Article pubs.acs.org/IECR
Semiempirical Determination of Overall Volumetric Molar Transfer Coefficient for the Scrubbing of Gaseous Tars in Biodiesel Gershom Mwandila,* Shusheng Pang, and Woei-Lean Saw †
Department of Chemical Engineering, The Copperbelt University, Kitwe, Zambia Chemical and Process Engineering, University of Canterbury, Christchurch 8140, New Zealand § School of Chemical Engineering, The University of Adelaide, Adelaide, 5005 Australia ‡
ABSTRACT: This work contains a description for the determination of the liquid phase molar transfer coefficient (KXa) by a method which is different from that by Onda correlation. The method is different because KXa is for the transfer of the tars which change their phase and size as the temperature and pressure change. In the method, the solubility of the tars in biodiesel was predicted and ultimately the equilibrium coefficient was calculated. The equilibrium coefficient and measured tars compositions in liquid and gas phases at steady state were used to determine KXa. In this way, the determination of KXa for the wet scrubbing of tars into biodiesel was achieved semiempirically. The predicted equilibrium coefficient of the 0.3818 mole ratio at liquid phase temperature of 300 K and atmospheric pressure was used in the calculation. Under these conditions, KXa depended on the liquid to gas flow rate ratio, the inlet and outlet liquid phase compositions, and the exit gas composition. As a result, the measured values of these parameters together with the predicted equilibrium coefficient were fitted into a semiempirical correlation defined as KXa = 0.0143L0.7704G0.0282. This fitting is reasonably satisfactory as it satisfies the conditions cited in the literature and can be effectively applied at liquid to gas flow rate ratios of 36 and 38.
■
INTRODUCTION In biomass gasification, tars in producer gas offer the most hindrance to the application of the gas such as in electricity generation and liquid fuel synthesis. They are poly aromatic hydrocarbons of molecular weight greater than that of benzene.1 The tar components, composition, and concentration vary with biomass feedstock, gasifier type, and gasification operation conditions. When the tars condense, they cause numerous problems such as fouling, plugging, clogging, and blocking of the ducts.2 Various methods such as wet scrubbing, in-bed catalysis, downstream tar cracking, granular bed filtration, electrostatic precipitation, plasma technology, fabric filtration, rotational particle separation, and so forth have been tried to remove tars from the producer gas.3−5 The wet scrubbing method which uses biodiesel as a solvent has been widely reported to be successful.6−9 However, the wet scrubber design requires the determination of molar transfer coefficient, either the film transfer coefficients in both liquid and gas phases or the overall transfer coefficient (KXa). The overall volumetric molar transfer coefficient is a complex quantity as it is a function of the compound being scrubbed, solvent and gas loading rates, operating temperature, and type and size of packing. Consequently, experimental data can be used to determine this coefficient. The tars have a tendency to condense or to solidify as the producer gas temperature decreases and its pressure increases.2,10,11 This tendency makes the use of empirical correlations for determining the overall volumetric molar transfer coefficient unreliable.12 The objective of this work was to develop a semiempirical model to predict the equilibrium coefficient for the nitrogenbiodiesel system and then to use it for the determination of KXa in the wet scrubbing of tars in the producer gas. In the present study, nitrogen was used to simulate the gasification producer © 2014 American Chemical Society
gas because it has nearly the same molecular weight as that of the producer gas based on analysis from previous research work.13 Theoretical Basis for the Determination of the KXa. The determination of KXa is based on the following fundamental equation:14,15 L dx = KX a(X * − X ) dZ
(1)
In eq 1, KXa varies with physical properties and flow rates of the solvent phase and the gas phase, and the packing configuration; therefore, it can be determined using either empirical or semiempirical correlations. For developing a semiempirical correlation, a correlation for determination of equilibrium coefficient can be first developed and then used to determine the KXa. For determination of the equilibrium coefficient of tars in biodiesel solvent, Henry’s law can be used as shown in eq 2.14
f2 = x 2H12
(2)
Equation 2 is given here in its simple form because the activity coefficient of tars in biodiesel is almost unity as the system is considered to be diluted as it has been shown in earlier research work13 and with use of the UNIFAC group method.16 Dividing both sides of eq 2 by the total pressure (p) of the system yields f2 p
= x2
Received: Revised: Accepted: Published: 4424
H12 p
(3)
June 9, 2013 February 22, 2014 February 23, 2014 February 24, 2014 dx.doi.org/10.1021/ie401823r | Ind. Eng. Chem. Res. 2014, 53, 4424−4428
Industrial & Engineering Chemistry Research
Article
Figure 1. Schematic diagram of the tar removal system.
