Kinetic Modeling of Lime-Enhanced Biomass Steam Gasification in a

Article Cite This: Ind. Eng. Chem. Res. 2019, 58, 12953−12963

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Kinetic Modeling of Lime-Enhanced Biomass Steam Gasification in a Dual Fluidized Bed Reactor Bijan Hejazi,*,† John R. Grace,‡ and Andreś Mahecha-Botero‡,§ †

Chemical Engineering Department, Faculty of Engineering, Ferdowsi University of Mashhad, Mashhad 9177948944, Iran Department of Chemical and Biological Engineering, University of British Columbia, 2360 East Mall, Vancouver, British Columbia V6T 1Z3, Canada

‡

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S Supporting Information *

ABSTRACT: This paper develops a simple yet practical steady-state kinetic reactor model for lime-enhanced biomass steam gasification in a dual fluidized bed reactor, one of the most promising technologies for the sustainable production of hydrogen. The focus is on kinetic modeling of the bubbling fluidized bed gasifier, accounting for in situ sorbent carbonation, while assuming complete char combustion and complete sorbent calcination in the circulating fluidized bed riser. This kinetic model assumes perfect mixing of solids and plug flow of gas phase coupled with a two-step reaction kinetic mechanism for biomass pyrolysis, with phenol as a model tar compound and a reaction network for tar thermal cracking and reforming, major homogeneous and heterogeneous gasification reactions, and a firstorder kinetic model for the carbonation of sorbent particles suitable for steady state Ca-looping operation. Predictions of the product gas distribution are in good agreement with literature experimental data on the effect of Ca-looping rate, gasifier temperature, and steam-to-biomass ratio for absorption enhanced reforming (AER) of biomass in both 20 kWth and 200 kWth dual fluidized bed systems operating at steady-state. This predictive model is useful for optimizing design and operation of dual fluidized bed biomass gasifiers with lime-based CO2 capture.

1. INTRODUCTION Moving toward a sustainable energy future is among the top priorities of mankind today. Anthropogenic emissions of greenhouse gases (especially CO2) to the atmosphere have been proven to contribute to climate change. Among the alternatives capable of producing H2 in an eco-friendly and efficient manner, gasification of biomass as a renewable source of energy has recently attracted the attention of many researchers around the globe.1 Enhanced hydrogen production from biomass gasification integrated with CO2 capture and sequestration technologies could potentially lead to negative emissions of CO2. Steam gasification of biomass produces higher hydrogen content of product gas compared with gasification with a mixture of steam and oxygen, whereas the hydrogen concentration in product gas generated by air gasification is the lowest of these options.2 Whereas in autothermal gasifiers, partial oxidation of biomass (with air or oxygen) provides the necessary heat to conduct the highly endothermic biomass gasification reactions, allothermal gasifiers derive the required energy from external sources. A schematic of a dual fluidized bed (DFB) gasifier is shown in Figure 1. Biomass is fed into one reactor and fluidized by steam. The remaining fraction of unconverted carbon (char) resulting from incomplete gasification is circulated to a second fluidized bed (i.e., the © 2019 American Chemical Society

Figure 1. Operation of dual fluidized bed steam gasifier. Adapted from ref 3. Copyright 2004 American Chemical Society.

combustor) and burnt in air at higher temperatures. If necessary, an additional source of fuel (biomass for a renewable system) or an external source of heat may also be supplied to the combustor. The hot solid bed materials are circulated back from the combustor to the gasifier to drive the endothermic gasification reactions at steady-state. By separating the gasification zone from the combustion zone, the DFB Received: Revised: Accepted: Published: 12953

March 5, 2019 June 13, 2019 June 26, 2019 June 26, 2019 DOI: 10.1021/acs.iecr.9b01241 Ind. Eng. Chem. Res. 2019, 58, 12953−12963

