effect of particle size on the burnout and emissions of ... · particulate matter from biomass...

Effect of Particle Size on the Burnout and Emissions of

Particulate Matter from Biomass Combustion in a Drop

Tube Furnace

Vera Sofia Branco Lopes

Thesis to obtain the Master of Science Degree in

Mechanical Engineering

Supervisor: Prof. Mário Manuel Gonçalves da Costa

Examination Committee

Chairperson: Prof. João Rogério Caldas Pinto

Supervisor: Prof. Mário Manuel Gonçalves da Costa

Member of the Committee: Dr. Abel Martins Rodrigues

May 2016

ii

Acima de tudo… para mim!

Para a Lina e para o Franklim…

E para a Dália! Do fundo do coração!

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Acknowledgments

Firstly and foremost, I wish to thank my supervisor, Professor Mário Costa, for his support, orientation

and friendship throughout the course of this project.

I wish to thank Cláudia Casaca and Ulisses Fernandes for their amazing support and availability during

the experiments and many helpful discussions.

I would also like to thank Miriam Rabaçal for many helpful discussions, to Manuel Pratas for all the

technical support on the laboratory during the experiments and to Rita Maia for her friendship and

support in some of my less-motivated moments.

I would also like to thank my other colleagues of the Combustion Laboratory for their support and

assistance during all the stages of this project, namely Isabel Ferreiro, Afonso Ferreira, Gonçalo

Guedes, André Moço, Tomás Botelho, Tomás Prudente, Paula Martins, Sandrina Pereira, Nuno Barbas

and Ana Filipa Ferreira.

To all of my friends from BEST for all the opportunities given along all these years to grow as a person

and as a professional.

To all my friends, with a special mention to Sérgio Potra, Diogo Ferreira, Sílvia Carvalho, Pedro

Martinho, Luis Oliveira, Joana Correia and Gonçalo Guerreiro for all the support and affection throughout

my entire life and, in particular, along the course of this dissertation. Without you, the journey would

have been much harder!

Finally, I wish to express my deepest gratitude to my parents, to my brothers João and Pedro, to Ricardo

Antunes and Ricardo Miguel, to my grandparents, Lina and Franklim, to my godfather Frankie, to my

aunt Ana Sofia and the kids for all the support and guidance throughout my entire life.

Last but not least, to Dália and to Joca. I am sure that, wherever you are, you are very proud of my

achievement.

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Abstract

Milling and grinding biomass fuels for pulverized combustion in industrial furnaces can be very

expensive. This study aims to evaluate the influence of the particle size on the burnout and emissions

of particulate matter from biomass (wheat straw and rice husk) combustion in a drop tube furnace. To

this end, three narrow size classes were established for each biomass fuel; specifically, 100-200 µm,

400-600 µm e 800-1000 µm. Subsequently, all biomass fuels, including the original biomass particle

size distributions, were burnt in a drop tube furnace at 1100 ºC. The results reported include profiles of

temperature, burnout and particulate matter (PM) concentration and size distribution measured along

the DTF. In addition, selected PM samples for all biomass fuels were examined in a scanning electron

microscope. The main conclusions from this study are: i) PM emissions are higher for wheat straw than

for rice husk, being the secondary particle fragmentation more evident on small to intermediate particle

size classes (100-200 µm and 400-600 µm), ii) Ca and P tend to be retained in larger particles, while K

and Cl present higher concentration in the fine PM, and iii) from combustion efficiency and PM emissions

point of view there is no benefit to separate pulverized fuels in narrow particle size classes.

Keywords

Drop tube furnace, biomass, burnout, particle size, particle fragmentation

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Resumo

O processo de moagem e peneiração de combustiveis sólidos como a biomassa em fornalhas

industriais pode ser muito dispendioso. O presente trabalho pretende avaliar a influência do tamanho

inicial das partículas na oxidação do residuo carbonoso e na emissão de particulas (PM) na combustao

de biomasa (palha de trigo e casca de arroz) num reactor de queda livre. Para este fim, três classes de

tamanho de partículas foram estabelecidos para cada amostra de biomassa; especificamente 100-200

µm, 400-600 µm e 800-1000 µm. Seguidamente, todos os combustíveis, incluindo as amostras com

distribuição de tamanhos não segregados, foram queimados no reactor a 1100 ºC. Os resultados

obtidos incluem perfis de temperatura, burnout e concentração e distribuição de tamanhos de partículas

ao longo do reactor. Adicionalmente, amostras seleccionadas de PM foram examinadas num

microscópio de varrimento electrónico. As principais conclusões deste trabalho são as seguintes: i) as

emissões de PM são maiores no caso da palha de trigo do que no caso da casca de arroz, sendo a

fragmentação secundária mais evidente para partículas nas gamas 100-200 µm e 400-600 µm), ii) Ca

e P tendem a ficar retidos em partículas maiores, ao passo que K e Cl apresentam maiores

concentrações em PM de menores dimensões, e iii) do ponto de vista da eficiência de combustão e da

emissão de PM não existem benefícios em segregar a biomassa pulverizada em classes de tamanho

tão estreitas.

Palavras-chave

Reactor de queda livre, biomassa, burnout, tamanho de particula, fragmentação de particulas

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Table of contents

Acknowledgments ................................................................................................................................ iii

Abstract .................................................................................................................................................. v

Resumo................................................................................................................................................. vii

List of tables .......................................................................................................................................... x

List of figures ........................................................................................................................................ xi

Nomenclature ...................................................................................................................................... xiii

1. Introduction .................................................................................................................................... 1

1.1 Motivation .............................................................................................................................. 1

1.2 Structural composition of biomass ........................................................................................ 4

1.3 Combustion process of biomass ........................................................................................... 5

1.4 Particulate matter emissions ................................................................................................. 7

1.5 Previous studies .................................................................................................................. 10

1.6 Objectives ............................................................................................................................ 18

2. Materials and Methods ................................................................................................................ 19

2.1 Fuel preparation and characterization ................................................................................. 19

2.3 Experimental setup .............................................................................................................. 23

2.4 Experimental methods ......................................................................................................... 25

2.5 Test conditions ..................................................................................................................... 29

3. Results and Discussion .............................................................................................................. 30

3.1 Wheat straw ......................................................................................................................... 30

3.2 Rice husk ............................................................................................................................. 37

4. Closure .......................................................................................................................................... 45

4.1 Conclusions ......................................................................................................................... 45

4.2 Future work .......................................................................................................................... 45

5. References .................................................................................................................................... 46

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List of tables

Table 1.1 Challenges of using biomass as a fuel.................................................................................... 3

Table 1.2 Previous studies on particulate matter emissions. ................................................................ 12

Table 2.1 Properties of the biomass fuels. ............................................................................................ 22

Table 2.2 Particle diameter of each stage of DLPI................................................................................ 27

Table 2.3 Experimental conditions used in the DTF. ............................................................................. 29

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List of figures

Figure 1.1 Shares of biomass in final energy consumption in some regions of the world (adapted from

[4]). ........................................................................................................................................................... 2

Figure 1.2 Carbon life cycle (adapted from [5]). ..................................................................................... 2

Figure 1.3 Deposition potential of particles from different sizes (µm) on human body (adapted from [9]).

................................................................................................................................................................. 4

Figure 1.4 Schematic of solid fuels combustion process [12]. ............................................................... 5

Figure 1.5 Schematic of particulate matter formation processes on biomass combustion (adapted from

[17]). ......................................................................................................................................................... 8

Figure 2.1 Samples of raw a) wheat straw and b) rice husk. ............................................................... 19

Figure 2.2 SS-15 Gilson Economy 203 mm Sieve Shaker (Global Gilson). ........................................ 19

Figure 2.3 Particle size classes of wheat straw: a) 800-1000 µm b) 400-600 µm c) 100-200 µm. ...... 20

Figure 2.4 Particle size classes of rice husk: a) 800-1000 µm b) 400-600 µm c) 100-200 µm. ........... 20

Figure 2.5 Particle size distribution of raw samples measured using the Malvern 2600 Particle Size

Analyzer. ................................................................................................................................................ 21

Figure 2.6 Schematic of the Drop Tube Furnace and auxiliary equipment. ......................................... 24

Figure 2.7 Thermocouple probe used for the temperature measurements along the DTF. ................. 25

Figure 2.8 Schematic of Tecora total filter holder. ................................................................................ 26

Figure 2.9 Schematic of the low pressure three-stage cascade impactor. ........................................... 27

Figure 2.10 Schematic of the sampling system used to perform all the PM tests................................ 28

Figure 2.11 Scanning electron microscope. ......................................................................................... 29

Figure 3.1 Temperature profiles for wheat straw. ................................................................................. 30

Figure 3.2 Burnout profiles for wheat straw. ......................................................................................... 31

Figure 3.3 PM emissions and particle burnout for wheat straw: a) 100-200 µm b) 400-600 µm c) 800-

1000 µm d) original. ............................................................................................................................... 33

Figure 3.4 Particle size distribution for wheat straw at x = 1100 mm. .................................................. 34

Figure 3.5 Chemical composition obtained using the SEM-EDS for wheat straw: a) 100-200 µm b) 400-

600 µm c) 800-1000 µm d) original. ...................................................................................................... 36

Figure 3.6 SEM images for wheat straw: a) 100-200 µm b) 400-600 µm c) 800-1000 µm d) original. 37

Figure 3.7 Temperature profiles for rice husk. ...................................................................................... 38

Figure 3.8 Burnout profiles for rice husk. .............................................................................................. 38

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Figure 3.9 PM emissions and particle burnout for rice husk: a) 100-200 µm b) 400-600 µm c) 800-1000

µm d) original. ........................................................................................................................................ 40

Figure 3.10 Particle size distribution for rice husk at x = 1100 mm. ..................................................... 41

Figure 3.11 Chemical composition obtained using the SEM-EDS for rice husk: a) 100-200 µm b) 400-