The term H12/p is defined as the equilibrium coefficient, and f 2/p is dependent on the composition of the tars in the gas phase. Therefore, eq 3 can be rearranged to the following form to determine the equilibrium coefficient: m=
X* − X =
(4)
KX a =
In eq 4, the solubility of the tars as a function of temperature can be predicted by modifying the equation reported by Prausnitz et al.17 following the method by Yen and McKetta.18 − ln x 2 =
ν2Lφ12 RT
2
2
2
0.5
[δ1 + δ2 − 2δ2(δ1 + Δ) ] + ln f
p
A* ⎛ B* ⎞ ln⎜1 + ⎟ B∗ ⎝ z2 ⎠
) )
(11)
In which the parameters φ, α, and β can be determined from experimental data by using the regression method.
■
EXPERIMENTS Equipment, Materials and Operation Conditions. The experiments were conducted in a vertically packed scrubber column as shown on the left side part of Figure 1, which was filled with Raschig ceramic rings of 12 mm in diameter. The height of the column was 1000 mm and had an inner diameter of 153 mm and a randomly packed height of 850 mm. In operation, nitrogen and tar vapor were fed from the bottom of the scrubber column to contact biodiesel in countercurrent. In addition, a stripper column was integrated into the system as shown on the right side part of Figure 1 for the purpose of removing tars from loaded biodiesel by hot air. The tar-loaded biodiesel was fed from the top to contact with the hot air flowing countercurrently. The tars were desorbed from the biodiesel when they were contacted with hot air which regenerated the biodiesel. In order to ensure an effective removal of the tars in the scrubber column, the scrubbing biodiesel liquid was controlled at low temperatures in the range of 297−317 K by using two water cooled heat exchangers.
(6)
(7)
The equation for overall molar transfer coefficient based on the liquid phase concentration difference can be derived by rearranging eq 1 as follows:
Ka dX = X dZ X* − X L
)
KX a = φLαG β
All of the quantities in eq 6 can be evaluated using literature data except for the compressibility factor which can be determined using the Lee−Kesler correlation tables.20 By using eqs 4−6, the equilibrium coefficient can be calculated and used to determine KXa by the following functional relation: KX a = f (L /G , m , X1 , X 2 , Y1)
( mGL
( (
The validation of eq 10 can be achieved by fitting its experimentally determined KXa values in the following semiempirical correlation:21
oL
(5)
= z 2 − 1 − ln(z 2 − B*) −
⎡ X L − 1 − L X + Y1 ⎤ mG 1 m ⎥ ⎢ 2 mG ln⎢ Y ⎥ L L − 1 Z ⎣ X1 mG − 1 − mG X1 + m1 ⎦ L
(10)
The fugacity of tars in the gas phase can be predicted by using the Soave−Redlich−Kwong equation of state, defined as follows:19 f2
(9)
Substitution of eq 9 into eq 8 and then integrating eq 8 from X1 to X2 over a packed column yields
f2 x 2p
Y L (X − X1) + 1 − X mG m
(8)
In order to integrate eq 8, the term (X* − X) can be defined by using the equations of the equilibrium relation (X* = Y/m) and operating line [Y = (L/G) (X − X1) + Y1] as follows: 4425
dx.doi.org/10.1021/ie401823r | Ind. Eng. Chem. Res. 2014, 53, 4424−4428
Industrial & Engineering Chemistry Research
Article
Before each experiment, tars used were first collected from gasification of radiata pine wood pellets in a dual fluidized bed gasifier.13 The collected tars were then cooled and solidified. At the start of each experiment, the solidified tars were placed into an autoclave and heated to preset temperatures ranging from 553 to 593 K to vaporize the tars. Once the autoclave reached a set point, a stream of nitrogen gas, which was heated to a temperature of about 493 K by tube furnace 2, was introduced and allowed to flow through the autoclave where it carried tar vapor through the scrubber column. The nitrogen gas was used to simulate the producer gas produced from the biomass gasification experiments. The vaporized tars and nitrogen were subjected to a temperature of about 493 K and atmospheric pressure which are similar to the conditions under which the tars exist in the producer gas from the gasifier. The vaporized tars were analyzed and found to have not undergone any chemical or physical changes during the solidification and vaporization after the results of the analysis were compared with the earlier research results.13 Experiment Procedures. The air and nitrogen at the gas flow rates ranging from 4 to 12 L/min were introduced into the system when the temperatures of the autoclave, tube furnace 1, and tube furnace 2 were set to 623, 493, and 673 K, respectively. At the same time, pump 1 and pump 2 for the biodiesel circulation at liquid flow rates ranging from 3 to 7 L/ min and water supply to the heat exchangers at rates ranging from 2 to 4 L/min were turned on. Once the system was at the stable