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Kinetic study of the catalytic reforming of biomass pyrolysis volatiles over a commercial Ni/Al2O3 catalyst Aitor Arregi, Gartzen Lopez*, Maider Amutio, Itsaso Barbarias, Laura Santamaria, Javier Bilbao, Martin Olazar Department of Chemical Engineering, University of the Basque Country UPV/EHU, P.O. Box 644, E48080 Bilbao, Spain
article info
abstract
Article history:
An original kinetic model has been proposed for the reforming of the volatiles derived from
Received 23 February 2018
biomass fast pyrolysis over a commercial Ni/Al2O3 catalyst. The pyrolysis-reforming
Received in revised form
strategy consists of two in-line steps. The pyrolysis step is performed in a conical
2 May 2018
spouted bed reactor (CSBR) at 500 C, and the catalytic steam reforming of the volatiles has
Accepted 4 May 2018
been carried out in-line in a fluidized bed reactor. The reforming conditions are as follows:
Available online xxx
600, 650 and 700 C; catalyst mass, 0, 1.6, 3.1, 6.3, 9.4 and 12.5 g; steam/biomass ratio, 4, and; time on stream, up to 120 min. The integration of the kinetic equations has been carried
Keywords:
out using a code developed in Matlab. The reaction scheme takes into account the indi-
Biomass
vidual steps of steam reforming of bio-oil oxygenated compounds, CH4 and C2-C4 hydro-
Pyrolysis
carbons, and the WGS reaction. Moreover, a kinetic equation for deactivation has been
Reforming
derived, in which the bio-oil oxygenated compounds have been considered as the main
Kinetic model
coke precursors. The kinetic model allows quantifying the effect reforming conditions
Hydrogen
(temperature, catalyst mass and time on stream) have on product distribution.
Catalyst
© 2018 Hydrogen Energy Publications LLC. Published by Elsevier Ltd. All rights reserved.
Introduction The production of H2 from renewable sources will be a way for solving near future problems involving the increasing demand of this raw material in industry and its potential use as energy carrier [1,2]. In this scenario, biomass is an attractive raw material to produce renewable H2 with a lower emission of greenhouse gases than by reforming natural gas, which is currently the main route for H2 production [3,4]. Amongst the different biomass conversion methods, onestep thermochemical routes (pyrolysis or gasification) are especially interesting for their industrial implementation and allow obtaining high H2 yields from different types of
biomasses, especially when in-situ reforming catalysts and CO2 capture sorbents are used [5,6]. Hydrogen production by reforming bio-oil (the main product in the biomass fast pyrolysis) has also received significant attention [7]. The attractive aspect of this initiative is that fast pyrolysis can be carried out in a delocalized way, at low temperatures (around 500 C) and attaining high bio-oil yields (in the 60e75 wt% range) [8]. Moreover, the high water content in the bio-oil obtained by pyrolysis is not a drawback, as it is used in the reforming process. The potential interest of steam reforming of bio-oil has been proven by studying the reforming of several model compounds [9e14], especially acetic acid [15e18], and the bio-oil aqueous fraction [19e24]. However, there are few studies dealing with the reforming of
* Corresponding author. E-mail address: [email protected] (G. Lopez). https://doi.org/10.1016/j.ijhydene.2018.05.032 0360-3199/© 2018 Hydrogen Energy Publications LLC. Published by Elsevier Ltd. All rights reserved. Please cite this article in press as: Arregi A, et al., Kinetic study of the catalytic reforming of biomass pyrolysis volatiles over a commercial Ni/Al2O3 catalyst, International Journal of Hydrogen Energy (2018), https://doi.org/10.1016/j.ijhydene.2018.05.032
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raw bio-oil [25e28], whose main problem is related to the catalyst deactivation caused by the deposition of high amounts of pyrolytic lignin produced by the repolymerization of phenolic compounds (derived from lignin pyrolysis). Consequently, in order to minimize catalyst deactivation, a bio-oil pretreatment is usually carried out by polymerizing and separating the pyrolytic lignin [28e30]. An interesting alternative of the aforementioned strategies lies in performing pyrolysis and reforming steps using two inline reactors, which allows establishing the optimum conditions in each step for obtaining almost all the hydrogen contained in the biomass [31]. This strategy has been studied by Waheed and Williams [32] by valorizing different types of biomasses in a semi continuous system with fixed bed reactors for pyrolysis and reforming steps. Nahil et al. [33] used the same system of reactors to study the improvement in H2 yield by CO2 adsorption in the reforming reactor. Efika et al. [34] used a continuous screw kiln reactor for the pyrolysis and a fixed bed reactor for the reforming of pyrolysis volatiles. In previous papers, the good performance of a configuration made up of a conical spouted bed reactor and a fluidized bed reactor has been reported for the pyrolysis-reforming of biomass in continuous regime [35,36]. The conical spouted bed reactor (CSBR) is a suitable reactor for the treatment of different types of biomasses due to the high heating rate and vigorous movement of the bed [37,38]. The yield of bio-oil is very high (around 75 wt%) at 500 C when feeding several types of biomasses [37,39,40]. Moreover, the applicability of this reactor has been validated operating in a 25 kg h1 pilot plant [41]. Furthermore, catalyst deactivation by coke deposition is attenuated when a fluidized bed reactor (FBR) is used rather than a fixed bed reactor. Erkiaga et al. [42] observed bed clogging by coke when a fixed bed reactor was used in a CSBRfixed bed system for H2 production from waste plastics. In order to progress towards the industrial implementation of this two in-line reactor system for H2 production from biomass, an original kinetic model has been developed in this study to quantify the effect reforming conditions (temperature, catalyst mass and time on stream) have on product distribution. The background of the kinetic modelling of biooil steam reforming or biomass pyrolysis volatiles refers exclusively to the reforming of bio-oil model compounds, such as ethanol, acetone, glycerol, acetol or acetic acid. Thus, steam reforming of two representative compounds in the aqueous fraction of bio-oil (acetone and ethanol) over nickel based supported catalysts (Ni/Al2O3 and Ni-Rh/Al2O3) has lez-Gil et al. [43], i.e., they analysed been investigated by Gonza the influence of temperature (in the ranges 500e1027 C for acetone and 200e900 C for ethanol) and of the steam/feed ratio. The kinetic model for acetone steam reforming has been developed considering five main reactions, as are: the steam reforming of acetone and CH4, the WGS reaction, the decomposition of acetone into ketene and CH4, and the decomposition of ketene into ethylene and CO. In the steam reforming of ethanol, the reforming of ethanol and CH4 and the WGS reaction have been considered. Wang et al. [11] studied the steam reforming of glycerol in the 400e600 C range on different Ni-Mg-Al based catalysts considering only the reaction of glycerol reforming and based on a power law model. The kinetics for the steam reforming of acetol, which is
representative of the ketonic fraction in the bio-oil, has been studied by Dubey and Vaidya [44] in a fixed bed reactor in the mez 350e500 C range, on a commercial 5% Pt/C catalyst. Galda et al. [45] proposed first-order kinetic equations in the steam reforming of acetic acid at 650 C, and calculated the kinetic constants for the formation of the main gaseous products (H2, CO2, CH4 and C2). It should be pointed out that the catalyst deactivation has not been considered in the aforementioned studies dealing with model compounds. In this study, a CH4 reforming Ni commercial catalyst has been used for the reforming of biomass pyrolysis volatiles, which has shown high activity for the steam reforming of different feeds derived from the pyrolysis of biomass [35], plastics [46e48] and their mixtures [49]. The methodology for developing the kinetic model consists in two calculation steps. Firstly, a kinetic model corresponding to zero time on stream (fresh catalyst) has been established. Following a similar procedure as the one by Oar-Arteta et al. [50] for the steam reforming of dimethyl ether (DME), a reaction scheme with four reaction steps has been chosen, i.e., the steam reforming of bio-oil oxygenated compounds, the WGS reaction, and the steam reforming of C2-C4 hydrocarbons and CH4 (produced from the decomposition of bio-oil oxygenates). Secondly, a deactivation kinetic equation has been coupled to the zero time on stream in order to quantify the decrease in catalyst activity with time on stream. The model proposed in this study allows quantifying the evolution of product distribution with time on stream, which is required in further studies dealing with the simulation of reforming processes and optimization of their operating conditions.