600 µm c) 800-1000 µm d) original. ...................................................................................................... 43

Figure 3.12 SEM images for rice husk: a) 100-200 µm b) 400-600 µm c) 800-1000 µm d) original. ... 44

xiii

Nomenclature

Acronyms

CEN Comité Européen de Normalisation

DLPI Dekati low pressure impactor

DTF Drop tube furnace

GHG Greenhouse gases

LPI Low pressure impactor

PM Particulate matter

PSD Particle size distribution

SEM Scanning Electron Microscope

UNFCC United Nations Framework Convention on Climate Change

VOC Volatile organic compounds

Greek letters

𝜀 Emissivity

𝜆 Excess air

𝜎 Stefan-Boltzmann constant, σ = 5.67 x 10-8 J/(s m2 K4)

𝜓 Particle burnout

𝜔𝑓 Ash weight fraction in the input biomass fuel

𝜔𝑥 Ash weight fraction in the char sample

Symbols

d Thermocouple bead diameter

k Gas thermal conductivity

Nu Nusselt number

Tgas Gas temperature

Tt Thermocouple temperature

Twall Furnace wall temperature

1

1. Introduction

1.1 Motivation

The increasing concern regarding the protection of the environment and the human health is leading to

strong investments in alternative sources of energy in order to reduce the demand of the traditional fossil

fuels, responsible for emissions of greenhouse gases, particulate matter and other harmful components

to the atmosphere. Global awareness of renewable energy and its potential have shifted considerably

along the last decade. Today, renewable energy technologies are viewed not only as tools for improving

energy security and mitigating and adapting to climate changes, but are also increasingly recognized as

investments that can provide direct and indirect economic advantages by reducing the dependence on

fossil fuels.

The last decade saw a steady increase in global demand for renewable energy. In 2004, the annual

overall primary energy supply from renewables was around 57.7 EJ. By 2013, the total supply had grown

to 76 EJ annually, with renewables supplying approximately 19% of the world’s final energy

consumption, a little less than half of which coming from traditional biomass [1].

Across Europe, a combination of policies and incentives by national governments has enabled

considerable progress towards fulfilment of the EU targets in order to obtain 20% of Europe’s total

primary energy consumption from renewable energies by 2020. According to [2], the global distribution

of GHG emissions has shifted with changes in the global economy. At the beginning of the 20th century,

along with the industrialization of Europe and USA, the energy-related CO2 emissions were almost

exclusively generated by these areas. This ratio dropped to around two-thirds of total emissions by the

middle of the century and today, because of all the existing policies regarding GHG control, stands at

below 30%. However, a constant monitoring is necessary. The 21st Conference of the Parties of the

UNFCC took place in Paris in December 2015, with the aim of adopting new global agreements to limit

greenhouse gas emissions. To fulfill the goal, a transformation of the energy sector becomes mandatory,

since it accounts for roughly two-thirds of all anthropogenic greenhouse gas emissions nowadays.

Biomass solid fuels were probably the first on-demand source of energy that humans exploited.

However, less than 25% of our primary energy demand is currently met by biomass-derived fuels. The

position of biomass as a primary of energy varies widely depending on the geographical and

socioeconomic conditions. In developed countries, biomass contributes roughly 12% to the total energy

supplies, but in developing countries the contribution reaches about 35% of the energy demand [3].

Figure 1.1 shows the share of biomass in final energy consumption for some regions in the world.

2

Figure 1.1 Shares of biomass in final energy consumption in some regions of the world (adapted from [4]).

When the process of biomass combustion starts the carbon present in its structure reacts with the

oxygen present on the oxidizer, in general, air, to form carbon dioxide, which is released to the

atmosphere. If fully combusted, the amount of CO2 produced during the process is equal to the amount

that was absorbed by the biomass from the atmosphere during its growing stage. So there is no net

addition of CO2 to the atmosphere. This cycle is known as the zero carbon emissions cycle or carbon

cycle and it is illustrated in Figure 1.2.

Figure 1.2 Carbon life cycle (adapted from [5]).

Biomass is formed from living species like plants and animals. It is formed as soon as a seed sprouts or

an organism is born. Unlike solid fuels, biomass does not take millions of years to develop. Plants use

3

sunlight through photosynthesis to metabolize atmospheric carbon dioxide and grow. Fossil fuels do not

reproduce whereas biomass does. This is one of the major advantages as an energy source.

In addition, there are some other important characteristics that give value to the use of biomass as a

fuel source. Biomass is considered a low-cost resource, which allows a strong economic competition

with conventional solid fuels as coal. Due to its diversity and security on supply as an energy resource,

it is still possible to integrate biomass in coal-fired systems in order to reduce emissions of nanoparticles

and achieve an economic benefit. Despite of the many advantages regarding the use of biomass as a

fuel, there are some challenges that need to be overcome in order to achieve, as much as possible, the

characteristics of coal combustion. Table 1.1 shows some of the challenges of using biomass as a fuel

[4].

Table 1.1 Challenges of using biomass as a fuel.

Challenges of using biomass as a fuel

Low energy density

High contents of moisture and inorganic matter (Cl, K, Na and Mn)

High harvesting, pulverization, transportation and storage cost

Some biomass fuels may not be available in sufficient quantities to make an impact as an energy

source

High levels of particulate matter emissions

During combustion, several phenomena may occur that contribute to the release of particles of different

sizes. Particles can undergo aggregation by coagulation, condensation and particle nucleation, which

are mainly responsible by the formation of new inorganic particles or by the increase of the size of a

particle. However, particle elimination phenomena, caused by deposit formation on the furnace walls,

and phenomena of size reduction, by evaporation or particle fragmentation, may also occur [6].

The particles contained in the exhaust gases can reach small sizes so that their capture becomes

inefficient using conventional gas treatment systems. Consequently, the release of high levels of

particulate matter and inorganic matter to the atmosphere represents a significant issue to the human

health and to the environment.

The size of the particles has been directly linked to being the main cause of health problems like

respiratory and cardiovascular diseases, decreased lung function and premature mortality [7][8].

Generally, the smaller a particle is, the more deeply it will penetrate to deposit on the respiratory system

[9]. Figure 1.3 shows the deposition potential of particles from different sizes on human body, in µm.

4

Figure 1.3 Deposition potential of particles from different sizes (µm) on human body (adapted from [9]).

1.2 Structural composition of biomass

The components of ligno-cellulosic biomass solid fuels include cellulose, hemicellulose and lignin. Other

components are present as well such as proteins, simple sugars, starches, water, ashes and other

compounds, creating a complex structure. The concentration of each compound depends on species,

type of plant tissue, stage of development and growing conditions. Some minerals are present on

biomass structure such as sodium, phosphorous, calcium and iron.

Cellulose is the primary structural component of the cell walls and it is a long chain polymer with a high

degree of polymerization and a large molecular weight. It has a crystalline structure made of glucose

molecules. Contrasting with cellulose, hemicellulose has a random, amorphous structure with low

strength, having in its composition chain structures of carbohydrates. Lignin is the cementing agent of

the cell walls and it is a complex highly branched polymer of phenylpropane [5].

Biomass contains a large number of complex organic compounds, comprising four principal elements

such as carbon, hydrogen, oxygen and nitrogen, moisture, and a small amount of inorganic impurities

known as ash. Biomass may contain as well small amounts of chlorine and sulphur, which is a major

issue regarding SO2 emissions.

The composition of biomass can be described using the ultimate and proximate analyses. The ultimate

analysis includes elementary analysis of organic compounds such as carbon (C), hydrogen (H), oxygen

(O), nitrogen (N) and sulphur (S), as well as the ash and moisture content. Carbon is usually the

dominating element. Proximate analysis can provide information regarding moisture (M), volatile matter

(VM), fixed carbon (FC) and ash (A) content of the biomass sample.

5

One of the major characteristics of biomass, in contrast with other solid fuels like coal, is the high

moisture content. The total moisture content of biomass can be as high as 90%. The previous knowledge

regarding this characteristic of a solid fuel can influence the need of pre-treatments, like drying, to

improve the efficiency of any conversion process of biomass.

Biomass particles are typically much larger than pulverized coal particles and its shapes are very

irregular, with varying surface area to volume rations. Most biomass particles are non-spherical and

resemble cylinders or flakes, in contrast with coal, which shape can be approximated as spheres with

aspect rations of less than 2, while the aspect ratios for biomass particles commonly exceed 6 [10].

The irregular shapes associated to biomass particles results in more complex particle conversion

behaviour than in coal combustion, where the surface area to volume plays a key role on particle

conversion characteristics.

1.3 Combustion process of biomass

Most of the actual knowledge about solid fuel combustion processes emerged from studies of

combustion of small quantities of coal particles in laminar flows. Despite of its complexity, it is already

well established that the combustion of solid fuels is divided in three steps: particle drying and heating,

devolatilization and char oxidation [11]. Usually, the combustion of pulverized fuels occurs at heating

rates close 105 ºC/min. In these conditions, devolatilization and char oxidation can occur simultaneously.

A schematic of solid fuels combustion process is present in Figure 1.4.

Figure 1.4 Schematic of solid fuels combustion process [12].

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1.3.2 Particle drying and heating

The moisture content of a biomass fuel plays an important role in the combustion process. The process

of drying and heating of a biomass particle starts with some important physical changes and begins

when the particle reaches 105 ºC, when moisture has changed into gaseous phase and moves through

from the particle pores to the surface. If the release of water vapour from the particle is too slow, enough

cracks on the particle surface could be generated and the particle could break into smaller particles.

Drying and heating are endothermic processes controlled by heat and mass transfer and, therefore,

dependent on important variables like temperature and particle size. For smaller particles, like pulverized

biomass, it is assumed that the particles heat up virtually instantly, but there is an efficiency loss due to

the latent energy of water evaporation from the biomass. To avoid this, and because of the high moisture

content of biomass, a drying process is usually carried out separately.

