ash supported nickel–iron catalysts for biomass pyrolytic gasification combined with the mixing-simulation in fluidized-bed gasifier

Applied Energy xxx (2014) xxx–xxx

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Applied Energy journal homepage: www.elsevier.com/locate/apenergy

In situ catalytic conversion of tar using rice husk char/ash supported nickel–iron catalysts for biomass pyrolytic gasification combined with the mixing-simulation in fluidized-bed gasifier q Yafei Shen a,⇑, Peitao Zhao b,c, Qinfu Shao d, Fumitake Takahashi a, Kunio Yoshikawa a a

Department of Environmental Science and Technology, Interdisciplinary Graduate School of Science and Engineering, Tokyo Institute of Technology, Yokohama 226-8502, Japan Key Laboratory of Energy Thermal Conversion and Control of Ministry of Education, School of Energy and Environment, Southeast University, Nanjing 210096, PR China School of Electric Power Engineering, China University of Mining and Technology, Xuzhou 221116, PR China d Department of Environmental System, Graduate School of Frontier Sciences, The University of Tokyo, Chiba 277-8563, Japan b c

h i g h l i g h t s  Tar can be in situ converted by the RHC/RHA supported nickel–iron catalysts.  The tar conversion efficiency could reach about 92.3% by the RHC Ni–Fe.  Partial metal oxides in the carbon matrix could be in-situ reduced into the metallic state.  Mixing with RHA Ni can also improve biomass fluidization behavior.

a r t i c l e

i n f o

Article history: Received 4 August 2014 Received in revised form 25 September 2014 Accepted 27 October 2014 Available online xxxx Keywords: Biomass gasification Tar conversion Rice husk char Catalysts Mixing-simulation

a b s t r a c t A catalytic gasification technology has been proposed for tar in situ conversion using the rice husk char (RHC) or rice husk ash (RHA) supported nickel–iron catalysts. Biomass tar could be converted effectively by co-pyrolysis with the RHC/RHA supported nickel–iron catalysts at 800 °C, simplifying the follow-up tar removal process. Under the optimized conditions, the tar conversion efficiency could reach about 92.3% by the RHC Ni–Fe, which exhibited more advantages of easy preparation and energy-saving. In addition, the tar conversion efficiency could reach about 93% by the RHA Ni. Significantly, partial metal oxides (e.g., NiO, Fe2O3) in the carbon matrix of RHC could be in-situ carbothermally reduced into the metallic state (e.g., Ni0) by reducing gases (e.g., CO) or carbon atom, thereby enhancing the catalytic performance of tar conversion. Furthermore, mixing with other solid particles such as sand and RHA Ni, can also improve biomass (e.g., RH) fluidization behavior by optimizing the operation parameters (e.g., particle size, mass fraction) in the mode of fluidized bed gasifier (FBG). After the solid–solid mixing simulation, the RH mass fraction of 0.5 and the particle diameter of 0.5 mm can be employed in the binary mixture of RH and RHA. Ó 2014 Elsevier Ltd. All rights reserved.

1. Introduction Biomass pyrolysis and/or gasification is recognized as one of the most promising technologies for the production of sustainable fuels used for power generation system or syngas applications [1–5]. Biomass gasification is a process in which biomass experiences incomplete combustion to produce syngas that mainly

q This paper is included in the Special Issue of Energy innovations for a sustainable world edited by Prof. S.k Chou, Prof. Umberto Desideri, Prof. Duu-Jong Lee and Prof. Yan. ⇑ Corresponding author. Tel.: +81 45 924 5507; fax: +81 45 924 5518. E-mail addresses: [email protected], [email protected] (Y. Shen).

consists of H2, CO, CH4, and CO2. Biomass gasification has many advantages over direct combustion. It can convert low-value feedstocks to high quality gas products directly burned or used for electricity generation. Syngas is also synthesized into liquid transportation fuels [6]. Condensable organics referred as tar are produced with syngas during biomass gasification and their contents of 0.5–100 g/m3 depending on the type and design of gasifier, feedstock types, and processing conditions [7]. Herein, tar is composed of all organic compounds in syngas [8]. Tar can condense in pipes, filters, or downstream equipment and processes, thereby breaking down the entire system. Tars may also deactivate catalysts in the refining process. Tar removal by efficient adsorption and reforming to syngas would be important and

http://dx.doi.org/10.1016/j.apenergy.2014.10.074 0306-2619/Ó 2014 Elsevier Ltd. All rights reserved.

Please cite this article in press as: Shen Y et al. In situ catalytic conversion of tar using rice husk char/ash supported nickel–iron catalysts for biomass pyrolytic gasification combined with the mixing-simulation in fluidized-bed gasifier. Appl Energy (2014), http://dx.doi.org/10.1016/j.apenergy.2014.10.074

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Y. Shen et al. / Applied Energy xxx (2014) xxx–xxx

indispensable for commercialization [9]. It is essential to reduce the level of tars to enable widespread utilization of syngas. Up to now, several approaches such as physical treatment [10–12], thermal cracking [13], plasma-assisted cracking [14,15], and catalytic reforming [16–20], have been widely applied for tar elimination. Among these, catalytic reforming is considered the most promising in large-scale applications due to fast reaction rate and reliability [20] to increase the additional syngas such as CO and H2. Various types of catalysts such as calcined rocks [21], zeolites [22], iron ores [23], alkali metals [24], Ni-based catalysts [25,26], and noble metals [27–31] have been employed for tar removal in biomass pyrolysis/gasification. Due to catalytic activity and economic reasons, the nickel-based catalysts show considerable performances on tar reforming [32–38]. Nickel catalysts are usually supported by metal oxides or natural minerals (e.g., dolomite, olivine) [39–44]. These supports are relatively expensive, and the catalyst preparation steps are complex and energy consuming. As an alternative, char has been employed as a low-cost adsorbent/ catalyst in tar removal [45–49]. The deactivated char catalysts could be simply burnt or catalytic gasified to recover the energy without the frequent regeneration. However, biomass char has unfixed properties depending on biomass type and process conditions. Recently, Wang et al. [50] studied char and char-supported nickel catalysts for secondary syngas cleanup. Ni-based catalysts were fabricated by mechanically mixing NiO with char particles. More than 97% of tars can be removed by using the Ni/coal-char and Ni/wood-char catalysts (15% NiO loading) at 800 °C. Iron-based catalyst and additive iron have also been attracted more attention. For instance, Nemanova et al. [51] used the Fe based catalysts for biomass tar decomposition. Liu et al. [52] studied in details, the different metal additives (i.e., Fe, Mg, Mn, Ce) on catalytic reforming of biomass tar over Ni6/palygorskite. It has been proved that iron plays a better role in improving its reactivity. Fe-based catalysts are cheaper and environmental friendly than Ni-based catalysts [53]. Besides, mono- or bi-metallic catalysts, such as Fe/Al2O3, Co/Al2O3, Fe–Co/A12O3 and Ni–Co/A12O3 were benefit for steam reforming of tar [54,55]. In this work, we investigated in-situ tar conversion by co-pyrolysis of biomass and the rice husk char (RHC) and rice husk ash (RHA) supported nickel–iron catalysts for biomass gasification. Subsequently, the RHA-supported catalysts could be considered as bed materials by mixing-simulation to optimize the mass fraction and particle size used for the fluidized-bed gasification.

