Experimental Investigation of The Effects of Fuel ... · Liquid-Ethanol Blends in a Swirl Burner...

Experimental Investigation of The Effects of Fuel Properties on

Combustion Performance and Emissions of Biomass Fast

Pyrolysis Liquid-Ethanol Blends in a Swirl Burner

by

Sina Moloodi

A thesis submitted in conformity with the requirements

for the degree of Master of Applied Science

Graduate Department of Mechanical and Industrial Engineering

University of Toronto

Copyright© 2011 by Sina Moloodi

ii

Abstract

Experimental Investigation of The Effects of Fuel Properties on

Combustion Performance and Emissions of Biomass Fast Pyrolysis

Liquid-Ethanol Blends in a Swirl Burner

Sina Moloodi

Master of Applied Science

Graduate Department of Mechanical and Industrial Engineering

University of Toronto

2011

Biomass fast pyrolysis liquid, also known as bio-oil, is a promising renewable fuel for heat and

power generation; however, implementing crude bio-oil in some current combustion systems can

degrade combustion performance and emissions. In this study, optimizing fuel properties to

improve combustion is considered. Various bio-oils with different fuel properties are tested in a

pilot stabilized spray burner under very close flow conditions. Effects of solids, ash and water

content of bio-oil as well as ethanol blending were examined. The results show the amount of

solids and ash fractions of the fuel were correlated with combustion efficiency. The CO and

unburned hydrocarbon emissions decreased with both water and ethanol content. Increasing the

fuel’s volatile content by blending in ethanol has been shown to improve flame stability. Also,

the organic fraction of particulate matter emissions was found to be a strong function of the

thermogravimetric analysis residue of the fuel.

iii

Acknowledgements

I would like to thank Professor Murray J. Thomson for his guidance and supervision during the

course of this project. This work would not have been possible without the help and support of

my parents. I also acknowledge the contribution of my brother, Soheil, for being always there for

me and providing moral support.

Dr. Tommy Tzanetakis, deserves special thanks for being my mentor, and for his endless support

during various stages of this project. I am indebted to Nicolas Farra, because of his generous

advice during the design stage of the work and also for setting up the gas analysis instruments. I

am also grateful for all the support and help received from Brian Nguyen during the setup design,

construction, and running the experiments.

Many thanks to Milad Zarghami-Tehran and Umer Khan for their helps during the experiments

and also Arran Mc.Grath for providing me with precious insight into the modeling aspects of the

project and for being such a generous colleague. I would also like to thank R. Rizvi and

Professor H. Naquib for their help with the thermogravimetric analyzer. The help and support of

other combustion research group members, especially, Meghdad, Parham and Coleman is

gratefully appreciated.

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Table of Contents

Abstract………………………………………………………………………………………....…ii

Acknowledgements……………………………………………………………………………....iii

Table of Contents ........................................................................................................................... iv

List of Tables ............................................................................................................................... viii

List of Figures ................................................................................................................................ ix

Nomenclature ................................................................................................................................ xii

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

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

1.2 Objective ............................................................................................................................. 2

Literature Review ....................................................................................................................... 3 2

2.1 Thermochemical Conversion of Biomass to Fuel ............................................................... 3

2.2 Fast Pyrolysis Process ......................................................................................................... 4

2.3 Bio-oil properties ................................................................................................................ 5

2.3.1 Water Content ......................................................................................................... 6

2.3.2 Solids Content ......................................................................................................... 7

2.3.3 Ash Content ............................................................................................................ 9

2.3.4 Evaporation of Bio-oil and Ethanol as an Additive .............................................. 10

2.3.5 Other Properties .................................................................................................... 12

2.4 Fundamentals of bio-oil combustion ................................................................................ 14

v

2.5 Heat and Power Generation from Bio-oil ......................................................................... 16

2.5.1 Heat Generation in Boilers and Furnaces ............................................................. 16

2.5.2 Gas Turbines and Diesel Engines ......................................................................... 18

Experimental Methodology ...................................................................................................... 20 3

3.1 Bio-oil Burner ................................................................................................................... 20

3.1.1 Swirl Combustor ................................................................................................... 22

3.1.2 Fuel Nozzle ........................................................................................................... 25

3.1.3 The Pilot flame ...................................................................................................... 29

3.2 Measurement and Analysis Tools ..................................................................................... 30

3.2.1 Fuel Analysis ........................................................................................................ 30

3.2.1.1 Basic Fuel Properties .............................................................................. 30

3.2.1.2 Thermogravimetric Analysis (TGA) ...................................................... 31

3.2.1.3 Photo microscopy ................................................................................... 31

3.2.2 Gas phase species measurement systems .............................................................. 32

3.2.2.1 Oxygen Sensor ........................................................................................ 32

3.2.2.2 Flame Ionization Detector (FID) ............................................................ 33

3.2.2.3 Fourier Transform Infrared Spectroscopy (FTIR) .................................. 33

3.2.3 Particulate Matter Measurement System .............................................................. 35

3.2.3.1 Isokinetic Particulate Matter Sampling .................................................. 35

3.2.3.2 Gravimetric Analysis and Loss on Ignition Test .................................... 40

vi

3.2.3.3 Uncertainty Level of Particulate Matter Measurement System.............. 43

3.2.4 Flame Photography ............................................................................................... 44

3.3 Combustion Test Procedure .............................................................................................. 45

Results and Discussion ............................................................................................................. 49 4

4.1 Experimental Test Plan ..................................................................................................... 49

4.2 A Conceptual Model of Bio-oil Combustion .................................................................... 52

4.3 Ethanol Tests ..................................................................................................................... 53

4.4 Solids and Ash Tests ......................................................................................................... 57

4.5 Water Tests ....................................................................................................................... 62

4.6 NOx Emissions of Bio-oil Blends ...................................................................................... 65

4.7 Acetaldehyde, Formaldehyde and Methane Emissions .................................................... 67

4.8 A Linear Model for CR Emission Index ........................................................................... 68

4.9 Pure bio-oil Combustion and Comparison with Heavy Fuel Oil ...................................... 70

4.10 Unsuccessful Works .......................................................................................................... 73

Conclusions and Recommendations ........................................................................................ 75 5

5.1 Conclusions ....................................................................................................................... 75

5.2 Recommendations and future works ................................................................................. 76

References ..................................................................................................................................... 79

A Theoretical Isokinetic Sampling Flow Rate…………………………………………………86

B The Flow Straightener Drawing…………………………………………………….……….89

vii

C Table of Fuel Properties, Test Conditions and Emissions…………………………………..91

D TGA Curves………………………………………………………………………………....96

E Microscopic Photos……………………………………………………………………….....99

F FTIR Calibration Method……………………………………………………………….......101

G Data Acquisition System and a Sample of Recorded Data…………………………………104

viii

List of Tables

Table 3.1. List of basic fuel properties measurement standards ................................................... 31

Table 3.2. Detection limits and uncertainty levels of the FTIR models ....................................... 34

Table 3.3. Calculation methods of different PM fractions ............................................................ 42

Table 3.4. Uncertainties associated with EICR measurements ...................................................... 44

Table 4.1. Number one and two operating conditions .................................................................. 50

Table 4.2. Primary properties and emissions of ethanol, solids/ash, water and heavy fuel oil

batches at base operating condition ...................................................................................... 51

Table 4.3. NOx emissions of the ethanol, solids/ash, water and heavy fuel oil batches at base

operating condition ............................................................................................................... 51

Table 4.4. Batches with non-zero acetaldehyde, formaldehyde and methane emissions ............. 67

Table 4.5. Tests with PM collection efficiencies not equal to 100% ............................................ 69

Table 4.6. The regression analysis results and averages of parameters ........................................ 70

Table 4.7. Comparison of heavy fuel oil and pure bio-oil properties and emissions ................... 71

Table 4.8. Comparison of NOx and flame temperatures of bio-oil and heavy fuel oil ................. 71

Table C.1. Fuel properties table…………………………………………………………………93

Table C.2. Summary of test conditions………………………………………………………….94

Table C.3. Summary of all emissions………………………………………………………....…95

ix

List of Figures

Figure 2.1. Fast pyrolysis process [3] ............................................................................................. 5

Figure 2.2. Non-evaporated mass fraction of bio-oil sample(Y) as a function of temperature and

time for bio-oils from different pyrolysis plants (in air atmosphere) [22] ............................ 11

Figure 2.3. TGA curves of pure bio-oil and ethanol-bio-oil mixtures in nitrogen [6] .................. 12

Figure 2.4. Kinematic viscosity of a mixture of 80% vol. bio-oil and 20% vol. ethanol mixture

[6] .......................................................................................................................................... 13

Figure 2.5. From left to right, stages of bio-oil droplet combustion [16] ..................................... 15

Figure 2.6. The last stage of droplet combustion; burning of a cenospheric residue [16] ............ 15

Figure 3.1. The Bio-oil Burner ..................................................................................................... 21

Figure 3.2. Schematic of the experimental setup [4] .................................................................... 22

Figure 3.3. Calculated streamlines in a free annular jet with a swirl number of 1.57 [37] ........... 24

Figure 3.4. Drawings of different flame regimes in a swirl combustor; Coanda stabilized flame

(CSF), Nozzle stabilized flame (NSF), swirl stabilized Flame (SSF), pinched jet flame

(PJF), back-wall stabilized flame (BSF) [38] ....................................................................... 25

Figure 3.5. Schematic of the air blast atomizer [4] ....................................................................... 26

Figure 3.6. The fuel nozzle after at least 50 hours of bio-oil operation ........................................ 26

Figure 3.7. Nozzle cooling system schematic ............................................................................... 28

Figure 3.8. Good and poor alignments of the fuel nozzle [4] ....................................................... 30

Figure 3.9. Schematic of the gas phase emissions measurement system [4] ................................ 32

Figure 3.10. Gas stream lines around the probe when sampling velocity is lower than the main

stream velocity [46] .............................................................................................................. 36

x

Figure 3.11. PM sampling system piping diagram ....................................................................... 38

Figure 3.12. Isokinetic probe dimensions and the pressure taps [7] ............................................. 39

Figure 3.13. The loss on ignition and gravimetric analysis procedure ......................................... 42

Figure 3.14. Borescope schematic ................................................................................................ 45

Figure 4.1. Pollutants formation mechanisms of the bio-oil combustion ..................................... 53

Figure 4.2. Increase of the emissions by increase in the TGA residue ......................................... 54

Figure 4.3. Average CO and UHC as functions of ethanol volume fraction ................................ 56

Figure 4.4. Modified CR emission index as a function of ethanol volume fraction ..................... 56

Figure 4.5. Borescopic photos of bio-oil-ethanol blend flames with different ethanol content:

(a)25%, (b)20%, (c)15%, (d)10%, (e)5% ............................................................................ 57

Figure 4.6. Average CO and UHC as functions of solids mass fraction for batches S2, 3, 4 ....... 58

Figure 4.7. CR emission index as a function of solids mass fraction for batches S2, 3, 4 ........... 59

Figure 4.8. Microscopic photos of batches S1-4. All photos are taken using the same optical

conditions and are 170x240 µm ............................................................................................ 61

Figure 4.9. From left to right: flame photos of S1, 2, 3, 4 ............................................................ 61

Figure 4.10. CO and UHC emissions of W2, 3. W1 not shown because of failing to achieve

stable condition ..................................................................................................................... 63

Figure 4.11.CR emission indexes of W2, 3. W1 not shown because of failing to achieve stable

condition ............................................................................................................................... 63

Figure 4.12. Comparison of Batches W3 and W4 ........................................................................ 65

Figure 4.13. Borescopic photos of the water tests ........................................................................ 65

xi

Figure 4.14. NOx conversion ratio for all bio-oil batches. Error bars show variations of measured

NOx in each test ..................................................................................................................... 67

Figure 4.15. Comparison of the corrected experimental CR emission indexes and the curve fit.

Error bars are not shown since they are negligible compared to the scatter in the

experimental results .............................................................................................................. 70

Figure 4.16. Combustion of fuel oil (left) and pure bio-oil (right) under condition 2 .................. 72

Figure A.1. Average velocity profile inside the exhaust duct [4]……………………………….87

Figure B.1. Flow straightener drawing………………………………………………………….90

Figure D.1. TGA curves of batches S1, 2, 3, 4………………………………………………….97

Figure D.2. TGA curves of batches S5 and S6………………………………………………….97

Figure D.3. TGA curves of batches W1, 2, 3……………………………………………………98

Figure D.4. TGA curves of batches E0, E20, H1 and Diesel. …………………………………..98

Figure E.1. Microscopic photos of the batches that clogged the nozzle ……………………….100

Figure F.1. Schematic of the carbon dioxide calibration setup…………………………………103

Figure G.1. Front panel of the Labview program………………………………………………105

Figure G.2. All temperatures logged testing batch W3 ………………………………………..106

Figure G.3. Logged voltage signals when testing batch W3…………………………………...106

xii

Nomenclature

P Pressure

r Radial distance from the center of the burner

R Inner radius of the combustion chamber inlet

S Swirl number

U Axial gas velocity

W Tangential gas velocity

Axial flux of the tangential momentum in the combustor

Axial flux of the axial momentum in the combustor

Fuel mass flow rate

Absolute pressure as measured by the gauge in condenser exit

Gas temperature at the condenser exit

Dry gas flow rate though the PM sampling line

Wet gas flow rate though the PM sampling line

Total exhaust flow rate from the burner

Molar fraction of water in the wet exhaust based on mixture stoichiometry

Sampling time of the filter

xiii

Greek Symbols

ρ Density

σ Surface tension

Abbreviations and Acronyms

ALR Air to liquid ratio

ASTM American society of testing and materials

BD Below detection

CHN Carbon-hydrogen-nitrogen content

CR Carbonaceous residue

EI Emission index

EPA Environmental protection agency

FID Flame ionization detector

FTIR Fourier transform infrared spectrometer

HHV Higher heating value

HMW Higher heating weight

NOx Nitrogen oxides

PM Particulate matter

PPM Parts per million

RMSE Root mean square error

xiv

SAT Saturated

SLPM Standard liters per minute

SMD Sauter mean diameter

TGA Thermogravimetric analysis

UHC Unburned hydrocarbons

VDC Volts DC

1

Chapter 1

Introduction 1

Introduction

1.1 Motivation

The Worlds’ energy consumption is rising steadily and various ways of producing clean and

sustainable energy are being investigated to meet the demand [1]. One way of producing energy

with net greenhouse gas emissions close to zero is using biomass, which is in fact an indirect use

of sunlight [2]. Biomass energy can be released by burning it directly which has been done since

ancient times by setting wood on fire or by combusting it in utility boilers to generate steam

which is done nowadays. Biomass, in its original shape, is usually difficult to handle, transport

and store and electricity generation efficiencies of its utilization in direct combustion systems

are normally about 15% to 30% depending on the scale and the technology level of the plant [3].

Biomass can also be converted into “biofuels” through different processes. Liquid Biofuels are

easier to handle and tend to be cleaner to burn which makes them available to a larger energy

market (road and air transportation for example) compared to the original biomass. However,

upgrading biomass into better quality fuels requires more energy and investment. Therefore,

cost effective upgrading of biofuels must be carefully done to a degree that these fuels are

economically competitive with fossil fuels and at the same time have similar combustion

performance for the intended purpose.

One such biofuel is “bio-oil” which is produced from biomass by a process called fast

pyrolysis which essentially converts biomass into a liquid by cracking the large molecules in it.

This process is flexible and can give different quality fuels with different physical and chemical

properties. Bio-oil is currently used for generating heat in mostly large scale boilers with long

residence times, but some properties of bio-oil make its utilization in a small scale burner with

short combustion residence times difficult. These properties include high viscosity, low heating

2

value compared to most hydrocarbon fuels, narrower flammability limits, existence of solid

particles, water, and ash which usually result in high emission levels compared to light heating

fuels [4]. Previous studies have investigated the potential of bio-oil for small scale heat

applications and have found the burner design requirements necessary for stable combustion of

bio-oil [5], [6], [7]. However, there is almost no literature regarding the effects of fuel properties

on combustion performance in a spray burner and how bio-oil compares to standard

hydrocarbon fuels. Such information would provide guidelines for bio-oil producers in making

the optimized fuel for a small scale burner and would shed some light on how bio-oil

optimization can solve bio-oil utilization problems in higher efficiency power generation

systems like gas turbines and diesel engine.

1.2 Objective

The primary target of this study is investigating the effects of fuel properties on combustion

performance and emissions of wood derived bio-oil and explaining the results by considering

fundamentals of the bio-oil combustion process. The fuel properties considered here are the ones

that can be controlled by adjusting the production process including the solids, ash and water

content of bio-oil. The effect of ethanol addition to bio-oil is also studied since it is reported to

be a simple upgrading method for bio-oil. In addition, ethanol addition shifts the molecular

weight distribution of bio-oil towards the lighter compounds, which simulates a higher degree of

cracking in bio-oil production. To this end, various batches of bio-oil with different properties

are tested in a pilot stabilized swirl burner designed and characterized by Tzanetakis [4].

Combustion performance is monitored by measuring gas phase and particulate matter emissions,

combustion chamber pressure and flame photography.

Another objective of this study is to develop a particulate matter (PM) measurement

system capable of quantifying ash and organic matter fractions of PM. This measurement

system is used in identifying the key fuel parameters that affect the PM emissions. These

emissions are critically important when considering bio-oil utilization in diesel engines, gas

turbines and also small scale boilers. In addition, the role thermogravimetric analysis can play in

predicting the bio-oil combustion emissions, is investigated. Yet another goal is comparing

combustion of bio oil and number 4 fuel oil under similar burner conditions.