1.3.3 Devolatilization

Devolatilization, which corresponds to the release of volatile matter of the solid fuel, occurs in the early

stages of the combustion process. In most of the biomass solid fuels, devolatilization starts between

160 ºC and 250 ºC; however for bituminous coal the temperature range increase to 350 ºC [13].

The amount and nature of the products released during devolatilization depends on factors like final

temperature reached by the particle, residence time inside the combustion system, the heating rate, and

is influenced by the initial particle size. Fast particle heating, under high temperatures, leads to higher

volatile matter released. Regarding the initial particle size, according to [14], volatile yields decreased

with the increase on the particle size. In pulverised biomass fuel combustion, volatile matter that is

produced during heating process crack to form CO, CO2, H2O, together with CH4, VOC, H2 and some

inorganic products [15]. The distribution of trace species such as N, Cl, P and K, and the metals between

the gases, the tar and the char is important in relation to their subsequent reaction and formation of

pollutants.

It should be noticed that, due to the high content of volatile matter present in most of the biomass solid

fuels when compared to coal (around 70% for biomass and 36% for coal), devolatilization usually

dominates the combustion process and char oxidation is of less importance regarding thermal efficiency

than it is in coal combustion.

1.3.4 Char oxidation

Char is the residue of the devolatilization process and it is essentially formed by carbon and ashes,

together with small amounts of hydrogen, oxygen, nitrogen and sulphur and represents about to 10%-

30% of the total biomass by weight. In general, char presents a spherical shape, especially for small

7

particles, and could have some cracks and fissures, as a result of high heating rates and gases that

escaped from the particle during devolatilization.

Despite of having several studies regarding char oxidation, with special emphasis in biomass char

reactivity and chemical kinetics, the physical and chemical mechanisms of the process are still not well

established in detail due to the lack of knowledge regarding the growth rate of the char porous structure

and the mass transfer processes inside the particle.

The carbon present on a char particle reacts heterogeneously with the oxygen present in the oxidizer.

The reaction can be controlled by chemical mechanisms, associated with low temperatures and low

reaction rates, or by diffusion, at high temperatures. The main heterogeneous reactions that can occur

at the char surface are the following:

𝐶 + 𝑂2 ⟹ 𝐶𝑂2 (1.1)

2𝐶 + 𝑂2 ⟹ 2𝐶𝑂 (1.2)

𝐶 + 𝐶𝑂2 ⟹ 2𝐶𝑂 (1.3)

𝐶 + 𝐻2𝑂 ⟹ 𝐶𝑂 + 𝐻2 (1.4)

The occurrence of these reactions depends mainly of the temperature at particle surface and they

usually take place between 800 ºC and 900 º C.

The porous structure of biomass chars is directly dependent on the type of biomass used, as well as the

conditions at which devolatilization occurs. Since the process of char oxidation is rather complex, due

to kinetics of heterogeneous reactions and mass transport involved, it is usual to express the

consumption rate of char during combustion by an apparent reaction rate expressed by a first-order

Arrhenius equation. Combining this result with the rate of diffusion of the combustion products from the

surface, it is possible to define an overall reaction rate of particle combustion as a function of oxygen

concentration, away from the particle.

Among all the steps of solid fuels combustion, char oxidation is, perhaps, the most serious issue

because it contributes to the formation of incomplete combustion products, which are considered as

precursors to pollutant formation [16].

1.4 Particulate matter emissions

Figure 1.5 shows a simplified scheme of the process of particulate matter (PM) formation mechanisms

and reactions involved. In general, coarse particles are generated by char fragments and fine particles

by soot formation and the vaporization of inorganic matter that consequently can grow by mechanisms

of agglomeration, nucleation and condensation.

8

Figure 1.5 Schematic of particulate matter formation processes on biomass combustion (adapted from [17]).

PM emissions could be defined with several criteria. The aerodynamic diameter is one of the main

criterion to describe its transport ability in the atmosphere and its ability to be inhaled by the respiratory

system of an organism. The most accepted particle size classification is the one that divide PM in to two

categories: ultrafine particles, with particle aerodynamic diameter lower than 2.5 µm (PM2.5) and the

coarse particles with particle aerodynamic diameter higher than 10 µm (PM10) [18].

1.4.1 Char fragmentation

The phenomena regarding reduction of particle size by char fragmentation are of particular importance

because during the combustion process a particle can generate two or more ultrafine particles that can

contribute in a large scale to the ultrafine PM emissions, highly harmful to the environment and therefore

to the human health. Due to its reduced size, the capture of these PM represents a challenge with

conventional technology available for flue gas cleaning.

Although there are only few studies focused on the processes and the governing factors that promote

particle fragmentation in biomass combustion, a typical definition derived from studies on coal

combustion and fragmentation can be applied to define the process [19]. Primary fragmentation occurs

during heating up and devolatilization stages when the particles are fed into the furnace, as a

consequence of internal overpressures associated with volatile matter release and possibly, thermal

shock. Secondary fragmentation refers to char fragmentation as combustion weakens the bridges within

the char particles. As secondary fragmentation is closely related to combustion, the combustion

progress affects the fragmentation extent. In particular, carbon burnout is usually used as an indicator

of the combustion degree [20].

9

Most of the studies in the literature regarding char fragmentation are focus on coal combustion. These

studies are, in general, based on variations of particle mean diameter during the combustion process

and on evaluations of particle fragmentation extent and morphology using electronic microscopes.

1.4.2 Inorganic matter emissions

Biomass solid fuels contain considerable amounts of ash forming inorganic elements responsible for

ash production during the combustion process that are released in the flue gas. Potassium, sulphur and

chlorine are the most relevant elements during the combustion of solid biomass fuels, whereas sodium

and some easily volatile heavy metals like zinc provide minor contributions.

The behavior of ash forming species is strongly dependent on the type of fuel, especially with the ash

composition, combustion technologies and combustion conditions. In studies performed in fluidized bed

combustion, the composition and presence of these elements varies within the particle size. The fine

particles are composed mainly of K, Cl, S, Na and Ca, while the coarse particles have Ca, Si, Na, Al, P

and Fe in its composition [21]. In fixed bed combustion conditions, a dependency of the particle

composition on size can also be found. K, S and Cl are mainly found in submicron fraction of the PM,

while the content of Ca is increasing with the increase on particle size. In general, the release of these

elements are made in different stages and steps and have different impacts on the performance of the

combustion system [22].

Chlorine, which concentration in biomass ranges from 0.2% to 2%, is released in two steps: the first

step at temperatures below 500 ºC, and the second around 700 ºC and 900 ºC. Chlorine can react with

metals such as K and Na, forming vapors and aerosols during the cooling process, leading to deposit

formation on the furnace walls [23].

Regarding potassium, it is known that its release becomes intense when the temperature exceeds 700

ºC. Above 1150 ºC, the release of K to the gas-phase can reach around 90%. The presence of potassium

at the emitted PM is highly influenced not only by the temperature but also by the presence of certain

elements on ash composition such as silicon. If the ashes of the original biomass fuel contain

considerable amounts of silicon, potassium can integrate the silicon matrix, making its vaporization

difficult. The presence of chlorine can also leads to high release of potassium due to the formation of

KCl [24].

Other elements like sulphur can reach 55% of release around 500 ºC and increase strongly its presence,

in case of high levels of silicon on the solid fuel, around 800 ºC. High presence of sulphur leads not only

to the formation of oxides like SO2 but can also be responsible for corrosion problems on the combustion

systems. The ratio between chlorine and sulphur is usually used to quantify the corrosive potential of a

fuel [25].

10

1.4.3 Soot formation

Although this study did not focus on soot formation, it is important to make a brief statement about this

type of component. Soot is formed under fuel-rich conditions in which hydrocarbon fragments have

greater probability to collide with each other to grow, rather than being oxidized to components like CO,

H2, CO2 and O2. Soot formation chemical reactions are essentially irreversible. Several studies have

been made on this subject, with a special emphasis on Bockhorn’s work that reviews the processes

involved in soot formation of combustion processes [26]. One of the critical steps pointed by Bockhorn’s

in soot formation mechanism is the formation of the first aromatic ring, usually benzene. Fuels with high

aromatic hydrocarbon content tend to form soot more easily.

1.5 Previous studies

In this section, previous related works are reviewed and Table 1.2 summarizes some important studies

performed in this area.

1.5.1 Effect of particle size

The initial particle size of the solid fuels is an important characteristic on the combustion of pulverized

solid fuels. Some of studies in the literature showed that solid fuels with particles with larger diameters

presented a delay in particle burnout due to the need of a higher particle heating time and

devolatilization, and lower residence times near the burner [27]. It was reported as well that for particles

with larger diameter some deterioration of particle burnout occurs since the particles do not have enough

residence time available to proceed with the process of oxidation [28]. To obtain full char oxidation, it is

necessary to establish a balance between the available residence time inside the reactor and the particle

size diameter available for combustion.

The study of Steer et al. [29] focused on the effects of particle grinding on the burnout and surface

chemistry during coal combustion suggested that the process of grinding alters the physical properties

of the samples, so that in some cases the larger size classification give improved combustion burnout

profiles when compared with smaller sizes. The samples of this study were separated into samples with

lower volatile content, with medium volatile content and with high volatile content. Each sample was also

separated into three particle size classes (< 106 µm, < 500 µm and < 1000 µm). One of most relevant

evidences in this work is related with the higher burnout value obtained to many of the larger particle

size classifications, suggesting that the larger sizes were more reactive than the smaller ones or that

additional grinding was detrimental to the burnout of the smaller sizes. For most of the cases, the

intermediate particle size (< 500 µm), resulted in higher burnouts despite of the volatile content of the

sample at the highest residence time studied (700 ms). Therefore, at longer residence times, the results

showed that additional grinding to smaller sizes has insignificant benefits and, in some cases can give

detrimental effects on burnout. In this study, the effect of particle grinding on particle swelling and

fragmentation were also evaluated using comparisons between the initial PSD of the coals and the PSD

11

of the remained chars at two residence times (35 ms and 700 ms). The trend is for larger size coals (<

1000 µm) to fragment and the smaller size coals (< 160 µm) to swell. The results for intermediate samples

were inconclusive regarding the governing phenomena.