operation, the data logging was started and the electrical heating of the hotter tank was turned on. Further, when the flow rates of all streams and the inlet and outlet temperatures of both the scrubber and stripper were steady for 5−10 min, samples of liquid and gas were collected from S1, S2, and gas sampling points 1 and 2, respectively. Tar Concentration Analysis. A method for the quantitative determination of tars in both the gas and the liquid samples was devised based on the literature.1,22 In this method, a portion of the gas exiting the scrubber column was bubbled through a series of four wash bottles of isopropyl alcohol (IPA) for 10−60 s at the gas flow rates ranging from 1 to 2 L/min to trap the tars in IPA. The wash bottles were submerged into a cold bath to maintain the temperature of the bottles around 0 °C, which enhanced tar solubility. After that, the bottles were swirled uniformly to dissolve the tars and left to allow settling, and then the concentrations of tars in the bottles were measured using an ultraviolet (UV)−visible spectrophotometer (Hitachi/101model). To ensure all of the available tars were sampled, the last bottle had to record a zero concentration. A calibration curve of ultravisible light absorbance against tar concentration in the IPA was established to determine the concentrations of the trapped tars, as shown in Figure 2. The concentration of the tars in the outlet gas in terms of mole ratio was determined using the sampling time, tb, and the volume of tar-free IPA used. In the setup for tar concentration determination, a gas delivery line was connected from the outlet port of the scrubber and its outlet to a flow meter which measured the volume flow rate. Then the IPA sample in each bottle was immediately collected for the absorbance measurements to determine the mass fraction of the trapped tars. The tar concentration in the outlet gas sample was calculated by Y1 =
nt ng
Figure 2. Calibration curve for determining tar mass fraction in biodiesel.
Using the mass ratio of tars in IPA, the total volume of IPA, the density of IPA, and the tar molecular weight, the number of moles of tars in the gas slip stream was determined as follows: nt =
xt ⎛ ρIPA VIPA ⎞ ⎜ ⎟ 1 − xt ⎝ M t ⎠
(13)
On the other hand, the number of moles of tar-free gas at an absolute operating temperature was determined as follows: 273vf tb ng = (14) 22400T The method of using a UV−visible spectrophotometer to determine the tar concentration in biodiesel was modified slightly to allow for large biodiesel dilutions with IPA of 1:5000 which yielded colorless solutions because the method is used to measure colorless solutions. Then a calibration curve of ultravisible light absorbance against the tar mass fraction in biodiesel was established to determine the tar concentrations in the liquid phase as shown in Figure 3.
Figure 3. Calibration curve for determining tar mass fraction in IPA.
■
RESULTS AND DISCUSSION The KXa values contained in Figure 4 were determined experimentally using eq 10, a packed column of height of 0.85
(12)
Figure 4. Effect of L on KXa in the scrubber at 300 K. 4426
dx.doi.org/10.1021/ie401823r | Ind. Eng. Chem. Res. 2014, 53, 4424−4428
Industrial & Engineering Chemistry Research
Article
Notes
m, and the theoretically predicted equilibrium coefficient of 0.3818 mole ratio for the liquid phase temperature of 300 K. Figure 4 shows that KXa increases with L, and its data set follows a linear correlation whose square of the correlation coefficient (R2 = 0.789) is reasonably satisfactory. The increase of KXa with L agrees with the results reported by Cypes and Engstrom.21 In addition, the KXa was correlated with L and G by a multilinear regression method, and it yielded φ, α, and β as 0.0143, 0.7704, and 0.0282, respectively. These parameter values are in the acceptable range for the correlation in this study because empirical correlations of α and β reportedly lie between 0 and 1.23 Therefore, eq 10 has been validated and found to fit into eq 11 reasonably well. Further, the KXa values calculated using the determined parameters of eq 11 were compared with those experimentally determined by eq 10, as shown in Figure 5.
The authors declare no competing financial interest.
■
ACKNOWLEDGMENTS We thank Biodiesel Manufacturing Ltd. of Rangiora in New Zealand for the biodiesel which was used in this study and New Zealand Aid for granting a scholarship to G.M. In addition, G.M. is grateful to Prof. Shusheng Pang and Copperbelt University for providing financial support after the expiry of the scholarship. This work would have not been achieved without their support.
■
Figure 5. Comparison of the KXa values determined by eq 10 and eq 11 at 300 K.