3

Chapter 2

Literature Review 2

Literature Review

2.1 Thermochemical Conversion of Biomass to Fuel

Renewable energy from sustainable biomass resources is one alternative to fossil fuel based

energy. Various types of biomass can be utilized to generate energy. Fuels produced from

sugars, grains or seeds are generally called first generation biofuels [8].One such biofuel is

bioethanol produced from fermentation of crop plants. These fuels have one major problem

which is being in competition with food crops. This competition results in the global increase in

food and fuel cost. Second generation biofuels on the other hand, are generated from non-edible

and usually waste feedstock. Examples are lignocellulosic biomass from wood, pulp and paper

industries, forestry residues, and residues of food crop production. Biomass for second

generation biofuels can be optimized for land and water use and this is the main advantage over

first generation biofuels. This study focuses on one example of second generation biofuels.

Three dominant routes of converting biomass into energy are discussed in the literature:

thermochemical, physical and biological conversion [3]. Thermochemical conversion of

biomass into energy is most commonly done in three ways: combustion, gasification, and

pyrolysis. Direct combustion of biomass is by far the most widely used method and accounts for

over 97% of bioenergy production in the world [2] . Efficiency, emissions and handling issues

leave large scale combustion of biomass a challenge. Gasification converts the biomass into a

mixture of combustible gases (mostly H2, CO, CO2, and CH4) in presence of oxygen at high

temperatures [2]. There are various reactor types and processes for gasification. But typically,

ground biomass, is fed in the gasification reactor, and then dries as it becomes in contact with

the circulating material. The dried particles of biomass are then pyrolysed and give vapors, non-

condensable gases, tar vapors and solid residues. Most of these chemicals then partially oxidize

or gasify and any remaining solid char particles or tar are filtered in a cyclone or other gas

4

cleaning processes [3]. One major advantage of gasification is the phase uniformity of the

product gases given the different types of biomass and waste. Syngas can be fed into gas

turbines for very efficient combined gas-steam power cycles. In addition, syngas can be the

input to the Fischer-Tropsch process for the generation of valuable chemicals or synthesized

into fuels like diesel, gasoline or aviation fuels. One shortcoming of gasification is the low

energy density of the syngas and the inherent difficulties with transportation of the gas phase

fuel. Generally it is more economical to have the gasifier and the plant using it at the same

location. Another problem is the challenge associated with removing the tar from the syngas [3].

Pyrolysis is the third most common path of thermochemically converting biomass into

renewable fuel. A recent review describing pyrolysis process and potentials is published by

D.Vamvuka [9]. Thermal decomposition in the absence of oxygen is called pyrolysis and is the

first step in the biomass gasification or combustion process. In pyrolysis process, products are: a

liquid known as bio-oil, flue gases and solid residue in the form of char. The target is usually to

maximize the liquid, as opposted to gasifiers where the target is to maximize the gas yield.The

next section explains the fast pyrolysis process in more detail.

2.2 Fast Pyrolysis Process

Similar to gasifiers, there are various designs for pyrolysis reactors and depending on

temperature, residence time, and heating rate of the biomass in the reactor, products with

significantly different chemical and physical properties can be obtained. Based on the residence

time, this process is categorized into fast, intermediate or slow pyrolysis. Short residence times

combined with high temperatures usually favours higher yield of liquid while long residense

times along with lower temperatures results in the more charcoal [2]. Pyrolysis with a vapor

residence time of about 1 seconds and temperature of approximately 500˚C is known as fast or

flash pyrolysis [2]. Bio-oil from fast pyrolysis process is the subject of this study. The

circulating fluidized bed is a common type of fast pyrolysis reactors and is shown in Figure 2.1.

Biomass is dried and then ground before entering the reactor. The ground biomass converts to

gas, condensable vapors and char particles in reactor. All these intermediate products are carried

to the cyclones where char particles and the fluidizing sand are separated and fed back to the

reactor. Char burns in the reactor to provide heat. Vapor and non-condensable gases are directed

into the condenser units. Non-condensable gases are used for providing heat for the pyrolysis

5

process or other applications. The condensed liquid is bio-oil. Typically, up to 75% of the dry

feedstock mass can be recovered in the bio-oil [2]. One of the main advantages of fast pyrolysis

is the ease of transport and storage of bio-oil. Another advantage, similar to gasification, is the

flexibility of the process in terms of feedstock; nearly 100 types of industrial, forestry and food

processing residues are studied in the literature [3]. As a second generation biofuel, bio-oil can

be used for producing valuable chemicals including hydrocarbon fuels by means of upgrading,

as feed material for gasification process, or power generation by combustion which is the main

focus of this report.

Figure 2.1. Fast pyrolysis process [3]

2.3 Bio-oil properties

Bio-oil is a dark-brown viscous liquid which is a micro-emulsion of pyrolytic lignin macro-

molecules suspended in an aqueous solution of decomposed oxygenated compounds [3], [10].

As many as 300 compounds have been identified in bio-oil; water, acids, alcohols and mostly

polar compounds with relatively low molecular weights form the continuous phase in the micro-

emulsion. Water insoluble compounds are mostly heavy molecular weight partially pyrolysed

polymers originating from the biomass feedstock. Water insoluble compounds form an oily

fraction dispersed in water soluble fraction by hydrogen binding in the form of micelles [10].

The water soluble fraction is usually about 75% of the total mass of the bio-oil and the oily

6

fraction is approximately 25% [4]. Solid particles of char coming from incomplete pyrolysis of

biomass also constitute a small (typically in the order of 0.5 % of mass) fraction of bio-oil. In

addition, a tiny amount of minerals (normally less than 0.1% of mass) in the form of ash exists

in bio-oil. The type and fractions of chemical compounds in bio-oil is a function of the biomass

feedstock and also the pyrolysis process conditions. The most common feedstock used in

pyrolysis is wood which consists of mostly cellulose (40-50% of dry wood mass), hemicellulose

(25-35% of dry wood mass) and Lignin (16-33% of dry wood mass) [11].

2.3.1 Water Content

The most abundant single component in bio-oil is water. Mass fraction of water is between 10-

35% for most of the bio-oils. This fraction depends on the original moister content of biomass

and also on the pyrolysis conditions. Water content of bio-oil is usually measured by the Karl-

Fischer titration method. Bio-oil becomes unstable if more than a certain amount of water is

added to it; the microstructure of the bio-oil will be destroyed and it will separate into water

soluble and oily phases [10]. There are both positive and negative effects of water when

considering bio-oil combustion. On one hand, water decreases the combustion reaction rates,

adiabatic flame temperature, increases the ignition delay time and heat of evaporation [12]. On

the other hand, water can enhance the atomization process through decreasing viscosity and

increasing the chance of effective micro-explosions of the fuel droplets, can reduce NOx

emissions by decreasing the flame temperatures and can accelerate soot oxidation by providing

OH radicals [10, 12, 13].

The water content of bio-oil can be controlled by changing the moisture content of the

biomass fed into the reactor, which is done with a drier. The energy spent on drying the biomass

is not wasted because the water will be eventually vaporized during the pyrolysis process. One

problem with removing water from the biomass before entering the reactor is the beneficial

effect of the steam in the pyrolysis reactor. The literature suggests that water not only increases

the amount of bio-oil yield in the normal pyrolysis process, but also affects the fraction of

volatile matter in the pyrolysis product [13]. Compared to inert atmospheres like nitrogen, water

is reported to be reactive during the pyrolysis and more efficient in the solid biomass particle

penetration and removal of the volatile products from the pores of the particle. These arguments

are likely to hold true during the fast pyrolysis process as well. In addition, water can be

7

controlled by post pyrolysis water removal, but these processes may affect the volatile organic

fraction of the bio-oil as well.

Water is normally a tiny fraction of liquid hydrocarbon fuels since it is not miscible with

non-polar hydrocarbons. However, there are many reports showing the effect of adding water to

the combustion chamber either by emulsifying water into the diesel or by separate injection of

water [14]. Water can decrease the NOx emissions by decreasing the temperature of the

combustion products which is very effective at reducing thermal NOx formation [15]. Soot is

decreased because of the positive effect of OH radicals on soot oxidation. When considering

diesel-water emulsions, water has a lower boiling temperature than diesel. Therefore, during the

combustion and evaporation processes, the droplet may pass the heterogeneous or homogeneous

boiling point of water while diesel is still evaporating and not boiling. This condition can lead to

sudden evaporation of the water existing in the droplet which shatters the original droplet into

satellite ones and effectively decreases the average droplet size. This phenomenon is called

micro-explosion or secondary atomization and is observed in fuels with components that have

significantly different boiling temperature. Micro-explosions enhance the mixing of fuel and

hence suppress soot formation as well as unburned hydrocarbons. Bio-oil also has components

with significantly different boiling points. This causes the bio-oil droplets to undergo micro-

explosions similar to diesel-water emulsions [16]. Single droplet combustion studies have

shown that water addition to bio-oil delays the micro-explosion occurrence, but at the same time

it intensifies the dispersive power of the explosion [17].

2.3.2 Solids Content

Solid particles normally constitute in the order of 0.1% mass of the bio-oils, although this

fraction could be as high as 3% mass. The standard way of measuring the mass fraction of solids

usually involves first diluting and mixing the bio-oil with some powerful solvent like ethanol or

a mixture of methanol and dichloromethane and then filtering the mixture [10]. These solid

particles usually have sizes less than 200 microns [4]. The particles are mostly in the form of

organic char or inorganic ash particles both of which are carried out of the reactor by the

pyrolysis vapors. Char particles are residues of biomass pyrolysis. The size and chemical

characteristics of char particles depends on the biomass grinding degree and the pyrolysis

conditions. Pyrolysis vapors pass through a cyclone to separate the char particles and sand from

8

the vapors (Figure 2.1). Cyclones can capture about 95% of the solid particles in the vapor [18].

However, given the fact that cyclone collection efficiency decreases as the particle size

decreases, it is generally difficult to separate particles of less than 10 micron size and most of

the particles found in bio-oils are about this size [10]. One study showed that numerically, over

93% of the char particles are below 1 micron diameter [18].

Solid particles have several negative effects on bio-oil as a fuel. Char particles can

agglomerate during the storage and form a sludge layer on the bottom of the container. During

the production process, char particles can act as vapor cracking catalysts, so they can decrease

the bio-oil yield. Char has also been reported to accelerate the bio-oil separation process over

long periods, which is called aging in the literature [3]. Solid particles in bio-oil are problematic

in atomizing nozzles because of their erosion and clogging potential. The effect of char content

of fuel on single droplet combustion behavior of bio-oil was studied by Shaddix et al. [17].

They have concluded that char particles can accelerate the micro-explosion process, since char

particles provide nucleation sites for the heterogeneous boiling of the light components.

However, these early micro-explosions are not very effective at shattering the parent bio-oil

droplet and the overall effect of char presence in the bio-oil combustion is not desirable.

One way of further decreasing the fraction of char particles in the bio-oil is hot pyrolysis

vapor filtration [3, 18, 19]. This additional step can give ash levels of approximately 0.01% and

alkali metal content of less than 10 PPM. The bio-oil yield from the process will decrease by

about 10% because of char accumulation on the filter which also acts as a catalyst to crack

vapors [19]. Thermal cracking of hot vapors decreases the average molecular weight of the

resulting bio-oil which is beneficial from combustion chemistry point of view [12]. However,

increased pressure drop over the hot filter is a problem because of the condensation of heavy

fractions of bio-oil and char accumulation over the filter [19]. Cold filtration of bio-oil is

another option for separating char from bio-oil, but the issues with pressure drop and filter

blocking still exists [20]. These problems show the necessity of some study showing the degree

to which solids content should be separated from bio-oil in order to have a reasonable

combustion quality.

9

2.3.3 Ash Content

Ash is defined as the residue of the bio-oil after heating it to 775˚C in the presence of oxygen

[10]. Most of the ash existing in the bio-oil is bound up in the char particles. This ash could also

be originating from the fluidizing material which is usually sand. Therefore, it is expected that

mineral elements existing in the feedstock dominate the ash composition in the bio-oil. One

study on the bio-oil from wood shows trace amounts of some notable alkali metals include

calcium, sodium and potassium, in addition to silicone, iron, aluminum and zinc [20]. The same

study shows that most of the ash resides in the char and a higher percentage of most of the

mineral elements exists in the oily fraction. However, potassium components which are more

water soluble are more found in the aqueous fraction. Alkali metal ions are polar and, over time,

have the potential to leach out from the char into the aqueous fraction. Another study showed

that about all of the potassium in bio-oil is sequestered in char [18] which is in contradiction to

another reference [20]. Both of these studies are done at room temperature, but there is no data

in the literature commenting on the ash leach out at elevated temperature similar to what is

found during bio-oil droplet combustion. Not considering potassium, both studies suggest that

most of the ash exists in the char particles. This situation makes separation of ash from bio-oil

more feasible, as discussed in section 2.3.2 there are a few options for removing char from bio-

oil. One study was successful in reducing the alkali content of the bio-oil to as low as 3 PPM

using the hot vapor filtration method [19].

Ash in bio-oil has a detrimental effect on combustion devices. Ash deposited on the hot

surfaces on turbine blades or heat transfer surfaces of the boilers can cause corrosion or erosion.

For instance, alkali metals of potassium and sodium can form compounds with low melting

points and can stick to the burner surfaces or turbine blades if the temperature is less than the

melting point [10]. This can decrease the desired heat transfer coefficients and can also cause

erosion or corrosion problems for the turbine blades. Analysis of ash remaining after the

combustion of one bio-oil sample shows silicone, aluminum, potassium and calcium were more

abundant than other elements [21]. On the positive side, potassium, sodium, calcium and

silicone ash deposits are not found to form compounds with chlorine, which are highly fouling

[21]. Considering the systems required to handle ash in a power plant, bio-oil utilization is a

major improvement to direct biomass combustion, since pyrolysis and separation of char from

liquid and sequestration of ash in solid char particles, results in the ash concentration in the bio-

10

oil being tens of times lower than the original biomass. For instance, many of the biomass

feedstocks have ashes ranging from 1-15% while bio-oil usually has in the order of 0.1% ash

[18].

2.3.4 Evaporation of Bio-oil and Ethanol as an Additive

Bio-oil consists of components with different boiling points and the mass distribution of these

boiling points is very important for spray combustion applications. In addition, the Pyrolysis

vapor forming bio-oil carries some aerosols into the condenser. This means that, in contrast to

diesel and light hydrocarbon fuels, bio-oil contains some non-distillable fraction [10]. This

property of bio-oil is similar to heavy fuel oils, although the chemical composition of the non-

distillable fractions of these two types of fuel are not necessary very similar. In the previous

works, thermo-gravimetric analysis (TGA) is used as a tool to monitor the different stages of

droplet evaporation and combustion [22]. A TGA test is done by continuously measuring the

mass of a bio-oil sample while heating it up to a certain temperature, at a controlled atmosphere

and heating rate. TGA results of bio-oils from different pyrolysis plants under air atmosphere

show some similar qualitative features and are shown in Figure 2.2 . Most of the volatile

components and water evaporate or boil below 373 K. For temperatures below 450 K,

evaporation and boiling of the components with various boiling points is the reason for the mass

loss. For temperature about 450-600 K, cracking of the heavier molecules and evaporation of the

resulting light molecules is an additional feature. At approximately 600K, the mass loss rate

decreases significantly and visual observations also show swelling and formation of a solid

residue known as “secondary char”, to distinct it form the primary char formed during the

biomass pyrolysis process. The amount of this solid residue remaining from bio-oils from

different pyrolysis sources is reported to be 25-39% [22]. Similar behavior can be observed

when TGA is done under a nitrogen environment (Figure 2.3).

A high mass fraction of volatile material in bio-oil corresponds to a low average

molecular weight and can be observed by a large area under the left hand side of a TGA curve.

The average molecular weight has been shown to affect the ignition delay of bio-oil; a lower

average molecular weight encourages faster evaporation and shorter ignition delay [12]. One

11

way of decreasing the average molecular weight of bio-oil is blending it with lighter fuels.

Ethanol is miscible in bio-oil and has been suggested to improve the ignition properties as well

as expand the operational limits of bio-oil in a spray combustor [6]. Ethanol increases the

volatile fraction of bio-oil, but close analysis of Figure 2.3 shows that ethanol does not have any

effect other than dilution over the secondary char fraction. Methanol was also considered as an

additive to bio-oil in an earlier study [17] . Methanol existence in the bio-oil droplet decreases

the time required for micro-explosions to happen, but compared to water, it is less effective at

dispersing the droplet mass.

Adding lighter fuels to heavier fuels in order to improve the combustion properties is

done in various combinations. For instance, number 6 fuel oil can be blended with number 2

fuel oil to improve the combustion and decrease the non-evaporative fraction of number 6 fuel

oil. As another example, single droplet combustion of ethanol-number 2 distillate fuel solution

was studied by Lashers et al. and ethanol was reported to enhance the atomization by micro-

explosions in a certain concentration range [23]. This secondary atomization can enhance the

fuel-air mixing by dispersing the fuel particles and also decreasing the average droplet size.

Figure 2.2. Non-evaporated mass fraction of bio-oil sample(Y) as a function of

temperature and time for bio-oils from different pyrolysis plants (in air atmosphere) [22]

12

Figure 2.3. TGA curves of pure bio-oil and ethanol-bio-oil mixtures in nitrogen [6]

2.3.5 Other Properties

Bio-oil has several distinctive properties that make it different from hydrocarbon fuels. Some

important features are discussed in this section. Bio-oil has 35-60 wt% oxygen; many of the

components in bio-oil are oxygenated and polar. This means that bio-oil is not miscible in

common hydrocarbon fuels [10]. High oxygen content of this fuel also causes the heating value

of bio-oil to be less than that of petroleum fuels (16 versus 42 MJ/kg on average). The viscosity

of bio-oil is close to that of heavy fuel oils and is a very strong function of temperature. The

kinematic viscosity decreases with temperature and this trend has been shown to exist even in

the ethanol-bio-oil mixture as shown in Figure 2.4. The viscosity of bio-oil is important for

design of fuel injection and pumping systems.

