Wildfire Combustion Chemistry

& Smoke

Fire Sciences Laboratory,

Department of Mechanical Engineering,

Technological Educational Institute,

Larissa, Greece

Dr. Miltiadis A. Boboulos

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TABLE OF CONTENTS

1. INTRODUCTION _________________________________________________________1

2. BIOMASS FUEL PROPERTIES AND COMBUSTION _________________________3

2.1. PROPERTIES OF BIOMASS FUEL ___________________________________________ 3

2.2. PYROLYSIS AND ITS PRODUCTS ___________________________________________ 5

2.3. PROPERTIES OF THE BIOMASS COMBUSTION PROCESS ____________________ 7 2.3.1. Flaming and glowing______________________________________________10

2.3.2. Smoke production ________________________________________________11 2.3.2.1. Release of carbon_________________________________________11 2.3.2.2. Particles formation________________________________________12 2.3.2.3. Emission of trace gases and pollutant emissions_________________13

2.3.2.3.1. Nitrogen gases ____________________________________14 2.3.2.3.2. Sulfur emissions (carbonyl sulfide) ____________________15 2.3.2.3.3. Methyl chloride ___________________________________15 2.3.2.3.4. Carbon monoxide __________________________________15 2.3.2.3.5. Methane _________________________________________15

2.3.3. Biomass combustion process _______________________________________16 2.3.3.1. Drying _________________________________________________16 2.3.3.2. Devolatilization __________________________________________17

3. COMBUSTION PROCESS MODELLING ___________________________________18

3.1. TURBULENT COMBUSTION MODELS______________________________________ 19 3.1.1. Turbulent combustion models, based on the “flamelet theory” _____________19

3.1.2. Probability density function models (PDF)_____________________________19

3.1.3. Turbulent models based on the eddy dissipation approach_________________19 3.1.3.1. Eddy Break Up Model (EBU) _______________________________19 3.1.3.2. Eddy Dissipation Combustion Model (EDM) ___________________20

3.2. MODELLING OF THE CHEMICAL REACTIONS _____________________________ 21 3.2.1. Methane oxidation model __________________________________________21

3.2.2. Full mechanism __________________________________________________22

3.2.3. Skeletal mechanism_______________________________________________22

3.2.4. Reduced mechanism ______________________________________________22 3.2.4.1. Four steps reduced mechanism:______________________________22 3.2.4.2. Two steps reduced mechanism ______________________________22 3.2.4.3. One step global reaction mechanism __________________________23

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3.3. MODELLING OF THE TURBULENCE-CHEMICAL REACTIONS INTERACTION ___________________________________________________________ 24 3.3.1. The smallest rate is the limiting _____________________________________24

3.3.2. The series process approach ________________________________________24

3.4. BIOMASS COMBUSTION MODELLING _____________________________________ 25 3.4.1. The energy value of biomass________________________________________25

3.4.1.1. Energy value – basic concepts_______________________________25 3.4.1.2. Ash contents in the biomass ________________________________26 3.4.1.3. Carbon contents __________________________________________26 3.4.1.4. Water contents ___________________________________________26 3.4.1.5. Organic contents _________________________________________27 3.4.1.6. Gas production___________________________________________27 3.4.1.7. Char production: _________________________________________28 3.4.1.8. Tar production ___________________________________________28 3.4.1.9. Thermal cracking of tar: kinetic analysis_______________________29 3.4.1.10. Biomass combustion ______________________________________29 3.4.1.7. Rates of combustion ______________________________________30 3.4.1.8. Metal contents in biomass __________________________________31 3.4.1.9. Biomass devolatilization rates _______________________________32

3.4.2. Model development_______________________________________________34 3.4.2.1. Main assumptions ________________________________________34 3.4.2.2. Mathematical description of the combustion process _____________34

3.4.2.2.1. Moisture evaporation _______________________________34 3.4.2.2.2. Fuel pyrolysis _____________________________________35 3.4.2.2.3. Combustion of the volatiles __________________________35 3.4.2.2.4. Char oxidation ____________________________________36

REFERENCES:_____________________________________________________________38

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1. INTRODUCTION

Forest fires are rather impressive by the power of released elements and by the other hand the inadequacy of the mankind in coping with it. Knowledge of fires, which is gradually accumulated over a very long period has until recently been purely empirical. The main reasons for that fact are: complexity of the process (the geometry of the objects included, its chemical structure, the dynamics of the ambient atmosphere, etc.). Only until recently (recent twenty year form the previous century) scientific methods of fire analysis have been developed. In recent years several research centres made considerable advances in this area of human knowledge - both experimental and experimental [1].

The free fires are wide known around the world, but less investigated due to: • uncontrollable environment in which they occur ; • lack of information for the conditions at which this phenomena happens –atmosphere

conditions ; • unknown properties (in some cases roughly known) of the fuel ; • scarce detailed information for the properties of the combustion process ;

Forest fires, especially large-scale ones result in great amount of money in financial losses annually around the Globe [2]. These fires can locally disrupt complete ecosystems and even produce changes in the meteorological processes. Thus if there are computer models developed to simulate forest fire spread under variety of topographical and vegetation conditions and much more, they should be applicable for example for making fire-fighting strategies [3]. Forest-fires are extremely complicated natural phenomena – it is a collection of many different phenomena, each is itself quite complex. The fire is example of combustion process – unsteady, no homogeneous environment with mass, heat and momentum transport and the details could not be depicted. Thus there are needed great efforts in developing accurate models for the chemical kinetics and related burning rates, heat release rates and flow temperature field.

The free fire processes as well as forest fires are widely spread around the World. Some of them are threats, endangering the environment and the human habitat [2, 4]. Forest fires are known to change the landscape of wide regions of the globe, especially Australia and Central Latin America. These fires are presumably controllable and the expected results are easily achieved. The actual results are far from expectation of the actuators – great amounts of pollutants are released in the atmosphere, the vegetation as well as animal environments are threatened from extinction. Some of the released combustion gases (NOx) are polluting the Earths atmosphere by causing depletion of the protective ozone layer, thus increasing the risk from dermatological cancer of the Earth’s animal habitants and influencing the vegetation. The free fire burning process is accompanied with release of number of pollutant gases, like CO, NOx, hydrocarbons, SOx as well as solid matter – primarily soot [forest fires, principles of fire behaviour].

With the continuing increase in the computer power as well as Internet technology it is becoming possible to make numerical modelling applications in forest-fires prediction, rather then phenomenological models developed so far. The detailed numerical models reveal practical workability in great variety of applications, such as air flow modelling, flow around buildings, automotive applications, and combustion modelling in its wide range of engineering tasks. Parallel supercomputers are being used for solving such problems as their productivity approaches Tflops (1012 flops – floating point operations per second). [5, 6, 7].

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Nowadays even the personal computers (as their power approaches Gflops and the available allocated memory is in the range of gigabytes) are used for implementation of sophisticated and realistic models [5, 8], such as forest fires.

The models of discussion include equations of fluid motion, heat and mass transfer as well as chemical reactions, occurred in a fire process. However the complexity of the entire process does not give opportunity to go in deep details for each item, so reasonable approximations are needed in order to achieve useful processing speeds [9, 10, 11]. Thus the fire flow field modeling implementation is based on well known Navier-Stokes equations with additional models in order to represent turbulence phenomena, species chemical reactions and heat (conduction, convection, radiation) transfer involved, depicted in figure 1.

Figure 1. Fire complex model;

The process of the propagation of forest fires is extremely complex and difficult to depict. Wide ranges of unknown variables are used to describe forest fires: fuel moisture content, type of the biomass and its thermo-chemical properties, wind flow profiles over complex terrains, atmospheric conditions, etc [12]. Various factors affect the fire spread rate, the most important is the local wind velocity and is the most difficult to forecast. The other factors can be evaluated or at least their values vary over a limited range depending on the seasons of the year, the geographic position of the place and the local topography [13].

The fire itself is complex process of fuel oxidation, gas products, soot and ash and heat energy is released as well. Thus the process includes chemistry, heat, mass and momentum transfer and combustion process. That’s why the depiction of process needs knowledge of all these phenomena in order to try to understand the “jungle” of free fires as well as forest ones. Actually the description of the process relies both of the physics of the process as well as accumulated data for real observed fires in order to build a model that tends to depict this extremely complex phenomena.

Forest fires are difficult to describe, because many aspects are hard to depict [3], such as: • forest fuel material is no homogeneous and irregularly distributed; • chemical reactions are complex and radiation properties of the combustion process are

basically unknown; • turbulence of the flow field influences on the entire process; • the combustion process is frequently two-phase flow, i.e. volatiles oxidation and

particle’s char combustion.

The fire process involves hundreds of different materials, but the most important is wood, i.e. biomass. Consequently knowledge of the combusting material is required in order to depict such a complex process. The work presented does not appeal to resolve all the items pointed, but to reveal an approach for investigation of such a complex process with the problem described in details in the following sections.

FLOW APPROXIMATION TURBULENCE CHEMISTRY RADIATION THERMOCHEMICAL

DATA

COMPLEXMATHEMATICAL

MODELBOUNDARYCONDITIONS

GEOMETRY

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2. BIOMASS FUEL PROPERTIES AND COMBUSTION

2.1. PROPERTIES OF BIOMASS FUEL

Photosynthesis process of the vegetation results in the production of structural and non-structural carbohydrates comprising the plant tissues. The plat matter in its variety will be summarized in the name biomass. The components of biomass include cellulose, hemicelluloses, lignin, lipids, proteins, simple sugars, starches, water, HC, ash, and other compounds [Forest fires, B.M. Jenkins]. The concentrations of each class of compound vary depending on species, type of plant tissue, stage of growth, and growing conditions. The contents of most wood material varies as follows: between 41% and 53% cellulose, between 15% and 25% hemi cellulose, and between 16% and 33% lignin. The lignin content of wood is much higher (up to 65%) in decaying wood because cell wall polysaccharides are partially removed by biological degradation [12].

Cellulose is a linear polysaccharide of β-D glucopyranose units linked with (1-4) glycosidic bonds. Hemicelluloses are polysaccharides of variable composition including both five and six carbon monosaccharide units. The lignin is an irregular polymer of phenylpropane units. Plants producing large amounts of free sugars, such as sugar cane and sweet sorghum, are attractive as feedstocks for fermentation, as are starch crops such as maize (corn) and other grains. Lignins are not yet generally considered fermentable, and thermochemical means are usually proposed for their conversion [14]. Typically, 60-80% of the feedstock mass is ultimately fermentable. Combustion process can be applied either to the direct conversion of the whole biomass, or to portions remaining following some sort of biochemical separation such as fermentation. Combustion, unlike the biochemical and some other thermochemical conversion strategies, is essentially non-selective in its use of the biomass, and intends to reduce the whole fuel to set of simple products. This is not to suggest that the complex structure of biomass does not have significant influences on its combustion behaviour [15].

Due to the carbohydrate structure, biomass is highly oxygenated with respect to conventional fossil fuels including HC, such as liquids and coals. Typically 30-40% (weight based) of the dry matter in biomass is oxygen. The principal constituent of biomass is carbon, making up from 30 to 60 wt.% of dry matter depending on ash content [14]. Of the organic compound, hydrogen is the third major constituent, comprising 5-6% dry matter. Nitrogen, sulfur and chlorine can also be found in quantity, usually less than 1% dry matter but occasionally well above these values. The latter are important in the formation of pollutant emissions and sulfur and chlorine. Nitrogen is a macronutrient for plants, and critical to their growth. Certain inorganic elements can be found in high concentrations as well. In annual growth tissues, concentration of the macronutrient potassium frequently exceeds 1% dry matter. In some grasses ad straws, silica is the third largest component, in rice straw for example, silica is 10-15% of dry matter [14].