and proximate analysis, which were conducted by the elemental analyzer (EA, Vario MICRO Cube, Elementar, Germany) and the thermogravimetric analyzer (TGA, DTG-50, SHIMADZU, Nakagyo-ku, Kyoto, Japan), respectively. In addition, the chemical composition of RHA was determined by the X-ray fluorescence (XRF, SHIMADZU, Rayny EDX 700, Japan). It can be found that RHA is composed of a mass of SiO2, up to 94.64%, and a small quantity of minerals, such as alkali or earth alkali metal oxides. If RHC or RHA is employed as a catalyst support, it is necessary to introduce some metal species (e.g., Ni and Fe) with the aim of improving the catalytic performances. Furthermore, the BET surface area of RHC was larger than those of RH and RHA. It could be concluded that RHC is more suitable to be used as a support for catalysts preparation. 2.2. Catalysts preparation RHC was fabricated by slow pyrolysis from 25 to 700 °C in an inert gas (i.e., N2) atmosphere. The general procedure of the RHC/ RHA catalysts preparation was illustrated in Fig. 1. Three RHA Ni (Ni2+: 0.2 mol/L), RHA Fe (Fe3+: 0.2 mol/L) and RHA Ni–Fe (Ni2+: 0.1 mol/L, Fe3+: 0.1 mol/L) catalysts were simply prepared by the incipient wetness impregnation and calcination using the Fe(NO3)39H2O and Ni(NO3)26H2O as iron and nickel precursors. After impregnation and drying overnight at 105 °C, the metal species in RHC were calcined in air at 600 °C for 1 h before storage and further use. However, RHC Ni–Fe (Ni2+: 0.1 mol/L, Fe3+: 0.1 mol/L) was prepared without calcination. Furthermore, the fresh and used catalysts were characterized by the TGA and the X-ray diffraction (XRD, Rigaku, XRD-DSC II, Japan), respectively. 2.3. Biomass gasification and tar conversion

2. Materials and methods

The main experimental parameters of operating condition are shown in Table 2. Fig. 2A presents a schematic diagram of experimental apparatus, composed of a gas supplying system, a gas cleaning system and a pyrolysis-reforming facility. First, the gasification temperature was heated to 800 °C. Then, the carrier gas of nitrogen (N2) was continuously leaded into the entire system before adding the feedstock to ensure the gasification conducted in the absence oxygen. When the RH blended with the RHC or RHA catalysts was fed into the pyrolyzer (first-zone), the volatile matters were released in the forms of gas and tar (Fig. 2B). Consequently, biomass tar could be in-situ cracked and transformed by thermochemical reactions and catalytic conversion. Finally, the residual tar was condensed and collected in the gas-cleaning unit.

2.1. Biomass and char characterization

2.4. Sampling and analysis

Biomass feedstock of RH was collected from Thailand. Table 1 shows the properties of RH, RHC and RHA including the ultimate

The condensable tar can be determined by weighing [56]. And the yield of producer gas including the non-condensable tar was

Table 1 The properties of RH, RHC and RHA. Ultimate analysis (wt.%, dry and ash free basis) H

Oa

N

S

VMb

FCc

Ash

Moisture

37.9 64.8 9.5

6.3 2.4 0.3

55.3 35.1 90.2

0.4 0.1 0

0.1 0 0

60.5/59.3 11.7 5.4

11.9/10.4 34.3 7.8

22.0/20.5 52.0 85.3

5.6/9.8 2.0 1.5

2.2 117.0d 65.4

Chemical composition of RHA (wt.%) SiO2 Al2O3 Fe2O3

CaO

MgO

Na2O

K2O

Zn (ppm)

Mn (ppm)

Cu (ppm)

Cd (ppm)

94.64

1.88

0.96

0.39

0.58

18.20

52.24

32.17

0.48

RH RHC RHA

a b c d

SBET (m2/g)

Proximate analysis (wt.%, dry basis/as received)

C

0.06

0.23

Calculated by mass difference. VM-volatile matters. FC-fixed carbon. 700 °C char.

Please cite this article in press as: Shen Y et al. In situ catalytic conversion of tar using rice husk char/ash supported nickel–iron catalysts for biomass pyrolytic gasification combined with the mixing-simulation in fluidized-bed gasifier. Appl Energy (2014), http://dx.doi.org/10.1016/j.apenergy.2014.10.074

Y. Shen et al. / Applied Energy xxx (2014) xxx–xxx

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Fig. 1. Schematic diagram of the RHC/RHA Ni–Fe catalysts preparation procedure.

Table 2 Main experimental parameters of operating conditions.

3. Results and discussions

Condition

Parameter

Gasification style Pyrolysis temperature (°C) Biomass feedstock Feedstock size (mm) Sample weight (g) Carrier gas Carrier gas flow rate (L/min) Char particle size (mm) Amount of used catalyst (g)

Fast pyrolysis 800 Rice husk <0.5 10 N2 1.0 Original size 5

calculated by mass balance. The produced syngas mainly composed of H2, CH4, CO, CO2, and C2 (i.e., C2H4, C2H6) was collected by using an air bag at the outlet and measured by the micro gas chromatograph (Agilent, Micro GC, 3000A, America), which was fitted with a thermal conductivity detector (TCD). Each trial was maintained for 10 min to ensure the mass balance and the repeatability experiments were performed. Therefore, the collected tar sample was the total amount of tars generated from the repeatability experiments.

3.1. Catalysts characterization Fig. 3 shows the thermogravimetric (TG) analysis of the RHC and RHA/RHC supported catalysts under the air atmosphere. It can be observed that the RHA supported catalysts after calcination had higher thermal stability ascribed to the ash-basis. Nevertheless, the mass of RHC and RHC Ni–Fe was decreased with the increase of heat temperature under the air condition. When the temperature was above 400 °C, the mass of RHC was decreased rapidly due to the char-basis. After that, the mass kept constant after the temperature up to 600 °C. It could be suggested that RHC Ni–Fe are appropriate for tar catalytic conversion in the oxygen-free or oxygen-less atmosphere to extend its use longevity. It is known that carbon in RHC could react with plenty of oxygen agents to generate carbon oxides (i.e., CO, CO2) at high temperatures. The carbonaceous residue in the presence of high content of silica had considerable thermal stability and abrasive resistance. From TG curves of the RHC and RHC Ni–Fe, it indicated that the temperature range of 400–450 °C could be chosen for thermal regeneration of the RHC supported catalysts.

Fig. 2. Schematic of the lab-scale experimental setup (A) and biomass gasification scheme (B).