.

12

Table 1.2 Previous studies on particulate matter emissions.

Reference,

Objectives

Type of fuel,

Particle size

Experimental setup and

techniques

Main conclusions

Jiménez et al. [30]

Particle formation and

emission of four

biomass solid fuels

and chemical

composition of the

ashes

Olive residue

300-400 µm

Oak tree

Chesnut tree

Eucalyptus wood

250-300 µm

Entrained flow reactor

Particle emission measurements with 11-

stage Berner LPI at the exit of the reactor

at 1300 ºC

Morphology and chemical composition of

impactor deposits analysis using a

Scanning Electron Microscope (SEM)

equipped with an X-ray Energy

Dispersive Spectrometer (XEDS)

Bimodal distribution was found in all the cases with fine

mode centred in 30-70 nm (except for olive residues,

which was centred in 200 nm) and a coarse mode, with

mean sizes 4-10 times smaller than the original fuels

Origin of larger particles attributed to char fragmentation

and coalescence of mineral matter and fine aerosols

generated from condensable mineral species

Coarse particles essentially retain the original fuel mineral

matter characteristics while the fine mode are composed

only for alkali sulphates and chlorines – phosphorus

appears in significant amount (up to 10%, molar basis)

Steer at al. [29]

Influence of grinding

on physical properties,

surface chemistry and

combustion behaviour

of coal

Coal

100 % < 106 µm

100 % < 500 µm

100 % < 1000 µm

(with 50% < 250

µm)

Drop tube furnace

Particle burnout measurements at 1100

ºC at 5 different residence times,

between 35 ms and 700 ms

Fragmentation and swelling detected

using Malvern Mastersizer 3000 laser

diffraction particle analyser at 35 ms and

700 ms

Surface chemistry analysis using X-ray

photoelectron spectroscopy (XPS)

Some of larger particle sizes had better burnouts than

smaller sizes

Smaller particle size coals tend to swell while larger size

coals tend to fragment

More mineral phase changes occurred in the larger size

coals

Process of grinding alters the physical properties and

surface chemistry

13

Nimomiya et al. [31]

Influence of the

particle size on

particulate matter

emissions and

chemical composition

on coal combustion

3 coal samples

separated in 3

particle size

classes each:

125-250 µm

63-125 µm

< 63 µm

Drop tube furnace

Particulate matter concentration

measurements at 1200 ºC with the aid of

LPI (13 stages)

Chemical species of inorganic elements

with raw coal, fly ash and PM were

analyzed using CCSEM - EDS

(Computer-controlled SEM - EDS)

3 substracts were analyzed regarding

chemical composition (3.9 µm, 0.76 µm

and 0.13 µm

Decrease of coal particle size leads to formation of more

PM due to direct transferring of more excluded minerals.

Compared to coal of 125-250 µm, combustion of 63-125

µm resulted in great increase of PM; with coal decreasing

further to < 63 µm, PM was increased slowly

Coals of 125-250 µm and coals of 63-125 µm, formed a

single mode distribution of PM while for coals < 63 µm, a

bimodal.

Costa et al. [32]

Influence of

torrefaction on particle

fragmentation during

combustion

Pine Shells

Wheat Straw

Olive Stones

(raw and

torrefied)

95% < 1000 µm

Drop tube furnace

Particle burnout measurements at 1100

ºC

Particulate matter concentration

measured with LPI cascade impactor (3

stages) at 5 axial positions of the reactor


analysis of particle morphology

Pine shells present the lowest PM concentration due to its

highest burnout values

Fragmentation is more evident for pine shells, both raw

and torrefied

Torrefaction promotes fragmentation only in the case of

wheat straw

Haykiri-Acma et al.

[33]

Investigation on extent

of size fragmentation

Hazelnut shells

+ 10 mm

5-10 mm

2-5 mm

0.25-0.5 mm

Burning tests performed in a thermal

analyzer (TA Instruments SDT Q600)

The content of extractives tend to form more fragile

structures leading to particle fragmentation

14

Gao et al. [34]

Emission behaviour

and characteristics of

PM1 and PM10

Mallee bark

biochars from

slow and fast

pyrolysis

75-150 µm

Drop tube furnace

Particulate matter experiments at 1300

ºC and collected via a cyclone to remove

particles larger than 10 µm and a Dekati

LPI (DLPI) to study particles less than 10

µm and a Dekati LPI (DLPI)

Combustion of biochars leads to substantial reductions in

both PM1 yields and the mass of Na, K and Cl in PM1 in

comparison to direct biomass combustion (less

contribution of volatile combustion to PM1)

Biochar combustion results in significant increase on

PM1-10 yields and mass of Ca and Mg on PM1-10 in

comparison to direct biomass combustion (significant

changes on char structures)

Yani et al. [35]

Emission behaviour of

PM < 10 µm of

torrefied biomass in

pulverized fuel

conditions

Raw and torrefied

mallee

75-150 µm

Drop tube furnace

Particulate matter experiments at 1400

ºC and collected via a cyclone and a

Dekati LPI (DLPI). The collected mass of

PM10 was measured using a Mettler MX5

microbalance

Due to intensified char fragmentation, combustion of

torrefied biomass leads to substantial increases of ash-

based yields of PM1-10, Mg and Ca in PM1-10

The ash-based yields of PM0.1, and Na, K and Cl in PM0.1

from torrefied biomass combustion are considerably lower

than those of raw biomass; this can be attributed to the

release of Cl during torrefaction

Combustion of torrefied biomass leads to similar yields of

PM2.5 but considerably higher yields of PM10, than that for

raw biomass.

15

Seames [36]

Study on fine

fragmentation fly ash

mechanisms during

coal combustion

Two bituminous

coals and one

subbituminous

coal

Downflow combustor

PM sampling made with the aid of a

BLPI, with a pre cyclone to eliminate

particles larger than 1 µm, in order to

collect enough masses of ultrafine

particles on lower stages of the BLPI.

Collected samples analysed using SEM-

EDS (morphology and chemical

composition)

Tri-modal particle size distribution for all the samples with

central mode centred around at 1- 2 µm for all the samples

Supermicron region: only a very small fraction of particles

showed evidence of deformation and irregularities

Fine region: preponderance of irregular shapes could be

consequence of fragmentation mechanisms (cracking,

particle inflation)

Ultrafine region: particle size is inefficient because it is at

the resolution limits of SEM, but the examined particles

appeared to be primarily spherical

Yu et al. [37]

Study on the formation

mechanisms of central

mode particles during

pulverized coal

combustion

Bituminous coal

Fine coal

100 % < 63 µm

Coarse coal

100-200 µm

Drop tube furnace

PM sampling made with the aid of a

Dekati cyclone (SAC-65) to remove

particles larger than 10 µm and DLPI to

study particles less than 10 µm

Combustion experiments with 50 % of O2

Density-separated coal samples were

also used (Light and Heavy coals) to

study the influence of extended minerals

Fly ash size distributions had a general central particle

mode at ~4 µm for all the coal samples. Most of the central

mode particles were produced at higher temperatures due

to the enhanced char fragmentation

Higher concentration of central mode particles for small-

size coal sample suggested that fine particles present in

the original sample can contribute to the formation of the

central mode.

16

Almeida [38]

Particle fragmentation

of solid biomass fuels

and coal at the last

stages of combustion

Cork residues

Furniture residues

Platanus

branches

100 % < 1000 µm

UK Bituminous

Coal

100 % < 1000 µm

Semi-industrial furnace (Maximum

power = 500 kW)

Particle burnout and PM sampling with

LPI cascade impactor (3 stages) and

DLPI (13 stages) in the last three stages

of the furnace


analysis of particle morphology and

chemical composition

Particle fragmentation occurs during combustion of coal,

cork residues and platanus branches

Particle fragmentation does not occur during combustion

of furniture residues

For cork residues and coal, the PSD suggested a bimodal

behaviour, with higher particle concentration on cork

residues then on coal

Korbee et al. [39]

First line ash formation

processes in

pulverized fuel

conditions

Wood chips

Waste wood

Olive residue

Straw

Polish coal

UK coal

100 % < 1000 µm

Labscale combustion simulator (LCS)

equipped with flat flame gas burner

Particle burnout levels measured at

different residence times

PSD of coarse, fine and aerosols

obtained with several cascade impactors


and EDX analysis to each stage of the

impactor

Ash transformations and char combustion occurs under

kinetic-diffusion controlled regime

Fragmentation is found to be dependent on the overall fuel

chemical conversion and devolatilization. The quicker and

the higher the fuel chemical conversion and the

devolatilization, the more pronounced will be

fragmentation.

17

Ninomiya et al. [31] also performed studies with different particle sizes of coal; although the particle size

range used was narrow than the one used in the previous study. Three coals were divided into sizes of

125-250 µm, 63-125 µm and < 63 µm in order to evaluate the effect of the particle size on the emissions

of PM during combustion. The samples were combusted completely in a drop tube reactor and their

particle size had little influence on its burnout, so that the formed PM contains insignificant amounts of

unburnt carbon. With the decrease of the coal size, the PM concentration increase for all the three coals.

For the smallest particle size, the PM concentration is almost three times higher than for the highest

particle size distribution. Since the studies were performed using an LPI of 13 stages, it was also

possible to segregate the total PM concentration into particle size distributions in order to evaluate the

PM generated modes. For the largest particle size distributions of 125-250 µm and 63-125 µm, the PSD

revealed a unimodal behaviour at around 4 µm, and for coals < 63 µm, a bimodal behaviour was

identified with the large mode centred at around 4 µm and the small mode centred on 0.5 µm. The

increasing of PM concentration with the decreasing of the particle size was due to the presence of

excluded minerals and their behaviour along the combustion process.