The proximate and ultimate analysis of selected biomass materials is presented in [16].

Biomass differs from coal in many important ways, including the organic, inorganic, energy content and physical properties, Relative to coal, biomass contains less carbon, more oxygen, more silica and potassium, less aluminum and iron, lower heating value, higher moisture contents, lower density and friability. The depicted comparison between these two fuels reveals that the accumulated knowledge for the coals will be useful in understanding the biomass behavior, but also new knowledge should be achieved in order to properly handle the biomass mater as fuel material [10, 14, 15].

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Biomass is compared with other fuels in the so-called coalification diagram [14]. In the following figure the approximate boundaries between different classes of fuels are shown. The diagram can be used in order to infer the chemical structure and some inorganic fuel aspects.

Figure 2. Coalification diagram showing compositional differences among coals and biomass.

The release of atomically dispersed inorganic material from fuel particle is influenced both by its inherent volatility and the reactions of the organic portions of the fuel. Materials that are inherently volatile at combustion temperatures include derivatives of some alkali and alkaline earth metals, most notably potassium and sodium. Other, non-volatile material can be released by convective transport during rapid pyrolysis. Alkali material plays a central role in both pyrolysis and char oxidation processes. Potassium is the dominant source of alkali in most biomass fuels. Although the total amount of potassium in wood is typically much lower than in straws, the fraction in the ash may be higher [14]. Calcium reacts with sulfur to form sulfates in ways somewhat analogous to potassium, but the mobility of calcium and the properties of the deposits it forms are both more favourable than the ashes formed from straw and grasses.

Chlorine is a major factor in ash formation. Chlorine facilitates the mobility of many inorganic compounds, in particular potassium. Potassium chloride is among the most stable high-temperature, gas-phase, alkali-containing species. Chlorine concentration often dictates the amount of alkali vaporized during combustion as strongly as does the alkali concentration. In most cases, the chlorine appears to play a shuttle, role, facilitating the transport of alkali from the fuel to surfaces, where the alkali often forms sulphates. In the absence of chlorine, alkali hydroxides are the major stable gas-phase species in moist, oxidizing environments, i.e. combustion gases [14]. The composition of biomass are complex, involving six major elements (C, H, N, S, Cl, O) in the organic phase and at least 10 other elements (Si, Al, Ti, Fe, Ca, Mg, Na, K, S, P), not including heavy metals, in the inorganic phase important to ash characterization [14].

The inorganic content of the fuel defines the ash behaviour and especially ash melting temperature [14]. Principally the detailed chemistry of ash formation is not fully developed, the removal of alkali and other elements is known to increase the fusion temperature of the ash. For example the experiments in leaching of alkali metals plus chlorine by simple water washing reveals dramatic improvements in fusion temperature for straw ash – the result is about 80% of alkali and about 90% of the chlorine reduction and thus reduction of the acid gas emissions as well as chlorine facilitation in ash deposition. Principally biomass washing increases the melting temperature of the ash. The potential of decreasing the fusion temperature also exists. There are other impacts of leaching on the combustion behaviour.

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The amount of fuel lost during the pyrolysis stage of combustion increases with increasing hydrogen to carbon ration and, to lesser extent, with increasing oxygen to carbon ration. Typically, the volatiles loss during early pyrolysis of biomass is about 75%. Biomass material consists of polymeric organic compounds, generally described by chemical formula CxHyOz. The actual form of the chemical formula depends on many factors: type of the plant, material conditions – dry or wet.

Figure 3. Cellulose chemical structure, a polymer built from the glucosan monomer [1].

2.2. PYROLYSIS AND ITS PRODUCTS

Pyrolysis is defined as the thermal destruction of organic materials in the absence of oxygen [15, 16, 17]. Biomass fuel as is heated up in atmosphere with absence of oxygen or partially combusted in a limited oxygen supply, produces a hydrocarbon rich gas mixture, an oil-like liquid and carbon rich solid residue. As with coal, pyrolysis is a relatively slow chemical degradation (and reaction) process occurring at low temperatures and is highly temperature dependent. The pyrolysis mechanism of cellulose contents may be represented by two competing reactions – figure 4:

• dehydration (slightly endothermic - with rate R1) ;

• polymer break-up (strongly endothermic – with rate R2) ;

Figure 4. Simplified pyrolysis process mechanism.

The resulting dehydrocellulose is further decomposed to form char and gaseous products in an exothermic reaction with a rate R3. The tar produced is mostly composed from levoglucosan [1] – figure 5:

Cellulose

Dehydrocellulose+ H2O

Tar

Char + H2 + H2O + CO + CO2 + NH3 + ....

R1

R2

R3

H

O

C

C

C

H

O H

H

C

H

O H

O

C

H

C H O H

H

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Figure 5. Levoglucosan chemical structure.

The released levoglucosan is volatile and in the temperature range in question it vaporizes to form light gases that support gas-phase flame. The gases evolved in the dehydration path are partly non-combustible and are produced in small quantities. Therefore this reaction can support only the surface oxidation or “glowing” combustion of char. The yield of levoglucosan in the second reaction indicates that tar evolution results from a radical “unzipping” process of the basic polymer. Physically, the process greatly resembles the coal devolatilization process [18] (well, coal is millions of year’s old transformed biomass). The devolatilization rate and tar production are represented by an Arrhenius type equation:

⎟⎠⎞

⎜⎝⎛ −

= RTE

AR1

exp11 - devolatilization rate , [1/s] ( 1 )

and respectively ⎟⎠⎞

⎜⎝⎛ −

= RTE

AR2

exp22 tar release rate , [1/s] ( 2 ) where : A1, A2 – pre-exponential factors for the corresponding reactions , [1/s] ; E1, E2 – activation energy for the corresponding reactions , [J/(mol.K)] ;

These parameters (A1, A2 , E1, E2) are strongly fuel dependent as well as the conditions at which the reactions are realized, primarily heating rates. There are quite reliable data for a wide range of fuels of interest, but mostly at conditions far from the wild land fire. Thus these data are appropriate to be utilized with having in mind that additional investigation for the influence of these parameters on the model developed.

The other two major components of biomass – hemicelluloses and lignin have less regular structures that cellulose and consequently will show more complex behavior at the heating process. Therefore the overall kinetics of biomass pyrolysis process varies from one species to another but, typically is similar to cellulose.

The demonstration of that fact is that thermal analysis of different biomass show common general characteristics – the observed endothermic region at around 100oC where hygroscopic water is evaporated (the drying process), next as the material is heated up at temperature region of about 200 – 280oC is identified as shallow endothermic (and intensive mass loss due to volatiles release), plateau or slightly exothermic, next the deep endothermic region at about 280-340oC (the ignition and combustion of the volatiles) which changes the strong exothermic behavior at about 350oC [15, 19].

In the burning region, the rate of mass loss proceeds so rapidly that it reaches to its maximal value. The rapid mass-loss is immediately slowed down at temperatures 350 – 450oC. After then, burning rate apparently decreases and consequently some small losses in the mass

C

C

C

H

OH

H

C

H

OH

O

C

H

H2C

H

O

HO

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of the fuel sample continuously goes on as long as particle temperature is increased to about 1000oC – this is the region of slow carbonized residue oxidation. As char combustion process is finished no mass loss is observed and the solid residue consists of mineral matter - ash. The most important characteristic temperatures of a burning profile are ignition temperature and peak temperature [15]. The ignition temperature is fuel temperature at which the burning profile underwent a sudden rise due to volatiles oxidation. The ignition temperatures of samples are determined from the burning profiles, obtained in the laboratory experiments. The burning profile peak temperature is usually taken as a measurement of the reactivity of the sample.

The fuel of concern is biomass, especially forest residues. Biomass is considered to be treated as low calorific fuel and only recently its properties are under investigation, primarily because its CO2 pollution neutral behavior. Furthermore the Kyoto protocol [20] states that up to year 2015 at least 15% of the human kind consumed energy should be replaced with biomass matter, thus reducing the intensity of fossil fuel consumption as well as oil and even nuclear fuel (unfortunately there are countries that still have not signed it). That’s why many laboratories are occupied in achieving properties of the biomass matter. The properties of concern are the proximate and ultimate analyses, principally most of the biomass matter of interest are already investigated. Nevertheless some specific (rare) biomass fuels need to be investigated.

However the achieved laboratory results for the fuel contents, i.e. proximate and ultimate analyses are not enough for characterization of the fuel. Further needed data are drying, devolatilization and char oxidation rates. These data are mostly achieved by TGA (thermo-gravitometric analysis) at specified laboratory conditions. Unfortunately the laboratory rates data are principally quantitative, because of the methodology, primarily because of the low heating rates at which experiment is done. The nature rates of drying, devolatilization and char combustion are far higher that the laboratory achieved. Nevertheless the values are post-adjusted in order to become applicable for modeling.

Dead plant matter accumulated on the forest floor is rich in nutrients and is transformed by microorganisms into humus in which individual plants are no longer identifiable. This process results in increase of the sulfur and nitrogen concentrations due to microorganisms, which utilize these elements in their growth and reproduction [15]. In addition, tree leaves and needles generally have higher composition of N and S than stems and limbs. Nitrogen is one of the most dominant of the macronutrients and thus is of primary interest, because of the large number of nitrogen-based compounds produced at biomass combustion.

Compared to the fossil fuels there is a relative higher content of oxygen in the biomass, which predetermines specific approaches for describing the chemistry of the combustion process.

2.3. PROPERTIES OF THE BIOMASS COMBUSTION PROCESS

Biomass combustion process passes through the following phases of combustion: Preheating, flaming, smoldering and glowing combustion compete for the available fuel and are markedly different phenomena that contribute to the diversity of the combustion products [12]. The characteristics of the fuel (including arrangement, distribution by size, moisture and chemistry) dominate in affecting the duration of flaming and smoldering combustion phases and combustion efficiency. Wild fire occurs through a diffusion flame process in which the fuel from the interior of the flame (i.e. oxygen deficient area) diffuses outward, and the oxygen from the free-air diffuses inward. This results in a narrow envelope around the fuel-releasing

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zone where the oxygen and fuel are mixed at stochiometric level and intensive chemical reactions are proceeded which result in the visible emission of light called flame [12]. The heat energy from the chemical reactions also causes feeds back energy source to the interior of the flame envelope and ahead of the flame envelope. This causes further devolatilization of fuels with low vapor pressures and pyrolysis of solid fuels.

Initial heating of unburned fuel releases the ore volatile components by distillation, which then leads to pyrolysis and fragmentation of polymers and the release of oxygenated organic compounds. Flaming is initiated when there is a source of ignition and the fuel-to-oxygen mixture reaches flammable proportions. Flaming and smoldering combustion are reasonable distinct regimes of the combustion processes that involve different chemical reactions as well as appearance.

Experimental investigation [21] of the reactivities of carbonaceous materials of biomass primarily consists of isothermal and non-isothermal thermo gravimetric techniques. In the following table the proximate analysis for some biomass samples are given:

Table 1. Proximate analysis of the biomass samples.

