42
Energy & Fuels 1989,3, 42-55
particles. We can estimate this outer surface area by assuming a hard spherical model of a particle, having a certain particle size and density. The average particle sizes of the coals and macerals used in these experiments were between 1and 2 Mm in diameter, which yield outer surface areas for the hard sphere model of 2-5 m2/g, depending on the maceral type. The average particle sizes of the fractions are almost the same for each maceral group.22 Comparison of these surface areas with those in Table VI11 suggests that the actual surface areas are much larger than the calculated hard spherical surface areas.
Summary The results of this study show that the macerals bind surfactants in solution with a Langmuir-like adsorption isotherm. However, this behavior cannot always be strictly defined in the same sense as a Langmuir analysis, due to
problems of irreversible adsorption on the maceral particles and an overlap of adsorption into the critical micelle region of some surfactants. In all cases that were examined, the macerals showed only moderate selectivity for any single surfactant. Generally, the selectivities fall within a factor of 2, and in all cases at least two of the three macerals groups have nearly the same adsorption. In the case of DTAC, more surfactant is bound than expected for smooth, nonporous particles. This may be due to multilayer adsorption or adsorption into pores or both.
Acknowledgment. The assistance of A. G. Kostka and A. Svirmickas with the NMR experiments is gratefully acknowledged, as well as the help from Dr. L. Kaplan of Argonne National Laboratory with the syntheses of the radiolabeled compounds used in this study. Registry No. DTAC, 112-00-5; Brij-35, 9002-92-0; CPYC, 123-03-5.
(22) Dyrkacz, G.R.; Leboulec, K. Unpublished results.
Pyrolysis of Argonne Premium Coals: Activation Energy Distributions and Related Chemistry Alan K. Burnham,* Myongsook S. Oh, and Richard W. Crawford Lawrence Livermore National Laboratory, Livermore, California 94550
Alain M. Samoun Lab Instruments, Kenwood, California 95452 Received July 11, 1988. Revised Manuscript Received October 6, 1988
We report pyrolysis yields and kinetics at heating rates of several degrees Celsius per minute measured by modified Rock-Eva1 pyrolysis and by pyrolysis interfaced to triple-quadrupole mass spectrometry (TQMS). Pyrolysis temperatures from pyrolysis-TQMS were consistent with those from Rock-Eva1 considering that compounds less than about C8only were monitored by the TQMS. Rate data at three heating rates from the Rock-Eval apparatus were analyzed by using Gaussian and discrete activation energy distribution models. Although T,, increases with coal rank, the average activation energy is lower for high-volatile bituminous coals than for lower or higher rank coals. The activation energy distribution became substantially narrower as carbon content increased and oxygen content decreased. The evolution profile of most compounds measured by TQMS indicated the presence of activation energy distributions, multiple generation processes, or both. A Gaussian distribution is usually only a fair approximation when a distribution in activation energy is required, either for individual compounds or for total hydrocarbons. The TQMS data also showed that T,, for different compounds had different dependencies on coal rank. Methane was relatively constant, but others generally increased with coal rank. The decrease in activation eqergy distribution width with increased coal rank is attributed in part to a convergence of T,, values of different species at high coal rank. Finally, we discuss the validity of a parallel reaction approach for modeling both coal processing and geological maturation.
Introduction It has been known for many years that coal pyrolysis is a complicated process involving several physical and chemical processes that occur in parallel and in series, so it cannot be modeled by a single first-order reaction.lS2 Though models that treat both chemical kinetics and different modes of volatiles transport are a ~ a i l a b l etheir ,~~ (1) Chermin, H.A. G.; van Krevelen, D. W. Fuel 1967, 36, 85-104. (2) Pitt, G.J. Fuel 1962, 41, 267-274. 0887-0624/89/2503-0042$01.50/0
applicability is often limited by the complexity of the model and the knowledge of the coal properties available. Even in the ideal case where transport effects are small, a single reaction cannot account for the diversity of (3) Russel, W. B.; Saville, D. A.; Greene, M. I. AIChE
J. 1979, 25,
65-80.