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sintering with the mineral MgO in RHA. Nevertheless, the iron crystal phases in the used RHA Fe2 were both iron oxide and metallic iron. During the pyrolysis, partial iron oxide in RHA Fe1 might be reduced into the metallic iron (i.e., Fe0) by the carbothermal reduction (R1) and (R2) and hydrogen reduction (R3). In the same way, partial nickel oxides in the fresh RHA Ni were reduced into the metallic nickel (i.e., Ni0) after used for biomass catalytic pyrolysis. In addition, the bimetallic catalysts of RHA Ni–Fe and RHC Ni–Fe can form the crystal structures of nickel iron oxides. The nickel oxides in the carbon matrix of RHC could be much easier reduced into the metallic nickel, while the iron oxides (e.g., Fe2O3) were transformed into the magnetites (R4).

Fig. 3. TG curves of RHC and RHA/RHC supported catalysts under the air atmosphere.

C ðsÞ þ NiO ðsÞ ! Ni ðsÞ þ CO ðgÞ

ðR1Þ

CO ðgÞ þ NiO ðsÞ ! Ni ðsÞ þ CO2 ðgÞ

ðR2Þ

H2 ðgÞ þ NiO ðsÞ ! Ni ðsÞ þ H2 O ðgÞ

ðR3Þ

Fe2 O3 ! Fe3 O4 ! FeO ! Fe

0

ðR4Þ

3.2. Tar yield and conversion efficiency The identification of crystal phases was performed by XRD using Rigaku D/Max 3400 powder diffraction with Cu Ka radiation (k = 0.1542) at 45 kV and 40 mA with a scanning rate of 5°/min. Fig. 4 shows the XRD patterns of the RHC, the fresh and used RHC/RHA supported nickel–iron catalysts. Moreover, their characteristics peaks are listed in Table 3. The typical amorphous silica characteristic peak in RHC is observed at a broad peak centered at 2h = 22.5°, which is attributed to the presence of the disordered cristobalite (SiO2) [57]. In the RHA supported metal (i.e., Fe, Ni) catalysts, the main crystal phases were metal oxides. As for the fresh RHA Fe1, the iron crystal phases were in the forms of iron oxide and magnesioferrite, which might be caused by iron oxide

Fig. 5 shows the condensable tar yield and conversion efficiency with the different char-supported catalysts. From the tar instance graphs after in-situ conversion, it could be intuitively observed that tar yield was decreased through co-pyrolysis of RH with the RHC/ RHA supported catalysts. The conversion efficiency of biomass tar was around 42% only mixed with RHC; whereas it can reach about 93% by co-pyrolysis with RHA Ni. It can indicate that the Ni-based catalysts have higher tar cracking/reforming performances. Metallic nickel (Ni0) catalyst possesses much higher reforming activity of hydrocarbons than metallic iron (Fe0) catalyst caused by the high activation ability of C–H and C–C bond in the hydrocarbon

Fig. 4. XRD patterns of the RHC, the fresh (1) and used (2) RHC/RHA supported catalysts.

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Y. Shen et al. / Applied Energy xxx (2014) xxx–xxx Table 3 XRD characteristic peak lists of the fresh and used RHC/RHA supported catalysts. No.

2h (deg)

d (Å)

Height (cps)

FWHM (deg)

Int. I (cps)

Phase name

RHA 1 2 3 4 5 6 7 8 9 10 11 12 13

Fe 1 30.22(6) 33.10(6) 35.639(12) 36.9946 40.8148 43.34(8) 49.53(10) 53.94(10) 57.407(14) 62.82(2) 64.13(8) 71.3758 74.5292

2.955(5) 2.705(4) 2.5172(8) 2.4280 2.2091 2.086(4) 1.839(3) 1.699(3) 1.6039(4) 1.4781(5) 1.4510(17) 1.3204 1.2722

70(8) 72(8) 274(17) 0.6652 338.3194 27(5) 14(4) 23(5) 49(7) 72(8) 9(3) 202.9877 851.8438

0.33(7) 0.35(6) 0.27(2) 0.4004 0.4004 0.36(6) 0.57(14) 0.65(8) 0.37(4) 0.40(3) 0.7(2) 0.4004 0.4004

41(3) 41(3) 120(3) 5.2712 6.6079 10(2) 11(3) 16(3) 22(2) 41(2) 8(12) 2.9033 5.9823

Magnesioferrite, syn(2, 2, 0) Iron oxide(1, 0, 4) Magnesioferrite, syn(3, 1, 1), Magnesioferrite, syn(2, 2, 2) Iron oxide(1, 1, 3) Magnesioferrite, syn(4, 0, 0), Iron oxide(0, 2, 4) Magnesioferrite, syn(4, 2, 2), Magnesioferrite, syn(5, 1, 1), Magnesioferrite, syn(4, 4, 0) Iron oxide(0, 2, 7) Magnesioferrite, syn(6, 2, 0), Magnesioferrite, syn(5, 3, 3)

RHA 1 2 3 4 5 6 7 8

Fe 2 30.3(2) 35.64(3) 43.47(15) 44.63(3) 53.81(14) 57.44(4) 62.70(14) 63.90(17)

2.95(2) 2.5169(19) 2.080(7) 2.0287(15) 1.702(4) 1.6030(11) 1.481(3) 1.456(4)

11(3) 65(8) 17(4) 70(8) 4(2) 13(4) 19(4) 7(3)

0.6(4) 0.55(6) 0.89(19) 0.20(4) 0.5(4) 0.29(12) 0.79(16) 2.2(8)

12(5) 59(3) 23(5) 17(2) 2(2) 6.9(17) 21(3) 32(5)

Iron oxide(2, 2, 0) Iron oxide(3, 1, 1) Iron oxide(4, 0, 0) Iron, syn(1, 1, 0) Iron oxide(4, 2, 2) Iron oxide(5, 1, 1) Iron oxide(4, 4, 0) Iron, syn(2, 0, 0)

RHA 1 2 3 4 5

Ni 1 37.236(19) 43.254(9) 62.88(3) 75.36(3) 79.34(10)

2.4128(12) 2.0900(4) 1.4767(6) 1.2602(4) 1.2066(13)

298(17) 520(23) 177(13) 57(8) 32(6)

0.29(2) 0.27(2) 0.41(4) 0.39(4) 0.51(8)

144(3) 247(3) 117(3) 32(2) 20(2)

Bunsenite(1, 1, 1) Bunsenite(2, 0, 0) Bunsenite(2, 2, 0) Bunsenite(3, 1, 1) Bunsenite(2, 2, 2)

RHA 1 2 3 4 5 6

Ni 2 37.1689 43.2593 44.461(10) 51.801(8) 62.9559 76.317(11)

2.4170 2.0898 2.0360(4) 1.7635(3) 1.4752 1.2468(15)

1.8510 5.6194 846(29) 331(18) 1.6701 128(11)

0.1895 0.1895 0.189(18) 0.181(14) 0.1895 0.19(2)

11.0002 19.4574 261(5) 103(2) 6.8988 42(2)

Bunsenite, syn(1, 1, 1) Bunsenite, syn(2, 0, 0) Nickel, syn(1, 1, 1) Nickel, syn(2, 0, 0) Bunsenite, syn(2, 2, 0) Nickel, syn(2, 2, 0)

RHA 1 2 3 4 5 6 7 8 9 10 11

Ni–Fe 1 30.35(4) 33.11(5) 35.63(2) 37.246(14) 43.262(15) 49.33(17) 53.94(2) 57.58(4) 62.85(2) 75.36(2) 79.37(8)