Sample Moisture, wt. %

Volatile matter, wt.%

Fixed carbon, wt.%

Ash, wt.%

Gross calorific value,

[MJ/kg] Sunflower shell 8.1 76.4 12.2 3.3 16.12

Colza seed 8.4 70.0 15.8 5.8 19.38

Pine cone 9.4 69.0 20.9 0.7 18.65

Cotton refuse 5.4 75.8 12.3 6.5 18.83

Olive refuse 15.6 56.0 8.1 20.3 15.77

A plot of rate of weight loss against temperature while burning a sample under an oxidizing atmosphere is referred to as the “burning profile”. The burning profiles of the biomass samples are shown in the following figures. The first peak observed on the burning profiles of the biomass samples corresponds to their moisture release. After releasing the moisture, some small losses in the mass of the sample occurred due to desorption of the adsorbed gases. A sudden loss in the mass of the samples started at the temperatures between 450 and 500 K, representing the release of some volatiles and their ignition. In the rapid burning region, the rate of mass loss proceeded so rapidly that it reached its maximum value. The rapid loss of mass immediately slowed at temperatures between 600 and 700 K. After this point, the burning rate apparently decreased, and consequently, some small losses in the mass of the sample continued as long as the temperature was increased.

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Figure 6 Weight loss of different biomass samples: ■ sunflower shell, ▲colza seed, ●pine cone, ○cotton refuse, ▫ olive refuse)

as function of the temperature, [K]

Figure 7 Burning profile of olive refuse

Figure 8 Burning profile of pine cone

Figure 9 Burning profile of sunflower shell

Figure 10 Burning profile of cotton refuse

Figure 11 Burning profile of colza seed

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The observation of the applied figures show that although the proximate analysis differ considerably (Table 1), the ignition temperatures of the biomass samples changed in narrow interval (Table 2). It has been observed that an increase in the volatile matter contents of the biomass samples cause, as general tendency, an increase in the peak temperature. The rate of weight loss at the burning profile peak temperature is called the “maximum combustion rate”. Different biomass samples have close values of the maximum combustion rates, the differences can be attributed to the differences in their chemical and physical properties.

Table 2. Combustion sample properties. Sample Ignition temperature

[K] Maximum combustion

rate [mg/min] Peak temperature ,

[K] Sunflower shell 475 5.50 573

Colza seed 423 2.80 535

Pine cone 475 5.20 565

Cotton refuse 423 3.70 598

Olive refuse 473 3.40 537

The presented data for different biomass mater reveals that the burning profiles have qualitative common behaviour and the flaming temperatures are in close range. It can be concluded that common approach could be applied in order to describe the biomass combustion behaviour, considering the ultimate analysis data for the specific biomass material.

2.3.1. Flaming and glowing Flaming combustion dominates during the startup phase, with the fine fuels and surface

materials supplying the volatile gases required for the rapid oxidation reactions to be sustained in a flaming environment. The heat energy from the flame structure and the diffusion and turbulent mixing of oxygen at the surface of the solid fuel promote generation of energy, required to sustain the pyrolysis processes. At the early stages of the flaming phase, the more volatile hydrocarbons are vaporized from the fuels. The later stages of the same combustion phase the cellulosic and lignin-containing cellular materials decompose through pyrolysis. These processes produce the fuel gases that sustain the visible flame structure – homogeneous combustion. Once the pyrolytic reactions no longer produce sufficient fuel gases to maintain the flame envelope, solid carbon and ash are revealed on the solid fuel surfaces. For combustion process to continue, oxygen must reach (through diffuse and turbulent convection) to the surface of the fuel. Diffusion of oxygen and the availability of oxygen at the fuel surface are enhanced through turbulence in the combustion zone and through premixing by oxygen transport at ground level. This allows oxidation to take place at the solid fuel surface and provides routes for heat evolution and energy feedback to accelerate the pyrolytic reactions and volatilization of the fuel gases from the solid matter. The processes ultimately leads to the production of charcoal for which the only combustion occurring is of the glowing type – a surface reaction of oxygen with carbon residue.

There are several features describing the thermal environment and the effect of changing heat load on the early evaporation and the later pyrolysis of fuel:

I. Evaporation of the highly volatile compounds. Condensation or polymerization is not expected for the compounds released that are not in close proximity to the flame envelope;

IIa. Evaporation rate of the highly volatile compounds increases in this zone and the potential for polymers to form increases as bond rupturing takes place for the terrenes;

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IIb. Abundant evaporation of oleoresins occurs with partial oxidation due to the intense thermal environment and extreme chemical bond rupturing resulting from the high-intensity radiant energy income;

III. Penetration of evaporated oleoresins into a high-temperature oxygen-deficient environment with considerable oxidation occurring as molecules diffuse through the flame envelope. Those not undergoing complete oxidation may be fragmented into ethylene units and/or free radicals;

IV. Very high-temperature environment with oxygen depletion occurring as the carbon fragments reach the tip of the flame envelope. The amount of compound oxidation is dependent on the depth of the flame envelope and the amount of ventilation (turbulence). As the flames become taller, the heat feedback to the solid fuel becomes less, and the radiant energy loss becomes greater. The result is that particle formation/polymerization reactions may be increased because of the loss of heat energy within the fuel-rich zone;

V. Recombination takes place with the formation of compounds not found during the evaporation phase or inside the flame envelope due to pyrolysis. Aromatic hydrocarbon molecules are synthesized during this phase of transport;

VI. Products of pyrolysis and glowing combustion are transported across the flame surface;

VII. Transport of products of pyrolysis and glowing combustion completely miss the flame envelope and enter with no additional oxidation;

2.3.2. Smoke production The smoldering combustion phase produces large amounts of particulate matter and CO.

Very low intensity fires of (those in which the flaming combustion phase is barely sustained) produce proportionately higher amounts of particulate matter. Heading fires generally are associated with conditions that produce two to three times as many particles (by weight) as backing fires. Primarily from two processes the formation of particles results:

(1) the agglomeration of condensed hydrocarbon and tar materials ;

(2) mechanical processes which entrain fragments of vegetation and ash ;

2.3.2.1. Release of carbon The vegetation burnout process results in carbon release in the form of CO2, CO,

hydrocarbons, particulate matter, and other substances in decreasing abundance. Researchers often employ a carbon mass-balance procedure in developing emission factors for different fuel conditions. An emission factor is defined as the mass of a specific combustion product released per unit dry mass of fuel consumed and is expressed in kg/kg. Emission factors are highly variable, but generally a large part of the variance can be explained through using a measurement of combustion efficiency for the independent variable. Under a given set of weather and fuel conditions the combustion efficiency is a measure of the overall oxidation capacity for the combustion of fuel. It is a ratio of the mass of carbon released in the form of CO2 to the mass of carbon in the original fuel and ranges from 0.98 for flaming combustion of fully cured grass vegetation with virtually no smoldering combustion to 0.75 for 100% smoldering combustion of deep duff. In order to simplify the calculation of combustion efficiency it is proposed to adopt the use of modified combustion efficiency (MCE), or the ratio of the carbon released as CO2 to the sum of carbon released in the form of CO2 and CO.

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2.3.2.2. Particles formation Wild land fires are a complex form of the diffusion flame process where pyrolysis of solid

fuels produce light gases and vapors that interdiffuse with O2 from the atmosphere. Turbulent mixing of fuel and oxygen is of main importance for the combustion process. The flame characteristics and the chemical processes occurring in the flame zone change as the turbulence intensity increases. Although this has never been completely substantiated, it is believed that there is a level of fire intensity where MCE reaches its highest level (approximately 0.96-0.98 for many fuel types) and particulate matter production is lowest. For very high-intensity fires some of the pyrolysed fuel matter may no longer pass through an active oxidation zone. Sometimes even in lower intensity fires, pockets of unburned, partially oxidized gaseous fuels escape the combustion zone or undergo delayed ignition.

The influence turbulence fluctuations of the of flame on combustion efficiency is not fully understood, however, as the intensity of the combustion process increases and the zone of complete mixing of gaseous fuel gases and oxygen moves farther from the solid fuel, combustion efficiency is believed to decrease and the production of pollutants increases. Because of the increased depth and height of the flame zone, heading fires and area fires create an extended reduction environment in which continued pyrolysis and synthesis of hydrocarbon gases and fragmented particles can occur under conditions of reduced O2 content. Additionally heat energy re-radiated from the particles to the atmosphere can reduce the reactions rates as the unburned gases and particles are convected away from the active combustion zone. Combustion of the particles requires prolonged exposure at high temperatures (Tp>800oC ; Tp–temperature of the particle) in a zone with near ambient concentrations of O2. Intensive premixing seems to reduce the production of fine particles (for particles with diameter dp<2.5 micrometers).

Biomass combustion chemistry plays an important role in the formation and release of particles to the atmosphere. It is well known that fuels with high production of oleoresins smoke profusely when burned. The pitch has high content of terpenes, which are similar to aromatic compounds in structure (five carbon atom building block instead of six carbon atoms which occurs in benzene and some other highly aromatic compounds). These highly volatile compounds have a low oxygen content and during pyrolysis process produce ethylene units which tend to polymerize and form long-chain compounds which, it turn, condense into tar-like substances that coal most particles from fires. It is found that emission factors for particulate matter are inversely related to the oxygen content of the fuel molecules and suggested that cellulose and hemicellulose may produce less particulate matter when burned, due to their high oxygen content, than the very low oxygen content oleoresins. Smoke particles have been measured using sophisticated instruments ranging from DMPS (Differential Mobility Particle Sizer) to methods for sizing particles based on their aerodynamic properties. These instruments have been used on board aircraft to cover the broad range of particle sizes from 0.01 to over 43 µm. The results suggest a very pronounced number concentration peak at a diameter of 0.15 µm. The volume distribution (assuming unit mass density for smoke particles) represents the mass distribution and exhibits a bimodal distribution with peaks at about 0.3 µm and greater than 43 µm.

Emission factors have been measured for a number of different combinations of biomass and weather influences. The empirical data suggest that emission factors for particulate matter range from 4 to more than 40 g/kg for particles less than 10 µm in diameter (EFPM10), for particles without regard to size (EFPM), the range may be 20% larger, and emission factors for particles less than 2.5µm diameter (EFPM2.5) are typically 10% smaller that EFPM10. The difference between EFPM and EFPM2.5 is highly dependent on the fire intensity.

13

The content of particulate matter varies between flaming and smoldering combustion. Particle’s mass may consist of trace elements of potassium, chlorine, sulphur, phosphorus and sodium – principally between 1 and 10%. On a percentage basis, the mass of trace elements contained in particles from smoldering combustion is 10-20% of that from the flaming phase.

Emissions of graphitic and organic carbon are especially important because of the increased absorption of light energy by smoke particles that are high in graphitic carbon content. Absorption of light is due to the black carbon content of the particles. Though graphitic or black carbon is produced proportional to the intensity of fire, it is generally true that emission factors for PM2.5 are inversely proportional to higher intensity burns. The organic fraction of the particles smaller than 2.5µm is as much as 50-70% of the mass of particulate matter for the smoldering phase, but can be lower for the flaming phase emissions.

