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Air-Blown Entrained Flow Gasification of Biocoal: Gasification Kinetics and Char Behavior Ludwig Briesemeister, Michael Kremling, Sebastian Fendt, and Hartmut Spliethoff Energy Fuels, Just Accepted Manuscript • DOI: 10.1021/acs.energyfuels.7b01611 • Publication Date (Web): 01 Aug 2017 Downloaded from http://pubs.acs.org on August 9, 2017
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Air-Blown Entrained Flow Gasification of Biocoal: Gasification Kinetics and Char Behavior Ludwig Briesemeister*†, Michael Kremling†, Sebastian Fendt†, Hartmut Spliethoff†‡ †
Technical University of Munich, Germany, Department of Mechanical Engineering, Institute for
Energy Systems, Boltzmannstr. 15, 85748 Garching ‡
ZAE Bayern, Germany, Walther-Meißner-Straße 6, 85748 Garching
KEYWORDS: biomass, entrained flow gasification, hydrothermal carbonization, random pore model, intrinsic reactivity, thermogravimetric analysis
ABSTRACT
Air-blown entrained flow gasification of biomass has the potential of overcoming tar-related problems that occur in fixed bed or fluidized bed gasifiers. For designing entrained flow reactors (EFR), specific information on the gasification behavior of the fuel is required. Therefore, experiments with biocoal from the hydrothermal carbonization (HTC) of different feedstock (beech, biogenic residuals, municipal waste and green waste) are performed under EFR conditions and compared to lignite. Pyrolysis chars from biocoals and lignite are obtained in EFR at 900-1300 °C for a reactivity analysis. Intrinsic reaction rates of the char reactions with CO2, H2O and O2 are measured in a thermogravimetric analyzer (TGA). Compared to lignite,
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chars from biocoal are less reactive due to smaller surface areas and less catalytic ash constituents. Char samples from gasification with varying air-to-fuel equivalence ratios λ and residence times are sampled from an autothermal gasifier and from a lab-scale EFR at 900-1300 °C. Carbon and overall conversion is determined by means of the ash-tracer-method. The evolution of particle size, surface area and density of the chars with increasing conversion is measured and simple model approaches are applied to describe the observed behavior. The results show that fuel properties and gasification conditions significantly influence the prevailing reaction regimes and require particular consideration.
1 INTRODUCTION Today, global primary energy consumption is mainly based on the utilization of fossil fuels with 41 % of the energy-related CO2-emissions caused by power generation.1,2 In order to reduce CO2-emissions, renewable energies like biomass or biogenic residues can be used in small-scale units. State-of-the-art technologies for lignocellulosic biomass conversion are gasification (fixed or fluidized bed gasifiers) or direct combustion. While small-scale combustion cycles (with steam or organic media as the working fluid) have limited thermodynamic efficiencies, biomass gasification is often associated with technological problems especially related to tar generation. Therefore, recent research aims at the application of entrained flow gasification for biomass to produce a tar-free gas for power generation or synthesis processes.3–5 In order to fulfill the high fuel quality requirements, biomass is usually thermally pre-treated by torrefaction5–7 or HTC4,8,9. Air is preferred to oxygen as a gasification agent because an air separation unit for the supply of oxygen is not economically feasible, especially for decentralized power generation.10 The syngas
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of air-blown gasifiers can be used in gas engines that are suitable for lean gases with lower heating values of around 5 MJ/Nm3.11,12 Compared to entrained flow gasifiers using oxygen as gasification agent, air-blown gasifiers operate at significantly lower temperatures due to the high nitrogen content. This can lead to lower cold gas efficiencies as a consequence of incomplete fuel conversion. Fuel conversion can be increased by optimizing the operating conditions, e.g. by air preheating10,13 and process control in terms of air and fuel staging14. However, the design of the gasifier geometry itself is one of the key aspects. It requires detailed information on the fuel behavior and its reaction kinetics under entrained flow gasification conditions. Simulation models of the process should consider the specific pyrolysis behavior of a fuel as well as intrinsic reaction kinetics and the influence of char morphology on diffusion effects.15 For fossil fuels, complex sub-models and simulation approaches are described in literature15–18 whereas the state of knowledge for biogenic fuels is less developed19. During the conversion in an EFR, the fuel is rapidly heated with 104-106 K/s while releasing water and volatiles.20 Subsequently, the remaining porous char reacts with CO2 and H2O to form syngas (CO, H2, CO2, H2O, N2) which is the rate-determining step.21 The gas-solid reactions take place inside the particle pores and the corresponding reaction rates are therefore – amongst other influences – dependent on the available specific surface area and the gas diffusion through the particle boundary layer and inside the pores. In order to describe the overall reaction, a common attempt is to separately measure the chemical intrinsic reactions (without influences of diffusion effects) and the char behavior under conditions relevant for EFR.22,23 Different authors report strong influences of the pyrolysis conditions on char reactivity. The main influences leading to decreased reactivity are the residence time and the temperature24,25, whereas a high heating rate favors porous chars with a high reactivity26–28. Intrinsic reaction rates