Experimental Materials The main characteristics of the pine wood waste used are set out in Table 1, which have been measured by the techniques described in previous studies [35,51]. The size of the biomass particles used (between 1 and 2 mm) eases their continuous feeding into the pyrolysis-reforming unit. The reforming catalyst used (G90LDP) is the one for CH4 reforming in industry. This catalyst was chosen mainly for its availability and because it avoids reproducibility problems in the catalyst preparation. The catalyst is composed of NiO, CaO and Al2O3, with the nominal content of NiO being 14 wt%
Table 1 e Pine sawdust characterization. Ultimate analysis (wt%) Carbon Hydrogen Nitrogen Oxygen Proximate analysis (wt%) Volatile matter Fixed carbon Ash Moisture HHV (MJ kg1)
49.33 6.06 0.04 44.57 73.4 16.7 0.5 9.4 19.8
Please cite this article in press as: Arregi A, et al., Kinetic study of the catalytic reforming of biomass pyrolysis volatiles over a commercial Ni/Al2O3 catalyst, International Journal of Hydrogen Energy (2018), https://doi.org/10.1016/j.ijhydene.2018.05.032
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according to the supplier (Su¨d Chemie). The catalyst is provided in the form of 10-hole rings with their size being 19 16 mm. Nevertheless, suitable fluidization in the FBR makes necessary crushing and sieving in order to attain particles in the 0.4e0.8 mm range. In addition, the reduction of the catalyst has been performed at 710 C for 4 h under a 10 vol% H2 stream, with this temperature being conditioned by the temperature programmed reduction (TPR) profile, which has been shown in previous studies together with the main physical properties of the catalyst [42,52].
Experimental equipment and operating conditions The bench-scale laboratory plant has been previously described in detail [35,53] and is provided with two in-line reactors (CSBR-FBR). The pyrolysis of biomass is carried out in a CSBR at 500 C because this is the suitable temperature to maximize the bio-oil fraction, with its yield being around 75 wt% using either N2 or steam as fluidizing agent [35,37,39,51]. The main dimensions of the CSBR are as follows: height of the conical section, 73 mm; diameter of the cylindrical section, 60.3 mm; angle of the conical section, 30 ; diameter of the bed bottom, 12.5 mm, and diameter of the gas inlet, 7.6 mm. A bed made up of 50 g of silica sand has been used in the reactor, with its particle size being in the 0.30e0.35 mm range in order to attain the fluidization regime needed for the vigorous movement of the bed. The biomass (0.75 g min1) and water (3 mL min1) have been fed continuously by means of a solid feeding system and a high pressure water pump, respectively. The steam injected into the reaction system crosses firstly a gas preheater located below the CSBR, which is filled with stainless steel pipes that increase the surface area for heat transfer and preheat the gases to the reaction temperature. The FBR used for the subsequent catalytic reforming step has a length of 440 mm and an internal diameter of 38.1 mm. The bed consists of 25 g of a mixture of catalyst (particle size in the 0.4e0.8 mm range) and silica sand (particle size in the 0.30e0.35 mm range) in order to ensure suitable fluidization of the bed and guarantee a velocity 3 or 4 times the minimum fluidization one. It should be emphasized that the attrition of the catalyst was negligible under these conditions due to its good mechanical properties and limited duration of the experimental runs. The experiments have been carried out at 600, 650 and 700 C with catalyst masses of 0, 1.6, 3.1, 6.3, 9.4 and 12.5 g in order to develop a kinetic model that predicts the initial product distribution and its evolution with time on stream. Moreover, the unit is provided with gas-solid and gasliquid separation systems, consisting of a lateral outlet for the char removal, high-efficiency cyclone, filter, condenser and coalescence filter. Finally, the analysis of the products has been carried out in-line, by means of a gas chromatograph (Agilent 6890) for volatile products and gas microchromatograph (Varian 4900) for permanent gases. A sample of the reforming reactor outlet stream (prior to condensation) has been injected into the gas chromatograph by means of a line thermostated at 280 C, once it has been diluted with an inert gas, using a suction pump connected to the vent of the chromatograph. The sampling point of the permanent gases is
placed after the liquid condensation system and several samples have been taken in each run operating always under steady state conditions in order to check the reproducibility of the experiments. The volatiles derived from the biomass pyrolysis are continuously fed into the FBR (CH1.93O0.92) and their composition has been determined by analysing the CSBR outlet stream. Thus, this molecular formula has been calculated based on the composition of the volatiles derived from biomass pyrolysis (gas and bio-oil), which has been reported elsewhere [35,51]. The significance of the oxygenate decomposition reactions has been determined at the temperatures at which the reforming step has been performed by replacing the catalyst with sand in the FBR. Further details of the product chromatographic analysis are given elsewhere [35].
Results The experimental results for the modelling have been obtained by conducting in-line pyrolysis-reforming of biomass. The experiments have been carried out under the following reforming conditions: temperature, 600, 650 and 700 C; catalyst mass, 0, 1.6, 3.1, 6.3, 9.4 and 12.5 g; time on stream, up to 2 h. A steam/biomass ratio of 4 has been used in all the experiments, given that almost the maximum H2 yield allowable by stoichiometry is attained under these conditions and a further increase in this parameter reduces energy efficiency in the process [35].
Proposed reaction scheme In order to establish the reaction scheme, the following reactions are considered: Reforming of bio-oil oxygenated compounds (CnHmOk ¼ CH1.93O0.92): Cn Hm Ok þ ðn kÞH2 O/ðn þ m=2 kÞH2 þ nCO
(1)
Water Gas Shift reaction (WGS): CO þ H2 O4H2 þ CO2
(2)
Reforming of the C2-C4 hydrocarbon fraction (produced by thermal decomposition of oxygenates): Cr Hs þ rH2 O/ðr þ s=2ÞH2 þ rCO
(3)
Reforming of CH4 (produced by thermal decomposition): CH4 þ H2 O/3H2 þ CO
(4)
Cracking of oxygenates and coke formation: Cn Hm Ok /Cx Hy Oz þ Cr Hs þ CH4 þ CO þ CO2 þ CðcokeÞ
(5)
It should be noted that the reactions involving oxygenate cracking and coke formation have not been considered in the proposed kinetic scheme due to the low content of coke obtained in the runs and the difficulty involving their kinetics.
Methodology for the kinetic modelling Ideal plug flow without radial concentration gradients has been assumed for the gas. Moreover, an isothermal bed has
Please cite this article in press as: Arregi A, et al., Kinetic study of the catalytic reforming of biomass pyrolysis volatiles over a commercial Ni/Al2O3 catalyst, International Journal of Hydrogen Energy (2018), https://doi.org/10.1016/j.ijhydene.2018.05.032
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been considered, as temperature differences at radial and longitudinal positions are lower than 1 C. This assumption is based on the turbulent solid mixing regime and the high heat transfer rates characteristic of fluidized beds. The change in the molar total flow rate, FT, has been considered along the reactor, since the reaction proceeds with an increase in the number of moles. Consequently, the mass conservation equation for each component i in the reaction scheme (H2, CO2, CO, H2O, CH4, C2-C4 hydrocarbons and bio-oil oxygenated compounds) in a differential element of the reactor volume (in which the catalyst mass is dW), is defined as follows: dFi dðFT xi Þ dxi dFT ¼ FT ¼ þ xi ¼ ðri Þ0 dW dW dW dW
(6)
where xi is the molar fraction of component i on a wet basis, Fi and FT are the molar flow rates of product i and the total molar flow rate, respectively, and (ri)0 is the formation rate at zero time on stream of each component i in the reaction medium. Based on Eq. (6), the evolution of the composition of each component along the reactor is obtained as follows: dxi ðri Þ0 xi dFT ¼ dW FT FT dW
(7)
The evolution of the molar fraction with catalyst mass, and therefore with the longitudinal position in the reactor, is calculated by integrating Eq. (7). Accordingly, the kinetic equations have been established considering the different reaction steps in the kinetic scheme in which component i is involved. ðri Þ0 ¼
j X
ðyi Þj rj 0
nc X i¼1
wi 4i ¼
nc X i¼1
wi ¼
1 p P xi
wi
p 2 X x*i;j xi;j
(9)
j¼1
where wi is the weight factor for each component i in the kinetic scheme, 4i is the sum of squares of the residuals for each component i, x*i,j is the molar fraction (on a wet basis) of the component i at the experimental condition j, xi,j is the corresponding predicted value, nc is the number of components in the kinetic scheme and p is the total number of experimental conditions. Moreover, weight factors (Eq. (10)) are required in the calculation of the error objective function to take into account
(10)
j¼1
The minimization of the error objective function and the integration of the model differential equations have been performed using fminsearch and ode15s Matlab functions, respectively. The fitting parameters are the kinetic constants for each step j in the reaction scheme, which are expressed as functions of Arrhenius equation. The Arrhenius equation has been reparameterized (Eq. (11)) by expressing the kinetic constant of each step (kj) as a function of its corresponding value (k*j ) at a reference temperature (T*), which leads to smaller binary correlation between the frequency factor and the activation energy [54,55]. Therefore, the parameters subjected to optimization in the kinetic model have been the kinetic constants at the reference temperature (650 C) and the corresponding activation energies. Ej 1 1 * kj ¼ k*j exp R T T
(11)
In addition, regression coefficients (R2) have been calculated based on the SST (Total Sum of Squares) and the SSE (Sum of Squares of the residuals), which is calculated as:
(8)
where (yi)j is the stoichiometric coefficient of component i in the step j in the kinetic scheme, and (rj)0 is the reaction rate in the step j. The calculation of the parameters for the kinetic model proposed has been carried out by fitting the experimental results of xi vs. W to the calculated ones by integrating Eq. (7) and determining the kinetic parameters of best fit by nonlinear multiple regression. A program has been developed in Matlab for the integration of the kinetic equations and application of the non-linear multiple regression. The models parameters have been obtained by minimizing an error objective function (OF) (Eq. (9)) defined as the weighted sum of squares of the differences between the experimental and calculated values of molar fractions: OF ¼
the by-products with low molar fractions. The values of these factors have been considered as inversely proportional to the average composition of each compound. The application of Eq. (10) gives similar results to those obtained by calculating the weight factors from the variances of the experimental results.