Further studies of the released smoke release that “young” smoke (less than 2 hours old) in comparison to “aged” smoke (from 2 to 4 days) from biomass fires in the very humid Brazilian Amazon region, the hydrocarbons of fewer than 11 carbon atoms were depleted over time and converted to CO2, CO, and reactive molecular species and likely removed through dry deposition and/or by conversion to particulate matter. Although somewhat contradictory, the argument concludes that individual particle mass increased over time, and it was estimated that 20-45% of the mass concentration of the particles was due to the condensation of organic compounds. The investigations show that most of the active “new” fires are lit between 1:00 and 3:00 pm local time and active flaming is nearly complete in 3 - 4 hours with smoldering combustion is the dominating mode and continues for several days. The organic content of particles produced during smoldering combustion of biomass is approximately 20% higher that the organic content of particles produced during the flaming combustion phase. There are still many issues to be resolved before it can be conclusively demonstrated that condensation of hydrocarbons occurs at higher rates than volatilization in contributing to the mass increase of particulate matter once the smoke is more than a few minutes old.

2.3.2.3. Emission of trace gases and pollutant emissions The products of combustion process of biomass are mainly CO2, H2O but other gases are

released as well – their amount is relatively small, but their presence is important for the properties of the problem and their influence on the environment. These gases are referred as trace gases, such as nitrogen gases, sulphur emissions, carbon monoxide, methyl chloride, and methane and non-methane hydrocarbons.

In the following section the trace gases will be overviewed. Critically related to the properties of biomass are pollutant emissions generated by combustion. Primary pollutants formed are particulate matter (PM), CO, HC, NOx, and SOx. Acid gases, such as HCl, may also be emitted, as may lead and other heavy metals. CO and HC, including volatile organic compounds (VOC) and polycyclic aromatic hydrocarbons (PAH), are products of incomplete combustion. These species are largely controlled by stoichiometry and proper fuel moisture control. PM includes soot, ash, condensed fumes (tars/oils) and sorbed materials including VOC and PAH. Most combustion generated particles are less than 1 µm aerodynamic particle size. Respirable particles of 10 µm or smaller (PM 10) are breathing hazards, as they retained deep in the alveoli of the lung. Mechanically generated particulate matter including carry-over fuel fines and ash particles tend to be fairly large compared to combustion aerosols. Biogenic silica in some materials, such as rice straw, is partly released as fibrous particulate matter which has become of concern recently for lung disease. Crystalline silica, including cristobalite, emitted from some power stations burning high silica fuels such as rice husk (hull), is also a breathing hazard and needs careful control.

14

Emissions of NOx and SOx arise predominately from N and S in the fuel. In most cases of industrial biomass combustion utilization the operating temperatures are low enough that thermal NOx contributes only to small fraction of the total. NOx in combination with HC photochemically leads to the formation of ozone, which is a lung and eye irritant and major problem in urban environments. Ozone is also damaging to plants. SOx are respiratory irritants, and their effects are enhanced in the presence of PM due to transport deep within the lung. Both NOx and SOx participate in the reactions leading to acid rain. Uncontrolled NOx emissions also depend partly on stoichiometry. For HC fuels, NO formation from fuel N occurs on time scales comparable to the HC oxidation, and is known to be sensitive to equivalence ratio, with fuel lean conditions producing high yields and fuel rich conditions producing low yields. Under fuel rich conditions, the relatively fast conversion of fuel C to CO competes for oxygen, leading to a reduced availability of O2 for NOx production. The fractional conversion of fuel N to NOx has been shown to decrease with increasing fuel N concentration for HC fuels, coals and biomass. The declining N to NO conversion is postulated to be due to the formation of a N containing species important to both the production and destruction of NOx.

The following table presents the pollutant emission factors (% dry fuel) for open field burning, commercial biomass-fuelled FBC, and experiments using an entrained flow multi-fuel combustor (MFC) laboratory combustor without pollution control [14].

Table 3 The pollutant emission factors (% dry fuel) for open field burning biomass.

Field fire MFC, stoichiometric ration=0.85 Pollutant content Wood Rice straw Wood Rice straw

CO 5.54 3.22 0.45 0.30

NOx 0.20 0.28 0.19 0.40

SO2 0.01 0.06 0.005 0.035

HC 0.89 0.44 0.04 0.01

2.3.2.3.1. Nitrogen gases The temperatures reached within flame structures of vegetation fires does not exceed

1000oC, which suggest that molecular nitrogen gas, N2, from atmosphere is not dissociated to combine with free radicals within the combustion zone to form oxides of nitrogen – NOx. However several studies have reported the production of NOx from the burning biomass. Nature experiments show that NOx concentrations as proportional to the fire intensity and reach as high as 0.025ppm. Additional research has shown that the production of NOx is proportional to the nitrogen content of the biomass burned. Conversion of fuel-bound nitrogen to NOx can occur readily in oxygen-depleted air. The quantity of fuel nitrogen converted to NOx was found to range from 6.1 to 41.7% for wood and organic soil, respectively. Thus proximate analysis for the nitrogen content is an important measurement to make interpretation between NOx emissions for different ecosystems. The emissions of N2O from combustion of forest fuels showed a small variance for different types of fuels. One of the sources for NOx production is NH3 released by biomass as it is burning, traces of NH3 are measured as well as NOx and N2O. Principally fuel-bound nitrogen is not released in free form, but as NH3 []. In addition, a fraction of the nitrogen remains in the particulate matter. Detailed measurements

15

reveal that NH4 is observed as well. All these data show that at biomass volatilization and combustion the yield of N2 and NOx can be significant, measured per total burned area.

2.3.2.3.2. Sulfur emissions (carbonyl sulfide) Along the nitrogen, sulfur is one of the essential nutrients required in the synthesis of plant

amino acids and other physiologically important substances. Hence, the volatilization and loss of these important nutrients is of extreme interest in sustaining the productivity of ecosystems. Nitrogen can be replaced through symbiotic N-fixation, whereas sulfur is replenished mainly through atmospheric deposition. Very little work has bee done in identifying the form of the sulfur- or nitrogen-containing emissions released during combustion biomass in wild fires, this is not the case in controlled combustion process with biomass feeded furnaces, developed recently [10, 12, 15].

The conducted experiments show that production of carbonyl sulfide yield is proportional to the sulfur content of the fuel. However the release of carbonyl sulfide is extremely sensitive to the thermal environment of the combustion process. Other sulfur-containing compounds were measured as well – H2S, (CH3)2S, CS2, CH3SSCH3 and other unknown mercaptan compounds. The sulfur quantified made up less than 0.25% of the total sulfur released during the combustion experiments. As with nitrogen compounds, the sulfur content of the fuel is highly variable and becomes the dominant characteristic in estimating the release of sulfur compounds.

2.3.2.3.3. Methyl chloride It is suggested as a natural traces unique to the combustion of biomass fuels and seems to

work well for apportioning the impact of residential wood combustion. For open fires it is found that methyl chloride is produced in much greater quantities in the smoldering combustion phase than in the flaming one. Experiments show that there is inverse relation between chlorine content of fine particles and the amount of methyl chloride released and that emission factors for methyl chloride are inversely proportional to the rate of heat energy release intensity. It is found that in most cases, if not all, methyl chloride is produced from the smoldering combustion process.

2.3.2.3.4. Carbon monoxide Carbon monoxide, CO, is the second most abundant carbon-containing gas released during

the combustion process of biomass. Combustion efficiency is nearly perfectly correlated with the production ratio of CO to CO2. It is found that particulate matter concentration is strongly correlated with carbon monoxide concentration (r=0.89). Experiments reveal that the concentration of formaldehyde is correlated with the concentration of carbon monoxide (r=0.93). Generally, emission factors for carbon monoxide on a mass basis are ten times greater that for the fine particle fraction. Emission factors for carbon monoxide range from 40 to over 300 g/kg of fuel consumed.

2.3.2.3.5. Methane Methane and nonmethane hydrocarbons – methane is produced in much larger quantities

during the smoldering combustion phase than in the flaming phase. Emission factors are about two to three times greater for the smoldering phase than for the flaming phase. For example, at an experiment they ranged from 5.7 to 19.4 g/kg of fuel consumed for smoldering phase and the flaming phase emission factor ranged from 1 to 4.2 g/kg. The volatile hydrocarbons are well correlated with methane. Experimental data shows linear relationship between CH4 emission factors and modified combustion efficiency for different fires in diversity of regions

16

(savanna and forest fires for example). In addition to the different slopes of linear regression models, typical modified combustion efficiency values were found to be 0.84 for slash fires in primary forests of Brazil, 0.90 for second-growth deforestation incineration in the same area, and 0.94 for cerrado savanna ecosystems.

2.3.3. Biomass combustion process This process results in complex mixture of gases, and solid particles are released. The

diversity of fuel types results in wide range of fuel chemistry, chemistry of the chemical reactants and products of the combustion process as well as properties and behaviour.

For wild land fires the chemistry of the fuel is rather complex, the fuel elements distribution is random and highly variable. The weather influences are difficult to characterize and quantify, even for one of the main properties of the fuel – its moisture contents. Furthermore wild fires are hardly reproducible in laboratory environment and thus less intensively researched [12, p.56]. Nevertheless several set of experimental approaches could be recognized:

• highly controlled micro combustion and pyrolysis devices ;

• laboratory experiments;

• field-based tower experiments – for studying smoke emissions ;

• airborne studies of full-scale fire burning under ambient atmospheric conditions ;

Biomass endures different stages of variation during heat-up process – drying, devolatilization and char combustion. The intensity of these stages of the entire process strongly depend on the environment conditions – heat-up rates, oxygen partial pressure as well ash contents. These stages of the biomass conversion will be described in details as follows:

2.3.3.1. Drying The drying is energy consuming (exothermic) process and it is considered to be finished

when the moisture contents of the fuel are evaporated. The moisture contents, achieved by proximate analysis are definitive for the description of the entire process. The water content is actually the mass of water, which mechanically conserved in the fuel sample and strictly depends on the environment conditions. At this stage the temperature of the fuel sample rises as heat energy is supplied up to the saturation temperature of water at the ambient pressure. The heat-up of the fuel is evaluated as the rate of the change of its temperature, i.e. [K/s]. At low drying rates (usually 10 – 103 K/s) the water contents are diffusing to the fuel surface and evaporate, as well as released through the pores of the sample. It worth saying that the structure (ash lattice) of the fuel sample is definitive for this process. At these levels of heat exchange the temperature of the sample could be considered constant and homogeneous. At high heating rates (up to 105 – 106 K/s) the moisture contents are released rather intensive and even could evaporate inside the pores of the fuel particle (no homogeneous temperature distribution in the fuel particle volume is observed), thus increasing internal pressure and even burst the solid matter. However this rarely happens, so one could assume more convenient (especially for modeling purposes) process, which occurs at low heating rates and resulting homogeneous temperature distribution. At drying regime the temperature of the fuel sample is relatively low (up to 100oC at atmospheric pressure) and no intensive thermo-destruction of the hydrocarbons proceeded. The energy, consumed for water evaporation in case of forest fires is energy (predominantly supplied by radiation) released during combustion of the biomass fuel

17

and rules as extinction factor for the burning process. This frequently occurs in case of combustion of raw (and thus wet) biomass.

