Bioresource Technology 177 (2015) 66–73

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Study on CO2 gasification properties and kinetics of biomass chars and anthracite char Guangwei Wang, Jianliang Zhang ⇑, Xinmei Hou, Jiugang Shao, Weiwei Geng School of Metallurgical and Ecological Engineering, University of Science and Technology Beijing, Beijing 100083, China

h i g h l i g h t s  CO2-gasification properties of biomass chars and anthracite char were studied.  Chemical components and physical structures of four chars were tested.  Carbonaceous structure is a key factor to evaluate reactivities of different chars.  Kinetics parameters were calculated by using nonlinear least-squares fitting method.  RPM model for biomass chars and VM model for anthracite char.

a r t i c l e

i n f o

Article history: Received 10 September 2014 Received in revised form 12 November 2014 Accepted 15 November 2014 Available online 20 November 2014 Keywords: Biomass char Thermogravimetric analysis Gasification Kinetics models

a b s t r a c t The CO2 gasification properties and kinetics of three biomass chars (WS-char, RL-char and PS-char) and anthracite char (AC-char) were investigated by thermogravimetric analysis method. Three nth-order representative gas–solid reaction models, random pore model (RPM), volume reaction model (VM) and unreacted core model (URCM) were employed to describe the reactive behavior of chars. Results show that gasification reactivity order of different chars from high to low was WS-char, PS-char, RL-char and AC-char. In addition, the chemical components as well as physical structures of four chars were systematically tested. It was found that gasification properties of char were determined by carbonaceous structure. It was concluded from kinetics analysis that RPM model was the best model for describing the reactivities of biomass chars and VM was the model that best fitted the gasification process of anthracite char. The activation energies obtained for the biomass and anthracite char samples lie in the range of 236.4–284.9 kJ/mol. Ó 2014 Elsevier Ltd. All rights reserved.

1. Introduction Biomass energy, serving as a kind of very important energy resource, occupies the proportion for 14% of total world energy consumption, meanwhile coal proportions for 20%, natural gas 15% and electricity 14% (Dong et al., 2014; Tahmasebi et al., 2013). Compared with fossil fuel, biomass energy has advantages of wide range of distribution, being reproducible as well as low carbon emission, and is one of important renewable energy resources to replace fossil fuel (Huo et al., 2014). Gasification is a main way to make clean and high efficient utilization of biomass, which could transform different kinds of biomass into biogas for use of supplying of heat, generation of electricity, production of chemical materials, as well as serving as fuel for vehicles (Kirtania et al., 2014). ⇑ Corresponding author. Tel.: +86 10 62332550; fax: +86 10 62332364. E-mail address: [email protected] (J. Zhang). http://dx.doi.org/10.1016/j.biortech.2014.11.063 0960-8524/Ó 2014 Elsevier Ltd. All rights reserved.

In general, the gasification process in the gasifier is very complex and includes water evaporation, volatiles pyrolysis, combustion, volatiles gasification and char gasification. Among these processes, char gasification is the controlling step because of its low gasification rate (Dupont et al., 2001). In addition, the CO2 gasification rate of chars is much slower than the steam gasification rate of chars, so char-CO2 gasification rate is considered as the rate-determining step in practical gasification process. As a result, investigation on the reaction behavior of char-CO2 gasification during reaction process, and the kinetic parameters of the gasification step can provide a basic foundation for a better understanding and proper reactor design for the biomass gasification process (Sangtong-Ngam and Narasingha, 2008; Fermoso et al., 2010; Liu et al., 2003). The majority of kinetics study of biomass char gasification was performed on the thermogravimetric analysis (TGA) instrument (Miao et al., 2009; Meng et al., 2011; Everson et al., 2008). Many workers (Khalil et al., 2009; Fermoso et al., 2008; Lahijani et al., 2013a) have studied isothermal gasification process

