Coal Char-CO2 Gasification Measurements and Modeling in a

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Coal Char-CO2 Gasification Measurements and Modeling in a Pressurized Flat-Flame Burner Randy C Shurtz, and Thomas H Fletcher Energy Fuels, Just Accepted Manuscript • DOI: 10.1021/ef400253c • Publication Date (Web): 22 May 2013 Downloaded from http://pubs.acs.org on May 23, 2013

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Coal Char-CO2 Gasification Measurements and Modeling in a Pressurized Flat-Flame Burner Randy C. Shurtz and Thomas H. Fletcher* Department of Chemical Engineering, Brigham Young University Provo, UT 84602, USA [email protected], [email protected]

Abstract A pressurized flat-flame burner (PFFB) was used to conduct coal gasification studies. The PFFB was designed to provide an environment with laminar, dispersed entrained flow, with particle heating rates of ~105 K/s, pressures of up to 15 atm, and gas temperatures of up to 2000 K. Residence times were varied from 30 to 700 ms in this study. Char gasification studies by CO2 were conducted on a subbituminous coal and 4 bituminous coals in the PFFB. Pressures of 5, 10, and 15 atmospheres were used with gas compositions of 20, 40, and 90 mole % CO2. Gas conditions with peak temperatures of 1700 K to 2000 K were used, which resulted in char particle temperatures of 1000 K to 1800 K. Three gasification models were developed to fit and analyze the gasification data. A simple 1st-order model was used to show that the measured gasification rates were far below the film-diffusion limit. The other two models, designated CCK and CCKN, were based on three versions of the CBK models. CCKN used an nth-order kinetic mechanism and CCK used a semi-global Langmuir-Hinshelwood kinetic mechanism. The two CCK models fit the PFFB gasification data better than the 1st-order model. The fits of the gasification data with CCK and CCKN were comparable to each other. The fit of the data in CCK suggests that Knudsen diffusion may have influenced the gasification rates in the PFFB experiments. The gasification rate parameters in each of the three models were correlated with coal rank. 13C-NMR parameters were used to estimate a structural parameter of the coal char. Char-CO2 gasification rate coefficients correlated better with this NMR-based char structure index than it did with the carbon and oxygen content of the parent coal. Keywords: Coal, Gasification, Pressure *Corresponding author: Chemical Engineering Department 350 CB Brigham Young University Provo, UT 84602 [email protected]

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1. Introduction

Following primary pyrolysis of coal in a gasifier the char, tar, and soot begin to undergo heterogeneous oxidation and gasification. Changes in the structure of a coal particle during pyrolysis influence the subsequent char reaction history in various ways. The magnitude and accessibility of surface area for heterogeneous reaction on the interior surfaces of the char particles determine the reaction rate at a given temperature. Gasification rates are particularly sensitive to post-pyrolysis particle size, which has been found to be quite sensitive to the maximum particle heating rate and total pressure for bituminous coals.1-6 The temperatures at which different physical processes dominate the observed reaction rate have been described in terms of three zones.7 At low temperatures (Zone I), oxidation or gasification kinetics are rate-limiting, while diffusion of reactants through the particle boundary layer is rate-limiting at very high temperatures (Zone III). At intermediate temperatures (Zone II) both reaction kinetics and diffusion through pores determine the observed reaction rates. Practical applications of combustion and gasification of pulverized coal typically occur in Zone II, where the particle size and pore structure strongly influence the rates at which gaseous reactants are transported to the internal surfaces of the char. Zone II rates are influenced by many physical phenomena, which make them difficult to predict accurately (effectiveness factors are embedded in the observed rates). The evaluation of new gasifier designs can best be accomplished through the use of relatively simple gasification kinetic mechanisms that have been fit to data obtained at high temperatures, high heating rates, and high pressures. Such data may also be used to validate more sophisticated kinetic models. For the development of advanced gasification models, pyrolysis and gasification 2


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experiments should be conducted at temperatures, initial heating rates, and pressures that are typical of industrial gasifiers. A review of published gasification experiments is found in Table 1, along with the corresponding pyrolysis conditions. Many gasification studies conducted at “high heating rates” occur in drop-tube furnaces (DTF) or other entrained-flow reactors (EFR) that are limited to initial heating rates on the order of 104 K/s, which is where maximum swelling seems to occur.1-3 Wire mesh reactors (WMR) and especially thermogravimetric analyzers (TGA) achieve much lower initial heating rates and are more suitable for measuring intrinsic Zone I rates. WMRs and TGAs often use large individual particles or a bed of particles that may experience significant transport limitations. For these reasons, experimental data from these devices may not be representative of industrial entrained-flow conditions. The work presented in this paper includes results of experiments on coal char gasification by CO2, performed in a pressurized flat-flame burner to achieve particle heating rates of 105 K/s at pressures up to 15 atm and gas temperatures up to 2000 K. The gasification data were used to fit rate parameters in three different gasification models. A means to correlate the char gasification reactivity with coal rank was devised for all three models. 2. Experimental