2.3.3.2. Devolatilization When the drying process has finished the biomass fuel consists only of combustible matter

and ash (mineral matter). The combustible matter consists of volatiles, tar and solid carbon residue. The volatile gases are products of thermal degradation of the combustible matter. Due to external heat supplied to the fuel the chemical chains of the complex hydrocarbons are broken and light organic matter – volatiles, is produced as well as tar. There is deep commitment between the heat-up rate of the fuel sample and yield of volatiles – as the heating rate is increased the released volatiles quantity is higher and respectively the tar yield is relatively lower. The thermal degradation is basically exothermic process and three staged of this process could be observed [12]. The energy, consumed for light gases devolatilization is called latent energy of devolatilization. Some authors (10, 11) ignore this energy, when come to build model for the devolatilization process, but principally this heat quantity is “hidden” .into the latent heat for water content evaporation.

⎟⎠

⎞⎜⎝

⎛ −

= RTE

volatilesvolatiles

volatiles

AR exp - devolatilization rate , [1/s] ( 3 )

18

3. COMBUSTION PROCESS MODELLING The combustion process is a complex phenomenon involving simultaneous coupled heat

and mass transfer with chemical reaction and fluid flow [14]. Its prediction for the purposes of design and control requires knowledge of fuel properties and the manner in which these properties influence the outcome of the combustion process.

Computer simulation of combustion processes is a powerful tool for combustion phenomena investigation. Numerical predictions of the behaviour of the flow pattern, flame characteristics, turbulence and heat flux distribution can be used for qualitative as well as quantitative investigation of wild fire burning process. The numerical procedure is based on a complex mathematical model, which includes modelling of the flow, turbulence, chemical reactions and radiative heat transfer. The description of the process is quite a complicated task and intensive research in combustion processes area is still going on. The modelling of chemical reactions is of particular importance since it concerns the complexity of the interaction between the turbulence and chemical kinetics. The phenomena depicted are extremely complex making their mathematical modelling a very sophisticated task. In fact, chemical reactions such as those in combustion processes can not be modelled in their completeness because of several physical preconditions e.g. the great number of simultaneous reactions (i.e.: 225 elementary reactions in case of CH4 oxidizing); the influence of the turbulence on the chemical reaction rate; the influence of the chemistry on the turbulent flow etc. Therefore, the turbulent combustion models developed are based on several assumptions. The present investigation deals with models based on the eddy dissipation approach since they are widely used in the practice.

Principally the problem of the mathematical modelling of turbulent-combustion processes is reduced to the task of modelling the interaction between the turbulence and the chemical reactions. The combustion process in forest fires occurs at conditions of continuous changes in the temperature, concentration of chemical components, velocity and chemical state of the reacting species. Under these conditions the process can be presented mathematically by formulating a complex system of non-linear differential equations, which covers following areas: flow approximation, turbulence, chemistry, heat transfer (radiation, convection and conduction), thermochemical data for the species involved, problem geometry and initial and boundary conditions, and application of complex mathematical model to involve all these models.

For a steady 3D flow the equation describing the transport of the mass fractions Yi can be presented in the following general form [15]:

ΦΦΦΦ =Γ−Γ−Γ−Φ+Φ+Φ R)zY(

z)

yY(

y)

xY(

x)w(

z)v(

y)u(

x~

∂∂

∂∂

∂∂

∂∂

∂∂

∂∂ρ

∂∂ρ

∂∂ρ

∂∂ (4)

where :

u,v,w - velocity components of the flow velocity kwjviuVrrrr

++= ;

x, y, z – cartezian coordinates;

ρ - density;

Φ – common variable (i.e. u, v, w, T, Yi) ;

ΓΦ – diffusion coefficient for Φ; YΦ - can be the mass fractions of fuel, oxidizer, products;

19

ΦR~ - mean reaction rate (in case Φ is YΦ , then ΦR~ is mean chemical reaction rate.

The determination of the chemical reaction rate is the basic problem in combustion processes modelling. The difficulties arise from the non-linear character of ΦR . The reaction rate is a function of the temperature, pressure and mass fraction of the chemical substances, but the mean value of ΦR is not function only of its averaged values. Therefore, in order to determine the reaction rate ΦR , a model describing the chemical reactions should be introduced. There is a large variety of models developed for turbulent combustion modelling. There are more then 100 models known and published in the literature. Their description is a huge task, but the models most widely used for practical predictions can be grouped in several approaches and classified according their development, application and improvement. Some of these models will only be mentioned in the following section and the emphasis will be on applied combustion model – eddy dissipation model (EDM).

3.1. TURBULENT COMBUSTION MODELS

3.1.1. Turbulent combustion models, based on the “flamelet theory” These methods assume that the turbulent reacting flows consist of an ensemble of reaction-

diffusion layers that are continuously displaced and stretched within the turbulent medium. The structure of the flamelets can be approximated by employing the flame sheet model or by assuming equilibrium or partial equilibrium. Several “flamelet” based models for turbulent combustion are developed. Some of them are : Flamelet Surface Density Models, Algebraic model of Bray-Libby- Moss, Model using transport equation for the mean flame surface ,etc.

3.1.2. Probability density function models (PDF) Probability density function models (PDF). Taking into account the stochastic character of

the turbulence it is logical to use the Probability Theory for mathematical describing of the turbulent flow field. Further the method is extended in deriving a transport equation for a joint (for the velocity components and for the scalars) probability density function. Thus becomes possible to define the velocity and the scalar components together. Therefore the joint PDF (JPDF) approach is widely used in turbulent combustion modelling. The idea is that the realistic chemistry, which includes a detailed chemistry, can be presented clearly, without any assumptions for the flame structure. However, the effects from the molecular processes and the pressure fluctuations gradient appear in the equation as conditional expectation, which has to be modelled. Obviously, the transport equation includes many unknown terms. The solution of the JPDF equation increases drastically the CPU time, thus leading to problems with the numerical implementation.

3.1.3. Turbulent models based on the eddy dissipation approach This type of models are widely used in combustion modelling society because of their

capacity to represent the combustion physics, computationally not so expensive as well as achieved results are qualitatively comparable and close to the experimental data.

3.1.3.1. Eddy Break Up Model (EBU) This model was presented by Spalding [Spalding] and widely used in the 1970s. The idea

of the EBU model is based on the following assumptions: combustion proceeds as an infinitely fast reaction; the chemical reaction rate Rt is proportional to the rate of dissipation (ε/κ) of the individual eddies; the whole process is presented as a single, irreversible one-step reaction:

20

[1kg of fuel] + [νFuel kg of oxidizer] → [(νFuel + 1)kg of products] (5)

These assumptions lead to the following mathematical expression for the reaction rate

REBU:

2' fuelEBUEBU YCRκερ= , [kg/(m3s)] (6)

where:

CEBU - model constant,

νFuel - stoichiometric coefficient (amount of oxygen ,required to oxidize 1kg of fuel at stoichiometric condition );

κ - turbulent kinetic energy , [m2/s2]

ε - dissipation rate of the turbulent kinetic energy , [m2/s3] ;

ρ – gas density, [kg/m3].

This equation expresses ideally the fact that the local chemical reaction rate depends on the gas mixture fluctuating components Y`. However, in practice this leads to a number of complications related to defining almost unpredictable variables such as fluctuations. The application of the EBU model is also mostly limited to modelling only pre-mixed combustion [23].

3.1.3.2. Eddy Dissipation Combustion Model (EDM) This model is proposed by Magnussen [Magnussen,Hejertager]. The model develops the

conception of eddy dissipation and overcomes successfully some problems related to EBU. In this model the chemical reaction rate is presented by the mean mass fraction values of the reacting species instead of their fluctuations – actually this is the main advantage of EDM compared to EBU. The main factor influencing the rate of infinitely fast chemical reactions is the diffusion of species. The chemical reaction itself takes place when the reagents have mixed up to the molecular level at high temperature. The chemical reaction rate is determined by the mixing rate, i.e. by the rate of dissipation of eddies. The fuel and oxidant appear as fluctuating intermittent quantities so that a correlation is possible to exist between the fluctuations of the chemical components and their mean values (Y Y≈ '2 ). Thus the reaction rate REDM can be expressed by the eddy decay rate and average mass fraction of the reacting elements:

⎟⎟⎠

⎞⎜⎜⎝

⎛

+=

fuel

products

fu

oxidizerfuelEDMEDM

YBYYAR

ννκερ

1

~,

~,~min , [kg/(m3s)] (7)

where : AEDM = 4.0 - model constants; BEMD = 0.5 - model constants;

fuelY~ - mean value of the mass fraction of fuel compound, [kg/kg];

oxidizerY~ - mean value of the mass fraction of oxidizer, [kg/kg];

productsY~ - mean value of the mass fraction of products, [kg/kg].

Because of its simplicity and testified applicability it is one of the most popular concepts for modelling local reaction rates in practical turbulent combustion systems. This model has

21

the ability to handle premixed, partially premixed and non-premixed combustion with sufficient accuracy.

This model will be used in the development of the complex model for free fire behaviour of biomass.

3.2. MODELLING OF THE CHEMICAL REACTIONS The chemistry of any combustion process is set on many chemical reactions. For example

the process of methane oxidizing consists of a great number of simultaneous elementary chemical reactions which rates depend on the temperature, pressure and mass fractions of the gas mixture. An elementary chemical reaction can be formulated as:

∑ ∑= =

⇔N

i

N

iii

1 1i

"i

' productreactant νν (8)

where : 'iν - stoichiometric coefficient of reactant i ; "iν - stoichiometric coefficient of product i ;

N – number of reacting species ;

The rate of production (consumption) of a specie i is defined as a sum of the forward, (qi) and backward (pi) reactions, where i takes place:

∑=

−==R

jjjijii

reactionchem pqrR1

. )(ρρω , [kg/(m3s)] (9)

where : R, number of elementary chemical reactions ;

'

1

ijrN

i j

jjfj W

Ykq ∏

=⎟⎟⎠

⎞⎜⎜⎝

⎛=

ρ - rate of the forward reaction (10)

''

1

ijrN

i j

jjbj W

Ykp ∏

=⎟⎟⎠

⎞⎜⎜⎝

⎛=

ρ - rate of backward reaction (11)

where ⎟⎟⎠

⎞⎜⎜⎝

⎛−=

RTE

TAk jjjf

j expβ (12)

3.2.1. Methane oxidation model Methane oxidation will be reviewed in order to present developed models for chemical

reactions of CH4 as representative for hydrocarbons. Further the developed models will be applied in more complex problems, such as biomass combustion process.

The process of methane oxidation is well known and therefore several mechanisms for the kinetics can be found in the literature. These mechanisms can be classified as:

22

3.2.2. Full mechanism

Full mechanism describes the interaction between hydrocarbons and the so called nitrogen chemistry. It consists of 225 elementary reactions and 48 participating species. Detailed description of each of these reactions is not necessary when practical engineering problems are considered, considering that their numerical investigation is limited by the computer possibilities.

3.2.3. Skeletal mechanism

Skeletal mechanism is obtained from the full mechanism after analysing the rate of generation and consumption and the dependence of the solution to the boundary conditions. Actually the skeletal mechanism represents a compromise and balance between complexity, accuracy and applicability of the model. Reduced set of 58 elementary reactions for the methane and 38 for the nitrogen chemistry are included. The mechanism can be applied for lean and relatively rich conditions where the local ratio fuel/air is less then 1.4.

3.2.4. Reduced mechanism

The reduced mechanism represents the methane oxidation under ideally stirred reactor and therefore it is of special interest for the current investigation.

