Fuel Property Effects on the Combustion Performance and Emissions

Aug 17, 2012 - Frank C. Lujaji , Akwasi A. Boateng , Mark A. Schaffer , Charles A. Mullen , Iddi ... Tommy Tzanetakis , Yashar Afarin , and Murray J. ...
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Fuel Property Effects on the Combustion Performance and Emissions of Hardwood-Derived Fast Pyrolysis Liquid-Ethanol Blends in a Swirl Burner Sina Moloodi, Tommy Tzanetakis, Brian Nguyen, Milad Zarghami-Tehran, Umer Khan, and Murray J. Thomson* Department of Mechanical and Industrial Engineering, University of Toronto, 5 King’s College Road, Toronto, Ontario M5S 3G8, Canada ABSTRACT: 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. Optimizing fuel properties to improve combustion is one way to solve this problem. There is currently limited information on the relationship between fuel properties and combustion performance and emissions of bio-oil. In this study, various hardwoodderived bio-oils with different fuel properties were tested in a pilot stabilized spray burner under the same flow conditions. The effect of solids, ash, and water contents of bio-oil as well as ethanol blending was examined. Steady-state gas phase and particulate matter emissions were measured. The results show that carbon monoxide and unburned hydrocarbon emissions correlate with the solids and ash fractions of bio-oil. Carbon monoxide and unburned hydrocarbon emissions decrease with both higher water and ethanol contents. Increasing the volatile content of fuel by blending in ethanol is shown to improve flame stability. The fraction of fuel nitrogen that is converted to nitrogen oxide emissions decreases with an increasing fuel nitrogen content. Also, the organic fraction of particulate matter emissions is found to be a strong function of the thermogravimetric analysis residue of the fuel. A conceptual model for bio-oil combustion is proposed that relates the fuel properties to the emissions.

1. INTRODUCTION The world’s energy consumption is rising steadily, and renewable energy from sustainable biomass resources is one way to meet this demand.1 Biomass can be converted into liquid biofuels to improve its transportation and handling. One such liquid biofuel is bio-oil, which is produced by a process called fast pyrolysis. This process converts biomass into a liquid by cracking the large molecules in a moderate-temperature reactor and then condensing the output vapors.2 This fuel is currently used primarily for generating heat in large-scale boilers.3 There are many different types of reactor configurations used to produce bio-oil. These include fluidized-bed reactors,4,5 transport and circulating fluidized-bed reactors,6 rotating cone reactors,7 ablative reactors,8 auger reactors,9 and conical spouted bed reactors.10,11 Each of these reactor designs achieves the basic principles of fast pyrolysis in a different way, leading to variation in liquid yields and final bio-oil fuel properties. Bio-oil is typically a dark-brown viscous liquid, which is a microemulsion of relatively large pyrolytic lignin molecules suspended in an aqueous solution of low-molecular-weight oxygenated compounds.2,12 Water, acids, alcohols, and mostly polar compounds form the continuous aqueous phase in the microemulsion. Water-insoluble compounds form an oily fraction dispersed in the water-soluble fraction by hydrogen bonding in micelles.12 The most abundant single component in bio-oil is water. The mass fraction of water is normally 10− 35%. The water content of bio-oil can be controlled to a certain extent by changing the moisture content of the biomass fed into the reactor. © 2012 American Chemical Society

Solid particles, which consist mostly of organic char particles leftover from the pyrolysis process, are another important constituent of bio-oil. These solid particles, referred to here as primary char particles, are problematic in atomizing nozzles because of their erosion and clogging potential. The effect of solids content on the combustion behavior of bio-oil was investigated by Shaddix et al.13 The study concluded that solid particles can accelerate the microexplosion process by acting as nucleation sites for heterogeneous boiling. However, these early microexplosions are not very effective at shattering the parent bio-oil droplet. From a combustion application point of view, the ash content is another important parameter for bio-oil. Most of the ash initially resides within the primary char particles and the oily fraction of bio-oil.14 Over time, however, inorganic ions can also leach into the aqueous, polar phase of the liquid. Even with complete combustion, ash in bio-oil has a detrimental effect on thermal conversion devices because it can erode turbine blades or deposit on the heat-transfer surfaces of boilers.12 Bio-oil consists of components with different boiling points, and the distribution of these boiling points is very important in a spray combustor. In contrast to diesel and light hydrocarbon fuels, bio-oil also contains a non-distillable fraction.12,15 In previous work, thermogravimetric analysis (TGA) has been used as a tool to monitor the different stages of droplet evaporation and combustion.15 A TGA test is performed by continuously measuring the mass of a bio-oil sample while Received: April 18, 2012 Revised: July 26, 2012 Published: August 17, 2012 5452

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Table 1. Fuel Properties of Burner Test Batches label ASTM method E25 E20 E15 E10 E5 S1 S2 S3 S4 S5 S6 W1 W2 W3 W4 E0f

HHV (MJ/kg)

C−H−N (mass %)

TGA residue (wt %)

kinematic viscosity (cSt)a

ethanol volume (vol %)

water (wt %)

4809

5291

N/A

445

N/A

E203

18.46 17.93 17.41 16.90 16.41 18.98e 18.68e 19.24e 19.38e 17.44 17.44 21.48 19.46 17.36 22.17 15.94

40.8−9.0−0.07 40.3−8.8−0.07 39.7−8.6−0.07 39.2−8.4−0.07 38.7−8.2−0.08 45.0−7.9−0.19 44.8−7.8−0.21 45.3−8.0−0.16 45.9−7.9−0.16 39.9−8.3−0.12 39.7−8.3−0.12 50.6−7.2−0.11 45.5−7.9−0.13 40.1−8.2−0.11 50.3−7.8−0.09 38.3−8.0−0.08

14.51c 15.21 15.89c 16.54c 17.18c 15.05 19.00 15.37 19.73 14.70 14.91 21.59 19.13 15.83 18.90c 18.08

1.8325d 2.2 2.5675d 2.935d 3.3025d 4.294 4.391 4.049 4.106 3.02 2.97 13.34 5.65 3.03 6.57 3.673

25 20 15 10 5 15 15 15 15 15 15 15 15 15 28 0

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 27.6

solids (wt %) MeOH−DCM insolublesb 0.057 0.060 0.063 0.065 0.068 0.081 0.089 0.839 2.217 0.054 0.054 0.054 0.045 0.027 0.047 0.070

ash (wt %) 482 0.049 0.051 0.054 0.056 0.058 0.027 0.223 0.241 0.294 0.036 0.054 0.000 0.009 0.000 0.000 0.060