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are often modelled with an nth order rate equation considering the influences of temperature and partial pressure of the reactants. Values for the activation energies and reaction orders are published for CO2, H2O and O2-reactions with chars from fossil fuels and biomass. Published values of the activation energy for CO2 and H2O are reported around 200 kJ/mol with corresponding reaction orders around 0.5.17,27,29,30 For O2, the activation energy is around 130150 kJ/mol with higher reaction orders around 0.53-0.9.23,29,31 Besides the intrinsic reactivity, particle behavior is investigated in terms of the surface area evolution, particle density and diameter. The surface area is often described by the random pore model (RPM) developed by Bhatia und Perlmutter.32 For modeling particle density and diameter evolutions, power law approaches are commonly used.33,34 However, currently no detailed investigations of the reactivity and char behavior for biomasses pre-treated with HTC are available. Therefore, this paper has the objective of investigating the gasification behavior of different pre-treated biomasses under reaction conditions relevant for industrial-like EFR. The applicability of commonly used modeling approaches to describe the intrinsic reactivity and the particle behavior is investigated. 2 EXPERIMENTAL SETUP Gasification and pyrolysis experiments are performed using two different gasification test rigs shown in Figure 1. The Baby High Temperature Entrained Flow Reactor (BabiTER) consists of an electrically heated ceramic tube (1) of 1.48 m length and an inner diameter of 40 mm. It is designed for atmospheric pressure and allows for gasification and pyrolysis experiments in varying gas atmospheres at well-defined temperatures. Particle and gas samples can be taken from the hot reaction zone (2) on different heights, thus allowing for a variation of the particle residence time.
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The BiOmass pilOt-Scale enTrained flow gasifiER (BOOSTER) on the other hand is a more industrial-like gasifier. It is designed for autothermal operation at pressures up to 5 barg and a thermal fuel input of around 100 kW. Fuel is supplied by a pneumatic dense-phase conveying system and inserted with a swirl burner (3) together with pre-heated air (4). A camera (5) allows for the observation of the flame inside the reaction chamber (6) which has an inner diameter of 250 mm and a total length of 2.3 m. The reactor vessel (7) contains a refractory. At the end of the reactor, the syngas is water quenched (8), filtered (9,10) and burnt in a flare (12). A regulation valve (11) controls the system pressure. Similar to the BabiTER, particle and gas samples can be taken from the hot reaction zone by a hot probe (13-15). More information on both devices can be found in other papers.4,5,35 fuel MFC dosing system reactor 1
MFC MFC
T1 T2 T3
2
reaction gas
3
gas preheating
4
5 T1
electric heaters
T2
6
7
T3 T4
exhaust gas
T5
N2 O2
9
T6
water quench syngas
8 10 13
14
11
15
12 syngas
Figure 1. Simplified flow sheets of BabiTER (left) and BOOSTER (right). For the investigation of the char reactivity, a TGA (Linseis Model PT 1600) is used. It allows for the gasification of char samples of 10-50 mg at different temperatures and gas atmospheres by
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adjusting the supply of CO2, H2O, N2 and O2. During gasification, the loss of char sample mass is measured time-resolved. Thereby the influence of temperature and partial pressure of the reactant gases on the reaction rate can be determined. Five fuels are used for the investigations to cover a wide range of different input materials. Four fuels represent hydrothermal carbonized biomass based on a mixture of biogenic residues for composting (HCo), beech wood (HBe), green waste (HGW) and municipal waste (HMW). HCo, HBe and HGW were produced in an HTC demonstration plant by SunCoal Industries. Applied HTC conditions were around 210 °C at 20-21 bar with a residence time of 3 hours. The Spanish company Ingelia produced HMW at 205-215 °C at 17-19 bar with a residence time of 6 hours. After HTC treatment, the fuels are mechanically dewatered, thermally dried and grinded in order to reach the final water content and particle size. Rhenish lignite (RL) was purchased as a filter dust directly from the manufacturer and required no further processing. It is selected in this work as a reference fuel due to its well-known fuel properties from literature so that a direct comparability of the results is given. Table 1 summarizes the chemical and physical properties of all fuels. HCo, HBe and HGW have similar properties as RL in terms of the chemical composition and the heating value. In comparison to these, HMW has a very high ash content and a high share of volatiles. Since ash constituents have a significant influence on the char reactivity19, they are evaluated by the alkali index AI (1). The AI is used by different authors to describe the combined effect of the composition and amount of ash both for biomasses36,37 and fossil fuels38,39. It is calculated by the ash content [wt.-%] of the fuel and the mass fractions of each ash constituent. = ∙
(1)
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A high AI-value denotes a high share of catalytic active species within the ash that increase the reactivity of the char. Calculated values for all fuels are given in Table 1.
