FLASHCHAIN Theory for Rapid Coal Devolatilization Kinetics. 8

Subscriber access provided by University of Newcastle, Australia

Article

FLASHCHAIN# Theory for Rapid Coal Devolatilization Kinetics. 8. Modeling the Release of Sulfur Species from Various Coals Stephen Niksa Energy Fuels, Just Accepted Manuscript • DOI: 10.1021/acs.energyfuels.7b00278 • Publication Date (Web): 07 Apr 2017 Downloaded from http://pubs.acs.org on April 8, 2017

Just Accepted “Just Accepted” manuscripts have been peer-reviewed and accepted for publication. They are posted online prior to technical editing, formatting for publication and author proofing. The American Chemical Society provides “Just Accepted” as a free service to the research community to expedite the dissemination of scientific material as soon as possible after acceptance. “Just Accepted” manuscripts appear in full in PDF format accompanied by an HTML abstract. “Just Accepted” manuscripts have been fully peer reviewed, but should not be considered the official version of record. They are accessible to all readers and citable by the Digital Object Identifier (DOI®). “Just Accepted” is an optional service offered to authors. Therefore, the “Just Accepted” Web site may not include all articles that will be published in the journal. After a manuscript is technically edited and formatted, it will be removed from the “Just Accepted” Web site and published as an ASAP article. Note that technical editing may introduce minor changes to the manuscript text and/or graphics which could affect content, and all legal disclaimers and ethical guidelines that apply to the journal pertain. ACS cannot be held responsible for errors or consequences arising from the use of information contained in these “Just Accepted” manuscripts.

Energy & Fuels is published by the American Chemical Society. 1155 Sixteenth Street N.W., Washington, DC 20036 Published by American Chemical Society. Copyright © American Chemical Society. However, no copyright claim is made to original U.S. Government works, or works produced by employees of any Commonwealth realm Crown government in the course of their duties.

Page 1 of 46

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

FLASHCHAIN Theory for Rapid Coal Devolatilization Kinetics. 8. Modeling the Release of Sulfur Species from Various Coals Stephen Niksa Niksa Energy Associates LLC, 1745 Terrace Drive, Belmont, CA 94002

ABSTRACT

This modeling study expands FLASHCHAIN theory to interpret the release rates and yields of H2S, COS, and SO2 and the sulfur contents of tar and char from any coal, and thereby completes the theoretical framework for the devolatilization of all five major organic elements in any coal. The proposed reaction set accurately interprets a database that represents heating rates from 10 to almost 104°C/s, temperatures to 1500°C, contact times to 7 min, and S-product distributions from 27 different coal samples representing ranks from lignites to anthracites, albeit with persistent uncertainties on the split between tar-S and noncondensable S-products. A single distributedenergy reaction with the same parameters for all coals accurately describes the release of H2S from pyrite during primary devolatilization. Additional kinetic rate data on sulfate decomposition under rapid heating is needed to close the analysis for inorganic S-species. By associating aliphatic and aromatic sulfide S-functional groups with labile bridges and peripheral groups,

ACS Paragon Plus Environment

1

Energy & Fuels

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

Page 2 of 46

FLASHCHAIN’s main reaction sequence for primary devolatilization accurately describes the release of noncondensable S-species with the rate parameters previously specified by the coal constitution submodel for individual coal samples.

A single distributed-energy reaction

accurately describes the release of thiophene-S, although additional datasets for temperatures of 1100°C and hotter with contact times of several seconds are needed to specify the rank dependence for this process. The analysis did not accurately describe the partitioning of SORG between tar-S and noncondensable S-products for most coals, although many reported levels of tar-S are implausibly high. Moreover, none of the available datasets for rapid heating conditions at elevated pressure could be qualified for model validation work, so it remains to be seen if the model-based trends will be validated as more data becomes available.


2

Page 3 of 46

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

Introduction Sulfur in coal is always problematic. In flames and furnaces, nearly all of it oxidizes into SO2, which must be eliminated by scrubbing or capture on sorbents before the flue gases pass through smokestacks. In gasifiers, coal-S partitions into several species that must be removed before they can poison catalysts in downstream syngas reforming processes. Sulfides in molten mineral deposits around burners and fuel injectors often promote corrosion on steam tubes and metallic reactor components. Despite numerous technologies to remove coal-S prior to utilization, all coals fed into commercial utilization technologies contain enough sulfur to warrant expensive gas cleaning operations. Sulfur in coal is distinctive because it appears both within minerals and as functional groups in the organic coal matrix. The mineral associations are predominately pyrite, with minor contributions from the sulfates of calcium, iron, and other cations. The organic associations are broadly classified as aliphatics (mercaptans, thiols, and aliphatic sulfides) and aromatics (aromatic sulfides and thiophenes), and these two groups comprise organic-S (SORG). Total sulfur is the sum of pyritic-S (SPYR), sulfate-S (SSO4), and SORG. The important caveat is that many coals from India, Australia, and elsewhere contain no pyrite at all, because siderite, FeCO3, is their predominant Fe-mineral. Also, brown coals and lignites often have no pyrite because their iron is atomically dispersed throughout the coal matrix. In these coals most coal-S is bound into the organic macromolecular structure, except for small contributions from SSO4. It is impossible to understand the release of volatile S-species and, especially, the retention of coal-S in char without a footing in the distribution of total-S among the different forms, because SORG decomposition is affected by coal quality whereas SPYR decomposition is essentially the same in any coal. Consequently, the proportions of SORG and SPYR are much more important than coal


3

Energy & Fuels

0.8 0.7 0.6

Sulfur Fraction in Char

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

Page 4 of 46

0.5 0.4 0.3 0.2 0.1 0.0 60

65

70

75

80

85

90

95

Carbon Content, daf wt.%

Figure 1. (Points) Measured and (line segments) simulated sulfur fractions in the ultimate chars from primary devolatilization in various reactor types at atmospheric pressure. rank, per se. One important practical implication of the different forms of coal-S appears in Fig. 1, which shows the fractions of coal-S retained in diverse chars after rapid heating to temperatures that achieved ultimate devolatilization yields. The other four major organic elements in coal exhibit distinct tendencies in their devolatilization behavior across the rank spectrum1-3, albeit with substantial sample-to-sample variability. But the retention of sulfur in char does not exhibit any apparent rank dependence, since the sample-to-sample variability is as great as the shift toward greater S-fractions in char for the low volatility coals (%C > 85 daf wt. %). Consequently sulfur retention reflects one or more processes in common with the other organic elements as well as the conversion of pyrite, FeS2, into troilite, FeS. Since pyrite levels in coals are mostly uncorrelated with coal rank and are often larger than the levels of SORG, the variations in char-S levels are also uncorrelated with rank, and with the retention of the four other major elements.


4

Page 5 of 46

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

Moreover, SPYR levels are almost always determined by the intensity of coal cleaning, so the only legitimate rank dependence in desulfurization is in SORG conversion, which reflects less aliphaticS and more thiophene-S in coals of progressively higher rank, albeit with large variations among different samples. The mechanism in this paper was developed to accurately predict the rates and distributions of volatile S-species from the devolatilization of any coal under rapid heating conditions, as occurs in all coal utilization technologies that entrain coal suspensions into hot reaction chambers. Despite the broad technological applications, this focus excludes two major portions of the reported knowledge base. First, the vast majority of tests on coal-S release characterized thermal desulfurization at temperatures cooler than 600°C with heating rates slow enough to sustain secondary tar decomposition within particles, and usually with contact times of at least an hour. Gaseous S2 and H2S released from pyrite and aliphatic S-forms can be re-incorporated into char as additional thiophene-S, provided that the heating rate is slow. In addition, tar-S and char-S levels will be distorted by tar deposition within char, given sufficient reaction time for volatiles before they escape the fuel particle. These complications are omitted by restricting the analysis to heating rates faster than about 1°C/s, like several other aspects of FLASHCHAIN theory. The bulk of the available kinetic analyses are also not pertinent because they do not reference any coal constitution submodel and, therefore, have no means to predict S-release from any set of coal properties, or to depict the distinctive behavior of individual coal samples. Among the three network depolymerization models that contain constitution submodels, neither CPD4 nor previous versions of FLASHCHAIN5 contain any sulfur forms in their coal constitution submodels. FG-DVC6 includes separate reactions for the production of H2S and COS from