(4) Unger, P. E.; Suuberg, E. M. Eighteenth Symposium (Interna-
tional)on Combustion; The Combustion Institute: Pittsburgh, PA 1981; pp 1203-1211. (5)Oh, M. S. Softening Coal Pyrolysis. Sc.D. Thesis, Department of
Chemical Engineering, MIT, Cambridge, MA, 1985. 0 1989 American Chemical Society
Pyrolysis of Argonne Premium Coals
ref no. 101 202 301 401 501 601 701 801
Table I. Properties of the Argonne Premium Coal Samoles as-received anal., % seam rank desk. water ash VM Upper Freeport, PA mvb UFMB 1.1 13.0 27.1 WYSB 28.1 6.3 Wyodak, WY subb 32.2 ILHB 8.0 14.3 36.9 Illinois No. 6, IL hvb hvb 1.7 Pittsburgh No. 8, PA PTHB 9.1 37.2 lvb 0.7 4.7 18.5 Pocahontas No. 3, VA PCLB BCHB 4.6 4.5 43.7 Blind Canyon, UT hvb 2.4 19.4 Lewiston-Stockton, WV hvb LSHB 29.4 lig 32.2 6.6 30.5 Beulah-Zap, ND BZL
chemical reactions. A commonly used alternative is a multiple parallel reaction model described by a single frequency factor and a Gaussian distribution of activation energies! The global kinetic parameters from the multiple parallel reaction model can be extrapolated over a wide range of heating rates and are a powerful tool to compare pyrolysis behavior of different coal types. Even so, a wide variation in the kinetic parameters have been reported,&1° so the best kinetic parameters for any particular coal are open to debate. Both Gaussian and discrete activation energy distributions have been used in petroleum geochemistry to predict the geological temperature of oil generation.l1-le While there is no rigorous theoretical justification for such a long extrapolation of pyrolysis kinetics, the empirical evidence indicates that it works quite well.13915 The types of pyrolysis experiments typically used by geochemists are different from those used by coal researchers, and it is instructive to apply an increasingly common geochemical kinetic technique to a set of samples that will be thoroughly examined by coal researchers and to compare the resulting kinetic parameters. In addition, type I11 (terrestrial) kerogens, which include coal, are an important source of natural gas through geological maturation, and chemical kinetics for that process would also be useful to explorers. We measured pyrolysis rates at three heating rates for the Argonne premium coals in a modified Rock-Eva1 I1 apparatus, which detects components up to about C35and has been widely used for measuring kinetics of petroleum source r o ~ k s . ~ ~We J ~analyzed ~' the data by using both Gaussian and discrete distributions of activation energies. We also examined these coals at a single heating rate by pyrolysis-TQMS. A heated condenser trapped products greater than about Clo. This technique provides insights into the nature of the activation energy distributions. Comparing the distributions for coals of different rank (6) Anthony, D. B.; Howard, J. B. AIChE J . 1976,22,625-655. (7) Howard, J. B. In Chemistry of Coal Utilization, 2nd Supplemental Volume; Elliot, M. A., Ed.; Wiley: New York, 1981; pp 665-784. (8) Solomon, P. R.; Hamblen, D. G. Prog. Energy Combust. Sci. 1983, 9, 323-361. (9) Solomon, P. R.; Serio, M. A.; Carangelo, R. M.; Markham, J. R. Fuel 1986,65, 182-194. (10) Solomon, P. R.; Serio, M. A. Evaluation of Coal Pyrolysis Kinetics. Presented at the NATO Workshop on Fundamentals of Physical Chemistry of Pulverized Combustion, Les Arcs, France, July 28-Aug 1, 1986. (11) Tissot, B.; Espitali6, J. Reu. Inst. Fr. Pet. 1975, 30, 743-777. (12) Ungerer, P.; Espitali6, J.; Marquis, F.; Durand, B. In Thermal Modeling in Sedimentary Basins; Burrus, J., Ed.; Editions Technip: Paris, 1986; pp 531-546. (13) Ungerer, P.; Pelet, R. Nature 1987,327, 52-54. (14) Quigley, T. M.; MacKenzie, A. S.; Gray, J. R. In Migration of Hydrocarbons in Sedimentary Basins; Doligez, B., Ed.; Editions Technip: Paris, 1986; pp 649-666. (15) Sweeney, J. J.: Burnham, A. K.; Braun, R. L. AAPG Bull. 1987, 71, 967-985. (16) Burnham, A. K.; Braun, R. L.; Gregg, H. R.; Samoun, A. M. Energy Fuels 1987,1, 452-458. (17) Burnham, A. K.; Braun, R. L.; Samoun, A. M. Org. Geochem., in press.
