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Two-dimensional mathematical model for flue gas desulfurization in a spray column at low temperature with seawater: Design and optimization Yadollah Tavan, Seyyed Hossein Hosseini, and Martin Olazar Energy Fuels, Just Accepted Manuscript • DOI: 10.1021/acs.energyfuels.6b00139 • Publication Date (Web): 22 Mar 2016 Downloaded from http://pubs.acs.org on March 23, 2016
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Two-dimensional mathematical model for flue gas desulfurization in a spray column at low temperature with seawater: Design and optimization Yadollah Tavan a∗, Seyyed Hossein Hosseini b, Martin Olazar c a
b
National Iranian Gas Company (NIGC), Tehran, Iran.
Chemical Engineering Department, Faculty of Engineering, Ilam University, 69315-516 Ilam, Iran. c
Department of Chemical Engineering, University of the Basque Country, Bilbao, Spain.
Abstract: Industrial SO2 absorption process using seawater has been mathematically modeled using a two-dimensional model in order to obtain velocity profiles and SO2 concentrations in the gas and liquid phases at low temperatures in a spray column. A study has been conducted involving the influence on the SO2 removal efficiency of seven design and operating parameters, namely, gas flow rate, liquid flow rate, gas inlet temperature, liquid inlet temperature, operating pressure, droplet size and column diameter. The optimization of the plant has been performed using the practical method of response surface methodology (RSM) and the optimum values for the operating variables have been determined. Furthermore, the interactions between the variables have been assessed and a simple and reliable correlation (regression coefficient, R2 = 0.9623) has been proposed to predict SO2 removal efficiency.
Keywords: RSM, flue gas desulfurization, SO2, Seawater
∗
Corresponding author: Tel/Fax: +98-21-81315646, Email address:
[email protected] (Y. Tavan).
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1. Introduction It is well-known that sulfur dioxide (SO2) damages human health and causes acid rain, which has led to stringent environmental regulations for reducing its emissions.1-4 Up to now, many technologies have been proposed and studied for reducing emissions, as are those based on spray dryer absorbers, fluidized bed flue gas desulfurization (FGD), wet scrubbers, seawater scrubbers, UV/H2O2 advanced oxidation, packed bed columns, venturi scrubbers, membrane contactors, anion-functionalized ionic liquids and plasma electrostatic precipitators.5-11 Seawater FGD can be used for coastal industries in a simple contactor and SO2 is absorbed into lean seawater. Rich seawater containing acid gas is further oxidized and returned to the sea. Literature regarding seawater FGD is scarce and few thermodynamic studies approach this matter. Douabul and Riley measured solubility of sulfur dioxide in distilled water and decarbonated seawater at a pressure of 1 atm and temperatures in the 5.8-30 °C range.
12
They
have shown that solubility of sulfur dioxide in seawater decreases by an increase in salinity and also that solubility in seawater is lower than in distilled water. In contrast, Abdulsattar et al. found at certain temperature and pressure ranges that sulfur dioxide is two to three times more soluble in seawater than in pure water. 13 Al-Enezi et al. reported the solubility of sulfur dioxide as a function of temperature and initial salinity.
14
They measured higher solubility of sulfur
dioxide in seawater than in pure water, which they explained based on the physical absorption and the chemical reactions with the salt contained in the seawater, a simple comparison shows SO2 solubility data by Al-Enezi et al. 14 are lower than those by Abdulsattar et al. 13. Moreover, unlike Douabul and Riley, 12 Al-Enezi et al. reported an increase in SO2 solubility for a higher initial salinity.
14
With these discrepancies in the literature, Rodriguez-Sevilla et al. presented a
new equilibrium measurement at low partial pressures and different temperatures observing 2 ACS Paragon Plus Environment
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small differences between total absorption capacity of the natural and artificial seawater samples.