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G. Wang et al. / Bioresource Technology 177 (2015) 66–73

of biomass char, coal char, carbon black, tire-char under CO2 and steam conditions. However, in isothermal mode only the overall reactivity of char could be studied. Compared with the isothermal method, non-isothermal method has advantages of less experiment while shorter time and more data. In addition, in practical process, the gasification temperature often changes and thus non-isothermal study is closer to practical situation. Miura and Silveston (1989) showed the validity of the temperature programmed reaction (TPR) technique for analysis of non-catalytic gas–solid reaction. Fermoso et al. (2010) also stated that in a non-isothermal experiment to determine the kinetic parameters of steam gasification of coal-biomass blend chars. In this study, the gasification properties and kinetic behaviors of wheat stalk char (WS-char), rice lemma char (RL-char), pine sawdust char (PS-char) and anthracite char (AC-char) were investigated by using a non-isothermal thermogravimetric analysis (TGA) method. Various factors including elementary composition, alkali index, surface area and carbonaceous structure were analyzed systematically, and three mathematical models including the random pore model (RPM) (Bhatia and Perlmutter, 1980), volume reaction model (VM) (Shang and Eduardo, 1984; Kasaoka et al., 1985) and the unreacted core model (URCM) (Ochoa et al., 2001) were used to determine the kinetic parameters. It is expected that this study will be useful in understanding of gasification process of biomass chars and provide the information required for design and operation of the gasifier.

2.2. Gasification tests Tests were carried out on a thermogravimetric analyzer (HCT-3, Henven Scientific Instrument Factory, Beijing) at atmospheric pressure. Approximately 5 mg of sample was placed in a crucible with height of 2 mm and a circular base with diameter of 5 mm. A thermocouple was located close to the platinum basket to monitor the temperature. In this work, all the tests were performed under nonisothermal conditions from room temperature to 1473 K at four different heating rates: 2.5 K/min, 5 K/min, 10 K/min and 20 K/ min. Small amount of sample and slow heating rates were used to avoid heat transfer limitation and minimize mass transfer effects. The flow rate of the reactive gas introduced into the thermobalance during the gasification experiments was 60 ml/min of high purity CO2. It was important to ensure that the tests had good reproducibility. Therefore each run was repeated at least for three times before a final result was ascertained. The gasification conversion (x) was calculated using the following equations

x¼

ðm0  mt Þ ðm0  mash Þ

ð1Þ

where m0 denotes the sample mass at the start of gasification; mt is the sample mass at gasification time of t; mash is the mass of ash remaining in char after being completely converted.

2. Experimental

2.3. Characterization of char CO2-gasification

2.1. Preparation of samples

For quantitative characterization of changing rules of initial weight loss temperature, peak conversion rate temperature and total weight loss temperature, according to gasification characteristic parameters of char gasification, parameters of Ti, Tf, Tm and tg were defined. The initial gasification temperature Ti is not a physical property of a fuel, which is evaluated for the different samples in the same reaction–off procedure or operating condition (sample mass, heating rate and surrounding gas) in order to compare their activity. The initial gasification temperature (Ti) and total gasification temperature (Tf), from the conversion curves and conversion rate curves are evaluated in literatures (Li et al., 2006; Chen et al., 2004). The comprehensive gasification characteristic index S is determined by the equation as follow (Li et al., 2011):

Wheat stalk (WS), rice lemma (RL), pine sawdust (PS) and anthracite (AC) were collected from several provinces in China. Before devolatilization, samples were primarily processed and the size distribution was controlled to 0.5–1 mm. These samples were devolatilized in a fixed bed reactor under a flowing nitrogen atmosphere at the temperature of 1373 K for 90 min to ensure complete pyrolysis. After devolatilization, the obtained chars were ground into fine powder using a mortar and pestle. The proximate and ultimate analysis results of raw materials and chars were conducted according to the Chinese standard GB/T 212-2001 and GB/T 476-2001, respectively. The results are shown in Table 1. The ash of sample chars was prepared by air oxidation at 1173 K in a muffle furnace according to the Chinese standard (GB/T 2122008). The chemical composition of ash was obtained using Xray fluorescence spectrometer (XRF). Surface areas of samples were analyzed by an automated surface area analyzer, and the specific surface areas were calculated using BET method. Intrinsic carbon structures of chars were investigated by a Raman spectrometer.

S¼

ðdx=dtÞmax  ðdx=dtÞmean

ð2Þ

T 2i  T f

where dx/dtmax is the maximum gasification rate; dx/dtmean represents mean value for gasification rate.