Energy &Fuels, Vol. 3, No. 1, 1989 43
C 85.5 75.0 77.7 83.2 91.1 80.7 82.6 72.9
daf compn, % H 0 4.7 5.4 5.0 5.3 4.4 5.8 5.3 4.8
7.5 18.0 13.5 8.8 2.5 11.6 9.8 20.3
allows us to explore limitations of multiple parallel reaction models. Although the heating rates of 4-58 "C/min used in these experiments are considered slow to coal pyrolysis and combustion researchers, they are considered rapid to those interested in geological maturation. They provide an excellent reference point for evaluating the validity of extrapolating kinetics over a wide range of temperatures, both higher and lower.
Experimental Section Materials. The Argonne premium coal samples18 were acquired in sealed glass ampules. Reported compositions are given in Table I, ordered according to sample number. We also used a dry Indian Zap lignite sample and poly(l,4-dimethylenenaphthalene) kindly provided by P. Solomon (Advanced Fuel Research). Rock-Eva1 Pyrolysis. The procedure for these measurements has been described in detail p r e v i ~ u s l y . ' ~ Briefly, J~ about 100 mg of specimen is heated in a stainless-steel crucible at rates of 5, 16, and 59 OC/min in a Delsi Instruments Rock-Eva1 I1 instrument. The evolution rate of hydrocarbons (actually, total nonoxidized carbon) is measured by a flame-ionization detector. Temperature is measured by an unsheathed thermocouple touching the bottom of the sample crucible. The furnace temperature profile is nonuniform, so the difference between average sample temperature and the thermocouple temperature depends on sample size. The Argonne coal samples were diluted with an equal amount of 200 "C) 120 77 110 77 89 65 4 0.4 j
I
I
1
I
20
1
BZL
I I
0
i
t70
/-g/g fixed C
75
80
85
2
A-2.9x1016
0 -WYSB
I
0.1
1.1
3.4 8.3 15
II
.-
0.3
PCLB 17.1 40.9 2.0 6.0 2.0
90
1
30
I , , ,
I
I
,
BCHBl
,
-
,
A=2.0x1012
95
Carbon content, wt%
Figure 3. Methane yield normalized to various properties of the coal.
mation in Table I11 with the Rock-Eva1 yields and proximate analysis of the coals gives the global product distribution shown in Figure 2. Considering that information was used from three distinct types of experiments under different heating conditions, the mass closure is very good. Part of the discrepancy is because we have not accounted for H2S,NH3, and N2 in the volatiles (also CO for samples LSHB and UFMB). H2S yield from ILHB is 2 wt % of daf coal.21 The hydrocarbon gas yields in Table I11 show substantially less rank dependence than the oxygen-containing gases. The largest trend was for butane, which showed a maximum for coal WYSB. However, the butane data are the least reliable. Not included is the possible occurrence of absorbed or weakly bound butane evolved below 300 OC, which was detected occasionally but was not reproducible (possibly due partially to residual acetone used in cleaning). Assuming equal amounts of alkenes and alkanes for C3 and C4,the total C2to C4yield increases from 21 mg/g of dry, ash-free (daf) BZL coal to 31 mg/g of WYSB coal and then decreases to 14 mg/g of PCLB coal. Methane yield increases from 24 to 41 mg/g of daf coal, so except for lignite, the yield of C1 to C4 hydrocarbons is nearly constant at about 60 mg/g of daf coal. While CH4 yield per gram of daf coal increases with rank, the yield per gram of organic carbon shows less increase, as shown in Figure 3. The yield of CHI per gram of fixed carbon is more nearly constant but has its highest values for hvb coals. Finally, the fraction of volatile nonoxidized carbon occurring as methane decreases from about 25% for lignite to 10-15% for hvb coals and then increases to about 35% for sample PCLB.
10
*
10
0
A-5.1 x l O1
70 Activation energy, kcal/mol
Figure 4. Discrete activation energy distributions derived from Rock-Eval pyrolysis at 5, 16, and 58 OC/min.