A newly developed pressurized flat-flame burner (PFFB) system was used to perform the pyrolysis and gasification tests at pressures up to 15 atm. A schematic of the PFFB system is shown in Figure 1, and is fully described by Shurtz.1, 2, 8 This system used an array of diffusion flamelets in a pressure vessel to convectively heat the coal particles at rates on the order of 105 K/s for particles smaller than ~100 µm. These particle heating rates are 2-10 times higher than conventional electrically-heated drop-tube furnaces. 3


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Table 1. Recent pyrolysis and gasification studies

Source

Coal Particle Size, Pyrolysis System, Initial Heating Rate

Pyrolysis Temperature, Pressure

Gasification System & Reactants

Gasification Temperature, Total Pressure

Industrial PC Gasifiers

50 – 150 µm entrained flow at ~106 K/s

Up to 2000oC 2.5 – 3.0 MPa

Entrained Flow O2, H2O, CO2

up to 2000oC; Zone II-Zone III 2.5 – 3.0 MPa

Peng et al., 1995 9

149 – 210 µm TGA at 102 – 103 K/s

1000 – 1400oC 0.1 MPa

TGA, H2O

1000 – 1400oC 0.1 MPa

Lim et al., 1997 10

106 – 150 µm WMR at 103 K/s Fixed Bed at 10 K/s

1000oC 0.1 – 3.0 MPa

WMR, Fixed Bed O2, CO2

850oC, 1000oC 0.1 – 3.0 MPa

Messenböck et al., 1999, 2000 11, 12

106 – 150 µm, WMR at 103 K/s

1000oC 0.1 – 3.0 MPa

WMR, TGA O2, H2O, CO2

1000oC 0.1 – 3 MPa

Roberts and Harris, 2000, 2006 13, 14

1000 – 6000 µm Crucibles at 0.17 K/s

1100oC 0.1 MPa

PTGA O2, H2O, CO2

500 – 940oC 0.1 – 3 MPa

Wu et al., 2000 15

63 – 90 µm DTF, PDTF at ~104 K/s

1300oC 0.1 – 1.5 MPa

N/A N/A

N/A N/A

Ahn et al., 2001 16

45 – 64 µm PDTF at 104 K/s

1400oC 0.1 MPa

PDTF, TGA CO2

900 – 1400oC 0.5 – 1.5 MPa

Kajitani et al., 2002, 2006 17, 18

26 – 39 µm DTF at ~104 K/s

1100 – 1500oC 0.1 MPa

PDTF, PTGA CO2, H2O

1100 – 1500oC 0.2 – 2.0 MPa

19

N/A PEFR, PDTF at ~104 K/s Crucibles at 0.17 K/s

1100oC 0.1 – 1.5 MPa

PTGA O2, H2O, CO2

Zone I (low) 0.1 – 1.5 MPa

Yu et al., 2004a 20

45 – 185 µm, 63 – 95 µm PEFR, DTF at ~104 K/s

1100 – 1400oC 0.1 – 2.0 MPa

PEFR H2O, CO2, O2

1100oC, 1400oC 0.1 - 2.0 MPa

Zeng and Fletcher, 2005 21

44 – 90 µm PFFB at ~105 K/s

1027oC, 1300oC 0.085 – 1.5 MPa

PFFB, PTGA O2

1150oC, 500oC 0.25 – 1.5 MPa

Harris et al., 2006 22

45 – 180 µm WMR at 103 K/s PEFR at ~104 K/s

1100oC, 1500oC 1.5 MPa

PEFR, PTGA H2O, CO2, some O2 in PEFR

800oC, 900oC 1.5 MPa

Roberts and Harris, 2007 23

1000 – 6000 µm Crucibles at 0.17 K/s

1100oC 1 – 5 MPa

PTGA mixed H2O, CO2

850oC, 900oC 1 – 5 MPa

Yang et al., 2007 24

4 atm CO2 Wyodak 2010, < 4 atm CO2 Wyodak 2011, > 4 atm CO2

20

0 0

20

40

60

80

100

Experimental Mass Release (daf wt%, Char Basis)

Figure 6. Fit of PFFB data with 1st-order model using E = 123 kJ/mol and A from correlation with CharAr.