The four steps reduced mechanism is derived by the following algorithm:

(1) Choose the full mechanism;

(2) By analyses of the main reactions the chemical scheme is simplified;

(3) By assumption for “steady state” and “partial equilibrium” conditions for the minor species the skeletal mechanism is simplified. Thus reduced system of chemical reaction equations is produced and applied in the combustion model;

3.2.4.1. Four steps reduced mechanism:

CH4 + 2H + H2О → CO + 4H2 (13a)

CO + H2O → CO2 + H2 (13b)

2H + M → H +H +M (13c)

O2 + 3H2 → 2H + 4H2O (13d)

This mechanism is more detailed than one and two step reaction mechanism, but actually is some cases makes the numerical modelling unstable and slow converging, the results are close to the less complicated and more computationally stable two step reaction model without paying the efforts for describing the complex chemistry phenomena.

3.2.4.2. Two steps reduced mechanism Two steps reduced mechanism is proposed by Dryer and Glassman and it is valid for high

temperature oxidation of CH4 and CO, as follows:

CH4 + 3/2O2 kinCHR 4

→ CO +2H2O (14a)

23

CO +1/2O2 kinCOR

→ CO2 (14b)

where the global rates are presented as Arrhenius low as follows : a

Oa

CHTT

CHkinCH YYeAR g +−−= 1/

24

1

44

~~ρ (15a)

bOH

bOCO

bTTCO

kinCO YYYeAR g 2

22)31(/ ~~~2 +−= ρ (15b)

where:

4CHA =1.15x109 , [s-1] – pre-exponential factor for the CH4 chemical reaction ;

ACO = 5.42x109; [s-1] – pre-exponential factor for the CO chemical reaction;

T1 = u

CH

RE

4 = 24444 [K];

T2 = u

CO

RE = 15152 [K];

a = 0.3 ; b = 0.25;

4CHE - activation energy for CH4 chemical reaction , [J/mol] ;

ЕCO - activation energy for CO chemical reaction , [J/mol] ;

Ru – universal gas constant, [J/(mol.K)] ;

The numerical simulations based on the two steps mechanism, depicted with equation (14a) and (14b), show a good approximation of the combustion process. This mechanism can be used for both: initial calculation followed by more detailed calculation of the turbulent combustion and for the complete calculation of the combustion process. Furthermore, the results are quite close to the experimental data and thus reliable applicable in most of the engineering combustion problems.

3.2.4.3. One step global reaction mechanism This model based on the assumption for an infinitely fast reaction where CH4 converts

directly to CO2 and H2O vapour without considering intermediate species. CH4 + 2O2 → CO2 +2H2O (16)

The use of this mechanism leads to several advantages when engineering problems are considered and therefore it is widely used. However when local flame characteristics are of importance the model does not provide the adequate accuracy. Actually it commonly over predicts the temperature field and thus introduces significant error in the numerical investigation.

The most spread approach used in the numerical simulation of turbulent combustion in wide variety of combustion process modelling is the assumption of infinitely fast one step global reaction, where CH4 converts directly to the combustion products. The use of this approach leads to relatively good numerical results for the temperature field. From engineering point of view the flow field as well as temperature fuel are the basic operating parameters of interest. On the other side however, the neglecting of the slow reactions and the related intermediate species leads to less accurate presentation of the complex physical-chemical processes of the combustion phenomena.

24

Actually the chemical kinetics plays a main role in the process of generation and consumption of the chemical species involved in the combustion process. Therefore, including the kinetics into the calculations and accounting the interaction between the turbulence and the kinetics is appropriate way to represent more adequately the combustion phenomena. The validity of the predictions can be improved significantly if the turbulent combustion model includes the complex physical and chemical phenomena like local extinction. The appropriate approach to achieve this is the implementation of the full mechanism of CH4 oxidation. However, this approach is related with some difficulties concerning the necessary computational resources. Therefore the efforts of the researchers are directed mainly to implementation of the reduced mechanisms, which (although are simplified) provide the necessary information for correct and in reasonable time calculation of the CH4 turbulent combustion.

3.3. MODELLING OF THE TURBULENCE-CHEMICAL REACTIONS INTERACTION

The inclusion of the kinetics into the calculation is related to the choice of appropriate model for the turbulent combustion. There are several known techniques for coupling the turbulence and the chemical kinetics, based on the Eddy Dissipation Approach.

3.3.1. The smallest rate is the limiting When the turbulent mixing and the chemical kinetics are considered to happen

simultaneously, it is considered that the limiting factor will be the smallest rate, i.e. the time for the reaction is determined by the time needed of the slowest of turbulent mixing or chemical kinetics phenomena. Thus the effective rate will have the following expression:

),min( .kineticschemturbulenceeffective RRR = [kg/(m3.s)], (17)

where

Reffectivee – effective rate of the chemical reaction in turbulent reacting flow.

3.3.2. The series process approach This approach is appropriate for first order kinetic rates. The reacting species should mix

due to turbulence and once they are well mixed the kinetics are considered. To eliminate the initial composition in the well-mixed zone, the two processes, mixing and reaction are considered in series and a global rate is defined as follows:

kineticschemturbulenceeffective RRR .

111+= , [kg/(m3.s)] (18)

This approach is testified and gives more realistic results and is widely applied in

applications involving combustion modeling. That’s why series approach will be used in development the model for forest fires.

25

3.4. BIOMASS COMBUSTION MODELLING

Biomass investigation is carried out in laboratory scale units in order to simulate the operating conditions of the process of interest. However, it is difficult and expensive to simulate conditions of the full-scale problem and sometimes the obtained results differ much from the experimental data for similar cases. Most researchers used laboratory scale fixed bed units to simulate operation in grate furnaces, because it is difficult and expensive to obtain detailed in-bed data from full-scale units. Furthermore, experimental and simulated results showed that an analogy exists between combustion in a fixed bed and on a grade [H. Zhou]. The same similarity will be used for biomass combustion modelling for forest fires because of lack of detailed data for the process and the similarity of the investigated combustion processes.

The batch pyrolysis process is clearly unsteady [22]. The volatiles contents depend on the pyrolysis conditions and the chemical contents of the organic matter of the fuel. Thermal degradation of the tar results in generation of light gases, thus their contents strongly depend on the heating rates of the pyrolysis process. The unsteady behaviour of the stoichiometric coefficients with respect to time is a reflection of the varying molecular composition of the conversion gas. For example the released volatile gas for wood pellets and wood chips a stoichiometry around CH2.6O1 in the initial stage of the pyrolysis process, and roughly CH2O0.9 in the intermediate stage, and CH0O0 in the final stage – char residue. Experimental investigation of the combustion gases for three different types of wood biomass [18] show that the measured time-averaged stoichiometric coefficients are in good agreement with the stoichiometric coefficients based on the elementary analysis for these fuels. This assumption will be used for the chemistry of the volatiles oxidation process.

A global reaction for the combustion of a biomass fuel in air might take the following form, where the first reactant compound is biomass fuel [14]:

CX1HX2OX3NX4SX5ClX6SiX7KX8CaX9MgX10NaX11PX12FeX13AlX14TiX15 + n1H2O + n2(1+e)(O2+3.76N2) →n3CO2 + n4H2O + n5O2 + n6N2 + n7CO + n8CH4 + n9NO + n10NO2 + n11SO2 + n12HCl + n13KCl + n14K2SO4 + n15C + ....

The inclusion of 15 elements in the empirical formula for the fuel is incomplete. There are many more, some of which are important to the issue of biomass combustion. Heavy metals, for example, have a strong influence on ash disposal, but are not included in the elemental structure above.

The detailed chemistry describing the simple global reaction above is far from understood. Making generalization and engineering recommendation concerning the description of biomass combustion systems is made difficult by the variable composition of biomass , as indicated by the element coefficients for different types of biomass fuels. Although there are many similarities, there are also many differences.

3.4.1. The energy value of biomass

3.4.1.1. Energy value – basic concepts The standard measure of the energy content of a fuel is its heating value, sometimes called

the calorific value or heat of combustion. In fact, there are multiple values for the heating value, depending on whether it measures the enthalpy of combustion , the internal energy of combustion, and whether, for a fuel containing hydrogen, product water is accounted for in

26

vapour phase or condensed phase. The enthalpy of combustion is determined at constant pressure, and so includes flow work. With water in vapour phase, the lower heating value at constant pressure measures the enthalpy change due to combustion. The higher heating value at constant pressure measures the enthalpy change of combustion with water condensed. If the combustion is carried out at constant volume, the internal energy due to combustion with water in the condensed state is the higher heating value at constant volume (the standard value measured with bomb calorimeter), while the lower heating value at constant volume measures the internal energy change with product water in vapour phase. In addition, moisture in the fuel reduces the heating value compared to dry weight determination [18]. Determination of thermal efficiency is often difficult to interpret because the basis for the heating value determination is not reported. Thermal efficiencies must be reduced to the same basis for direct comparison.

There are many formula proposed to calculate the heating value, for example:

HHV = 354.68*C + 1376.29*H + 71.26 – 15.92*Ash – 124.69*(O + N) , [19];

where:

HHV – higher heating value, [kJ/kg]

C,H,O,N, Ash – mass fractions of the elements, achieved by proximate and ultimate analysis of the fuel;

The following table show comparison of calculated and measured HHV for biomass materials.

Table 4. Elemental composition of tar obtained at 500 oC [24.]

HHV , [kJ/kg] Biomass material C H O Measured Calculated Woods 53.9 6.8 39.3 22.196 23.647 Coconut shells 57.3 6.3 36.4 24.223 25.214

3.4.1.2. Ash contents in the biomass The heating value of biomass can be partially correlated with ash concentration – woods

with less than 1% ash typically have heating values near 20 MJ/kg, each 1% increase in ash translates roughly into a decrease of 0.2 MJ/kg, because the ash does not contribute substantially to the overall heat released by combustion, although elements in the ash may be catalytic to the thermal decomposition.

3.4.1.3. Carbon contents Heating value can be correlated with carbon concentration, with each 1% increase in C

elevating the heating value by approximately 0.39 MJ/kg for woods and wood pyrolysis products.

3.4.1.4. Water contents Fuel moisture is a limiting factor in biomass combustion due to its effect on heating value.

The combustion reaction is exothermic, the evaporation of water strongly endothermic. The autothermal limit (self-supporting combustion) for most biomass fuels is around 65% moisture content wet basis (mass of water per mass of moist fuel). Above this point, insufficient energy is liberated by combustion to satisfy evaporation and product heating [20].

27

3.4.1.5. Organic contents Cellulose has a smaller heating value (17 MJ/kg) than lignin (26.7 MJ/kg) because of its

higher degree of oxidation. Other compounds, such as HC in the fuel with lower degrees of oxidation, tend to raise the heating value of the biomass. Coals and HC liquids in general have heating values greater than those for biomass because of lower degree of oxidation. Some lower rank coals have heating values nearly identical to biomass.

3.4.1.6. Gas production The total volume of gas produces is illustrated in the following figure. Sharp increase of the

gas volume is observed above 500 oC. Straw appears to yield more gas than the other tested biomaterials, namely wood and coconut shells [21]. The low thickness of the wall of the straw wisp, compared with the others biomass materials, results in a higher heat transfer and hence a higher rate of pyrolysis, which is favourable to gas and tar production. Figure 12 shows the gas production as function of the gasification temperature for different biomass materials – the gas yields are quite close for the investigated materials, which reveal opportunity for applying common model with slight modification of model’s constants.