SSE ¼
p nc X 2 X x*i;j xi;j i¼1
(12)
j¼1
Kinetic model at zero time on stream The kinetic equations proposed for each step in the reaction scheme are shown in Eqs. 13e16, in which a first order reaction has been considered for each reactant. ðr1 Þ0 ¼ k1 xCn Hm Ok xH2 O
(13)
ðr2 Þ0 ¼ kWGS xCO xH2 O xH2 xCO2 KWGS
(14)
ðr3 Þ0 ¼ k3 xC2 C4 xH2 O
(15)
ðr4 Þ0 ¼ k4 xCH4 xH2 O
(16)
The equilibrium constant of the WGS reaction (KWGS) has been calculated based on the following expression: 1 1 KWGS ¼ exp a þ b þ c logðTÞ þ dT þ eT2 þ f 2 T T
(17)
in which parameters a-f have been calculated based on thermodynamic principles, using the methodology described by Smith [56]. These values are as follows: a ¼ 1.8 101; b ¼ 5.8 103; c ¼ 1.8; d ¼ 2.7 104; e ¼ 0; f ¼ 5.8 104. Table 2 shows the kinetic parameters (frequency factor and activation energy) for Eqs. 13e16, as well as the regression
Please cite this article in press as: Arregi A, et al., Kinetic study of the catalytic reforming of biomass pyrolysis volatiles over a commercial Ni/Al2O3 catalyst, International Journal of Hydrogen Energy (2018), https://doi.org/10.1016/j.ijhydene.2018.05.032
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coefficient, which have been calculated by the methodology described above. It should be noted that the results shown in Table 2 correspond to apparent kinetic parameters, given that kinetic experimental results were influenced by external and internal mass transfer limitations. As observed in Table 2, the frequency factor of the WGS reaction is the highest one, which shows that it is the fastest reaction. On the other hand, it should be noted that the activation energy for the reforming of bio-oil oxygenated compounds is low, 14.5 kJ mol1, whereas those corresponding to the reforming of CH4 and C2-C4 hydrocarbons and the WGS reaction are more sensitive to temperature in the 600e700 C range. Nevertheless, all activation energy values are quite low, which can be explained by the narrow temperature range studied and the similar product distribution obtained in all the experiments. Moreover, the low activation energies can be related to the fact that they are apparent values. In fact, the increase of both internal and external mass transfer limitations at higher temperatures give way to lower activation energy values. The external mass transfer limitations are associated to the use of fluidized bed reactor in the reforming step, with the interstitial gas velocity being lower than in fixed bed reactors. In addition, the high particle size of the catalyst used in this study (up to 0.8 mm) and its limited porous structure favor remarkable internal mass transfer limitations. Fig. 1 shows the quality of the fit for the kinetic model proposed by comparing the evolution of experimental results of product molar fractions with catalyst mass (dots) and those calculated using the model (lines). It should be noted that the experimental results have been obtained by extrapolating the evolutions of molar fractions with time on stream to zero time on stream. Moreover, the results obtained in the catalytic cracking without catalyst (bed made up of sand) have been considered at zero space time. The fitting is adequate and the model proposed predicts reasonably well the effect temperature and catalyst mass have on product distribution at zero time on stream.
Effect of reforming conditions on product distribution at zero time on stream As observed in Fig. 1, when catalyst mass is increased both the steam reforming (Eqs. (1), (3) and (4)) and the WGS (Eq. (2)) reaction are enhanced in the temperature range studied, and therefore H2 and CO2 molar fractions increase, whereas that corresponding to H2O decreases. The same trend has been
Table 2 e Apparent kinetic parameters of best fit and their corresponding confidence intervals at a 95% confidence level, and the regression coefficient. 1 k01, mol g1 cat s 1 k0WGS, mol g1 cat s 0 1 1 k3, mol gcat s 1 k04, mol g1 cat s 1 E1, kJ mol EWGS, kJ mol1 E3, kJ mol1 E4, kJ mol1 2
R
3
6.0 10 ± 3.6 101 ± 4.1 102 ± 1.3 102 ± 14.5 ± 2.2 30.0 ± 5.4 33.7 ± 5.7 20.7 ± 4.0 0.997
3
0.9 10 0.4 101 0.5 102 0.2 102
5
reported in the literature for H2 and CO2 yields in bio-oil reforming studies [29,57,58]. Thus, a maximum H2 production of around 11 wt% (by mass unit of biomass in the feed) is attained in the temperature range studied, which is higher than those in other studies in which pyrolysis and in-line catalytic reforming of biomass was carried out [59e62]. As observed in Fig. 1a, H2 concentration increases when the catalyst mass is increased, especially from 0 to 6.3 g, obtaining a maximum value for 9.4 g of catalyst. The same trend is observed for CO2 molar fraction, obtaining a maximum concentration in the 6.3e12.5 g range. Concerning by-product concentrations (Fig. 1b), it is observed that CH4 and C2-C4 hydrocarbon concentrations are very low at 600 C, even when space time is very low. Finally, the concentration of nonreacted bio-oil decreases considerably as catalyst mass is increased, attaining full reforming of oxygenated compounds with 12.5 g of catalyst. At 650 C (Fig. 1c and d) the effect of catalyst mass follows a similar trend as at 600 C, and the highest H2 and CO2 concentrations are achieved with a catalyst mass of 12.5 g, i.e., all oxygenated compounds are reformed. Finally, at 700 C (Fig. 1e and f), the reforming reaction rate is higher and the concentration of non-reacted bio-oil oxygenated compounds decreases rapidly when catalyst mass is increased, whereas H2 concentration increases. In this case, almost full conversion is obtained with a catalyst mass of 9.4 g. Consequently, this catalyst mass is lower than that corresponding to the same situation in the 600e650 C range. Nevertheless, a deactivation kinetic equation should be coupled with the model to quantify the evolution of product distribution with time on stream when the catalyst undergoes deactivation by coke deposition.