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Industrial & Engineering Chemistry Research reactor produces a N2- and flue-gas-free syngas with a relatively high concentration of H2 and thus a higher product gas heating value.3 In spite of a common misconception in the biomass gasification literature, a dual fluidized bed gasifier as a whole unit should not be termed “allothermal” because heat is supplied by combustion of a fraction of biomass in the form of residual char resulting from incomplete gasification. A dual fluidized bed gasification system can operate under different combinations of flow regimes depending on the gas velocity inside the two beds. Experimental findings suggest that a bubbling fluidized bed as a fuel gasifier interconnected with a circulating riser as a char combustor improves gasification efficiency, reduces tar production, and maintains steady circulation of particles and thus effective heat transfer between the two beds,4 as is the case in this study. Although biomass gasification has been identified as the most attractive route for hydrogen production,5 it needs to be combined with other advanced technologies to become a sustainable energy path. There are a number of areas of improvement for biomass gasification to meet industrial requirements. These include low yields of produced H2 (e.g., 40% by volume, dry), high tar content (e.g., ∼ 10 g/Nm3) in the product gas, and high operating temperatures (>800 °C) that are costly to achieve with steam as the fluidizing agent.1 Provision of very high heat fluxes required for biomass drying, pyrolysis, and gasification reactions poses the key challenge for the scale-up and commercialization of DFB gasifiers, which are relatively compact to allow the integration of a heat exchanger of sufficient surface area.6 In addition, typical operating temperatures of biomass gasifiers are chemically constrained by carbon conversion, product gas tar content, sulfur species, and CO2 capture, as well as fouling and agglomeration of ash. Although high temperatures maximize tar cracking, lowmelting compounds (alkali metals together with silica) coat bed particles, promote agglomeration, and may cause defluidization. To prevent agglomeration, high-melting minerals such as limestone or dolomite can be added.7 Lime-enhanced biomass gasification via calcium looping in a dual fluidized bed reactor shows considerable signs of future success for renewable hydrogen production and CO2 capture at the same time.8 This can be achieved by selectively removing CO2 in situ through exothermic carbonation of calcined lime and shifting the thermodynamic barrier of equilibrium reactions, such as the water−gas shift reaction, toward more H2 production, as CO + H 2O ↔ CO2 + H 2

° = −41 kJ/mol ΔHrxn

CaO(s) + CO2 (g) ↔ CaCO3(s)

Figure 2. Schematic of lime-enhanced biomass steam gasification in a dual fluidized bed reactor. Adapted with permission from ref 8. Copyright 2008 Elsevier.

transportation. The simultaneous biomass gasification and CO2 capture via CaO conversion to CaCO3 under suitable operating conditions produces a product gas that is rich in H2. The produced CaCO3 together with unreacted char are transported to the fluidized bed calciner−combustor to produce a concentrated stream of CO2, if sorbent is regenerated by external heat or oxy-fuel combustion of char and additional fuel. The hot solid stream containing calcined lime (CaO) is then circulated back to the gasifier for cyclic gasification−carbonation. The first large-scale application of Ca-looping was for enhancing the heating value of syngas from coal gasification.9 The CO2 acceptor process, developed in the 1960s through the 1980s, consisted of two bubbling fluidized beds linked by solid particle streams, where a gasifier−carbonator operated at 10 bar and 825 °C using steam, and a combustor−calciner operated at atmospheric pressure and 1000 °C.10 Enhanced H2 production (up to 75% dry vol) at lower temperatures (600− 700 °C) and low tar contents (thought to be due to tar cracking mechanisms catalyzed by CaO) from biomass steam gasification was recently achieved by means of the adsorptionenhanced reforming (AER) process,11 which was scaled up to a 100 kWth dual fluidized bed at the Vienna University of Technology12 and to an 8 MWth combined heat and power unit in Güssing, Austria, demonstrating the feasibility of sorption-enhanced gasification on an industrial scale.13 Furthermore, a detailed investigation of 20 kWth benchscale14 and 200 kWth pilot-scale dual fluidized bed reactors demonstrated the feasibility of sorption-enhanced reforming (SER) steam gasification for hydrogen production at the Institute of Combustion and Power Plant Technology (IFK) of the University of Stuttgart.15,16 Pfeifer17 reviewed the thermodynamics of sorption-enhanced gasification in detail on laboratory and pilot scales and concluded that it has better overall performance with respect to gas composition, gas yield, and tar concentration compared with that of the nonenhanced gasification process. Most models for integrated biomass gasification and CO2 capture are based on thermodynamic equilibrium, with few models based on reaction kinetics. The upper limit for the lime-enhanced H2 production process has been frequently studied via thermodynamic analysis.8,18,19 Equilibrium models developed in Aspen Plus have been used to find the desirable operating conditions for sorbent-enhanced biomass gasification.20−23 Pröll et al.8 developed a process simulation model for gasification of biomass in a dual fluidized bed gasifier, with and without lime-based CO2 capture in IPSEpro software. This study shows that CO2 capture enhances the

