BIAGINI, ENRICO

M. Falcitelli

TOGNOTTI, LEONARDO

English

Archivio della Ricerca - Università di Pisa

Devolatilisation and Pyrolysis of Biomasses: Developmentand Validation of Structural ModelsE. Biagini 1 , M. Falcitelli 1 and L. Tognotti 2(*)  1 Consorzio Pis a Ric erc he SCaRL,  Ita ly - En ergy and En vironment Div ision -Lun ga rno M ed iceo  16, 56127 Pis a - ITALY2 Un ive rsità  deg li S tu di di Pis a - D ipa rtime nto  di Ingegneria  Chim ica ,Chim ica  Ind ustriale e Scie nza dei  M ate ria li – Via  Dio tisalvi 2,  56100 Pis a –ITALY1. IntroductionThis work involved modifying the currently available Chemical Percolation Devolatilization(CPD) model [1], and making it suitable for modeling pyrolysis of biomass feedstocks. Theassessed  version  of  CPD  simulates  coal  as  a  macromolecular  network  and  includes  astatistical processes of depolymerization, from which derives the release of non-condensablegases evolving from the bond rupture and the vaporization of the lighter n-mers, competingwith  cross-linking,  for  tar  and  char  formation.  Recent  development  in  the  modelling  ofbiomass devolatilisation involves the use of other network models such as the bio-FG DVC[2] and bio-FLASHCHAIN [3]. This suggest that also the CPD may be extended to biomasspyrolysis. Some partial  efforts in that direction have already been accomplished, focusingmainly  on  lignin  [4,  9],  which  is  similar  to  coal  in  being  a  cross-linked  aromatic.Nevertheless, at now, unlike the cases of coal and lignin, no general CPD model of wholebiomass pyrolysis (including cellulose and hemicellulose components) has yet been proposed.Achieving the bio-version of CPD is a goal of primary importance, because, owing to itscomputational efficiency, it  can be included in comprehensive 3D combustion codes. Forexample, a modified coal version of the CPD model has been incorporated already into amechanistic combustion code, and applied for process studies of combustion devices [5].The pyrolysis of biomass fuels has been the subject of numerous studies, as summarized inseveral reviews and collected papers (see references in [6]). One of the principal differencesbetween coal and biomass is the fact that coal is predominantly an aromatic material, whereasthe aromatic component of biomass (lignin) is a relatively minor constituent (~20%) for manybiomass materials. Biomass also has a much higher oxygen content as compared with coal,that  is  present  as  ether,  hydroxyl,  carboxyl,  aldehyde,  and  ketone  functionalities,  whichdecompose during pyrolysis to  produce oxygenated gases (CO, CO2,  H2O). The yields ofthese species are similar to those produced by pyrolysis of low-rank coals (5-10 dry wt.% forCO2 and H2O, 5-15 dry wt.% for CO). Biomass pyrolysis, however, gives much higher tar(liquid) yields than low-rank coals (40-50% versus 10-20% on a dry basis). The increased taryield comes primarily at the expense of char, the yield of which is much lower for biomassthan for  low-rank coals  (<10% versus  40-50%).  The  depolymerization  of  biomass  is  thepredominant pyrolytic reaction [7], whereas, in the case of coal, depolymerization reactionscompete with cross-linking events, which enhance the char formation [8]. Most of the charformed from biomass is derived from the lignin component, which is close to low-rank coalin its chemical composition. As in the case of coal, the yield and distribution of products frompyrolysis  of  biomass  depend  on  other  variables  in  addition  to  the  final  temperature  andholding time. These include heating rate, total pressure, ambient gas composition, and thepresence  of  mineral  catalysts  [7].  One approach to  the  quantitative  modeling of  biomass* Corresponding author: tognotti@ing.unipi.it29th Meeting on Combustionpyrolysis  is  based  on  the  approximation  that  the  three  main  components  of  biomass(cellulose, hemicellulose, and lignin) behave independently during pyrolysis (see, e.g., Nunnet  al.  in  ref.  [6]).  Consequently,  yields  can  be  predicted  based  on  a  knowledge  of  thebehaviour of pure components. The shortcoming of this technique is that it cannot account forpossible  interactions  between the  biomass  components.  Following the  behaviour  of  eachcomponents (cellulose, hemicellulose and lignin) a complex model, called CHL, was recentlydeveloped and validated over a wide range of experimental conditions [6]. As schematised infig. 