Kinetic equation of the deactivation In a previous study [53], coke deposition has been proven to be the main deactivating cause of the catalyst due to the blockage of Ni active sites. Given that the deactivation is fast and depends on reaction conditions, a kinetic model that quantifies their effect is required for establishing large scale operation strategies in the reforming process, such as reactionregeneration cycles or catalyst circulation in a fluidized bed reactor. A non-selective deactivation model has been considered, and therefore the same activity parameter has been used for the different steps in the kinetic scheme (reforming of oxygenated compounds, C2-C4 hydrocarbons and CH4, and the WGS reaction). Activity has been defined as the ratio between the reaction rate at time t and the reaction rate at zero time on stream: a¼
ri ðri Þ0
(18)
Consequently, the formation rate of component i at time t has been calculated based on the reaction rate at zero time on stream, (rj)0, Eqs. 13e16. The general expression for the kinetic equations is as follows: ri ¼
j X
ðyi Þj rj 0 a
(19)
Please cite this article in press as: Arregi A, et al., Kinetic study of the catalytic reforming of biomass pyrolysis volatiles over a commercial Ni/Al2O3 catalyst, International Journal of Hydrogen Energy (2018), https://doi.org/10.1016/j.ijhydene.2018.05.032
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Fig. 1 e Comparison of the experimental results of evolution of product molar fractions (dots) with catalyst mass at zero time on stream, with those predicted using the model (lines), at 600 C (a, b), 650 C (c, d) and 700 C (e, f).
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In order to solve Eq. (19), a deactivation kinetic equation is required to relate catalyst activity with operating conditions (temperature, time and composition of the reaction medium). Studies based on temperature programmed oxidation (TPO) and microscopic analysis allowed determining that coke
7
content and nature (amorphous and condensed) and their effect on catalyst activity are related to the concentration of bio-oil oxygenated compounds in the reaction medium [53]. This relationship allows confirming that bio-oil oxygenated compounds are the main coke precursors for amorphous and
Fig. 2 e Comparison of the experimental results of the evolution of product molar fractions with time on stream (dots) with those predicted by the model (lines), at 600 C (a, b), 650 C (c, d) and 700 C (e, f). Catalyst mass, 12.5 g. Please cite this article in press as: Arregi A, et al., Kinetic study of the catalytic reforming of biomass pyrolysis volatiles over a commercial Ni/Al2O3 catalyst, International Journal of Hydrogen Energy (2018), https://doi.org/10.1016/j.ijhydene.2018.05.032
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deactivating coke. This role of oxygenate compounds is consistent with the results obtained in the reforming of pure oxygenates [63e65] and bio-oil [19,29,66]. The formation of encapsulating amorphous coke has also been reported as the main responsible for the deactivation of Ni based catalysts in the biomass pyrolysis-reforming studies [32e34]. Therefore, the kinetic equation for deactivation considers catalyst deactivation rate proportional to the concentration of bio-oil oxygenated compounds in the reaction medium. da ¼ kd xCn Hm Ok a dt
(20)
where xCnHmOk is the molar fraction of bio-oil oxygenated compounds, kd is the kinetic constant of deactivation and a is activity. Considering catalyst activity, the reaction rates of the steps in the reaction scheme at t time on stream are as follows: r1 ¼ k1 xCn Hm Ok xH2 O a
(21)
r2 ¼ kWGS xCO xH2 O xH2 xCO2 KWGS a
(22)
Fig. 3 e Parity plot for the proposed model.
r3 ¼ k3 xC2 C4 xH2 O a
(23)
r4 ¼ k4 xCH4 xH2 O a
(24)
predicted by the model (lines) for three temperatures, 600 C (Fig. 2a and b), 650 C (Fig. 2c and d) and 700 C (Fig. 2e and f). The results correspond to a catalyst mass of 12.5 g, which has been taken as an example. In addition, Fig. 3 shows the adequate fit between the experimental and the predicted values (parity plot) of the molar fractions. As observed in Fig. 2, the model satisfactorily predicts the evolution of molar fractions of the products (H2, CO2, CO and H2O) with time on stream, which confirms the validity of Eq. (20). Moreover, the deactivation rate increases linearly when the concentration of bio-oil oxygenated compounds in the reaction medium is increased. The poorest fit for the evolution of the molar fractions of bio-oil oxygenated compounds and by-products (CH4 and C2-C4 hydrocarbons) should be attributed, on the one hand, to their very low values (they are much smaller than those for the reforming products) and, on the other hand, to the formation of these by-products by decomposition of oxygenated compounds, which are not considered in the reaction scheme due to the difficulty involving their kinetics (decomposition reactions overlap oxygenate reforming reactions). The fact that the deviation of results is higher when temperature is increased reinforces this hypothesis that oxygenate cracking is the main cause of this deviation. Concerning the evolution of product yields with time on stream, a similar trend was observed by Medrano et al. [67] in the reforming of biomass pyrolysis liquids at 650 C, in which a decrease in H2 and CO2 yields and an increase in CO and CH4 yields were observed. The same trends have also been reported by some authors in the steam reforming of bio-oil [19,22,68e70].
The equilibrium constant of the WGS reaction has been calculated using Eq. (17) with the aforementioned parameters. A similar methodology as that for zero time on stream has been used to calculate the kinetic parameters. The mass conservation equations for each component i (Eq. (6)) have been solved together with the deactivation kinetic equation, and the experimental molar fractions with time on stream have been fitted to the model by multiple non-linear regression. Given that the experimental values have been obtained in a fluidized bed reactor, there is no longitudinal profile of activity along the reactor, but activity is uniform at each time in the catalytic bed. Therefore, activity is calculated for each catalyst mass value, W, based on the following expression: Z
W
adW aW ¼
0
W
(25)
Thus, activity is calculated as an average for the whole bed for each time on stream. This average activity value is the one used to calculate the reaction rate of each step j in the reaction scheme (Eqs. 21e24) for each value of time on stream. The optimization has consisted in minimizing the error objective function (Eq. (9)). Similarly as in the kinetic modelling at zero time, the deactivation kinetic constants have been reparameterized. Furthermore, the kinetic parameters for the reaction steps are those previously calculated based on the results at zero time on stream (Table 2). Thus, the values calculated for the frequency factor and activation energy for the deactivation kinetic equation (Eq. (20)) have been 3.0 101 ± 0.4 101 s1 and 18.6 ± 2.4 kJ mol1, respectively, with R2 being 0.997. This low value of activation energy is evidence of a small effect of temperature in the 600e700 C range. The adequate fit of the kinetic model is shown in Fig. 2, in which the experimental data (dots) are compared with those
Conclusions A kinetic model has been established considering a scheme made up of four reactions, as are: reforming of bio-oil
Please cite this article in press as: Arregi A, et al., Kinetic study of the catalytic reforming of biomass pyrolysis volatiles over a commercial Ni/Al2O3 catalyst, International Journal of Hydrogen Energy (2018), https://doi.org/10.1016/j.ijhydene.2018.05.032
i n t e r n a t i o n a l j o u r n a l o f h y d r o g e n e n e r g y x x x ( 2 0 1 8 ) 1 e1 1
oxygenated compounds, C2-C4 hydrocarbons and CH4, and the WGS reaction. Likewise, a deactivation kinetic equation dependant on the concentration of bio-oil oxygenated compounds has been proposed because these are the main coke precursors, and therefore the main responsible for catalyst deactivation. The fitting of adequacy of the model proposed for quantifying the distribution of products (H2, CO2, CO, H2O, CH4, C2-C4 hydrocarbons and non-converted bio-oil oxygenated compounds) and the evolution of these products with time on stream have been verified. The model suitably fits the experimental results of component molar fraction at the reactor outlet, in the 600e700 C and 0e12.5 g ranges, and up to 2 h time on stream. Thus, the full kinetic model proposed suitably predicts the experimental results obtained in the reforming of volatiles from biomass pyrolysis, in a wide range of operating conditions. It is therefore a suitable tool for further simulation, optimization, and scaling up studies in CSBR-FBR systems for continuous H2 production from biomass.
Acknowledgments This work was carried out with financial support from the Ministry of Economy and Competitiveness of the Spanish Government (CTQ2016-75535-R (AEI/FEDER, UE) and CTQ2015-69436-R (MINECO/FEDER, UE)), the Basque Government (IT748-13) and the University of the Basque Country (UFI 11/ 39). A. Arregi and I. Barbarias thank the University of the Basque Country for their postgraduate grants (UPV/EHU 2017 and 2016, respectively).