Table 1 Proximate and ultimate analysis of samples. Sample

WS RL PS AC WS-char RL-char PS-char AC-char

Proximate analysis (wt.%)

Ultimate analysis (wt.%)

Mole ratio (mol/mol)

FCda

Ad

Vd

Cd

Hd

Oda

Nd

Sd

O/C

H/C

18.05 14.17 16.39 70.43 61.81 50.92 93.37 82.37

5.13 18.41 0.45 14.69 36.63 47.01 1.58 15.35

76.82 67.42 83.16 14.88 1.56 2.07 5.05 2.28

47.88 48.94 48.04 75.23 65.74 45.20 96.18 83.29

6.10 6.21 5.60 2.50 0.93 0.61 1.47 0.64

45.50 44.46 39.77 1.01 3.17 1.01 1.89 0.35

0.31 0.34 0.37 0.93 1.06 0.71 1.01 0.78

0.21 0.05 0.06 0.85 0.65 0.25 0.06 0.25

– – – – 0.0362 0.0168 0.0147 0.0032

– – – – 0.1698 0.1619 0.1834 0.0922

FC, fixed carbon; A, ash; V, volatile matter; d, dry basis. a Calculated by difference.

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Combustion and gasification of char is gas–solid non-catalytic heterogeneous reaction and the reaction equation can be expressed as following:

where (dx/dt)exp,i is experiment data; (dx/dt)calc,i is value calculated by model; N is the number of data points. The non-isothermal thermogravimetric analysis method or temperature programmed reaction involves heating the samples at a constant rate b. The temperature T is related to time t by:

dx=dt ¼ kðpg ; TÞ f ðxÞ

T ¼ T0 þ b  t

3. Kinetic models

ð3Þ

where k denotes apparent reaction rate constant, which includes the effect of reaction temperature T and partial pressure in the gas phase pg; f(x) is kinetics mechanism function in combustion or gasification reaction; t is time. If the partial pressure in the gas phase remains constant during the process, the apparent reaction rate constant is dependent on the temperature and can be expressed using the Arrhenius equation, which is written as: E=RT

k ¼ k0 e

ð4Þ

where k0 is pre-exponential factor or called frequency factor; E stands for activation energy; R is the universal gas constant. All existing models can be classified into two groups: theoretical and semi-empirical. Well-known examples of theoretical kinetic models include the RPM, URCM and VM models. The RPM model (Bhatia and Perlmutter, 1980) developed by Bhatia and Perlmutter takes into account the pore structure and its evolution during the course of reaction. When reaction is the control step, gasification rate can be written as:

qffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi dx=dt ¼ kRPM eE=RT ð1  xÞ 1  w lnð1  xÞ

ð5Þ

where w is a parameter of particle structure, with the expression of e0 Þ w ¼ 4pL0Sð1 ; S0, L0 and e0 are the pore surface area, pore length, and 2 0 solid porosity, respectively. The VM model (Shang and Eduardo, 1984; Kasaoka et al., 1985) does not consider the structure changes of coal char during gasification, but assumed that the gasifying agents react with char at all active sites, which are uniformly distributed on both the outside and inside the particle surface. The rate expression is then given by:

dx=dt ¼ kVM eE=RT ð1  xÞ

ð6Þ

The URCM model (Ochoa et al., 2001) assumes that the reaction initially occurs at the external surface of char and gradually moves inside. At the intermediate conversion of the solid, there is a shrinking core of non-reacted solid. The reaction is described as the follow:

dx=dt ¼ kURCM eE=RT ð1  xÞ2=3

ð7Þ

According to Miura and Silveston’ report (Miura and Silveston, 1989), the determination of the kinetic parameters from a single TPR run may lead to unreliable rate parameters and, furthermore, the fitting of data by a model may not validate the model when just one TPR run is used. These authors claimed that at least three TRP runs at different heating rates are required to estimate reliable parameters and accurate activation energies. Therefore, in this study the kinetic parameters were determined from four TPR runs, each one performed at a different heating rate. Eqs. (5)–(7) are three explicit formulae that describe the gasification conversion rate dx/dt, the conversion x, temperature T, under condition of reaction control. The kinetic parameters including E, k0 and w can be calculated from experimental data by employing nonlinear least-squares fitting methods. The objective function can be written as:

OF ¼

N  2 X ðdx=dtÞexp;i  ðdx=dtÞcalc;i i¼1

ð8Þ

ð9Þ

where T0 is the temperature at which heating is started. Eqs. (5) and (9) can be integrated to give:

    ðT  T 0 Þ E x ¼ 1  exp  k0   exp b RT   k0 ðT  T 0 Þ E  expð Þ  1þ b RT 4w

ð10Þ

Similarly, Eqs. (8) and (9) can be transformed into:

  3 k0 ðT  T 0 Þ E x¼1 1  exp 3b RT

ð11Þ

   ðT  T 0 Þ E x ¼ 1  exp k0  exp b RT

ð12Þ

Eqs. (10)–(12) are used to calculate x by introducing the previously estimated k0, E and w. The x calculation was performed in order to verify the reliability of the kinetic models and their capacity to describe not only the conversion rate, dx/dt, but also char conversion, x. By comparing the experimental and calculated x values, the kinetic model may be further tested and verified. The deviation (DEV) between the experimental and calculated curves was calculated using the following equation:

P  N DEVðxÞð%Þ ¼ 100 

i¼1

2 1=2 xexp;i  xcalc;i =N max ðxÞexp

ð13Þ

where DEV(x)(%) is relative error; xexp,i is experiment data; xcalc,i is value calculated by model; max (x)exp is maximum conversion of experiment. 4. Results and discussion 4.1. Thermogravimetric analysis Conversion and conversion rate curves of different chars are presented in Fig. 1. All reaction curves have one common character that they all have one single peak rate. So the gasification process of different chars could be divided into three stages: in the first stage, the weight increases a little due to adsorption of gas by char. The second stage is gasification of chars and weight loss happens quickly. The third stage is ending of the total gasification and the residue is ash. Gasification happens mainly in second stage, and its reaction properties could represent gasification properties of char, so the focus of the kinetics study is concentrated on the second stage. Gasification characteristic parameters of different chars are shown in Table 2. It can be found that the values of Ti of four chars obey the order of WS-char < PS-char < RL-char < AC-char. Tm as well as Tf of four chars have the same order. At the same time, conversion rates of PS-char are found to be the highest, followed by those of the WS-char and RL-char. The conversion rate of AC-char is the lowest. Normally, when values of Ti and Tf are low which indicated the gasification reactivity of char would be high. However for these four chars, there is no obvious relation between gasification reactivity with Ti and Tf, which means gasification reactivity could not be represented only through Ti and Tf. In this study, comprehensive characteristic index S is used to represent gasification reactivities of different chars. The S of different chars from high to low can be ranked as WS-char, PS-char, RL-char and

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G. Wang et al. / Bioresource Technology 177 (2015) 66–73

(a)

0.0

2.5K/min 5K/min 10K/min 20K/min

0.2

(b)

0.0

2.5K/min 5K/min 10K/min 20K/min

0.2

0.4

0.4 0.25

x

x

0.2 0 0.20

0.6

0.1 5 -1

0.15

0.10

0.8

dx/dt ,m in

0.8

dx/dt ,m in

-1

0.6

0.1 0

0.0 5 0.05

1.0

0.00 600

800

600

700

1000

Tem perature,K

800

900

1200

1.0

1400

1000

1100

0.0 0 6 00

80 0

100 0

1200

1300

1400

600

700

800

900

Temperature,K

140 0

1000

1100

1200

1300

1400

Temperature,K

(c)

0.0

(d)

0.0

2.5K/min 5K/min 10K/min 20K/min

0.2

12 00

T em p erature ,K

2.5K/min 5K/min 10K/min

0.2

0.4

0.4 0.07

x

x

0.20 0.06

0.6

0.8

0.05

-1

dx/dt,min

-1

0.15

0.10

0.8

dx/dt,m in

0.6

0.04

0.03

0.02

0.05 0.01

1.0

0.00 600

800

1000

1200

1.0

1400

0.00 600

8 00

600

700

800

900

1000

1100

1000

1200

1 400

T em p e ra ture ,K

Tem perature,K

1200

1300

1400

600

700

800

900

1000

1100

1200

1300

1400

Temperature,K

Temperature,K

Fig. 1. Experimental conversion and conversion rate curves of different chars: (a) WS-char; (b) RL-char; (c) PS-char; (d) AC-char.

Table 2 Characteristic gasification parameters of different chars at four different heating rates. Char

Heating rate(K/min)

Ti (K)

Tm (K)

Tf (K)

dx/dtmax (min1)

dx/dtmean (min1)

S  1012

tg (min)

WS-char

2.5 5 10 20 2.5 5 10 20 2.5 5 10 20 2.5 5 10

1062.2 1095.6 1124.7 1157.7 1122.7 1138.0 1165.7 1191.4 1104.3 1126.3 1155.4 1184.7 1148.9 1174.1 1205.7

1128.7 1159.1 1191.6 1218.2 1183.0 1218.5 1245.1 1282.2 1160.9 1194.9 1124.4 1283.6 1223.0 1268.9 1313.2

1159.3 1188.3 1221.4 1259.2 1231.8 1276.2 1298.4 1336.9 1175.6 1206.6 1254.1 1305.8 1347.2 1381.2 1427.1