5

Energy & Fuels

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

Page 6 of 46

different forms of coal-S. But this analysis incorporates measured values for the ultimate H2S and COS yields from particular coal samples under standardized test conditions, instead of measured distributions of the sulfur forms in each particular coal sample. This modeling study expands FLASHCHAIN theory to interpret the release rates and yields of H2S, COS, and SO2 and the sulfur contents of tar and char from any coal, and thereby completes the framework for the devolatilization of all five major organic elements in any coal. The release mechanisms for SORG are independent of those for SPYR and SSO4, but fully connected to the predominant depolymerization chemistry of the organic coal mass. Consequently, only one distributed-energy rate constant was added for the process that ruptures rings to release thiophene-S once tar production winds down, and another for the decomposition of SPYR and SSO4 in parallel. In principle, the analysis requires only the proximate and ultimate analyses and a S-distribution to predict the release of coal-S from any coal under any conditions, provided that heating rates are not slow. However, in practice, data sufficient to specify proportions of aliphatic and aromatic forms of SORG are also required, as explained below. The proposed reaction set accurately interprets a database that represents heating rates from 10 to almost 104°C/s, temperatures to 1500°C, contact times to 7 min, and S-product distributions from 27 different coal samples representing ranks from lignites to anthracites, albeit with persistent uncertainties on the split between tar-S and noncondensable S-products. Extensions to the Theory As explained elsewhere in more detail7, FLASHCHAIN represents coals’ cross-linked macromolecular structure as a mixture of chain fragments ranging in size from a monomer to the nominally infinite chain. The diverse assortment of structural components in real coals is


6

Page 7 of 46

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

rendered coarsely with four structural components: aromatic nuclei (A), labile bridges (B), char links (C), and peripheral groups (S). Aromatic nuclei are refractory units having the characteristics of the hypothetical aromatic cluster inferred from 13C NMR spectra. Except for HCN production from their nitrogen and H2S production from thiophene-S, nuclei are immutable. Nuclei are interconnected by two types of linkages: labile bridges and char links. Labile bridges represent groups of aliphatic, alicyclic, and heteroatomic functionalities, not distinct chemical bonds. They contain all the oxygen, aliphatic carbon and hydrogen, and all aliphatic-S, mercaptans, and aromatic sulfides, but no aromatic components other than aromatic sulfides. Peripheral groups are the remnants of broken bridges on fragment ends that have the same composition. Being refractory, char links initially present in coal are completely aromatic with no heteroatoms. Labile bridges that decompose into char links during devolatilization leave a fraction of their oxygen in the new link, which is subsequently released as CO on a longer time scale, but none of the sulfur. Throughout devolatilization, fragments in the condensed phase disintegrate as bridges break and reintegrate as char links form, so that the amount of tar precursors, called metaplast, passes through a maximum that depends on coal quality. Fragment statistics incorporate the chemical kinetic rates of bridge conversion and of bimolecular recombination of fragments to describe the changing fragment size distributions. Tar production rates are related to metaplast concentrations with the flash distillation analogy8, in which a phase equilibrium relates the instantaneous mole fractions of like fragments in the tar vapor and condensed phase. No finiterate mass transport phenomena are involved because all volatiles escape in a convective flow driven by the chemical production rate of noncondensable gases, which restricts the analysis to sizes smaller than about 1 cm.


7

Energy & Fuels

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

Page 8 of 46

In the model’s main four-step reaction mechanism, labile bridges are the key reaction centers. Bridge conversions in FLASHCHAIN are complex chemical processes involving numerous steps and species, not unimolecular scissions. However, a single distributed-energy rate expression represents the temperature dependence of bridge conversion. Conversion of a bridge initiates two distinct reaction pathways: Scission generates smaller fragments, including precursors to tar, with peripheral groups on their new ends. Spontaneous charring forms a new char link accompanied by the immediate release of noncondensable gases. The pathway to char links depletes the bridge population without inducing fragmentation, thereby suppressing the production of tar precursors. Oxygen in bridges shifts the selectivity between scission and spontaneous charring toward char link production, consistent with the observed connections between crosslinking and the release of CO2 and H2O9. As an analog to crosslinking, additional char links and gases may also form by bimolecular recombination between the ends of metaplast fragments. To keep adjustable parameters to a minimum and eliminate all laboratory support requirements, FLASHCHAIN contains an accounting system that tracks the release of heteroatoms to predict the yields of individual noncondensable gases. As seen in earlier analyses for release of coal-N2 and coal-O3, the analysis proceeds through the following sequence of steps: (1)

Allocate the organic portion of a subject heteroatom among nuclei, labile bridges,

peripheral groups, and/or char links in the parent coal. (2)

Propose reactions to describe the release of individual noncondensable gases via bridge

conversion, peripheral group elimination, and bimolecular recombination.


8

Page 9 of 46

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

(3)

Propose separate reactions for gas release after bridge conversion is complete, including

partial decomposition of aromatic nuclei. (4)

Formulate species conservation laws that combine the contributions from all proposed

reactions with tar shuttling to predict the yields of individual gases, as well as the heteroatom concentrations in tar and char. (5)

If necessary, separately describe the release of any portions of the heteroatom from

inorganic compounds. This approach directly couples the release of noncondensables to the gross disintegration of the macromolecular structure that produces tar, for consistency with very similar features in the dynamic release patterns for tar and most major noncondensable products3. This consistency also means that the same rate constants that describe the macromolecular disintegration also describe major portions of gas production, including H2S and COS production. The partitioning of coal-S is the most complex among the five major coal elements because coalS is dispersed among bridges (sulfides, thiols, sulfoxides), aromatic nuclei (thiophenes), and inorganics (pyrite and sulfates). Consequently, mechanisms for S-release coalesce all the conversion channels for oxygen and nitrogen, and add independent submodels for pyrite and sulfate decomposition. Coal-S is first distributed into SPYR, SSO4, and SORG, either by the conventional analysis for sulfur forms in coal, or with the correlations presented below in eq. 1. SORG is then further resolved into aliphatic forms (Sal), aromatic sulfides (Sar), and thiophenes (Sth), to account for the grossly different thermal behavior of these three functional forms: When subjected to uniform thermal histories with a rapid heating rate10, Sal decomposes between 400 and 750°C; Sar decomposes from 700 to 900°C; and Sth starts to decompose at 900°C but may


9

Energy & Fuels

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

Page 10 of 46

not be fully converted until 1500°C or hotter. Since their thermal responses overlap, Sal and Sar are both associated with labile bridges. And since sulfides are among the most reactive functional groups in any coal, spontaneous bridge condensation expels all the associated sulfur, so that neither Sal nor Sar ever appears in char links. Bridge scissions transfer Sal and Sar into peripheral groups, which subsequently decompose into noncondensable gases. The distinctive thermal responses of Sal and Sar are depicted by associating Sal with the portion of the energy distribution for bridge conversion whose energies are lower than some threshold, Eal; Sar species decompose with energies greater than Eal. Fixed proportions of Sal and Sar are converted into H2S and COS during char link formation and peripheral group elimination via both direct destruction and bimolecular recombination. In this way the overall bridge condensation rate governs part of the release of both Sal and Sar, and rates of peripheral group elimination govern the rest. No new reactions or rate constants are needed. Since Sth appears in condensed aromatic ring structures, it is associated with aromatic nuclei. By analogy with the release of pyridinic- and pyrrolic-N, Sth is expelled in a new distributed-energy reaction that produces only H2S. All three forms of SORG are also shuttled away in intact labile bridges, peripheral groups, and nuclei in tar fragments, which determines the fractions of SORG in tar. The sulfur in all remaining intact bridges and peripheral groups and unconverted aromatic nuclei in fragments within the condensed char phase determine the residual SORG in char. Being inorganic species, both SPYR and SSO4 are not bound into any of the organic coal components. So SSO4 directly decomposes into SO2, although this process is rarely monitored during testing because most coals contain so little SSO4 to begin with. In the mechanism, SSO4 decomposes into SO2 at a rate associated with the pyrite decomposition rate, pending rate data that can specify a dedicated rate expression for SSO4.


10

Page 11 of 46

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

Pyrite appears in coal as both mineral inclusions within the macromolecular matrix and as extraneous mineral grains. During primary devolatilization, this distinction is inconsequential provided that the local atmosphere is reducing with an abundance of hydrogen. Pyrite thermal decomposition moves through several intermediate mineral phases, many of which have variable compositions that are strongly affected by the concentrations of species in the gas phase. Under inert and highly reducing conditions, the major condensed mineral forms are pyrite (FeS2), pyrrhotite (FeSX), troilite (FeS), and metallic iron (Fe). A phase equilibria comes into play in the conversion of pyrrhotite to troilite, but the other steps are irreversible. Pyrite decomposes into pyrrhotite, a sulfide intermediate whose composition depends on temperature, the partial pressure of S2 gas, and, to a lesser extent, pressure11. Pyrrhotite’s variable composition reflects the incongruent melting of FeS2 at 743°C into FeSX and a sulfur-rich liquid phase. Given sufficient time under an S-deficient vapor phase, the pyrrhotite will eventually become troilite. If temperatures are progressively increased under an inert atmosphere, pyrrhotite/troilite will be reduced to metallic iron, as was observed at 1700°C12 and at 1800°C13. The accumulation of S2 vapor can inhibit or reverse the decompositions of pyrrhotite and troilite, whereas H2S is not nearly as effective. So the presence of H-atoms is important, because they convert S2 into H2S. Hydrogen-atoms are generated during the production of light gaseous hydrocarbons (GHCs) during primary devolatilization, and volatile matter does promote pyrite decomposition. In tests with slow heating rates, extents of desulfurization were lower (1) from pure FeS2 than from FeS2 in coal under the same test conditions14,15; (2) from FeS2-enriched specific gravity cuts than from the pyrite in raw coal fractions16,17; (3) from mixtures of pyrite and char than from mixtures of pyrite and volatile hydrocarbon solids13; and (4) when the FeS2enriched fractions were not blended with raw coal fractions18. Moreover, pyrite decomposition