Nomenclature a, aW Ej OF Fi, FT kd kj, k*j k0j KWGS nc p R R2 (ri)0, ri (rj)0, rj SSE SST t T, T* W
Catalyst activity and catalyst activity for each catalyst mass value Activation energy of the step j (kJ mol1) Error objective function Molar flow rate of product i and total molar flow rate (mol s1) Kinetic constant of deactivation (s1) Kinetic constant of step j at T temperature and at the 1 reference temperature (mol g1 cat s ) 1 1 Frequency factor (mol gcat s ) Equilibrium constant of the WGS reaction Number of compounds in the kinetic scheme Total number of experimental conditions Gas constant (kJ mol1 K1) Regression coefficient Formation rate of component i at zero time on 1 stream and at t time (mol g1 cat s ) Reaction rate of the step j at zero time on stream and 1 at t time (mol g1 cat s ) Sum of squares of the error Total sum of squares Time (min) Temperature and reference temperature (K) Catalyst mass (gcat)
wi xi x*i,j, xi,j (yi)j 4i
9
Weight factor for component i Molar fraction of component i in the reaction medium (on a wet basis) Experimental and predicted molar fractions of component i at the experimental condition j Stoichiometric coefficient of component i in the step j in the kinetic scheme Sum of squares of the residuals for component i
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Available online at www.sciencedirect.com
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Kinetic study of the catalytic reforming of biomass pyrolysis volatiles over a commercial Ni/Al2O3 catalyst Aitor Arregi, Gartzen Lopez*, Maider Amutio, Itsaso Barbarias, Laura Santamaria, Javier Bilbao, Martin Olazar Department of Chemical Engineering, University of the Basque Country UPV/EHU, P.O. Box 644, E48080 Bilbao, Spain
article info
abstract
Article history:
An original kinetic model has been proposed for the reforming of the volatiles derived from
Received 23 February 2018
biomass fast pyrolysis over a commercial Ni/Al2O3 catalyst. The pyrolysis-reforming
Received in revised form
strategy consists of two in-line steps. The pyrolysis step is performed in a conical
2 May 2018
spouted bed reactor (CSBR) at 500 C, and the catalytic steam reforming of the volatiles has
Accepted 4 May 2018
been carried out in-line in a fluidized bed reactor. The reforming conditions are as follows:
Available online xxx
600, 650 and 700 C; catalyst mass, 0, 1.6, 3.1, 6.3, 9.4 and 12.5 g; steam/biomass ratio, 4, and; time on stream, up to 120 min. The integration of the kinetic equations has been carried
Keywords:
out using a code developed in Matlab. The reaction scheme takes into account the indi-
Biomass
vidual steps of steam reforming of bio-oil oxygenated compounds, CH4 and C2-C4 hydro-
Pyrolysis
carbons, and the WGS reaction. Moreover, a kinetic equation for deactivation has been
Reforming
derived, in which the bio-oil oxygenated compounds have been considered as the main
Kinetic model
coke precursors. The kinetic model allows quantifying the effect reforming conditions
Hydrogen
(temperature, catalyst mass and time on stream) have on product distribution.
Catalyst
© 2018 Hydrogen Energy Publications LLC. Published by Elsevier Ltd. All rights reserved.
Introduction The production of H2 from renewable sources will be a way for solving near future problems involving the increasing demand of this raw material in industry and its potential use as energy carrier [1,2]. In this scenario, biomass is an attractive raw material to produce renewable H2 with a lower emission of greenhouse gases than by reforming natural gas, which is currently the main route for H2 production [3,4]. Amongst the different biomass conversion methods, onestep thermochemical routes (pyrolysis or gasification) are especially interesting for their industrial implementation and allow obtaining high H2 yields from different types of
biomasses, especially when in-situ reforming catalysts and CO2 capture sorbents are used [5,6]. Hydrogen production by reforming bio-oil (the main product in the biomass fast pyrolysis) has also received significant attention [7]. The attractive aspect of this initiative is that fast pyrolysis can be carried out in a delocalized way, at low temperatures (around 500 C) and attaining high bio-oil yields (in the 60e75 wt% range) [8]. Moreover, the high water content in the bio-oil obtained by pyrolysis is not a drawback, as it is used in the reforming process. The potential interest of steam reforming of bio-oil has been proven by studying the reforming of several model compounds [9e14], especially acetic acid [15e18], and the bio-oil aqueous fraction [19e24]. However, there are few studies dealing with the reforming of
* Corresponding author. E-mail address: [email protected] (G. Lopez). https://doi.org/10.1016/j.ijhydene.2018.05.032 0360-3199/© 2018 Hydrogen Energy Publications LLC. Published by Elsevier Ltd. All rights reserved. Please cite this article in press as: Arregi A, et al., Kinetic study of the catalytic reforming of biomass pyrolysis volatiles over a commercial Ni/Al2O3 catalyst, International Journal of Hydrogen Energy (2018), https://doi.org/10.1016/j.ijhydene.2018.05.032
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raw bio-oil [25e28], whose main problem is related to the catalyst deactivation caused by the deposition of high amounts of pyrolytic lignin produced by the repolymerization of phenolic compounds (derived from lignin pyrolysis). Consequently, in order to minimize catalyst deactivation, a bio-oil pretreatment is usually carried out by polymerizing and separating the pyrolytic lignin [28e30]. An interesting alternative of the aforementioned strategies lies in performing pyrolysis and reforming steps using two inline reactors, which allows establishing the optimum conditions in each step for obtaining almost all the hydrogen contained in the biomass [31]. This strategy has been studied by Waheed and Williams [32] by valorizing different types of biomasses in a semi continuous system with fixed bed reactors for pyrolysis and reforming steps. Nahil et al. [33] used the same system of reactors to study the improvement in H2 yield by CO2 adsorption in the reforming reactor. Efika et al. [34] used a continuous screw kiln reactor for the pyrolysis and a fixed bed reactor for the reforming of pyrolysis volatiles. In previous papers, the good performance of a configuration made up of a conical spouted bed reactor and a fluidized bed reactor has been reported for the pyrolysis-reforming of biomass in continuous regime [35,36]. The conical spouted bed reactor (CSBR) is a suitable reactor for the treatment of different types of biomasses due to the high heating rate and vigorous movement of the bed [37,38]. The yield of bio-oil is very high (around 75 wt%) at 500 C when feeding several types of biomasses [37,39,40]. Moreover, the applicability of this reactor has been validated operating in a 25 kg h1 pilot plant [41]. Furthermore, catalyst deactivation by coke deposition is attenuated when a fluidized bed reactor (FBR) is used rather than a fixed bed reactor. Erkiaga et al. [42] observed bed clogging by coke when a fixed bed reactor was used in a CSBRfixed bed system for H2 production from waste plastics. In order to progress towards the industrial implementation of this two in-line reactor system for H2 production from biomass, an original kinetic model has been developed in this study to quantify the effect reforming conditions (temperature, catalyst mass and time on stream) have on product distribution. The background of the kinetic modelling of biooil steam reforming or biomass pyrolysis volatiles refers exclusively to the reforming of bio-oil model compounds, such as ethanol, acetone, glycerol, acetol or acetic acid. Thus, steam reforming of two representative compounds in the aqueous fraction of bio-oil (acetone and ethanol) over nickel based supported catalysts (Ni/Al2O3 and Ni-Rh/Al2O3) has lez-Gil et al. [43], i.e., they analysed been investigated by Gonza the influence of temperature (in the ranges 500e1027 C for acetone and 200e900 C for ethanol) and of the steam/feed ratio. The kinetic model for acetone steam reforming has been developed considering five main reactions, as are: the steam reforming of acetone and CH4, the WGS reaction, the decomposition of acetone into ketene and CH4, and the decomposition of ketene into ethylene and CO. In the steam reforming of ethanol, the reforming of ethanol and CH4 and the WGS reaction have been considered. Wang et al. [11] studied the steam reforming of glycerol in the 400e600 C range on different Ni-Mg-Al based catalysts considering only the reaction of glycerol reforming and based on a power law model. The kinetics for the steam reforming of acetol, which is
representative of the ketonic fraction in the bio-oil, has been studied by Dubey and Vaidya [44] in a fixed bed reactor in the mez 350e500 C range, on a commercial 5% Pt/C catalyst. Galda et al. [45] proposed first-order kinetic equations in the steam reforming of acetic acid at 650 C, and calculated the kinetic constants for the formation of the main gaseous products (H2, CO2, CH4 and C2). It should be pointed out that the catalyst deactivation has not been considered in the aforementioned studies dealing with model compounds. In this study, a CH4 reforming Ni commercial catalyst has been used for the reforming of biomass pyrolysis volatiles, which has shown high activity for the steam reforming of different feeds derived from the pyrolysis of biomass [35], plastics [46e48] and their mixtures [49]. The methodology for developing the kinetic model consists in two calculation steps. Firstly, a kinetic model corresponding to zero time on stream (fresh catalyst) has been established. Following a similar procedure as the one by Oar-Arteta et al. [50] for the steam reforming of dimethyl ether (DME), a reaction scheme with four reaction steps has been chosen, i.e., the steam reforming of bio-oil oxygenated compounds, the WGS reaction, and the steam reforming of C2-C4 hydrocarbons and CH4 (produced from the decomposition of bio-oil oxygenates). Secondly, a deactivation kinetic equation has been coupled to the zero time on stream in order to quantify the decrease in catalyst activity with time on stream. The model proposed in this study allows quantifying the evolution of product distribution with time on stream, which is required in further studies dealing with the simulation of reforming processes and optimization of their operating conditions.