Figure 12 Gas production as a function of temperature

The heating value of the gas fraction stabilizes above 700 oC, at a value around 15-16 MJ/Nm3. The composition of the gas fraction versus temperature between 500 and 900 oC does not vary a lot with the kind of the following tested materials – wood, straw and cocnut shells [L.Fagbemi]. The concentrations of CH4 and C2Hx reach a maximum value at about 750 oC. A regular decrease in CO2 concentration with temperature occurs with a simultaneous increase in CO and H2 concentration. High temperatures are known to favour the production of H2 to the detriment of higher hydrocarbons which are dehydrogenated by thermal cracking. The evolution and CO2 concentrations are consistent particularly when considering the heterogeneous gas-solid reaction at the thermodynamic equilibrium (C + CO2 = 2CO), an increase in the temperature results in al larger in a larger concentration in CO. The composition of the yields of the gas is presented in the following table.

28

Table 5 Yields of the major gases (in 5 volume), [23].

Temperature, T [oC] Gas compound

Biomass material sample

400 500 600 700 800 900

Wood 34.2 39.7 42.5 44.3 50.2 53.5 Coconut shell 31 35.0 38.1 40.1 44.2 -

CO

Straw - 35.0 37.7 41.0 48.1 53.5 Wood 51.9 36.6 23.0 16.7 9.1 5.0 Coconut shell 53.1 42.2 28.7 17.9 9.8 -

CO2

Straw - 40.7 30.0 15.8 8.4 4.5 Wood 1.3 7.6 10.8 15.5 20.8 25.3 Coconut shell 1.0 5.4 12.4 18.5 23.5 -

H2

Straw - 7.4 12.8 19.2 23.4 24.6 Wood 9.3 12.8 16.5 16.1 14.2 12.1 Coconut shell 10.2 13.2 16.8 17.2 15.8 -

CH4

Straw - 11.8 13.0 15.3 13.7 12.1 Wood 3.3 3.3 7.2 7.4 5.8 4.1 Coconut shell 4.7 4.2 4.0 6.3 5.3 -

C2Hx

Straw - 5.1 5.5 8.7 6.5 5.5

3.4.1.7. Char production: The yield in solid residue regularly decreases with increasing temperature [L.Fagbemi]. At

900 oC it is between 21 and 30 %, depending on the type of the fuel. The elemental compositions of solid fractions are presented in the following table.

Table 6 The elemental compositions of solid fractions [23].

Biomass material sample

Temperature of the sample C H O Ash HHV ,

[kJ/kg] 500 88.51 2.78 8.12 0.59 34.268 700 93.22 1.09 4.6 1.09 34.043 Wood 900 93.18 0.62 5.1 1.10 33.320 500 87.09 2.6 8.88 1.43 33.408 700 91.83 1.05 5.71 1.41 33.352 Coconut shell 900 92.02 0.7 5.55 1.73 32.953 500 69.38 2.23 9.82 16.25 27.088 700 71.7 1.07 13.12 16.43 24.254 Straw 900 71.63 1.15 9.86 17.36 25.553

3.4.1.8. Tar production The tar production evolution is similar for the investigated biomass samples. The quantity

of tar reaches a maximum value at about 500 oC and then drops with increasing temperature. At temperatures higher than 600 oC the secondary reactions (i.e. tar cracking) prevails, leading to a larger amount of gas. Moreover, the cracking of tar improves the energetic content of the product gas. The heating value and therefore the elementary composition of the recovered tar depends on the nature of the raw biomass. The experiments show that the secondary reactions play a major role in the production of pyrolytic oil.

29

3.4.1.9. Thermal cracking of tar: kinetic analysis Tar cracking produces a purified gas. Experiments show that thermal cracking increases the

yield of gas, but has actually no effect on the composition of the gas except at higher temperature (T>700 oC), where an increase in hydrogen is observed. The thermal cracking of tar is effective above 500 oC - at these temperatures, the yield of tar reaches a maximum value.

3.4.1.10. Biomass combustion Biomass consists of relatively higher content of oxygen than the fossil fuels. Thus the

combustion process needs air for reaction, less diluent in the form of atmospheric nitrogen must be heated along with combustion products to achieve the adiabatic flame temperature (because N does not participate in the primary oxidation reactions). Stoichiometric air fuel rations for HC fuels are typically between 14 and 17, for biomass they are 4 to 7, the lower values due largely to the higher O2 contents of biomass. Adiabatic flame temperatures for biomass (dry basis) are typically in the range of 2000 to 2700 K (for comparison CH4 adiabatic temperature is approximately 2300 K and its higher heating values of CH4 is 55.6 MJ/kg – about 3 times than of wood). In the following figure is presented the relative values of standard heating value for range of fuels.

Figure 13 [14] Relative values of the standard heating value and the heating value (heating value divided by the mass of products, or equivalently the mass of air and fuel). The values shown are

relative to a bituminous coal (bituminous coal 1).

The versatility of the heating values (as well as the proximate and ultimate analysis of the fuels) reveals that the combustion process is complex and no common combustion model could be applied.

Pyrolysis if lingo-cellulosic biomass is very complex process of interdependent reactions; nevertheless it can be reduced to the reaction illustrated in the following figure, universally known as the Broido-Shafizadeh mechanism.

30

Figure 14 Overall reaction mechanism.

Secondary reactions are related to the thermal degradation of volatile tars. Strong interactions occur during secondary reactions. Thus, it was well established, that more solid char is formed if the volatile compounds constituting tar are confined within the solid matrix, by increasing the pressure or by slowing down the heating rate. The distinction is commonly made between fast and slow pyrolysis. Fast (flash) pyrolysis is performed on a coarse material or at low heating-rates yielding a solid char of up to 35%. Concerning the thermal degradation of biomass materials, most of the investigations focused on their major component: the cellulose. The decomposition of cellulose at low temperature leads to two groups of basic compounds :

• monomeric volatile sugars, such as levoglucosan, resulting from a total depolymerisation of cellulose ;

• partially-depolymerized compounds, called anhydrocellulose, which are precursors of the residual solid char;

The subsequent degradation of the primary basic compounds at higher temperatures leads to products distributed among various fractions or physical phases: solid char, light gas, water fraction and tar fraction. A knowledge of the kinetics of pyrolysis reactions is useful for the biomass combustion modelling. For pure cellulose, the kinetics of the primary reactions have been extensively studied. By comparison, the secondary reactions of tar decomposition are less well understood.

3.4.1.7. Rates of combustion The rates at which biomass fuels burn depends on a number of physical phenomena. Two

predominant factors are the rates of heat transfer and the kinetic rates of reaction. Biomass particle size dominates the influence of heat transfer, with small, thin (thermally thin) particles heating rapidly and coarser, thicker (thermally thick) particles heating more slowly. Combustion occurs both in the gas phase with the burning of volatile materials released through pyrolysis of the fuel upon heating, and heterogeneously in the solid phase as char oxidation. The burning of volatiles is generally quite rapid and follows as fast as volatiles are released, the oxidation of the char occurs much more slowly. The residence time of the volatiles in the combustion region is therefore important to the total conversion attained through combustion as well as emissions.

Biomass

gas

Tar

Char

Light gas

char

Primary reactions (endothermic)

Secondary reactions (exothermic)

31

Fundamental to the combustion rate are the rates of fuel pyrolysis and char oxidation. The standard method of measuring these rates is via dynamic thermogravimetric analysis (TGA), whereby a small sample of the fuel (5-15 mg typically) is heated at a controlled rate in a controlled atmosphere while simultaneously recording weight, time, and temperature. Other techniques are also employed. The resulting thermogram has a characteristic shape for biomass. Starting from room temperature, the sample is observed to dry (if the sample contains moisture which is normally the case, biomass being hygroscopic, and extreme care is needed in handling to achieve a bone dry sample in the TGA) with a small weight loss up to about 150 oC. Details of the process are shown in section 2.2. (Pyrolysis and its products) of the report. The shape of the thermogram (the conversion curve) is dependent on a number of factors, including the type of fuel, the atmosphere (oxidative, reducing, inert), and the heating rate (for most apparatus this rate is rather low at 2 K/s or less, whereas full scale combustion processes in combustors as well as free fires, may heat fuel particles at 100 – 1000 K/s or more). From the thermogram, kinetic parameters can be determined by which the overall rate of reaction can be predicted. The following figure shows dimensionless thermogram for conversion of rise straw

Figure 15 Conversion of rice straw in nitrogen at 1.7 [K/s] by dynamic TGA – experimental data and three component model predictions [B.M. Jenkins].

A multi-component kinetic model for prediction of the actual conversion consists of three simultaneous component reaction models employing first order Arrhenius kinetics and based on the mass fractions of hemicellulose, cellulose, and lignin, are superimposed to yield the total conversion[17]. Such multi-component models have proved useful in predicting the overall kinetics behaviour of biomass fuel in oxidative, reducing, and inert atmospheres, although the fitting technique is not entirely straightforward.

3.4.1.8. Metal contents in biomass Metals in biomass are known to have an effect on reaction rates, and are thought to be

catalytic to pyrolysis. This has recently been observed with water leached straw, as in seen in the following figure:

32

Figure 16 Rate of weight loss under dynamic TGA for rice straw in air at 1.7 [K/s]. The leached straw was soaked in distilled water for 24 hours.

The figure shows the weight rate loss as s function of temperature. There exists a define kinetic shift for the leached material relative to the fresh, untreated straw. Although the activation energy for the leached material is found to be lower than for the untreated materials in the main stage of pyrolysis, the frequency factor is also lower, resulting in a slower overall rate of reaction. The result is consistent with what is known about the effects of alkali-chlorides on the pyrolysis rates of biomass. However, under isothermal heating, the emission rate for volatiles has been observed to terminate earlier with the leached material than for the untreated material. The ignition requirements are lower for leached straw compared to untreated straw (which can be observed quite readily in case of rice straw by suspending straw vertically and igniting from below). Chlorine is known to retard flame propagation in polymeric materials (e.g., polyvinylchloride) by terminating free radicals chain reactions. Chlorine is leached from biomass by water, and the burning phenomena observed may be related to the role of chlorine in flame suspension. Much remains to be understood about the chemistry of biomass combustion.

3.4.1.9. Biomass devolatilization rates By analogy to coal combustion, the combustion of biomass can be considered as three

steps: devolatilization to char and volatiles, and combustion of volatiles and char. A number of parameters are required as inputs to existing CFD particle combustion models, such as devolatilization yields and rates, composition of volatiles, amount of char formed and char burning rates. In the following table proximate and ultimate analysis for wheat straw and Pittsburgh No 8 coal are presented, as well as input parameters for single step Arrhenius type devolatilization rate model, applicable in CFD calculations [23].