Rate Measurements. The kinetic parameters from the regression analysis of the Rock-Eva1 rate data are summarized in Table IV and Figure 4. The discrete model is a multiple parallel reaction model consisting of a set of
Burnham et al.
46 Energy & Fuels, Vol. 3, No. 1, 1989 Table IV. Kinetic Parameters from Rock-Eva1 Pyrolysis, Ordered Accordine to Coal Rank" approximate anal. nonlinear regression A En U A Ell U samale lig 3.4e18 66 660 6.1 7.le16 61530 6.7 BZL 9.le16 61 580 6.2 1.2e15 55488 6.1 WYSB 1.9e18 66 310 5.3 1.7e17 62760 5.8 ILHB 3.9e12 47 960 3.6 Me13 50180 4.7 1.5e12 47 230 3.0 1.2e12 46860 4.0 BCHB 4.6e12 49 750 2.5 4.0e12 49700 3.6 LSHB PTHB 3.le12 49 380 2.5 2.2e12 48860 3.8 UFMB 1.9e16 63 500 2.3 8.le15 62600 3.1 8.3e17 58390 4.8b 2.9e12 52 570 2.2 4.4e12 53260 3.9 PCLB "A in s-l (le10 = 1 X lolo), Eo in cal/mol, and u in 9i of E@ Parameters for small 1st peak. Zap Indian Head lignite from P. Solomon.
reactions that are spaced at a chosen activation energy interval while sharing a common frequency factor. The weighting factors are constrained to be greater than zero and to add to one, but the distribution can have any shape. The discrete model kinetic parameters are determined by a nested nonlinear-constrained linear regression analysis. Gaussian model parameters were determined by using both a conventional nonlinear least-squares analysis and a simplified "approximate" procedure. In the approximate analysis,%which is extremely rapid and requires minimal information at two or more heating rates, the mean activation energy is determined by linear regression of In (Hr/Tm,,2) = -Eo/RTm,
+ In (AR/Eo)
(1)
The distribution parameter u is then obtained by u = l.l/p3
- 0.66/p3"
+ 2.88~- 1.12
(2)
where p = (52.4/Eo)0~5(AT,/ATo), AT, is the experimental profile width at half-maximum, and AT, is the profile width calculated by using A and Eo from eq 1. Finally, A from eq 1 is modified by using a correlation involving a. The rate parameters from the Gaussian model analysis, both approximate analysis and nonlinear regression, agree reasonably well with those from the discrete model analysis. A comparison of the observed and calculated reaction rates at 16 "C/min is given in Figure 5. The Gaussian activation energy distribution model fits the general width but not the details of the hydrocarbon evolution profile. Two distinct parallel reactions were required for sample UFMB. The parameters in Table 4 are from a local minimum in the residual sum of squares. The lowest minimum had one reaction characterizingthe sharp profile and a second with u equal to 10 kcal/mol. The second reaction produced a very broad peak, which also fitted the high-temperature tail. This minimum was discarded because the reactions occurring before and after the principal generation reactions are completely different, as discussed in the next section. For most coals, the Gaussian underestimates the amount of product at high and low temperatures but overestimates the profile width at halfmaximum rate. A better fit was obtained for sample PCLB by using two reactions, but again one had a very high u and was rejected. A better fit probably could be obtained by using a distribution having more intensity in its wings, such as a Lorentzian. Figure 6 shows the u values determined by the approximate analysis, which decrease more smoothly with coal rank than the nonlinear regression (25) Braun, R. L.; Burnham, A. K. Energy Fuels 1987, I, 153-161.