0.04385 0.06591 0.12389 0.20748 0.03032 0.05062 0.09925 0.17946 0.04778 0.08001 0.12015 0.19192 0.01893 0.03369 0.06129

0.01794 0.02678 0.04870 0.08516 0.01331 0.02293 0.04837 0.08508 0.01845 0.03539 0.05628 0.08792 0.00714 0.01347 0.02824

0.60 1.24 3.91 10.47 0.26 0.70 2.72 8.05 0.61 1.85 4.04 9.21 0.08 0.24 0.83

38.84 18.54 9.67 5.08 43.64 27.64 13.27 7.275 28.52 16.06 9.87 6.055 79.32 41.42 22.14

RL-char

PS-char

AC-char

Note: Ti, initial gasification temperature; Tm, corresponding temperature of the peak conversion rate; Tf, total gasification temperature; dx/dtmax, maximum gasification rate; dx/dtmean, mean gasification rate; S, comprehensive gasification index; tg is the time zone of Ti/Tf.

AC-char. So it could be concluded that gasification reactivities of four chars can be ranked as WS-char > PS-char > RL-char > AC-char. It also could be found in Fig. 1 that gasification curves with different heating rates are similar to each other, and as heating rate increasing, curves moved into high temperature zone. On one hand, with the increase of heating rate, temperature increases faster and individual reaction does not have enough time to reach completion or equilibrium, and they overlap with the adjacent higher temperature reaction; On the other hand, there is hysteresis

in high heating rate condition, which also leads combustion process move into high temperature zone. Gasification characteristic parameters at different heating rates are shown in Table 2. It can be seen that with the increase of heating rate, Ti, Tm and Tf of different chars all increase correspondingly, and at the same time dx/dtmax, dx/dtmean as well as index S all increased. The time needed for gasification (tg) is shortened. Taking WS-char for example, as heating rate increased from 2.5 K/min to 20 K/min, index S of WS-char increased from 0.60  1012 to 10.47  1012. The tg

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G. Wang et al. / Bioresource Technology 177 (2015) 66–73

is shortened from 38.84 min to 5.08 min. It could be concluded that reactivities of chars are also improved by increasing heating rate. 4.2. Correlation between gasification reactivity and characteristics of char Influences of volatile matter, mineral content, carbon content and particle size on gasification reactivities of chars have been extensively investigated (Lv et al., 2010; Gao et al., 2010). However, volatile matter of chars in this study may not be the main factor affecting the gasification reactivity, because the chars obtained in this study have been experienced a comparatively complete pyrolysis and most of the volatile matter content (almost > 90%) has been removed. As shown in Table 1, the main contents of the chars are fixed carbon and ash, so it is necessary to study the effect of ash content on gasification of four chars. During CO2 gasification of char, K2O is the strongest catalyst, followed by Na2O, while the catalysis effect of CaO is much weaker and MgO performs almost no catalysis effect. SiO2 and Al2O3 have strong inhibition effect on the gasification (Zhang et al., 2008). In order to denote the effects of mineral in ash on char gasification, the alkali index was proposed in literatures (Lahijani et al., 2013b; Huo et al., 2014).The alkali index (A) is calculated by the following equation:

A ¼ Ash 

Fe2 O3 þ CaO þ MgO þ Na2 O þ K2 O SiO2 þ Al2 O3

ð14Þ

As shown in Table 3, the order of the alkali index (A) sequence for various chars can be ranked as WS-char > RL-char > AC-char > PS-char. There was no good relation between the reactivities and alkali index (A) for different chars in this study. The particle size distributions of four chars are shown in Table 4 and it could be found that the particle sizes are concentrated in the range of 10–50 lm. The particle size of PS-char and AC-char are larger than that of WS-char and RL-char. This is not in accordance with the common knowledge that activity of char increases as the particle size decreases. Thus in this study the particle size is not the main factor affecting gasification process. From above analysis, it could be concluded that the characteristics of the raw material are not the main factors which affect the gasification reactivity. Therefore, the structure or the carbon crystalline structure of the char may play a significant role on char gasification reactivity. Fig. S1 shows the SEM graphs of different chars, with (a) WSchar, (b) RL-char, (c) PS-char, (d) AC-char. It can be found that there is obvious vertical texture, with thin skeleton and porous structure for WS-char. For RL-char, the obvious framework structure with large random pores can be observed. For PS-char, there is honeycomb structure and after crushing there is mainly slice structure