4.2

Comparison of 1st-Order Rate Parameters to Literature Figure 7 shows a comparison of the optimal 1st-order CO2 rate parameters from this study

(see Table 5) to rate parameters obtained using an atmospheric drop-tube furnace. 37 The range of gas temperatures used by Goetz is indicated with vertical lines on the plot. The Goetz particle temperatures were probably slightly lower than the gas temperatures due to endothermic gasification reactions and radiation to cold surfaces such as the collection probe. The transitions from dashed to solid lines in Figure 7 indicate the particle temperature limits predicted by the 1storder model for the PFFB data.

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1

10

Goetz Gas Tempererature Range: 1366-1728 K

0

10 10

2

Rate Constant (gC/cm /s/atmCO2)

10

10 10 10 10 10 10

Wyodak 2010 Wyodak 2011

-1

-2

-3

-4

-5

-6

Texas Lignite, Goetz et al. (1982) Wyoming Subbituminous C, Goetz et al. (1982) Illinois #6, Goetz et al. (1982) Pittsburgh #8, Goetz et al. (1982)

-7

-8

2500 K

2000 K

0.0004

0.0005

1667 K

1429 K

1250 K

1100 K

0.0007

0.0008

0.0009

-9

10 0.0003

0.0006

0.0010

1/Tp 1

10

Goetz Gas Tempererature Range: 1366-1728 K

0

10

2

Rate Constant (gC/cm /s/atmCO2)

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

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-1

10

Illinois #6 Eastern Bituminous Coal A Eastern Bituminous Coal B Kentucky #9

-2

10

-3

10

-4

10

-5

10

Texas Lignite, Goetz et al. (1982) Wyoming Subbituminous C, Goetz et al. (1982) Illinois #6, Goetz et al. (1982) Pittsburgh #8, Goetz et al. (1982)

-6

10

-7

10

-8

10

2500 K

2000 K

0.0004

0.0005

1667 K

1429 K

1250 K

1100 K

0.0007

0.0008

0.0009

-9

10 0.0003

0.0006

0.0010

1/Tp

Figure 7. PFFB 1st-order CO2 gasification rate parameters for Wyodak subbituminous coal (top) and 4 bituminous coals (bottom) compared to rates of Goetz et al. (1982).

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The maximum particle temperature limits of the PFFB data in Figure 7 were similar to the maximum gas temperatures of Goetz et al. (1982), and the minimum particle temperatures where gasification was measured were 100 K to 250 K lower than the lowest Goetz gas temperature. It is noteworthy that the maximum particle temperatures in the PFFB were similar to the maximum Goetz gas temperatures, because heat loss is so pronounced in facilities operating at elevated pressures.38,

39

The higher partial pressures of CO2 used in the PFFB

allowed conversion to be measured at low temperatures compared to the atmospheric data of Goetz. It is important to measure gasification at low temperatures as well as high temperatures to obtain the best possible activation energies and to determine at what temperatures gasification rates become insignificant. The slopes of the lines in Figure 7 represent the apparent activation energies in Zone II. The Goetz activation energies range from 165 kJ/mol (39.5 kcal/mol) for Texas lignite to 236 kJ/mol (56.4 kcal/mol) for Illinois #6. The PFFB activation energies are all lower than those of Goetz et al. (1982) for coals of similar ranks. The low activation energies may be due to the combined effects of the high particle heating rates and elevated pyrolysis pressures on the physical and chemical structures of the char. In terms of the three-zone theory the low activation energies may be indicative of Zone II behavior, where the activation energy is typically half the value measured under intrinsic kinetic conditions (Zone I). Since the Wyodak 2010 parameters include a better fit of a greater number of measurements and higher extents of gasification at high temperatures, the Wyodak 2010 kinetics are more likely to be representative of subbituminous coals compared to Wyodak 2011. The 2010 parameters also predict rate constants that are very consistent with the subbituminous rates 22