2.943(4) 2.704(4) 2.5178(14) 2.4121(9) 2.0897(7) 1.846(6) 1.6985(6) 1.5995(9) 1.4773(5) 1.2602(3) 1.2062(10)

40(6) 22.9777 167(13) 176(13) 293(17) 7(3) 20(4) 21(5) 151(12) 29(5) 26(5)

0.30(7) 0.17(15) 0.35(4) 0.24(3) 0.28(3) 0.3(2) 0.10(6) 0.60(10) 0.41(5) 0.39(7) 0.42(15)

18(3) 4.1273 110(3) 78(3) 140(3) 4(2) 4.1(12) 15(2) 112(3) 12(2) 19(2)

Nickel iron oxide(2, 2, 0) Hematite, syn(1, 0, 4) Nickel iron oxide(3, 1, 1), Hematite, syn(1, 1, 0) Nickel oxide(0, 0, 3), Nickel iron oxide(2, 2, 2) Nickel oxide(0, 1, 2), Nickel iron oxide(4, 0, 0), Hematite, syn(2, 0, 2) Hematite, syn(0, 2, 4) Hematite, syn(1, 1, 6) Nickel iron oxide(5, 1, 1), Hematite, syn(1, 2, 2) Nickel oxide(1, 1, 0), Nickel Iron Oxide(4, 4, 0) Nickel oxide(0, 2, 1), Nickel iron oxide(6, 2, 2), Hematite, syn(2, 1, 7) Nickel oxide(0, 0, 6), Nickel Iron oxide(4, 4, 4), Hematite, syn(1, 3, 1)

2.497(3) 2.0746(9)

16(4) 180(13)

0.71(15) 0.44(4)

13(4) 163(7)

RHA Ni–Fe 2 1 35.93(5) 2 43.591(19)

Iron oxide(1, 1, 0)

Iron oxide(2, 0, 2) Iron oxide(2, 0, 5) Iron oxide(0, 1, 8)

Iron oxide(1, 0, 10)

3 4 5 6

44.412(18) 50.87(3) 51.75(8) 63.1114

2.0382(8) 1.7935(9) 1.765(2) 1.4719

137(12) 59(8) 51(7) 4.6439

0.22(3) 0.29(4) 0.60(10) 0.5974

45(6) 26(4) 49(6) 13.9212

7 8

74.7538 76.165

1.2689 1.2489

43.4666 37.5747

0.5974 0.5974

23.0236 27.5757

Tetrataenite(1, 0, 1), Maghemite-Q, syn(2, 2, 5), Magnetite, syn(3, 1, 1) Tetrataenite(1, 1, 1), Maghemite-Q, syn(0, 0, 12), Magnetite, syn(4, 0, 0), Nickel oxide(2, 0, 0) Nickel, syn(1, 1, 1), Maghemite-Q, syn(4, 0, 2) Tetrataenite(0, 0, 2), Maghemite-Q, syn(2, 2, 11) Nickel, syn(2, 0, 0), Maghemite-Q, syn(4, 2, 4) Tetrataenite(1, 1, 2), Maghemite-Q, syn(3, 3, 11), Magnetite, syn(4, 4, 0), Nickel oxide(2, 2, 0) Tetrataenite(2, 0, 2), Maghemite-Q, syn(5, 4, 3), Magnetite, syn(5, 3, 3) Nickel, syn(2, 2, 0), Maghemite-Q, syn(5, 0, 13), Magnetite, syn(6, 2, 2), Nickel oxide(3, 1, 1)

RHC 1 2 3 4 5 6 7

Ni–Fe 1 10.94(2) 13.69(3) 16.6995 25.1916 32.9989 35.8752 53.7269

8.078(16) 6.465(16) 5.3045 3.5323 2.7123 2.5011 1.7047

63(8) 77(9) 13.3456 136.1396 19.4265 58.9951 13.6425

0.22(3) 0.32(3) 0.3163 0.3163 0.3163 0.3163 0.3163

17(2) 28(3) 9.9955 19.3182 10.2001 10.1228 4.8268

Nickel nitrate hydroxide Nickel nitrate hydroxide Nickel nitrate hydroxide Nickel nitrate hydroxide Nickel nitrate hydroxide Hematite, syn(1, 1, 0) Hematite, syn(1, 1, 6)

2.956(14) 2.5129(17)

23(5) 64(8)

1.0(3) 0.44(5)

48(6) 42(3)

Maghemite, syn(2, 2, 0) Maghemite, syn(3, 1, 1)

RHC Ni–Fe 2 1 30.20(15) 2 35.70(3)

hydrate(2, 0, 0) hydrate(2, 0, 2) hydrate(3, 0, 0) hydrate(2, 0, 4) hydrate(3, 1, 0), Hematite, syn(1, 0, 4)

(continued on next page)

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Table 3 (continued) No.

2h (deg)

d (Å)

Height (cps)

FWHM (deg)

Int. I (cps)

Phase name

3 4 5 6 7 8 9 10

43.43(3) 44.4788 50.58(7) 51.73(3) 53.89(7) 57.38(18) 62.87(17) 74.42(8)

2.0818(12) 2.0353 1.803(2) 1.7659(9) 1.700(2) 1.604(4) 1.477(3) 1.2738(12)

121(11) 63.8036 33(6) 29.0116 10(3) 13(4) 18(4) 18(4)

0.6597 0.3719 0.5454 0.3139 0.3(3) 0.73(14) 1.1(3) 1.8(2)

157.4386 25.2644 38.7336 17.8529 5(2) 11(3) 37(3) 72(4)

Iron nitride(1, 1, 1), Maghemite, syn(4, 0, 0) Maghemite, syn(4, 1, 0), Nickel, syn(1, 1, 1) Iron nitride(2, 0, 0), Maghemite, syn(4, 2, 1) Nickel, syn(2, 0, 0) Maghemite, syn(4, 2, 2) Maghemite, syn(5, 1, 1) Maghemite, syn(4, 4, 0) Iron nitride(2, 2, 0), Maghemite, syn(5, 4, 1), Nickel, syn(2, 2, 0)

3.3. Gas yield and composition Synthesis gas is the prime product of biomass pyrolysis. Their properties can reflect the pyrolysis and tar conversion efficiency with the different catalysts, because tar is cracked or transformed into the gas molecules by catalytic reforming. The gas yield could be estimated by expression (E1). In addition, the volume concentration of the dominate syngas components (i.e., H2, CO, CO2, CH4, C2H4 and C2H6) can be calculated by expressions (E2)–(E6). Gas yield ðL=gÞ ¼

H2 ðvol:%Þ ¼ Fig. 5. Heavy tar yield and conversion efficiency using char and different char catalysts.