in residue sample. AC-char mainly exists in particle form with non-uniform surface, no significant gap and some micro pores. From SEM micrographs, it could be concluded that porosity and specific surface of biomass char are higher than that of anthracite char. This can explain the phenomenon that the gasification properties of biomass char are better than that of anthracite char, which is in accordance with the fact that gasification properties of char increase with increasing specific surface reported in literature (Malekshahian and Hill, 2011). However it was hard to quantitative characterization of specific surface of different chars through SEM photos. To further quantitatively characterize specific surface of them, specific surface area analyzer was used for testing. BET specific surface areas (SBET) of the biomass chars are shown in Fig. 2. The order of SBET sequence for various chars can be ranked as PSchar > WS-char > RL-char > AC-char. This phenomenon indicates that the relationship between gasification reactivity and SBET has the same tendency except for PS-char. Yuan et al. (2011) also stated that the gasification reactivities of biomass chars were not controlled by the pore structure. Moreover some studies (Zhang et al., 2010) indicated that the pore structure obtained by the method of physical adsorption was not a clear descriptor in predicting the gasification reactivities of different chars. Although the SBET performs better than the alkali index, it also cannot well explain the difference in reactivities among different chars. Based on the results mentioned above, a suitable factor or parameter should be found to evaluate the gasification reactivities of different chars. Raman spectrum method was used to test physical structure of different chars. Generally, biomass char and coal char exhibit two strong peaks at the D and G-bands, as shown in Fig. S2. The D-band is the Raman band at shift of 1300– 1400 cm1, whose relative intensity increases with the increasing number of amorphous carbon structures. The G-band is the Raman band for a shift of 1550–1600 cm1, which is attributed to a stretching vibration mode of graphite C@C bonds, and the intensity of the G-band is sharpened as the degree of graphitization increases. Normally, amorphous carbon structure could improve gasification reactivity of char, and accordingly the higher graphitization degree is, the lower the gasification reactivity will be. However, as shown in Fig. S2, ID of four chars from high to low the order is RL-char, WS-char, PS-char and AC-char, and IG has the same order, which means that gasification reactivities of different chars could not be ascertained only through ID or IG. Between peaks D and G-bands, there is a valley value represented by IV, and the uniformity of carbonaceous structures can be reflected by the IV/IG (Okumura and Okazaki, 2007). The intensity of the Raman parameter IV/IG increases with a decrease in the uniformity of carbonaceous structure, i.e., as the degree of amorphousness increases.

48

Table 3 Ash composition and A value of different chars. Fe2O3

CaO

Na2O

K2O

MgO

A

WS-char RL-char PS-char AC-char

31.85 81.03 43.21 36.54

0.78 0.76 8.76 20.57

0.89 4.69 4.31 15.93

15.1 2.32 18.82 16.34

0.32 0.52 1.68 0.59

29.63 7.06 7.9 0.91

4.56 0.58 2.76 1.45

56.7 8.72 1.08 9.61

40

32 -1

Al2O3

2

SiO2

SBET/m ·g

Sample

24

16

Table 4 Particles size distribution of different chars. Particle size(lm)

WS-char

RL-char

PS-char

AC-char

50

17.35 56.03 22.36 4.26

18.70 65.76 15.42 0.12

2.78 35.27 30.43 21.20

19.31 38.72 24.09 18.15

8

0 WS-char

RL-char

PS-char

Fig. 2. The SBET of different chars.

AC-char

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G. Wang et al. / Bioresource Technology 177 (2015) 66–73

mole ratios of the sample are witnesses to a more graphitic structure. Therefore, it can be inferred that the structure of anthracite char is the most graphitic and the detailed order of graphitic degree sequence for these four chars can be ranked as WSchar > PS-char > RL-char > AC-char. This validated the results obtained from Raman analysis. So the carbonaceous structure can be regarded as an important factor to evaluate gasification reactivities of different chars.

0.65

IV IG

0.60

0.55

4.3. Kinetics parameters 0.50

Relations of conversion rate and conversion under different heating rates are shown in Fig. 4. It could be found that during reaction process, conversion rate first increases with increasing the conversion and after the peak value is reached it would decrease. This could be explained by the following sections. At the early stage of reaction, increasing temperature would increase conversion rate. When the reaction process reaches a certain degree, although temperature would be further increased, the decreases of specific surface area as well as active points would then lower conversion rate (Sekine et al., 2006). RPM, VM and URCM models aforementioned in chapter 2 were used to investigate gasification kinetics of four chars. Table 5 shows the kinetic parameters (E, k0 and w) determined from the data obtained at the heating rates of 2.5 K/min, 5 K/min, 10 K/min and 20 K/min for all the char samples. Fig. 4 shows the experimental dx/dt data and the dx/dt curves calculated (Eqs. (5)–(7)) using the parameters obtained from the data at different heating rates. The RPM model

0.45 WS-char

RL-char

PS-char

AC-char

Fig. 3. The IV/IG values of different chars.