Table 1. Chemical and physical properties of the fuels, all values on an as received (ar) basis HTC Compost
HTC Beech
HTC Green Waste (HGW)
HTC Municipal Waste (HMW)
(HCo)
(HBe)
Rhenish Lignite (RL)
Ultimate analysis in wt.-% C
59.96
55.62
60.74
35.28
60.30
H
3.67
4.25
5.28
2.74
3.79
N
0.68
0.35
0.70
1.85
0.67
S
0.57
0.31
0.38
1.48
0.52
O (calculated)
20.15
25.56
26.61
11.06
17.48
Proximate analysis in wt.-% Moisture
11.32
8.51
2.29
11.13
13.32
Volatile yield
55.11
56.03
59.71
45.10
46.19
Ash
3.66
5.40
3.99
36.46
3.92
Fixed carbon (fc)
29.91
30.07
34.01
7,31
36,56
20.34
22.75
13.21
22.06
53.1
87.3
56.2
52.2
56.5
28.3
2.0
5.7
47.0
50.8
Lower heating value in MJ/kg LHVfuel
22.00
Particle size analysis in µm d50 Alkali index [-] AI
In order to maintain a stable gasification operation, the physical ash behavior plays an important role. While oxygen-blown EFR operate in slagging mode (i.e. the fuel ash completely melts), airblown gasification is preferably operated in a non-slagging mode. HTC pre-treatment is known to increase the ash-melting temperature, which makes it beneficial for air-blown gasification.40 Therefore, most of the fuels used in this work show high ash-fusion temperatures that were determined by standard procedure [DIN 51730] in an ash-melting microscope, see Figure 2.
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Compared to the other fuels, the ash fluid and hemispherical temperatures of HGW and HMW are considerably lower. 1600
temperature [°C]
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1400
deformation temp. spherical temp. hemispherical temp. fluid temp.
1200
1000
800 RL KOM HCo GSM HGW BUC HBe HMW RBK OSA
Figure 2. Ash-fusion temperatures of the tested fuels. 3 Experimental RESULTS The reaction kinetics of the fuels HGW, HBe and RL are investigated in detail, whereas the other fuels are only analyzed for their char behavior during gasification under autothermal conditions. 3.1 Pyrolysis char production Pyrolysis chars are produced under inert atmosphere in the BabiTER in order to measure the final volatile yield at high heating rates and temperatures from 900-1.300 °C. Feeding rate and gas flows are adjusted in such a way that a constant plug-flow residence time is reached. Char samples are collected after 0.5 s and 1 s. The dry and ash-free (daf) volatile yield is calculated via an ash-tracer-method, assuming that ash behaves inertly and completely remains in the char.41,42 Since HTC reduces the amount of volatile ash constituents40,43 this assumption is considered as justifiable. By comparing the content of ash in the fuel , and in the pyrolysis char sample , the volatile yield can be calculated as the overall conversion with equation (2).
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=
!"#$%,& ⁄"#$% !"#$%,&
(2)
In this work, the Q factor is used, which describes the volatile yield under EFR conditions compared to the yield from the proximate analysis (3). ( factor =
/01 230 45 (57)
230 45 9:3;<0 =4>> (57)
(3)
Figure 3 shows the results of the pyrolysis experiments. After 0.5 s, the volatile yield at 900 °C is incomplete and reaches significantly lower values than for 1 s. After 1 s, the Q factor is between 0.9-1.2, whereas a clear trend for the influence of temperature is not visible. Since relevant temperatures for air-blown gasification are above 1000 °C, a very fast volatile release can be expected. A Q factor around 1 is typical for fossil fuels at pyrolysis temperatures between 1100-1300 °C and residence times between 0.2-0.6 s.44,45 Therefore, in this work, a constant volatile yield equal to the one from the proximate analysis is assumed for the evaluation of the gasification trials.