Measured or calculated at the fuel injection temperature (approximately 80 °C in all cases). bMethanol−dichloromethane (MeOH−DCM) insolubles consist mostly of organic primary char particles. cCalculated from the measured TGA of E0, E20 or W1 assuming that ethanol addition has only a dilution effect on the residue.33 dLinearly interpolated or extrapolated from the measured values of E0 and E20 at 80 °C. eCalculated on the basis of the measured atomic composition of fuel using eq 1. fThe test with 100% pure bio-oil (E0) was run at slightly different burner conditions (see Table 2 and section 3.3 for discussion). a

increasing its temperature to a certain point under a controlled atmosphere and heating rate. At approximately 600 °C, the mass loss rate decreases significantly and visual observations show sample swelling and formation of a solid residue. The amount of solid residue remaining from different bio-oils is reported to be 25−39 wt % and is named the “TGA residue” in this paper. Although the TGA residue is formed at a lower heating rate than that which would typically be encountered in a flame, previous work has suggested that it still acts as a good indicator of the solid residue forming or coking potential of droplets undergoing combustion.16 Similar evaporative behavior has been observed when TGA is performed under either a nitrogen or an air atmosphere.17 Fundamental single-droplet combustion experiments can be used to shed some light on the spray combustion behavior of bio-oil.18 After ignition, volatile compounds evaporate from the droplet surface and burn in a quiescent spherical blue flame. As volatile materials continue to evaporate from the surface, an outer layer is left containing mostly viscous, heavy-molecularweight compounds that have polymerized to form a hardened shell structure around the droplet.19 Eventually, the flame extinguishes, and a porous cenosphere remains from the original droplet. At this stage, the particle burns relatively slowly in a solid-phase combustion mode similar to that exhibited by coal particles. The combustion stages of bio-oil can also be qualitatively studied by TGA. One important feature implied from TGA is the high temperature and long time requirements for carbonaceous residue (CR) burnout.15 This can explain some of the problems encountered when implementing bio-oil in combustion devices designed for fully evaporative fuels and with relatively short residence times, such as diesel engines and gas turbines. Several prior studies have investigated the potential for using bio-oil in small (kW) to large (MW) scale heat and power systems, such as boilers, diesel engines, and gas turbines.20−31

The technical challenges associated with displacing conventional hydrocarbon fuels with bio-oil in these applications include poor ignition quality, rapid injector clogging from solids and polymerized material, significant residue formation and coke deposition within the combustion chamber, and hot alkali corrosion from ash in the fuel. Most studies that investigate small-scale burners and large-scale stationary diesel or gas turbine engines (i.e., devices with short residence times) report higher unburned hydrocarbon, carbon monoxide, and particulate matter emissions when using bio-oil instead of the original design fuel. There are two ways of addressing the technical challenges and high emissions: one is through combustor design modification, and the other is through bio-oil optimization. The latter is the focus of this study because there is limited literature regarding the detailed effects of bio-oil properties on the combustion performance in a spray burner. Such information would provide guidelines for bio-oil producers in terms of making the optimal fuel for small-scale burners. It would also shed some light on how bio-oil optimization could solve the emissions problems encountered in higher efficiency power generation systems that have inherently short residence times, including gas turbines and diesel engines. The primary objective of this study is to investigate the effects of fuel properties on the combustion performance and emissions of hardwood-derived bio-oil and explain the results by considering the fundamental bio-oil combustion processes. The bio-oil fuel properties considered here are those that can be controlled by adjusting the production process: solids, ash, and water contents. The effect of ethanol addition is also studied because it has been reported as a simple upgrading method for improving the fuel quality of bio-oil.28,29 Besides improving combustion stability and reducing emissions, ethanol addition improves the homogeneity, decreases the viscosity and density, lowers the flash point, and increases the heating value of bio-oil.32 The addition of alcohol also significantly delays the 5453

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Table 2. Burner Operating Conditions for Test Batchesa label

adiabatic flame T (K)

total exhaust flow (SLPM)

swirl air T (°C)

swirl air flow (SLPM)

atomizing air flow (SLPM)

equivalence ratio

fuel flow (kg/min)

SMD (μm)

E25 E20 E15 E10 E5 S1 S2 S3 S4 S5 S6 W1 W2 W3 W4 E0

2171 2161 2151 2141 2130 2206 2197 2210 2214 2186 2195 2332 2241 2178 2332 2119

309 308 311 309 312 302 314 310 309 304 302 301 303 308 301 277

325.1 328.2 326.1 329.5 326.1 326.5 320.0 322.2 326.9 337.4 334.9 322.6 328.1 332.2 324.5 368.1

250.4 247.8 249.6 246.8 249.6 249.2 254.7 252.8 248.9 240.5 242.5 252.5 247.9 244.6 250.9 219.0

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

0.62 0.63 0.62 0.63 0.63 0.62 0.62 0.62 0.63 0.63 0.62 0.60 0.62 0.63 0.60 0.72

0.0360 0.0370 0.0383 0.0394 0.0407 0.0345 0.0354 0.0342 0.0337 0.0381 0.0378 0.0300 0.0336 0.0385 0.0291 0.0418

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 99.0

All tests were performed at a maximum swirl number of 5.4, with a stoichiometric CH4−O2 pilot flame operating at 0.5 kW, a primary air preheat power input of 1.5 kW, and a fuel flow rate scaled to provide 10 kW of energy input to the burner. a

were calculated using a formula suggested by Demirbas et al.34,35 for lignocellulosic biomass fuels based on their ultimate analysis

aging rate of bio-oil or its natural tendency to change composition, become more viscous, and lose volatility over time.32 Although the focus of this work is on wood-derived pyrolysis liquids, the core parameters being considered, such as ash content and TGA residue, are common to many types of bio-oil produced from a wide variety of feedstock types. However, future work will still be needed to ascertain if the same observed trends are applicable to non-wood-based biooils.