1.5.2 Chemical composition of PM

Reference [30] was only focused on one narrow particle size for all the tested samples (250-300 µm for

oak tree, chestnut and eucalyptus wood and 300-400 µm, for olive residue). However, it is still important

to discuss some of the conclusions regarding the PM distributions and its composition. As referred to

above, bimodal PM distributions were observed for all the tested samples, with a fine mode peak at 30-

70 µm for woody biomass fuels and 200 nm for olive residues, and a coarse mode. The fine particles

produced have been found to be composed by alkali sulphates and chlorines, in contrast with the coarse

mode, which was composed mainly by silicon, calcium and iron. The authors suggested that the origin

of the larger particles was attributed to char fragmentation and coalescence of minerals, retaining most

of the original fuel mineral composition, while most of the fine particles were generated by condensable

mineral species.

The results of reference [39], which was focused on a wide range of particle sizes (<1000 µm), are

important for the understanding of the char conversion phenomena, devolatilization but, above all, of

the particle fragmentation and the influence of mineral matter on its composition. Four biomass fuels

(wood chips, waste wood, olive residue and straw) and two coals (UK coal and Polish coal) were burnt

for residence times between 200 ms and 1300 ms in a Labscale Combustion Simulator, which is an

advanced drop tube furnace equipped with a flat flame gas burner, to ensure initially high heating rates

and temperatures. The authors state that fragmentation looks to be dependent on the fuel chemical

conversion and devolatilization. For wood chips and wastes, and olive residue, with high volatile matter

content, devolatilization results in a fast process than for the other fuels. The same was verified

regarding char conversion. High levels of char conversion lead to high levels of fragmentation.

Apparently, particle fragmentation is also promoted by the low content of some mineral matter on the

original fuel like silicon, aluminium and sulphur. At the maximum residence time of 1300 ms, it was

18

observed for biomass fuels like olive residues and straws a presence of potassium and chlorine,

promoting an increase of aerosol particles formation.

1.6 Objectives

The main objective of this study is to evaluate the effect of the initial particle size of biomass solid fuels

on particle burnout and PM emissions. Wheat straw and rice husk solid biomass fuels were separated

into three narrow particle size classes to perform the experiments in a drop tube furnace, namely 100-

200 µm, 400-600 µm and 800-1000 µm. Additionally, the original sample of each biomass solid fuel, with

particle size below 1000 µm, will also be studied. The specific objectives of this work included: 1. to

study of the impact of the particle size of the solid fuels on particle burnout, and 2. to study PM emissions

(secondary char fragmentation and inorganic matter) and trends for the different particle size classes

collected on the last stages of the drop tube furnace.

19

2. Materials and Methods

2.1 Fuel preparation and characterization

Two different biomass samples were chosen to perform this study, wheat straw (WS) and rice husk (RH).

Both raw biomass fuels were pulverized with a 1-mm-diameter sieve using a laboratory-scale mill Retsch

SM 100. The raw samples of wheat straw and rice husk are presented in Figure 2.1.

Figure 2.1 Samples of raw a) wheat straw and b) rice husk.

The narrow particle size classes were obtained with the aid of a SS-15 Gilson Economy 203 mm Sieve

Shaker, represented in Figure 2.2, with different sieve sizes, namely 1000 µm, 800 µm, 600 µm, 400

µm, 200 µm and 100 µm to obtain the three different particle size classes used to perform this study:

100-200 µm, 400-600 µm and 800-1000 µm.

Figure 2.2 SS-15 Gilson Economy 203 mm Sieve Shaker (Global Gilson).

20

The particle size classes of each biomass used in this study are represented in Figure 2.3 for wheat

straw, and Figure 2.4 for rice husk.

Figure 2.3 Particle size classes of wheat straw: a) 800-1000 µm b) 400-600 µm c) 100-200 µm.

Figure 2.4 Particle size classes of rice husk: a) 800-1000 µm b) 400-600 µm c) 100-200 µm.

The samples were stored in sealed containers to prevent oxidation. Figure 2.5 shows the particle size

distribution of the raw samples used in this study as measured by the Malvern 2600 Particle Size

Analyser.

21

Figure 2.5 Particle size distribution of raw samples measured using the Malvern 2600 Particle Size Analyzer.

22

Table 2.1 shows the properties of both the raw and the particle size classes of each biomass fuel,

including the ash composition. The ultimate analysis was determined accordingly to the standards

CEN/TS 15104 and CEN/TS 15408 and the proximate analysis was determined following the

procedures of the standards CEN/TS 15414:2006, CEN/TS 15402: 2006 and CEN/TS 15403:2006. The

heating values of all the samples were determined following the procedures specified in the standards

CEN/TS 14918:2015 and the chemical composition of the ashes was determined with the aid of X-Ray

fluorescence spectroscopy.

Table 2.1 Properties of the biomass fuels.

Sample Rice Husk Wheat Straw

100-200 400-600 800-1000 Original 100-200 400-600 800-1000 Original

Proximate

Analysis

(wt,% as

received)

Volatiles 64.5 66.2 64.9 65.0 64.9 65.2 64.8 63.8

Fixed

Carbon 12.7 13.6 14.3 13.3 12.4 15.2 15.4 14.9

Ash 12.8 11.1 11.6 12.2 14.7 11.4 11.5 13.0

Moisture 10.0 9.1 9.2 9.5 8.0 8.2 8.3 8.3

Ultimate

analysis

(wt.%. as

dry ash

free)

Carbon 42.4 44.4 43.7 44.0 41.1 43.0 42.6 42.0

Hydrogen 5.6 5.5 5.8 5.6 5.3 5.4 5.4 5.4

Nitrogen 0.8 0.4 0.4 0.6 0.7 0.6 0.6 0.6

Sulphur < 0.2 < 0.2 < 0.2 < 0.2 < 0.2 < 0.2 < 0.2 < 0.2

Oxygen 51.1 49.4 50.0 49.6 52.6 50.8 51.2 51.8

Heating

Value

(MJ/kg)

Low 14.6 14.6 14.4 14.5 13.0 13.8 13.6 13.2

High 15.8 15.8 15.6 15.7 14.1 14.9 14.8 14.3

Ash

Analysis

(wt.% dry

basis)

SiO2 86.6 91.1 92.3 90.4 42 40.5 43.5 42.5

Al2O3 1.2 0.7 0.9 1.0 8.7 8.6 8.7 8.5

Fe2O3 0.5 0.3 0.3 0.4 5 4.8 4.9 4.9

CaO 1.5 1.8 1.6 1.6 28 27.9 25.3 26.9

SO3 0.4 0.3 0.3 0.3 1 1.1 1 1.1

MgO 1.0 0.7 0.7 0.9 3.7 4.6 4 4

P2O5 2.2 1.3 0.6 1.1 2.6 2.7 2.6 2.9

K2O 3.6 2.0 1.6 2.5 6.9 8.1 7.7 7.2

Na2O 0.3 0.3 0.3 0.3 0.6 0.5 0.9 0.7

Cl 0.5 0.5 0.6 0.5 0.6 0.4 0.5 0.6

Other

Oxides 2,2 1 0,8 1 0.9 0.8 0.9 0.7

23

2.2 Experimental setup

Figure 2.6 shows the schematic of the drop tube furnace (DTF) and auxiliary equipment used in this

study. The combustion chamber is a cylindrical electrically heated ceramic tube, with a total length of

1300 mm and an inner diameter of 38 mm. The DTF can reach a maximum temperature of 1100 ºC.

The furnace wall temperatures are continuously monitored using eight thermocouples (type-K) along

the combustion chamber. The feeding system is composed by a water-cooled injector, placed at the top

end of the DTF and it is used to feed the fuel and the oxidizer to the combustion chamber. The injector

has a central pipe for the introduction of the pulverized biomass and transport fluid and a concentric

passage for the introduction of the secondary stream. A twin-screw volumetric feeder transfers the

biomass to an ejector system from which the particles are gas-transported to the water-cooled injector.

The transport and secondary oxidizer is air supplied by an air compressor (10 bar). The flow rates are

controlled using mass flow meters. The particle colleting system is composed by a water-cooled,

nitrogen quenched stainless steel probe, a Tecora total filter holder with a 47 mm of diameter quartz

microfiber filter and a vacuum pump.

24

Figure 2.6 Schematic of the Drop Tube Furnace and auxiliary equipment.

25

2.3 Experimental methods

2.3.1 Temperature measurements

The local mean temperature measurements along the axis of the DTF were obtained using 76 µm

diameter fine wire type-R thermocouples (platinum/platinum-13% rhodium).

Figure 2.7 shows the thermocouple probe used. The thermocouple hot junction was installed and

supported by 350 µm wires of platinum/platinum-13% rhodium located in a twin-bore alumina sheath

with 5 mm of external diameter. The analogic outputs of the thermocouple were transmitted via an A/D

board to a computer where the signals were processed and the mean values computed.

Figure 2.7 Thermocouple probe used for the temperature measurements along the DTF.

The temperature measured with an exposed thermocouple is the gas temperature biased by the furnace

wall temperature so that the real temperature was estimated based on an energy balance on the

thermocouple bead [40]. The energy balance to the thermocouple bead neglects the heat transfer by

conduction through the wires and the catalytic effects so it only takes into account the balance between

radiation and convection under steady state conditions, according to the equations:

𝑄𝑐𝑎𝑡 + 𝑄𝑐𝑜𝑛𝑑 + 𝑄𝑟𝑎𝑑

+ 𝑄𝑐𝑜𝑛𝑣 = 0 (2.1)

𝜀𝑡𝜎(𝑇𝑡4 − 𝑇𝑤𝑎𝑙𝑙

4 ) + ℎ(𝑇𝑡 − 𝑇𝑔) = 0 𝑤𝑖𝑡ℎ ℎ =𝑁𝑢. 𝑘

𝑑

(2.2)

Based on Eq. (2.1) and its simplified form on Eq. (2.2), the maximum uncertainty of the temperature

measurements in this study was around 10%. More details about thermocouple corrections could be

found in [41].