(1)

° = −178 kJ/mol ΔHrxn (2)

Carbonation occurs when the partial pressure of CO2 exceeds its equilibrium partial pressure at a given temperature, at a rate that depends on several process parameters. On the other hand, the endothermic calcination reaction, which readily goes to completion for a wide range of conditions, is favored for CO2 partial pressures less than the equilibrium value. Figure 2 shows a schematic of integrated biomass steam gasification with in situ Ca-looping. Replacement of inert bed material such as silica sand by limestone particles within the dual fluidized bed configuration gives the limestone particles dual roles of a heat carrier and a selective sorbent for CO2 12954

DOI: 10.1021/acs.iecr.9b01241 Ind. Eng. Chem. Res. 2019, 58, 12953−12963

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Industrial & Engineering Chemistry Research

• There is negligible loss of sorbent and char due to entrainment. • Heterogeneous char gasification and sorbent carbonation reactions are chemically controlled. • Complete char combustion and complete limestone calcination occur inside the combustor−calciner.29,30 2.1. Reaction Kinetics. As seen in Figure 3, the primary pyrolysis kinetic model includes thermal decomposition of

hydrogen content of the product gas and increases the energy efficiency of the process. Ahmad et al.24 used PETRONAS iCON to simulate hydrogen production from high-pressure biomass gasification integrated with CO2 capture. They reported that increasing gasifier temperature, pressure, and steam-to-biomass ratio increased the hydrogen yield. The influences of temperature, steam/biomass ratio (S/B), and sorbent/biomass ratio on steam gasification were analyzed by Inayat et al.25 via MATLAB. The thermodynamic efficiency of the gasifier was observed to increase with increasing temperature and S/B. Furthermore, they predicted a 10% increase in thermodynamic efficiency after using CaO as a sorbent in the gasifier. Hejazi et al.18 performed a modeling study on the effects of various operating conditions, such as temperature, pressure, S/B, sorbent circulation rate, and others, on enhanced H2 production with in situ cyclic CO2 capture. On the basis of a survey of the main fluidized bed gasifier models, there are still ambiguities associated with the model structure. There is a lack of comparison with experimental results from large-scale fluidized bed gasifiers. Such data are necessary to make models comprehensive and reliable. The novelty of the present study is the presentation of a steady-state kinetic reactor model that is capable of predicting the behavior of bench- and pilot-scale steam gasification of biomass with Ca-looping in a dual fluidized bed reactor over wide ranges of operating conditions. To develop a kinetic model, primary and secondary biomass pyrolysis kinetic mechanisms, major heterogeneous and homogeneous gasification reactions, and carbonation kinetic rates of sorbent particles are included in an ideal reactor model. The model developed in this paper extends an earlier model,26 with the added CO2 capture feature as per the derivations below. Although other model features remain common to the ones developed previously,26 the good agreement of this model’s predictions with additional experimental data is a significant step toward model validation. This kinetic model provides a practical approach to tackling the complicated task of modeling Ca-looping in dual fluidized bed biomass gasifiers, which are usually modeled assuming thermodynamic equilibrium. The generality of our model is verified by comparing its predictions with experimental data. These include the effects of the Calooping rate, steam/biomass ratio, and gasifier temperature on the product gas distribution. Our idealized fluidized bed reactor model reveals the dominance of the kinetics of such reactions as water−gas shift and carbonation on the product gas distribution. In addition, the effect of sorbent sintering due to cyclic operation is incorporated as a severe challenge confronting the feasibility of Ca-looping enhanced biomass gasification.