molecules on the nickel metal surface [58]. Comparing the two bimetallic catalysts of RHA Ni–Fe and RHC Ni–Fe, the RHC Ni–Fe exhibited higher tar conversion efficiency (92.3% vs. 86%). Based on the catalysts characterization, RHA Ni–Fe exists mainly in form of the silica-based catalyst, whereas RHC Ni–Fe is the carbon–silica hybrid-based catalyst. Carbon in the RHC Ni–Fe plays a significant role for tar conversion. On one hand, porous carbon could increase the BET surface areas of catalysts contributing to the sorption effect; one the other hand, carbon itself can work as a medium decreasing metal oxides and tar at high temperature by reductive reactions. Guan et al. [9] proposed that partial metal oxides might be reduced into a metallic state by the reducing gases in syngas (i.e., H2 and CO) produced from the biomass pyrolysis without the aid of the catalyst. Therefore, Fe and Ni in their metallic forms rather than oxide forms were considered the main active sites for the tar reforming. Besides, it is possible that amorphous NiO in the RHC Ni–Fe catalyst might easier to be reduced into the metallic state of Ni (Ni0) than the crystalline NiO in RHA Ni–Fe. RHC Ni–Fe without calcination could be used for tar conversion as well. The synergy effect between the activation of tar on the Ni species and the oxygen atom supplied to the carbonaceous intermediate from neighboring Fe atoms was not displayed due to the low catalytic activity of iron oxide at lower temperature and pressure. Moreover, probably in the absence of steaming water, the Fe distribution in the samples after pyrolysis exhibits an imbalance between the phases FeO and Fe3O4 providing for tar conversion. Those Fe species always occur in the redox equations of the water gas shift reactions (R5) and (R6) [59]. Therefore, steam reforming by using the char-supported monometallic Fe and bimetallic Ni–Fe catalysts should be further studied to enhance the tar conversion efficiency and H2 yield.

Fe3 O4 ðsÞ þ CO ðgÞ $ 3FeO ðsÞ þ CO2 ðgÞ

ðR5Þ

3FeO ðsÞ þ H2 O ðgÞ $ H2 ðgÞ þ Fe3 O4 ðgÞ

ðR6Þ

Exit gas ðLÞ  N2 flow rate ðL=minÞ  Pyrolysis time ðminÞ Feedstock weight ðgÞ ðE1Þ

H2 ð%Þ H2 ð%Þ þ CO ð%Þ þ CO2 ð%Þ þ CH4 ð%Þ þ C2 H4 ð%Þ þ C2 H6 ð%Þ ðE2Þ

CO ðvol:%Þ ¼

CO ð%Þ H2 ð%Þ þ CO ð%Þ þ CO2 ð%Þ þ CH4 ð%Þ þ C2 H4 ð%Þ þ C2 H6 ð%Þ ðE3Þ

CO2 ðvol:%Þ ¼

CH4 ðvol:%Þ ¼

C2 ðvol:%Þ ¼

CO2 ð%Þ H2 ð%Þ þ CO ð%Þ þ CO2 ð%Þ þ CH4 ð%Þ þ C2 H4 ð%Þ þ C2 H6 ð%Þ ðE4Þ CH4 ð%Þ H2 ð%Þ þ CO ð%Þ þ CO2 ð%Þ þ CH4 ð%Þ þ C2 H4 ð%Þ þ C2 H6 ð%Þ ðE5Þ

C2 H4 ð%Þ þ C2 H6 ð%Þ H2 ð%Þ þ CO ð%Þ þ CO2 ð%Þ þ CH4 ð%Þ þ C2 H4 ð%Þ þ C2 H6 ð%Þ ðE6Þ

Fig. 6 shows the producer gas yield and syngas composition when different catalysts were used. It can be found that the amount of gas yield increased when the RHC and RHC-supported catalysts were applied. The increase of gas yield may be attributed to the thermochemical reactions between char, tar and catalysts at higher temperatures. On one hand, char can react with syngas (i.e., CO2 and H2) to produce more other syngas components (i.e., CO, CH4); on the other hand, tar can be cracked/converted into gas components by dry reforming over RHC and RHC-supported catalysts. More importantly, the further devolatilization of char could also contribute to the increase of gas yield. In particular, the gas yield can reach approximately 2.11 L/g when co-pyrolysis of RH and RHC Ni–Fe at 800 °C. When char was blended with RH, the CO volume concentration increased from 44.8% to 52.0%; whereas, the CO2 volume concentration decreased from 24.0% to 15.8%. It suggested that CO2 most likely reacted with char by Boudouard reaction in the presence of nickel catalysts, leading to the increase of CO volume concentration. Meanwhile, the methane (CH4) volume concentration slightly increased from 7.5% to 8.0%, possibly

Please cite this article in press as: Shen Y et al. In situ catalytic conversion of tar using rice husk char/ash supported nickel–iron catalysts for biomass pyrolytic gasification combined with the mixing-simulation in fluidized-bed gasifier. Appl Energy (2014), http://dx.doi.org/10.1016/j.apenergy.2014.10.074

Y. Shen et al. / Applied Energy xxx (2014) xxx–xxx

Fig. 6. Gas yield and composition with the RHC and RHA/RHC supported catalysts.

ascribed to the methanation reactions between CO2, C and H2. In addition, char itself could play the role of an adsorption-type catalyst for tar and CO2 conversion. Because of char further decomposition and catalytic effect, the gas yield by mixing with the RHC Ni–Fe was slight higher than the gas yield by mixing with the RHA Ni–Fe (2.11 L/g vs. 1.96 L/ g). Regarding to the volume concentrations of CO (55.2% vs. 41.8%) and H2 (22.7% vs. 31.5%), it was concluded that H2 could be slightly consumed in the presence of char and metal oxides at high temperatures. Herein, high concentration of H2 was not achieved, but the volume concentrations of CO and CH4 got improved. It should be noted that compared to raw yield (24.0%), CO2 volume concentrations were greatly decreased (the yields as follows: 15.8%, 11.9%, and 8.2%) by mixing with RHC, RHC Ni–Fe and RHA Ni, respectively. Furthermore, it is accorded with the previous result that NiO can play a critical role in decreasing the carbon deposit and increasing the amount of CO in the gaseous product [60]. The lower heating value (LHV) and the higher heating value (HHV) of the produced syngas is calculated by the empirical expressions of (E7) [61] and (E8) [62,63], respectively, where (CO), (H2), and (CH4) are molar fraction of the produced syngas in Fig. 6. The theoretical results are presented in Table 4. The LHV and HHV could reach about 10.64–12.80 MJ/m3, and 13.02–14.55 MJ/m3, respectively, at 800 °C, indicating a good quality of the syngas. Moreover, the producer gas showed a higher HHV by using the RHC supported catalysts.

LHV ðkJ=m3 Þ ¼ ½30ðCOÞ þ 25:7ðH2 Þ þ 85:4ðCH4 Þ  4:2 HHV ðkJ=N m3 Þ ¼

ðE7Þ

12:63ðCOÞ þ 12:75ðH2 Þ þ 39:82ðCH4 Þ þ 63:43ðCn Hm Þ 100 ðE8Þ

3.4. Tar catalytic conversion mechanisms In this work, monometallic Ni catalysts exhibited much higher reforming activity of hydrocarbons than monometallic Fe catalysts. This property is caused by the high activation ability of C–H and

Table 4 The LHV and HHV of the produced syngas using RHC and RHC/RHA supported catalysts.