13

Figure 2.4. Kinematic viscosity of a mixture of 80% vol. bio-oil and 20% vol. ethanol

mixture [6]

There is some limited literature about thermophysical properties of bio-oil. The heat

capacity of bio-oil is close to water and higher than diesel fuel. Another important property of

bio-oil is acidity; pH is about 2-4. Stainless steel is the preferred metal for fuel system

components. Bio-oil chemical components are not at equilibrium and this causes the bio-oil to

chemically and physically change during storage. This process is known as aging and the

existence of some compounds in bio-oil that react with themselves and form larger molecules

are responsible for it. Aging has some negative effects on the fuel properties of bio-oil,

including an increase in viscosity, water content and a decrease in volatility [19] . The reactions

responsible for aging happen even at room temperature, but can be slowed down by storage in a

refrigerated environment [4]. If bio-oil is stored at high temperatures for a short period, or a long

period at room temperature (in the order of 6 months), the aqueous and oily fractions of bio-oil

will separate; this phenomena is known as phase separation. The oily phase rests on the bottom

of the container and may eventually become a carbonaceous solid [19].

Ignition of bio-oil is more difficult than hydrocarbon fuels and is usually done with a

pilot flame. This is mostly due to the large fraction of water in fuel which has a very high heat

14

of evaporation [10]. Ignition delay is a critical parameter in designing diesel engines and one

comprehensive study of this subject was published by Shihade et al. [12] which shows bio-oils

with lower average molecular weights and lower fractions of water have better ignition

characteristics.

2.4 Fundamentals of bio-oil combustion

The first series of single droplet combustion experiments on bio-oil were done by Wornat et al.

[16]. These experiments were done by continuously releasing single droplets of bio-oil in a

controlled temperature and pressure environment. Successive stages of droplet combustion are

depicted in Figure 2.5. After ignition the first stage of combustion takes place, volatile

compounds evaporate from the droplet surface and burn in a quiescent spherical blue flame. In

the second stage, since bio-oil is a multi-component fuel and mixing inside the droplet is limited

due to the high viscosity of bio-oil, bubbles of fuel vapor form inside the droplet. Bubble

formation swells the droplet. At the same time, as the volatile material burn and evaporate from

the surface, an outer crust is left with mostly viscous heavy molecular weight compounds which

tend to polymerize and form a shell structure around the droplet [24]. Existence of the shell

structure can be confirmed by evaluating the microscope photos of the droplet residues [7, 17].

This shell acts as a mechanical resistance to droplet size change. The shell combined with the

increased volume of vapor pockets cause the droplet pressure to go up and eventually, the

droplet releases the vapor or explodes. This micro-explosion can disperse the droplet mass and

decrease the effective droplet size. A yellow flame around the droplet at this stage is attributed

to soot formation and oxidation [16]. A similar phenomenon happens in types of gel propellant

combustion, except that instead of heavy molecular weight material on the surface, gallant

forms a layer around the drop and the process of vapor pressure buildup and release is repeated

several times till all of the liquid fuel is burned [25, 26]. Next, the droplet contracts and goes

back to around the original droplet size [25]. The flame surrounding the droplet also shrinks to

the surface showing the significant decrease of evaporation and fuel vapor pressure. Eventually

the flame extinguishes and that point is the beginning of the last stage of the combustion [26]. A

porous cenosphere is what remains from the original droplet at this stage; it burns slowly in a

non-volatile solid particle combustion mode similar to coal [15]. Carbon to oxygen ratio for this

residue is 9 to 1 and the porous structure is reported to consist of cellular type building blocks

15

[16]. The heterogeneous burning stages of this carbonaceous residue can be seen in Figure 2.6.

Usually 20-40% of bio-oil is a non-evaporative fraction [22]. This fraction has to either burn

heterogeneously in the last combustion stage or pyrolyse/crack and form lighter materials that

can evaporate and burn as vaporized fuel in the early stages. Ultimately, ash should be the only

remaining material if the combustion is complete.

Figure 2.5. From left to right, stages of bio-oil droplet combustion [16]

Figure 2.6. The last stage of droplet combustion; burning of a cenospheric residue [16]

The combustion stages of bio-oil can also be studied by TGA [22]. Despite the fact that

the heating rates and time scales in this type of analysis are significantly different from the

droplet combustion studies, the general features are described correctly by both methods (see

section 2.3.4). One important feature implied from TGA is the high temperature and time

requirement of carbonaceous residue burnout [22]. This would foretell the existence of some

problems implementing bio-oil in combustion devices designed for fully evaporative fuels such

as diesel and jet fuel with relatively short burning times. The long residence time issue is also

16

reported in the metalized slurry fuels literature along with elevated particulate matter emissions

[25, 29].

Because of the solid suspended particles, bio-oil shares some features with slurry fuels.

Slurry fuels are a mixture of fine solid particles mixed in a liquid fuel or water [27]. Examples

are aluminum-jet fuel slurry and coal-water slurry. Additives including surfactants and gallants

are also sometimes added to the mixture in order to improve the dispersion of the suspended

phase or in the case of gel-propellants to change the physical, safety and rheological properties

[28].

2.5 Heat and Power Generation from Bio-oil

Burning bio-oil instead of fossil fuels can help decrease the greenhouse gas effect. So far, bio-

oil has mostly been considered as a fossil fuel replacement in stationary heat or power

generating systems. Detailed reviews of bio-oil applications were published by Chiaramonti et

al [29] and Czernik et al [30]. Stationary gas turbines, diesel engines, Stirling engines and steam

power plants are the candidates for electricity production or combined heat and power cycles

while boilers of different size have the potential for utilizing bio-oil to generate heat.

2.5.1 Heat Generation in Boilers and Furnaces

Furnaces and boilers are the most flexible combustion systems in terms of fuel quality since the

residence times are usually longer than diesel engines or gas turbines and particulate matter

emissions are better handled in these systems. As a result, there is a lot of interest in replacing

heavy fuel-oils with bio-oil in stationary heating application. For instance, bio-oil has been

commercially in use in Red Arrow Products pyrolysis plant in Wisconsin for more than 15 years

to generate heat. The mentioned plant uses a 5 MW swirl burner and emissions are all well

below the permitted value [30]. However, when considering intermediate size boilers1, a report

of a 200kW burner suggests existence of some issues including sensitivity of combustion

behavior and emissions to water, solids and viscosity of bio-oil [31]. Among the measured

emissions, compared to light fuel oils, the main problem is the excess amounts of particulate

1 As a rough classification, boilers smaller than 15-20 kW are small scale, heavy fuel oil boilers are in the order of

1MW and intermediate boilers are between these two extremes [31].

17

matter emissions which are believed to be unburned or partially burned tar-like material [31].

The same report suggests decreasing the solids content of bio-oil and improved atomization

quality to address the particulate matter issue. In addition, refractory lining of the combustion

chamber and preheating of bio-oil to decrease the viscosity are used as measures to enhance the

combustion stability and decrease the emissions. Another report shows steady state combustion

efficiency of bio-oil in a 100kW spray burner is very close to unity (0.35 ppm CO) ; although

under transient operation and non-optimal fuel to air ratios, carbon monoxide emissions as high

as 1000PPM are observed [21].

Small scale burners have been studied separately by Tzanetakis and Krumdieck et al. [4],

[5]. Both studies have identified that most of the problems observed in intermediate size burners

also exist in small ones. High carbon monoxide and unburned hydrocarbon emissions are

additional problems. The addition of ethanol to improve the flame stability is practiced in both

studies. Particulate matter emissions of bio-oil are characterized by Tzanetakis et al. and it is

shown that in addition to ash, partially burned carbonaceous residue is a significant fraction of

the particulate matter emissions [7]. In general, the main design features of a combustor

including aerodynamic design, atomizing spray, ignition source, combustion air preheat and fuel

to air ratio have been shown to affect the combustion performance and emissions of bio-oil

much more than number 2 fuel oil [4]. Comparing the literature of different bio-oil burner sizes,

the scale of the combustor is an important parameter and utilizing bio-oil in smaller scale

burners seems to require either combustor modification or fuel optimization. For instance, even

with the additional 20% volumetric ethanol, the combustion efficiency of the small scale burner

(10 kW) studied by Tzanetakis et al. in reference [6] is lower than the intermediate scale burner

(200 kW) studied by Gust et al in reference [31]. However, the former combustor lacked

refractory lining and the burner was not optimized. The main issue causing this deterioration of

combustion performance and emissions with decreasing the burner size seems to be the shorter

residence times associated with the small burners [4].

Co-firing bio-oil with a fossil fuel such as natural gas or coal is another option.

Successful bio-oil co-firing with coal is reported in a large scale, one month period trial [30].

Co-firing in the current coal or natural gas fired power stations is relatively easy and does not

need huge modifications to the combustion systems since these power plant are usually

18

equipped with oil burners as a backup [32]. Bio-oil oil combustion in a utility boiler for a

combined cycle power plant was tried in 2002 and similar to coal, results were satisfactory for

the costumer [32].

2.5.2 Gas Turbines and Diesel Engines

Boilers of various types are the most studied devices for heat and power generation from bio-oil

since they are able to handle low quality fuels like bio-oil. However, diesel engines and gas

turbines offer higher thermal efficiencies if used in combined heat and power applications [30].

There are a few studies about using bio-oil in a diesel engine and most of the literature suggests

difficult ignition, fuel corrosiveness, and high emissions are the common problems observed

when running bio-oil in diesel engines [12, 32, 35].

Gas turbines are usually designed for light distillable fuels like kerosene and diesel [33],

so combustion system modification or fuel quality improvements are required if bio-oil is

considered for a gas turbine. An early study by Moses on the combustion performance and

durability of gas turbine using bio-oil emphasized the impact of fuel properties on these

parameters: ignition, lean stability or turn down ratio, combustion efficiency, liner temperature,

particulate matter and gas phase emissions, turbine and combustion chamber corrosion and

erosion, thermal stability and material compatibility [33]. To evaluate the burning time of bio-

oil, Moses approximates bio-oil with bunker fuel because of the slow evaporation rate. It is then

showed that a bio-oil droplet has to be 3-6 times smaller than a kerosene fuel droplet to

completely burn in a typical stationary gas turbine with a droplet residence time of 10

milliseconds in the combustor. Poor atomization can reduce the combustion efficiency and this

inefficiency can be seen in the reports of the other gas turbine experiences with bio-oil [34],

[35]. One important problem existing in most of the gas turbine experiments, which seems to be

partly caused by the short residence times, is the particulate matter emissions consisting of

unburned or partially burned fuel combined with ash. These particles can be carried out of the

combustor by the exhaust or they sometimes form a slag or large amounts of deposits on the

exhaust passages [32, 37]. In addition to environmental issues and turbine blade erosion,

particulate matter emissions can increase the flame radiation and decrease the combustion liner

life [33]. While carbon monoxide is also reported to be higher in bio-oil compared to diesel

fuel, NOx is usually less or within the limits of petroleum fuels [30]. The most recent reported

19

tests on gas turbines are by Orenda Aerospace Corporation, Canada, using a modified 2.5 MW

gas turbine designed to handle heavy fuel oils [32, 35]. The reports show that carbon monoxide

and NOx emissions are below the Ontario emissions requirement although both CO and

particulate matter emissions of bio-oil are higher than diesel.

Considering the literature of bio-oil utilization, one can conclude that the differences in

the combustion performance and emissions of bio-oil and light petroleum fuels is amplified

whenever combustion residence times are not long enough to fully burn the droplets, which

results in incomplete combustion products including particulate matter emissions and carbon

monoxide. Examples are gas turbines designed to burn light fuels, diesel engines and small scale

boilers. There are two ways of addressing this issue, one is combustion system modifications

and the other is bio-oil optimization. The latter is the focus of this study.

20

Chapter 3

Experimental Methodology 3

Experimental Methodology

3.1 Bio-oil Burner

A 10 kW spray burner, designed by Tzanetakis [4], has been used in this study and is depicted in

Figure 3.1. This burner uses a water cooled twin fluid atomizer and compressed air as the

atomizing fluid to enhance the spray quality of relatively viscous bio-oil. Primary combustion

air is introduced from the top section and first passes through a 1.5 kW electric heater which

increases the air temperature to approximately 300°C. Then the air enters the moving block

swirl generator which is installed on top of the combustion chamber. A methane-oxygen torch

positioned below the nozzle is used to stabilize the combustion. Flames are normally stabilized

in the partially premixed region right after the nozzle exit. The combustion chamber diameter is

221 mm. Various diagnostic instruments are installed in the exhaust line, which are all described

in this chapter.

21

Figure 3.1. The Bio-oil Burner

As can be seen in Figure 3.2, a bio-oil blend or ethanol is pumped to the nozzle by

means of two parallel peristaltic pumps. Regulated compressed air is used for the air blast

atomizer and primary combustion air is sucked into the burner. Primary air flow to the

combustion chamber is controlled by a stack fan at the end of the exhaust line in such a way that

the chamber and the main exhaust line are under slight vacuum (chamber pressure is measured

by a manometer and is usually negative 224 Pa). The Stack fan speed is manually controlled by

a variac. After gas and particulate matter sampling junctions, the main exhaust passes through a

water cooled spiral heat exchanger. Most of the particulate matter and the condensed water

vapor in the exhaust are collected in the water traps positioned below the heat exchanger.

Cooled exhaust gas at room temperature enters the stack fan and is then vented to the roof stack.

22

Figure 3.2. Schematic of the experimental setup [4]

3.1.1 Swirl Combustor

The purpose of the swirl generator is to add tangential velocity and as a result angular

momentum to the main combustion air. A moving block, radial swirl generator was used in this

study. This configuration delivers different air angular momentums by dividing the incoming air

into radial and tangential streams. By changing the ratio of tangential and radial components of

the air stream, different flow patterns can be created in the combustor. Details of this type of

swirl generator are further described in the previous works [4, 6]. To simplify the categorization

of swirling flows, a dimensionless number named swirl number ( ) is cited in the literature for

axisymmetric conditions which represents the ratio of axial flux of angular momentum ( ) to

the axial flux of axial momentum ( ) in a flow cross section [36]:

23

∫

(3.1)

∫

∫

(3.2)

(3.3)

Here, is the section radius, and are the local axial and tangential components of the air

velocity, is the density and is the local static pressure deviation from a reference

pressure. The swirl number is constant along free, frictionless jets as defined above. The

pressure term in the axial flux of momentum definition is to account for the pressure changes as

a result of flow passage area changes.

The swirl generator used in this study was capable of giving a swirl number from 0 to

5.41 [6]. In addition to enhancing mixing between the fuel and air streams, swirling the air has

some other advantages for the combustion. In a non-reactive jet, a swirl number of typically

more than 0.6 results in a radial pressure gradient close to the nozzle exit which drags the

surrounding air into a hypothetical bubble of low velocity fluid [37](streamlines are depicted in

Figure 3.3). This bubble of low velocity gas is called the recirculation zone. In a reactive

combusting jet, recirculation zone contains mostly product gases and is approximately uniform

in composition and temperature [36] . The existence of such high temperature zone close to the

nozzle enhances the combustion stability since it acts as a source of active chemical species and

heat required for igniting the incoming fuel and oxidizer.

24

Figure 3.3. Calculated streamlines in a free annular jet with a swirl number of 1.57 [37]

Studies done on a confined geometry swirl combustor show that depending on the swirl

number, various regimes of flames could be stabilized [38]. These flame categories are depicted

in Figure 3.4. Visual observations of bio-oil flames in this study show that all the flames are in

the high swirl nozzle stabilized regime (the pilot flame also plays an important role in stabilizing

flame close to the nozzle as described in section 3.1.3). Each type of flame corresponds to a

degree of mixing and the recirculation zone is not necessarily established close to the nozzle in

all cases. One has to consider that the swirl number is not the only important dimensionless

number when analyzing a combustor and other geometrical features (design of the diffuser for

instance) also play a key role in the fluid dynamics of the burner. Some swirl numbers may even

correspond to two or three steady state flames [38]. The dynamics of swirl flames is still an

active subject of research and further insight into the current setup requires some information

about the velocity or temperature fields and is not investigated here.

25

Figure 3.4. Drawings of different flame regimes in a swirl combustor; Coanda stabilized

flame (CSF), Nozzle stabilized flame (NSF), swirl stabilized Flame (SSF), pinched jet flame

(PJF), back-wall stabilized flame (BSF) [38]

3.1.2 Fuel Nozzle

An internal mix, air-blast nozzle from BEX Engineering Ltd. (model 1/4”JX6BPL11 with a 152

mm long extension tube and 2X2JPL back-connect body) is used in this study which is depicted

in Figure 3.5. This nozzle is installed in the centerline of the burner and the tip is 15.9 mm

above the pilot torch. Fuel and air mix in the small chamber inside the air cap of the nozzle and

then the mixture exits through six orifices arranged symmetrically at the tip. This nozzle is

constructed from 316 stainless steel and inspections after all the bio-oil tests showed no sign of

corrosion or erosion (Figure 3.6).

26

Figure 3.5. Schematic of the air blast atomizer [4]

Figure 3.6. The fuel nozzle after at least 50 hours of bio-oil operation

One problem identified during the previous experiments on this setup was the fuel

boiling inside the nozzle before injection [4]. This phenomena is known as flash atomization

and if it takes place in a controlled fashion can significantly decrease the droplet size and widen

the spray angle which is beneficial for combustion [39]. As the mass flow rate of fuel is fixed

during a test, and also noting that the density of the vapor is usually hundreds of times lower

than the liquid, one can conclude that vapor discharge through the nozzle happens at a velocity

much higher than normal liquid. In other words, bubbles formed in the fuel act as an atomizing

27

gas during the discharge process and shatter the liquid ligaments which in turn decrease the

droplet size [40]. The problem arises when flash atomization is intermittent and not controlled

which results in combustion instabilities and even blow-out in some cases. Controlling the flash

atomization which means controlling the void fraction of the fuel requires accurate temperature,

pressure and flow rate control and also good knowledge of the fuels’ thermo-physical properties.