2.3.2 Particle sampling and burnout

The particle (char) sampling along the DTF was performed with the aid of the 1.5 m long, water-cooled

stainless steel probe shown in Figure 2.6. The probe comprised a centrally located 3 mm inner diameter

tube, through which quenched samples were evacuated with the aid of a pump. The quenching of the

chemical reactions was achieved by nitrogen direct injection jets in the main gas stream through small

holes near to the probe tip. At the exit of the probe, the solid char samples were collected in a Tecora

total filter holder, represented in Figure 2.8, equipped with a 47 mm-diameter quartz microfiber filter.

After the sampling, the solid char samples were placed in an oven to eliminate the moisture content, at

approximately 105 ºC. In order to understand if the moisture content had been completely removed from

26

the solid char samples, repeated drying and weighting of the samples were made until the measured

mass became constant.

The ash content in the solid samples was evaluated following the procedures described in the standard

CEN/TS 14775. Particle burnout data were calculated using the following equation:

𝜓(%) = 1 −

𝜔𝑓

𝜔𝑥

1 − 𝜔𝑓

× 100

(2.3)

where 𝜓 is the particle burnout, 𝜔𝑓 is the ash weight fraction in the input biomass fuel, and 𝜔𝑥 is the ash

weight fraction in the char sample.

Figure 2.8 Schematic of Tecora total filter holder.

Uncertainties in particle burnout calculations based on the use of the ash as a tracer are related to ash

volatility at high heating rates and temperatures and ash solubility in water [42]. The char sampling was

repeated, at least, three times for each test condition and the repeatability of the data from these

independent tests in regard to particle burnout was always below 10%.

All sampling probes were inserted into the combustion chamber through the bottom end of the DTF. The

positioning of the probes was accurate to within ± 1 mm.

2.3.3 Particulate matter concentration and size distribution

PM concentration and size distributions were obtained with the aid of a low pressure three-stage

cascade impactor (LPI, TCR Tecora), represented schematically in Figure 2.8, and a low pressure

thirteen-stage impactor (DLPI, Dekati Ltd.), represented in Figure 2.9.

PM was sampled isokinetically from the centreline of the combustion chamber of the DTF at three axial

positions (700 mm, 900 mm and 1100 mm from the top end of the DTF), using the water-cooled and

nitrogen-quenched stainless steel probe referred to above.

27

The LPI used allowed collecting three PM cut sizes during the same measurement: PM with diameters

above 10 µm (PM10), PM with diameters between 2.5 µm and 10 µm, and PM with diameters below 2.5

µm (PM2.5). PM was collected on quartz microfiber filters of 47 mm diameter, which were dried in an

oven at 105 ºC and weight before each test. After each test, the filters were again dried, to eliminate any

moisture, and weighted to determine the mass of PM captured. In order to avoid condensation along

the line connecting the probe outlet to the impactor inlet and also inside the impactor, a heating jacket

(model Winkler WOXT1187) was used during the PM sampling.

Figure 2.9 Schematic of the low pressure three-stage cascade impactor.

The DLPI allowed classifying particle diameters according to Table 2.2. PM was collected on aluminium

substrates of 25 mm diameter. These substrates were weighed before and after each measurement in

order to determine the mass size distribution. Figure 2.10 shows a schematic of the sampling system

used to perform all the PM tests.

For each test condition, at least, three independent measurements were performed. The data

repeatability was, on average, within 20% of the mean value.

Table 2.2 Particle diameter of each stage of DLPI.

Impactor Stage Aerodynamic Diameter (µm)

1 0.028

2 0.055

3 0.094

4 0.158

5 0.265

6 0.386

7 0.616

8 0.950

9 1.597

10 2.384

11 3.979

12 6.651

13 9.862

28

Figure 2.10 Schematic of the sampling system used to perform all the PM tests.

2.3.4 Chemical species and particle morphology

Figure 2.11 shows the Scanning Electron Microscope (SEM) – Hitachi S2400 – facility used to evaluate

the morphology and the chemical composition of selected char samples. The microscope is equipped

with an energy dispersive X-ray spectroscopy (EDS) detector, which allows the quantification of the

ultimate composition of a sample with a resolution of about 1 µm2. For each selected char sample,

selected PM substrates chemical composition data was obtained from five different areas of about 50 x

50 µm2.

29

Figure 2.11 Scanning electron microscope.

2.4 Test conditions

Table 2.3 shows the experimental conditions used in DTF to perform all the measurements reported in

this thesis.

Table 2.3 Experimental conditions used in the DTF.

Temperature (º C) 1100

Biomass feed rate (g/h) 23

Excess air coefficient (λ) 2.6

Air flow rate (l/min) 4

Initial particle velocity (m/s) 0.3

30

3. Results and Discussion

3.1 Wheat straw

3.1.1 Temperature and burnout

Figure 3.1 shows the measured temperature profiles along the axis of the drop tube furnace for all the

samples of wheat straw studied. It is possible to observe that in regions near the burner there are no

significant variations in the temperature profiles with the particle size of the sample. Variations start to

become noticeable near the middle of the reactor, as the particles approach the reactor exit.

Figure 3.1 Temperature profiles for wheat straw.

Figure 3.2 shows the burnout profiles along the axis of the drop tube furnace for all the samples of wheat

straw studied. The effect of particle size on particle burnout is remarkable. At the exit of the reactor, the

particle burnout increases as the initial particle size of the sample decreases. The difference between

the highest and the lowest values of particle burnout, corresponding to the smaller and larger particle

size classes, respectively, is around 40%, at x = 1100 mm.

For 100-200 µm particle size class, burnout varies between 75.9% at x = 300 mm and 93.6% at x =

1100 mm. This size class reaches constant levels of burnout very early in the reactor (around x = 700

mm). This behaviour may indicate that the particle residence time is more than enough to ensure

maximum oxidation, which is compatible with the assumption of an almost-complete combustion.

For the intermediate particle size class of 400-600 µm, burnout variations vary from 22.2% at x = 300

mm to 91.4% at x = 1100 mm. For 800-1000 µm particle size class, burnout varies between 7.3% at x =

300 mm, and 54.4%, at x = 1100 mm. Such a variation can be explained by the initial particle size. Since

the particle is too large, the residence time associated for this condition does not allow the particle to

31

reach a higher degree of char oxidation. In regard to the original wheat straw, with particle size below

1000 µm, burnout varies between 8.3% at x = 300 mm and 67.8% at x = 1100 mm.

Overall, larger particles require longer residence times than smaller particles, so that the burnout can

be higher. Samples have residence times necessary to the completion of the combustion process in the

following ascending order: 100-200 µm, 400-600 µm, raw and 800-1000 µm.

Figure 3.2 Burnout profiles for wheat straw.


Figure 3.3 shows the PM emissions and particle burnout for three axial positions along the axis of the

DTF, namely x = 700 mm, 900 mm and at 1100 mm from the top of the DTF, for all the samples of wheat

straw studied.

For the 100-200 µm particle size class (Figure 3.3a), particle burnout varies between 92.2% for x = 700

mm and 93.6% for x = 1100 mm, while the concentration of PM with size below 10 µm (PM2.5 and PM2.5-

10) increase from 97.8% for x = 700 mm to 99.3% for x = 1100 mm, and the concentration of PM with

size above 10 µm (PM10) decreases from 2.2% to almost 0. Between x = 900 mm and the exit of the

DTF, the increase in PM below 10 µm, together with the sudden decrease of PM10, could indicate the

occurrence of secondary fragmentation. In addition, particle burnout remains almost constant between

these two stages.

For the 400-600 µm particle size class (Figure 3.3b), particle burnout varies between 84.7% for x = 700


10) increase from 89.9% for x = 700 mm to 98.3% for x = 1100 mm, and the concentration of PM with

size above 10 µm (PM10) decreases from 10.1% to 1.7%. Some evidences of particle fragmentation can

be seen between x = 900 mm and x = 1100 mm, where both particle burnout and the total concentration

32

of PM are almost constant, varying only the relative concentration of PM10, which has a considerable

reduction, in contrast with the increase of PM below 10 µm.

For particles between 800-1000 µm (Figure 3.3c), particle burnout varies from 36.6% at x = 700 mm

and 54.4% at x = 1100 mm. The concentration of PM2.5 and PM2.5-10 vary from 70.7% for x = 700 mm

and 92.6% for x = 1100 mm, with the PM10 decreasing from 29.3% to 7.4%. Therefore, it is not possible

to conclude clearly that the increase in PM below 10 µm, contrasting with the decrease in PM above 10

µm, is a direct result of the secondary fragmentation process due to the high variation of particle burnout

that occurs between the two axial positions (around 26%).

In regard to the original wheat straw (Figure 3.3d), particle burnout varies from 54.7% at x = 700 mm to

67.8 at x = 1100 mm. The concentration PM2.5 and PM2.5-10 vary from 89.1% at x = 700 mm to 99.2% at

x = 1100 mm, with the PM10 decreasing from 10.9% to 1.1%. Despite the particle burnout and the PM

concentration remaining almost constant between x = 900 mm and x =1100 mm, the differences in PM

concentration distribution between PM10 and PM2.5 and PM2.5-10 do not allow to state clearly the

occurrence of fragmentation.