Experimental Materials The main characteristics of the pine wood waste used are set out in Table 1, which have been measured by the techniques described in previous studies [35,51]. The size of the biomass particles used (between 1 and 2 mm) eases their continuous feeding into the pyrolysis-reforming unit. The reforming catalyst used (G90LDP) is the one for CH4 reforming in industry. This catalyst was chosen mainly for its availability and because it avoids reproducibility problems in the catalyst preparation. The catalyst is composed of NiO, CaO and Al2O3, with the nominal content of NiO being 14 wt%
Table 1 e Pine sawdust characterization. Ultimate analysis (wt%) Carbon Hydrogen Nitrogen Oxygen Proximate analysis (wt%) Volatile matter Fixed carbon Ash Moisture HHV (MJ kg1)
49.33 6.06 0.04 44.57 73.4 16.7 0.5 9.4 19.8
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according to the supplier (Su¨d Chemie). The catalyst is provided in the form of 10-hole rings with their size being 19 16 mm. Nevertheless, suitable fluidization in the FBR makes necessary crushing and sieving in order to attain particles in the 0.4e0.8 mm range. In addition, the reduction of the catalyst has been performed at 710 C for 4 h under a 10 vol% H2 stream, with this temperature being conditioned by the temperature programmed reduction (TPR) profile, which has been shown in previous studies together with the main physical properties of the catalyst [42,52].
Experimental equipment and operating conditions The bench-scale laboratory plant has been previously described in detail [35,53] and is provided with two in-line reactors (CSBR-FBR). The pyrolysis of biomass is carried out in a CSBR at 500 C because this is the suitable temperature to maximize the bio-oil fraction, with its yield being around 75 wt% using either N2 or steam as fluidizing agent [35,37,39,51]. The main dimensions of the CSBR are as follows: height of the conical section, 73 mm; diameter of the cylindrical section, 60.3 mm; angle of the conical section, 30 ; diameter of the bed bottom, 12.5 mm, and diameter of the gas inlet, 7.6 mm. A bed made up of 50 g of silica sand has been used in the reactor, with its particle size being in the 0.30e0.35 mm range in order to attain the fluidization regime needed for the vigorous movement of the bed. The biomass (0.75 g min1) and water (3 mL min1) have been fed continuously by means of a solid feeding system and a high pressure water pump, respectively. The steam injected into the reaction system crosses firstly a gas preheater located below the CSBR, which is filled with stainless steel pipes that increase the surface area for heat transfer and preheat the gases to the reaction temperature. The FBR used for the subsequent catalytic reforming step has a length of 440 mm and an internal diameter of 38.1 mm. The bed consists of 25 g of a mixture of catalyst (particle size in the 0.4e0.8 mm range) and silica sand (particle size in the 0.30e0.35 mm range) in order to ensure suitable fluidization of the bed and guarantee a velocity 3 or 4 times the minimum fluidization one. It should be emphasized that the attrition of the catalyst was negligible under these conditions due to its good mechanical properties and limited duration of the experimental runs. The experiments have been carried out at 600, 650 and 700 C with catalyst masses of 0, 1.6, 3.1, 6.3, 9.4 and 12.5 g in order to develop a kinetic model that predicts the initial product distribution and its evolution with time on stream. Moreover, the unit is provided with gas-solid and gasliquid separation systems, consisting of a lateral outlet for the char removal, high-efficiency cyclone, filter, condenser and coalescence filter. Finally, the analysis of the products has been carried out in-line, by means of a gas chromatograph (Agilent 6890) for volatile products and gas microchromatograph (Varian 4900) for permanent gases. A sample of the reforming reactor outlet stream (prior to condensation) has been injected into the gas chromatograph by means of a line thermostated at 280 C, once it has been diluted with an inert gas, using a suction pump connected to the vent of the chromatograph. The sampling point of the permanent gases is
placed after the liquid condensation system and several samples have been taken in each run operating always under steady state conditions in order to check the reproducibility of the experiments. The volatiles derived from the biomass pyrolysis are continuously fed into the FBR (CH1.93O0.92) and their composition has been determined by analysing the CSBR outlet stream. Thus, this molecular formula has been calculated based on the composition of the volatiles derived from biomass pyrolysis (gas and bio-oil), which has been reported elsewhere [35,51]. The significance of the oxygenate decomposition reactions has been determined at the temperatures at which the reforming step has been performed by replacing the catalyst with sand in the FBR. Further details of the product chromatographic analysis are given elsewhere [35].
Results The experimental results for the modelling have been obtained by conducting in-line pyrolysis-reforming of biomass. The experiments have been carried out under the following reforming conditions: temperature, 600, 650 and 700 C; catalyst mass, 0, 1.6, 3.1, 6.3, 9.4 and 12.5 g; time on stream, up to 2 h. A steam/biomass ratio of 4 has been used in all the experiments, given that almost the maximum H2 yield allowable by stoichiometry is attained under these conditions and a further increase in this parameter reduces energy efficiency in the process [35].
Proposed reaction scheme In order to establish the reaction scheme, the following reactions are considered: Reforming of bio-oil oxygenated compounds (CnHmOk ¼ CH1.93O0.92): Cn Hm Ok þ ðn kÞH2 O/ðn þ m=2 kÞH2 þ nCO
(1)
Water Gas Shift reaction (WGS): CO þ H2 O4H2 þ CO2
(2)
Reforming of the C2-C4 hydrocarbon fraction (produced by thermal decomposition of oxygenates): Cr Hs þ rH2 O/ðr þ s=2ÞH2 þ rCO
(3)
Reforming of CH4 (produced by thermal decomposition): CH4 þ H2 O/3H2 þ CO
(4)
Cracking of oxygenates and coke formation: Cn Hm Ok /Cx Hy Oz þ Cr Hs þ CH4 þ CO þ CO2 þ CðcokeÞ
(5)
It should be noted that the reactions involving oxygenate cracking and coke formation have not been considered in the proposed kinetic scheme due to the low content of coke obtained in the runs and the difficulty involving their kinetics.