values because they are not affected by anomalies in the initial and final stages of reaction. The residual sum of squares for the discrete model is typically 5-10 times lower than that for the Gaussian model. This is logical because the discrete model has more free parameters. However, many of the parameters turn out to be zero, as is evident in Figure 4. Figure 4 also shows that a limitation of the Gaussian model is that the distributions are often not symmetic. Although this could be rectified by using a reaction order other than 1 or a Weibull distribution, the discrete distribution offers more insight into the distribution and is reasonably simple to obtain. Though the regression analysis takes a bit longer, using the discrete model requires no more computer time than a Gaussian model because the Gaussian must be split into a series of discrete parallel reactions anyway. Although there is no definite trend of activation energy with rank, it does seem certain that the principal activation energies of the hvb coals are systematically lower than those of either higher or lower rank. Deviations from a smooth relationship may be due to limits on the accuracy of the activation energy values. Values reported were determined from one set of experiments. Ordinarily, replicate measurements give the same activation energy to within 2 kcal/mol, but there are occasional differences of up to 6 kcal/mol. This also may explain the apparent difference between the Argonne (BZL) and Solomon lignite parameters in Table IV. The T, values of the two lignite samples at the various heating rates are very close, and because of the narrow range of heating rates used, only a few degrees shift in the profile at one of the end heating rates can have a large impact on the activation energy.16 The rates of total product and total hydrocarbon evolution determined by pyrolysis-TQMS are shown in Figure 7. The former was determined by subtracting contributions from Ar ( m / z 20, 36, and 40), and the latter by subtracting additional contributions from H20 (m/z 17 and 18),CO and C02 ( m / z 28 and 44) and H2S (m/z 34 X 1.9 to account for H2S fragments at m / z 33 and 32). The ion currents at some of these masses contain hydrocarbon contributions, but this procedure is close enough for our purposes. The low-rank coals show a large difference between total product and total hydrocarbon because of the large amounts of C02and H20 evolved during the early stages of pyrolysis and of CO evolved at higher temperatures. The amount of H 2 0 and C02 evolved decreases markedly with rank as shown in Table 111. For the highrank coals, the largest remaining differences are due to H2S from pyrite decomposition at about 580 "C and carbon oxide evolution at about 700 "C. Rates of C02and H 2 0 generation are shown in Figure 8. Multiple generation reactions are evident. The broad H,O peaks for lignite and subbituminous coals resolve into at least two components for the higher rank coals. Dehydration at 500 "C and above may have contributions from clay minerals. The C02 generation in the 550-600 "C region for sample ILHB and higher rank may be due to decomposition of an iron-rich carbonate. Because of its coincidence with H,S evolution, it may be related to FeS or CaS formation;there is a shoulder in the water peak at the same temperature for many of the coals, which is required for sulfide formation. T, for COz in the 300-500 "C region tends to increase with rank. Likewise, a slight shoulder at 300 "C for sample BCHB gradually becomes more distinct until it is quite prominent for samples UFMB and PCLB at 360 and 427 "C, respectively. Hydrocarbon evolution is coincident with both COP peaks below 500 "C shown in Figure 7, perhaps related to
Pyrolysis of Argonne Premium Coals
Energy &Fuels, Vol. 3, No. 1, 1989 47 I
I
I
I
1
I
I
I
LSHB
I
I
I
I
I
I
I
I
I
I
BCHB
ILHB
I
I
I
I
PTHB
I
1
I
UFMB
I
PCLB
Temperature (C)
Figure 5. Comparison of the Rock-Eval data ( 0 )at 5 "C/min with calculated rates from the discrete (-) and Gaussian (- - -) kinetic
rate parameters.
the decomposition of coal carboxylic acids, salts, or esters. Mass spectra of the entire product from sample UFMB at 355 and 470 "C are shown in Figure 9. Masses characteristic of long chain alkyl groups (mlz 55, 57, 69, 71, 83,85, etc.) and alkylthiophenes (mlz 45,97,105,106, 119, 120) are relatively more abundant in the lower temperature peak. Masses characteristic of alkylbenzenes (mlz 77, 91, 94,115,121) and phenols ( m / z 65,94,107,108,121,122)
are more abundant in the high-temperature peak. Evolution profiles of both aliphatic and alkyl aromatic fragments have two distinct peaks with T,, values of 354 and 471 "C. The first peak is more prominent for the aliphatic fragments and becomes larger with increased mass, for example, increasing from only 5% of the second for mlz 41 to about 65% for mlz 125. These same effects are seen in coal PTHB and to a smaller extent in coal BCHB.
48 Energy & Fuels, Vol. 3, No.1, 1989
Burnham et al.
e7 e4
e5
75
"70
80
1
I
85
90
4 I
95
Carbon content, wt% ash tree
Figure 6. Decrease in the Gaussian distribution parameter, u, with rank. The increase in carbon content corresponds to a
decrease in oxygen content.