HHV = 33.5[C] + 142.3[H] − 15.4[O] − 14.5[N]

(1)

where [C], [H], [O], and [N] are the carbon, hydrogen, oxygen, and nitrogen mass fraction in the dry, ash-free fuel, respectively. The HHVs calculated from this formula were compared to measured values for several similar bio-oil batches from the same producer. The average error in the heating value prediction was only 2.5%, with a standard deviation of 1.38%. This comparison demonstrates that eq 1 can be used to reliably calculate the HHV of wood-derived biomass pyrolysis liquids in this study. 2.2. Bio-oil Burner. In this section, the 10 kW bio-oil burner is only very briefly described. Details regarding the burner assembly and system design are provided in prior publications.29−31 Primary combustion air first passes through a 1.5 kW electric heater, which increases its temperature to approximately 300 °C. The air then flows through a swirl generator, which can vary the theoretical swirl number between 0 and 5.4 before entering the main combustion chamber. All tests were carried out using the maximum swirl number of 5.4. An internal-mixing air-blast nozzle is used to atomize the fuel. The tip has six symmetrically arranged discharge orifices, 0.89 mm in diameter, which create a spray pattern with a quiescent core and a total angle of about 65°. At the location of the nozzle tip, the burner opens up into a diffuser section with a half angle of 35°. The throat diameter of the diffuser is 130 mm, and the final burner diameter is 221 mm. The inside of the burner is without a refractory lining. A premixed methane−oxygen torch operating at stoichiometric conditions and with a total power input of 0.5 kW is used to ignite the bio-oil spray. It also acts as a continuously stabilizing pilot flame during combustion. The bio-oil flames are normally anchored to the partially premixed region of fuel and air just downstream of the nozzle tip. Droplet size plays a very important role in spray combustion systems. The Sauter mean diameter (SMD) can be used to compare the atomization quality between the various test cases run in the burner. A non-dimensional relationship for air-blast atomizers was thus selected to estimate the SMD for the different fuel batches considered36

2. EXPERIMENTAL SECTION 2.1. Fuel Analysis. The fuel properties of each tested batch are given in Table 1. The methods for measuring the heating value, chemical composition, viscosity, and water, solids, and ash contents are also provided in the table and were chosen on the basis of previously recommended techniques for bio-oil in the literature.29 The TGA tests were performed by heating a small (∼20 mg) sample of fuel to 600 °C under a nitrogen atmosphere at a constant rate of 10 °C/min. To study the specific effects of ash, solids, water, and ethanol contents on bio-oil combustion, a series of tests were performed that considered the variation of one parameter while keeping all other parameters as constant as possible. To improve combustion stability, which has been found to be a problem with smaller burners,29,30 most bio-oil batches were mixed with 15% volumetric ethanol. Each section of Table 1 belongs to a separate series of tests that is labeled with the primary fuel parameter being varied: ethanol (E), solids/ash (S), and water (W). The values in the table represent the fuel properties of the mixtures that were burned in the combustion chamber and, thus, already account for the effect of ethanol addition/dilution. The ethanol batches E5−E25 were all created from the same parent fuel batch E0. As a result, only some of the properties of these batches were measured, whereas others were estimated. The TGA residue of batches E5, E10, E15, and E25 were all calculated from the measured TGA residue of E0 and E20. The calculation is based on the observation that ethanol addition has only a dilution effect on the TGA residue.33 The viscosity of these four batches was also estimated using linear interpolation or extrapolation of the measured viscosity of E0 and E20 at 80 °C (the fuel injection temperature). The higher heating value (HHV) of all bio-oil batches (except S1− S4) was measured prior to testing to determine the fuel flow rate corresponding to 10 kW operation. Therefore, the tests were run based on equivalent energy throughput. The HHV of batches S1−S4

0.4 ⎛ σ ⎞0.4 ⎛ SMD 1 ⎟⎞ ⎟ ⎜1 + = 0.48⎜⎜ 2 ⎟ ⎝ do ALR ⎠ ⎝ ρA UR do ⎠

⎛ μ 2 ⎞⎛ 1 ⎟⎞ + 0.15⎜⎜ L ⎟⎟⎜1 + ⎝ ⎠ σρ d ALR ⎝ L o⎠ 5454

(2)

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where σ is the surface tension, ρA and ρL are the air and liquid densities, respectively, UR is the relative velocity between the air and liquid, and do is the discharge orifice diameter. It is easy to identify the three main dimensionless numbers dominating the SMD: the inverse Weber number (σ/ρAUR2do), air/liquid mass flow rate ratio (ALR), and Ohnesorge number (μL2/σρLdo). Although bio-oil is considered a microemulsion, a previous rheological study has shown that similar pyrolysis liquid samples with high primary char content and inhomogeneous microstructure exhibit Newtonian behavior at high strain rates and temperatures up to 80 °C.37 Therefore, it is reasonable to use this standard SMD correlation to estimate and compare mean bio-oil droplet sizes between test cases. The SMD for each case is given in Table 2. One effect not accounted for using a simple SMD correlation to describe spray quality is the variation in droplet size distribution. It is possible to have two sprays with the same SMD and a different percentage of larger drops. However, for air-blast atomizers, droplet size distribution as well as other external spray characteristics, such as spray angle, are governed primarily by the velocity of air.36 Because the atomizing air flow rate is kept constant (see Table 2), it is assumed that any differences in the droplet size distribution or spray angle are relatively small. Another important parameter that can account for observed differences in combustion quality and emissions in spray flames is the adiabatic flame temperature. This is especially true when investigating the effect of varying the water content in bio-oil. The adiabatic flame temperature is calculated using the HHV and chemical composition of the fuel batches listed in Table 1. It is assumed that combustion is complete (i.e., no dissociation), the process occurs at atmospheric pressure, and the reactants are all initially at 298 K. The final flame temperature values are also provided in Table 2, along with other test parameters, including important flow rates and overall equivalence ratio. Note that the burner conditions were kept as constant as possible to ensure a true comparison of fuel property effects. 2.3. Gas-Phase Species Measurements. The measured gasphase pollutants considered here are total unburned hydrocarbons (UHCs), CO, and nitrogen oxides (NOx). To measure these species as well as the equivalence ratio, a system consisting of a heated sample line, a heated filter, a flame ionization detector (FID), a Fourier transform infrared (FTIR) spectrometer, and an oxygen sensor was used. The equivalence ratio for each test was back-calculated using the measured O2 in the exhaust. The UHC and exhaust O2 values were continuously monitored using a 0−5 V direct-current (DC) analog output signal from the FID and oxygen sensor, respectively. CO and NOx emissions were acquired by taking an average of five consecutive infrared spectra from the FTIR spectrometer at steady-state burner operating conditions. Further details regarding the experimental system and the methodologies employed have been described in previous work.29,30 2.4. Particulate Matter (PM) Measurement. Particulates were collected using an isokinetic sampling system placed in the burner exhaust. Details about the design of the system as well as the uncertainty analysis employed in the PM measurement are provided elsewhere.17,30 The PM was deposited on 47 mm borosilicate filters (Tissuquartz, product number 7202 from Pall Life Sciences) with an aerosol retention efficiency of 99.9% at 0.3 μm. The filters are made of pure quartz microfibers without any binding material and are therefore able to withstand temperatures up to 1100 °C. To separate the amounts of water, ash, and unburned or partially burned CR fractions in the PM, a standard method called “loss on ignition” [American Society for Testing and Materials (ASTM) D4422-03] was used.38 In this test, the PM collected on the filters is first dried and then burned in a Thermo Scientific Thermolyne EW-33900-03 muffle furnace at 750 °C. The leftover material is considered to be ash. The inherent assumption here is that the material on the filters consists only of water, CR, and ash and that, by performing gravimetric analysis between each stage of the test, the amount of each fraction can be quantified.17,30 Figure 1 shows the various steps and weight measurements made during the loss on ignition method. Each weight