11

Energy & Fuels

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

Page 12 of 46

temperatures were lower by 100°C in whole coals than for pure pyrite19,20. Perhaps the most relevant results from the slow heating literature for commercial applications are those that characterize the impact of elevated pressures. Raising the pressure of an inert atmosphere inhibits sulfur release during pyrite decomposition19,20. Whereas FeS2 was completely transformed into FeS at 950°C under N2 at atmospheric pressure, it progressed no further than FeS1.34 at the same temperature under 3 MPa. The most informative tests with rapid heating rates were reported by McLennan et al.21, who operated their entrained-flow reactor (EFR) at stoichiometric ratios (SR) of 0.6 and 1.5 at 1300, 1450, and 1600°C with residence times between 1 and 2s. They observed FeS/FeO eutectics under both oxidizing and reducing conditions, even from extraneous pyrite particles. An external reducing atmosphere sustains the eutectic in extraneous particles, whereas the locally reducing environment surrounding included pyrite particles sustains it in whole coal particles under any ambient conditions. Even for SR-values as low as 0.6, FeS and FeO comprised half the Fe minerals in flyash, and the rest was magnetite. This observation corroborates that very high temperatures are required to completely eliminate all sulfur from pyrite under inert gases, which has been further corroborated by thermodynamic equilibrium calculations21. One of the few test series with rapid heating at elevated pressure monitored S-distributions throughout pyrolysis of a high volatile (hv) bituminous coal in an EFR at 916°C for pressures from 0.7 to 6.1 MPa and residence times from 0.1 to 1.7 s22. Ultimate extents of desulfurization diminished from 45 to 10 % as pressures were increased from 0.7 to 6.1 MPa and, more importantly, SPYR levels increased from 0.1 to 0.3 daf wt. % over this pressure range. Hence, the


12

Page 13 of 46

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

suppression of S-release during pyrite decomposition at elevated pressures seen in slow heating tests has been confirmed for rapid heating conditions as well. These features will be incorporated into the reaction mechanism with a single distributed-energy rate law for the conversion of FeS2 into FeSX and H2S, where the stoichiometry for sulfur in the product is unity for pressures to 0.5 MPa, and increases linearly to 1.8 for progressively higher pressures to 6 MPa. A temperature dependence for this stoichiometry was reported by Hu et al.11, but it gives no sulfur in the condensed phase under inert atmospheres at 0.1 MPa for temperatures beyond 1306°C, which is too cool for application with rapid heating rates. Here, troilite is regarded as the ultimate condensed Fe-species at all temperatures at atmospheric pressure, on the premise that, in any commercial process that imposes very hot temperatures, the nascent char is attacked by either O2 or H2 before troilite can decompose any further. In such systems, troilite oxidation should be regarded as an aspect of char conversion rather than primary devolatilization. Constitution Submodel for Sulfur Reactants Distributions of the three main forms of sulfur in coal are usually reported on a dry basis, which the proposed mechanism accepts as input data. When such analyses are unavailable, the following correlations are recommended:

SORG = 50.3 - 5.02x10 -1 C daf - 4.70x10 -1 H daf - 4.94x10 -1 O daf - 5.90x10 -1 N daf

S PYR =

(1a)

( S PYR ) Strugala 1.777

(1b)

SSO 4 = 0.07

(1c)


13

Energy & Fuels

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

Page 14 of 46

where each sulfur level is in dry wt. %. The correlations are based on two databases, one of 384 sets of coal properties from the Pennsylvania State University Coal Sample Bank (PSOC) and another of 133 sets of properties from numerous worldwide sources from open literature. The correlation for SORG from the PSOC database gave a correlation coefficient (r2) of 0.978 and a std. dev. of 0.30 dry wt. %. The correlation for SPYR is based on the method reported by Strugala et al.23. This regression is satisfactory (r2 = 0.942 with 0.62 std. dev.), provided that the raw estimates are reduced by a factor of 1.777, although the scatter in the values for the literature database is much greater than for the PSOC database, which reflects variations in the test methodology and QA and QC protocols and, perhaps, distinctive regional variations in SPYR levels among the numerous sources of these data. In comparisons of the final forms of the three estimates to the two databases, the estimates for PSOC coals were satisfactory (r2 = 0.943 with 0.35 std. dev.), except for a handful of coals with relatively very high SSO4 levels. However, the statistics for the final estimates for the literature database were not nearly as fine (r2 = 0.531 with 0.67 std. dev.), suggesting that these correlations may not have reached their ultimate form. Once the three major forms of sulfur have been specified, the analysis resolves SORG into contributions on a daf basis for the three functional groups, Sal, Sar, and Sth. Since there are no routine laboratory analyses that can accurately assign the functional groups in SORG in specific coal samples, these fractions can only be estimated from their tendencies with coal rank: The percentage of SORG as thiophene increases from 25 - 30 % for lignites to 100 % for anthracites in rough proportion to C-content, while aliphatic forms diminish from 50 % to zero24. The aromatic sulfides are uniform at about 25 % for most coal types, then fall off for low volatility coals. In turn, these specifications determine average numbers of functional groups per unit coal component from the following definitions:


14

Page 15 of 46

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

ξ al ( 0 ) =

 ρ0 S al  b MW S f al B ( 0 )  A0

  

(2a)

where

f alb = ∫

Eal

0

f B ( E B )dEB

(2b)

B(0) = p(0)F b (0)

(2c)

  ρ0   MW MWC MWB − MWC  MWB   = MWA 1+ pb (0) + ( p(0) − pb (0)) + (1− p(0)) C + pe (0)  MWA MWA MWA  MWA   A0  

(2d)

In these expressions, ξal is the moles of Sal per labile bridge; Sal is the mass of aliphatic sulfur in daf wt. %; B(0) is the initial molar concentration of labile bridges per nucleus; falb is the fraction of bridges whose decomposition energies are Eal or lower; MWS is the molecular weight of sulfur; and ρ0/A0 is the average molecular weight of a coal monomer expressed in terms of the molecular weights of the three main coal components and the probabilities that nuclei are connected to another nucleus (p(0)), and that a particular connection is a labile bridge (pb(0)). The fraction of all intact linkages that are labile bridges is Fb(0). The likelihood that a fragment contains a peripheral group on an end is pe(0). All the probabilities were explicitly defined by Niksa and Kerstein7. The original definitions of the molecular weights for bridges, peripheral groups, and aromatic nuclei must be modified to include only SORG, rather than STOT, in the bridge weight, and to add Sth into the weight of a nucleus. The weights of char links stay the same. Similarly, for Sar, the initial average number per bridge is

ξ ar (0) =

 ρ0  (1 - f ) MW S B (0)  A0 S ar

b al

  

(2e)


15

Energy & Fuels

2.00

1.25

Assigned Values

Sal/Lo-E Bridge Sar/Hi-E Bridge Sth/Nucleus

1.00

1.75

Sal/Lo-E Bridge Sal/Hi-E Bridge Sth/Nucleus

1.50 1.25

0.75

1.00

Heuristic Estimates

0.75

0.50

0.50

0.4

0.4

0.3

0.3

0.2

0.2

0.1

0.1

0.0

0.0

60

65

70

75

80

85

90

60

65

70

C-Content, daf wt.%

75

80

85

S-FG/Component

S-FG/Component

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

Page 16 of 46

90

C-Content, daf wt.%

Figure 2. Assigned moles of () Sal/Lo-energy bridge; () Sar/Hi-energy bridge; and () Sth/nucleus (left panel) based on reported heuristic trends and (right) specified to fit the validation database in this paper. and for Sth, the initial average number per nucleus is

ξ th (0) =

S th MW S

 ρ0   A0

  

(2f)

These three initial assignments are evaluated for the 27 coals in the validation database with two approaches. The left panel shows estimates based on the heuristics that Sal diminishes from 75 % of SORG for coals of progressively higher rank, while Sar is one-quarter of SORG for all but low volatility coals, and Sth is the remainder of SORG. The right panel shows the values assigned to fit the validation database, as explained below. Note the expanded scale on the y-axis in the top half of the right panel. Both estimates give only 1 Sal per five or more bridges, and only 1 Sth per three or more nuclei for the vast majority of coals, so these forms of SORG are too sparse to promote any distinctive conversion dynamics. Whereas the assigned Sal values exhibit the


16

Page 17 of 46

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

heuristic tendency for less Sal in coals of progressively higher rank, the sample-to-sample variability on Sal and Sth is at least as important. The main difference between both estimations is that the fit values for Sar are much larger than those based on heuristics, which directly reflects the assignment for Eal. For all coals, this energy was specified as 213 kJ/mole, which apportions all Sar atoms to no more than 10 % of the available labile bridges and thereby increases the initial values by almost an order of magnitude. In other words, the kinetics for the elimination of Sar are skewed toward the most severe conditions in any thermal history, consistent with the reported relative kinetic responses of Sal and Sar10. The initial molar amounts of the inorganics, SSO4 and SPYR, are given by