Figure 3.4 shows the particle size distributions obtained with the aid of the DLPI of 13 stages at x = 1100

mm. The samples with particle size between 100-200 µm, 400-600 µm and with particle size below 1000

µm shows a bimodal particle size distribution, contrasting with the unimodal behaviour of the 800-1000

µm particle size class. The fine mode for all conditions is centred on 0.3 µm and the intermediate mode

on 0.7 µm. It is possible to identify zones of coarse particles between 1 and 10 µm.

33

Figure 3.3 PM emissions and particle burnout for wheat straw: a) 100-200 µm b) 400-600 µm c) 800-1000 µm d)

original.

34

Figure 3.4 Particle size distribution for wheat straw at x = 1100 mm.

3.1.3 Chemical composition and morphology

Figure 3.5 shows the chemical composition of four selected subtracts, namely 9, 7, 5 and 4,

corresponding to particle diameter cut offs of 1.951 µm, 0.616 µm, 0.265 µm, and 0.158 µm, respectively,

from the 13-stages, for all tested conditions. These substrates were chosen in order to cover different

PM sizes collected in the DLPI.

The most relevant elements are potassium (K) and chlorine (Cl), having higher concentrations in the

subtracts with particles with lower diameters. Other relevant conclusion is the presence of calcium (Ca)

and phosphorus (P) only in the subtract 9, and in subtract 7 for the particle size class of 800-100 µm

(Figure 3.5c), indicating that these elements are retained only in the particles with higher diameters. The

concentration of both elements is directly proportional to the initial particle size of the samples. This

result matches what is expected from other studies on inorganic matter release from biomass

combustion.

The presence of significant quantities of iron is observed in all samples, with the exception of the 800-

1000 µm size class. Some studies on coal combustion suggested that the presence of iron on smaller

particles can be a result of char fragmentation [43].

Figure 3.6 shows the images obtained using the SEM for all substrates previously selected. In general,

it is possible to observe some differences between substrates. For example, in the case of the 100-200

µm size class (Figure 3.6a), it is possible to identify larger particles in subtracts 7 and 9, and the

existence of spherical and prismatic structures. These structures are also visible in the 400-600 µm size

35

class (Figure 3.6b) and original biomass (Figure 3.6d). In the size class 800-1000 µm (Figure 3.6c), it is

not possible to visualize clearly the shape of the fine particles in substrates 4 and 5, due to the

occurrence of water condensation. Other important observation relates to the size of the spherical and

prismatic structures found in the original biomass (Figure 3.5d), which tend to be substantially larger

compared to the other biomass size classes. This fact is confirmed by the results obtained by EDS

analysis, which reveals higher amounts of certain inorganic elements.

36

Figure 3.5 Chemical composition obtained using the SEM-EDS for wheat straw char: a) 100-200 µm b) 400-600

µm c) 800-1000 µm d) original.

37

Figure 3.6 SEM images for wheat straw char: a) 100-200 µm b) 400-600 µm c) 800-1000 µm d) original.

3.2 Rice husk

3.2.1 Temperature and burnout

Figure 3.7 shows the measured temperature profiles along the axis of the drop tube furnace for all the

samples of rice husk studied. It is possible to observe that the higher temperatures zones are located in

the regions near the burner for all cases.

Figure 3.8 shows the burnout profiles along the axis of the drop tube furnace for all the samples of rice

husk studied. The effect of particle size on particle burnout is less pronounced when compared with the

wheat straw, but even though, some differences should be noted. At the DTF exit, particle burnout

increases as the particle size decreases. However, the difference between the highest and the lowest

particle burnout values at the exit of the reactor, corresponding to the smaller and larger particle size

classes, respectively, is only around 21%. As the particles reaches the reactor exit, the differences

observed between the samples become less significant.

38

Figure 3.7 Temperature profiles for rice husk.

For the 100-200 µm particle size class, particle burnout varies between 77.8% at x = 300 mm and 97.8%

at x = 1100 mm. For the 400-600 µm particle size class, particle burnout ranges from 37.2% at x = 300

mm to 93.2% at x = 1100 mm. For the 800-1000 µm particle size class, burnout varies between 6.9% at

x = 300 mm and 77.2% at x = 1100 mm. For the original particle size, particle burnout varies between

13.1% at x = 300 mm and 82.1% at x = 1100 mm. Given the fact that differences between burnout

profiles are smaller, when compared with wheat straw, it can be concluded that in the case of rice husk,

the effect of particle size does not have significant impact on combustion behaviour. The residence time

necessary to achieve the nearly complete combustion state has a slight variation between all the rice

husk samples, suggesting that the reactivity of the samples are very similar.

Figure 3.8 Burnout profiles for rice husk.

39


Figure 3.9 shows the PM emissions and particle burnout along the axis of the drop tube furnace for

three axial positions, namely x = 700 mm, 900 mmm and at 1100 mm from the top of the DTF, for all

samples of rice husk studied.

For the 100-200 µm particle size class (Figure 3.9a), particle burnout varies between 96.9% for x = 700


10) increase from 97.8% to 99.0%, and the concentration of PM with size above 10 µm (PM10) decreases

from 2.2% to 1%. For this condition, secondary fragmentation can occur especially between x = 900 mm

and x = 1100 mm, where a sudden increase in PM2.5, followed by the decrease of PM2.5-10 and PM10 is

verified.

For the 400-600 µm particle size class (Figure 3.9b), as presented previously, particle burnout varies

between 92.3% for x = 700 mm and 93.2% for x = 1100 mm, while the concentration of PM with size

below 10 µm (PM2.5 and PM2.5-10) increase from 95.3% for x = 700 mm to 97% for x = 1100 mm, and the

concentration of PM with size above 10 µm (PM10) decreases from 4.7% to 2.7%. Despite the particle

burnout and the total PM concentration remaining almost constant between stages, the differences in

PM concentration distribution between PM10, PM2.5 and PM2.5-10 do not allow to state clearly that char

fragmentation have occurred.

For the 800-1000 µm particle size class (Figure 3.9c), particle burnout varies from 71.2% at x = 700 mm

to 77.2% at x = 1100 mm. The concentration of PM2.5 and PM2.5-10 varies, for the same DTF axial

positions, from 87.7% to 90.9% with the PM10 decreasing from 12.3% to 9.1%. For this condition, it is

not possible to conclude regarding the occurrence of secondary fragmentation because of the significant

variations verified in particle burnout.

For the original rice husk, with particle sizes below 1000 µm (Figure 3.9d), particle burnout varies from

81.0% at x = 700 mm to 82.0% at x = 1100 mm. The concentration of PM2.5 and PM2.5-10 vary from 98.1%

at x = 700 mm to 99.3% at x = 1100 mm, with the PM10 decreasing from 1.9% to almost 0%. Small

changes in PM2.5-10 and PM2.5 from x = 900 mm to x = 1100 mm could indicate the occurrence of

secondary fragmentation, however a clear statement on secondary fragmentation occurrence it is not

possible. The same trends regarding particle burnout versus total PM concentration can be verified in

the previous results. As the particle burnout increases, the total PM concentration tends to decrease, as

a result of the higher level of conversion and vice-versa. When compared to wheat straw, rice husk has

smaller total PM concentrations, because burnout levels are higher.

40

Figure 3.9 PM emissions and particle burnout for rice husk: a) 100-200 µm b) 400-600 µm c) 800-1000 µm d)

original.

41

Like the wheat straw samples, it has been found that PM emissions from the rice husk samples are

dominated by PM2.5. Figure 3.10 shows the particle size distributions obtained with the aid of the DLPI

of 13 stages at x = 1100 mm. The behaviour of the rice husk regarding the particle size distribution is

rather different than that observed for the wheat straw. All the rice husk samples revealed a unimodal

behaviour. The fine mode is centred on 0.3 µm. It is possible to identify zones of coarse particles

between 1 and 10 µm.

Figure 3.10 Particle size distribution for rice husk at x = 1100 mm.

3.2.3 Chemical composition and morphology

Figure 3.11 shows the chemical composition of 4 selected subtracts, namely 9, 7, 5 and 4, corresponding

to particle diameter cut offs of 1.951 µm, 0.616 µm, 0.265 µm, and 0.158 µm, respectively, from the 13-

stages DLPI, for all tested conditions.

Potassium (K) and chlorine (Cl) remained as the most relevant elements, although sulphur (S) appears

here in larger quantities than in the wheat straw samples. This fact could be explained by the ash

composition of the rice husk, which are very rich in silicon (around 90% in contrast with 40% for wheat

straw).

There is no significant changes in the global concentration of K and Cl between subtracts, with the

exception of the original rice husk size class, where K and Cl increases as the subtract particle cut off

decreases. This conclusion is in line with previous findings regarding inorganic matter emissions, i.e.,

these elements tend to nucleate and grow on the surface of small particles. This conclusion is reinforced

by the fact that this particular sample includes originally a considerable amount of fine particles.

42

It should be noted the presence of calcium (Ca) and phosphorus (P) as well, especially in the substrats

that contains particles with larger sizes. A similar conclusion could be deduced regarding the ability of

these elements to be retained in particles with larger diameters. The concentration of Ca and P is directly

proportional to the initial particle size of the samples.

Figure 3.12 shows the images obtained using the SEM of all substrates previously selected. It is possible

to observe some differences between substrates. For example, the 100-200 µm size class (Figure

3.12a) has residual crystalline structures. In the substrats containing larger particles (7 and 9), however,

as the initial particle size increases, the spherical structures become more evident. In substrats

containing small particles, namely substrats 4 and 5 (Figure 3.12c and Figure 3.12d), spherical

structures are replaced by prismatic structures with considerable size.

43

Figure 3.11 Chemical composition obtained using the SEM-EDS for rice husk char: a) 100-200 µm b) 400-600

µm c) 800-1000 µm d) original.

44

Figure 3.12 SEM images for rice husk char: a) 100-200 µm b) 400-600 µm c) 800-1000 µm d) original.