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of Goetz et al. (1982) and do not intersect the bituminous rates of Goetz at realistic gasification temperatures. It is thought that differences in the physical structure of chars produce most observed differences in high-temperature reactivity through complex transport effects.19 Since the physical structures of subbituminous chars are unlikely to change much when the heating rate and pyrolysis pressure are changed, it makes sense that the observed rates for subbituminous coal in the PFFB would be similar to those in the atmospheric drop-tube furnace of Goetz et al. (1982). Greater differences would be expected for bituminous coal gasification rates obtained from atmospheric drop-tube furnaces and pressurized flat-flame burners because of the effects of particle heating rate and pressure on the particle size and physical structure of char after pyrolysis. The comparison of the bituminous CO2 gasification rates in the PFFB to those of Goetz et al. (1982) shows that the differences in activation energy can be significant (see Figure 7). The bituminous gasification rates near 1700 K yield the most reasonable trends of reactivity with coal rank since gasification is easier to measure accurately at higher temperatures (see Figure 7). The Eastern Bituminous B (EBB) gasification rates in Figure 7 have almost negligible dependence on particle size and temperature compared to all the other coals. The high carbon content of this coal indicates that it has the highest rank in this suite of coals, and the trends of the Goetz data suggest that it also has the lowest reactivity. It is likely that the sparse EBB data were corrupted by excessive soot contamination at long residence times.8 It is also possible that the measured swelling ratios used in the model were influenced by soot and/or fragmentation in the char collection system before changes were made to eliminate these problems.8 The Kentucky #9 activation energy also appears to be suspiciously low (see Figure 7). However, the Kentucky #9 rate parameters determined from the low-CO2 experiments changed 23


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very little when the 2 reinjection experiments with high CO2 were included, and the fit was reasonable (see Figure 6). The Kentucky #9 data included fewer measurements with heaters compared to the Wyodak and Illinois #6 chars. An inspection of the 1st-order model results suggests that about half of the reinjected Kentucky #9 char conversion occurred at particle temperatures of 1250 K to 1450 K, which corresponds to the middle third of the inverse temperature range in Figure 7. Therefore, the rates should be quite reliable at least in this range. The similarity of the bituminous rates to each other and to the rates of Goetz et al. (1982) suggests high pressure and high heating rates affect CO2 gasification rates most strongly through transport effects relating to the particle size developed during pyrolysis. Char particle size effects were accounted for in the 1st-order model and also in the work of Goetz through use of the experimental swelling ratios. It appears that differences in other morphological features and chemical characteristics of the chars weakly influenced gasification rates under the conditions of this study. 5. CO2 Gasification Data with the CCKN Model The nth-order Char Conversion Kinetics model (CCKN) was used to fit the PFFB gasification data. The partial pressures of CO, H2O, and H2 were neglected in the optimization of rate parameters because CCKN has no CO inhibition mechanism and the concentrations of the other species were low. The pre-exponential factor and activation energy for CO2 gasification were varied to obtain the best fit of the data. When the reaction order was varied, it was found to have a value near 0.5 for most of the chars. Therefore, a reaction order of 0.5 was assigned to all the chars to simplify the parameter optimization and rank correlation.

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The fit of the PFFB data with CCKN shown in Table 7 was better for the EBB coal and the EBA coal than it was in the simple 1st-order model (see Table 5). The fit was also very good for the other coals. The EBB activation energy was lower than the other coals, as in the 1st-order model. The unrealistic activation energies in both models suggest that the EBB data set was not extensive enough in terms of temperature and perhaps CO2 partial pressure for kinetic modeling, and the conversions obtained were low enough to be strongly influenced by experimental noise. It is likely that the kinetic parameters obtained for EBB were biased towards excessively low rates because soot agglomerates collected with the char became larger and more numerous with increasing residence time. Soot contamination was a more severe problem for this high-rank bituminous coal with in-situ pyrolysis than for any other coal in this study. Table 7. CO2 gasification kinetic parameters for the CCKN model Coal Pyrolysis Points fitted

Wyodak 2010 Wyodak 2011 In-situ In-situ 16 7 Parameters with fixed reaction order of n = 0.5 6.616×106 4.327×106 A [s-1 (mol/m3)-n], n=0.5 33.45 36.11 E [kcal/mol], n=0.5 12.6% 24.8% Relative Error (char basis) 988.2 1363.5 SSE (char basis) Coal Pyrolysis Points fitted

Illinois #6 EBA* Reinjection In-situ 8 5 Parameters with fixed reaction order of n = 0.5 7.145×106 2.968×105 A [s-1 (mol/m3)-n], n=0.5 37.53 32.52 E [kcal/mol], n=0.5 4.78% 17.2% Relative Error (char basis) 308.0 45.65 SSE (char basis) *Eastern Bituminous A and B