Figure 5 shows that the discrepancies between the KXa values determined by eq 10 and eq 11 are generally larger at lower L/ G values and smaller at higher L/G values. This trend shows that eq 10 is nearly in agreement with eq 11 at high L/G values. In addition, the results of eq 10 and eq 11 compare very closely for 36 and 38 L/G values. Therefore, eq 10 and eq 11 would give the same results under the operation conditions of liquid to gas flow rate ratios of 36 and 38.
■
CONCLUSION A semiempirical determination of the KXa for wet scrubbing of tars into biodiesel has been achieved using a predicted equilibrium coefficient of 0.3818 mole fraction at liquid phase temperature of 300 K. It has been shown that the KXa depends on the liquid to gas flow rate ratio, the inlet and outlet liquid phase composition, and the exit gas composition. As a result, measured values of these parameters together with the predicted equilibrium coefficient have been used to obtain t h e s e m i em p i r i ca l c o r r el a t i o n fi t t i n g o f K X a = 0.0143L0.7704G0.0282. This fitting is reasonably satisfactory as it satisfies the conditions cited in literature for the correlation by Cypes and Engstrom and can be effectively applied at liquid to gas flow rate ratios of 36 and 38.
■
AUTHOR INFORMATION
Corresponding Author
*E-mail:
[email protected]. 4427
NOMENCLATURE α = liquid phase parameter of the overall volumetric mass transfer coefficient in the scrubber β = gas phase parameter of the overall volumetric mass transfer coefficient in the scrubber δ1 = solubility parameter of biodiesel, (J/m3)0.5 δ2 = solubility parameter of the tars, (J/m3)0.5 Δ = characteristic constant for the correction of polarity, cal/ cm3 or J/m3 νL2 = molar liquid volume of naphthalene ρt = tar density, kg/m3 φ1 = volume fraction of biodiesel in the prediction of tar solubility in biodiesel a = area per unit volume of packing, m2/m3 A* = first characteristic constant determined by properties of naphthalene B* = second characteristic constant determined by properties of naphthalene f = mathematical symbol for function f 2 = fugacity of the model tar (naphthalene), N/m2 foL = fugacity of the pure liquid model tar (naphthalene) for solubility in polar solvents, N/m2 H21 = Henry’s law coefficient for the transfer of model tars (naphthalene) in biodiesel KXa = overall volumetric liquid phase molar transfer coefficient, kmol/(m3·s) KYa = overall volumetric gas phase molar transfer coefficient, kmol/(m3·s) G = gas molar flow rate per area, kmol/(m2·s) L = liquid molar flow rate per area, kmol/(m2·s) m = equilibrium coefficient in the scrubber, mol/mol Mt = tar molecular weight ng = number of moles of tar-free gas nt = number of moles of tars in the gas slip stream p = total pressure, N/m2 R = universal gas constant, J/(mol·K) R2 = square of the regression coefficient T = absolute temperature, K tb = gas sampling time Vf = flow rate read by flow meter (l/min) VIPA = total volume of IPA, mL x2 = mole fraction solubility of naphthalene in biodiesel, mol/mol xt = mass ratio of tars in IPA X = liquid phase mole tars per mole biodiesel, mol/mol X* = equilibrium liquid phase mole tars per mole biodiesel, mol/mol X1 = liquid phase moles of tar per mole of biodiesel at the top (exit) column, mol/mol X2 = liquid phase moles of tar per mole of biodiesel at the bottom (inlet) column, mol/mol dx.doi.org/10.1021/ie401823r | Ind. Eng. Chem. Res. 2014, 53, 4424−4428
Industrial & Engineering Chemistry Research
Article
(21) Cypes, S. H.; Engstrom, J. R. Analysis of a Toluene Stripping Process: A Comparison between a Microfabricated Stripping Column and a Conventional Packed Tower. Chem. Eng. J. 2004, 101, 49−56. (22) Giger, W.; Blumer, M. Polycyclic Aromatic Hydrocarbons in the Environment: Isolation and Characterization by Chromatography, Visible, Ultraviolet and Mass Spectrometry. Anal. Chem. 1974, 46, 1663−1671. (23) Hsieh, C.; Babcock, R. W.; Stenstrom, M. K. Estimating Semivolatile Organic Compound Emission Rates and Oxygen Transfer Coefficients in Diffused Aeration. Water. Environ. Res. 1994, 66, 206− 210.