Figure 1. Loss on ignition gravimetric analysis method.

measurement (labeled M1−M4) was carried out 3 times consecutively on a Scientech SM-128D microbalance to take an average from the data and perform an appropriate uncertainty analysis. 2.5. Test Procedure. The optimal operating conditions for the burner, including equivalence ratio and atomizing air flow rate, were determined in a previous study on the same burner.29 This operating condition, named the base point condition, is summarized in the notes of Table 2. As previously mentioned, the operating conditions for each individual test are also provided in Table 2. At the beginning of each test, the burner is run with pure ethanol for the first 15 min to warm up the combustion chamber. The fuel line is then switched over to the appropriate bio-oil/ethanol batch, reaching stable operation at about the 25 min mark. At this point, the particulate sampling procedure is started. The PM sampling for one filter lasts 5 min, and two successive filters are usually collected. FTIR sampling for CO and NOx emissions begins at about the 55 min mark and lasts until the 60−65 min mark. As previously mentioned, five consecutive spectra are usually taken, the results of which are averaged in the analysis. The UHC emissions reported are averaged over a 5 min window when the exhaust oxygen concentration is very stable, usually just prior to FTIR sampling in the timeline. All of the CO, NOx, UHC, and CR emissions from this study are summarized in Table 3.

Table 3. Summary of Emissions for All Test Batches label

CO (mg/MJ)

UHC (ppm)a

NOx (ppm)a

NOx conversion ratio (%)b

CR (mg/kg of fuel)

E25 E20 E15 E10 E5 S1 S2 S3 S4 S5 S6 W1 W2 W3 W4 E0

303.7 382.1 605.4 702.4 750.3 202.9 498.0 573.9 1151.7 349.9 775.8 575.6 266.0 186.3 157.4 1207.5

25 25 70 70 85 45 78 171 299 94 214 >300c 220 33 79 >300c

167 193 176 159 192 133 183 173 154 125 129 57 82 92 111 157

92 103 85 68 84 23 34 41 35 30 30 4 14 19 40 53

155.0 160.0 174.4 173.0 248.0 125.1 185.5 199.4 492.4 257.1 205.6 359.8 567.5 153.7 526.7 255.0

a Values were corrected to a total exhaust flow rate of 310 SLPM. bFuel NOx was calculated assuming 50 ppm of thermal NOx in measured data.29 cFID reading was saturated at the time of measurement.

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3. RESULTS AND DISCUSSION 3.1. Conceptual Model for Bio-oil Combustion. Figure 2 shows the proposed conceptual stages for bio-oil droplet

the mass of the secondary char particle (or TGA residue), the higher the amount of CO and UHC emissions. It is important to note that this conceptual model is a simplified version of the droplet combustion process in spray flames with a sharp boundary between two distinct stages. Although there may be some overlap in these stages (i.e., some simultaneous evaporation of heavier compounds and cracking), the goal of the model is to outline the most dominant physical processes that lead to the observed emissions. Given this, there are some other important mechanisms that could be contributing to emissions in addition to the quenching of secondary char particle burnout. In particular, flame or gaseous reaction quenching can also lead to significant CO and UHC emissions. In fact, it has been previously discussed that the small scale (short residence time), lack of refractory lining, and high heat losses of the current system are responsible for the relatively high UHC and CO emissions compared to larger scale burner systems.29,31 This phenomenon is responsible for the high baseline in these emissions, but as the subsequent data analysis indicates, the observed differences in UHC and CO correlate very strongly with the differences in solids, ash, water, ethanol, and TGA residue among the various bio-oil batches. 3.2. Ethanol Addition. Previous studies using the same burner and experimental setup described in this work were all conducted with fixed 80:20 volumetric bio-oil/ethanol blends.29,30 The reason for this blending was to achieve stable combustion performance over a wide range of burner operating conditions. To investigate the effect of ethanol addition on combustion, a parent batch of bio-oil (E0) was mixed with different percentages of ethanol and each batch was tested under the same burner operating conditions (tests E25−E5). The trends observed here were expected to be similar to increasing the volatile fraction of the parent bio-oil via further thermal cracking or reduction of the condensation temperature during the pyrolysis production process.41 Looking at Table 2, the estimated SMD for all of the ethanol tests are very similar. Previous work on bio-oil droplet combustion has also indicated that ethanol addition does not improve the effectiveness of microexplosion fragmentation;13 thus, there are not likely to be any secondary atomization effects associated with changing the additive content. Therefore, any differences in the observed emissions should be mostly due to differences in the ethanol content and not the spray quality. As seen in Table 1, ethanol addition decreases the TGA residue of a given fuel batch by simple dilution. It is expected that the secondary char mass fraction that forms within the spray droplets during combustion should also decrease, leading to less heterogeneous particle combustion. As discussed in the conceptual model, the second stage of bio-oil combustion or secondary char particle burnout happens primarily outside of the spray flame where lower temperatures lead to reaction quenching. This mechanism is responsible for most of the emission differences observed between the batches. Reduced char particle burnout should therefore lead to lower CO, UHC, and CR emissions, and Table 3 shows that this is indeed the case. Therefore, consistent with the proposed conceptual model, the decrease in the TGA residue via ethanol dilution corresponds to a decrease in all of the measured emissions. The detailed effect of ethanol on CR emissions is shown in Figure 3. The data are normalized to the mass fraction of bio-oil in the blend to remove the effect of ethanol dilution on the results, unlike the data in Table 3. This graph shows that, between 10 and 25%, ethanol addition to bio-oil has no

Figure 2. Conceptual model for bio-oil droplet combustion.