S SO 4 ( 0 ) =

S SO 4 MW S

and

FeS 2 ( 0 ) =

S PYR 2 MW S

(3)

These species levels are tracked on a dry basis without any connections to any of the organic sulfur species or coal components. Reaction Set and Rate Equations The analysis for SORG is developed with molar concentrations, Yi, for the three sulfur functional groups, and of H2S and COS. All concentrations are nondimensionalized with the total moles of nuclei in a parent coal, as are the other FLASHCHAIN state variables. For Yal and Yar, the concentrations are restricted to only those bridges that satisfy the restriction on bridge decomposition energies, so that ∞

Yi, B = ξ i ∑ B j ,i

where i = al , ar

j =1

(4a)


17

Energy & Fuels

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

Page 18 of 46

where Bj,i denotes a bridge of type i in a j-mer fragment The summation extends over all fragments in the condensed phase. These forms of sulfur are released whenever a bridge spontaneously decomposes into a char link, according to 1−ν B ) k B B − S i , B (  → ν Hi 2 S H 2 S + (1 - ν Hi 2 S ) COS + C

i = al , ar

where

(R1)

where B-Si,B is a sulfur atom within a labile bridge and C is a char link. No residual sulfur from these reactants persists in the char link. Bridge scission forms two peripheral groups with intact sulfur functional groups but no gases according to kS B kB B − S i,B ν → 2S - Si,S → ν Hi 2S H 2S + (1-ν Hi 2S ) COS i

where i = al, ar

where S is a peripheral group and Si,S equals one-half of Si,B. The rate constants,

(R2) kSi,

for the

elimination of Si,S differ from the overall rate for peripheral group elimination in FLASHCHAIN, which is denoted by kG. This is because the predicted distributions of the major products are insensitive to the parameters in kG, whereas distributions of sulfur products are not. These rate constants are evaluated from the coal specific energy-distributions for bridge conversion and the assigned value of Eal, according to

k

k

al S

ar S

d =− dt

  E al  −  ln exp  ∫0    

d =− dt

  ∞   ln  ∫E exp  −   al 

∫

t

0

∫

t

0

−

AB e

−

AB e

EB RT ( t ')

EB RT ( t ' )

   dt '  f B ( E B ) dE B      

(5a)

   dt '  f B ( E B ) dE B      

(5b)

Both AB and the std. dev., σB, about the mean energy, EB, in fB(EB) have sample-specific values from FLASHCHAIN’s coal constitution submodel1, whereas EB and Eal are fixed for all coals. Restricting the rate constants in eqs. 5a & b to energies lower or greater than Eal ensures that Sal is much more reactive than Sar. Another implication is that the proportions of these functional


18

Page 19 of 46

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

groups vary throughout devolatilization, even though the numbers of these groups per bridge and per peripheral group remain uniform. Sulfur gases are also released whenever the ends of two metaplast fragments recombine into a new char link, provided that the participating ends contain at least one peripheral group. For the situation where peripheral groups are present on both ends, the stoichiometry is kR E M − S i , S + E M − S i , S → ν Hi 2 S H 2 S + (1 - ν Hi 2 S ) COS + C

where

i = al , ar

(R3)

where EM is a metaplast fragment end, two of which recombine into the new char link and release noncondensables, and kR is the rate constant for bimolecular recombination defined previously1. Recombination is most important for hv bituminous coals, and becomes negligible for both lignites and anthracites. Finally, both reactants are shuttled away within the bridges and peripheral groups in tar fragments. Their concentrations, Yi,B and Yi,S, are governed by

dYi,B dt i

i

J*

= −k BYi , B − ξ i ∑

p mb j pm j

j =1

=

pmb j pm j

( j − 1)Γ j

where i = al, ar

and Yi , B (0) = ξ i f i b B(0) (6a)

Yi , B ∞

∑ ( j − 1) x

j

j =1

(6b) 2

 k J ξ J = 2ν BkBYi, B − k Y − 2 p R ∑ mj  − 2 pmSi i ∑ Γj dt 2  j =1  2 j =1 *

dYi,S

p mS i =

i S i,S

Si m

*

where i = al, ar

∞

and Yi ,S (0) = ξi ∑ x j j =1

(6c)

Yi , S ∞

2∑ x j j =1

(6d)


19

Energy & Fuels

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

Page 20 of 46

where Γj is the molar production rate for tar j-mers and the ratios of probabilities in eq. 6b are the number fractions of bridges containing one of these two sulfur functional groups. The noncondensable products of these reactions are governed by

dYHi 2S dt

Y

i COS

=ν

=

i H2S

(1 − ν B )k Y

i B i,B

(1 − ν

ν Hi

i H 2S

)

+

ν Hi S 2

2

k Y

2

 k νH S  J + 2 p R 2 ξ i ∑ m j  ; YHi 2 S (0) = 0 2 2  j =1  i

i S i,S

*

Si m

where i = al, ar

(6e)

Y Hi 2 S

2S

(6f)

where νH2Si are the molar stoichiometric coefficients for H2S production from Sal and Sar functional groups. The hydrogen, carbon, and oxygen needed to form these gases are extracted from other noncondensables when these elements are allocated to GHC products. The conversion of Sth produces only H2S according to th S th → H 2S

k

(R4)

where the hydrogen will also be extracted from GHCs. This functional group is also subject to tar shuttling, so the governing rate equation is ∞

dYth = dt

dξ th ∑ jx j j =1

dt

∞

J*

j =1

j =1

= −k thξ th ∑ jx j − ξ th ∑ jΓ j

∞

and Yth (0) = ξ th (0)∑ jx j (0) j =1

(7a)

Tar shuttling is the only means to eliminate nuclei from the condensed phase, so this equation simplifies to the following first-order decay in the number of thiophene groups per nucleus:

dξth = −kthξth ; ξth (0) from dt

eq.2 f (7b)

Since kth is a distributed-energy rate constant, the solution to eq. 7b is


20

Page 21 of 46

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

ξ th

=

ξ th ( 0 )

∫

∞

0

E th −  t  RT ( t ')  exp − ∫ Ath e dt '  f ( E th ) dE th  0   

(7c)

And since the moles of thiophene (and also pyrrolic and pyridinic N) per nucleus continuously diminish, the weight of the nucleus must be updated as follows:

MWA =

MWH2S  CA  1  H  H fa'  14 N  η MWHCN  MWS  Sth  ξth η ξ ) + + (1− th )(1− )   1+   '  +   + (1− )(1− 12CT  12 C  fa  12 C η0 η0 14  12  C ξth(0) ξth(0) MWS 

(7d)

where η is the moles of nitrogen per nucleus. The H2S from Sth decomposition is given by

dY Hth2 S dt

= k th ξ th Yth ; Y Hth2 S (0) = 0

(7e)

The five reactants in SORG and the H2S and COS they release are converted to a fractional weight basis with

A  Wi =  0 MWS (Yi, B + Yi,S )  ρ0 

where i = al, ar (8a)

∞ A  Wth =  0  MWS ξ th ∑ jx j j =1  ρ0 

A  W Hi 2 S =  0  MW S YHi 2 S  ρ0  A  i i WCOS =  0 MWS YCOS  ρ0 

(8b)

where

i = al , ar , th (8c)

where

i = al, ar (8d)

These three functional groups accumulate in the cumulative tar sample, according to al b ar b daf J* J* J* pm j pm j  ρ 0  S ORG d SORGf TAR   = ξ th ∑ jΓ j + ξ al ∑ ( j − 1)Γ j + ξ ar ∑ ( j − 1)Γ j + dt j =1 j =1 p m j j =1 p m j  A0  MWS


21

Energy & Fuels

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

(p

J*

Sal m

ξ al + p ξ ar )∑ Γj ; Sar m

SORG

Page 22 of 46

f TAR (0) = 0

j =1

where

(9a)

SORG

fTAR is the number fraction of organic sulfur in the whole tar product, which

determines the weight percentage of sulfur in tar as

% S TAR

daf S ORG S ORG f TAR = 100 WTAR

(9b)

Similarly, the weight percentage of residual SORG in char is given by ∞   MWS Yal, B + Yar, B + Yal, S + Yar, S + ξth ∑ jx j  j =1   ORG %SCHAR = 100  ρ0   WCHAR  A0 

(9c)

The sulfur in SSO4 and SPYR is released by the following two independent reactions:

S SO 4  → SO 2 (g)

(R5)

k

py FeS2 → FeSX (s) + (2 − X ) H 2 S ( g )

(R6)

where the stoichiometry, X, in the condensed pyrite-derived product varies from unity at pressures to 0.5 MPa to 1.8 at 6 MPa but is independent of temperature. The required hydrogen and oxygen are assumed to be extracted from hydrated minerals, rather than organic coal components. Pyrite decomposes via a single distributed-energy reaction, so that E  t  − PYR ∞  FeS2 (t )  RT   = ∫ exp − ∫ APYRe ( t ') dt '  f PYR ( EPYR ) dEPYR  0   FeS2 (0)  0  