1.2
Q factor [-]
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1
0.8
0.6 800 1100 1400 800 1100 1400 800 1100 1400 temperature [°C] temperature [°C] temperature [°C] residence time 0.5 s
residence time 1 s
Figure 3. Relative volatile yields for HGW (left), HBe (middle) and RL (right). 3.2 Char production by gasification
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Gasification chars are collected from BabiTER trials between 900-1300 °C after residence times of 0.5 and 1 s. Furthermore, ? is varied between 0.3-0.5. It describes the ratio of the actual oxygen input @A to the oxygen required for stoichiometric combustion @A ,>03/ (4). ?=
BAC
BAC ,DEFGH
(4)
The gasification trials at the BabiTER are evaluated regarding carbon and overall conversion and the results are shown in Figure 4. Overall conversion is calculated using equation (2) and describes the conversion of all reactive components in the fuel. Carbon conversion I is also derived from the ash-tracer-method and is calculated by equation (5). " ∙"#$%,&
I = 1 − "L
L,& ∙"#
%$(5)
Here, I, and I are the carbon contents in the fuel and in the char, while , and are the ash contents in the fuel and the char with all values on a water-free basis (wf). For all fuels, the increase of the temperature has the strongest impact on conversion due to increasing reaction rates of the endothermic gasification reactions. By increasing λ, more oxygen is available for the combustion of the volatiles, which leads to increased partial pressures of CO2 and H2O. On the other hand, λ has a minor effect on the temperature for these trials due to the low thermal input by the fuel compared to the electric heating. Overall, increasing temperatures, λ and residence times lead to higher conversions. Some measurements, especially those performed at 0.5 s, show inconsistencies regarding this trend. These occur due to methodological and measurement errors and do not represent specific gasification phenomena. The predominant sources of error in this context are the ash-tracer-method and the char sampling. For RL, the residence time has a great influence on conversion. In contrast, for HBe, longer residence times do not affect the conversion significantly. The conversion after 1 s is similar to the one reached with RL. When looking at the comparably high volatile yield of HBe, it can be
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concluded that the conversion results mainly from the pyrolysis, whereas the residual char after pyrolysis has a low reactivity. HGW behaves almost like RL, but the achieved conversions are higher mainly due to the higher volatiles yield. The strong influence of λ and residence time
0.9
0.9
overall conversion [-]
carbon conversion [-]
indicates a high reactive char.
0.7
0.5
0.3 0.25 0.35 0.45 0.55 λ
0.7
0.5
0.3 0.25
0.45
0.55
0.9
overall conversion [-]
carbon conversion [-]
0.35 λ
0.9
0.7
0.5
0.7
0.5
0.3 0.25 0.35 0.45 0.55 λ
0.3 0.25 0.35 0.45 0.55 λ 0.9
0.9
overall conversion [-]
carbon conversion [-]
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0.7
0.5
0.3 0.25 0.35 0.45 0.55 λ 900°C; 0.5s 1100°C; 0.5s 1300°C; 0.5s
0.7
0.5
0.3 0.25
0.35
0.45
0.55
λ 900°C; 1s 1100°C; 1s 1300°C; 1s
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Figure 4. Influence of temperature and λ on carbon and overall conversion for HGW (top), HBe (middle) and RL (bottom). Chars from BOOSTER are collected for all fuels. The experimental procedure is described in another paper in which the trials for HGW are described in detail.4 For the other fuels, the test procedure is comparable to HGW. Since the BOOSTER operation is autothermal, a separate investigation of λ and temperature is not possible. Therefore, different conversions of the chars used in this work result from mixed influences of λ-variation between 0.3-0.6 and partly from the addition of steam. These conditions are representative for industrial-like autothermal gasification. 3.3 Determination of char reactivity Char reactivities are analyzed for pyrolysis chars from BabiTER for RL, HGW and HBe. With the objective of reaching a thermal pre-treatment representative for EFR-conditions, pyrolysis chars from BabiTER at 1100 °C and 1 s residence time are considered for TGA measurements. Thereby a high heating rate is achieved and the char is thermally annealed16,24. A sample mass of 20 mg is applied to the TGA and different gasification trials with varying temperatures and partial pressures are performed in isothermal operation. Temperatures are chosen as low as possible to ensure reaction conditions of regime I (chemical reaction without diffusion effects). Investigated partial pressures MN of CO2, H2O and O2 are 0.05, 0.1 and 0.2 bar in order to cover the range of partial pressures occurring in air-blown gasification. The observed reaction rate OP [g/(g ∙ s)] is derived from the measurement data by equation (6). VB
OP = VW∙ B = − (
!XL%#Y )
VXL%#Y VW
(6)
Here, m is the actual sample mass and IZ is the char conversion.