Methodology for the kinetic modelling Ideal plug flow without radial concentration gradients has been assumed for the gas. Moreover, an isothermal bed has
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been considered, as temperature differences at radial and longitudinal positions are lower than 1 C. This assumption is based on the turbulent solid mixing regime and the high heat transfer rates characteristic of fluidized beds. The change in the molar total flow rate, FT, has been considered along the reactor, since the reaction proceeds with an increase in the number of moles. Consequently, the mass conservation equation for each component i in the reaction scheme (H2, CO2, CO, H2O, CH4, C2-C4 hydrocarbons and bio-oil oxygenated compounds) in a differential element of the reactor volume (in which the catalyst mass is dW), is defined as follows: dFi dðFT xi Þ dxi dFT ¼ FT ¼ þ xi ¼ ðri Þ0 dW dW dW dW
(6)
where xi is the molar fraction of component i on a wet basis, Fi and FT are the molar flow rates of product i and the total molar flow rate, respectively, and (ri)0 is the formation rate at zero time on stream of each component i in the reaction medium. Based on Eq. (6), the evolution of the composition of each component along the reactor is obtained as follows: dxi ðri Þ0 xi dFT ¼ dW FT FT dW
(7)
The evolution of the molar fraction with catalyst mass, and therefore with the longitudinal position in the reactor, is calculated by integrating Eq. (7). Accordingly, the kinetic equations have been established considering the different reaction steps in the kinetic scheme in which component i is involved. ðri Þ0 ¼
j X
ðyi Þj rj 0
nc X i¼1
wi 4i ¼
nc X i¼1
wi ¼
1 p P xi
wi
p 2 X x*i;j xi;j
(9)
j¼1
where wi is the weight factor for each component i in the kinetic scheme, 4i is the sum of squares of the residuals for each component i, x*i,j is the molar fraction (on a wet basis) of the component i at the experimental condition j, xi,j is the corresponding predicted value, nc is the number of components in the kinetic scheme and p is the total number of experimental conditions. Moreover, weight factors (Eq. (10)) are required in the calculation of the error objective function to take into account
(10)
j¼1
The minimization of the error objective function and the integration of the model differential equations have been performed using fminsearch and ode15s Matlab functions, respectively. The fitting parameters are the kinetic constants for each step j in the reaction scheme, which are expressed as functions of Arrhenius equation. The Arrhenius equation has been reparameterized (Eq. (11)) by expressing the kinetic constant of each step (kj) as a function of its corresponding value (k*j ) at a reference temperature (T*), which leads to smaller binary correlation between the frequency factor and the activation energy [54,55]. Therefore, the parameters subjected to optimization in the kinetic model have been the kinetic constants at the reference temperature (650 C) and the corresponding activation energies. Ej 1 1 * kj ¼ k*j exp R T T
(11)
In addition, regression coefficients (R2) have been calculated based on the SST (Total Sum of Squares) and the SSE (Sum of Squares of the residuals), which is calculated as:
(8)
where (yi)j is the stoichiometric coefficient of component i in the step j in the kinetic scheme, and (rj)0 is the reaction rate in the step j. The calculation of the parameters for the kinetic model proposed has been carried out by fitting the experimental results of xi vs. W to the calculated ones by integrating Eq. (7) and determining the kinetic parameters of best fit by nonlinear multiple regression. A program has been developed in Matlab for the integration of the kinetic equations and application of the non-linear multiple regression. The models parameters have been obtained by minimizing an error objective function (OF) (Eq. (9)) defined as the weighted sum of squares of the differences between the experimental and calculated values of molar fractions: OF ¼
the by-products with low molar fractions. The values of these factors have been considered as inversely proportional to the average composition of each compound. The application of Eq. (10) gives similar results to those obtained by calculating the weight factors from the variances of the experimental results.
SSE ¼
p nc X 2 X x*i;j xi;j i¼1
(12)
j¼1
Kinetic model at zero time on stream The kinetic equations proposed for each step in the reaction scheme are shown in Eqs. 13e16, in which a first order reaction has been considered for each reactant. ðr1 Þ0 ¼ k1 xCn Hm Ok xH2 O
(13)
ðr2 Þ0 ¼ kWGS xCO xH2 O xH2 xCO2 KWGS
(14)
ðr3 Þ0 ¼ k3 xC2 C4 xH2 O
(15)
ðr4 Þ0 ¼ k4 xCH4 xH2 O
(16)
The equilibrium constant of the WGS reaction (KWGS) has been calculated based on the following expression: 1 1 KWGS ¼ exp a þ b þ c logðTÞ þ dT þ eT2 þ f 2 T T
(17)
in which parameters a-f have been calculated based on thermodynamic principles, using the methodology described by Smith [56]. These values are as follows: a ¼ 1.8 101; b ¼ 5.8 103; c ¼ 1.8; d ¼ 2.7 104; e ¼ 0; f ¼ 5.8 104. Table 2 shows the kinetic parameters (frequency factor and activation energy) for Eqs. 13e16, as well as the regression
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coefficient, which have been calculated by the methodology described above. It should be noted that the results shown in Table 2 correspond to apparent kinetic parameters, given that kinetic experimental results were influenced by external and internal mass transfer limitations. As observed in Table 2, the frequency factor of the WGS reaction is the highest one, which shows that it is the fastest reaction. On the other hand, it should be noted that the activation energy for the reforming of bio-oil oxygenated compounds is low, 14.5 kJ mol1, whereas those corresponding to the reforming of CH4 and C2-C4 hydrocarbons and the WGS reaction are more sensitive to temperature in the 600e700 C range. Nevertheless, all activation energy values are quite low, which can be explained by the narrow temperature range studied and the similar product distribution obtained in all the experiments. Moreover, the low activation energies can be related to the fact that they are apparent values. In fact, the increase of both internal and external mass transfer limitations at higher temperatures give way to lower activation energy values. The external mass transfer limitations are associated to the use of fluidized bed reactor in the reforming step, with the interstitial gas velocity being lower than in fixed bed reactors. In addition, the high particle size of the catalyst used in this study (up to 0.8 mm) and its limited porous structure favor remarkable internal mass transfer limitations. Fig. 1 shows the quality of the fit for the kinetic model proposed by comparing the evolution of experimental results of product molar fractions with catalyst mass (dots) and those calculated using the model (lines). It should be noted that the experimental results have been obtained by extrapolating the evolutions of molar fractions with time on stream to zero time on stream. Moreover, the results obtained in the catalytic cracking without catalyst (bed made up of sand) have been considered at zero space time. The fitting is adequate and the model proposed predicts reasonably well the effect temperature and catalyst mass have on product distribution at zero time on stream.
Effect of reforming conditions on product distribution at zero time on stream As observed in Fig. 1, when catalyst mass is increased both the steam reforming (Eqs. (1), (3) and (4)) and the WGS (Eq. (2)) reaction are enhanced in the temperature range studied, and therefore H2 and CO2 molar fractions increase, whereas that corresponding to H2O decreases. The same trend has been
Table 2 e Apparent kinetic parameters of best fit and their corresponding confidence intervals at a 95% confidence level, and the regression coefficient. 1 k01, mol g1 cat s 1 k0WGS, mol g1 cat s 0 1 1 k3, mol gcat s 1 k04, mol g1 cat s 1 E1, kJ mol EWGS, kJ mol1 E3, kJ mol1 E4, kJ mol1 2
R
3
6.0 10 ± 3.6 101 ± 4.1 102 ± 1.3 102 ± 14.5 ± 2.2 30.0 ± 5.4 33.7 ± 5.7 20.7 ± 4.0 0.997
3
0.9 10 0.4 101 0.5 102 0.2 102
5
reported in the literature for H2 and CO2 yields in bio-oil reforming studies [29,57,58]. Thus, a maximum H2 production of around 11 wt% (by mass unit of biomass in the feed) is attained in the temperature range studied, which is higher than those in other studies in which pyrolysis and in-line catalytic reforming of biomass was carried out [59e62]. As observed in Fig. 1a, H2 concentration increases when the catalyst mass is increased, especially from 0 to 6.3 g, obtaining a maximum value for 9.4 g of catalyst. The same trend is observed for CO2 molar fraction, obtaining a maximum concentration in the 6.3e12.5 g range. Concerning by-product concentrations (Fig. 1b), it is observed that CH4 and C2-C4 hydrocarbon concentrations are very low at 600 C, even when space time is very low. Finally, the concentration of nonreacted bio-oil decreases considerably as catalyst mass is increased, attaining full reforming of oxygenated compounds with 12.5 g of catalyst. At 650 C (Fig. 1c and d) the effect of catalyst mass follows a similar trend as at 600 C, and the highest H2 and CO2 concentrations are achieved with a catalyst mass of 12.5 g, i.e., all oxygenated compounds are reformed. Finally, at 700 C (Fig. 1e and f), the reforming reaction rate is higher and the concentration of non-reacted bio-oil oxygenated compounds decreases rapidly when catalyst mass is increased, whereas H2 concentration increases. In this case, almost full conversion is obtained with a catalyst mass of 9.4 g. Consequently, this catalyst mass is lower than that corresponding to the same situation in the 600e650 C range. Nevertheless, a deactivation kinetic equation should be coupled with the model to quantify the evolution of product distribution with time on stream when the catalyst undergoes deactivation by coke deposition.
Kinetic equation of the deactivation In a previous study [53], coke deposition has been proven to be the main deactivating cause of the catalyst due to the blockage of Ni active sites. Given that the deactivation is fast and depends on reaction conditions, a kinetic model that quantifies their effect is required for establishing large scale operation strategies in the reforming process, such as reactionregeneration cycles or catalyst circulation in a fluidized bed reactor. A non-selective deactivation model has been considered, and therefore the same activity parameter has been used for the different steps in the kinetic scheme (reforming of oxygenated compounds, C2-C4 hydrocarbons and CH4, and the WGS reaction). Activity has been defined as the ratio between the reaction rate at time t and the reaction rate at zero time on stream: a¼
ri ðri Þ0
(18)
Consequently, the formation rate of component i at time t has been calculated based on the reaction rate at zero time on stream, (rj)0, Eqs. 13e16. The general expression for the kinetic equations is as follows: ri ¼
j X
ðyi Þj rj 0 a
(19)
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Fig. 1 e Comparison of the experimental results of evolution of product molar fractions (dots) with catalyst mass at zero time on stream, with those predicted using the model (lines), at 600 C (a, b), 650 C (c, d) and 700 C (e, f).