1, CHL, compared to other approaches, is closer to be a complete tool for simulating thepyrolysis behaviour of a large number of lignin-cellulosic materials in different conditions. Itencompasses the material  balance, the energy balance and the description of physical andchemical phenomena occurring during the process, and it was validated with experimentaldata from both “fast pyrolysis” and “slow pyrolysis” conditions (see references in [6]). Fue ls(B iom ass, Coa ls ,R D F, ec c.)Pyro lysis D at aT GAFlashP yrolysisE xper im enta lPyro ly sis waysC hem ica l  M odelsC hem ica l A na lysisK ine ti c M ode lsD A E M S F O R Ultim at e andproxim ate N M RS t eamE xp losion S E MM ul ti step  g lobalkine ti cs+M acro-par tic lem ass t rasportC HLS ingle  andM u lti step  produc tK ine ti csC PDM u l tis tep bondkinet ics+M o lecula r st ructure+F lash  d istil l iza tionFig. 1 Methodological approaches to the modelling of biomass pyrolysis.Even  if  some  important  phenomena  are  neglected  (as  the  vaporisation  of  condensableproducts), the complexity, the high number of parameters and the high computational cost ofCHL model make it suitable to describe most of phenomena of practical interest for a singleparticle. Nevertheless, it cannot be included straight in comprehensive combustion codes, butit can be used as simulator to provide a set of data for assisting the development of  structuralmodels. The scheme of the work still in progress and some preliminary results are describedin the following.2. Overview of the structural modelAccording to the CPD model for coal pyrolysis [1], the labile bonds (i.e. linking movable orbreakable bridging bonds) between the clusters in the molecular structure lattice are cleaved,resulting in two general classes of fragments. One set of fragments has a molecular weightlow enough (and correspondingly a vapour pressure high enough) to escape from the biomassparticle  as  light  gases.  The  other  set  of  fragments  are  tar  vapour  precursors  that  have  arelatively higher molecular weight (and correspondingly a lower vapour pressure), and tend toremain for longer periods of time in the particle during typical devolatilization conditions.Italian Section of the Combustion InstituteDuring this time, reattachment with the biomass lattice can occur, which is referred to ascrosslinking. The high molecular weight compounds plus the residual lattice are referred to asmetaplast. The portion of the lattice structure that remains after devolatilization comprisesmetaplast, char and mineral matter. The CPD model characterizes the chemical and physicalprocesses  by  considering  the  molecular  structure  as  a  simplified  lattice  or  network  ofchemical bridges linking the polymeric clusters. The description of the cleaving of the bridgesand the generation of light gases, char and tar precursors is then considered to be analogous tothe following chemical reaction scheme.The previous kinetic scheme was  firstly introduced by Bradbury et al. (1979) (see referencesin [6]) for the decomposition of cellulose and adopted also in the CHL for all constituents.According to the novel perspective of CPD model, that kinetic scheme doesn’t refer to theglobal  component  anymore,  but  to  the  bounds.  The  variable  β represents  the  originalpopulation of labile bridges in the biomass lattice. Upon heating, these bridges become the setof reactive bridges,  β′. For the reactive bridges, two competing paths are available. In onepath, the bridges react to form side chains, δ. The side chains may detach from the aromaticclusters to form gases, g1. As bridges between neighbouring aromatic clusters are cleaved, acertain fraction of the biomass matter becomes detached from the lattice. These detachedpolymeric clusters are the heavier molecular weight tar precursors that form the metaplast.The  metaplast  vaporizes  as  tar.  The  metaplast  can  also  reattach  to  the  lattice  matrix(crosslinking). In the second path, the bridges react and become a char bridge, c, with therelease of an associated light gas product, g2.  The related set of reaction rate expressionsdescribe this reaction scheme assuming that the reactive bridges are destroyed at the same ratethat  they  are  created  [1].  