100'
300
500
700
900
Temperature, "C
Figure 7. Total product ion current and totalhydrocarbon ion current (totalproduct current minus contributionsfrom H20, CO, N2,C02,v d Ha).The non-hydrocarbon contributions decrease and T ,, increases as rank increases.
Evolution profiles for CO are shown in Figure 10 for all but sample UFMB. A small peak below 500 OC is evident, and it gradually shifts to higher temperature and decreases
in magnitude as coal rank increases. This peak occurs at about the same temperature as both the largest COz peak and the main tar-generating reactions as measured by Rock-Eval pyrolysis. However, most of the CO is evolved at higher temperatures as the carbon content of char increases. Coal ILHB also has a contribution between 700 and 750 "C from char reacting with carbonate COz. Moreover, high-temperature CO profiles may be modified by the water gas shift reaction. Evolution profiles for Hzand methane are shown in Figures 11and 12a for three selected coals. The Hzprofiles for hvb and higher rank are very similar. The Hz profile from subbituminous coal looks similar to that from lignite except that it is shifted about 25 "C higher. The methane profile also shows little rank dependence. Although methane TmB,increases very slightly with rank, a more noteworthy feature is the later start and sharper rise to T- for the higher ranks. The reason for plotting methane rates per gram of fEed carbon and Figure 12b are discussed in the next section. Figure 13 compares the T,, values of methane with those from total light hydrocarbon generation (i.e., gas plus light liquids) in the same pyrolysis-TQMS experiment and the extrapolated tar plus gas T,, from Rock-Eval. At low ranks, the Rock-Eva1 T,, is lower than the MS T,, although not as low as that for H a and COP This suggests that most of the tar generation precedes light liquid evolution for low-rank coals. Because T,, values for COz and HzS are closer to the Rock-Eval T,, it appears that tar generation is more closely associated with breakdown of oxygen and sulfur functionalities while light liquid generation involves breaking stronger bonds. The Rock-Eval and MS T- values tend to converge at high rank as the oxygen content of the coal decreases, both approaching that of methane at high rank. This is due primarily to an increase in the T,, of individual products, as illustrated in Figure 14. A t high rank, an increase in the fraction of product represented by methane may also be an important factor, as noted in Figure 3. Figure 14 provides additional insight into the chemistry of coal pyrolysis. The evolution profiles of aromatic compounds are generally broader than those of aliphatic compounds. Profiles of phenol and benzene are similar, both in width and peak temperature. Profiles of thiophene and methylthiophene are also broad,2l but precede benzene and toluene, typically by 50 "C. More T,, data for individual compounds are given in Table V. In general, the rank dependence of T,, for aliphatic compounds is less than that for other compounds. Because the TQMS experiments were conducted at only one heating rate, we cannot derive unique kinetics. However, we can deduce some properties of the required kinetic expressions. First, it is evident that some individual components, particularly aliphatic hydrocarbons, can be described more closely by a single first-order reaction. For example, ATo for a first-order reaction with A = 1 X 1013 s-l and Eo = 51 kcal/mol is 48 "C, while the observed value for propane from coal PCLB (Figure 14) is about 53 "C. Using eq 2, we estimate that u for propane is about 1.5 kcal/mol. The propane profiles for lower rank coals are wider, indicating that u decreases with rank as expected for a parallel reaction The aromatic evolution profiles for all coals are much wider, indicating the need for substantially larger activation energy distributions. In addition, two distinct generation processes are suggested for benzene from coal BZL, which may also be the cause of the non-first-order shape of the evolution profiles from coals PCLB and BCHB. The high-temperature tail for
Pyrolysis of Argonne Premium Coals
Energy & Fuels, Vol. 3, No. 1, 1989 49 f
300
500
700
300 Temperature, OC
500
7
700
Figure 8. Carbon dioxide and water evolution profiles in order of coal rank. The maximum rate of COz evolution for T < 500 O C ranges from 0.82 (cms/min)/g of daf BZL coal to 0.05 (cm3/min)/g of UFMB coal. Table V. T , compd methane ethane ethene propane butane m/z = 57 acetic acid COz (