combustion in spray flames based on the observed experimental trends of this study and the current understanding as it exists in the literature.18,39 In the first stage, water and other volatile compounds evaporate from the droplet surface and burn in a homogeneous combustion mode, forming an envelope flame around a droplet. The particle that remains from the first stage contains mostly heavy-molecular-weight material (HMWM) that cannot evaporate quickly or that cannot evaporate at all. This residue, which may not yet be completely solidified, is referred to as a secondary char particle because it is formed during droplet combustion. In addition, the secondary char particle contains ash and other solid (primary char) particles. The secondary char particle burns in a heterogeneous combustion mode, which is eventually collected by the PM sampling filter in the burner exhaust. If the original droplet does not undergo complete combustion, the total PM that it contains will consist of both ash and solid CR. The TGA residue forms under a nitrogen atmosphere but, similar to secondary char, consists of ash, solids, and the material that has not evaporated at a very high temperature. As previously mentioned, this suggests that the TGA residue can act as an indicator of the secondary char formation potential of bio-oil during droplet combustion. Because the CR is formed from the secondary char, the hypothesis is that, despite the complicated chemical composition of bio-oil, CR emissions can be predicted on the basis of the solids content and the TGA residue. Measurements during bio-oil combustion at the base operating point estimate the temperature of the gas immediately downstream of the flame to be about 1000 K.29 On the basis of visual flame observations, it is evident that a large fraction of secondary char particles still burn in a region outside of the primary spray flame.31 According to Glassman, temperatures below 1100 K are not enough for complete oxidation of CO to CO2.40 In addition, on the basis of the results, UHC emissions closely follow the CO emissions. It is possible for UHC emissions to be generated during the heterogeneous combustion stage because the secondary char particles contain up to 5 wt % hydrogen along with fixed carbon.15 The char particles are burning in an oxygen-limited environment, which can lead to fuel cracking, quenching, and UHC emissions. These observations and considerations therefore lead to another part of the hypothesis, which states that the CO and UHC emissions are both mostly formed during the second combustion stage. In other words, the higher 5456

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3.4. Solids and Ash Contents. Batches S1−S6 were tested to investigate the effects of solids and ash contents. The data from Tables 1 and 2 indicate that batches S1−S4 have very similar water and ethanol contents and SMD. Also, the solid primary char particles in the fuel are not likely to significantly affect atomization quality because their characteristic size is generally less than 10 μm,17 which is much less than the predicted SMD of around 75 μm. Therefore, any trends in the emissions can be primarily attributed to the differences in solids, ash, and TGA residues of these fuels. Batches S2, S3, and S4 can shed some light on the isolated effect of solids or primary char particles, because they all have very similar ash content. As seen in Table 3, the CO, UHC, and CR emissions all generally increase with an increasing solids content for these batches. This trend can be explained using the suggested conceptual model. The solid primary particles eventually have to burn in the second or heterogeneous combustion stage and are therefore more likely to generate higher CO, UHC, and CR emissions. However, the observed increase in emissions between the batches is not linear, and some special cases can help explain these results. Batches S2 and S3 have an order of magnitude difference in solids content, but a statistically insignificant difference in CR emissions (see Table 3). The parameter that seems to be counteracting the effect of high solids content in S3 is its 23% decrease in TGA residue compared to S2. As discussed in the conceptual model, both TGA residue and solids play an important role in CR formation. It is physically plausible for a fuel with low solids to have a higher TGA residue than one with high solids because the polymerization of lighter compounds into heavier compounds contributes to secondary char formation as well.12 Another special case to consider is the large increase in all emissions from batch S3 to S4. In addition to a large increase in the solids content, batch S4 also has a significantly higher TGA residue. The higher TGA residue contributes to secondary char formation and thus higher CO, UHC, and CR emissions. The higher ash content may also have an independent effect. When S1 and S2 are compared, the solids content is almost the same for both; therefore, the jump in the gas-phase emissions can be attributed to an order of magnitude increase in ash as well as the increase in the TGA residue. To confirm the existence of an independent trend, tests S5 and S6 were conducted where all of the parameters for both fuel batches were approximately the same, except for the ash content. The CO and UHC of batch S6 were approximately doubled with respect to S5, suggesting the existence of an independent ash effect on gas-phase emissions. The ash in bio-oil contains various alkali metals, including potassium compounds,30 which are reported to have an accelerating effect on the gasification of coal particles.43 Therefore, the ash could be catalytically accelerating the gasification of CR during the second combustion stage. This explanation is also consistent with the lower CR emissions of S6 compared to S5 (i.e., the conversion of CR into CO and UHC). From a practical point of view, techniques such as hot gas filtration or other methods of solid separation from pyrolysis vapors can decrease the solids and ash contents during the fast pyrolysis process,44 thereby reducing gaseous combustion emissions. 3.5. Water Content. The addition of water to bio-oil increases droplet evaporation time because of its high latent heat of vaporization, slows gas-phase combustion reactions, and decreases the adiabatic flame temperature.41 On the other hand,

Figure 3. Normalized CR emission index versus ethanol content in bio-oil.

significant effect on the organic portion of PM other than dilution. This is consistent with observations in heavy fuel oil droplet studies, where the addition of lighter fuel oil to residual oil only has a dilution effect on the formation of coke particles.42 These results suggest that the CR is a strong function of the amount of HMWM or TGA residue within the fuel. The ethanol dilution effect on CR is also consistent with the conceptual combustion model. Consider that, for an individual droplet, the oxidation of CR happens in the second stage of combustion, which is likely to take place outside of the main flame sheet, even for high concentrations of ethanol.17 On the other hand, volatile ethanol is expected to participate in the first stage of combustion and should not have a significant effect on CR oxidation. In summary, the higher the ethanol or volatile fraction in the bio-oil, the higher the dilution of the TGA residue and the lower the UHC, CO, and CR emissions. 3.3. Pure Bio-oil Combustion. Pure bio-oil (label E0) was also tested at the base operating condition, but the flame was blown out before any data collection could proceed. Pure biooil and batch E5 behaved different from the rest of the ethanol study batches because of their inherent combustion instability. The partially premixed region of the spray close to the nozzle and pilot plays an important role in stabilizing the flame. Visual observations show that flame lift-off from this anchoring point increases as the ethanol content decreases.17 This lift-off is a result of longer droplet evaporation time and the narrower flammability limits of bio-oil relative to ethanol.29 Both E5 and pure bio-oil showed a relatively large lift-off combined with combustion chamber pressure fluctuations during the first several minutes after the ethanol warm-up. In Figure 3, the jump in CR emissions when ethanol decreases from 10 to 5% can therefore be attributed to the contribution from flame instability. These instabilities are fluctuations in heat release and steady burning, which correspond to local, instantaneous blowouts and the extinguishing of droplet combustion. These results indicate that, for this burner, at least 10% ethanol is required to stabilize the flame close to the nozzle and avoid blow-out. Understanding the blow-out and instability mechanism of the ethanol batches helped in finding a more suitable condition for burning pure bio-oil. To decrease flame lift-off and improve stability, both the atomizing air and primary combustion air were decreased, resulting in slightly different operating parameters for E0 (see Table 2). Although these changes proved to enhance the stability, previous work has shown that deviations from the base point 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.29,30 5457