Given  the  set  of  reaction  equations  for  the  lattice  structureparameters, it is necessary to relate these quantities to changes in mass and the related releaseof volatile products. The fractional change in the mass as a function of time is divided intothree parts: light gas, tar precursor fragments, and char. Algebraic expressions are obtainedfor each part using percolation lattice statistics. In accounting for mass in the metaplast (tarprecursor  fragments),  the  part  that  vaporizes  is  treated  in  a  manner  similar  to  flashvaporization,  where  it  is  assumed  that  the  finite  fragments  undergo  vapor/liquid  phaseequilibration on a time-scale that is rapid with respect to the bridge reactions. As an estimateof the vapor/liquid that is present at any time, a vapor pressure correlation based on a simpleform of Raoult’s law is used. For the part of the metaplast that reattaches to the coal lattice, acrosslinking rate expression is used. In the present work, the mathematical formulation of themass balances was substantially revised introducing a population balance for the liquid n-mers, and the ability to differentiate the fate of the tar yields in the vapour phase and theliquid metaplast remaining in the particle.3. Setting model parametersFor the development of bio-CPD, the basic assumption of CHL is maintained: each biomassfuel consists of cellulose, lignin and hemicellulose (hard- and softwood), so the problem is toassess kinetic, structural parameters and vapour pressure correlation for each component. The structure of the cellulose molecule is well known, its representative formula is (C6H10O5)nand its molecular weight varies from 250.000 to 1.000.000. Cellulose is a linear polymer:29th Meeting on Combustionunlike starch, no coiling occurs, and the molecule adopts an extended rod-like conformation.In microfibrils,  the multiple hydroxyl groups on the glucose residues hydrogen bond witheach other, holding the chains firmly together and contributing to their high tensile strength.As a consequence of the previous considerations, the structural parameters required by CPDfor the initial  cellulose network schematisation may be assigned with less uncertainty: thenumber of attachments per cluster (σ + 1) are very close to 2, the fraction that are stablebridges (p0) is  near to 1, the molecular weight  per cluster (MCL) is  near to the molecularweight of the monomer 166 a.m.u.. The molecular weight per side chain (Mδ) is supposed tobe small, because it has to be considered a mean value expressed on a per monomer basis ofthe  mass  of  the  terminal  chains  and  of  the  lattice  amorphous  defects.  Finally,  cellulosepyrolysis produces much lower char yields, when compared with hemicellulose and lignin, sothe initial value for the population of char bridges (c0) may be set to 0. The exact values of allthe structural parameters, together with kinetic parameters need to be fitted to data on lightgases, tar and char yields over a meaningful range of temperatures. To that purpose CPDmodel was used together with an optimization program to find the best parameter values.The hemicellulose is a hetero-poly-saccharide: its molecular structure is not so well definedas  that  of  cellulose.  It  is  formed  by  C6  (glucose,  mannose,  galattose)  and  C5  (xylose,arabinose)  units.  The  molecular  weight  of  the  monomers  is  usually  lower  than  that  ofcellulose and they have a weak undifferentiated structure compared to crystalline cellulose. Itsdegree of polymerisation is very much lower than that of cellulose: this could explain thehigher  reactivity  and  the  lower  thermal  stability  of  hemicellulose.  Practically,  thedecomposition  of the  hemicellulose can be assumed to  follow the  same pathways of thecellulose decomposition, and it may be described with appropriate modifications of structuraland kinetics parameters. Respect to the cellulose, the more branched but still linear structureof the hemicellulose may be represented with a value of (σ + 1) between 2 and 3; the value ofp0 will be lesser because to account for the higher initial fragmentation; c0 is greater than 0 toexplain the increased char yield; the molecular weight per cluster (MCL) may be assumedsomething more than the xylan one, with side chains contribution (Mδ) more substantial thanfor the cellulose network.Lignin  is  similar  to  low rank coal  with  a  three-dimensional  lattice  structure  of  phenoliccompounds. Its structure is not well defined and depends on the biomass type. One of themain problems when studying lignin is the impossibility of extracting it from the biomasswithout  chemically  modifying  it.  Using  13CNMR  analysis  and  theory  research,  previousinvestigations [9] proposed that for the CPD model coniferyl, sinapyl and p-coumaryl acidsare the base clusters. The set of values for the structural parameters recently proposed in theabove citation was adopted in the present work as initial “guess” for a further optimization.4. ResultsThe primary step of the work consisted in tuning the CPD model parameters. The data sets forthe optimisazion was generated with CHL model, used as generator of equivalent ‘numerical’experiments.  