(9a)

The levels of the products are described by


22

Page 23 of 46

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

dYHPYR 2S dt

= (2 − X )k PYR FeS2 ; YHPYR (0) = 0 2S

and

dFeSX = k PYR FeS2 ; FeS X (0) = 0 dt (9b)

These concentrations are evaluated from stoichiometric relations to give

 FeS2 (t )  YHPYR = ( 2 − X ) FeS ( 0 ) 2 S 1 −  2  FeS2 (0) 

 FeS2 (t )  and FeSX = FeS2 (0)1 −   FeS2 (0) 

(9c)

Pending additional measurements on the kinetics for SSO4 decomposition, sulfate decomposition is directly related to pyrite decomposition with

S SO4 (t ) S SO 4 (0 )

=

FeS 2 (t ) + 0 .37 FeS 2 (0 )

and

 S SO4 (t )  YSOSO24 = S SO 4 (0 ) 1 −   S SO 4 (0 ) 

(10a)

which ensures that the fractional conversion of SSO4 never exceeds 63 %, consistent with the time-resolved SO4 conversion data reported by Fatemi-Badi22. On a dry basis, the product yields are

W HPYR = MW H 2 S YHPYR 2S 2S

and

WSOSO24 = MW SO2 YSOSO24

(10b)

The ash content is adjusted for pyrite and sulfate decomposition with SO4 Adry(t ) = Adry(0) − WHPYR − WSO 2S 2

(10c)

and the weight percentage of sulfur in char, in dry wt. %, is

dry % S CHAR

ORG  2MWS  XMWS MWS % S CHAR dry daf YFeS2 + YFeS X + WSO4 + WCHAR   MWFeS X MWSO4 100  MWFeS2  = 100 dry WCHAR

(10d)

Hence, the analysis for the devolatilization of coal-S adds ten ordinary differential equations to the theory, and nine rate parameters: Eal, νH2Sal, νH2Sar, Ath, Eth, σth, APYR, EPYR, and σPYR. Based on interpretations of the validation database, the three parameters for pyrite decomposition do


23

Energy & Fuels

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

Page 24 of 46

not depend at all on coal quality, and Eal, νH2Sal, νH2Sar, Eth, and σth were also fixed for all coal types, because the FLASHCHAIN parameters for bridge conversion already have strong rank dependences1. To this point, only Ath was adjusted for some coals, although more data with a few dozen coals for temperatures hotter than 1100°C will be needed to finalize this rank dependence. General Guidelines for the Data Interpretations Sulfur release during devolatilization is obviously connected to numerous fuel properties including S-distributions and the functional group distributions in SORG, as well as all factors that govern the partitioning of coal into noncondensables and tar. Moreover, the domain of commercial applications covers huge ranges in heating rate, temperature, time, pressure, and coal quality. S-distributions were reported for all coals in the validation database, but none of the distributions of Sal, Sar, and Sth were determined. This is a major omission because, according to the theory, these three functional group classes have grossly different kinetic responses. It was managed by adjusting the proportions of Sal and Sar in each coal to tune-in the predicted behavior to each dataset. As seen in Fig. 2, above, the assigned values abide by the expected tendencies for Sal and Sth, albeit with substantial sample-to-sample variability, which may or may not be realistic. The other important omission is that most datasets monitored changes to either the condensed coal phase or to volatile S-species but not both phases. The three most complete datasets25-27 reported time-resolved levels of SPYR, SFeS, SORG, SGAS and STAR; the reported values for SSO4 were uniform either by assumption or due to the short transit times in these tests. Fatemi-Badi et al.22 reported time-resolved S-distributions for chars from a hv bituminous coal, although these


24

Page 25 of 46

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

values are too scattered for model validation work. Others monitored only the S-contents of chars at the end of each test28,29 or the coal-S fractions released as H2S, COS, and CS230, and Cai and coworkers determined the levels of sulfur in tar and char31, and in char only32. Tests were conducted in wire mesh reactors31,32, fixed bed reactors29,30, and with coflow28 and counterflow25-27 free-fall reactors. The database represents heating rates from 10 to nearly 104°C/s, temperatures to 1500°C, pressures to 7 MPa, and S-distributions from 27 different coal samples representing ranks from lignite to anthracite. A coalification diagram and the Sdistributions for the samples are reported in Supplementary Material as Figs. S1 and S2. The main inconsistency in the database is that tar-S levels were usually excessive, in so far as fractional SfTAR levels were often much greater than fractional tar yields. As seen in Table 1, below, several of the disparities are implausibly large. One potential explanation is that all the studies that reported tar-S levels25-27,31 passed the product streams through tar collectors cooled by liquid N2 upstream of H2S traps. Since H2S boils at -60°C, this configuration admits the possibility that condensed H2S was recovered with condensed liquid products, which would skew the tar-S levels toward excessive values. Another inconsistency pertaining to the variations in tar-S levels across a pressure range is discussed below. In the FLASHCHAIN simulations, reported values of heating rate, temperature, time, and pressure and the fuel properties were imposed as operating conditions. Whenever possible, parameters in the coal constitution submodel were adjusted to closely match reported total and tar yields in individual tests, to eliminate any discrepancies that would otherwise obscure the evaluations of predicted S-devolatilization. A simulation of each thermal history usually required less than a second on a 3.2 GHz microprocessor.


25

Energy & Fuels

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

Page 26 of 46

Results The model parameters that are uniform for all coals were estimated from preliminary calculations. The threshold energy for S-functional groups in bridges, Eal, was first estimated as 198 kJ/mol to roughly match the thermal response reported by Calkins10 for Sal and Sar model compounds, but then increased to 213 kJ/mol to better match validation datasets. In fact, data taken for short reaction times are very insensitive to this parameter, so one value could be applied to the entire database. Similarly, the parameters for thiophene decomposition were estimated to match Calkins’ results (Eth = 251 kJ/mol and σth = 25 kJ/mol). The frequency factor had to be adjusted for individual coals, provided that they were tested at temperatures hotter than 1100°C; otherwise, contributions from Sth decomposition were too small to resolve in the overall behavior, so the frequency factor was fixed at 1x106 s-1. The stoichiometry for H2S production from Sal and Sar was fixed at 0.945 for both functional groups, primarily because COS yields were not reported in all but one of the datasets. Yani and Zhang’s TGA datasets on pure pyrite pyrolysis15 were interpreted to assign the parameters in kPY as APY = 4x1014 s-1; EPY = 293 kJ/mol; and σPY = 20.9 kJ/mol. Only the frequency factor had to be increased to 5x1015 to describe the decomposition of coal-bound pyrite, and these parameters were applied to all coals. The first case in Fig. 3 interprets char-S fractions from six lignites and one medium volatile (mv) bituminous coal (V. Cuka) heated for 7 min at 500 to 1000°C. The dataset29 included two other fuels whose rank is too low to process with FLASHCHAIN and another whose properties did not close material balances. The analysis accurately interprets the gradual elimination of sulfur from char across the temperature range, and the acceleration at the hottest temperature due to appreciable decomposition of Sth. It also describes the substantial eliminations for extended


26

1.0

1.0

0.9

0.9

0.8

0.8

V. Cuka

0.7

Kostolac

0.6

fCHAR

fCHAR

0.7

S

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

Resavica 0.6

Kolubara A

S

Page 27 of 46

Soko 0.5

Kovin

Bogovina

0.4

0.5

0.4

500

600

700

800

900

1000

1100

500

600

700

Temperature,C

800

900

1000

1100

Temperature,C

Figure 3. Char sulfur fractions for six lignites and a mv bituminous coal heated at 10 – 35°C/s for 7 min at 0.1 MPa29. heating at 500°C, albeit for only four of the seven samples.

The case in Fig. 4 covers four diverse coals heated at 5000°C/s to 1500°C with a 2 s isothermal reaction period (IRP)32. These are the only tests in the database with sufficient thermal severity to destroy appreciable portions of Sth. To obtain the agreement in Fig. 4, Ath was adjusted from 1.3x106 to 3x107 s-1. The two subbituminous coals had the fastest rates, as expected, although the trend in Fig. 4 gives the mistaken impression that S-retention can be simply correlated to Ccontent. Many more datasets in this temperature range are needed to unravel the rank dependence in Sth decomposition, and to develop accurate correlations for Ath that depict the distinctive behavior of individual coals. The time-resolved distributions of sulfur products in Fig. 5 were recorded with a free-all reactor under N2 at atmospheric pressure, for which the coal heating rate was estimated to approach