Therefore, in this study, a water cooling system was added to the nozzle to completely prevent

the flashing, which is depicted in Figure 3.7. This system consists of a 1/16” stainless steel tube

wrapped around the fuel tube. This coil occupies a fraction of the annulus which is the

atomizing air passage, but pressure drop tests showed no detectable flow obstruction. This

design does not change any geometrical features of the outside flow since both the inlet and

outlet of the cooling line are contained inside the nozzle body. Building water runs through this

line at 50 (ml/min) and its temperature increases by around 25°C as it cools down the nozzle.

An automatic control system connected to a solenoid valve is used to activate or de-activate the

cooling. During the early tests, a 50% duty cycle was chosen to keep the temperature between

50-60°C. The water cooling was active for 10 seconds and then was off for 10 seconds. Based

on the results of the first test round, the decision was made to keep the line always active since

the temperature control goal was achieved even with the system continuously operating.

28

Figure 3.7. Nozzle cooling system schematic

To estimate the Sauter mean diameters (SMDs) of different test conditions a correlation

is used in this study. Bio-oil is a shear thinning liquid similar to coal water slurry fuels [41].

Literature of air-blast atomization suggests that the effect of liquid rheology of a Newtonian

liquid on SMD can be predicted by three dimensionless groups: Weber number, the air to liquid

ratio in the nozzle and the Ohnesorge number. Studies by Tsai et al [42] on micronized coal-

water slurries with particle sizes close to bio-oil and solids volume fractions even higher than

bio-oil show that SMDs of air blast atomization of such slurry can still be calculated knowing

the same three dimensionless groups. Thus, a non-dimensional relation for air assist atomization

of Newtonian liquids was selected for bio-oil blend spray evaluation [40]:

(

)

( ⁄ )

(

)

( ⁄ ) (3.4)

Here, σ is surface tension, ρA and ρL are air and liquid densities, UR is the relative velocity of the

liquid and air, and d0 is the orifice diameter. One can easily identify the three main

dimensionless numbers dominating the SMD: inverse of the Weber number(

), air to

Sink

Water Tap

Solenoid Valve

Water Filter

Thermocouple

Solid State Relay

Computer

Data Acquisition Card

5 VDC

120 VAC

29

liquid mass flow rate ratio (ALR), and Ohnesorge number(

). The density and velocity of

air are estimated by assuming isentropic ideal gas flow through the nozzle orifice. The liquid

density is assumed to be the same as room temperature (incompressible flow) and ALR is

known from the measured air and liquid flow rates. Liquid viscosity is measured using an

ASTM standard test (Table 3.1) at the nozzle temperature, which is usually around 80˚C. For

bio-oil blends, the surface tension of a wood derived bio-oil at 80˚C is 30mN/m which is taken

from the literature [41]. For heavy fuel oil, 20mN/m was used which is also from literature [40].

3.1.3 The Pilot flame

A premixed, stoichiometric, oxygen-methane torch is inserted vertical to the burner axis right

before the diffuser section [4]. The pilot flame stands under the nozzle tip and helps stabilize the

main flame. Pilot is always on during the whole tests and provides 0.5 kW of energy into the

combustor. This energy is 5% of the total 10 kW energy input from the bio-oil blend and

corresponds to 0.9 SLPM of methane and 1.8 SLPM of oxygen.

As explained by Tzanetakis, after assembling the burner system, one ethanol combustion

test is used to find the correct alignment of the nozzle relative to the combustor and the pilot [4].

The pilot flame is fixed to the combustor, but the nozzle can be rotated around the burner center

line. The purpose of the alignment test is to make sure that all fuel jets are ignited evenly and the

pilot is not impinging on any of the jets which can cause flame instabilities as shown in Figure

3.8. Once the correct angle is found the nozzle is fixed to the burner by means of four set-screws

and won’t be touched till the next nozzle overhaul.

30

Figure 3.8. Good and poor alignments of the fuel nozzle [4]

3.2 Measurement and Analysis Tools

The main purpose of this study is to experimentally relate the basic fuel properties of bio-oil to

the combustion performance and emissions. Therefore, two broadly different groups of

experiments were done which are fuel and combustion measurements.

3.2.1 Fuel Analysis

3.2.1.1 Basic Fuel Properties

The water, solids and ash content of bio-oil, which are described in sections 2.3.1, 2.3.2, and

2.3.3 respectively, are measured according to the standard methods recommended in the

literature. The Carbon, Hydrogen, Nitrogen (CHN) content of fuel, Higher Heating Value

(HHV) and kinematic viscosity are the other important fuel properties. Oxygen content of bio-

oil is usually reported by assuming bio-oil only consists of carbon, hydrogen, nitrogen and

oxygen and using the CHN analysis results. Table 3.1 summarizes the test methods used for

measuring these basic properties. The listed properties are either provided by the manufacturer

or outsourced for measurement.

31

Table 3.1. List of basic fuel properties measurement standards

Property Common Unit Test Method

Water Content wt % ASTM E203

Solids Content wt % MeOH-DCM insolubles

Ash Content wt % ASTM 482

CHN content wt % ASTM 5291

HHV MJ/kg ASTM 4809

Kinematic Viscosity at the Injection Temperature

cSt ASTM 445

3.2.1.2 Thermogravimetric Analysis (TGA)

As described in section 2.3.4, TGA is used to find distillation curve of bio-oil. A “TA

instrument” model Q50 analyzer is used in this study. The analysis starts with shaking and

homogenizing the fuel in the bottle and picking a representative sample of it. The sample of

around 15 mg will be put in an aluminum crucible and then the crucible is placed in the sample

holder of the thermogravimetric analyzer. From this moment the sample is exposed to 100

ml/min of nitrogen flow under atmospheric pressure throughout the test. During the first 5

minutes, the sample is kept at room temperature to make sure all the lines and the test oven are

free of oxygen. After this purging, the main test stage begins which is heating the fuel to 600˚C

by a heating rate of 10˚C/min. The non-evaporative mass remaining after heating the fuel to

600˚C is a representation of the char forming potential of the fuel and is reported as “TGA

residue” in this study [26].

3.2.1.3 Photo microscopy

When comparing bio-oils with different solids content, some information about the size

distribution of suspended particles is important. The characteristic size of the particles can also

be indicative of the potential of the fuel to block the narrow passages of the nozzle. A

microscope with 50x optical zoom was used to get visible light photos of several bio-oil batches.

The method for sample preparation is similar to what described in the previous works [4].

Several photos were taken from each sample and it was made sure that the photos reported in

this work are representative of the whole bottle being considered.

32

3.2.2 Gas phase species measurement systems

Gas phase pollutants measured are total Unburned Hydrocarbons (UHC), nitrogen oxides (NOx)

and carbon monoxide (CO). For measuring these pollutants as well as oxygen (O2) percent in

the exhaust, a system consisting a FID unit, one FTIR unit and an oxygen sensor were used

which has been described in more detail in the previous works [4, 46]. The overall system is

depicted in Figure 3.9. A combination of manually set and feedback controlled heating tapes are

used in all the sampling lines leading to the measurement sensors in order to prevent any vapor

from condensation. Gas temperature inside the heated lines is maintained between 190 ˚C to

195˚C. Each subsystem is briefly described in this section.

Figure 3.9. Schematic of the gas phase emissions measurement system [4]

3.2.2.1 Oxygen Sensor

The oxygen percent in the exhaust is continuously monitored during the test by a Zirconia

(ZrO2) model OXY6200 oxygen sensor from Engine Control and Monitoring. This sensor can

measure the oxygen percent from 0 to 21% with an accuracy of ±0.1 O2 %. As depicted in

Figure 3.9, the O2 sensor is using a separate line from the other measurement instruments since

the sensing element is kept at a high temperature that can oxidize unburned species including

33

CO and UHC. The flow rate is 1.8 SLPM and the sensor is always under vacuum since a

vacuum pump is used to draw the required flow rate from the exhaust.

The conditioned output voltage is 0-5 volts DC (VDC) analog and is logged by a data

acquisition system connected to a computer. The calibration of this sensor requires only one

point (room air 21% O2) and the output voltage has a linear relation with the oxygen

concentration. Total combustion air and the equivalence ratio are calculated based on the fuel

composition, oxygen concentration in the exhaust, fuel flow rate and assuming complete

combustion. Even in the cases where the carbon monoxide is high, the combustion efficiency is

high and the complete combustion assumption produces a negligible amount of error in the

equivalence ratio calculations.

3.2.2.2 Flame Ionization Detector (FID)

This device is used for measuring the concentration of unburned hydrocarbons (UHC) in the

exhaust. The FID works by passing exhaust gas through a small hydrogen/air flame where it

burns and subsequently produces an ionized current proportional to the number of carbon atoms

in the sample [43]. The input gas is kept at 188-195°C to keep the hydrocarbons from

condensing and the flow rate is automatically kept at 1.5 SLPM by an internal pump. The output

signal is a voltage linearly proportional to the concentration of the UHC which is logged by a

computer connected to a data acquisition card. Calibration is done before each test by feeding

two different standard gases, one is purified air (zero PPM UHC) and the other one is 104 PPM

methane in air. The measurement range is 0-300PPM methane in this study and the uncertainty

is ±3PPM. The FID has a 0-5 VDC analog output (linearly proportional to the measured PPM

methane) which is used for recording the real time UHC concentration.

3.2.2.3 Fourier Transform Infrared Spectroscopy (FTIR)

A Nicolet 380 Fourier transform infrared spectrometer (FTIR) is used to measure CO, NOx,

methane (CH4), formaldehyde (CH2O) and acetaldehyde (C2H4O) emissions. This analyzer

works by comparing the absorption spectrum of a gas sample in the mid infrared region (500 to

4000 cm-1

) against known standards. The gas cell volume is 0.19 L and the sample gas is

continuously drawn through the cell by means of a vacuum pump as depicted in Figure 3.9. A

three way valve is used to switch the gas sampling between the FTIR and the FID. The sampling

34

flow is 10.3 SLPM during the test. The gas cell temperature is kept between 115°C and 120°C at

a pressure of 86.3 kPa. Usually 5 spectrums are collected in each test. Each spectrum is the

average of 24 scans of the instrument from the gas cell over one minute. Considering the gas

cell volume and sampling flow rate, the cell is refilled 50 times during each spectrum collection

which must give a good average of the gas composition. The wave number resolution of the

FTIR is 1 cm-1

.

A partial least squares model is used to calibrate the instrument. A detailed treatment of

the FTIR calibration methodology, including a description of the experimental setup and

spectral ranges is provided elsewhere [44]. The root mean squared error (RMSE) is used to

provide an estimate of the accuracy of the model which represents the deviation between the

calibration model prediction and the actual concentration in a standard gas sample mixture.

Details of the detection limits and calibration model accuracies are summarized in Table 3.2.

Three different models are used in this work, each suitable for a certain range of carbon

monoxide concentrations. Once a spectrum is collected, it is compared with the standard gas

spectra and based on the carbon monoxide concentration estimation one of the three spectrum

quantifying models is applied. The reason is that the CO absorption versus concentration curve

is significantly nonlinear. The two models used for medium and low concentrations of CO are

the same as the ones used in the previous works [4, 46] and the high CO quantification method

was added in order to handle a few of the tests. An error bar in any of the gas phase emission

graphs corresponds to one standard deviation of the several spectrums collected under the same

condition, since instrumental error is often much smaller than the process variations.

Table 3.2. Detection limits and uncertainty levels of the FTIR models

Species Detection Limits(PPM) RMSE(PPM)

CO(low) 10-600 15.6

CO(medium) 600-1500 25.5

CO(high) 1500-2800 31.4

NOx 10-300 6.3

CH4 10-250 3.1

CH2O 10-150 1.7

C2H4O 30-150 5.2

35

3.2.3 Particulate Matter Measurement System

As explained in literature, measuring PM (or any other pollutant) from a source has two stages;

the first is obtaining a representative sample and the second is finding the concentration of the

PM in the sample with the first step being usually more difficult [45]. Isokinetic sampling is the

method for taking the suitable sample from the exhaust and gravimetric analysis is used for

measuring the concentration of the PM in the sampled gas.

3.2.3.1 Isokinetic Particulate Matter Sampling

Sampling of a dusty gas in a duct is usually done by inserting a small diameter probe in the duct

facing upstream and collecting the sample with minimum disturbance of the flow. Isokinetic

sampling is the method used for keeping the aerodynamic effect of probe insertion to a

minimum. Fundamentally, two conditions must be satisfied for sampling to be called isokinetic:

(1) the suction velocity of the sampling nozzle should be equal to the free gas velocity in the

duct; and (2) the nozzle should be aligned parallel to the flow stream [49, 50]. The second

condition sounds obvious; the first condition is for making sure the sampled gas has the same

particle size distribution as the main stream and is usually satisfied by controlling the sampling

flow rate with a needle valve. Fine particles follow the gas stream lines very closely, but as

particle size is increased, inertial effects will have a more dominant effect on the PM dynamics

and the deviation of PM trajectories from the gas streamlines becomes more significant. As

depicted in Figure 3.10, if the sampling velocity is less than the mainstream, streamlines are

deflected outwards near the nozzle. Since heavier particles may not follow the streamlines and

enter the nozzle, this condition leads to the shift of the particle size distribution of the sampled

gas towards the bigger particles relative to the particle size distribution of the main stream (sub-

isokinetic condition). A reverse situation exists when sampling velocity is higher than the

mainstream velocity (super-isokinetic condition) [49, 51].

36

Figure 3.10. Gas stream lines around the probe when sampling velocity is lower than the

main stream velocity [46]

There are two ways of finding the sampling flow rate corresponding to the isokinetic

condition. One method is measuring the gas velocity by a pitot tube as recommended in the EPA

methods, and the other way is matching the velocities by matching the static pressures of the

main stream and sampling stream which is called “null method” [52, 53]. Due to the dusty

nature of the exhaust gas, a pitot tube was not used which would have resulted in frequent

blocking of the tube passages (one hole of the pitot tube measures the total pressure of the gas

which faces directly upstream). Instead a null type was designed which uses two static pressure

measurement holes parallel to the streamlines. When analyzing the null type probe, we can treat

the gas as incompressible and frictionless (Mach number <<0.3). By using Bernoulli’s equation

along a streamline entering the sampling probe from the main stream, one can easily show that

if the static pressure inside the sampling tube is the same as the duct, velocities of these two

streams should equalize.

Using a null type isokinetic sampler has some error due to the friction of the gas and

aerodynamic effects that can vary the pressure field from what is obtained from one dimensional

and ideal flow assumptions made in the previous paragraph [47]. As a result, location of the

static pressure taps should be chosen with care and the sampling flow rate corresponding to the

37

isokinetic condition found from the “null” method should be verified against a pitot tube or

theoretical prediction. Appendix A shows the agreement between the theory and experiment for

this device.

Figure 3.11 shows the schematic of the PM sampling line. The gas inside the combustion

chamber is highly swirling, so PM size distribution is not uniform. Good sampling is done from

a homogenized dusty gas and the first step towards homogenizing the PM concentration is

eliminating the swirl. To this end, a metal mesh consisting of 0.25mm thick stainless steel sheets

arranged into a checkerboard pattern is added at the exit of the combustion chamber which acts

as a flow straightener (appendix B). Principally, isokinetic sampling probe takes advantage of

the pressure difference between fully stagnated and free stream flow, so a detectable dynamic

pressure is required inside the main exhaust pipe. That justifies the pipe size reduction from the

102mm i.d. elbow to the 38mm i.d. elbow in Figure 3.11. Reducing the pipe size increases the

gas velocity (gas velocity in the pipe is around 8m/s during a bio-oil test) which elevates the

dynamic pressure to typically 21 Pa that is easily detectable on a manometer with an uncertainty

of 1.2 Pa. During sampling, the manometer is used to keep the pressure difference between the

two streams always zero by changing the sampling flow rate. As emphasized in the literature,

one important parameter in choosing the sampling position in a pipe is the unobstructed length

of the pipe before and after the sampling port [48]. A straight pipe section with a minimum

length of 8 pipe diameters before and 3 pipe diameters after the port is recommended in order to

make sure the PM size distribution is uniform. Therefore, considering the confined lab space, a

length of 10.4 pipe diameters (394mm) was left straight before the sampling probe and 1.7 pipe

diameters (64mm) was left after the sampling probe in order to prevent any aerodynamic

interference of the downstream or upstream obstruction on the flow pattern around the sampling

port.

38

Figure 3.11. PM sampling system piping diagram

Figure 3.12 shows the position of the sampling probe and the static pressure

measurement points. The diameter of the probe was chosen based on the ranges recommended

in the EPA methods [49]. Some additional design constraints were the maximum flow rate of

the probe that the vacuum pump could sustain during a reasonable sampling time, the maximum

allowed filter flow rate and also a reasonable amount of PM mass on the filter given the limited

sampling time. The static pressures of the sampled and main gas streams were measure by a

small diameter tube inserted in the sampling tube, and a tube mounted perpendicular to the

exhaust stream, respectively (Figure 3.12).

The sampled gas has a temperature of around 250˚C, and if fed directly into the filter

holders it can damage some gaskets. A controlled filter temperature of 120-130˚C is desired

according to the EPA codes [49], as a result a cooling jacket is installed around the sampling

tube which uses room temperature compressed air run through a pipe around the tube (Figure

39

3.11). In addition to the main sampling line and filter, an auxiliary line and filter is installed with

ball valves required to switch the gas between them. This auxiliary line is used during a filter

change in the main line; the purpose is to keep the sampled gas flow at a steady rate. This

switching prevents any changes in the combustion chamber pressure and also keeps the

sampling line passages warm.