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Figure 5 shows the procedure for analyzing the temperature influence using HBe chars in CO2atmosphere as an example. Temperatures at which the reaction starts are determined by heating rate experiments (left). Based on this information, trials with different temperatures are performed (middle) and the reaction rate is calculated. For the calculation of the activation energies, the reaction rates are averaged at low char conversion between 0.1-0.2 (right). Hence, the measured surface area from BabiTER pyrolysis chars can be assumed to derive intrinsic reaction rates.17 935 °C 900 °C 850 °C 800 °C
900
4 0
∆m T
-4
600 -8 ∆m
T
300
-12
0
-16 0
1 2 time [h]
3
0
1
2 3 time [h]
4
935°C 900°C 850°C 800°C averaging interval
1E-02
sample weight [mg] robs [s-1]
1200
temperature [°C]
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5
1E-03
1E-04 0
0.25 0.5 0.75 char conversion [-]
1
Figure 5. Methodology of the TGA char reactivity analysis using HBe at M[\] = 0.1 bar. Eventually, the intrinsic reaction data, in terms of the pre-exponential factor aNbWZ,N , the reaction order cN and the activation energy d,N are derived by equation (7). The specific surface areas ef of the pyrolysis chars are measured by CO2 adsorption (CO2-DFT-method) in order to represent the surface area of micro pores.46 l
b
m,n g = ef ∙ ONbWZ,N = aNbWZ,N ∙ ef ∙ exp k− o∙p q ∙ MN n (7) OP,N
Table 2 summarizes the results of the TGA experiments and contains fuel and reaction specific temperature intervals of the performed trials. In order to determine the reaction orders, changes of the partial pressure are performed at intermediate temperatures. Both activation energies and
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reaction orders are comparable to literature data, though the values of the CO2-activation energy for RL and HBe are lower than expected. The char reaction with H2O and O2 is significantly more sensitive to pressure influence than the CO2-reaction. Due to the different temperature levels of the trials, a direct comparison of the char reactivities is not possible.
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Table 2. Intrinsic reaction data of pyrolysis chars from BabiTER fuel
RL
HGW
HBe
c
aNbWZ
[kJ/mol]
[−]
[g⁄(m ∙ s ∙ bar ) ]
C + H] O
221.7
0.40
8.27E+05
C + CO]
176.3
0.27
9.94E+02
C + O]
117.8
0.97
1.83E+04
350-450 °C
C + H] O
215.7
0.51
1.18E+05
700-800 °C
C + CO]
195.4
0.27
5.20E+03
C + O]
122.4
0.84
2.09E+04
350-450 °C
C + H] O
211.3
0.55
2.83E+04
750-850 °C
C + CO]
174.2
0.34
1.77E+02
C + O]
129.5
0.74
1.53E+04
reaction
d
]
=
ef
T
[m] ⁄g (57) ]
[°C] 650-750 °C
637
671
545
700-800 °C
700-800 °C
800-935 °C 400-450 °C
Therefore, based on the relation in equation (7) observed reaction rates of the three reactions are calculated for all fuels at the same reaction conditions and compared in Figure 6. The calculated values do not include diffusion effects, which are likely to occur at 800 °C especially for the O2reaction. For all reactions, RL has the highest reactivity while HBe char is the most unreactive. This corresponds to the order of the AI-values, indicating a high catalytic influence of the fuel ash for all reactions. The pyrolysis char surfaces, on the other hand, are on a similar level and cannot explain the large differences in reactivity. Char reaction with O2 is several magnitudes faster than the gasification reactions of which in turn the H2O-reaction is significantly faster than the one with CO2. These findings are in accordance with literature data for coal chars47–49 and show the importance of the H2O-reaction for the gasification process.