45

4. Closure

4.1 Conclusions

The main objective of this study was to examine the effect of particle size on the burnout and emissions

of particulate matter from biomass combustion in a drop tube furnace. Wheat straw and rice husk were

separated into three narrow particle size classes to perform the experiments. Additionally, original

samples of each biomass, with particle size below 1000 µm, were also studied. The major conclusions

are as follows:

1. The effect of the initial particle size is more accentuated in the case of the wheat straw than in

the case of the rice husk. The morphology and pre-treatment that the samples were subject to

may be responsible for this behavior. Smaller particles tend to be more reactive than larger

particles.

2. The effect of the initial particle size in PM emissions is more evident in the case of the wheat

straw. The higher burnouts of rice husk results in lower total concentrations of PM.

2.1 Occurrence of particle fragmentation is more evident in biomass fuels with initial small (100-

200 µm) to intermediate (400-600 µm) particle size classes than in the case of biomass

fuels with larger particle size classes.

2.2 Emissions of inorganic matter are affected by the initial particle size class and fuel chemical

composition. Larger particles tend to retain more amounts of Ca and P, along with lesser

amounts of Cl and K, which tend to be in the fine particles.

4.2 Future work

For future works, it is recommended to do some deep research in the following topics:

1. To perform this study with biomass solid fuels with similar particle morphology in order to isolate

more clearly the effect of the particle size in the combustion process.

2. To perform measurements with the 13-stage impactor along the DTF in order to obtain more

conclusive results regarding particle fragmentation.

3. To extend this study for other biomass fuels.

46

5. References

[1] Renewable Energy Policy Network for the 21st Century - The First Decade: 2004-2014, 10 Years

of Renewable Energy Progress, (2014).

[2] International Energy Agency, Energy and climate change, World Energy Outlook Special Report.

(2015).

[3] M.F. Demirbas, M. Balat, H. Balat, Potential contribution of biomass to the sustainable energy

development, Energy Conversion and Management. 50 (2009) 1746–1760.

[4] R. Saidur, E.A. Abdelaziz, A. Demirbas, M.S. Hossain, S. Mekhilef, A review on biomass as a

fuel for boilers, Renewable and Sustainable Energy Reviews. 15 (2011) 2262–2289.

[5] P. Basu, Biomass Gasification and Pyrolysis: Practical Design and Theory, Academic Press,

2010.

[6] J.S. Lighty, J.M. Veranth, A.F. Sarofim, Combustion Aerosols Factors Governing Their Size and

Composition and Implications to Human Health, Journal of the Air & Waste Management

Association. 50 (2000) 1565–1618.

[7] R. Guaita, M. Pichiule, T. Mate, C. Linares, J. Diaz, Short-term impact of particulate matter

(PM2.5) on respoiratory mortality in Madrid, International Journal of Environmental Health

Research. 10 (1999) 8–16.

[8] J. Halonen, T. Lanki, T. Tuomi, P. Tiittanen, M. Kulmala, J. Pekkanen, Particulate air pollution and

acute cardiorespiratory hospital admissions and mortality among the elderly, Epidemiology.

(2009) 143–153.

[9] K.-H. Kim, E. Kabir, S. Kabir, A review on the human health impact of airborne particulate matter,

Environment International. 74 (2015) 136–143.

[10] H. Lu, L.L. Baxter, Solid Biofuels for Energy: A Lower Greenhouse Gas Alternative, Springer

London, 2011.

[11] D.A. Tillman, Combustion of Solid Fuels & Wastes, Academic Press, 1991.

[12] J. Saastamoinen, J. Richard, Research in Thermochemical Biomass Conversion, Springer

Netherlands, 1988.

[13] P. Coelho, M. Costa, Combustão, Edições Orion, 2012.

[14] H. Lu, E. Ip, J. Scott, P. Foster, M. Vickers, L.L. Baxter, Effects of particle shape and size on

devolatilization of biomass particle, Fuel. 89 (2010) 1156–1168.

[15] A. Williams, J.M. Jones, L. Ma, M. Pourkashanian, Pollutants from the combustion of solid

biomass fuels, Progress in Energy and Combustion Science. 38 (2012) 113–137.

[16] B. Moghtaderi, A study on the char burnout characteristics of coal and biomass blends, Fuel. 86

(2007) 2431–2438.

[17] H. Wiinikka, R. Gebart, the Influence of Fuel Type on Particle Emissions in Combustion of

Biomass Pellets, Combustion Science and Technology. 177 (2005) 741–763.

[18] R. Esworthy, Air Quality : EPA’s 2013 Changes to the Particulate Matter (PM) Standard, (2015).

[19] O. Senneca, M. Urciuolo, R. Chirone, D. Cumbo, An experimental study of fragmentation of coals

during fast pyrolysis at high temperature and pressure, Fuel. 90 (2011) 2931–2938.

47

[20] U. Arena, A. Cammarota, R. Chirone, Primary and secondary fragmentation of coals in a

circulating fluidized bed combustor, Symposium (International) on Combustion. 25 (1994) 219–

226.

[21] J.K. Jokiniemi, T.J. Lind, J. Hokkinen, J. Kurkela, E.I. Kauppinen, Modelling and experimental

results on aerosol formation, deposition and emissions in fluidized bed combustion of biomass,

Aerosols from Biomass Combustion. (2001) 31–40.

[22] I. Obernberger, T. Brunner, M. Joller, Characterisation and formation of aerosols and fly-ashes

from fixed-bed biomass combustion, Aerosols from Biomass Combustion. (2001) 69–74.

[23] L.J.R. Nunes, J.C.O. Matias, J.P.S. Catalão, Biomass combustion systems: A review on the

physical and chemical properties of the ashes, Renewable and Sustainable Energy Reviews. 53

(2016) 235–242.

[24] O. Sippula, T. Lind, J. Jokiniemi, Effects of chlorine and sulphur on particle formation in wood

combustion performed in a laboratory scale reactor, Fuel. 87 (2008) 2425–2436.

[25] I. Obernberger, T. Brunner, G. Barnthaler, Chemical properties of solid biofuels-significance and

impact, Biomass and Bioenergy. 30 (2006) 973–982.

[26] H. Bockhorn, Soot formation in combustion: mechanisms and models, Springer-Verlag, 1994.

[27] J. Ballester, J. Barroso, L.M. Cerecedo, R. Ichaso, Comparative study of semi-industrial-scale

flames of pulverized coals and biomass, Combustion and Flame. 141 (2005) 204–215.

[28] H. Spliethoff, K.R.G. Hein, Effect of co-combustion of biomass on emissions in pulverized fuel

furnaces, Fuel Processing Technology. 54 (1998) 189–205.

[29] J.M. Steer, R. Marsh, D. Morgan, M. Greenslade, The effects of particle grinding on the burnout

and surface chemistry of coals in a drop tube furnace, Fuel. 160 (2015) 413–423.

[30] S. Jiménez, J. Ballester, Particulate Matter Formation and Emission in the Combustion of

Different Pulverized Biomass Fuels, Combustion Science and Technology. 178 (2006) 655–683.

[31] Y. Ninomiya, L. Zhang, A. Sato, Z. Dong, Influence of coal particle size on particulate matter

emission and its chemical species produced during coal combustion, Fuel Processing

Technology. 85 (2004) 1065–1088.

[32] F.F. Costa, M. Costa, Evaluation of Particle Fragmentation of Raw and Torrified Biomass in a

Drop Tube Furnace, Physics Procedia. 66 (2015) 277–280.

[33] H. Haykiri-Acma, A. Baykan, S. Yaman, S. Kucukbayrak, Effects of fragmentation and particle

size on the fuel properties of hazelnut shells, Fuel. 112 (2013) 326–330.

[34] X. Gao, H. Wu, Biochar as a fuel: 4. Emission behavior and characteristics of PM 1 and PM10

from the combustion of pulverized biochar in a drop-tube furnace, Energy & Fuels. 25 (2011)

2702–2710.

[35] S. Yani, X. Gao, H. Wu, Emission of inorganic PM10 from the combustion of torrefied biomass

under pulverized-fuel conditions, Energy & Fuels. 29 (2015) 800–807.

[36] W.S. Seames, An initial study of the fine fragmentation fly ash particle mode generated during

pulverized coal combustion, Fuel Processing Technology. 81 (2003) 109–125.

[37] D. Yu, M. Xu, H. Yao, X. Liu, K. Zhou, L. Li, et al., Mechanisms of the central mode particle

formation during pulverized coal combustion, Proceedings of the Combustion Institute. 32 II

48

(2009) 2075–2082.

[38] M. Almeida, Fragmentação de partículas durante os estágios finais da combustão de biomassa

numa fornalha laboratorial, Master Thesis. (2015).

[39] R. Korbee, K. V. Shah, M.K. Cieplik, C.I. Betrand, H.B. Vuthaluru, W.L. Van De Kamp, First line

ash transformations of coal and biomass fuels during pulverized fuel combustion, Energy &

Fuels. 24 (2010) 897–909.

[40] G. Wang, R.B. Silva, J.L.T. Azevedo, S. Martins-Dias, M. Costa, Evaluation of the combustion

behaviour and ash characteristics of biomass waste derived fuels, pine and coal in a drop tube

furnace, Fuel. 117 (2014) 809–824.

[41] C.R. Shaddix, Correcting thermocouple measurements for radiation loss: a critical review,

Proceedings of the 33rd National Heat Transfer Conference. (1999).

[42] F.F. Costa, G. Wang, M. Costa, Combustion kinetics and particle fragmentation of raw and

torrified pine shells and olive stones in a drop tube furnace, Proceedings of the Combustion

Institute. 35 (2015) 3591–3599.

[43] C. Wen, X. Gao, Y. Yu, J. Wu, M. Xu, H. Wu, Emission of inorganic PM10 from included mineral

matter during the combustion of pulverized coals of various ranks, Fuel. 140 (2015) 526–530.

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