33

Table 7 Biomass and fossil fuel properties

Wheat straw Pittsburgh No 8 % moisture 8.0 % moisture 1.4

% volatiles matter 71.7 % volatiles matter 31.1 % fixed carbon 15.1 % fixed carbon 56.2

Proximate analysis

% ash 5.2 % ash 11.3 %C 47.7 %C 82.6 %H 6.0 %H 4.9 %O 44.4 %O 8.8

Ultimate analysis (daf*)

%N 0.5 %N 1.6 Calorific heating value (daf) , [MJ/kg] 19.25 34.18

Devolatilization model parameters

Products yields Predicted Experimental Predicted ExperimentalChar yield (% daf) 25.8 26.6 51.8 51.0 Tar yield (% daf) 0.0 26.2 Gas yield (% daf) 68.9 18.07 Light hydrocarbons 5.3

73.4 3.93

49.0

Activation energy E , [kJ/mol] 239 229 Pre-exponential factor A , [1/s] 9.1x1013 2.3x1014 Char combustion model parameters **

%C 68.17 %C 95.14 %H 15.12 %H 0.78 %N 2.90 %N 1.96 %O 13.81 %O 8.81 Wheat straw Pittsburgh No 8 Char burning rates Activation energy, [kJ/mol] Activation energy, [kJ/mol] Low temperature 78.3 - High temperature 46.0 108.9 Pre-exponential factor A, [1/s] Pre-exponential factor A, [1/s] Low temperature 9.4x103 - High temperature 8x10-7 9.04x10-6 * daf – dry ash free ** the char ultimate analysis data is predicted by FGDVC

The presented data reveals similarities of the properties of biomass and fossil fuel. However, relative to the coal, the straw devolatilises more rapidly, produces a higher yield of volatiles (mostly CO and H2) and consequently has a shorter ignition delay. The set of data

34

were applied in CFD model [23] and the results are compared with experimental data. This information will provide useful insights into the methodology of biomass combustion modelling.

3.4.2. Model development

3.4.2.1. Main assumptions

• The combustion process is described by homogeneous reactions of the volatiles oxidation and char combustion as heterogeneous reaction.

• The gas is described as ideal gas, [H.Zhou et al.]

• Based on experimental observation, the effects of volume reduction during the drying, pyrolysis, and combustion are neglected, [H,Zhou]. Furthermore, the fire bed is stationary at low airflow rates.

• The fuel is composed of C, H, O. The gas-phase species included in the model is CO, CO2, H2O, O2, H2, CH4, higher hydrocarbons, tar (described by CxHy and CHmOn respectively) and inert gas N2.

3.4.2.2. Mathematical description of the combustion process The biomass combustion process may be divided into four successive or overlapping sub-

processes: moisture evaporation, volatile/char formation, volatiles combustion, and char particles oxidation. A mathematical description for each process is provided in the following sections.

3.4.2.2.1. Moisture evaporation Biomass usually contains moisture either as liquid water stored in the pores due to capillary

forces or as water bound to the biomass structure by ultra-molecular forces. In some cases, the process is assumed to take place instantaneously or to be diffusion limited. The later treatment together with a Clausius-Clapeyron expression for vapour pressure at the solid surface is used for describing the rate of moisture release from the solids:

)(2)(22

gR

l OHOH OH⎯⎯ →⎯ , where:

).(.222

gOH

sOHdOH YYSkR −= - volumetric vaporization rate

kd- mass transfer coefficient;

S – specific particle surface area (particle surface area per unit volume);

( )2,

22inpp

fuel

ps rrr

S −=ρρ

ρs – bulk density of the biomass, [kg/m3];

ρfuel –density of the fuel particle wall, [kg/m3];

rp – the external radius of the fuel particle, [m];

rp, in – the internal radius of the hollow fuel particle (if hollow, for example straw), [m]; s

OHY2

- mass fraction concentration of the moisture at the particle surface, [-];

gOHY

2- mass fraction concentration of the moisture in the gas flow, [-];

35

3.4.2.2.2. Fuel pyrolysis Compared with coal, biomass contains higher content of volatile matter. The volatiles are

composed mainly of CO, CO2, H2, CH4, CxHy, CHmHn and other trace compounds. Biomass pyrolysis may be simply described as one-step global reaction:

Biomass fuel → volatiles + char Volatiles = αgas + βtar Gas = γ1CO + γ2CO2 + γ3CxHy + γ4H2 + γ5CH4

The rate of formation of volatiles from biomass devolatilization is taken from an Arrhenius type of the following expression:

Rvol=kvol.mvol – devolatilization rate , [kg/s];

where

kvol – constant of the rate of devolatilization , ⎟⎟⎠

⎞⎜⎜⎝

⎛−

= sTvolk

1660010 exp10.56.1 , [1/s];

mvol – mass of the volatiles remaining in the biomass particle , [kg] ;

γi – mass fraction of different species formed during biomass pyrolysis , [-] ;

Ts – temperature of the solid fuel, [K] ; The yield and evolution patterns of the volatile products are a function of temperature, to

miner extent-heating rate and particle size, etc. The volatiles composition mass fraction differ for biomass fuels, the data are obtained by laboratory experiments and is obtained from the literature. For simplification, hydrocarbons such as acetaldehyde (CH3CHO), acetic acid ( CH3COOH ) and other very minor compounds are treated as tar. The yields of different pyrolysis gas are presented in the following table:

Table 8 Volatiles & Gas contents, mass fraction

Volatiles contents, mass fraction [%]

tar Gas 71.65 28.35

Gas compounds mass fraction [%]

CO CO2 CH4 CmHn H2 28.8 63.0 3.5 3.5 1.2

3.4.2.2.3. Combustion of the volatiles Combustion of volatiles, particularly tar, is an important process in biomass combustion.

Tar is a complex mixture of condensable hydrocarbons. The amount and composition of tar that form from biomass pyrolysis depend on: type and properties of the biomass (moisture, particle size) and pyrolysis conditions (e.g. temperature, heating rates). For simplification, tar is modeled as hydrocarbons CH1.84O0.96. The tar is oxidized to produce CO and H2O: CH1.84O0.96 + 0.48O2 → CO + 0.92H2O

The kinetic rate for tar oxidation is obtained by the following expression:

36

296.084.1

5.09650

5 exp..10.9.2 OOCHT

etar YYTR e⎟⎟⎠

⎞⎜⎜⎝

⎛−

= - tar kinetic reaction rate, [mol/(m3.s)] where sfe TTT )1( αα −+= , (Tf≤Ts) and Te=Tf , (Tf>Ts)

α – weighting factor, α = 0.5

Te – mean temperature at which the reaction rate is calculated, [K] ;

Tf – temperature of the gas, [K] ;

96.084.1 OCHY - tar mass fraction , [-];

2OY - oxygen mass fraction, [-] ; The species produced are oxidized to form H2O and CO, CO is then converted by further

oxidation to form CO2. The kinetic rates for H2, CH4, CxHy (C2H6 is instead of CxHy) are presented in the following table:

Table 9 Combustion of the volatiles

Reaction Reaction rate, [mol/(m3.s)]

Kinetic constant [1/s]

OHOH 222 22 →+ 2222

5.1OHOHH YYkR =

⎟⎟⎠

⎞⎜⎜⎝

⎛−

= fTH Tk

3420

23

exp8.512

OHCOOCH 224 223

+→+ 8.07.0

2444 OCHCHCH YYkR = ⎟⎟⎠

⎞⎜⎜⎝

⎛−

= fTCHk

24157

10 exp10.6.14

OHyxCOOyxHC yx 22 242+→⎟

⎠⎞

⎜⎝⎛ ++ 2OHCHCHC YYkR

nmnmnm=

⎟⎟⎠

⎞⎜⎜⎝

⎛−

= f

nm

TfHC Tk

20131

8 exp10.7.2

2221 COOCO →+

5.05.022 OHOCOCOCO YYYkR =

⎟⎟⎠

⎞⎜⎜⎝

⎛−

= fTCOk

15098

7 exp10.25.3

3.4.2.2.4. Char oxidation The char forms as volatiles escape from the biomass particles. The reactivity of biomass

char not only depends on the properties of the fuel and the pyrolysis conditions, but also on the mineral content such as potassium. The primary products of char combustion are CO and CO2. The char oxidation reaction is:

22 121121 COCOOC ⎟⎠⎞

⎜⎝⎛ −Θ

+⎟⎠⎞

⎜⎝⎛

Θ−→

Θ+ where

Θ - stoichiometric ratio for char combustion,

c

c

r

r1

21

11

+

+=Θ , where

rc – the ration of CO – CO2 formation rate, which can be estimated by :

37

⎟⎟⎠

⎞⎜⎜⎝

⎛−

== STc CO

COr3300

2

exp12

The char combustion rate is controlled by mixed gas film diffusion and chemical reaction. The film diffusion is taken into account with a correlation for gas flow through combustion volume. The combustion volume is modelled as packed bed with appropriate porosity.

⎟⎠⎞

⎜⎝⎛ += 368.082.0 Re

365.0Re

765.0kJbε where

bε - the bed porosity ;

f

Pff dVν

ρ=Re - Reynolds number, [-] ;

dP – biomass fuel particles diameter , [m] ; Vf – gas velocity , [m/s] ; J – factor, defined as follows:

⎟⎟⎠

⎞⎜⎜⎝

⎛=

Re31

Sc

ShJ where:

2O

pd

Ddk

Sh = – Sherwood number, [-] ;

2OD - molecular diffusion coefficient of O2 in the air ;

( )2Of

f

DV

Scρ

= – Schmidt number, [-] ;

38

REFERENCES:

1. L. Fagbemi, L. Khezami, R. Capart, “Pyrolysis products from different biomasses: application to the thermal cracking of tar”, Applied energy, 69 (2001), 293 – 306.

2. H.Zhou, A.D. Jensen, P.Glarborg, P.A.Jensen, A.Kavaliauskas, “Numerical modeling of straw combustion in a fixed bed” Fuel, 84 (2005), 389-403.

3. J. M. Jones, M. Pourkashanian, A.Williams, D.Hainsworth, “A comprehensive biomass combustion model”, Renewable energy 19 (2000), 229-234.

4. Johnson E. A., Miyanishi K. Forest fires, behavior and ecological effects, 2001. Academic Press.

5. B.M. Jenkins, L.L. Baxter, T.R. Miles Jr., T.R. Miles, “Combustion properties of biomass”, Fuel Processing Technology, 54 (1998) 17-46.

6. Warnatz J, Maas U, Dibble R. W. Combustion, Physical and chemical fundamentals, Modeling and simulation, Experiments, Pollutant formation. 4rth Edition, 2006. Springer, New York.

7. Brink; P. Kilpinen; M. Hupa; L. Kjäldman Study of Alternative Descriptions of Methane Oxidation for CFD Modeling of Turbulent Combustors Combustion Science and Technology, Volume 141 Issue 1 - 6 1999, Pages 59 – 81.

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The book presents the main aspects

involved in the ignition and behaviour of

biomass materials in fires taking place in an

evenly distributed vegetation. At present,

research relating to forest fires is focused on the

development of models based on detailed

descriptions of the physical nature of processes

taking place. This involves both in-depth

experimental studies but also employs methods

for describing the variety of phenomena

observed in this multidisciplinary area: heat

transfer processes between individual phases

and within each phase; decomposition of solid

vegetation particles and mass transition into the

gas phase; chemical processes of gas-type of

combustion; and surface reaction.

Reviewed are basic approaches for

modelling the heating up, ignition and

vegetation burning Thermal decomposition of

the vegetation comprises the drying – an

endothermic process of evaporation of

moisture; and devolatilization – a process of

releasing the main combustible fractions,

volatiles, char and tar. Vegetation combustion

involves the oxidation of these three basic

products accompanied by the release of heat

which maintains the processes of thermal

decomposition and fire spread. Section 3 and 4

also present the basic reaction models and

chemical reaction sets used for the modelling of

the combustion; these are primarily based on

the oxidation of hydrocarbons and methane in

particular.

Dr. Miltiadis A. Boboulos

Wildfire Combustion Chemistry & Smoke