LHV (MJ/m3) HHV (MJ/m3)

No catalyst

RHC

RHA Fe

RHA Ni–Fe

RHA Ni

RHC Ni–Fe

10.64 13.02

11.69 14.46

10.95 13.50

11.93 13.17

12.80 13.78

12.10 14.55

7

C–C bond in the hydrocarbon molecules on the metal (Ni) surface. Consequently, it seems that the additive effect of Fe is the increase of the number of active Ni surface, while the characterization results in the particle size and surface enrichment of Fe on the Ni–Fe bimetallic particles did not support the increase of the surface Ni atoms. Another reason might be the co-catalytic function of Fe. Since Fe has high oxygen affinity than Ni, the addition of Fe to Ni catalysts can increase the coverage of oxygen atoms during the reforming reactions. The catalytic activity of the RHC/RHA supported Ni–Fe catalysts for tar conversion can be concluded as the following order: RHA Ni > RHC Ni–Fe > RHA Ni–Fe > RHA Fe > RHC. In summary, biomass was initially decomposed into the small pieces of gas, tar and char by thermochemical reactions in the pyrolyzer. The produced tar could be further cracked and reformed simultaneously through the RHC/RHA supported Ni–Fe catalysts at high temperatures. Herein, RHC most likely plays two significant roles in the process of biomass pyrolysis. On one hand, it works as an intermediate carbon source to reduce the metal oxides by carbothermal reduction; on the other hand, it works as a carbon adsorbent to insert metal cations and tar.

3.5. Mixing-simulation in fluidized bed gasifier (FBG) Gasification of biomass and wastes in FBG has advantages, since FBGs are capable of being used in the pilot and large scales, overcoming limitations found in smaller scale, fixed-bed gasifiers. On the other hand, the bed temperature is limited to avoid the bed agglomeration and the gasification efficiency of a fluidized bed (FB) may be limited if part of the fuel energy remains in unconverted char. Meanwhile, if the temperature is not high enough in the gasifier, tar in the producer gas can make the process unsuitable from a technical and economical point of view. Models can be helpful for design of gasifier, for prediction of operation behavior and emissions during normal conditions, startup, shutdown, changes of fuel and load. The modeling could be carried out from preliminary design of an industrial process to complex simulation of a unit. Experiments, especially at large scale, are usually expensive and complicated. Nevertheless, modeling is economy and convenient and it can support the preparation and optimization of experiments to be conducted in a real system [64]. The tools available for modeling of the FBG reactors are the more or less simplified equations for conservation of mass, energy and momentum, which complemented by boundary conditions, constitutive relationships, and terms expressing the sources and sinks of the system. To determine the latter, rate laws for the chemical or physical conversion processes are required. Thermodynamic data are considerable to estimate properties and thermal data as well as reaction products by equilibrium assumptions. Fig. 7 schematically presents each process occurs in an FBG including the bed level with bubble and emulsion phases, the particle level with gases release and char gasification, and the gas phase reactions where water gas shift reaction plays a significant role. Some processes strongly interact between one level and another. For instance, the heat and mass transport to a particle takes place on the particle level, while their rates are determined by the fluid dynamics of the bed (reactor level) and by fuel reactivity, both in case of devolatilization and char conversion. Moreover, these processes are included in source terms of the conservation equations treated by the sub-models during execution of numerical calculations. The description on the particle level is composed of the particle size and biomass properties, such as density and thermal conductivity, which affect the devolatilization time and the volatiles composition. On the reactor level various factors are considered: residence time (mass inventory in an FB), boundary conditions, just like fuel feed points and feed rate, freeboard size,

Please cite this article in press as: Shen Y et al. In situ catalytic conversion of tar using rice husk char/ash supported nickel–iron catalysts for biomass pyrolytic gasification combined with the mixing-simulation in fluidized-bed gasifier. Appl Energy (2014), http://dx.doi.org/10.1016/j.apenergy.2014.10.074

8

Y. Shen et al. / Applied Energy xxx (2014) xxx–xxx

Fig. 7. Description of processes in an FBG.

fluidization velocity, and their effects on solids elutriation, solids and gas mixing, segregation, etc. [64]. The performance of FBG, including the carbon conversion efficiency and the tar content, may significantly depend on the movement of solids and gas in bed and freeboard. For instance, in a pilot circulating FBG (CFBG), reactor conditions resulting in lack of contact between char/oxygen and tar/catalyst and an unfavorable consumption of oxygen by the devolatilization gases were identified, resulting in lower char conversion and higher tar content in the product gas. Modeling of solids and gas mixing can identify the best arrangement for design and operation of the gasifier. Particularly, the solids mixing simulation could optimize the operation parameter of solid particles (i.e., biomass, sorbent, catalyst, bed material) in FBG as well. In theory, the solid–solid mixing of species i could be determined by the expression (E9), applied for transport of solid (index s) in an isothermal system. The closest representation of the real process is a balance on the transported variables formulated and solved for each phase k (gas and solids and their i components): density, momentum, and enthalpy (qk, qk,i, lk, and hk, in general terms, u). The balance of the conserved variables u over a fixed element (eulerian formulation) of reactor volume can be expressed in the following form (somewhat simplified, in the case of momentum), applicable to any reactor type: the accumulation of u is due to the net difference between the rates of change by convection and dispersion or by generation and consumption, S, per unit volume.

@ uk þ div ðuk uk Þ ¼ div ðD/k grad uk Þ þ Su;k @t

ðE9Þ

@csi þ div ðus csi Þ ¼ div ðDsV=H;i grad csi Þ þ Ssi @t

ðE10Þ

The solids movement in an FB is often described by the simple version of the expression (E9), in which diffusion and convection are lumped into one term, called dispersion and expressed by the fine particles and deep beds, i.e., chemical reactors, where the small-scale mixing mechanisms are dominant. In the FB, besides

the inert bed material or solid catalyst, there is a distribution of fuel and char particles in the bed. Therefore, the movement of solids in the vessel should be described by accounting for three or more solids types. Nevertheless, qualitatively the motion of biofuel particles could be visualized as the movement of flotsam particles in a jetsam-rich bubbling FB (BFB). High superficial velocity might improve the mixing behavior, but biomass particles with lower density and larger size than bed material particles are still nonuniformly distributed. At a given fluidization velocity, char particles are most likely to be elutriated from the bed or to sink from the bed surface than devolatilizing particles. The reason is that the jet force from escaping volatile matters tends to keep them floating. A key issue in modeling FBG is whether the fuel particles keep floating, once they have reached the bed surface or if they are compelled to descend. This depends much on the segregation behavior of a few flotsam particles in a bed of many jetsam particles. Thereby, segregation should be avoided to preserve the bed from sintering or excessive tar emission in an FBG. Segregation is most likely to occur if the ratio is equal to or below 0.5. A mixing ratio between 0.5 and 1 is desirable to be out of segregation problems [64]. Nevertheless, Fermoso et al. [55] investigated a sorption enhanced catalytic steam gasification of biomass in a combined downdraft FB and fixed bed reactor. The solids feed was composed of 15 wt.% of raw biomass and 85 wt.% of a mixture of sorbent and catalyst particles (sorbent/catalyst = 9 g/g) with the aim of producing high purity hydrogen (>99.9 vol.%). It can be indicated that the mixing ratio of biomass and catalyst is, in a great extent, determined by practical demands. Fluidization mainly depends on the bed pressure drop and fluidization velocity. As shown in Fig. 8, when the fluid velocity is too small, the solid particles will remain on the bed. The phase between A and B is the fixed bed phase. When the gas velocity exceeds to B phase, the bed pressure drop decreases slightly attributed to the loose arrangement of solid particles. After that, the gas velocity continues increasing, whilst the bed pressure drop keeps constant and the bed height increases gradually. In this moment, the solid particles can float in the fluid and roll up and down with the gas movement, which is called the fluidized bed phase. When