Figure 3. Primary biomass pyrolysis kinetic mechanism.31−33

biomass to noncondensable gas, tar, and char according to three parallel first-order rate expression:31−33 kj = k 0j exp( −Ej /RT )

(3)

where the pre-exponential factors and activation energies are reported in Table 1. Details of the elemental balances used to estimate dry pyrolysis gas composition (wi,pyro) are discussed elsewhere.26 Table 1. Kinetic Parameters for Primary Pyrolysis33 j

k0j (s−1)

Ej (kJ/mol)

ΔHrxn,j (kJ/kg)

1 2 3

1.30 × 108 2.00 × 108 1.08 × 107

140 133 121

64 64 64

For modeling thermal cracking of tar generated from primary pyrolysis to noncondensable gas over a wide range of operating conditions, phenol is used as a model tar compound.34 The kinetic rate expressions for secondary pyrolysis and the major gasification reactions are listed in Tables 2 and 3, respectively. Experimental evidence shows that after the formation of a critical thickness of the CaCO3 layer (h), the carbonation shifts from a fast chemically controlled regime to a slow diffusioncontrolled one.43−45 Because of its simplicity, the shrinking core model (SCM) has been widely adopted to describe the carbonation reaction in both regimes.46,47 A modified version of SCM was used by Johnsen et al.48 that was only applicable at lower conversions. Bhatia et al.49 successfully used the random pore model (RPM) to predict the behavior of CaO carbonation in the reaction and diffusion-controlled regimes. However, their model was complex and required many structural parameters. Some researchers modified RPM to account for the abrupt transition between the two carbonation regimes.50,51 In RPM, the effects of product layer diffusion and the surface reaction are neglected in the reaction and diffusioncontrolled stages, respectively. Liu et al.52 modified the grain model (GM) to consider both the rapid reaction and diffusioncontrolled regimes during the carbonation process. Stendardo et al.53 proposed structural changes to GM by including variable gas diffusivity. In addition to SCM, RPM, and GM, apparent kinetic models have been adopted as the simplest modeling approach for carbonation. Sun et al.43 developed a model based on the discrete pore size distribution with

2. MODEL DEVELOPMENT A steady-state kinetic reactor model is developed for biomass steam gasification with in situ CO2 capture via Ca-looping in a bubbling fluidized bed (BFB) that is a component of a dual fluidized bed (DFB) reactor. However, modeling char combustion and sorbent calcination in the internally connected riser is beyond the scope of the current work. To develop this model, the following simplifying assumptions are adopted, in addition to those listed by Hejazi et al.26 • The bed material consists of sorbent and char particles, with weak catalytic effects on tar cracking reactions.27,28 12955


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Industrial & Engineering Chemistry Research Table 2. Reaction Network for Secondary Pyrolysis of Tar tar cracking/reforming reaction

reaction kinetic rate expression

C6H6O → CO + 0.4C10H8 + 0.15C6H6 + 0.1CH4 + 0.75H 2

C6H6O + 3H 2O → 4CO + 2CH4 + 2H 2

−3 −1

7

5

−3 −1

7

5

ref

rtar1 (mol·m ·s ) = 10 exp(− 10 /RT )CC6H6O

ref 35

rtar2 (mol·m ·s ) = 10 exp(− 10 /RT )CC6H6O −3 −1

C10H8 → 7.38C + 0.275C6H6 + 0.97CH4 + 1.235H 2

14

ref 35 5

1.6

−0.5

5

1.3

−0.4

rtar3 (mol·m ·s ) = 1.7 × 10 exp(− 3.5 × 10 /RT )CC10H8 C H2 −3 −1

C6H6 + 2H 2O → 1.5C + 2.5CH4 + 2CO

16

rtar4(mol· m · s ) = 2.0 × 10 exp(− 4.43 × 10 /RT )CC6H6 C H2

ref 36

C H2O

0.2

ref 36

Table 3. Major Gasification Reactions gasification reaction

reaction kinetic rate expression −1

9.25

ref

0.4

(

)

C(s) + CO2 → 2CO

rC1 (s ) = 10

C(s) + H 2O → CO + H 2

rC2 (s−1) = 1.23 × 107 exp(− 198 000/RT )pH O0.75 (1 − x ̅ ) 2

exp(− 262 000/RT ) pCO /ptotal

−1

rC3 (s ) = 16.4 exp(− 94 800/RT )PH2

C(s) + 2H 2 → CH4

−3 −1

2

0.75

(1 − x ̅ )

37 38

0.93

39

5

CH4 + H 2O ↔ CO + 3H 2

rSMR (mol· m · s ) = 3 × 10 exp(− 125 000/RT )CCH4C H2O

40

CO + H 2O ↔ CO2 + H 2

KWGS = 0.0265 exp(3968/T )

41

rWGS (mol·m−3·s−1) = 2.78 exp(− 1510/T ) CCOC H2O − CCO2C H2/KWGS

(

)