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In order to solve Eq. (19), a deactivation kinetic equation is required to relate catalyst activity with operating conditions (temperature, time and composition of the reaction medium). Studies based on temperature programmed oxidation (TPO) and microscopic analysis allowed determining that coke
7
content and nature (amorphous and condensed) and their effect on catalyst activity are related to the concentration of bio-oil oxygenated compounds in the reaction medium [53]. This relationship allows confirming that bio-oil oxygenated compounds are the main coke precursors for amorphous and
Fig. 2 e Comparison of the experimental results of the evolution of product molar fractions with time on stream (dots) with those predicted by the model (lines), at 600 C (a, b), 650 C (c, d) and 700 C (e, f). Catalyst mass, 12.5 g. Please cite this article in press as: Arregi A, et al., Kinetic study of the catalytic reforming of biomass pyrolysis volatiles over a commercial Ni/Al2O3 catalyst, International Journal of Hydrogen Energy (2018), https://doi.org/10.1016/j.ijhydene.2018.05.032
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deactivating coke. This role of oxygenate compounds is consistent with the results obtained in the reforming of pure oxygenates [63e65] and bio-oil [19,29,66]. The formation of encapsulating amorphous coke has also been reported as the main responsible for the deactivation of Ni based catalysts in the biomass pyrolysis-reforming studies [32e34]. Therefore, the kinetic equation for deactivation considers catalyst deactivation rate proportional to the concentration of bio-oil oxygenated compounds in the reaction medium. da ¼ kd xCn Hm Ok a dt
(20)
where xCnHmOk is the molar fraction of bio-oil oxygenated compounds, kd is the kinetic constant of deactivation and a is activity. Considering catalyst activity, the reaction rates of the steps in the reaction scheme at t time on stream are as follows: r1 ¼ k1 xCn Hm Ok xH2 O a
(21)
r2 ¼ kWGS xCO xH2 O xH2 xCO2 KWGS a
(22)
Fig. 3 e Parity plot for the proposed model.
r3 ¼ k3 xC2 C4 xH2 O a
(23)
r4 ¼ k4 xCH4 xH2 O a
(24)
predicted by the model (lines) for three temperatures, 600 C (Fig. 2a and b), 650 C (Fig. 2c and d) and 700 C (Fig. 2e and f). The results correspond to a catalyst mass of 12.5 g, which has been taken as an example. In addition, Fig. 3 shows the adequate fit between the experimental and the predicted values (parity plot) of the molar fractions. As observed in Fig. 2, the model satisfactorily predicts the evolution of molar fractions of the products (H2, CO2, CO and H2O) with time on stream, which confirms the validity of Eq. (20). Moreover, the deactivation rate increases linearly when the concentration of bio-oil oxygenated compounds in the reaction medium is increased. The poorest fit for the evolution of the molar fractions of bio-oil oxygenated compounds and by-products (CH4 and C2-C4 hydrocarbons) should be attributed, on the one hand, to their very low values (they are much smaller than those for the reforming products) and, on the other hand, to the formation of these by-products by decomposition of oxygenated compounds, which are not considered in the reaction scheme due to the difficulty involving their kinetics (decomposition reactions overlap oxygenate reforming reactions). The fact that the deviation of results is higher when temperature is increased reinforces this hypothesis that oxygenate cracking is the main cause of this deviation. Concerning the evolution of product yields with time on stream, a similar trend was observed by Medrano et al. [67] in the reforming of biomass pyrolysis liquids at 650 C, in which a decrease in H2 and CO2 yields and an increase in CO and CH4 yields were observed. The same trends have also been reported by some authors in the steam reforming of bio-oil [19,22,68e70].
The equilibrium constant of the WGS reaction has been calculated using Eq. (17) with the aforementioned parameters. A similar methodology as that for zero time on stream has been used to calculate the kinetic parameters. The mass conservation equations for each component i (Eq. (6)) have been solved together with the deactivation kinetic equation, and the experimental molar fractions with time on stream have been fitted to the model by multiple non-linear regression. Given that the experimental values have been obtained in a fluidized bed reactor, there is no longitudinal profile of activity along the reactor, but activity is uniform at each time in the catalytic bed. Therefore, activity is calculated for each catalyst mass value, W, based on the following expression: Z
W
adW aW ¼
0
W
(25)
Thus, activity is calculated as an average for the whole bed for each time on stream. This average activity value is the one used to calculate the reaction rate of each step j in the reaction scheme (Eqs. 21e24) for each value of time on stream. The optimization has consisted in minimizing the error objective function (Eq. (9)). Similarly as in the kinetic modelling at zero time, the deactivation kinetic constants have been reparameterized. Furthermore, the kinetic parameters for the reaction steps are those previously calculated based on the results at zero time on stream (Table 2). Thus, the values calculated for the frequency factor and activation energy for the deactivation kinetic equation (Eq. (20)) have been 3.0 101 ± 0.4 101 s1 and 18.6 ± 2.4 kJ mol1, respectively, with R2 being 0.997. This low value of activation energy is evidence of a small effect of temperature in the 600e700 C range. The adequate fit of the kinetic model is shown in Fig. 2, in which the experimental data (dots) are compared with those
Conclusions A kinetic model has been established considering a scheme made up of four reactions, as are: reforming of bio-oil
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oxygenated compounds, C2-C4 hydrocarbons and CH4, and the WGS reaction. Likewise, a deactivation kinetic equation dependant on the concentration of bio-oil oxygenated compounds has been proposed because these are the main coke precursors, and therefore the main responsible for catalyst deactivation. The fitting of adequacy of the model proposed for quantifying the distribution of products (H2, CO2, CO, H2O, CH4, C2-C4 hydrocarbons and non-converted bio-oil oxygenated compounds) and the evolution of these products with time on stream have been verified. The model suitably fits the experimental results of component molar fraction at the reactor outlet, in the 600e700 C and 0e12.5 g ranges, and up to 2 h time on stream. Thus, the full kinetic model proposed suitably predicts the experimental results obtained in the reforming of volatiles from biomass pyrolysis, in a wide range of operating conditions. It is therefore a suitable tool for further simulation, optimization, and scaling up studies in CSBR-FBR systems for continuous H2 production from biomass.
Acknowledgments This work was carried out with financial support from the Ministry of Economy and Competitiveness of the Spanish Government (CTQ2016-75535-R (AEI/FEDER, UE) and CTQ2015-69436-R (MINECO/FEDER, UE)), the Basque Government (IT748-13) and the University of the Basque Country (UFI 11/ 39). A. Arregi and I. Barbarias thank the University of the Basque Country for their postgraduate grants (UPV/EHU 2017 and 2016, respectively).
Nomenclature a, aW Ej OF Fi, FT kd kj, k*j k0j KWGS nc p R R2 (ri)0, ri (rj)0, rj SSE SST t T, T* W
Catalyst activity and catalyst activity for each catalyst mass value Activation energy of the step j (kJ mol1) Error objective function Molar flow rate of product i and total molar flow rate (mol s1) Kinetic constant of deactivation (s1) Kinetic constant of step j at T temperature and at the 1 reference temperature (mol g1 cat s ) 1 1 Frequency factor (mol gcat s ) Equilibrium constant of the WGS reaction Number of compounds in the kinetic scheme Total number of experimental conditions Gas constant (kJ mol1 K1) Regression coefficient Formation rate of component i at zero time on 1 stream and at t time (mol g1 cat s ) Reaction rate of the step j at zero time on stream and 1 at t time (mol g1 cat s ) Sum of squares of the error Total sum of squares Time (min) Temperature and reference temperature (K) Catalyst mass (gcat)
wi xi x*i,j, xi,j (yi)j 4i
9
Weight factor for component i Molar fraction of component i in the reaction medium (on a wet basis) Experimental and predicted molar fractions of component i at the experimental condition j Stoichiometric coefficient of component i in the step j in the kinetic scheme Sum of squares of the residuals for component i
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