Kentucky #9 In-situ and reinjection 9 coal + 2 char 6.350×105 33.27 44.6% 281.1 EBB* In-situ 8 8.163×102 12.97 36.1% 181.5

The effectiveness factors that were predicted by CCKN indicate that the PFFB experimental conditions used in this study corresponded to the transition between Zone II and Zone I gasification behavior. The Wyodak 2010 had effectiveness factors below 0.9 at 25


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temperatures as low as 1350 K, indicating Zone II behavior. The effectiveness factors for the bituminous coals were very close to 1 at particle temperatures below 1500 K, indicating Zone I behavior. However, the bituminous coal effectiveness factors decreased at higher temperatures, indicating the onset of Zone II behavior.8 5.1

Correlation of CCKN Model with Coal Rank The two Arrhenius CCKN rate parameters with a fixed CO2 reaction order of 0.5 were

correlated with coal rank in a manner similar to the 1st-order model. An autocorrelation approach used in previous combustion kinetics studies

36, 40

was applied to fit the CO2 gasification data

from coals in the PFFB. The activation energy was first fit to some measure of coal rank or char properties. Next, new optimal pre-exponential factors (differing from those in Table 7) were generated from the experimental data using the correlated values of the activation energy. Finally, the pre-exponential factor was correlated with both the correlated activation energy and coal rank. As in the 1st-order rank correlation, EBB was omitted from the CCKN rank correlations. However, Kentucky #9 was included because it exhibited better trends in the CCKN model (see Figure 8). The CCKN Arrhenius parameters were compared to many measures of coal rank. As with the 1st-order model, the best correlations were found with C/O and CharAr = Mclust Mδ(σ+1). A linear form was used for C/O and a quadratic form was chosen for Mclust -Mδ(σ+1),

as shown in Figure 8.

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40

Activation Energy (kcal/mol)

Activation Energy (kcal/mol)

40

30

20

Selected Coals Omitted Coal Activation Energy Correlation

10

2

4

6

8

10

12

30

20

10

0 120

0 14

Selected Coals Omitted Coal Activation Energy Correlation

140

(a) E with C/O

180

200

220

240

220

240

(b) E with Char Parameter

-2500 3 -n

)

)

-1000

3 -n

Selected Coals Omitted Coal Pre-Exponential Factor Correlation

-1500

Selected Coals Omitted Coal Pre-Exponential Factor Correlation

-2000

-1

-2600

ln(A) - EgTref ln(s [mol/m ]

-1

160

Mclust-Mδ(σ+1)

C/O Mass Ratio

ln(A) - EgTref ln(s [mol/m ]

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Energy & Fuels

-2700

-2800

-2900

-3000 2

4

6

8

10

12

14

-2500

-3000

-3500

-4000 120

140

180

200

Mclust-Mδ(σ+1)

C/O Mass Ratio

(c) A with C/O

160

(d) A with Char Parameter

Figure 8. Correlations of kinetic parameters with coal rank for CCKN gasification model.

The correlations that correspond to Figure 8 are presented in Table 8. The R2 values for the activation energy indicate that the quadratic fit with CharAr = Mclust -Mδ(σ+1) in part b of Figure 8 is much better than the linear C/O fit shown in part a of Figure 8. It appears that the parameter CharAr = Mclust -Mδ(σ+1) yields a more meaningful rank order for gasification reactivity. The R2 values for the pre-exponential factor correlations in Table 8 are essentially

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unity for both measures of coal rank (compare to parts c and d of Figure 8). This result indicates the success of the autocorrelation approach.

Table 8. Coal rank correlations for CO2 gasification parameters in the CCKN model with Tref = 1450 K R2

Correlation

cal mol E ln [ AC / O ] = 95 .776 (C / O ) − 3221 .0 + C / O R g Tref E C / O = − 348 .3(C / O ) + 36482

0.15 1.00

cal mol E Char = 0.21101 Char Ar2 − 70 .876 Char Ar + 2924 .0 + R g Tref

E Char = − 1.622 Char Ar2 + 573 .0Char Ar − 13988 Ar

[

ln AChar

Ar

]

Ar

0.61 1.00

The CCKN fit with the CharAr correlation is shown in Figure 9. The correlation increased the predicted conversion for most of the coals with respect to the optimal parameters in Table 7. The CharAr correlation yielded lower conversion for Illinois #6 and EBB (EBB was excluded from the correlation). The overall fit using the CharAr correlation is very good, and the fit of the Illinois #6 data in particular is much better than the best correlation with the 1st-order model (see Figure 6). It appears that the use of a model with a reaction order of 0.5 and advanced features such as effectiveness factors made better correlations with coal rank possible compared to the 1storder model.