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1E+01
O2
CO2
H2O
1E+00 1E-01
robs [s-1]
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1E-02 1E-03 1E-04 1E-05 GSM HGW
BUC HBe
RBK RL
Figure 6. Comparison of observed reaction rates calculated at 0.1 bar, T = 800 °C.
3.4 Particle behavior during gasification Models used for simulating the particle behavior describe the evolution of diameter, surface area and density based on the char conversion. Therefore, char conversion is calculated just like the carbon conversion but considering only the fixed carbon content in the fuel zI, that neglects the volatile carbon fraction, see equation (8). This calculation is only valid for a Q factor = 1, which is roughly assumed from Figure 3. " ∙"#$%,&
IZ = 1 − L "
{L,& ∙"#
%$(8)
In order to describe the surface area evolution with conversion, the RPM formulation in equation (9) is used, which Feng and Bhatia46 derive from the original version developed by Bhatia and Permutter32 in order to consider mass based surface area values. ef = ef ∙ |1 − } ∙ ln (1 − IZ )
(9)
Based on the initial surface area after devolatilization ef [m] /g], the model uses } as the only adjustable parameter. The value of the structural parameter } characterizes the pore system in the particle in which large values of } describe a strong development during gasification due to
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pore growth and overlapping, whereas small values indicate a fully developed system after pyrolysis. In this work, } is used as a fitting parameter and determined by a least squares method to match experimental data. All given surface areas are daf-based, thus representing only the specific surface area of the carbon mass. Strictly speaking, the RPM in this form only describes the reaction behavior under regime I conditions. However, different authors successfully use it for modeling the surface area evolution even under oxygen-blown gasification or combustion conditions both for biomass50,51 and fossil coals17,29 in which char reactions usually occur in regime II or III. The results of the surface area measurements and the best RPM-fits are represented in Figure 7 separately for BabiTER and BOOSTER trials, whereby results for HCo are only available from BOOSTER. Herein, data from BabiTER trials are shown for the experiments at 1100 °C and 1300 °C after 0.5 s and 1 s, whereas measurements at 900 °C are not considered. Due to a strong influence of incomplete volatile release and reduced heating rates at 900 °C, the surface areas are much smaller. Both data from 1100 °C and 1300 °C trials are used for the model fit due to the small number of measuring points. ef is considered as the surface area measured in the pyrolysis experiments at 1100 °C after 1 s. With increasing conversion, the surface area clearly increases for RL, while for HBe and HGW, the trend is almost constant. Compared to RL, the surface areas of HBe are smaller. This can be attributed to remaining structures of beech as feedstock, which forms stable fibrous structures of little micro porosity during pyrolysis.52 Chars from HGW have large surface areas already after pyrolysis. Although some values are far scattered, it can be concluded from the data that the pore system develops during pyrolysis but does not change much subsequently. Based on the BabiTER results, with regard to the simulation of lignocellulosic biomass gasification (in contrast to fossil fuels like RL) a consideration of
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detailed sub-models for surface area evolution does not seem to provide additional information. This finding was already stated by Di Blasi when comparing approaches of different scientific works in which similar gasification devices are used.19 RL
1100
HBe
1100
HGW
1100
HCo
1100
Ψ = 1.01
Sg [m²/g(daf)]
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800
Ψ = 0.03
800
800
800
Ψ = 0.05 Ψ = 0.48
500
Ψ=0.617 500
500
500
Ψ =2.21 200 0
0.2 0.4 0.6 0.8 1 char conversion [-]
Ψ = 3.88
200
200 0
0.2 0.4 0.6 0.8 1 char conversion [-] BOOSTER
0
0.2 0.4 0.6 0.8 1 char conversion [-]
BabiTER 1300°C
200 0
0.2 0.4 0.6 0.8 1 char conversion [-]
BabiTER 1100°C