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removing water can make the fuel very viscous and reduce the likelihood of effective microexplosions,13 both of which degrade atomization quality. To see which group of these mechanisms is more dominant in a spray combustion system, tests on batches W1, W2, W3, and W4 were performed. These batches all had very low and similar solids and ash contents. Results of TGA show that water has only a dilution effect on these residues.17 As shown in Table 3, the batch with the highest amount of water has the lowest emissions. Batch W1 was extremely viscous, and there is a significant difference between the calculated SMD of W1 and those of the other batches. Visual observations of burner operation with W1 showed unsteady combustion and many fuel droplets accumulating on internal burner surfaces before burning out. As a result of this, some flames along the internal walls of the combustion chamber were observed. This behavior is primarily due to the higher SMD and thus longer droplet evaporation time of W1 compared to the other water batches. The reported CR emissions for W1 are lower than W2 but should not be considered indicative because of the aforementioned droplet wall deposition phenomenon. The main effect of water can be isolated by comparing W2 and W3 because they both have a very similar SMD and relatively low solids and near zero ash contents. The only major difference between W2 and W3 is thus the difference in the TGA residue, which is essentially due to water dilution.17 Considering the conceptual combustion model, the higher TGA residue of W2 corresponds to a higher mass of secondary char, which is, in turn, responsible for its higher CO, UHC, and CR emissions compared to W3. This is true even when normalizing the emissions to mg/MJ to account for the difference in the fuel flow rate because of the disparity in heating values between these batches (see Table 3 for CO; CR emissions are 31.75 and 9.86 mg/MJ for W2 and W3, respectively). The TGA residue effect therefore seems to dominate over the expected combustion benefits in evaporation time, chemical kinetics, and flame temperature associated with a lower water content. The lowest emission bio-oil blend among all of the batches tested in this study was W3. The high water content of this batch definitely plays an important role by enhancing the atomization compared to W1 and lowering the TGA residue compared to W2. To further investigate the effect of the 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 as 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). The water−ethanol mixture was added until the Zahn cup viscosity of the newly created batch (W4) was close to that of W3. The SMD of both batches is very similar, and although W4 has much more ethanol (see Tables 1 and 2), Figure 4 indicates that the UHC, CO, and CR of W4 are similar or higher than those of W3. Once again, this can be attributed to the higher TGA residue of W4 because more secondary char is generated, leading to higher emissions. Overall, increasing the water content of bio-oil decreases the emissions through two parallel mechanisms: (i) decreasing viscosity and thus improving atomization and (ii) decreasing the TGA residue and thus secondary char formation. It is important to note that the amount of water in bio-oil cannot be increased indefinitely. Assuming that a stable bio-oil

Figure 4. Comparison of TGA and emissions for batches W3 and W4.

mixture is achievable at very high water contents (>30 wt %), the heating value and heat release rates of the fuel would eventually become too low to sustain a stable spray flame, even with the given pilot torch system. Unfortunately, it was not possible to determine this upper limit in the current study because the highest water content batch (W3) exhibited the best flame stability and lowest emissions. An attempt was made to investigate higher moisture content batches by adding water to W3. However, this led to aqueous/oily fraction separation of the fuel sample. On the other hand, there were already noticeable problems with flame stability at the lowest water content considered (8.9 wt %, batch W1); therefore, even lower moisture contents were not investigated. 3.6. NOx Emissions for Bio-oil Blends. Previous studies on bio-oil have one common conclusion related to NOx emissions: fuel NOx is the dominant formation mechanism.29,45 The ratio of fuel NOx to the total NOx that would be produced if all of the nitrogen in the fuel was converted is referred to here as the nitrogen or NOx conversion ratio.. For different types of fuels, including coal and heavy fuel oil, this ratio has been shown to decrease as the nitrogen in the fuel increases.46 The NOx values reported in Table 3 are the total measured emissions, which include contributions from both fuel and thermal NOx. The conversion ratio for each fuel batch has also been compiled in Table 3 and plotted in Figure 5. However, the

Figure 5. NOx conversion ratios for all bio-oil batches.

measured NOx values used in the calculation of the conversion ratio have been corrected for thermal NOx (i.e., fuel NOx = measured NOx − thermal NOx). In previous work, the thermal NOx emissions of 80:20 bio-oil/ethanol volumetric blends under similar burner operating conditions have been estimated to be only 50 ppm.29 The value is low because the combustion chamber in this particular setup is relatively cool. Applying the 50 ppm correction to all of the measured NOx emissions leads to a maximum conversion ratio in the data of approximately 5458

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100%. Figure 5 shows that bio-oil exhibits the same conversion ratio trend as other nitrogen-containing fossil fuels. 3.7. Linear Regression Model for the CR Emission Index. Results from the water, ethanol, and solids/ash tests indicate that, except for batches E5 and W1, which exhibited poor atomization quality and flame stability, CR emissions tend to increase with the TGA residue and solids content of the fuel. These findings can be explained using the conceptual bio-oil combustion model because both the HMWM and solids contribute to the formation of secondary char, the precursor to CR. The actual measured TGA residue consists of HMWM and polymerized material, solids, and ash. Because ash is not a part of the CR, the (i) solids and (ii) HMWM and/or polymerized material within the droplets should be the most important contributors to the measured CR emissions. Statistically, the solids content and TGA residue of the fuel samples have a relatively low correlation coefficient (rxy = 0.36) and do not show a strong trend between one another. In comparison to the mass fraction of the TGA residue, the mass fractions of ash and solids are also typically 1 or 2 orders of magnitude lower. As a result, the TGA residue can effectively be treated as one independent variable (representing HMWM and polymerized material), while the solids or primary char mass fraction is treated as the other independent variable in the linear regression analysis. Before using regression analysis to investigate the relationship between CR, TGA residue, and solids, a correction was applied to the CR emission index of a few test batches. This was performed because deposition of PM on internal burner walls was not negligible for some cases. These cases were identified by noting that the amount of filter-collected ash was less than the ash measured in the fuel. 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 same filter. This ratio can be calculated by combining the ultimate analysis of fuel and the measured ash emission index. This ratio is called the collection efficiency, and because both ash and CR losses to the walls happen by the same PM deposition mechanism, it is reasonable to assume that the collection efficiencies of CR and ash are the same. Dividing the measured CR emissions index by the PM collection efficiency gives the corrected CR emissions index, which is then used for the regression analysis. The best fit was found when linear regression was applied to find the average CR emissions index as a function of the TGA residue and solids. It was assumed that both of the independent variables, the TGA residue and solids fraction, vary within a small enough range for the effects to all be linear. A formula was therefore fit to the available data with the following format:

Table 4. Linear Regression Model Parameters and Averages value 0.281 3.425 −2.079 0.958 0.28 16.52 395.4

what the normalized CR would be if both the solids content and TGA residue were 0. The β coefficient is about 12 times larger than α and indicates that the TGA residue is more important in determining CR emissions than the solids content. This means that, for burners with short residence times, reducing the TGA residue would be an important upgrading method for keeping CR emissions low. The coefficient γ theoretically corresponds to the normalized CR if both the solids content and TGA residue are 0. Because these values lie outside the range of applicability for the current regression analysis, the negative γ in Table 4 does not have a true physical meaning in the model. Figure 6 and the R2 value in Table 4 indicate that eq 3 provides a good fit to the experimental data.

Figure 6. Comparison of measured and modeled corrected CR emission indices.

An attempt was made to develop several other linear regression models for CO and UHC emissions with respect to different fuel input parameters. However, these models tended to yield R2 values of less than 0.8 and were therefore deemed inadequate. This is likely because the dependence of these emissions upon the fuel variables studied is not linear.

4. CONCLUSION The effects of solids, ash, water, and ethanol addition in various bio-oil mixtures were examined, and results from combustion diagnostics show trends that bio-oil producers can use to make the fuel more suitable for small-scale burners, diesel engines, or gas turbines. In addition, on the basis of the results, a conceptual model is proposed that describes the formation of pollutant emissions from bio-oil combustion. Results suggest that water removal from bio-oil does not improve combustion quality or lower emissions. This is mainly due to the fact that removing water increases the TGA residue and increases the viscosity of the fuel. CO and UHC emissions show a sensitivity to ash content, which may be due to the catalytic effect that alkali metals have in accelerating the gasification of secondary char particles. The addition of around 10% volumetric ethanol

⎛ solids (wt %) ⎞ CR ⎟⎟ = α⎜⎜ CR avg ⎝ solidsavg (wt %) ⎠ ⎛ TGA residue (wt %) ⎞ ⎟⎟ + γ + β ⎜⎜ ⎝ TGA residueavg (wt %) ⎠

regression model parameter α β γ R2 average solids (wt %) average TGA residue (wt %) average CR emissions (mg/kg of fuel)

(3)

Averages of CR, solids, and TGA residue are taken over all batches, except W1, E5, and E0 (which was run at different burner conditions). The fit coefficients are listed in Table 4 along with the calculated averages. Coefficients α and β show the significance of each independent variable, while γ indicates 5459

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(5) Heo, H. S.; Park, H. J.; Park, Y. K.; Ryu, C.; Suh, D. J.; Suh, Y. W.; Yim, J. H.; Kim, S. S. Bioresour. Technol. 2010, 101, S91−S96. (6) Oasmaa, A.; Solantausta, Y.; Arpiainen, V.; Kuoppala, E.; Sipilä, K. Energy Fuels 2010, 24, 1380−1388. (7) Venderbosch, R. H.; Prins, W. Biofuels, Bioprod. Biorefin. 2010, 4, 178−208. (8) Lédé, J.; Broust, F.; Ndiaye, F. T.; Ferrer, M. Fuel 2007, 86, 1800−1810. (9) Ingram, L.; Mohan, D.; Bricka, M.; Steele, P.; Strobel, D.; Crocker, D.; Mitchell, B.; Mohammad, J.; Cantrell, K.; Pittman, C. U. Energy Fuels 2008, 22, 614−625. (10) Amutio, M.; Lopez, G.; Aguado, R.; Artetxe, M.; Bilbao, J.; Olazar, M. Energy Fuels 2011, 25, 3950−3960. (11) Amutio, M.; Lopez, G.; Aguado, R.; Bilbao, J.; Olazar, M. Energy Fuels 2012, 26, 1353−1362. (12) Lu, Q.; Li, W.; Zhu, X. Energy Convers. Manage. 2009, 50, 1376− 1383. (13) Shaddix, C. R.; Tennison, P. J. Proc. Combust. Inst. 1998, 27, 1907−1914. (14) Elliott, D. C. Biomass Bioenergy 1994, 7, 179−185. (15) Branca, C.; Di Blasi, C.; Elefante, R. Ind. Eng. Chem. Res. 2005, 44, 799−810. (16) Garcìa-Pérez, M.; Lappas, P.; Hughes, P.; Dell, L.; Chaala, A.; Kretschmer, D.; Roy, C. IFRF Comb. J. 2006, No. 200601. (17) Moloodi, S. Experimental investigation of the effects of fuel properties on combustion performance and emissions of biomass fast pyrolysis liquid−ethanol blends in a swirl burner. M.A.Sc. Thesis, Department of Mechanical and Industrial Engineering, University of Toronto, Toronto, Canada, 2011. (18) Wornat, M. J.; Porter, B. G.; Yang, N. Y. C. Energy Fuels 1994, 8, 1131−1142. (19) Hallett, W. L. H.; Clark, N. A. Fuel 2006, 85, 532−544. (20) Huffman, D. R.; Vogiatzis, A. J.; Clarke, D. A. In Bio-oil Production and Utilization; Bridgwater, A. V., Hogan, E. H., Eds.; CPL Press: Newbury, U.K., 1996; pp 227−235. (21) Oasmaa, A.; Kytö, M.; Sipilä, K. In Progress in Thermochemical Biomass Conversion; Bridgwater, A. V., Ed.; Blackwell Science: Oxford, U.K., 2001; pp 1468−1481. (22) Shihadeh, A.; Lewis, P.; Manurung, R.; Beér, J. In Proceedings of the Biomass Pyrolysis Oil Properties and Combustion Meeting; Estes Park, CO, Sept 26−28, 1994; NREL-CP-430-7215, pp 281−295. (23) Gust, S. In Developments in Thermochemical Biomass Conversion; Bridgwater, A. V., Boocock, D. G. B., Eds.; Blackie Academic and Professional: London, U.K., 1997; pp 481−488. (24) Oasmaa, A.; Peacocke, C.; Gust, S.; Meier, D.; McLellan, R. Energy Fuels 2005, 19, 2155−2163. (25) Shihadeh, A.; Hochgreb, S. Energy Fuels 2000, 14, 260−274. (26) Czernik, S.; Bridgwater, A. V. Energy Fuels 2004, 18, 590−598. (27) Strenziok, R.; Hansen, U.; Künstner, H. In Progress in Thermochemical Biomass Conversion; Bridgwater, A. V., Ed.; Blackwell Science: Oxford, U.K., 2001; pp 1452−1458. (28) Krumdieck, S. P.; Daily, J. W. Combust. Sci. Technol. 1998, 134, 351−365. (29) Tzanetakis, T.; Farra, N.; Moloodi, S.; Lamont, W.; McGrath, A.; Thomson, M. J. Energy Fuels 2010, 24, 5331−5348. (30) Tzanetakis, T.; Moloodi, S.; Farra, N.; Nguyen, B.; Thomson, M. J. Energy Fuels 2011, 25, 1405−1422. (31) Tzanetakis, T.; Moloodi, S.; Farra, N.; Nguyen, B.; McGrath, A.; Thomson, M. J. Energy Fuels 2011, 25, 4305−4321. (32) Oasmaa, A.; Kuoppala, E.; Selin, J. F.; Gust, S.; Solantausta, Y. Energy Fuels 2004, 18, 1578−1583. (33) Tzanetakis, T. Spray combustion characteristics and emissions of a wood derived fast pyrolysis liquid−ethanol blend in a pilot stabilized swirl burner. Ph.D. Thesis, Department of Mechanical and Industrial Engineering, University of Toronto, Toronto, Canada, 2011. (34) Demirbas, A.; Gullu, D.; Gaglar, A.; Akdeniz, F. Energy Sources 1997, 19, 765−770. (35) Demirbas, A. Prog. Energy Combust. 2004, 30, 219−230.