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Model Mass Release (daf wt%, Char Basis)

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100 Illinois #6 re-injection, > 4 atm CO2 Eastern Bituminous A,< 4 atm CO2 Eastern Bituminous B, < 4 atm CO2 Kentucky #9, mostly < 4 atm CO2, with 2 re-injection experiments, > 4 atm CO2

80

60

40

20

Wyodak 2010, < 4 atm CO2 Wyodak 2011, > 4 atm CO2

0 0

20

40

60

80

100

Experimental Mass Release (daf wt%, Char Basis) Figure 9. Parity plot of PFFB CO2 gasification data with CCKN predictions using CharAr kinetic correlation.

6. CO2 Gasification Data with the CCK Model The CCK model was used to fit the PFFB gasification data using the same procedures that were used with the CCKN model. The partial pressures of CO, H2O, and H2 from the reaction zone in PFFB were included in the CCK inputs for each case. A parametric study was conducted with the two best data sets (Wyodak 2010 and Illinois #6) to understand the sensitivity of the model outputs to the user-defined parameters.8 It was found that adjusting the activation energy and the pre-exponential factor together did not significantly improve the fit of the two best data sets. Therefore, only the pre-exponential factor A7,0 was adjusted for the scaling reaction in this study.8 The activation energy E7 for the scaling reaction was assigned a value of 35 kcal/mol for

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all coals. Additionally, it was found that the extent of gasification predicted by CCK was not strongly affected by CO at the concentrations and temperatures found in the PFFB. In the attempts to fit the PFFB data using both of the CCK models, a slight skew was observed, wherein char conversions below 50% were over-predicted and higher char conversions were under-predicted (see Figure 9). The CBK sub-models that reduce oxidation rates with increasing conversion appear to cause excessive reductions in gasification rates when applied to the experimental conditions in this study. Sensitivities of the fit to model parameters were studied and are documented elsewhere.8 The parameters studied include the random pore model, the mode of conversion, and a pore structural parameter. The random pore model was added to CBK/G to facilitate modeling large particles,30 and appears to be unnecessary to model these entrained-flow gasification conditions. The mode of conversion specifies whether char is consumed at the external surface, the interior surfaces, or some combination of the two. The pore structural parameter is used in the calculation of the effective diffusivity of reactants through the porous char. It was found that the extent of gasification was not highly sensitive to the mode-ofburning parameter α or to the random pore model, which is controlled by ψ0. The shape of the gasification versus residence time profile appeared to be more sensitive to the pore structural parameter τ/f, which could be increased within reasonable limits to improve the consistency of the fit to the PFFB data over a wider range of conversion. This suggests that tortuosity and pore structure may be different for the PFFB chars compared to what the CBK default values of τ/f would suggest, or Knudsen diffusion (which was neglected in CCK and CCKN) may make a significant contribution to CO2 gasification rates. There is evidence that Knudsen diffusion may be more important for gasification26 compared to combustion 41 because the reactions are slower, 30


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which ought to allow reactants to penetrate deeper into the micropores. However, the effect of τ/f on the overall fit was not large enough to justify the use of τ/f as an adjustable parameter for the purposes of this study, so the CBK/E29 default value of 12 was used for CCK and the CBK831 default value of 6 was used for CCKN. If reactants penetrate far enough into the micropores, Knudsen diffusion reduces the pressure dependence of the combined diffusivity,8 as illustrated in Figure 10. Optimized fits of the Illinois #6 and Wyodak data in CCK with adjustable τ/f suggest that at most the combined diffusivity may be reduced to ~10% of the molecular diffusivity for the bituminous coal and 1% of molecular diffusivity for the subbituminous coal.8 At pressures of 10 atm to 15 atm used in PFFB, the combined diffusivity reaches a value equal to 10% of the molecular diffusivity in pores having diameters of ~10 nm (see Figure 10). The combined diffusivities would be equal to 1% of the molecular diffusivity in pores with diameters of ~5 nm. Measurements of the CO2 surface areas for Illinois #6, Kentucky #9, and Wyodak chars created in the PFFB indicate that the micropore diameters are all about 1.15 nm,8 which is easily small enough to account for the increase in τ/f by 1 to 2 orders of magnitude compared to its default value that was derived for combustion.31

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2

1.0 60 atm 30 atm 15 atm 10 atm 5 atm 1 atm

0.8

2

Diffusivity Ratio DCO ,comb/DCO

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

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0.6

0.4

0.2

0.0 0

20

40

60

80

100

120

140

Pore Diameter (nm) Figure 10. Combined diffusivity compared to molecular diffusivity as a function of pore diameter and pressure.