42

product layer effective diffusivity as the only curve-fitting parameter. The first-order carbonation kinetic rate of Grasa et al.54 is adopted in this work because of its applicability in a wide range of operating conditions: rcarb (s−1) = KSSav(1 − Xav )2/3 (CCO2 − CCO2,equil)

(4)

where KS is an intrinsic kinetic constant, and Sav is the particle average specific surface area that is proportional to the average carbonation conversion (Xav): Sav = ρCaO (VM CaCO3Xav /MWCaOh)

(5)

Table 4. Parameters Used to Calculate Sorbent Carbonation54 KS (m4/mol/s) −10

6.05 × 10

VMCaCO3 (m3/mol)

h (m)

36.9 × 10−6

50 × 10−9

Figure 4. Schematic of BFB reactor model. Black circles provide schematic representations of biomass or char and limestone particles.

for which Table 4 gives the values of the parameters used in this study. Furthermore, the equilibrium CO2 concentration is expressed as a function of carbonation temperature:55

Assuming that carbonation is an independent reaction occurring in parallel with other reactions and accounting for the contribution of biomass pyrolysis, tar cracking, and the homogeneous and heterogeneous gasification reactions, the ordinary one-dimensional differential equation is written for the CO2 mass balance, where the rate of selective CO2 capture due to Ca-looping is also taken into account. Therefore

10(−8308/T ) + 12.079 (6) RT 2.2. Reactor Model. Figure 4 provides a schematic of the BFB gasifier−carbonator model, which assumes perfect mixing of solids and plug flow of gas phase inside the dense bubbling bed. Assuming that the water vapor and volatiles released from biomass drying and pyrolysis, respectively, are uniformly distributed among the cells of the gas phase region of the dense bed of uniform temperature, the one-dimensional differential equations for tar and noncondensable gaseous species mass balances are written as in Hejazi et al.26 CCO2,equil =

dṁ CO2 dz

=

dṁ CO2,pyro dz

+

dṁ CO2,gas dz

+

dṁ CO2,carb dz

(7)

If Mchar and MCaO are the char and reacting sorbent hold-ups inside the dense bubbling bed of cross-sectional area A and height Lbed, then 12956


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Figure 5. Algorithm for simulation of lime-enhanced biomass gasification in a dual fluidized bed reactor.

dṁ CO2,pyro dz

= k1/(k1 + k 2 + k 3) × (ṁ B,in × wCO2,pyro/L bed)

dṁ CO2,gas dz

dz

(10)

∫0

Lbed

ij dṁchar,gas yz jj zz dz jj zz k dz {

(rC1 + rC2 + rC3)(Mchar /L bed) dz

(14)

(11)

where ṁchar,out = Mchar /τP

(12)

ṁchar,gen = k 3ṁ B,in /(k1 + k 2 + k 3)

(13)

(15)

Assuming that the perfectly mixed gasifier bed particles have the same average characteristics and given the experimentally determined mean solids residence time, the biomass char reactivity is approximated on the basis of the average char conversion (x̅) obtained iteratively from an overall char balance over the dense bubbling bed. In order to approximate the average carbonation conversion, Xav, on the basis of the reactor design specifications and operating conditions, several issues affecting the decay of sorbent effectiveness must be taken into account, such as • sorbent loss of surface area due to multiple capture and release cycles (i.e., sintering) • sufation of CaO • attrition and carryover of sorbent

The differential gas mass balances for H2, CO, and CH4 are similar to those given in ref 26. From a char balance over the bed with a mean solids residence time of τP and no char in the feed at steady-state ṁchar,out = ṁchar,gen − ṁchar,cons

=

Lbed

Mchar = k 3ṁ B,in /(k1 + k 2 + k 3) ÄÅ ÉÑ−1 Lbed ÅÅ Ñ (rC1 + rC2 + rC3) dz ÑÑÑ ÅÅ ∫ ÑÑ × ÅÅÅÅ1/τP + 0 ÑÑ ÅÅ ÑÑ L bed ÅÅÇ ÑÑÖ

(9)

= {(1 − ε)(MCaO/MWCaO)( −rcarb) /[AL bed(1 − ε)]}A × MWCO2

∫0

Substituting these values in the char balance equation, we obtain

= {ε(rWGS) + (1 − ε)(Mchar /MWchar)( −rC1) /[AL bed(1 − ε)]}A × MWCO2

dṁ CO2,carb

(8)