For  each  component  (cellulose,  hemicellulose  and  lignin)  CHL  producedtemporal profiles of gas, tar and char yields for an “ideal” particle small enough in order toneglect internal transport phenomena. The temporal profiles of the yields and for three finaltemperatures (773, 873, 973 K) and the respective temperature profiles calculated for fastheating rate conditions  (HR 14000 K/s) have been used to fit  the model parameters.  Thenumerical fit was formulated as a nonlinear least squares problem subject to bounds on thevariables and it was solved using a modified Levenberg-Marquardt algorithm and a finite-difference Jacobian. As example, the fitting curves for the cellulose yields are showed in fig.2 and 3. Once produced the best fit parameters for each component, then keeping them fixedthe assessment of the scheme was started by comparing model predictions with experimentalresults of effective biomasses, showing encouraging preliminary agreement.Italian Section of the Combustion InstituteFig. 2 Curve fitting of CPD model for gas yield from cellulose.Fig. 3 Curve fitting of CPD model for tar yield from cellulose.5. Final remarks and future workThe  CPD  model  has  been  modified  to  describe  biomass  pyrolysis  products  as  a  massweighted distribution of predictions for individual components. The framework of the bondkinetic scheme was maintained, but the formulation of the mass balances was substantiallyrevised introducing a population balance for the liquid n-mers, and the ability to differentiatethe fate of the tar yields in the vapour phase and the liquid metaplast remaining in the particle.In this  way also the role of the secondary reactions of tar cracking in the gas phase hasbecome  apparent.  The  chemical  structural  and  kinetic  parameters  for  each  component(cellulose, hemicellulose, lignin) have been developed based on theory, literature review andcurve-fitting. The predictions have been compared with experimental data with encouragingbut still preliminary results, some refinement are needed to better include secondary reactionsand the interactions among each component. Future work will  devoted to integration of aprogram calculating component composition from elemental analysis, and the development ofpredictive methods for the speciation of volatile yields and the reactivity of char yields.0 200 400 600 800 1000 12000.00.20.40.60.81.0973 K873 K773 KCellulose Gas Yield  CHL CPD  released mass fractiontime (ms)0 200 400 600 800 1000 12000.00.20.40.60.81.0773 K873 K973 KCellulose Tar Yield CHL CPD  released mass fractiontime (ms)29th Meeting on Combustion6. References1. Fletcher  T.H.,  Kerstein  A.R.,  Pugmuire  R.J.,  Solum  M.,  Grant  D.M.  A  ChemicalPercolation  Model  for  Devolatilization:  Summary.  Sandia  Technical  report  SAND92-8207, May 1992, available on line at http://www.et.byu.edu/~tom/devol_frame.html.2. Chen,  Y.,  Charpenay,  S.,  Jensen,  A.,  Wojtowicz,  M.A.  and  Serio,  M.A..  (1998).Modelling of Biomass Pyrolysis Kinetics. 27th International Symposium on Combustion.The Combustion Institute. pp. 1327-1334.3. S.  Niksa,  Predicting  the  rapid  devolatization  of  diverse  forms  of  biomass  with  bio-FLASHCHAIN, Proc. 28th Int. Symp. on Combustion, Edinburgh, UK, 2000, 2727-2733.4. Sheng,  C.  and  Azevedo,  JLT,  “Extending  the  Chemical  Percolation  devolatilization(CPD)  model  from  coal  to  lignin  pyrolysis”  Proceedings  of  the  11th  InternationalConference on Coal Science. San Francisco, CA. September 30 - October 5, 2001.5. Falcitelli M,  Consani G., Malloggi S., Rossi  N., Tognotti L. Characteristics of a twophase  CSTR  solver  for  modelling  pulverised  coal  flames.  ECCOMAS  ThematicConference on  Computational Combustion Lisbon 21-24 June, 2005.6. Biagini E. Energy and material recovery by thermal treatments of biomasses and wastes(co-combustion,  pyrolysis  and  gasification)  PhD  Thesis in  Chemical  Engineering  –University of Pisa – Italy (2003).7. Shafizadeh,  F.,  in  The  Chemistry of  Solid  Wood  (R.  M.  Rowell,  Ed.),  Advances  inChemistry Series No. 207, American Chemical Society, Washington, DC (1984).8. Solomon, P. R., Hamblen, D. G., Serio, M. A., Yu, Z. Z., and Charpenay, S., Fuel, 72, (4),489 (1993). 9. Pond, H. R., T. H. Fletcher, and L. L. Baxter, “Prediction of Tar and Light Gas DuringPyrolysis of Black Liquor and Biomass,” presented at the 3rd Annual Joint Meeting of theU.S. Sections of the Combustion Institute, Chicago, IL (March 16-19, 2003).

Devolatilisation and Pyrolysis of Biomasses: Development
and Validation of Structural Models

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Devolatilisation and Pyrolysis of Biomasses: Development and Validation of Structural Models

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