27

Energy & Fuels

0.7 0.6

fCHAR

0.5

S

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

Page 28 of 46

0.4

0.3 0.2

0.1

5000C/s to 1500C w/2s IRP 0.0 75

80

85

90

C-Content, daf wt.%

Figure 4. Char sulfur fractions for diverse coals heated at 5000°C/s to 1500°C with a 2s IRP32. 104°C/s. Estimated thermal histories for entrained coal suspensions are inevitably subject to substantial uncertainties due to ambiguous two-phase mixing at the fuel injector. This was countered by matching the reported char yields to the predicted values for the shortest transit time, in effect substituting the extent of devolatilization as a surrogate for the absolute time scale. Succeeding transit times were based on the reported time increments from the first sampling position. The same procedures were applied to independent datasets from a very similar free-fall pyrolyzer25,26. The product distributions in Fig. 5 are cumulative from the bottom upward for SSO4, SPYR, SFeS, and SORG in the char, and for SGAS and STAR for volatiles. Note that discrepancies between measured and predicted values for a particular product propagate upward and appear to affect the comparisons for all higher products in the figure. The reported SfSO4 levels were uniform for all transit times for all three coals, so sulfate decomposition was omitted from these simulations. Data in the two upper panels pertain to hv bituminous coals, and the lowest panel pertains to a mv bituminous. The analysis accurately describes the conversion of FeS2 into FeS for all coals,


28

Page 29 of 46

1.0

Cumulative S-Fractions

0.8

STAR 0.6

SORG SGAS

0.4

FeS2

0.2

FeS SO4

0.0 1.0

STAR


0.8

0.6

SGAS SORG 0.4

0.2

FeS2

FeS

0.0 1.0

STAR

0.8


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

SGAS

SORG

0.6

0.4

0.2

FeS2 FeS

0.0 0.0

0.2

0.4

0.6

0.8

1.0

Time, s

Figure 5. Sulfur product distributions from two hv bituminous and (bottom) one mv bituminous coals rapidly heated to 960°C under 0.1 MPa N227. Cumulative contributions appear for sulfur in () SSO4; () FeS2; () FeS; () SORG; () SGAS; and () STAR, as fractions of coal-S.


29

Energy & Fuels

1.0

1.0

STAR 0.8

STAR SGAS

SORG

0.6

0.6

SGAS 0.4

0.4

SORG FeS2

0.2

FeS2 0.0

0.2

FeS

FeS SO4

0.0 0.2

0.4

0.6

0.8

1.0

1.2


0.8


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

Page 30 of 46

SO4 0.0

0.2

0.4

Time, s

0.6

0.8

0.0 1.0

1.2

Time, s

Figure 6. Sulfur product distributions from (left) low-density and (right) high-density hv bituminous coal rapidly heated to 980°C under 0.1 MPa N226. Cumulative coal-S fractions appear for sulfur in () SSO4; () FeS2; () FeS; () SORG; () SGAS; and () STAR. although the predicted pyrite decomposition in the top and bottom panels is faster than the reported values, even while the predicted dynamics for FeS production are accurate. The predicted decay in SORG is also accurate for all coals. However, all the predicted splits between SGAS and STAR are biased toward low STAR levels. Since this flaw is seen in most cases with reported STAR levels it will be taken up in the Discussion section. The decompositions of SORG and SPYR were isolated in tests with density classified cuts of an hv bituminous coal in the same free-fall pyrolyzer26. An intermediate cut gave nearly the same product distribution as the low-density cut and is not shown. As seen in Fig. 6, the analysis accurately interprets SORG decomposition, although the predicted STAR levels are lower than half the reported levels. For the pyrite-enriched sample, the predicted SORG decomposition and the dynamics for both SGAS and STAR are within measurement uncertainties throughout, but the


30

Page 31 of 46

0.8

hv Bit 0.7 0.6

S-Fraction

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

0.5

Volatile-S

0.4

lv Bit

0.3 0.2 0.1

Tar-S

0.0 10

100

1000

10000

Heating Rate, C/s

Figure 7. Partitioning of coal-S into (&) volatile-S and (&) tar-S with hv and mv bituminous coals after heating at various rates to 950°C with 5s IRP at 0.1 MPa31. kinetics for pyrite decomposition are too fast. However, once the lead time for the predicted FeS2 dynamics is factored out, the predicted dynamics for FeS production are within the measurement uncertainties throughout this test. Since the ultimate FeS level equals half the initial pyrite level, it is hard to explain how different kinetics could pertain to these two condensed products, and also to the dynamics for both species for two of the three coals in Fig. 5. Perhaps difficulties in the resolution of condensed intermediates with the standard laboratory protocol33 are responsible. Product distributions from tests in a very similar free-fall pyrolyzer from four diverse coals25 are interpreted in Fig. S3 in Supplementary Material. The impact of heating rate variations is interpreted in Fig. 7, which shows volatile-S and tar-S from two coals for heating rates from 5 to 5000°C/s. The thermal severity in all tests was


31

Energy & Fuels

0.8 0.7

hv Bit

0.6

S-Fraction

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

Page 32 of 46

Volatile-S

0.5 0.4

lv Bit

0.3 0.2 0.1

Tar-S

0.0 0

1

2

3

4

5

6

7

8

Pressure, MPa

Figure 8. Partitioning of coal-S into (&) volatile-S and (&) tar-S with hv and mv bituminous coals after heating at 1000°C/s to 700°C with 10s IRP at various pressures31. sufficient to achieve ultimate primary devolatilization yields. Also, the simulated total and tar yields were matched to the reported values for every test. The familiar tendency for a stronger enhancement in a tar-characteristic than in the characteristic for all volatiles is apparent in the data and predictions for the hv bituminous coal: Predicted tar-S levels are within measurement uncertainties for all heating rates, while the enhancements to volatile-S may be slightly underestimated. The same tendencies are evident in the predictions for the lv bituminous, but the data show the opposite tendency: Measured tar-S levels diminish for progressively faster heating rates, while the volatile-S levels are tripled. The analysis cannot interpret such unusual behavior. The analogous case for the impact of pressure variations with the same two coals appears in Fig. 8. Although the temperature was lower in this series than in the heating rate study, the thermal severity was still intense enough to obtain ultimate primary devolatilization yields in every test;


32

Page 33 of 46

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

indeed, the tar yields were identical for the test at 0.1 MPa in Fig. 8 and for 1000°C/s in Fig. 731, despite the different temperatures and that different reactor facilities were used for each series. But the reported tar-S levels for 0.1 MPa in Fig. 8 are grossly different: 0.51 in Fig. 8 vs. 0.22 in Fig. 7 for the hv bituminous, and 0.19 vs. 0.11 for the mv bituminous. Since the reported tar yields are the same for these pairs of conditions, it is inconceivable that the tar-S levels could be so drastically different. Accordingly, the predicted tar-S levels are equal for these pairs of conditions, and diminish for progressively higher pressures while they relax to an asymptotic value for the highest test pressure. Predicted volatile-S levels diminish for progressively higher pressures, primarily because pyrite releases less H2S for progressively higher pressures and SPYR is substantial for both coals. Whereas measured tar-S levels diminish for higher pressures, the measured volatile-S levels remain the same for the hv bituminous and increase for the mv bituminous, which is very difficult to explain. These unresolved discrepancies will persist until the inconsistent tar-S levels for comparable conditions in Figs. 7 and 8 have been explained. Discussion Sulfur in coal is distributed among pyrite, sulfates, and various organic functional groups. Pyrite decomposition into H2S is accurately described with one DAEM-based rate and, to very good approximation, the same kinetic parameters for all coal types. As expected, decomposition rates for included pyrite are faster than for excluded pyrite. The mismatch in the apparent dynamics for pyrite decomposition and for troilite formation is the only unresolved ambiguity. Sulfate decomposition is almost always unimportant, although time-resolved data on this step for rapid heating rates would close a complete kinetic analysis for the inorganic S-species. According to the proposed reaction scheme, SORG is distributed among bridges, peripheral


33

Energy & Fuels

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

Page 34 of 46

groups, and aromatic nuclei in organic coal macromolecules, but not char links. The main sulfur gases, H2S and COS, are expelled in parallel by two independent processes: In one, bridge scissions first form peripheral groups with intact original S-functional groups, then the peripheral groups are released as noncondensables. In the other, S-gases are released along with all major noncondensables whenever bridges spontaneously decompose into char links. The main advantage of this approach is that previously specified kinetics for bridge conversion describe the production of noncondensable S-products for any coal sample, without modification. The only new parameter is the threshold decomposition energy that delineates the distinctive kinetic responses of Sal and Sar. Thiophene decomposition can be described with one DAEM-based rate process, albeit with relatively little empirical support because so few datasets have been reported for the thermal severities that expel appreciable portions of Sth. Rates for this step become slower for coals of progressively higher rank, although data on a few dozen coals rapidly heated to temperatures hotter than 1100°C over several seconds are needed to finalize the kinetic assignments. These relatively straightforward connections among organic-S functional groups and FLASHCHAIN’s coal constitution submodel and reaction mechanism for primary devolatilization accurately interpret S-release from coals across the rank spectrum throughout the operating domain for most commercial applications. Indeed, values from the analysis closely match reported values, as seen in Fig. 1, above, for the 22 coals in the validation database whose ultimate S-release was reported. But this performance does not yet signal any predictive capability that depicts the distinctive behavior of individual coal samples, for three reasons. First, the values of Sal and Sar were adjusted to tune-in the simulation results to the reported