ṁchar,cons =

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Figure 6. Effect of Ca-looping ratio on dry and N2-free product gas composition for lime-enhanced steam gasification of wood pellets at a reactor temperature of 650 °C. Continuous lines: model results (this work). Circles: experimental data from Poboss et al.14

MCaO = ṁ CaO,in

• CO2 diffusion resistances due to formation of a CaCO3 product layer on the surface of the particles Given a mean solids residence time (τP) from experimental measurements, no independent calculation of the average carbonation conversion is required in our model. Instead, the average carbonation conversion is estimated through an iterative procedure similar to that used above to determine the char hold-up in the dense bed. From a CaO balance on the dense bubbling bed at steady-state, the consumption rate of CaO in the carbonator−gasifier is ṁ CaO,out = ṁ CaO,in − ṁ CaO,cons

3. RESULTS AND DISCUSSION 3.1. Experimental Information. Because of their clearly defined design specifications and operating conditions, as well as the extensive variation of parameters such as the Ca-looping ratio, gasifier temperature, and steam-to-biomass ratio, the predictions of our model are first tested with the experimental results of Poboss et al.14,16 They studied the effects of the Calooping ratio (defined as the ratio of the molar flow rate of regenerated sorbent (CaO) to that of fuel carbon) on product gas yield and composition from sorption-enhanced reforming of biomass in a 20 kWth DFB reactor at the Institute of Combustion and Power Plant Technology (IFK). This DFB facility consists of a CFB regenerator, 12.4 m in height and 70 mm in diameter, and a BFB gasifier, 3.5 m in height and 114 mm in diameter. The experiments were carried out with steam as the fluidizing−gasifying agent and wood pellets as feedstock certified as EN 14961-2.14,16 Approximately 15 kg of precalcined Greek limestone of particle diameter 300−600 μm were used as the bed material in the DFB system.14,16 The

If MCaO is the reacting sorbent hold-up inside the dense bed, then (17)

ṁ CaO,cons = ṁ CaO,in Xav

(18)

On the other hand, from the axial partial pressure profile of CO2 in the gas phase, the CaO consumption rate can be approximated by ṁ CaO,cons =

∫0

=

∫0

Lbed

Lbed

ij dṁ CaO,carb yz jj zz dz j z d z k {

(rcarb)(MCaO/L bed) dz

(21)

Assuming negligible carryover of char and sorbent particles, only homogeneous reactions occur inside the solid-free freeboard (εfb = 1) that is modeled as an ideal plug flow reactor with boundary conditions specified at the surface of the bubbling bed. The algorithm for simulation of lime-enhanced biomass gasification in the BFB gasifier of a dual fluidized bed reactor is provided in Figure 5, where the char and sorbent hold-ups, as well as the expanded dense bed height, are obtained iteratively.

(16)

ṁ CaO,out = MCaO/τP

L ij ∫0 bed rcarb dz yzzz jj zz × jjj1/τP + zz jj L bed zz j k {

−1

• deactivation of sorbent particles due to coke formation

(19)

By combining eqs 16−19, the hold-up of sorbent available for CO2 capture is 12958


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Industrial & Engineering Chemistry Research gasifier and regenerator temperatures were set at 650 and 850 °C, respectively, ensuring complete combustion of char and calcination of the bed material at atmospheric pressure. The most important experimental conditions during the experiments studying the effects of Ca-looping ratio are summarized in ref 14. We also compared model predictions with experimental data from the 200 kWth pilot-scale AER gasification process involving two coupled fluidized beds at the Institute of Combustion and Power Plant Technology (IFK) of the University of Stuttgart.16 This pilot-scale DFB facility consisted of a CFB regenerator, 10 m in height and 0.21 m in diameter, and a BFB gasifier, 6 m in height and 0.33 m in diameter. Steam gasification of wood pellets certified as EN 14961-2 was carried out in the presence of 30−50 kg of Greek limestone as the gasifier bed material. The gasifier and regenerator temperatures were varied from 600 to 750 °C and from 850 to 950 °C, respectively, under atmospheric pressure, and the Ca-looping rate was set at 100−800 kg/h. In order to compensate for the loss of sorbent material due to attrition and to maintain a constant total solids inventory, fresh limestone was continuously fed to the regenerator at a ratio of 0.06 mol of CaCO3 per mole of C fuel. The effect of the steam-tocarbon or steam-to-biomass ratio in the range S/B = 1−2 kg of H2O per kilogram of dry, ash-free fuel on product gas distribution was experimentally investigated by varying the steam flow rate at a relatively constant fuel flow rate. The experimental conditions for the 200 kWth DFB test series with variable temperature and variable steam-to-biomass ratio are listed in ref 16. 3.2. Modeling Results. Figures 6 and 7 illustrate the product gas composition and yield from biomass steam