Figure 3.12. Isokinetic probe dimensions and the pressure taps [7]

Tissuquartz filters (Product No. 7202) provided by Pall Life Sciences with a diameter of

47mm were used in all the official tests. This type of filter is made up of pure quartz fibers

without any binder and as a result can withstand temperatures as high as 1100˚C without

decomposing. Typical aerosol retention efficiency is 99.90% for particles of 0.3 μm diameter

(following ASTM D 2986-95A at 32 L/min/100 cm2 filter media) [50]. Both the main and

auxiliary lines use an Advantec MFS Inc. stainless steel filter holder (Model LS47, Part

No.304700). As depicted in Figure 3.11, a J-type thermocouple is inserted just downstream the

filter to measure the temperature. To have accurate timing, a ball valve is used before filter to

abruptly start/stop the gas flow. The inside diameter of sampling line and all the associated

fittings including the ball valve before the filter were chosen in such a way that they minimize

the obstruction in the exhaust path and PM loss.

A shell and tube heat exchanger (Seakamp Engineering Inc. Part No. 2151414) was used

to condense the water vapor and prevent liquid from accumulating inside the vacuum pump,

40

needle valve and the gas rotameter (Figure 3.11).The shell is used for the exhaust gas and water

is run in tubes to cool down the gas. Cooling water flow rate is about 0.25 gallons per minute

and the water temperature increase is calculated to be about 2˚C in all the tests. In order to

measure the PM concentration, the total flow rate through the sampling line, or the “wet” gas

flow rate, should be quantified. The gas rotameter is calibrated at the test pressure using a

standard flow meter. However, this rotameter measures the “dry” exhaust flow rate, and it could

not be used before the heat exchanger to directly measure the wet gas flow rate because of the

condensation problem. However, the ratio of wet and dry flow rates can be obtained by

combining the data collected from the gas rotameter, thermocouple and the pressure gauge. By

assuming the gas coming out of the condenser is at equilibrium and saturated with water vapor,

and also performing a mass balance over the condenser, a relation between the standard

volumetric wet ( ) and standard volumetric dry ( ) gas flow rates can be found:

⁄

(3.5)

Here, is the saturation pressure at the temperature of the gas exiting the condenser ( is

found from standard steam tables given ), is the absolute pressure as measured by the

gauge in condenser exit, and is the molar fraction of water in the wet exhaust based

on mixture stoichiometry (calculated from the oxygen sensor). The volumetric water vapor

fractions in the wet and dry gases are about 13% and 2% respectively.

3.2.3.2 Gravimetric Analysis and Loss on Ignition Test

For most bio-oil tests, two successive filters are collected at any operating point. Each filter is

normally exposed to the exhaust for 5 minutes. If the deposition is estimated to be too small for

it to be detectable, 10 minutes is used instead. On the other extreme, if the PM loading is too

high and causes excessive pressure drop over the filter, 3 minutes is used. A bio-oil test was

done to confirm that the caking of the PM over the filter does not affect the PM collection

efficiency and the emission index found from the two filters with two different exposure times

are the same.

One target of this study is to isolate the effect of ash over the PM and quantify the

amount of unburned or partially burned carbonaceous residue (CR) of the PM. To this end, a

41

standard method called loss on ignition (ASTM code number D4422 –03) test was followed for

each of the filters [51]. In this test, the PM collected from the exhaust is first dried and then

burned in a muffle furnace, in a crucible at about 750˚C and what is left from the PM is

considered to be ash. The assumption here is that PM consists of ash, CR and water and by

measuring the sample weight between the stages of the test and calculating the differences; one

can quantify the amount of each fraction. The only modification made to the standard test

procedure is the addition of the Tissuquartz filters in the analysis. As mentioned in section

3.2.3.1, these filters can tolerate temperatures of up to 1100˚C without decomposition and the

fiber material is inert.

Figure 3.13 depicts the procedure followed for each filter which essentially consists of

four main stages and one mass measurement after each step. A filter is first placed in the oven

at 750˚C for two hours to burn off any possible contamination and also dry the filter. Then the

filter is used during the test for PM sample collection. Mass difference of the filter before and

after a test is the total PM deposition. Due to high vapor content of the exhaust and porosity of

the filter, some water is absorbed by the filter during the test which is evaporated in the draying

stage. The last step is burning of the CR fraction of the PM which is done very similar to the

first step. Each mass measurement is done three consecutive times, the numbers are recorded

and their average is used for analysis. Temperatures of heating steps are chosen based on what is

recommended in the literature [51]. Duration of each heating step was chosen by doing the

procedure for a few representative filters; heating was continued till the mass difference

between two consecutive measurements was outside of the microbalance precision level. Table

3.3 shows how the masses of water, ash and CR are calculated based on the nomenclature of

Figure 3.13.

42

Figure 3.13. The loss on ignition and gravimetric analysis procedure

Table 3.3. Calculation methods of different PM fractions

Total PM(mg) M2 - M1

Water(mg) M2 – M3

CR(mg) M3 – M4

Ash(mg) Total-Water-CR

Using Table 3.3, emission indexes for the CR and ash are:

(

⁄

)

(3.6)

(

⁄

)

(3.7)

Where is the mass flow rate of fuel, is the sampling time, and ( ⁄ ) is the ratio

of the sampling flow rate to the total exhaust flow rate. For calculating the emission indexes,

43

is obtained from multiplying the density by the measured volumetric flow rate of fuel,

is calculated from equation (3.5) and is found using the equivalence ratio indicated

by the oxygen sensor.

3.2.3.3 Uncertainty Level of Particulate Matter Measurement System

The total PM mass is usually about 10 mg. All masses are measured using a Scientech SM-

128D Microbalance, with a resolution of 0.01 mg and a repeatability of 0.13 mg. The oven used

here is a Thermo Scientific Thermolyne® model EW-33900-00 with ±2.0°C temperature control

accuracy. Filters are handled with extreme care and kept inside petri dishes. Filters are

maintained in a desiccator whenever a sample had to be kept at room temperature between the

stages. The measurement technique of the CR deposited on the filter using the oven was

validated against a bulk sample of particulate matter in a crucible (following the ASTM

standard) to guarantee the filter acts as an inert material during this test.

One way of finding the uncertainty level of the PM emissions results is to use a more

accurate method or replicate the tests. These methods are not considered here because of the

high fuel quantity requirement of such study. Instead, instrumental error is estimated based on

the error propagation of the various measurement steps. Most of the PM results are expressed in

terms of , since this dimensionless number can give the effect of combustion condition and

fuel over the PM without involving any dilution and ash effects. The uncertainties of all terms in

equation (3.6) are listed in Table 3.4. Since CR is the difference between M3 and M4 , and they

each have 0.13 mg uncertainty, the uncertainty of CR will be the square root of the sum of the

squares which is √ . The uncertainty in is coming from the error

associated with closing/opening the sampling line ball valve and is estimated based on the

operator’s reaction time. The error of fuel mass flow rate is estimated by repeated measurement

of a fixed flow rate. Uncertainty in the ( ⁄ ) term is calculated from equation (3.5)

which is done by combining the errors of the dry gas rotameter, oxygen sensor, condensation

outlet pressure and temperature as listed in Table 3.4.

44

Table 3.4. Uncertainties associated with EICR measurements

Parameter Uncertainty

CR 0.184 (mg)

1.6 % of the total

0.72 (sec)

Dry gas rotameter 1(SLPM)

2.2˚C

10 (kPa)

Oxygen sensor voltage 0.02 (volts)

Determining the total uncertainty of is done by differentiating equation (3.6) and by putting

the calculated coefficients in the following equation [52]:

[(

)

(

)

(

)

(

)

]

(3.7)

Where is uncertainty of CR as mentioned in Table 3.4. , , are defined

similarly, and “r” represents the ( ⁄ ) ratio.

3.2.4 Flame Photography

Flame detachment and combustion quality are judged based on the visual observations during

the test, combustion chamber pressure fluctuations and also by using a borescope. Figure 3.14

shows a schematic of the photography system. The probe is a rigid fiber-optic member with a

diameter of 9 mm and a tube length of 35 mm. This unit is coupled to a 10 mega pixel camera at

one end and a 90° mirror integrated to its body at the other end. When inserted into the burner,

this configuration gives an upward looking view of the flame along the central axis of the

burner. To protect the fiber optic tube as well as the mirror from the hot dusty gas of the burner,

a 19 mm tube is used as a sheath around the main tube, and room temperature compressed air is

used as the coolant. During a test, while ramping up the cooling compressed air, stack fan speed

is also increased in order to compensate for the extra gas introduced in the combustion chamber.

This process is done using the burner pressure as a feedback, which should be kept constant

while changing the compressed air flow rate and stack fan speed. Given the environment of the

combustion chamber, the fiber optic tube assembly should not be kept continuously inside. Thus

the camera and the tubes all slide together on a rail assembly which allows inserting the tubes,

45

taking videos and photos in a very short time (5-10 seconds), and taking the tubes out. Several

photographs are taken at a single operating condition while the aperture opening (f-stop), shutter

speed and ISO value (light sensitivity) of the camera are manually adjusted to achieve the best

picture quality possible. No post process image treatment (besides cropping and resizing) is

applied to any of the photographs.

Figure 3.14. Borescope schematic

3.3 Combustion Test Procedure

Fuel batches with different properties are tested on separate days all using the same procedure,

which is described here. Around three hours before a test, all the heated lines are warmed up, in

addition to the FID. The FTIR cell is heated to a steady state temperature and is put under

vacuum to prepare it for a clean background spectrum. The borescope assembly is put in

position and the alignment is checked to make sure the mirror is on the burner center line and

the sheath can easily slide in and out of its port on the burner body. Atomizing air is set to the

final flow rate and also the cooling water lines (main exhaust heat exchanger, PM condenser,

and nozzle cooling) are turned on at this time. Two hours before a test, the stack fan is turned on

and the swirl air flow rate is set to 240-250 SLPM while the air preheater is also put to 100%

46

power. One hour before a test, the FID is calibrated and the background spectrum for the FTIR

is collected. The oxygen sensor is turned on and its steady state voltage, while sampling room

air, is used for calculating mole fraction of oxygen during the test. The desired mixture of the

bio-oil and ethanol is prepared 1 hour before the test. The volumetric fuel flow rate for 10kW is

calculated and the peristaltic pumps are calibrated for it using a graduate cylinder and a stop

watch. Just before the test, the pilot flame is ignited and inserted into position. Labview begins

recording all the important temperatures, oxygen sensor and FID output voltage at the moment

the fuel spray ignites in the burner. The first 15 minutes of every bio-oil test is ethanol warm-up.

The swirl number is 50% of the full scale when running on ethanol to prevent the hot gasses

from excessively recirculating and warming-up the nozzle which could cause fuel boiling. At

this swirl number and depending on the initial conditions, aerodynamic instability is observed in

a few tests which if ignored can become self-sustaining and cause huge pressure fluctuations in

the combustion chamber. The dependency on the initial conditions suggests the existence of at

least two steady state solutions for this dynamic system, one being chaotic and the other one

stable. These instabilities are common in swirl combustors and are very difficult to predict

before the combustor is fired [53]. The advantage here is that this bifurcation is not observed in

100% swirl. One way around the problem is changing the swirl number to 100% and waiting a

few seconds till the fluctuations are dampened, then switching back the swirl to 50%. If done at

the correct moment, this act can bring the system into stable steady combustion, which

corresponds to the non-chaotic solution of the flow field. After the ethanol warm-up, the fuel is

switched to bio-oil by the two-way valve depicted in Figure 3.2 and swirl put to 100%.

Diagnostics are used in the same order and using the same timing in all the tests; first is the PM

sampling, then the FID and the FTIR and the borescope at the end.

Stable bio-oil combustion with the final fuel to air ratio is usually established at around

20 minutes, and at 25 minutes particle sampling procedure starts. At the beginning of the test

both sampling lines are closed and dummy filters are inside the filter holders. The main line’s

dummy is exposed to the exhaust for 3-5 minutes before significant pressure drop is observed

across the filter (due to PM caking over the filter). At that moment, the line is stopped and the

second dummy is put in. The official filters are used after the dummies. Dummy filters help the

sampling line temperature reach the desired 120-130˚C temperature. In addition, the sampling

line is cold at the beginning which causes water condensation in the line and also on the filter.

47

The auxiliary line uses only one dummy filter during a whole test and is only used while the

main line cannot be used because the filter is being changed. When running the exhaust through

the dummy filters, the operator has to find what flow rate makes the sampling line manometer

zero (corresponding to isokinetic condition), and keep that flow rate constant. This flow rate is

usually around 10.4% of the total exhaust flow as can be theoretically predicted (appendix A).

This condition should be satisfied while the oxygen sensor shows the correct fuel to air ratio.

Between one to three dummy filters are required to establish the isokinetic condition and also

the desired filter temperature. After that, official filters are exposed to the exhaust one after

another. Depending on the PM loading, one or two official filters are used. During the official

sampling, start/stop time, average dry gas temperature, sampling line rotameter value, average

oxygen concentration, and average condenser output pressure are all logged manually or

automatically by the data acquisition system and are later used in calculating the emission

indexes by equations (3.4-6).

After the PM sampling is finished, the primary air flow rate is adjusted quickly and

burner is left to stabilize again for 5 minutes. The UHC reported for each test is the average

during the time window between the time oxygen concentration is stabilized and FTIR sampling

starts (usually 5 minutes). The FTIR sampling begins at around 55 minutes and continuous till

60-65 minutes. Usually five spectrums are taken one after another. The FTIR cell pressure and

temperature are held constant between all the tests. The borescope is the last diagnostic

instrument used in a test. Before inserting the borescope tube, the combustion chamber pressure

is recorded. While the tube is just inserted enough to guide the cooling air into the chamber, the

stack fan and cooling air are both ramped up slowly in order to keep the burner pressure

constant. When the cooling air is at maximum, photos and videos are taken by fully inserting the

borescope tube. After all the data collection, the fuel is switched back to ethanol to clean the

nozzle and fuel lines. The air preheater is also turned off in order to prevent the fuel boiling

inside the nozzle. Ethanol runs for about 20 minutes before the shutdown.

After each test, the nozzle and combustion chamber are cleaned from any possible

deposits. Acetone is run through the nozzle to eliminate any interference between the separate

tests. In addition, the nozzle tip is cleaned mechanically from outside. Cleaning of the PM

system is done after each test by shooting compressed air backwards through the sampling lines.

48

Occasionally, an ethanol test is done between official tests where PM is measured to make sure

that fine deposits inside the burner do not contribute to the PM weight. Heavy fuel oil tests are

done in a very similar fashion to bio-oil, except that diesel is used instead of ethanol for warm-

up and shutdown.

49

Chapter 4

Results and Discussion 4

Results and Discussion

4.1 Experimental Test Plan

To study the effects of ash, solids, water and ethanol fractions of bio-oil mixtures and also to

compare bio-oil and heavy fuel oil, a total of 18 official tests were conducted in 8 month. All

bio-oils here are derived from fast pyrolysis process of wood using the same production plant. A

full factorial experiment design studying the effect of the four mentioned parameters in three

levels would require 81 tests [52]. Conducting that number of tests exceeds the time limit of this

project. Instead, a series of tests were done each studying the effect of one parameter while the

other parameters are held fixed as much as possible. The result of study of each parameter is

presented in a separate section; the fuel oil is also treated separately. A few extra tests were also

done in order to confirm the results of previous tests. To improve the combustion stability,

which is found to be a problem with small burners, most bio-oil batches were mixed with 15%

volumetric ethanol. The optimal burner parameters for bio-oil blend tests were found in the

previous study on the same burner [4]. This condition is called the “base” operating point or

condition one which is described in Table 4.1. Primary air flow rate, equivalence ratio and air

preheat temperature are reported as ranges since different fuel batches had slightly different

basic properties and also because of the limit in control accuracy of the system. However, these

variations are small among all tests. In real combustion applications, the power input is likely

fixed while fuel is changed, thus in all these tests the fuel flow rate was adjusted to keep the

power input at 10 kW. The variation of fuel flow rate means a change in the air to fuel ratio in

the nozzle which results in SMD changes. The only practical way of keeping the SMD constant

is adjusting the atomizing air between the tests, but the literature as well as preliminary

combustion tests with ethanol show the high sensitivity of the combustor flow field, mixing,

flame stability and recirculation patterns to the atomizing air [6, 58]. Therefore, to minimize the

50

flow field variations among the tests, the decision was made to assign a fixed atomizing air to all

tests done under the same condition and monitor the SMD variations using a correlation (section

3.1.2). Ethanol, solids, ash and water content tests were done under condition one in addition to

heavy fuel oil, while condition number two is used for two other tests; once for pure bio-oil and

another time for testing heavy fuel oil again. The reason for using condition two in pure bio-oil

test is explained in section 4.3.

Table 4.1. Number one and two operating conditions

Condition 1 (base) Condition 2

Swirl number 5.41 5.41

Power input from the blend 10 kW 10 kW

Pilot power input 0.5 kW 0.5 kW

Primary air preheater power 1.5 kW 1.5 kW

Primary air temperature at the swirl box inlet 320-337°C 368-391°C

Primary air flow rate 241-255 SLPM 205-219 SLPM

Equivalence ratio 0.6-0.63 0.72

Atomizing air flow rate 23.2 SLPM 18.2 SLPM

The primary fuel properties, emissions and SMDs of the tests done using condition one

are listed in Table 4.2 and Table 4.3. Each section of these tables belongs to a separate series of

tests that is recognizable by the label; ethanol (E), solids/ash (S), water (W), heavy fuel oil (H).

More detailed listing of individual test conditions and all other properties can be found in

appendix C. Emissions listed in Table 4.2 are mostly formed due to some sort of incomplete

combustion, while NOx formation mechanisms are very different and not necessarily related to

incomplete combustion of the fuel [6, 59]. Therefore, CO, UHC and CR are discussed together

in each section describing a fuel parameter while nitrogen oxide emissions results of all tests

done at base are discussed section 4.6.