Fig. 3 shows the dependence of parameter IV/IG of different chars, and it could be found that the order of IV/IG value sequence for various chars can be ranked as WS-char > PS-char > RL-char > AC-char. This trend was identical with the trend of the gasification reactivity. Therefore, the IV/IG value can be developed to evaluate gasification reactivities of different chars. At the same time atomic ratios of O/C and H/C of different chars are shown in Table 1. It can be seen that the O/C and H/C mole ratios of biomass chars were higher than anthracite char. It is known that relatively low O/C and H/C

(a)

0.25

(b)

0.20

-1

0.15

0.10

RPM

0.00

0.12

0.08

0.00 0.0

0.2

0.4

0.6

0.8

1.0

0.0

0.2

0.4

x

(c)

0.25

VM

RPM

0.6

0.8

1.0

x

(d)

0.07

URCM

-1

0.05

dx/dt,min

0.15

0.10

VM

RPM

URCM

2.5K/min 5K/min 10K/min

0.06

2.5K/min 5K/min 10K/min 20K/min

0.20

-1

URCM

0.04

0.05

dx/dt,min

VM

2.5K/min 5K/min 10K/min 20K/min

0.16

dx/dt,min

-1

URCM

2.5K/min 5K/min 10K/min 20K/min

0.20

dx/dt,min

VM

RPM

0.04 0.03 0.02

0.05 0.01 0.00

0.00 0.0

0.2

0.4

0.6

x

0.8

1.0

0.0

0.2

0.4

0.6

0.8

1.0

x

Fig. 4. Experimental conversion rate curves of chars and those calculated with three models (RPM, VM and URCM): (a) WS-char; (b) RL-char; (c) PS-char; (d) AC-char.

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G. Wang et al. / Bioresource Technology 177 (2015) 66–73

Table 5 Kinetic parameters of the different chars for three models. Sample

RPM

WS-char RL-char PS-char AC-char

VM 1

E (kJ/mol)

k0 (min

236.4 284.9 239.3 251.2

2.22E+06 9.34E+07 6.56E+05 1.33E+06

)

2

w

R

0.144 0.731 0.023 -3.984

0.9965 0.9993 0.9864 0.9948

URCM

E (kJ/mol)

k0 (min

280.4 311.1 300.8 239.1

4.34E+08 1.62E+09 1.25E+09 3.83E+05

(a)

0.0

E (kJ/mol)

k0 (min1)

R2

0.9711 0.9958 0.9678 0.9977

258.9 271.1 254.7 196.1

1.26E+07 8.19E+06 3.10E+06 1.66E+03

0.9925 0.9972 0.9744 0.9839

0.2

2.5K/min 5K/min 10K/min 20K/min

0.6

2.5K/min 5K/min 10K/min 20K/min

0.4

0.6

RPM

RPM

VM 0.8

VM 0.8

URCM

1.0 800

R

(b)

x

x

)

0.0

0.2

0.4

2

1

URCM

1.0 900

1000

1100

1200

1300

1400

800

900

1000

Temperature,K

(c)

0.0

1400

(d)

2.5K/min 5K/min 10K/min 20K/min

0.4

x

x

1300

0.2

2.5K/min 5K/min 10K/min 20K/min

0.6

0.6

RPM

RPM

VM 0.8

VM 0.8

URCM

1.0 800

1200

0.0

0.2

0.4

1100

Temperature,K

URCM

1.0 900

1000

1100

1200

1300

1400

Temperature,K

800

900

1000

1100

1200

1300

1400

Temperature,K

Fig. 5. Experimental conversion curves of char and those calculated with three models (RPM, VM and URCM) using parameters determined form different heating rates: (a) WS-char; (b) RL-char; (c) PS-char; (d) AC-char.