The optimal fit with CCKN (Table 7) appears to be slightly better than CCK (Table 9), especially for Kentucky #9 and Eastern Bituminous B (EBB), which were the two least reactive coals. This is most likely due to the fact that 2 rate parameters were adjusted in an empirical nthorder mechanism compared to 1 parameter in CCK. The CCK model fit the Wyodak 2010 series slightly better than CCKN. The poor fit of EBB with the most mechanistically advanced model used in this study is consistent with the other models and provides further evidence for the low quality of the EBB data compared to the other coal chars. Table 9. Optimized CO2 gasification A7,0 with the CCK model using E7 = 35 kcal/mol, ψ0 = 0, and τ/f = 12 Coal Pyrolysis Points fitted Fitted A7,0 (s-1) Relative Error (char basis) SSE (char basis)

Wyodak 2010 In-situ 16 8.659×108 13.8% 961.5

Wyodak 2011 In-situ 7 3.462×108 25.2% 1547.1

Kentucky #9 In-situ and reinjection 9 coal + 2 char 1.200×108 54.1% 491.1

Coal Pyrolysis Points fitted

EBA* In-situ 5

EBB* In-situ 8

Illinois #6 Reinjection 8

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6.488×107 6.914×107 Fitted A7,0 (s-1) 20.5% 69.2% Relative Error (char basis) 48.0 563.2 SSE (char basis) *Eastern Bituminous A and B

6.1

3.943×108 5.53% 435.4

Correlation of CCK Model with Coal Rank The kinetic parameter A7,0 was compared to various measures of chemical structure for

the same coals that were correlated with CCKN. As with the 1st-order model and CCKN, the best correlation for CCK was found with C/O and the char structural parameter CharAr = Mclust Mδ(σ+1). A quadratic correlation with CharAr was found to yield a fit that was more consistent

with the higher-quality Illinois #6 data (compare parts b and c of Figure 11). The correlations for the rate parameter A7,0 are presented in Table 10. The high R2 values indicate that the more advanced mechanism and the single adjusted parameter used in CCK allowed for a good correlation with rank. The CCK fit of the PFFB data with the recommended correlation #3 in Table 10 is shown in Figure 12.

22

22 Selected Coals Omitted Coal Correlation

20

ln(A7,0 )

ln(A7,0 )

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Energy & Fuels

18

16 2

4

6

8

10

12

14

20

Selected Coals Omitted Coal Correlation

18

16 120

140

160

180

200

220

240

Mclust-Mδ(σ+1)

C/O (a) Linear A7.0 with C/O

(b) Linear A7.0 with Char Parameter

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22

ln(A7,0 )

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

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20

Selected Coals Omitted Coal Correlation

18

16 120

140

160

180

200

220

240

Mclust-Mδ(σ+1) (c) Quadratic A7.0 with Char Parameter Figure 11. Correlations of kinetic parameter A7,0 with coal composition and NMR parameters.

Table 10. Correlations for A7,0 with coal rank for CO2 gasification with the CCK model Correlation

1. 2. 3.

ln [A 7 , 0 ] = − 3672 (C / O ) + 21 .33

ln[A7, 0 ] = −0.02500CharAr + 24.08

ln[A7 , 0 ] = −0.0002863Char + 0.07652CharAr + 15.44 2 Ar

R2 0.71 0.79 0.87

Of the three models, the CCKN rank correlations with the CharAr = Mclust -Mδ(σ+1) parameter appear to yield the best overall predictions of CO2-char reactivities when compared to the PFFB data. However, when the correlations from all three models are compared with respect to the optimal fits for the same model (i.e., Table 5 for the 1st-order model, Table 7 for CCKN, and Table 9 for CCK), the CharAr rank correlation reproduced the optimal kinetic parameters most accurately for the CCK model.8 Revision of the rank correlations from CBK/G

30

through 34


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optimization with highly detailed gasification data would probably allow CCK to yield rank correlations superior to CCKN. However, it is also possible that the chars produced at ~105 K/s in the PFFB have different reactivities compared to the chars used to produce the CBK/G rank correlations.