Boudouard reactions. As seen in Figure 7, with an increasing Ca-looping ratio, the product gas yield decreases, mostly because of the reduced time available for biomass conversion inside the gasifier. Figure 8 compares the predicted dry and N2-free product gas composition as a function gasifier−carbonator temperature with pilot-scale experimental data of the 200 kWth IFK DFB reactor with operating conditions reported in ref 16. As seen, increasing the reactor temperature increases CO concentration and decreases H2 concentration because of the exothermic WGS reaction. Raising the reactor temperature also reverses the exothermic carbonation, leading to less CO2 capture and thus less lime-enhanced H2 production. At increased reactor temperature, carbonation no longer occurs because the CO2 partial pressure in the gasifier falls below its equilibrium value. For temperatures below 700 °C, the predicted H2 content of dry product gas for the lime-enhanced biomass gasification exceeds 70 mol %. As seen in Figure 8, the CO2 dry volume percent in the product gas is slightly overpredicted, at the cost of underprediction of the CO volume percent. The species concentration profiles along the BFB gasifier of the pilot plant experimental setup show increased CO2 concentration along the freeboard. As reported by Poboss et al.,16 temperature variations due to the introduction of hot, regenerated CaO particles from the CFB riser to the top of BFB dense bed could partly contribute to the these deviations. Moreover, neglecting entrainment of solid particles, the adiabatic plug flow model adopted for the freeboard does not account for heterogeneous reactions (e.g., carbonation and Boudouard) that could remove CO2 in the freeboard. Figure 9 compares model predictions on the effect of steam/ fuel carbon ratio (equivalent to S/B) on dry and N2-free product gas composition with pilot-scale experimental data from the 200 kWth IFK DFB reactor under the operating conditions of ref 16. Except for slight overprediction of CO2 and underprediction of CO, good agreement is observed over the entire range (S/B = 1−2). The discrepancy is likely to be mainly related to the simplistic freeboard model that does not account for heterogeneous carbonation and gasification reactions. Furthermore, the ratio of CO/CO2 dominated by the WGS shift reaction is strongly dependent on temperature variations along the freeboard, as well as on the catalytic effect of CaO and other alkali metal contents in biomass ash, ignored in the current model. Other model uncertainties are attributed to the adopted simplifying assumptions as elaborated in ref 26.

Figure 7. Effect of Ca-looping ratio on product gas yield for limeenhanced steam gasification of wood pellets at a reactor temperature of 650 °C. Continuous lines: model results (this work). Circles: experimental data points from Poboss et al.14

4. CONCLUSIONS A unique kinetic modeling approach is presented for limeenhanced biomass gasification, which is often modeled by thermodynamic equilibrium. By adopting a first-order kinetic model for the carbonation rate of limestone particles, the BFB gasifier kinetic model of a dual fluidized bed reactor is extended to account for selective CO2 capture under steadystate Ca-looping operation. The modeling approach in this paper is a compromise between complexity and applicability of a fluidized bed gasifier model and provides the basis for more reliable kinetic models of lime-enhanced biomass gasification. The value of the model is demonstrated by comprehensive comparisons of model predictions with bench- and pilot-scale experimental data on the effects of Ca-looping rate, gasifier temperature, and steam-to-biomass ratio over a wide range. Slight overprediction of CO2 and underprediction of CO are mainly attributed to temperature variations, as well as catalytic

gasification in the 20 kWth IFK DFB gasifier with limestone as the bed material as a function of the Ca-looping ratio. With increasing Ca-looping ratio, it is seen that more CO2 is captured in situ in the gasifier, shifting the WGS equilibrium forward toward more CO consumption and more H 2 production. The model predictions are in good agreement with experimental data from Poboss et al.14 The slight observed overprediction of CO2 concentration may be attributed to the freeboard of the biomass gasifier, which is modeled by an isothermal plug flow reactor.14 However, in reality, carryover of CaO particles and char particles could result in further CO2 capture via the carbonation and 12959