fits the experimental data better than the other two models for WS-char, RL-char and PS-char, since it displays a significant fit and has the highest R2 value (Table 5). The RPM model predicts a maximum in conversion rate as the reaction proceeds, as pore overlapping is considered. Pore shape is assumed cylindrical and supposed to grow radially while reaction proceeds, instead of keeping initial volume. Initially, the cylinder growth causes an increase in total reaction surface, which means a higher conversion rate. Finally, reaction process brings about neighboring pore intersection. Due to pore overlapping, the reaction surface area is lowered and, consequently, the conversion rate decreases (Bhatia and Perlmutter, 1980). Conversely, the VM and URCM models cannot describe a maximum in conversion rate but predict a constant decrease in the conversion rate. In this study, using the models with the best fit, the activation energies for biomass and coal chars lie in the range of 236.4–284.9 kJ/mol (Table 5). In a previous

study, Li et al. (2009) calculated activation energy values for WSchar in CO2 atmosphere in the range between 147 kJ/mol and184 kJ/mol. Some researchers (Bhat et al., 2001; Dong et al., 2014) obtained activation energy values for RL-char under CO2 atmosphere of 197–238 kJ/mol, and the activation energy values of PS-char were 213–249 kJ/mol. Some researchers (Kang et al., 2013; Everson et al., 2008) achieved activation energy values for coal char in CO2 gasification which ranged between 192 kJ/mol and 247 kJ/mol. Activation energies reported in literature are a little lower than calculation results in this study. This could be attributed to the higher pyrolysis temperature and longer pyrolysis time used in this study, which are 1373 K and 90 min. At the same time, it could be found in Fig. 4(c) that for gasification of pine wood char the peak gasification rate appears at high conversion range, which could be explained as: In RPM model, particles are assumed to be spherical, but in practical situation shape

G. Wang et al. / Bioresource Technology 177 (2015) 66–73 Table 6 Deviation between the experimental data and calculated conversion data. Sample

WS-char RL-char PS-char AC-char

DEV(x) (%) RPM

VM

URCM

1.15 0.97 1.67 1.91

2.54 2.16 4.95 1.12

2.31 2.09 4.75 4.82

of particles are various. This could be concluded in Fig. S1, in which none complete spherical shape could be found for four chars, and among them WS-char has a columnar shape, RL-char as well as AC-char are similar to spherical shape, while PS-char exists in a plate like shape. For plate like shape particles, peak conversion rate appears in a high conversion range (Zhang et al., 2014). The conversion, x, of the chars during gasification were calculated (Eqs. (10)–(12)) by using the kinetic parameters estimated from data at the four heating rates (Table 5). Fig. 5 shows experimental data and calculated result. In order to quantify the errors produced by the kinetic models in predicting the values of conversion, the experimental and calculated x values were compared by calculating the deviation (DEV) between the experimental data and calculated curves using Eq. (13). The results obtained from the best fitting models for all samples are summarized in Table 6. The lowest deviation from the calculated values of the conversion rates was obtained by using the RPM model for PS-char, RL-char and PS-char and VM model for the AC-char. 5. Conclusions The gasification properties and kinetics for CO2 gasification of different chars were investigated in this work. The gasification reactivities of chars can be ranked as WS-char > PS-char > RL-char > AC-char. The carbonaceous structure is found to be an important factor to affect gasification reactivities of different chars by chemical components and physical structures analysis. The TPR technique employed in the analysis of gas–solid reactions was applied to estimate the kinetic parameters by best fitting the reactive behavior of the chars. The best model for describing the biomass chars was RPM, while VM model for anthracite char. Acknowledgements The present work was supported by National Key Technology R&D Program in the 12th Five year Plan of China (NO. 2011BAC01B02); National Science Foundation of China & Baosteel under Grant (51134008). Appendix A. Supplementary data Supplementary data associated with this article can be found, in the online version, at http://dx.doi.org/10.1016/j.biortech.2014. 11.063. References Bhat, A., Bheemarasetti, J.V.R., Rao, T.R., 2001. Kinetic of rice husk char gasification. Energy Convers. Manage. 42, 2061–2069. Bhatia, S.K., Perlmutter, D.D., 1980. A random pore model for fluid-solid reactions: I Isothermal kinetic control. AIChE J. 26, 379–385. Chen, J., Zhou, J.H., Liu, J.Z., 2004. Catalysis effect of carbide lime on various coal combustion. J. Fuel Chem. Technol. 67, 297–303. Dong, C.Z., Wang, X.H., Zeng, X.J., Shao, Z.H., 2014. Experimental study on the gasification kinetic parameters of biomass chars under CO2 atmosphere: I. Activation energy. J. Fuel Chem. Technol. 42, 329–335.

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