51

Table 4.2. Primary properties and emissions of ethanol, solids/ash, water and heavy fuel oil

batches at base operating condition

a Calculated assuming ethanol addition to bio-oil has only diluting effect on the TGA residue [4]

b Corrected to 310 SLPM exhaust flow rate

Table 4.3. NOx emissions of the ethanol, solids/ash, water and heavy fuel oil batches at base

operating condition

Batch Label Nitrogen (%) NOx (PPM)a

E25 0.07% 167

E20 0.07% 193

E15 0.07% 176

E10 0.07% 159

E5 0.08% 192

S1 0.19% 133

S2 0.21% 183

S3 0.16% 173

S4 0.16% 154

S5 0.12% 125

S6 0.12% 129

W1 0.11% 57

W2 0.13% 82

W3 0.11% 92

W4 0.09% 111

H1 0.26% 162 a Corrected to 310 SLPM exhaust flow rate

Batch

Label Solids Ash Water

Ethanol

Vol.

TGA

Residue

SMD

(μm)

CO

(mg/MJ)

UHCb

(PPM)

EICR

(mg/kg fuel)

E25 0.057% 0.049% 22.5% 25.0% 14.51%a 69.9 303.7 25 155.0

E20 0.060% 0.051% 23.6% 20.0% 15.21% 71.2 382.1 25 160.0

E15 0.063% 0.054% 24.7% 15.0% 15.89%a 72.6 605.4 70 174.4

E10 0.065% 0.056% 25.7% 10.0% 16.54%a 74.1 702.4 70 173.0

E5 0.068% 0.058% 26.7% 5.0% 17.18%a 75.6 750.3 85 248.0

S1 0.081% 0.027% 23.0% 15.0% 15.05% 74.4 202.9 45 125.1

S2 0.089% 0.223% 23.1% 15.0% 19.00% 75.0 498.0 78 185.5

S3 0.839% 0.241% 23.0% 15.0% 15.37% 73.6 573.9 171 199.4

S4 2.217% 0.294% 22.9% 15.0% 19.73% 73.4 1151.7 299 492.4

S5 0.054% 0.036% 25.7% 15.0% 14.70% 73.5 349.9 94 257.1

S6 0.054% 0.054% 25.4% 15.0% 14.91% 73.2 775.8 214 205.6

W1 0.054% 0.00% 8.9% 15.0% 21.59% 89.6 575.6 300+ 359.8

W2 0.045% 0.009% 17.5% 15.0% 19.13% 76.6 266.0 220 567.5

W3 0.027% 0.00% 26.1% 15.0% 15.83% 73.8 186.3 33 153.7

W4 0.047% 0.00% 8.9% 28.2% 18.90% a 75.4 157.4 77 526.7

H1 NA 0.024% NA NA 9.56% 52.4 32.3 BD 494.0

52

4.2 A Conceptual Model of Bio-oil Combustion

This section introduces the hypothesis of the study. Figure 4.1 depicts the stages of the bio-oil

droplet combustion, similar to section 2.4. In the first stage of the droplet combustion, gas

ejected from the droplet surface burns in a homogeneous combustion mode and forms a flame

around the droplet. A char particle is what remains from the first stage which mostly contains

heavy molecular weight (HMW) molecules that cannot evaporate as well as ash and solid

particles. This char particle burns in a heterogeneous mode and forms the PM which consists of

ash and partially burned char that is measured as CR. Different pollutants are formed during

different stages of bio-oil combustion. Part of the hypothesis is that the CO and UHC emissions

are both mostly formed during the second combustion stage. Therefore, the higher the amount of

HMW and solids in a bio-oil batch, the higher the amount of CO and UHC. Measurements

during bio-oil combustion at the base operating point have estimated the temperature of the gas

right below the flame to be around 1000K [6]. This region below the flame is where a fraction

of char particles burn and are seen as shining particles. According to glassman, temperatures

below 1100K are not enough for complete oxidation of CO to CO2 [54]. These temperatures

may not also be high enough to form CO from the UHC. Therefore, the hypothesis that CO and

UHC are formed during the second combustion stage outside of the flame is physically justified.

The results of various tests confirm that these two species follow the same trends. The role of

the ash content is investigated in section 4.4 and it is shown that ash encourages the char

gasification and thus increases the CO and UHC emissions.

As mentions in section 3.2.1.2, the TGA residue shows the char formation potential of

the bio-oil. The TGA residue consists of ash, solids and HMW molecules that cannot evaporate.

The mass fractions of ash and solids are normally one to two orders of magnitude lower than the

mass fraction of the HMW molecules. As a result, it is assume that the TGA residue represents

the HMW molecules content and is thus treated as a variable independent of the solids and ash

fractions. As can be seen in the mechanism in Figure 4.1, the CR emissions must be dominated

by the solids, HMW molecules and ash fractions of the bio-oil. Results of tests don’t show a

significant correlation between ash and CR emissions. The hypothesis for CR is that despite the

bio-oil’s complicated chemical composition, CR emission can be predicted by the solids content

and the TGA residue.

53

Figure 4.1. Pollutants formation mechanisms of the bio-oil combustion

4.3 Ethanol Tests

All the bio-oil batches mentioned in the previous studies of this setup were mixed with ethanol

[6, 7]. The reason is the small scale of the burner (and short residence times) and lack of

refractory lining, which would make stable combustion of some batches very difficult. To

further study the effect of ethanol addition, a parent batch of bio-oil was mixed with different

percentages of ethanol and each batch tested according to condition one (tests E25-E5). The

trends observed here are expected to be similar if another oxygenated volatile compound such as

methanol was added to bio-oil, or the volatile fraction of the parent bio-oil was increased by

further thermal cracking or reduced condensation temperature of the manufacturing process

[12]. From Table 4.2, one can observe that the calculated SMDs of all ethanol tests are very

close and hence any differences in the emissions should be mostly due to the ethanol content

differences. As can be seen in Figure 4.2 and 4.3, CO and UHC emissions increase steadily by

decreasing the ethanol mass fraction; this is mainly due to increase in the heterogeneous

combustion (corresponding to a high TGA residue as seen in appendix D) and also decrease in

the volatile fraction (ethanol) as explained in section 4.2. For a large number of droplets, the

char oxidation stage happens outside the flame sheet, because of the longer residence time

required for heterogeneous combustion. Therefore, a larger fraction of ethanol can decrease the

54

CO and UHC by two mechanisms: (i) increasing the flame size, since more ethanol means more

mass burns in the homogeneous combustion stage (this in turn increases the droplet residence

time in the hot flame zone), (ii) decreasing the fraction of fuel that gasifies outside the flame.

The transition from a stable flame to a less stable flame with more individual particles burning

can be seen in Figure 4.5.

Figure 4.2. Increase of the emissions by increase in the TGA residue

One interesting finding of the ethanol parametric study is the effect of ethanol on the CR

emissions which is shown in Figure 4.4. The vertical axis of this graph shows the EICR divided

by mass fraction of bio-oil in the blend to take out the dilution effect of ethanol on the results.

This graph is showing between 10% and 25% ethanol addition to bio-oil has no detectable effect

on the organic portion of the particulate matter, except for dilution. This is consistent with

observations in heavy fuel oil single droplet studies, where adding lighter fuel oil to residue oil

has no effect on the formation of the coke particle except for dilution, indicating that this residue

is more a function of the amount of some heavy molecular weight (HMW) chemicals in the

residual oil [55]. Although, the same source claims that the oxidation of the coke particles could

be enhanced by the addition of lighter fuels by dispersing a lower mass of HMW chemicals over

the same number of droplets, such a trend is not observed here. One argument supporting the

observed results here is that according to photos and visual observations, even at high ethanol

concentrations, individual droplet combustion seems to be dominant. Thus, the overall

0

50

100

150

200

250

300

0

200

400

600

800

1000

1200

1400

14.0% 14.5% 15.0% 15.5% 16.0% 16.5% 17.0% 17.5%

CO

an

d U

HC

(P

PM

)

TGA Residue

CO

UHC

CR

CR

(m

g/kg

fu

el)

E5

E10 E15

E20

E25

55

combustion can be explained by considering the droplets burning separately. In an individual

droplet, burning of CR must happen at the final stage of droplet combustion which is likely to

happen outside of the flame sheet, while most of the volatile ethanol is expected to burn in the

early stages of the droplet lifetime. Therefore, ethanol would not have a significant effect on the

CR oxidation unless most of the residue droplets are entrained and returned into the flame zone.

Pure bio-oil was also tested at the base condition (it is not mentioned in Table 4.2), but

the flame was blown out before data collection. Pure bio-oil and batch E95 behaved differently

from the rest of the ethanol study batches and one important feature of these fuels is instability.

The partially premixed region of the flame close to the nozzle, along with the pilot, plays an

important role in stabilizing the flame. Visual observations and flame photos imply that the

flame lift-off increases as the ethanol content decreases. This lift-off is a result of longer

evaporation time of the droplets and also narrower flammability of bio-oil relative to ethanol

[6]. Both E95 and pure bio-oil batches showed a relatively large lift-off combined with

combustion chamber pressure fluctuations during the first several minutes after the ethanol

warm-up. Therefore, the CR jump in Figure 4.4 when ethanol decreases from 10% to 5% can be

attributed to the contribution of the instability of the flame which corresponds to local

instantaneous flame blow out and extinguishing of the fuel droplets. This shows that for this

burner at least 10% ethanol is required to evaporate quickly and stabilize the flame close to the

nozzle. Understanding the blow out and instability mechanism of ethanol batches helped find a

more suitable condition for burning pure bio-oil. To decrease the flame lift-off, the atomizing air

was decreased and primary air was also decreased for more stability. Although these changes

proved to enhance the stability, previous tests have shown that these deviations from the base

condition come with the penalty of increased CO and UHC, particularly because of the increase

in SMD as a result of decreasing the atomizing air [6, 7]. This new condition (condition 2) was

used to study batches E0 and H2 in section 4.9.

56

Figure 4.3. Average CO and UHC as functions of ethanol volume fraction

Figure 4.4. Modified CR emission index as a function of ethanol volume fraction

0

10

20

30

40

50

60

70

80

90

0

100

200

300

400

500

600

700

800

0% 5% 10% 15% 20% 25% 30%

CO

[m

g/

MJ]

Ethanol volumetric fraction [%]

CO

UHC

UH

C [

PP

M]

E15 E10

E5

E20

E25

57

(a) (b) (c)

(d) (e)

Figure 4.5. Borescopic photos of bio-oil-ethanol blend flames with different ethanol

content: (a)25%, (b)20%, (c)15%, (d)10%, (e)5%

4.4 Solids and Ash Tests

Batches S1-6 were tested to investigate the effects of solids and ash content. Looking at Table

4.2, batches S1-4 have very close water content, ethanol content and SMD. Therefore, any

trends in the emissions can be attributed to the solids, ash and the TGA residues of these fuels.

This section first compares batches S1-4 and batches S5, 6 are used to support parts of the

arguments.

Batches S2, 3, 4 can shed some light on the isolated effect of solids, since they all have

similar ash content. Figure 4.6 and Figure 4.7 show graphs of CO, UHC and CR versus solids

content of these batches. A quick look at the trends shows the general increase of all emissions

pointing towards the detrimental effect of an increase in solids. This trend is consistent with the

mechanisms of CO, UHC and CR formations explained in section 4.2. However, the trend is not

58

always linear. The solid particles in fuel are not likely to affect the atomization since as

explained in section 2.3.2, characteristic size of the most of the particles is less than 10 µm,

which is much less than the predicted SMDs of around 75 µm.

The increase in CR from batch S2 to S3 (Figure 4.7) is not detectable. The important

parameter neutralizing the effect of solids increase from S2 to S3 is the 23% decrease in the

TGA residue. As discussed in section 4.2 both the TGA residue and solids play an important

role in CR formation.

Figure 4.6. Average CO and UHC as functions of solids mass fraction for batches S2, 3, 4

0

50

100

150

200

250

300

350

0

200

400

600

800

1000

1200

1400

0.0% 1.0% 2.0% 3.0%

UH

C [

PP

M]

CO

[m

g/M

J]

Solid[%]

CO

UHC

S2

S3

S4

59

Figure 4.7. CR emission index as a function of solids mass fraction for batches S2, 3, 4

The major increase in all emissions from batch S3 to S4 has several reasons. Ash and

solids have both increased from S3 to S4 by 22% and 264%, respectively. The TGA residue of

S4 is also higher.

Size distribution of the suspended solid particles is also another factor affecting the

combustion. Microscopic photos of batches S1-4 are shown in Figure 4.8. Most of the particles

existing in S1, 2, 3 are less than 10 µm, so they are unlikely to deviate the fuel atomization

process from what is predicted for Newtonian fluids. Bigger particles have a detrimental effect

on heterogeneous combustion emissions because they increase the droplet burning time

according to the “D squared” law [15]. But the effect is more severe when particle sizes are

close to the SMD (such as ones in S4 as seen in Figure 4.8). In spite of the calculated SMDs

being very close for batches S3 and S4, the effective SMD of S4 must be larger because of the

poor shattering and aerodynamic breakup of the primary droplets which is not accounted for

using the classical SMD correlations. This nonlinear effect is another justification for the

substantial increase of emissions from S3 to S4 compared to S2 and S3.

Comparing S1 and S2, the solids content is almost the same for both, so the jump in

emissions can be attributed to one order of magnitude increase in ash as well as the increase in

the TGA residue. To confirm the existence of ash trend, test S5, 6 were done, where all the

0

100

200

300

400

500

600

0.0% 0.5% 1.0% 1.5% 2.0% 2.5%

EIC

R[m

g/k

g fu

el]

Solid [%]

S2 S3

S4

60

parameters for the two fuels are the same except for the ash content. In that case, CO and UHC

are approximately doubled confirming the existence of some effect of ash-only on gas phase

emissions. Ash can have different effects on the combustion efficiency. Very high levels of ash

(more than 10%) existing in coal have been proved to decrease the combustion efficiency by

increasing the heat capacity of the char particle and blocking the oxidizer from the diffusion to

the char particle by forming a layer around it [56]. On the other hand, ash can catalytically

accelerate the gasification of CR in the char combustion stage according to gasification

literature. As described in section 2.3.3, bio-oil ash contains various alkali metals, including

potassium compounds which have been reported to have an accelerating effect on the

gasification of coal particles into CO [57]. These results are interesting, since already proven

methods such as hot gas filtration or other methods of solid separation from pyrolysis vapors

can decrease the solid and ash content at the same time (most of the ash present in the fuel is

bound up in the solid particles) [19].

61

S1 S2

S3 S4

Figure 4.8. Microscopic photos of batches S1-4. All photos are taken using the same optical

conditions and are 170x240 µm

Another interesting difference of batches with different amounts of solids and ash is the

flame luminosity. As is seen in Figure 4.9, especially when comparing S1 and S4, the batch with

higher solids is more luminous because of black body radiation effect of solid particles burning.

Figure 4.9. From left to right: flame photos of S1, 2, 3, 4

62

4.5 Water Tests

Removing water from bio-oil can decrease the droplet evaporation time due to the high latent

heat of evaporation, accelerate the gas phase combustion reactions and decreases the adiabatic

flame temperature [12]. On the other hand, removing water can make the fuel very viscous and

also reduce the likelihood of effective micro-explosions [17] as discussed in section 2.3.1. To

see which group of these mechanisms is more dominant in a spray combustion system, tests on

W1, 2, 3, 4 were done. These batches all have very low and similar contents of solids and ash. In

addition, they are all blended with the same amount of ethanol. Results of TGA (appendix D)

also show that water has no effect other than dilution on the residues. As shown in Figure 4.10

and Figure 4.11, the batch with the highest amount of water has the least emissions.

Batch W1 was extremely viscous and the fuel pumps were run at double the usual speed

to compensate for such high viscosity (the pumps run at room temperature). The effect of

viscosity is much less significant at nozzle temperature (80˚C); however, there is a notable

difference between the calculated SMD of W1 with other batches. W1 showed non-steady

combustion; many fuel droplets hit the burner walls before burning and as a result, flames on the

walls were observed as shown in Figure 4.13. This is due to higher SMD and longer droplet

evaporation time of W1 compared to all the batches tried under condition one. Flame

extinguishing on the walls is a cause of CO and UHC generation [15]. In addition, low wall

temperatures and poor mixing can be responsible for the high UHC emissions of W1 seen in

Table 4.2 (FID was saturated at 300 PPM). In simple words, this fuel is not suitable for this

combustion system.

63

Figure 4.10. CO and UHC emissions of W2, 3. W1 not shown because of failing to achieve

stable condition

Figure 4.11.CR emission indexes of W2, 3. W1 not shown because of failing to achieve

stable condition

UHC, CO and CR emissions of batch W2 was in the middle of W1 and W3 as was the

viscosity and water percentage. The effect of water can be clearly seen comparing W2 and W3

since they both have the same SMD, unlike W1 and W2. The main difference between W2 and

W3 is the TGA residue which is essentially because of water dilution. Considering this

64

difference, the higher CO, UHC and CR emissions of W2 relative to W3 are in consistent with

the mechanism described in section 4.2.

One important difference between the water batches is the heating values; the higher the

water content the lower the heating value. This means that when using W2, a lower amount of

fuel is required to generate the same amount of energy compared to W3. To take this effect into

account, CR can be expressed in units of (mg/MJ) as done in appendix C. Even with this help,

W2 generates more than three times higher CR compared to W3.

The best bio-oil blend among all the batches tried in this study was W3. Definitely, high

water content of this batch plays an important role, by enhancing atomization compared to W1

and lowering the TGA residue compared to both W1 and W2. To further investigate the effect

of TGA residue on CR, batch W4 was prepared by adding a mixture of ethanol and water to W1.

The mixture was prepared in such a way to keep the water content of W1 constant while

reducing the viscosity and thus the SMD. The water-ethanol mixture was added to W1 in steps

and after each step the viscosity was measured with a dip viscometer (Zahn cup). This

viscometer works by measuring the time it takes for the liquid to drain from a standard cup. The

water-ethanol mixture was added till viscosity of the newly created batch (W4) matched that of

W3. The test results of these two batches are compared in Figure 4.12. The SMDs are very close

and although W4 has much more ethanol, the combustion efficiency is lower than W3 (UHC,

CO and CR of W4 are either higher or in the same range as W3). This can only be attributed to

the TGA residue. These results along with the conclusions of section 4.3 all point out the

importance of reduction of the TGA residue of the bio-oil and also the importance of the spray

quality.