34

Page 35 of 46

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

behavior for every coal in the validation database, and these assignments appear in Fig. 2. Given these values, the analysis accurately interpreted S-release throughout broad domains of temperature and heating rate for particular coals. But it remains to be determined if and how the specified values are related to readily available coal properties, to provide the basis for accurate descriptions of S-release for any coal sample. In the meantime, the analysis can only be applied if sufficient data on S-release to specify these fractions is available, because the sample-tosample variability in S-release is so large (cf. Fig. 1). Such data should cover the ranges of temperature, heating rate, and contact time in a subject commercial application for all coals of interest. The second obstacle to a predictive capability pertains to the impact of pressure variations. None of the available datasets for rapid heating conditions at elevated pressure can be qualified for model validation work. So it remains to be seen if the unexpected tendencies in Fig. 8 can be firmly established, or if the model-based trends will be validated as more data becomes available. The third obstacle is the uncertainty surrounding the split of SORG between tar-S and gas-S. The analysis invokes the same tar shuttling mechanism used to accurately describe the accumulation of oxygen and nitrogen in a cumulative primary tar sample, whereby the sulfur in bridges, peripheral groups, and nuclei in tar fragments is simply carried out of the fuel particle as tar is released. Each structural component contains the average amount of each S-functional group allocated uniformly over the population of all fragments in the condensed phase. Consequently, there is a limit to the enrichment of a cumulative tar sample in any heteroatom, and this limit is determined by the competition between scission and spontaneous charring during bridge conversion. In isolation, scission produces peripheral groups containing S-functional groups at


35

Energy & Fuels

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

Page 36 of 46

Table 1. Sulfur enhancement of cumulative tar samples. %C

*YTAR

daf wt.%

daf wt.%

S-Enrichment Measured

71.0 27.6 72.9 24.1 75.6 29.8 77.3 31.6 77.6 31.6 77.7 35.0 80.6 38.1 81.0 36.6 81.3 32.9 86.1 28.9 87.6 29.5 87.9 13.8 *Estimated with FLASHCHAIN

1.05 1.14 0.93 1.05 1.36 1.40 0.97 1.98 1.20 1.42 0.80 1.40

Simulated 0.36 0.56 1.26 1.06 0.52 0.54 0.75 0.93 0.81 1.19 0.75 1.00

their initial level in coal. Since tar fragments are short they contain disproportionate numbers of peripheral groups on their fragment ends, so that scission can enrich tar samples in sulfur above and beyond the average level in a coal’s organic material. Conversely, both spontaneous charring and peripheral group elimination expel S-functional groups before they can be shuttled away as tar, and thereby deplete the tar sample of sulfur. A conservative upper limit to the enrichment from these mechanisms is approximately one-third, whereas depletion can eliminate virtually all sulfur from tar. Enrichment factors based on reported and simulated tar-S levels are compiled in Table 1. They are ratios of fractional tar-S levels to fractional tar yields, where the tar-S fractions are based on SORG only, since inorganic coal-S species cannot contribute to tar-S. Tar yields were reported only for the third and final entries; the rest are estimates from FLASHCHAIN for each set of test conditions. Among the 12 cases, only three simulation enrichments agree with the measured values. But the discrepancies cannot simply be attributed to flaws in the analysis because, in five cases, measured S-enrichments exceed the upper limit of four thirds for the primary


36

Page 37 of 46

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

depolymerization mechanism. These exceptional enrichment levels are either indications of problems in the tests, such as the co-condensation of H2S and tar noted earlier, or the first indications of some crucial heterogeneity in coal constitution that undermines the validity of average loadings of the S-functional groups within FLASHCHAIN’s average structural components. In so far as the averaging in FLASHCHAIN’s coal constitution submodel has performed well in so many other aspects of coals’ primary devolatilization6, this author is inclined to doubt that S-release mechanisms are really that exceptional. The types of tests needed to resolve these issues are discussed below. Notwithstanding the measurement uncertainties, the simulated S-enrichments in Table 1 are generally lower than unity, in some cases much lower. This is a consequence of the reported levels of SGAS in the tests behind Figs. 5, 6, and S3, for reasons that are illustrated in Fig. 9. These simulations subjected the same coal properties to standardized operating conditions, while fal, as a fraction of SORG, was varied from 0 to 0.25 to 0.50 under the constraint that the sum of fal and far was fixed at one-half. All these cases achieved ultimate primary devolatilization behavior with the same yields of tar and gas. Since the kinetics for Sal decomposition are much faster than those for Sar, greater portions of S-functional groups are eliminated before and during tar production for progressively greater values of fal. Consequently, greater proportions of SORG are released as noncondensables, along with correspondingly lower proportions in tar, for progressively more Sal in the coal. Since the sum of fal and far is fixed in all cases, the retention of char-S stays the same. Note especially that S-enrichment in tar becomes less pronounced with more Sal. So it is impossible to reconcile the appreciable levels of SfGAS derived from SORG at the first sampling


37

Energy & Fuels

2.00

SORG Fraction & Tar-S Enrichment

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

Page 38 of 46

1.75

fal

1.50 1.25

0.00

Tar-S Enrichment

1.00

0.25 0.50

0.75 0.5

Increasing fal SORG

0.4

fGAS

0.3 SORG

0.2 0.1

fTAR

Increasing fal

fal+far=0.5

0.0 0

200

400

600

800

1000

1200

Temperature C

Figure 9. Simulated (upper solid curves) tar-S enrichment, (lower solid curves) SGAS fractions, and (dashed curves) STAR fractions for heating a hv bituminous coal at 1000°C/s to 1150°C with no IRP at 0.1 MPa for fractional levels of SORG as Sal of 0, 0.25, and 0.5 with fixed sum of Sal and Sar. position for the tests in Figs. 5, 6, and S3 with their excessive S-enrichment factors in Table 1, because organic S-functional groups released as gas necessarily reduce S-enrichment in tar. Even relatively little production of S-gases rapidly diminishes the enrichment toward unity. Although the earliest tars are strongly enriched relative to coal loadings because of their abundance of peripheral groups, the enrichment diminishes throughout primary devolatilization as char links accumulate in tar precursors, and as peripheral groups are released from the condensed phase. As seen in Fig. 9, even with no coal-S in its most reactive Sal form, this mechanism cannot explain S-enrichment factors greater than 1.3, mostly because Sth is effectively an inert form during nearly all the operating conditions in the validation database.


38

Page 39 of 46

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

The tests needed to establish whether or not the partitioning of SORG into tar and noncondensables is amenable to a network depolymerization mechanism like FLASHCHAIN must simultaneously monitor all the S-classes in Figs. 5, 6, and S3, along with total and tar yields, throughout the primary devolatilization of at least a dozen coals. Time-resolution throughout all stages of tar production is essential, because whether or not gas production precedes tar production is the determining factor; it can be implemented either with rapid quenching or with tests across a broad temperature range with IRPs no longer than 1 or 2 s at each temperature. Conclusions (1) S-release can be accurately interpreted for any coal sample across broad ranges of temperature, heating rate, and contact time, provided that sufficient data is available to specify a functional group distribution in SORG. (2) A single distributed-energy reaction with the same parameters for all coals accurately describes the release of H2S from pyrite during primary devolatilization. (3) Additional kinetic rate data on SSO4 decomposition under rapid heating is needed to close the analysis for inorganic S-species. (4) By associating Sal and Sar with labile bridges and peripheral groups, FLASHCHAIN’s main reaction sequence for primary devolatilization accurately describes the release of noncondensable S-species from these precursors with the same rate parameters previously specified by the coal constitution submodel for individual coal samples. The


39

Energy & Fuels

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

Page 40 of 46

only new parameter is the energy threshold that delineates the distinctive kinetic responses of Sal and Sar. (5) A single distributed-energy reaction accurately describes the release of Sth, although additional datasets for temperatures of 1100°C with contact times of several seconds are needed to specify the rank dependence for this process. (6) The analysis did not accurately describe the partitioning of SORG between tar-S and noncondensable S-products for most coals. The tests needed to establish whether or not the partitioning of SORG into tar and noncondensables is amenable to a network depolymerization mechanism like FLASHCHAIN must simultaneously monitor all the major S-classes, along with total and tar yields, throughout the primary devolatilization of at least a dozen coals. (7) None of the available datasets for rapid heating conditions at elevated pressure could be qualified for model validation work, so it remains to be seen if the model-based trends will be validated as more data becomes available. References 1. Niksa, S. Flashchain theory for rapid coal devolatilization kinetics. 4. Predicting ultimate yields from ultimate analyses alone. Energy Fuels 1994, 8, 659-70. 2. Niksa, S. Flashchain theory for rapid coal devolatilization kinetics. 6. Predicting the evolution of fuel nitrogen from various coals. Energy Fuels 1995, 9, 467-78.