to bio-oil is recommended to help with stabilizing combustion in short residence time systems, such as the one considered here. An alternative to this would be to increase the inherent volatility of bio-oil via hot gas filtration or to decrease the vapor condensation temperature during the production process. Among the batches studied with 15% ethanol addition, W3 and S1 have the lowest emissions. A low viscosity as a result of the relatively high water content, low levels of ash and solids contents, and low TGA residue all contribute to this result. The nitrogen to NOx conversion ratio for various bio-oil batches was also studied and showed a decrease with an increasing fuel nitrogen content. Finally, it was found that CR emissions correlate very strongly with the TGA residue and solids content of the fuel. Thus, TGA and solids content measurements are recommended as a tool for estimating the PM-generating potential of different bio-oils in a spray burner.

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AUTHOR INFORMATION

Corresponding Author

*Telephone: +1-416-580-3391. Fax: +1-416-978-7753. E-mail: [email protected]. Notes

The authors declare no competing financial interest.

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ACKNOWLEDGMENTS The authors thank the Natural Sciences and Engineering Research Council of Canada (NSERC), and Agriculture and Agri-Food Canada for funding this work.

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NOMENCLATURE ALR = air/liquid mass flow rate ratio (ṁ A/ṁ L) ASTM = American Society for Testing and Materials CR = carbonaceous residue DC = direct current DCM = dichloromethane FID = flame ionization detector FTIR = Fourier transform infrared (spectrometer) HHV = higher heating value (MJ/kg) HMWM = high-molecular-weight material MeOH = methanol NOx = nitrogen oxides (NO + NO2) PM = particulate matter ppm = parts per million volume SLPM = standard liters per minute SMD = Sauter mean diameter TGA = thermogravimetric analysis UHC = unburned hydrocarbon R2 = coefficient of determination UR = air/liquid relative velocity (m/s) do = nozzle discharge orifice diameter (m) μL = liquid viscosity (Pa s) ρA = air density (kg/m3) ρL = liquid (fuel) density (kg/m3) σ = surface tension (N/m)

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REFERENCES

(1) Ghoniem, A. F. Prog. Energy Combust. 2011, 37, 15−51. (2) Bridgwater, A. V. Chem. Eng. J. 2003, 91, 87−102. (3) Chiaramonti, D.; Oasmaa, A.; Solantausta, Y. Renewable Sustainable Energy Rev. 2007, 11, 1056−1086. (4) Boateng, A. A.; Daugaard, D. E.; Goldberg, N. M.; Hicks, K. B. Ind. Eng. Chem. Res. 2007, 46, 1891−1897. 5460

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Energy & Fuels

Article

(36) Lefebvre, A. H. Atomization and Sprays; Taylor and Francis: New York, 1989. (37) Tzanetakis, T.; Ashgriz, N.; James, D. F.; Thomson, M. J. Energy Fuels 2008, 22, 2725−2733. (38) Brown, R. C.; Dykstra, J. Fuel 1995, 74, 570−574. (39) Calabria, R.; Chiariello, F.; Massoli, P. Exp. Therm. Fluid Sci. 2007, 31, 413−420. (40) Glassman, I.; Yetter, R. A. Combustion, 4th ed.; Elsevier, Inc.: Amsterdam, The Netherlands, 2008. (41) Shihadeh, A.; Hochgreb, S. Energy Fuels 2002, 16, 552−561. (42) Marrone, N. J.; Kennedy, I. M.; Dryer, F. L. Combust. Sci. Technol. 1984, 36, 149−170. (43) Veraa, M. J.; Bell, A. T. Fuel 1978, 57, 194−200. (44) Oasmaa, A.; Czernik, S. Energy Fuels 1999, 13, 914−921. (45) Baxter, L. L.; Jenkins, B. M.; Winter, F. Baseline NOx Emissions during Combustion of Wood-Derived Pyrolysis Oils; Sandia National Laboratories: Livermore, CA, 1995; SAND94-8780. (46) Flagan, R. C.; Seinfeld, J. H. Fundamentals of Air Pollution Engineering; Prentice Hall: Englewood Cliffs, NJ, 1988.

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