65

Figure 4.12. Comparison of Batches W3 and W4

W1 W2 W3 W4

Figure 4.13. Borescopic photos of the water tests

4.6 NOx Emissions of Bio-oil Blends

NOx formation is a complex function of operating condition and fuel chemistry [58]. Literature

about NOx emissions from bio-oil combustion is scarce, while detailed knowledge of nitrogen

oxides formation mechanisms is necessary to model or understand the full behavior of these

compounds. However, previous studies on bio-oil have one common important conclusion; they

have shown that fuel NOx formation mechanism is the dominant among the other forms of NOx

mechanisms (i.e. prompt and thermal) [6, 65]. NOx values presented here are sums of NO and

18.9 157

79

527

15.8 186

33

154

TGA residue(%) CO (mg/MJ) UHC (PPM) CR (mg/kg fuel)

W4

W3

66

NO2 concentrations with NO usually having a much larger share. By running ethanol under the

base condition, thermal NOx is estimated to be 50 PPM. When comparing the ethanol and

solids/ash tests, no definite trend showing the dependency of NOx on the control parameters can

be observed. For example, comparing E20 and E15 with S3 and S4, shows that whenever

nitrogen in fuel increases, NOx does not necessarily increase as expected [59]. However, an

increase in NOx can be gained by increasing the water content of bio-oil blends (batches W1, 2,

3). This reduction is likely due to a more complete combustion of the fuel droplets which can

result in better mixing of combustion air and nitrogen in the fuel. Another observation from the

water tests is that the effect water has in reducing the flame temperature and thermal NOx is

overwhelmed by fuel NOx formation by better fuel-air mixing.

When looking at all the NOx results from bio-oil tests together, a general trend, which is

also reported in various literature sources, can be found. The ratio of measured NOx to the total

NOx that could have been produced if all the nitrogen in the fuel had been converted to NOx is

called nitrogen conversion ratio and can show the potential of the fuel to form fuel NOx. For

different types of fuels, including bio-oil, this ratio has been proved to decrease as the nitrogen

in the fuel increases [65, 66]. This trend is depicted in Figure 4.14. For some batches this ratio is

greater than one which shows the contribution of thermal and prompt NOx, especially when

nitrogen in the fuel is very low.

67

Figure 4.14. NOx conversion ratio for all bio-oil batches. Error bars show variations of

measured NOx in each test

4.7 Acetaldehyde, Formaldehyde and Methane Emissions

For most of the batches, acetaldehyde, formaldehyde, and methane were below detection (BD)

limits. Table 4.4 lists the tests where these emissions were not below the detection limits. As can

be seen, all these batches have a relatively high UHC emission, which corresponds to poor or

unstable combustion. None of the other batches, including the number 4 fuel oil, have UHCs

more than 100 PPM.

Table 4.4. Batches with non-zero acetaldehyde, formaldehyde and methane emissions

0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

0.00% 0.05% 0.10% 0.15% 0.20% 0.25%

NO

x C

on

vers

ion

rat

io

Mass Fraction of Nitrogen in Fuel

Batch

Label

CH4

(PPM)

CH2O

(PPM)

C2H4O

(PPM)

UHC

(PPM)

S3 BD 20 21 171

S4 35 50 91 299

S6 15 15 BD 220

W2 BD 10 30 225

W1 BD 30 20 111

E0 30 12 BD SAT

68

4.8 A Linear Model for CR Emission Index

The results of water, ethanol and solids/ash batches tested under condition 1, show that except

for batches E5 and W1 where atomization or flame stability is relatively poor, CR in the rest of

the batches tends to increase with the TGA residue and the solids content. This can be explained

by the mechanism of bio-oil combustion explained in section 4.2. To investigate the relation

between CR, TGA residue and solids, regression analysis was used.

But before using the regression analysis, a correction was required for the CR emission

index in a few of the tests, results show that some PM (which consists of mostly CR and ash) is

deposited on the burner walls before reaching the PM sampler. Since the regression analysis

requires a relatively accurate knowledge of all the parameters, this loss should be somehow

accounted for. CR lost to the walls can be quantified by assuming that in each test, the fraction

of total generated CR that reaches the PM sampling filter is the same as the fraction of total ash

in the fuel that makes it to the PM sampling filter. In other words, the ash concentration

calculated from the filter deposition rate is usually a fraction of original ash concentration in

fuel because of the PM loss in the exhaust passage. This ratio can be calculated by combining

the ultimate analysis of fuel and the ash emission index from equation (3.7). This ratio is called

the collection efficiency and since both ash and CR loss to the walls happen by the same PM

deposition mechanism, it seems reasonable to assume the collection efficiencies of CR and ash

are the same. The batches with collection efficiencies less than 100% are listed in Table 4.5.

Batches W3 and W4 have zero ash which would make the usage of above method impossible.

For these batches, an efficiency of 100% was assumed due to relatively good combustion

quality and low observed wall deposition. Dividing the calculated EI CR obtained from equation

(3.6) by the PM collection efficiency gives the corrected CR emission index which is used in

this section for the regression analysis. It should be emphasized that the by applying the

corrections mentioned in this section, the CR trends and relative amounts discussed in the

previous sections are not invalidated, but mostly shifted to new values.

69

Table 4.5. Tests with PM collection efficiencies not equal to 100%

Batch

Label

PM Collection

Efficiency

S1 49.93%

S2 35.03%

S3 36.29%

S4 35.15%

S6 92.12%

The best fit was found when linear regression was applied to find the average CR

emission index as a function of TGA residue and solids. It was assumed that both the

independent variables, TGA residue and solids fraction, vary in a small range so that all effects

can be linearized. A formula was fit to the available data with the following non-dimensional

format:

(4.1)

The coefficients A, B and C are unknown and there are as many of these equations as the

number of tests being considered (13 equations). Averages of EICR, solids, and TGA residue are

taken over all the 13 batches being considered and are listed in Table 4.6. Linear regression

algorithm finds the unknown coefficients α, β and γ that minimize the sum of the squares of the

residues of all the equations [52]. These values are listed in Table 4.6; α and β show how the

significance of each independent variable is. γ shows what would the normalized EICR be if both

solids and TGA residue were zero, however, the negative number is not really physical since

that region is far away from the region where the linear assumption is valid. This analysis sheds

some light on the relative importance of solids and TGA residue on the CR; β is one order of

magnitude higher than α, which means for burners of this size, one important fuel upgrading

method is reducing the TGA residue (corresponding to decreasing the polymerization potential

and the fraction of HMW molecules), of course, in addition to solids. Another implication of

this analysis is that one can get rough estimates of CR emissions of different fuels without doing

the combustion tests and only by doing the TGA which is a relatively simpler test and requires

very minute quantities of fuel. A value of 0.958 for R square shows the goodness of the fit [52]

and one can also verify the validation of the model by comparing it to the corrected

70

experimental data in Figure 4.15. The number of experimental data points for each batch shows

how many filters are collected in the test.

Table 4.6. The regression analysis results and averages of parameters

R Square α β γ Average Solids Average TGA

residue Average EICR

0.958 0.281 3.425 -2.079 0.28% 16.52% 395.4 (mg/kg fuel)

Figure 4.15. Comparison of the corrected experimental CR emission indexes and the curve

fit. Error bars are not shown since they are negligible compared to the scatter in the

experimental results

4.9 Pure bio-oil Combustion and Comparison with Heavy Fuel Oil

As explained in section 4.3, stable bio-oil combustion at base operating point was not possible

and as a result another set of flow conditions (condition 2) were used for pure bio-oil and heavy

fuel oil comparison. Previous works on the same setup compared diesel with bio-oil blends and

suggested a heavier fuel must be used for comparison [4]. Number 6 fuel oil, as the lowest grade

heating oil, is the residue of crude oil distillation and requires preheating before pumping or

atomization, which could be problematic. Instead, a mixture of 50%(volumetric) diesel and 50%

0

200

400

600

800

1000

1200

1400

1600

1800

E25

E20

E15

E10 S1 S2 S3 S4 S5 S6 W2

W3

W4

Co

rre

cte

d E

I CR

(m

g/kg

fu

el)

Batch Label

Experiment

Fit

71

number 6 fuel oil was used which has a viscosity close to the bio-oil blends (appendix C) and

does not need preheat before pumping. According to the measured viscosity, this blend can be

classified as number 4 fuel oil [60], which is shown by letter “H” among the batches in the

tables. “E0” is the label for pure bio-oil (zero percent ethanol). One notable difference between

bio-oil and heavy fuel oil is the existence of water in bio-oil which results in a significant

reduction of heating value and also the adiabatic flame temperature as can be seen in Table 4.8.

The difference between heating values also makes the test design difficult since fuel flow rate of

bio-oil had to be almost 3 times that of fuel oil. This means that if one tries to match the SMDs,

either the atomizing air had to be changed to keep the ALR in the nozzle constant, which would

give very different aerodynamic conditions, or keep the atomizing air as well as the fuel flow

rates the same, which would give different power inputs and flow rates. Both scenarios were

discarded in favor of having a fixed atomizing air and power input, which is more likely to

happen if fuel oil is being directly replaced by bio-oil in an industril burner.

Table 4.7. Comparison of heavy fuel oil and pure bio-oil properties and emissions

a Viscosity measured at the injection temperature

b Corrected to 310 SLPM exhaust flow rate

Table 4.8. Comparison of NOx and flame temperatures of bio-oil and heavy fuel oil

Batch

Label

Nitrogen

(%) NOx (PPM)

a

Adiabatic Flame b

Temperature (K)

E0 0.08% 158 2119

H2 0.26% 136 2500 a Corrected to 310 SLPM exhaust flow rate

b Calculated using fuel composition, heating value, assuming stoichiometric and complete

combustion

The differences in SMDs can justify the higher amounts of CO and UHC emissions of

bio-oil relative to fuel oil as summarized in Table 4.7. TGA residue for bio-oil is also higher

which must be another contributing factor to higher gas phase emissions. One surprising result

Batch

Label Solids Ash Water

Kinematic

Viscositya

(cSt)

TGA

Residue

SMD

(μm)

CO

(mg/MJ) UHC

b

(PPM)

EICR

(mg/kg fuel)

E0 0.070% 0.060% 27.6% 3.67 18.08% 99.0 1207.5 300+ 255.0

H2 NA 0.024% NA 3.28 9.56% 65.4 18.0 BD 526.0

72

is the EICR of H2 being higher than E0. From the elemental analysis of bio-oil ash, it is apparent

that alkali metals, like potassium that can encourage gasification, are abundant [7]. This would

suggest that bio-oil combustion residues have a higher tendency to gasify compared to fuel oil

residues. Results also suggest that NOx formation potential of pure bio-oil is higher since in spite

of a lower nitrogen content (corresponding to a lower potential of fuel NOx formation) and lower

flame temperature (corresponding to thermal NOx formation potential) the final nitrogen oxides

emissions are slightly higher. This difference must be due to the differences of fuel chemistries

of these fuels and how different types of nitrogen containing groups are attached to fuel

molecules. The H2 flame was slightly more stable, flames were less detached (Figure 4.16), and

similar to bio-oil blends and unlike lighter fuels like diesel, individual droplets, were burning

outside of the flame sheet. The H2 flame was also extremely luminous and the exposure time of

the camera had to be decreased from a regular 1/15 second to 1/50 second to avoid a light

saturated photo. This is attributed to the high flame temperature and also the black body

radiation of the large amounts of cenospheres and soot.

Figure 4.16. Combustion of fuel oil (left) and pure bio-oil (right) under condition 2

Fuel oil was also tested under base condition (H1) with a smaller SMD, which is

mentioned in Table 4.2. Comparing H1 and H2 shows how a smaller SMD can help better

burnout of the CR particles for a conventional fuel. The CO emissions of H2 are slightly lower

than H1; the high shear of the atomizing air jet seems to enhance local cooling and

extinguishing of the flame as suggested in the previous study comparing bio-oil and diesel under

similar conditions [4]. Using this combustor, number 4 fuel oil performs better than bio-oil

blends and pure bio-oil in terms of stability and gas phase emissions while the particulate matter

emissions of it are comparable or worse than bio-oil batches. However, as explained in section

73

2.5, larger combustors with longer residence times may dampen the differences between bio-oil

and fuel oil emissions, especially in terms of CO and UHC.

4.10 Unsuccessful Works

From the previous studies as well as ethanol tests it was apparent that a nozzle that could

generate a fine spray using a low atomizing air flow rate is beneficial since it could help better

stabilize the flame and would increase the combustion efficiency. One such nozzle can be built

by simply replacing the liquid injection part of the nozzle assembly with a smaller one which is

also compatible with the air cap (Figure 3.5). The liquid orifice size would be approximately

500 microns, which is an order of magnitude larger than the typical solids particle size. This

nozzle was tested outside the burner without combustion and using batch S1, the nozzle clogged

after about 10 minutes. Coagulation of the small particles and the accumulation of the big ones

results in the blocking. As a result, the nozzle was not studied as a new design parameter.

Nozzle clogging is difficult to predict and happened during one official test,

unexpectedly. A batch with 0.98% solids clogged the nozzle and activated the fuel pressure

relief valve after about 20 minutes of combustion. Microscopic photos revealed that particle size

distribution of this batch tends to be shifted towards the larger particles. This means that for

clogging, the particle size is important, since S4 for example had twice the amount of solids but

did not clog the nozzle or even did not increase the nozzle pressure. Microscopic photos of this

batch along with two other batches that could not be tested are all provided in the appendix D.

These additional batches were also tested outside of the burner and proved to clog the nozzle in

a short time period. The decision was made not to test these batches in the burner because of the

likelihood of the nozzle clogging again. For future works, testing of the fuel outside of the

burner (using the same fuel system) is recommended before running it in the combustion test.

Before the system used in this study, a sampling system with a probe inside the

combustion chamber was designed and built. One advantage of that system was more credible

measurement of the PM since the sampling point was upstream of the two elbows and the orifice

at the end of the combustion chamber. On the other hand, there are some major drawbacks; the

PM had to be sampled from a swirling gas that would be affected by swirl number. In addition,

74

the PM is not homogeneously distributed in that cross section of the burner which would

necessitate the use of multi-point sampling and a complex flow rate control system.

75

Chapter 5

Conclusions and Recommendations 5

Conclusions and Recommendations

5.1 Conclusions

Effects of solids, ash, water and ethanol content of various bio-oil mixtures were tested and

results from combustion diagnostics show the trends bio-oil producers can use in order to make

fuels more suitable for small scale burners, diesel engines or gas turbines. In addition, based on

the results, a conceptual model for describing the pollutants emissions from bio-oil combustion

is presented which can be used as a basis to develop more advanced mathematical models.

One important conclusion is the influence of water over emissions; results suggest that

water removal from bio-oil does not improve combustion quality and efficiency. The main

reasons for this trend are the effects water has in diluting the TGA residue and in decreasing

viscosity.

Another important observation is the detrimental and nonlinear effects of solids and ash

on CO, UHC and CR emissions; at low levels of solids (less than 0.1 % in this system) changes

in the solids content has mild effects on the emissions, while at higher concentrations (in the

order of 1% in this burner) and larger particle sizes, especially when the particle sizes are close

to fuel spray SMD, the effects become significant. Test results from the high solids batch (S4)

and the low water content batch (W1) along with the literature about the effects of atomizing air

flow rate [6, 7] show the high sensitivity of combustion stability and emissions to the

atomization quality.

76

CO and UHC emissions are proven to be sensitive to ash content because of the catalytic

effects the alkali metals have in accelerating the gasification of the char particles.

Addition of at least 10% volumetric ethanol to bio-oil (in a system with this scale) or

increasing the volatility of the fuel through hot gas filtration or decreased vapor condensation

temperature in the production process is recommended to help the ignitability and stability of

the fuel. Ethanol addition is also shown to have more a diluting effect on the CR emissions in

the range studied here (10-25% volumetric).

Among the batches studied here that were mixed with 15% ethanol, batches W3 and S1

seem to have the lowest emission levels. The low viscosity as a result of relatively high water

content in these fuels leads to good atomization; ash, solids and TGA residues are also relatively

low for both these batches.

Another important conclusion is that CR emissions correlate with the TGA residue and

solids content, for fuels with similar SMDs. The TGA is recommended as a tool for estimating

the PM generation potentials of different bio-oils in a spray burner, along with solids content

measurement.

Nitrogen oxide emissions of bio-oil behave similar to other fuels; as the nitrogen content

of fuel increases, the conversion efficiency decreases.

Bio-oil is also compared to number 4 heavy fuel oil; results show that bio-oil performs

similar in terms of CR emissions, but stands inferior in terms of gas phase emissions (CO, UHC

and NOx ).

5.2 Recommendations and future works

This section lists the possible improvements to the burner systems or the research ideas that are

recommended for investigation in the current system:

1. Carbon monoxide and unburned hydrocarbon emissions of this burner can be decreased

by adding refractory lining or insulation to the hot sections of the combustor.

77

2. One problem existing in the current system is the possibility of the fuel droplets

impinging on the diffuser section walls according to the modeling study done on this

combustor [61]. One solution is to increase the diffuser section diameter, or the whole

combustor diameter. Another way is to decrease the droplet size which would decrease

the evaporation time. The latter is also beneficial from combustion efficiency point of

view as discussed below. Solving the droplet impingement problem could also decrease

the PM loss to the combustor walls.

3. One way of improving combustion efficiency for the current system is designing a new

nozzle. This nozzle would ideally not use atomizing air, which adds a large axial

momentum to the flow field and has negative effects on the stability. Nozzle designs

similar to single orifice pressure atomizers are not likely the proper choices for such low

power input system since as discussed in section 4.10 the char particles would easily

block the holes. One way around this problem is to change the total power input to the

burner.