Y1 = gas phase moles of tar per mole of biodiesel at the top column, mol/mol Z = height of packing, m/m z2 = gas phase compressibility factor of the model tar (naphthalene)
■
REFERENCES
(1) Milne, T. A.; Abatzoglou, N.; Evans, R. J. Biomass Gasifier “Tars”: Their Nature, Formation, and Conversion, NREL/TP-570-25357; National Renewable Energy Laboratory: Golden, CO, USA, 1998. (2) Chen, Y.; Lu, Y.; Wu, W.; Su, Y. Experimental Investigation on Tar Formation and Destruction in a Lab-Scale Two-Stage Reactor. Energy Fuels 2009, 23, 4659−4667. (3) Dou, B.; Gao, J.; Sha, X.; Baek, S. W. Catalytic Cracking of Tar Component from High-Temperature Fuel Gas. Appl. Therm. Eng. 2003, 23, 2229−2239. (4) Devil, L.; Ptasinski, K. J.; Jamssen, F. J. J. G. A Review of the Primary Measures for Tar Elimination in Biomass Gasification Processes. Biomass Bioenergy 2003, 23, 125−140. (5) Guzhev, G. P. Granular-Bed Gas Filters. Chem. Pet. Eng. 1971, 7, 649−652. (6) Zwart, R. W. R.; van der Drift, A.; Bos, A.; Visser, H. J. M. OilBased Gas Washing-Flexible Tar Removal for High-Efficient Production of Clean Heat and Power as well as Sustainable Fuel and Chemicals. Environ. Prog. Sustainable Energy 2009, 28, 324−335. (7) Hofbauer, H. Biomass CHPPlant Güssing: A Success Story. Pyrolysis and Gasification of Biomass and Waste: Proceedings of an Expert Meeting, Strasbourg, France, Sep. 30-Oct. 1, 2002; CPL Press: Newbury, U.K., 2003. (8) Boerrigter, H. Gas Cleaning at ECN: Lessons Learned and Results Achieved. GasNet & IEA Bioenergy Agreement Meeting, Strasbourg, France, Oct. 2, 2002. (9) Hasler, P.; Nussbaumer, T. Gas Cleaning for IC Engine Application from Fixed Bed. Biomass Bioenergy 1999, 16, 385−395. (10) Dayton, D. A Review of the Literature on Catalytic Biomass Tar Destruction, NREL/TP-510-32815; National Renewable Energy Laboratory: Golden, CO, USA, 2002. (11) Rabou, L. P. L. M.; Zwart, R. W. R.; Vreugdenhil, B. J.; Bos, L. Tar in Biomass Producer Gas, the Energy Research Centre of The Netherlands (ECN) Experience: An Enduring Challenge. Energy Fuels 2009, 23, 6189−6198. (12) Onda, K.; Tadeuchi, H.; Okumoto, Y. Mass transfer coefficient between gas and liquid phases in packed columns. J. Chen. Eng. Jpn. 1968, 1, 56. (13) Saw, W.-L.; Pang, S. The Influence of Cacite Loading on Producer Gas Composition and Tar Concentration of Radiata Pine Pellets in a Dual Fluidised Bed Steam Gasifier. Fuel 2012, 102, 445− 452. (14) Henley, E. J.; Seader, J. D. Equilibrium-Stage Separation Operations in Chemical Engineering; John Wiley & Sons: New York, 1981. (15) Geankoplis, C. Transport Processes and Separation Process Principles; Pearson Education: Upper Saddle River, NJ, USA, 2003. (16) Gmehling, J.; Lohmann, J.; Jakob, A.; Joh, R. A Modified UNIFAC (Dortmund) Model. 3. Revision and Extension. Ind. Eng. Chem. Res. 1998, 37, 4876−4882. (17) Prausnitz, J. M.; Lichtenthaler, R. N.; Gomes de Azevedo, E. Molecular Thermodynamics of Fluid-Phase Equilibria; Prentice Hall: Upper Saddle River, NJ, USA, 1999. (18) Yen, L. C.; McKetta, J., Jr. A Thermodynamic Correlation of Nonpolar Gas Solubilities in Polar Nonassociated Liquids. AIChE J. 1962, 8, 501−507. (19) Zhou, L.; Zhou, Y. Determination of compressibility factor and fugacity coefficient of hydrogen in the studies of adsorptive storage. Int. J. Hydrogen Energy 2001, 26, 597−601. (20) Smith, J. M.; Van Ness, H. C.; Abbott, M. M. Introduction to Chemical Engineering Thermodynamics, 5th ed.; McGraw-Hill: New York, 1996. 4428
dx.doi.org/10.1021/ie401823r | Ind. Eng. Chem. Res. 2014, 53, 4424−4428