40

Page 41 of 46

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

3. Niksa, S. Flashchain theory for rapid coal devolatilization kinetics. 7. Predicting the release of oxygen species from various coals. Energy Fuels 1996, 10, 173-87. 4. Fletcher, T. H., Kerstein, A. R., Pugmire, R. J., and Grant, D. M. Chemical percolation model for devolatilization. 3. Direct use of 13NMR data to predict effects of coal type. Energy Fuels 1992, 6, 414-31. 5. Niksa, S., Liu, G.-S., and Hurt, R. H. Coal conversion submodels for design applications at elevated pressures. Part I. Devolatilization and char oxidation. Prog. Energy Combust. Sci. 2003, 29, 425-77. 6. Solomon, P. R., Hamblen, D. G., Serio, M. A., Yu, Z.-Z., and Charpenay, S. A characterization method and model for predicting coal conversion behavior. Fuel 1993, 72, 469-88. 7. Niksa, S. and Kerstein, A. R. Flashchain theory for rapid coal devolatilization kinetics. 1. Formulation. Energy Fuels 1991, 5, 647-65. 8. Niksa, S. Rapid coal devolatilization as an equilibrium flash distillation. AIChE J 1988, 34, 790-802. 9. Suuberg, E. M., Lee, D., and Larsen, J. W. Temperature dependence of crosslinking processes in pyrolysing coals. Fuel 1985, 64, 1668-71. 10. Calkins, W. H. Determination of organic-sulfur containing structures in coal by flash pyrolysis experiments. Energy Fuels 1987, 1, 59.


41

Energy & Fuels

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

Page 42 of 46

11. Hu, G., Dam-Johansen, K., Wedel, S., and Hansen, J P. Prog. Energy Combust. Sci. 2006, 32(3), 295-314. 12. Grygleicz, G. and Jasienko, S. Fuel 1992, 71(11), 1225-29. 13. Patrick, J. W. Fuel 1993, 72(3), 281-85. 14. Gryglewicz, F., Wilk, P., Yperman, J., Franco, D. V., Maes, I. I., Mullens, J., and van Poucke, L. C. Fuel 1996, 75(13), 1499-1504. 15. Yani, S. and Zhang, D. An experimental study into pyrite transformation during pyrolysis of Australian lignite samples. Fuel 2010, 89, 1700-08. 16. Ibarra, J. V., Bonet, A. J., and Moliner, R. Fuel 1994, 73(6), 933-39. 17. Bonet, A. J., Ibarra, J. V., Lazro, M. J., and Moliner, R. Fuel Process. Technol. 1993, 36(1/3), 319-25. 18. Ibarra, J. V., Palacios, J. M., Moliner, R., and Bonet, A. J. Fuel 1994, 73(7), 1046-50. 19. Chen, H., Li, B., and Zhang, B. Proc. Tenth Int. Conf. on Coal Sci., Taiyuan, China, 1999, pp. 713-16. 20. Chen, H., Li, B., and Zhang, B., Fuel 2000, 79(13), 1627-31. 21. McLennan, A. R., Bryant, G. W., Stanmore, B. R., and Wall, T. F. Energy Fuels 2000, 14(1), 150-59. 22. Fatemi-Badi, M., Scaroni, A. W., and Jenkins, R. G., Proc. American Chemical Soc. Div. Fuel Chem. Preprints 1988, 33(1), 265-73.


42

Page 43 of 46

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

23. Strugala, A. Empirical formulae for calculating real density and total pore volume of hard coals. Fuel 1994, 73(11), 1781-85. 24. George, G. N., Gorbaty, M. L., Keleman, S. R., and Sansone, M. Direct determination and quantification of sulfur forms in coals from the Argonne Premium Sample Program. Energy Fuels 1991, 5, 93-97 25. Sugawara, T., Sugawara, K., Nishiyama, Y., and Sholes, M. A. Dynamic behavior of sulfur forms in rapid hydropyrolysis of coal. Fuel 1991, 70, 1091-97. 26. Sugawara, K., Tozuka, Y., Kamoshita, T., Sugawara, T., and Sholes, M. A. Dynamic behavior of sulfur forms in rapid pyrolysis of coals with alkali treatment. Fuel 1994, 73, 1224-28. 27. Sugawara, K., Abe, K., Sugawara, T., Nishiyama, Y., and Sholes, M. A. Dynamic behavior of sulfur forms in rapid pyrolysis of density-separated coals. Fuel 1995, 74, 1823-29. 28. Torrest. R. S. and VanMeurs, P. Laboratory studies of the rapid pyrolysis and desulphurization of a Texas lignite. Fuel 1980, 59, 458-64. 29. Manovic, V. and Grubor, B. Correlation for the total sulfur content in char after devolatilization. Energy Fuels 2006, 20, 133-37. 30. Garcia-Labiano, F., Hampartsoumian, E., and Williams, A. Determination of sulfur release and its kinetics in rapid pyrolysis of coal. Fuel 1995, 74, 1072-79. 31. Cai, H.-Y., Guell, A. J., Dugwell, D. R., and Kandiyoti, R. Heteroatom distribution in pyrolysis products as a function of heating rate and pressure. Fuel 1993, 72, 321-327.


43

Energy & Fuels

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

Page 44 of 46

32. Cai, H.-Y., Megaritis, A., Messenbock, L., Vasanthakumar, L., Dugwell, D. R., and Kandiyoti, R. Pyrolysis of coal maceral concentrates under pf-combustion conditions: Changes in heteroatom partitioning as a function of rank. Fuel 1998, 77(12), 1283-89. 33. Yan, J., Bai, Z., Zhao, H., Bai, J., and Li, W. Inappropriateness in the standard method in sulfur form analysis of char from coal pyrolysis. Energy Fuels 2012, 26, 5837-42. 34. Niksa, S. Interpreting coal conversion under elevated H2 pressures with FLASHCHAIN and CBK. Proc. 2011 Int. Conf. on Coal Science and Technol., IEA, Oviedo, Spain, 2011. Nomenclature Adry

Ash content in dry wt.%

Ai

Pseudo-frequency factor in a decomposition reaction for reactant i

B

Nondimensional molar concentration of labile bridges in coal

C

Nondimensional molar concentration of char links in coal

Eal

Threshold activation energy for the decomposition of Sal, kJ/mol

Ei

Activation energy in a decomposition reaction for reactant i

fa'

Fraction of aromatic carbon

fi

Si as a mass fraction of SORG in Fig. 9.

fi(Ei)

Gaussian distribution of activation energies for the decomposition of reactant i

Fb(0) Fraction of all intact linkages that are bridges in the condensed phase fib

Number fraction of either Sal or Sar in original labile bridges

FeS2

Molar concentration of pyrite

H

Fraction of aromatic hydrogen

fa’

SORG

fTAR

j

Fraction of SORG in a cumulative tar sample

Index on the degree of polymerization of coal fragments


44

Page 45 of 46

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

J*

Maximum degree of polymerization of tar precursor fragments

ki

Rate constant for the decomposition of functional group i

kS i

Distributed-energy rate constant for conversion of peripheral groups with either Sal or Sar

kR

Arrhenius rate constant for bimolecular recombination

mj

Metaplast fragment with j linked nuclei

MWi Molecular weight of species i p(0)

Likelihood that an aromatic nucleus in coal is connected to other nuclei

pmSi

The likelihood that a metaplast fragment end contains a peripheral group of type i

i

pmjb

Proportion of intact labile bridges with either Sal or Sar in a j-mer

pmj

Proportion of intact linkages in a j-mer

S

Nondimensional molar concentration of peripheral groups in the condensed phase

Si

Portion of SORG as aliphatic, aromatic sulfide, or thiophene functional groups, daf wt.%

SK

Percentage of organic, pyritic, or sulfate sulfur in coal, dry wt.%

SO4

Molar concentration of sulfate

%SCHARm

Mass percentage of char as sulfur on basis m

%STAR Mass percentage of tar as organic sulfur, daf wt.% t

Time

T

Temperature, K

Wi

Weight percentage of species i, daf wt.%

WiH2S Weight percentage of H2S from species i, daf wt.% X

Element number for sulfur in the condensed product of pyrite decomposition

xj

J-mer in the condensed phase

Yi,j

Nondimensional molar concentration of S-reactant i in coal component j

Yki

Nondimensional molar concentration of H2S or COS from the decomposition of Sreactant i

Wi

Mass fraction of reactant i, daf wt.%


45

Energy & Fuels

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

Wki

Page 46 of 46

Mass fraction of H2S or COS from functional group i, daf wt. %

Greek Symbols Γj

Molar production rate of tar j-mers

η

Average moles of nitrogen per aromatic nucleus

ρ0/A0 Initial average molecular weight of a coal monomer σi

Std. dev. about the mean energy in a decomposition reaction for reactant i

νH2Si

Molar stoichiometry for H2S production from the decomposition of reactant i

ξi

Moles of Sal or Sar per labile bridge, or moles of Sth per aromatic nucleus

Subscripts A

Aromatic nuclei

al

Aliphatic sulfur functional groups

ar

Aromatic sulfide functional groups

B

Labile bridges

C

Char link

ORG Organic sulfur functional groups of any kind PYR

Pyritic sulfur

S

Peripheral groups

SO4

Sulfate sulfur

T

Tar

th

Thiophene functional groups

Superscripts daf

Quantity in daf wt. %


46

FLASHCHAIN Theory for Rapid Coal Devolatilization Kinetics. 8

Recommend Documents