Please cite this article in press as: Shen Y et al. In situ catalytic conversion of tar using rice husk char/ash supported nickel–iron catalysts for biomass pyrolytic gasification combined with the mixing-simulation in fluidized-bed gasifier. Appl Energy (2014), http://dx.doi.org/10.1016/j.apenergy.2014.10.074

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In general, the terminal fluidized velocity ut could be calculated by the semi-empirical expressions of (E18)–(E20), if the Reynolds number is estimated. Additionally, the superficial gas velocity umf (m/s) at minimum fluidization can be calculated by the empirical expression of (E21). 2

ut ¼

gdp ðqs  qg Þ ; 18l

Rep;t 6 0:4

#1 2 3 4 gðqs  qg Þ ut ¼ dp ; 225 qg l

ðE18Þ

"

Fig. 8. Effect of gas velocity on the pressure drop in FBG.

ut ¼ the gas velocity is much higher than E point, the fluid can taken away the whole bed; consequently, the solid particles form the dilute phase in the state of suspension and are blown out. After E phase, the normal fluidization state is broken, and the bed pressure drop decreases rapidly. Thus, the gas velocity in point E is referred as the terminal or maximum fluidization velocity ut. Qualitatively judging the tendency of a particle to be carried away can be made by calculating the terminal velocity of a single particle ut.

/¼

s S

ðE11Þ

where / is the particle sphericity to account for particle shape, s is the surface of a sphere having the same volume as the particle and S is the actual surface area of the particle. In the previous study, a simple general correlation for predicting terminal velocities for isometric particles, given information on the particles and physical properties of the fluid, can be defined as the expressions (E12)– (E15) [65].

" ut

¼

18  2

ðdp Þ

þ

#1 ð2:335  1:744/Þ  0:5

ðdp Þ

" ut ¼ ut

q2g g lg ðqs  qg Þ

" 

dp ¼ dp

Rep;t ¼

#1=3

#1=3 g qg ðqs  qg Þ

l2g

¼

Rep;t Ar 1=3

¼ Ar1=3

qg dp ut lg

ð0:5 6 / 6 1Þ

ðE12Þ

ðE13Þ

ðE14Þ

ðE15Þ

" #1 3:1gdp ðqs  qg Þ 2

qg 1:82

umf ¼ 0:695

dp

;

0:4 6 Rep;t 6 500

Rep;t P 500

ðqs  qg Þ0:94

l0:88 q0:06 g

ðE19Þ

ðE20Þ

ðE21Þ

Mixtures of solid particles of different size and density tend to separate in vertical direction under fluidized conditions. The nonuniform distribution of the different solid components is caused by a competitive action of mixing and segregation mechanisms. RH has very low bulk density (96–160 kg/m3) with a very low terminal velocity ut (1.0–1.4 m/s based on its physical properties) [67]. The fluidization characteristics of single RH could be observed from Fig. 9. When the superficial gas velocity ug is smaller, the pressure drop increases with the increase of superficial gas velocity ug. However, the pressure drop decreases due to gas block caused by the formation of channeling and cavitas, when the superficial gas velocity ug is increased to 0.27 m/s. Although the gas flow increases, most of bed materials keep stationary. Meanwhile, small amounts of RH particles are entrained from channeling to bed by gas, and thus the cavitas and channeling continue caving and forming. Even if the pressure drop trends to be keeping constant, the RH particles cannot perform the fluidization behavior in the whole process. Rao and Ram [68] also proved that it is difficult to fluidize single RH, and its fluidization behavior is improved by mixing with other solid particles (i.e., sand). The biomass constituted 2%, 5%, 10% and 15% determined by weight of the mixtures. The minimum fluidization velocity umf increased with the increase of biomass mass fraction, as well as with increasing sand density and particle size. It also can be observed in Fig. 10A that the bed pressure drop versus superficial gas velocities is plotted with the aim of determining the minimum fluidization velocity umf of mixture, which is obtained

where ut is the terminal velocity of particle in fluid (m/s), ut⁄ is the dimensionless particle velocity (m/s), dp is the solid equivalent particle diameter (m), dp⁄ is the dimensionless particle diameter (m), Rep,t is the Reynolds number based on the equivalent spherical diameter of particle, qg is the density of gas (kg/m3), qs is the density of solid particle (kg/m3), lg is the viscosity of gas [kg/(m s)], g is the acceleration due to gravity (9.81 m/s2), and Ar is the Archimedes number. If the fluidizing medium was dry air and the measurements were conducted under a temperature of 20 ± 1 °C and the ambient pressure, the density and dynamic viscosity of the air could be estimated from the expressions of (E16) and (E17) [66].

qg ¼ 3:485

P T

lg ¼ 1:81  105

ðE16Þ 

0:66 T 293

ðE17Þ

Fig. 9. Characteristic curve of fluidization of single RH with the particle density of 950 kg/m3 and the particle diameter of 2 mm.

Please cite this article in press as: Shen Y et al. In situ catalytic conversion of tar using rice husk char/ash supported nickel–iron catalysts for biomass pyrolytic gasification combined with the mixing-simulation in fluidized-bed gasifier. Appl Energy (2014), http://dx.doi.org/10.1016/j.apenergy.2014.10.074

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Fig. 10. (A) Pressure drop of RH-sand and RH-silica sand binary mixture as a function of superficial gas velocity; (B) Minimum fluidization velocity as a function of mass fraction of RH particles. The density sand particles is 2600 kg/m3 with the average diameters of 360 and 440 lm; the density of silica sand particles is 2700 kg/m3 with the average diameters of 360 and 710 lm; the density of RH particles is 950 kg/m3 with the average dimension of 10  2  1 mm.

from the intersecting point of the curve of fixed bed at defluidization with the constant pressure line at the flow condition. Moreover, the minimum fluidization velocity umf can increase with the increase of the averaged mass fraction of RH, and decreases with the decrease of the sand particle size (Fig. 10B). The equivalent diameter of a sphere RH particle dr,av could be obtained by calculating the Ergun Eq. (E22) at a given superficial gas velocity ug [69]. Consequently, the appropriate RH particle size could also be obtained by measuring the pressure drop, in which the calculated equivalent diameter of RH particles is 1.54 mm.