15
They also observed higher SO2 solubility for artificial seawater than for distilled
water. Darake et al. 9 used the equilibrium data of Rodriguez-Sevilla 15 to predict the behavior of a packed bed column based on a one-dimensional mathematical model. They studied the effects of gas flow rate, liquid flow rate, pH, SO2 concentration and gas temperature on the SO2 removal efficiency. They studied the process at high temperatures (up to 350 °C) and found a decreasing-increasing trend for SO2 removal efficiency as temperature and pH are varied. Thus, they observed a decrease in SO2 removal efficiency as both gas flow rate and SO2 concentration are increased. Overall, the information reported in the literature allows drawing the following considerations: (i) high temperatures lead to solvent/liquid evaporation, low gas solubility and hinder NOx separation; (ii) packed bed systems cause high pressure drops and they may undergo plugging, thereby requiring high operating pressures; (iii) two-dimensional models predict process behavior better than one-dimensional models. (iv) the effect of operating pressure, liquid inlet temperature, droplet size and column diameter have not been investigated; (v) there is scarce information in the literature on velocity profiles and SO2 concentrations in the liquid phase. Accordingly, this study deals with the development of a two-dimensional model for SO2 removal from flue gas at low temperatures in order to obtain velocity profiles and SO2 concentrations in the gas and liquid phases in a spray column without packing (no significant pressure drop). Moreover, the influence of seven design and operating parameters on SO2 removal efficiency has been explored, namely, gas flow rate, liquid flow rate, gas inlet temperature, liquid inlet temperature, operating pressure, droplet size and column diameter. Unlike the literature, 9 optimization of the plant has been performed using the response surface 3 ACS Paragon Plus Environment
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methodology (RSM) with the Box-Behnken approach for the assessment of significant parameters. Furthermore, interactions between variables are analysed and a simple and reliable correlation to predict SO2 removal efficiency has been proposed. 2. Modeling In order to develop a model that is valid for a wide range of operating conditions, and specifically for large scale processes, the features of an industrial SO2 removal device have been extracted from the literature and they are shown Figure 1. The raw gas stream containing SO2 enters through the bottom of the device/absorber and flows upward in counter-current contact with seawater distributed at the top of the device by means of nozzles. The SO2 is absorbed by the seawater and the gas leaves the column through the top of the absorber. The following assumptions have been introduced in the model: 1. The gradient of concentration and temperature in the angular direction is neglected and the system is considered as one dimensional, i.e., the flow pattern follows a plug flow model [16]. 2. The difference of temperature along the absorber as well as heats of reaction and dissolution is neglected. Darake et al. showed that the temperature profile for temperatures lower than 100 °C is flat. 9 Since, this paper investigates SO2 removal at low temperatures, this assumption is reasonable.3 Hence, the process is considered isothermal and thermal and physical properties are constant. 3. Steady state operation 4. Negligible heat transfer resistance in the liquid 5. Droplets are spherical and remain spherical.3 4 ACS Paragon Plus Environment
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6. The diffusive term in the gas phase is much less significant than the convective term. 7- The equilibrium model by Rodriguez-Sevilla et al. is used.15 According to these assumptions, the model equation for the liquid phase is: 17
∂C ∂C DAB ∂ (r 2. A ) - r 2.KCA =r 2.Vd .( A ) ∂r ∂r ∂z
(1)
For the gas phase the following model is considered:
Qg.C.d
Sh =
at r= 0
at r= R
yA 6QL = K y.(yAb -yAi ).( ) Dd.Vd dz
µg K y .Dd ρ .V.Dd 0.5 =2+0.6(Re or g ) .(Sc or DAB.C µg ρg.D ∂CA =0 ∂r
)1/3
(3)
AB (4)
K y.(yAb -yAi )= DAB
at z= 0
(2)
∂CA ∂z
CA= 0
(5)
(6)
The solubility of SO2 in seawater is calculated by linearization of the chart by Siddiqi et al. Based on a momentum balance, the following motion equation is derived for the process: 18
(
ρ ρ dVd 3C D )= 1 [(1- g )g. (Vd + Vg ) 2 g ] dz Vd ρd 4 ρ d .D d
(7)
where CD is the drag coefficient calculated from: CD=24/Red
if Red