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Figure 8. Predicted dry and N2-free product gas composition for lime-enhanced steam gasification of wood pellets as a function of BFB gasifier− carbonator temperature. Continuous lines: model results (this work). Circles: experimental data points from Poboss et al.16

Figure 9. Predicted dry and N2-free product gas composition for lime-enhanced steam gasification of wood pellets as a function of steam/fuel carbon ratio (mol/mol). Continuous lines: model results (this work). Circles: experimental data from Poboss et al.16

below its equilibrium value. Furthermore, more than 70 mol %

effects of entrained sorbent and char particles in the freeboard of a real gasifier. Sensitivity analysis on gasifier−carbonator temperature as well as Ca-looping ratio clearly shows sorbent enhancement effects. According to the first-order intrinsic kinetic rate expression, carbonation no longer occurs above 700 °C because the CO2 partial pressure in the gasifier falls

H2 in dry product gas is expected. 12960


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■

τP

ASSOCIATED CONTENT

S Supporting Information *

mean solids residence time, s

Subscripts

The Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/acs.iecr.9b01241. Properties of the wood pellets and bed material used in the experimental study, operating conditions for the 20 kWth experimental study on variable Ca-looping ratios at IFK, operating conditions for the 200 kWth experimental study on variable gasifier temperature at IFK, and operating conditions for the 200 kWth experimental study on variable steam to biomass ratios at IFK (PDF)

Bijan Hejazi: 0000-0002-6912-7726

av B carb cons equil fb G gas gen i in j M pyro T V

Present Address

Abbreviations

A.M.-B.: NORAM Engineering, 200 Granville Street, Suite 1800, Vancouver, British Columbia V6C 1S4, Canada

AER a.r. BC BFB CHP CSTR DFB daf GM IFK LHV MS PFR RPM SCM S/B TGA WGS

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AUTHOR INFORMATION

Corresponding Author

*E-mail: [email protected] or [email protected]. Tel.: 00989155804299. ORCID §

Notes

The authors declare no competing financial interest.

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ACKNOWLEDGMENTS The authors gratefully acknowledge financial aid from Carbon Management Canada and the Natural Sciences and Engineering Research Council of Canada.

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NOMENCLATURE A bubbling bed cross-sectional area, m2 Ci concentration of species i, mol/m3 Ej activation energy of jth reaction, kJ/mol h thickness of CaCO3 product layer, m k0j pre-exponential factor of jth reaction, s−1 kj Arrhenius-type kinetic rate constant of jth reaction, s−1 KS intrinsic kinetic rate constant for carbonation reaction, m4/mol·s KWGS equilibrium constant for water−gas shift reaction,  Lbed dense bubbling bed height, m ṁ̇ mass flow rate, kg/s MCaO CaO hold-up inside dense bed, kg Mchar char hold-up inside dense bed, kg MW molecular weight, g/mol P reactor pressure, Pa Pi partial pressure of ith species, Pa VMCaCO3 molar volume of CaCO3, m3/mol r reaction rate, s−1 or mol/m3·s R universal ideal gas constant, 8.314 J/mol·K Sav average specific surface area available for sorbent particles carbonation, m2/m3 T temperature, K w mass fraction,  x̅ average char conversion,  Xav average carbonation conversion,  z axial coordinate along reactor height, m

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average biomass carbonation consumption equilibrium freeboard noncondensable gas gasification generation species number input to reactor reaction number moisture pyrolysis tar water vapor absorption enhanced reforming as-received boundary condition bubbling fluidized bed combined heat and power continuous stirred tank reactor dual fluidized bed dry, ash-free grain model Institute of Combustion and Power Plant Technology lower heating value mass spectrometry plug flow reactor random pore model shrinking core model steam-to-biomass ratio thermogravimetric analysis water−gas shift

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ΔH°rxn heat of reaction at standard conditions, kJ/mol ΔHrxn,j heat of jth reaction, kJ/kg ε bed voidage at height z,  12961


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Kinetic Modeling of Lime-Enhanced Biomass Steam Gasification in a

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