Figure 7. Measured char surface evolution with best RPM-fits for BabiTER and BOOSTER. However, especially the results for HBe and HGW from BOOSTER trials are quite different to those from BabiTER in terms of the achieved surface area level and its development with conversion. For the evaluation of the BOOSTER trials, besides }, ef is also used as a fitting parameter because pyrolysis experiments cannot be performed in BOOSTER. All fuels show a clear increase of the surface area with increasing conversion, however, for HBE and HGW, the predicted surface areas by the RPM at low conversion are much smaller than the values measured from pyrolysis trials. The most likely explanation for this behavior is the different experimental procedure of the autothermal trials. Here, higher conversion rates result from increased λ-values, which, in turn, reduce the residence times.4 Additionally, the calculated residence times in BOOSTER are in the range of 2.1-4.5 s and therefore much longer than those in BabiTER. These effects therefore indicate a reduction of available surface area due to ash fusion, which is mainly caused by long residence times and high temperatures.18 For HGW, the effect is particularly pronounced due its low ash-fluid temperature (see Figure 2). In contrast, for
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RL, the results from BabiTER and BOOSTER are comparable because pore closing for lignite gains importance only well above 1200 °C.18 HCo shows a similar behavior as RL and pore closing does not seem to occur. However, since most of the conversion during the gasification process occurs in the flame within short reaction times, the RPM model derived from BOOSTER experiments is likely to underestimate the available surface area for the reactions. Table 3 summarizes the model parameters for both BabiTER and BOOSTER trials. In any case, the results show that for understanding the surface area evolution of lignocellulosic biomass during gasification in autothermal EFR, the utilization of electrically heated reactors, like the BabiTER, does not cover all occurring phenomena. The change of the particle size with progressing conversion is only analyzed for HGW in more detail. In contrast to the surface area measurements, ash-related effects are not expected to play an important role for the particle size evolution. Hence, even by considering only the autothermal trials, the impact of typical reaction conditions in air-blown EFR on particle size can be described. Figure 8 shows particle size distributions and mean particle diameters of HGW, pyrolysis char sampled from BabiTER at 1100 °C after 1 s (Pyr) and gasification chars from BOOSTER with given char conversion values. Particle size distributions of fuels and chars are measured by means of laser diffraction (Shimadzu SALD 2201). HGW has a large share of fine particles that convert completely during pyrolysis. Starting from the particle size distribution after pyrolysis, the change during gasification is very little and the mean particle diameter almost stays constant. The apparent formation of large particles that do not appear in the particle size distribution of the fuel probably results from a measurement error due to particle adherence. For EFR conditions at comparably low temperatures, an unchanged mean particle diameter during conversion is typical and reported in literature.50 In comparison to combustion53,54 or oxygen-
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blown gasification18, the reaction conditions in air-blown EFR are less affected by limitations due to pore diffusion (regime II) or diffusion through the boundary layer (regime III). Therefore, the char reactions occur throughout the whole particle not only at the external surface. 120
dmedian [µm]
1.2
dV/dlog(dp)
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0.8 0.4
80
40
0
0.0 1
10 100 1000 particle diameter [µm] HGW 0.41 0.62 0.95
0 0.25 0.5 0.75 1 char conversion [-]
Pyr 0.58 0.78
Figure 8. Particle size distribution (left) and mean particle diameters (right). In the event of a constant particle diameter during gasification, the char conversion results from a decreasing particle density. In this work, particle densities are analyzed for chars from the autothermal gasification trials. For this purpose, the crucial reference value is the apparent density of the carbon structure I, describing the mass of carbon in relation to the volume of solid carbon and pores. Since I, cannot be measured directly, it is derived from the apparent particle density , by taking into account only the ash-free particle mass and volume. For this purpose, a constant ash density of 2.8 g/cm³ is assumed.18 , in turn is calculated from the bulk density ,P by considering a constant packing factor M (10). , = ,P ∙ M !