4. PM loss to the burner walls causes errors in the emissions measurements. Isokinetic

sampling at any location further upstream seems to be difficult due to geometrical

constraints. One solution for this problem is redesigning the combustion chamber and

sampling system targeting at reducing PM loss. Changes may include adding a nozzle at

the end of the chamber instead of the sudden contraction in the existing system and also

attaching the sampling pipe directly below the nozzle without any elbows in between.

5. In the current system, FID sampling cannot be done while FTIR is in use. Modifying the

heated line connections in order to make the simultaneously sampling possible can be

done easily by adding a junction before the current FID/FTIR branch.

6. The trends observed in this study could be better understood by conducting fundamental

single droplet combustion studies on bio-oil. In addition, since bio-oil is intended for gas

turbines and diesel engines, fundamental studies of bio-oil evaporation and combustion

in high pressures is a practical project. Such studies would also provide the physical

parameters required to develop a full computational fluid dynamics model of bio-oil or

to modify the existing ones [61].

78

7. TGA gives important information regarding the evaporation of bio-oil. However, another

piece of information would be a curve showing the heat input to a fixed mass of fuel

versus temperature. Such curve would differentiate between fuels based on the energy

required to evaporate.

8. Spray quality is definitely an important parameter dominating the combustion

performance and emissions. In this study, empirical correlations were used to compare

the SMDs of different fuels. However, the spatial droplet size distribution, spray angle,

jet and droplets velocity fields are also other important factors that require measurement.

9. One interesting study using the current setup would be investigating how the aging of

bio-oil would affect the combustion performance as well as the fuel properties.

10. In this study, ethanol was tested as a fuel additive. The emulsions of bio-oil and diesel,

bio-oil and gasoline or bio-oil and heavy fuel oils are also recommended for further

investigations.

11. Number 4 fuel oil was found to be slightly better in terms of combustion stability and

efficiency than bio-oil. Thus, heavier grade fuels are also worth comparing with bio-oil.

12. Another interesting research project can be planned to identify the effects of solid

particles size distribution on the emissions while the total amount of solids is fixed.

79

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Appendix A

Theoretical Isokinetic Sampling Flow Rate

87

To verify that PM line sampling flow rate corresponds to the isokinetic conditions, the ratio of

isokinetic sampling flow over total flow in the duct is theoretically calculated here. Within the

main duct, the Reynolds number may be estimated using the properties of air at 250 °C (based

on prior measurements at the probe cross section during combustion tests) and a total exhaust

mass flow rate of 6.06 g/sec (under average base operating conditions). This corresponds to a

Reynolds number of approximately 7400 and an average main duct velocity of 8 m/s, verifying

that the flow in the main duct is turbulent. Therefore, the following velocity profile may be used

to describe the duct velocity (Dennis et al. [47]):

(

)

⁄

(A.1)

Here, vmax is the maximum centerline velocity, y is the coordinate distance from the wall and R

is the inner radius of the main duct. Figure A. shows this theoretical velocity profile.

Figure A.1. Average velocity profile inside the exhaust duct [4]

One can find the flow rates of sampled gas and total exhaust gas by integrating the above

velocity profile over the sampling probe area and over the whole duct, respectively. The ratio of

sampled (the same as ) over total gas can be proved to be:

(A.2)

88

This ratio is about 10.4% for the current geometry and is independent of maximum velocity.

Most of the tests showed a ratio very close to this number based on equation (3.5) and total flow

rate calculated from the oxygen sensor. This agreement shows that during sampling, the velocity

profile must be very close to the above assumed profile, which means the sampling probe should

have a very minimal aerodynamic effect on the gas flow. This is in fact the purpose of isokinetic

sampling which is sampling the gas in such a way that flow doesn’t “know” the probe exists.

This isokinecity was further verified by doing a well-controlled ethanol combustion test and it

was proved that the ratio is again 10.4% when pressure inside the sampling duct and the main

duct are the same.

89

Appendix B

The Flow Straightener Drawing

90

Figure B.1. Flow straightener drawing

91

Appendix C

Table of Fuel Properties, Test Conditions and Emissions

92

The following tables summarize the results and conditions of all the tests. Equivalence ratio,

total exhaust flow rate and swirl air flow are calculated from the oxygen concentration in the

exhaust. Swirl air preheat temperature is calculated by knowing the total preheater power and

the mass flow rate of air going through it. Adiabatic flame temperature is calculated given the

heating value, fuel composition, complete atmospheric combustion and assuming all reactants

are initially at room temperature. These assumptions must lead to a good approximation of the

diffusion flame temperature studied here; however, the main purpose is comparison of different

fuels. Solids, ash, water, carbon, hydrogen, nitrogen are first measured for each pure bio-oil

batch by standard methods listed in Table 3.1 before the test; but it should be noted that adding

ethanol decreases these fractions and the second step is to include this dilution effect. The

numbers reported here all represent the fuel properties of the mixture burning in the combustor

and therefore the effect of ethanol dilution is already included in them by knowing the mass

fraction of ethanol. Viscosity of each blend is measured following ASTM 445 after the

combustion test. Heating value of all bio-oil batches (except for batches S1, 2, 3, 4) are

measured using ASTM 4809 before the tests in order to find the fuel flow rate corresponding to

10 kW. Heating value of heavy fuel oil is taken from a combustion handbook [60]. Heating

values of batches S1-4 are calculated from a formula suggested by Demirbas et al. [62] [63] for

lignocellulosic biomass fuels based on the ultimate analysis:

[ ] [ ] [ ] [ ] (

⁄ ) (C.1)

Where [C], [H], [O], [N] are carbon, hydrogen, oxygen and nitrogen concentrations in the fuel.

HHVs calculated from this formula for 11 similar bio-oil batches from the same producer were

compared to the measured values. The average error in HHV prediction was 2.5% and the

standard deviation of errors was 1.38% which shows the credibility of this formula for this type

of biomass derived fuel.

93

Ash

0.0

49

%

0.0

51

%

0.0

54

%

0.0

56

%

0.0

58

%

0.0

27

%

0.2

23

%

0.2

41

%

0.2

94

%

0.0

36

%

0.0

54

%

0.0

00

%

0.0

09

%

0.0

00

%

0.0

00

%

0.0

24

%

0.0

60

%

0.0

24

%

So

lids

0.0

57

%

0.0

60

%

0.0

63

%

0.0

65

%

0.0

68

%

0.0

81

%

0.0

89

%

0.8

39

%

2.2

17

%

0.0

54

%

0.0

54

%

0.0

54

%

0.0

45

%

0.0

27

%

0.0

47

%

0.0

00

%

0.0

70

%

0.0

00

%

Wat

er

22

.5%

23

.6%

24

.7%

25

.7%

26

.7%

23

.0%

23

.1%

23

.0%

22

.9%

25

.7%

25

.4%

8.9

%

17

.5%

26

.1%

8.9

%

0.0

%

27

.6%

0.0

%

Eth

anol

vo

lum

e

25

%

20

%

15

%

10

%

5%

15

%

15

%

15

%

15

%

15

%

15

%

15

%

15

%

15

%

28

%

NA

0%

NA

Kin

emat

ic

vis

cosi

ty a

t th

e

inje

ctio

n t

emp.

(cS

t)

1.8

325

2.2

2.5

675

2.9

35

3.3

025

4.2

94

4.3

91

4.0

49

4.1

06

3.0

2

2.9

7

13.3

4

5.6

5

3.0

3

6.5

7

3.2

8

3.6

73

3.2

8

TG

A

Res

idue

14.5

1%

15.2

1%

15.8

9%

16.5

4%

17.1

8%

15.0

5%

19.0

0%

15.3

7%

19.7

3%

14.7

0%

14.9

1%

21.5

9%

19.1

3%

15.8

3%

18.9

0%

9.5

6%

18.0

8%

9.5

6%

C-H

-N

(%m

ass)

40.8

-9.0

-0.0

7

40.3

-8.8

-0.0

7

39.7

-8.6

-0.0

7

39.2

-8.4

-0.0

7

38.7

-8.2

-0.0

8

45.0

-7.9

-0.1

9

44.8

-7.8

-0.2

1

45.3

-8.0

-0.1

6

45.9

-7.9

-0.1

6

39.9

-8.3

-0.1

2

39.7

-8.3

-0.1

2

50.6

-7.2

-0.1

1

45.5

-7.9

-0.1

3

40.1

-8.2

-0.1

1

50.3

-7.8

-0.0

9

85.6

-11.3

-0.2

6

38.3

-8.0

-0.0

8

85.6

-11.3

-0.2

6

Hig

her

hea

tin

g

val

ue

(MJ/

kg)

18

.46

17

.93

17

.41

16

.90

16

.41

18

.98

18

.68

19

.24

19

.38

17

.44

17

.44

21

.48

19

.46

17

.36

22

.17

44

.5

15

.94

44

.5

Lab

el

E2

5

E2

0

E1

5

E1

0

E5

S1

S2

S3

S4

S5

S6

W1

W2

W3

W4

H1

E0

H2

Table C.1. Fuel properties table

94

SM

D

(μm

)

69

.9

71

.2

72

.6

74

.1

75

.6

74

.4

75

.0

73

.6

73

.4

73

.5

73

.2

89

.6

76

.6

73

.8

75

.4

52

.4

99

.0

65

.4

Fu

el f

low

rate

(kg

/min

)

0.0

36

0

0.0

37

0

0.0

38

3

0.0

39

4

0.0

40

7

0.0

34

5

0.0

35

4

0.0

34

2

0.0

33

7

0.0

38

1

0.0

37

8

0.0

30

0

0.0

33

6

0.0

38

5

0.0

29

1

0.0

14

2

0.0

41

8

0.0

14

1

Eq

uiv

alen

ce

rati

o

0.6

2

0.6

3

0.6

2

0.6

3

0.6

3

0.6

2

0.6

2

0.6

2

0.6

3

0.6

3

0.6

2

0.6

0

0.6

2

0.6

3

0.6

0

0.6

0

0.7

2

0.7

2

Ato

miz

ing

air

flo

w

(SL

PM

)

23

.2

23

.2

23

.2

23

.2

23

.2

23

.2

23

.2

23

.2

23

.2

23

.2

23

.2

23

.2

23

.2

23

.2

23

.2

23

.2

18

.2

18

.2

Sw

irl

air

flo

w r

ate

(SL

PM

)

250.4

247.8

249.6

246.8

249.6

249.2

254.7

252.8

248.9

240.5

242.5

252.5

247.9

244.6

250.9

245.8

219.0

205.0

Sw

irl

air

pre

hea

t

tem

per

atu

re

(°C

)

325.1

328.2

326.1

329.5

326.1

326.5

320.0

322.2

326.9

337.4

334.9

322.6

328.1

332.2

324.5

330.7

368.1

391.6

To

tal

exh

aust

flo

w r

ate

(SL

PM

)

309

308

311

309

312

302

314

310

309

304

302

301

303

308

301

282

277

236

Est

imat

ed f

uel

inje

ctio

n

tem

per

atu

re (

˚C)

80

80

80

80

80

80

80

80

80

80

80

80

80

80

80

120

80

120

NO

x

con

ver

sio

n r

atio

13

1%

14

0%

11

8%

10

0%

11

2%

38

%

46

%

58

%

52

%

52

%

50

%

33

%

36

%

41

%

74

%

80

%

86

%

67

%

Ad

iab

atic

Fla

me

Tem

per

atu

r

e (K

)

21

71

21

61

21

51

21

41

21

30

22

06

21

97

22

10

22

14

21

86

21

95

23

32

22

41

21

78

23

32

25

00

21

19

25

00

Lab

el

E25

E20

E15

E10

E5

S1

S2

S3

S4

S5

S6

W1

W2

W3

W4

H1

E0

H2

Table C.2. Summary of test conditions

95

CO

(mg

/MJ)

30

3.7

38

2.1

60

5.4

70

2.4

75

0.3

20

2.9

49

8.0

57

3.9

11

51

.7

34

9.9

77

5.8

57

5.6

26

6.0

18

6.3

15

7.4

32

.3

12

07

.5

18

.0

CO

(PP

M)

51

5

65

0

10

20

11

91

12

60

35

2

83

1

97

0

19

53

60

3

13

46

10

02

46

0

31

7

27

4

60

22

84

40

CR

(mg

/kg

fuel

)

15

5.0

16

0.0

17

4.4

17

3.0

24

8.0

12

5.1

18

5.5

19

9.4

49

2.4

25

7.1

20

5.6

35

9.8

56

7.5

15

3.7

52

6.7

49

4.0

25

5.0

52

6.0

CR

(mg

/MJ)

9.3

0

9.8

6

11

.13

11

.36

16

.81

7.2

0

10

.93

11

.35

27

.68

16

.32

12

.96

18

.00

31

.75

9.8

6

25

.56

11

.71

17

.78

12

.39

CR

no

rmal

ized

to

bio

oil

mas

s (m

g

CR

/kg

bio

-oil

)

190.1

187.1

195.2

186.0

256.9

139.8

207.7

223.2

553.0

288.0

230.6

400.7

633.9

171.9

670.0

NA

255.0

NA

UH

C

(PP

M)

25

25

70

70

84

46

77

171

300

96

220

111

225

33

79

0

SA

T

0

UH

C

no

rmal

ize

d

to 3

10

SL

PM

,

(PP

M)

25

25

70

70

85

45

78

171

299

94

214

108

220

33

77

0

SA

T

0

NO

x

(PP

M)

168

194

175

160

191

137

181

173

154

127

132

59

84

93

114

178

176

178

NO

x

no

rmal

ized

to 3

10

SL

PM

167

193

176

159

192

133

183

173

154

125

129

57

82

92

111

162

157

136

CH

4

(PP

M)

0

0

3

5

5

0

3

9

35

0

15

0

5

0

0

0

30

0

CH

2O

(PP

M)

0

5

6

7

8

9

8

20

50

5

15

30

10

4

6

0

12

3

C2

H4

O

(PP

M)

0

0

6

7

0

2

8

21

91

3

6

20

30

2

0

0

7

0

Lab

el

E2

5

E2

0

E1

5

E1

0

E5

S1

S2

S3

S4

S5

S6

W1

W2

W3

W4

H1

E0

H2

Table C.3. Summary of all emissions

96

Appendix D

TGA Curves

97

Figure D.1. TGA curves of batches S1, 2, 3, 4

Figure D.2. TGA curves of batches S5 and S6

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

15 115 215 315 415 515

Weig

ht (%

)

Temperature (°C)

S1

S2

S3

S4

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

20 120 220 320 420 520

Wei

gh

t (%

)

Temperature (°C)

S5

S6

98

Figure D.3. TGA curves of batches W1, 2, 3

Figure D.4. TGA curves of batches E0, E20, H1 and Diesel

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

0 100 200 300 400 500

Wei

gh

t (%

)

Temperature (°C)

W1

W2

W3

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

20 120 220 320 420 520

Wei

ght

(%)

Temperature (°C)

E0

E20

Number 4 fuel oil

Diesel

99

Appendix E

Microscopic Photos

100

(a) (b)

(c)

Figure E.1. Microscopic photos of the batches that clogged the nozzle; (a) 0.98% solids,

(b) 2.2% solids, and (c) 2.1% solids. All photos are taken using the same optical conditions

and are 170x240 µm.

101

Appendix F

FTIR Calibration Method

102

FTIR calibration is normally done by defining a set of standard gas samples and using these

standards to build-up a mathematical model. In previous studies, [44], filling up the cell with

fractions of different gases in a batch mode was used to generate the standards. However, later

studies showed that this method is not very accurate for calibrating carbon dioxide [61]. The

problem is that spectrums taken from a fixed carbon dioxide-nitrogen mixture vary over time

(even after half an hour). This problem was more severe when carbon dioxide is first introduced

into the cell and then the nitrogen gas is added. Considering very low velocities of these gases in

the connection tubes (flows are laminar) and the difference between nitrogen and carbon dioxide

densities, it is suspected that mixing is not taking place quickly and as a result the mixture in the

cell is not uniform even after very long periods. Therefore, a continuous mixing process was

designed to overcome this problem and also oxygen sensor was used to verify the composition

of the gas entering the cell. This process is shown in Figure . Different gas mixtures of carbon

dioxide, oxygen and nitrogen are generated by using the needle valves and rotameters. Each

rotameter was calibrated beforehand for the specific gas (carbon dioxide, nitrogen or air) at the

correct pressure. The total flow rate of these gases after mixing is kept fixed at 15 SLPM.

Existence of elbows and long lines combined with a Reynolds number of approximately 4000,

guarantees close to full mixing of the gases before entering the FTIR and oxygen sensor.

Oxygen sensor flow rate as well as FTIR gas cell temperature and flow rate were all kept the

same as a normal test. The gas composition predicted by both oxygen sensor and FTIR showed

good agreement with the ones set by the rotameters. Although this method is promising in terms

of accuracy, one major drawback is the high consumption rate of expensive standard gases

compared to the batch method.

103

Figure F.1. Schematic of the carbon dioxide calibration setup

A National Instrument data acquisition card (model NI USB-9213) was used in this study to log

the temperatures and another card was used to control/ measure the DC signals (National

Instrument model NI USB-6229 BNC). The measured temperatures are: swirl box inlet, fuel

injection, nozzle sheath, port flange, exhaust flange, main exhaust heat exchanger outlet, main

cooling water inlet and outlet, swirl air direct, wet and dry PM line gases, and nozzle cooling

water outlet. The measured voltages are FID and oxygen sensor outputs. The only controlled

signal is solenoid valve activation voltage.

104

Appendix G

Data Acquisition System and a Sample of Recorded Data

105

Figure G.1. Front panel of the Labview program

106

Figure G.2. All temperatures logged testing batch W3

Figure G.3. Logged voltage signals when testing batch W3

Experimental Investigation of The Effects of Fuel ... · Liquid-Ethanol Blends in a Swirl Burner...

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