ð1  eg Þ2 lg ug DP 1  eg qg 2 ¼ 150 þ 1:75 u H e3g dr;av g e3g d2r;av

ðE22Þ

As shown in Table 5, although the bulk density qb of the mixed RHC/RHA is still low, its particle density qp and particle diameter dp are comparable to the sand particles. Moreover, the particle size of the RHA-supported catalysts could be modified easier than sand particles. It is most likely that mixing with the RHA-supported catalysts could improve RH fluidization behavior in FBG. Thus, with the aim of implementing a fluidized state, it is necessary to simulate the particle sizes of RH and RHA in a static system of binary mixture. In this case, the fluidizing medium is assumed dry air, carrying out at a temperature of 20 ± 1 °C under the ambient pressure, the gas density qg and the dynamic viscosity lg can be estimated as 1.2 kg/m3 and 4.26  105 kg/(m s), respectively. In the BFB, when biomass and inert particles are blended relatively homogeneous in

Table 5 The properties of RH, RHA and sand. Properties Density (kg/m3) Average particle diameter (dav,r, mm) Bed voidage (e) Sphericity (/) Minimum fludization velocity (umf, m/s)

Bulk (qb) Particle (qp) 1  (qb/qp) Theoretical calculation Experimental (pressure drop plot)

RH

RHA

Sand (250–595 lm)

100 950 2 0.9 0.19 –

120–140 2000 0.108 0.93–0.94 0.23–0.25 0.06

1460 2430 0.342 0.40 0.92 0.09

Fig. 11. Effect of (A) mass fraction (RH particle diameter: 2 mm) and (B) particle diameter (RH mass fraction: 0.5) on the minimum fluidization velocity in the modeled binary mixture of RH and RHC.

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Y. Shen et al. / Applied Energy xxx (2014) xxx–xxx

a good fluidization state, the mixture particle diameter and density could be normally calculated by the expressions of (E23) and (E24), respectively. Therefore, the minimum fluidization velocity umf in the binary mixture of RH and RHA could be estimated by the expression of (E20). As shown in Fig. 11, it was found that decreasing both the mass fraction and the particle diameter of RH can increase the minimum fluidization velocity umf of the mixture, thereby improving RH fluidization behavior. When the mass fraction of RH is increased up to 0.5, the minimum fluidization velocity umf can be increased dramatically (Fig. 11A). In contrast, when the particle size of RH exceeds to 0.5 mm, the increase tendency of the minimum fluidization velocity umf becomes weaken (Fig. 11B). If the particle diameters of two components have large differences, the mixture could obtain a higher minimum fluidization velocity umf due to the strong segregation effect. Accordingly, when the superficial gas velocity ug is too small, the high-density deposits (i.e., RHA, sand) would keep stable on the bed; whilst the low-density of RH can keep fluidization state. Thus, the particle diameters of RH and RHA should employ the approximate sizes. Furthermore, based on the experimental and simulated results, the mass fraction of 0.5 and the particle diameter of 0.5 mm can be selected for RH in this binary mixture, where the umf is 0.48 m/s.

"

qP ¼

dP ¼

x1

qp;1

þ

x2

qP;2

#1 ;

x 1 ¼ 1  x2

x1 qP;2 þ x2 qP;1 dP;1 dP;2 x1 qP;2 dP;2 þ x2 qP;1 dP;1

ðE23Þ

ðE24Þ

In summary, when the binary cocktail of RH and RHA catalysts was studied by mixing-simulation, some hidden factors were not considered. In the instance, the metal or metal oxides in RHA were ignored, which contributes to the increase of the particle density; and the real RH or RHA particles were non-uniform. Besides, the density of solid particle was assumed that it would not be changed with the change of particle diameter. In the actual situation, the density of single particle should be calculated as the sum of all the discrete densities that are produced from the discretisation of the particle. It is necessary to combine the experimental results in a small or a large scale FBG with the simulated results to analyze these influence factors in details. If necessary, the ternary cocktail of RH, RHA and other solid particles (e.g., sand, dolomite) could be studied with the objective of reducing the catalysts expense and improving the biomass fluidization behavior. Furthermore, the nickel-based carries (e.g., RHA Ni) might show some technical viability in the chemical looping combustion process [70]. 4. Conclusions An alternative biomass catalytic pyrolysis/gasification technology has been developed for in-situ tar conversion. Co-pyrolysis with the RHC/RHA supported Ni–Fe catalysts, the tar yield and CO2 concentration were greatly decreased during biomass gasification. Particularly, the condensable tar conversion efficiency could reach about 92.3% by mixing with the RHC Ni–Fe; accordingly, the light tar with three- and four-ring aromatic organic compounds could significantly be transformed into single-ring organic compounds or smaller gas molecules. It is worth pointing out that partial metal oxides were transformed into metallic states via carbon and gas in-situ thermal reduction, thereby enhancing the catalytic activity, in terms of tar conversion. Meanwhile, a higher gas yield of 2.11 L/g was obtained by blended with the RHC Ni–Fe attributed to char further devolatilization and tar conversion. Although the bimetallic RHC/RHA supported catalysts (i.e., RHA Ni–Fe, RHC Ni–Fe) exhibited lower tar conversion efficiency compared with

11

the monometallic RHA Ni, the expense of catalyst synthesis was much cheaper because of low-concentration Ni used. Moreover, omitting the calcination step, the preparation procedure of catalysts became much convenient and energy saving. Without water, the synergy effect between the activation of tar on the Ni species and the oxygen atom supplied to the carbonaceous intermediate from neighboring Fe atoms was not displayed in the dry reforming process. The char-supported catalyst (i.e., RHC Ni–Fe) is highly recommended to be employed for biomass gasification process in the absence or less of oxygen. Reacting with enough oxygen agents at high temperatures, char and char-supported catalysts could be easily consumed, possibly decreasing their service life and increasing CO2 concentration in syngas. However, the deactivated RHC Ni might be directly catalytic gasified into the additional syngas. Furthermore, by optimizing the operation parameters (e.g., particle size, mass fraction) in the mode of FBG, mixing with some solid particles (e.g., sand, RHA supported catalysts) could improve the RH fluidization behavior. Consequently, the RH mass fraction of 0.5 and the particle diameter of 0.5 mm can be employed in the binary mixture of RH and RHA. Tar and char are the unexpected by-products during the process of biomass pyrolysis/gasification. Although activated chars are extensively applied as carbon-based adsorbents to deal with various pollutants such as heavy metal wastewaters, they have been rarely fabricated into the catalysts or supports for tar conversion. Subsequently, an integrated sustainable pathway is proposed that chars including coal chars and biochars could be modified into activated carbons for heavy metal wastewater treatment (e.g., electroplating wastewater/sludge), along with the production of char-supported catalysts for tar conversion.

Acknowledgements We would like to thank the Chinese Scholarship Council (CSC) for the financial support under the Grant No. 201206230168. We are grateful of the editors and reviewers for their valuable comments.

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Please cite this article in press as: Shen Y et al. In situ catalytic conversion of tar using rice husk char/ash supported nickel–iron catalysts for biomass pyrolytic gasification combined with the mixing-simulation in fluidized-bed gasifier. Appl Energy (2014), http://dx.doi.org/10.1016/j.apenergy.2014.10.074