(10)
The use of a constant packing factor is a valid assumption if fuel and char particles have comparable sizes, which for HGW is shown in Figure 8. For M, a value of 0.42 determined by Ma for different coal chars is used.54
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The power law formulation in equation (11) is used to model the density evolution with increasing conversion. It is capable of describing reactions from regime I ( = 1) to regime III ( = 0). Since the carbon density after pyrolysis I,, cannot be measured from BOOSTER trials, both I,, and are fitted to experimental data. I, ⁄I,, = (1 − IZ )
(11)
Figure 9 shows the results of the experiments, theoretic boundaries of the different reaction regimes and the least square fits for RL, HMW and HCo. Regime III
1
Regime II 0.8
ρc,app/ρc,app,0 [-]
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0.6
0.4 0.2
=0 = 0.22 = 0.48 = 0.65 =1
0 0
0.2
RL
HCo
0.4 0.6 char conversion [-]
HGW
HBe
0.8
1
HMW
Figure 9. Char density evolution in BOOSTER. Except for HBe, the model is in good agreement with the experimental data. According to the model, the reactions mainly occur under regime II conditions denoting that the reaction rates are prevailingly limited by pore diffusion. Generally, the main influences on the predominant reaction regime are temperature and char properties (e.g. particle size, porosity, reactivity, surface area).20 Thereby, on the one hand, it is not possible to determine a single crucial property, but, on the other hand, when comparing the fuels, the large surface area and the high reactivity of RL favor diffusion limitations. For HMW, the gasifier temperatures are comparably low due to
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the high ash content in the fuel. Therefore, the conversion is almost solely controlled by chemical reactions. It is worth noting again that different conversions in BOOSTER result from changing λ. Thereby, the influence of diffusion limitations increases for chars with high conversion, as a consequence for low conversion, is slightly underestimated. Table 3 summarizes the parameters of the density model. Table 3. Model parameters for surface and density evolution, values in ( ) from BabiTER RL
HBe
HGW
HMW
HCo
Particle surface evolution ef [m] g (57) ]
603.1 (637.7)
257.7 (545.4)
214.2 (671.7)
[-] (-)
658.2 (-)
}
0.481 (1.012)
2.212 (0.046)
3.881 (0.030)
[-] (-)
0.617 (-)
Particle density evolution I,, [kg⁄m(57) ]
909.0
459.2
500.3
834.6
977.3
0.222
0.232
0.270
0.645
0.477
4 CONCLUSION AND OUTLOOK Air-blown entrained flow gasification of HTC biocoal is a promising technology. For the designing and optimization of the gasifier, specific information on the fuel behavior under conditions relevant for EFR are required. In this work, pyrolysis and gasification chars from lignite and different biocoals are produced at different temperatures, residence times and gasification atmospheres. Intrinsic reactions of pyrolysis chars in a CO2 and H2O-atmosphere are measured in TGA. Char from biocoal is less reactive than that of lignite, which is explained by the different catalytic effect of the fuel ash. For all chars, the dominant gasification reaction is with H2O. Chars of RL produced at 1100-1300 °C and low residence times show an increasing inner surface area with increasing conversion, in contrast to biocoals whose pore structure seems to be
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fully developed already after pyrolysis. Achieved surface areas are in the range of 450-900 m²/g. Biocoal chars produced in an autothermal process and longer residence times have significantly less surface area. Probably ash-fusion effects are the reason for this finding. It is concluded that chars sampled after short residence times better represent the surface area available for reactions in the flame. The RPM is used to model the surface area evolution with conversion and shows good results. Densities of chars from autothermal gasification are analyzed and the evolution with conversion is modeled using a power law approach. The model accords well with experimental data and indicates a significant influence of pore diffusion limitation on particle behavior. This effect is differently pronounced for the different fuels depending on the resulting gasifier temperature and specific fuel properties. In order to improve the gasification behavior of biocoals, future work should address the influences of the HTC treatment on fuel characteristics. Furthermore, the collection of char samples from autothermal gasification after different residence times without varying λ is desirable. The assumption of a constant packing factor should be verified by means of gas pycnometry or porosimetry.
AUTHOR INFORMATION Corresponding Author *
[email protected] Notes The authors declare no competing financial interest.
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ACKNOWLEDGMENT This work was supported by the German Federal Ministry for Economic Affairs and Energy (BMWi) within the framework of the project “FLUHKE” (FKZ 03KB074B). The authors would like to thank the students involved in this work (Roland Balint, Sung Ho Min and Martijn van Stiphout) as well as Karl Rainer Stephan for his valuable input. The support of the TUM Graduate School is gratefully acknowledged.
ABBREVIATIONS AI, alkali index; BabiTER, Baby High Temperature Entrained Flow Reactor; BOOSTER, BiOmass pilOt-Scale enTrained flow gasifier; DFT, density functional theory; daf, dry and ash free; EFR, entrained flow reactor; fc, fixed carbon; HBe, hydrothermal carbonized beech wood; HCo, hydrothermal carbonized residues for composting; HGW, hydrothermal carbonized green waste; HMW, hydrothermal carbonized municipal waste; HTC, hydrothermal carbonization; LHV, lower heating value; MFC, mass flow controller; pf, packing factor; RL, Rhenish lignite; RPM, random pore model; TGA, thermogravimetric analyzer; wf, water free
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