Model Mass Release (daf wt%, Char Basis)

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

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100 Illinois #6 re-injection, > 4 atm CO2 Eastern Bituminous A,< 4 atm CO2 Eastern Bituminous B, < 4 atm CO2 Kentucky #9, mostly < 4 atm CO2, with 2 re-injection experiments, > 4 atm CO2

80

60

40

Wyodak 2010, < 4 atm CO2 Wyodak 2011, > 4 atm CO2

20

0 0

20

40

60

80

100

Experimental Mass Release (daf wt%, Char Basis)

Figure 12. Parity plot of PFFB gasification data with CCK predictions from quadratic CharAr kinetic correlation.

7. Summary and Conclusions CO2 gasification measurements were performed for 4 bituminous coals and 2 varieties of a subbituminous coal at pressures of up to 15 atm with maximum particle heating rates of ~105 K/s. A reinjection strategy was found to be the most effective way to obtain good bituminous coal gasification kinetics at high temperatures without the influence of soot contamination. 35


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However, in-situ pyrolysis was found to be a successful strategy for subbituminous coals. Three models were developed and implemented to help interpret the data. A simple 1storder model was used to obtain a reasonable fit of most of the data. The 1st-order activation energies were lower than previously reported values. The lower activation energies suggest Zone II behavior prevailed in the PFFB. This may indicate that the observed reaction rates were influenced by the physical structure of the chars that were developed during pyrolysis at high heating rates and elevated pressures. The high extent of overlap in the 1st-order rate constants from this study with previously reported rate constants suggests that the strongest effect of high pressures and heating rates on gasification rates occurs as a result of the particle diameter developed during pyrolysis, at least for the particle temperatures that occurred in this study. The two advanced gasification models were based on the CBK oxidation and gasification models. The fit of the data with the advanced models was generally quite good. Fits of the data with CCK and CCKN were mostly comparable to each other. A very low activation energy was obtained using the 1st-order model for the Eastern Bituminous B (EBB) coal compared to the other coals. The fit of this coal was very poor in the most mechanistic model (CCK). The best-fit activation energy in CCKN was also unrealistically low for EBB. These results suggest that either this high-rank coal did not reach high enough temperatures and residence times to yield data appropriate for kinetic analysis, or else the soot contamination was severe enough to interfere with mass release measurements. The Kentucky #9 also had a low activation energy in the 1st-order model, but the rate parameters were reasonable in the other two models. The PFFB gasification data were found to yield rates far below the film-diffusion limit for the temperatures and pressures studied here. There were indications of the influence of both 36


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Energy & Fuels

intrinsic kinetics and diffusion through pores on the overall rate. There were indications that Knudsen diffusion may make significant contributions to the observed rate. The CCK model predicted that the concentrations of CO present in the PFFB should have little impact on the observed rates at the temperatures and residence times typical in this study. Correlations of kinetic parameters with coal rank were made for all three models. Reactivities generally decreased with increasing rank. C/O in the coal and the NMR parameter group Mclust -Mδ(σ+1) were used as indices of rank. Mclust -Mδ(σ+1) represents an estimate of the aromatic cluster mass in the char, and yielded better reactivity correlations than the more traditional C/O in all cases. The performance of C/O as a reactivity rank index was least comparable to Mclust -Mδ(σ+1) with the simple 1st-order model. Rank correlations for the CCKN kinetic parameters yielded the best overall fits of the PFFB data. However, the CCK rank correlations yielded predicted gasification rates that were more consistent with the optimal fit for the same model. Therefore, optimization of additional parameters in CCK would likely yield rank correlations superior to CCKN. The superior performance of the Mclust -Mδ(σ+1) index over the C/O ratio for gasification rate correlations has two related explanations. First, the accessibility of carbon atoms to gasification reactants in the char has a more direct mechanistic link to the gasification rate than the elemental composition of the parent coal. Carbon accessibility is closely related to aromatic cluster size, which is what the Mclust -Mδ(σ+1) index was designed to represent. Second, the Mclust -Mδ(σ+1) index has more information embedded in it because the method used to predict

the constituent NMR parameters in this index utilizes 4 measured coal properties rather than the 2 properties used in the C/O index. 37


Energy & Fuels

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Acknowledgments This material is based upon work supported by the Department of Energy under Award Number DE-NT0005015. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof. The assistance of Joseph W. Hogge, Kade C. Fowers, Gregory S. Sorensen, and Samuel S. Goodrich in upgrading the PFFB and conducting the gasification experiments is gratefully acknowledged.

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Coal Char-CO2 Gasification Measurements and Modeling in a

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