in the system. Those findings correspond to solubility reports found in literature. The model describes the solids occurring in the product. In a real system, local solubility exceedance can occur and lead to depositions. While the model does not depict those local concentration differences, it gives a good indication of key parameters influencing the precipitation in the system and provides a qualitative assessment of those influencing factors. Based on the performed analyses, it is recommended to ensure temperatures below 78 °C and a slurry/SO2 ratio of lower 4 when using a magnesium hydroxide slurry. Furthermore, it is recommended to prevent exceeding a pH value of 8 to limit precipitation issues in the system. For a further evaluation of those findings, measurements using infrared spectroscopy are recommended to identify the solids and to determine the ratio of SO3-- and HSO3- in the liquid product. Acknowledgements This work was financially supported by the Competence Center CHASE GmbH. CHASE Competence Center is subsidized in the frame of COMET – Competence Centers for Excellent Technologies by BMVIT, BMWFW, Wirtschaftsagentur Wien, State of Upper Austria and its scientific partners. 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