Impacts of Alternative Fuels on Morphological and Nanostructural

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Energy and the Environment

Impacts of alternative fuels on morphological and nano-structural characteristics of soot emissions from an aviation piston engine Longfei Chen, Xuehuan Hu, Jing Wang, and Youxing Yu Environ. Sci. Technol., Just Accepted Manuscript • Publication Date (Web): 25 Mar 2019 Downloaded from http://pubs.acs.org on March 25, 2019

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Environmental Science & Technology

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Impacts of alternative fuels on morphological and nano-structural

2

characteristics of soot emissions from an aviation piston engine Longfei Chen,† Xuehuan Hu,† Jing Wang,,

3

4

† Department

5

‡

6

8093 Zurich, Switzerland

7

§

8

Science and Technology, 8600 Dübendorf, Switzerland

9

∥

‡, §,

Youxing Yu∥

of Energy and Power Engineering, Beihang University, 100083 Beijing, China

Institute of Environmental Engineering, ETH Zurich - Swiss Federal Institute of Technology Zurich,

Laboratory for Advanced Analytical Technologies, Empa - Swiss Federal Laboratories for Materials

Department of Materials Science and Engineering, Beihang University, 100083 Beijing, China

10

ABSTRACT:

Soot

emissions

from

11

aviation piston engines (APEs) are a major

12

source of environment pollutions in airport

13

vicinity, stratosphere and troposphere, and

14

their nano-structure and surface chemistry

15

play a critical role in determining the impact on human health and environment. In this work,

16

the morphology and nano-structure of soot emitted from an aviation piston engine burning five

17

different fuels including blends of promising alternative jet and biofuels were investigated via

18

high-resolution transmission electron microscopy (HRTEM) and Raman spectroscopy. The

19

graphitic structures were observed by analyzing primary particles in the HRTEM images.

20

Morphological analysis demonstrated that the separation distance of the graphene layers of soot 1 / 21

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particles from kerosene-pentanol blend combustion was larger than that from kerosene-Fischer-

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Tropsch blend combustion, indicating that adding pentanol tended to generate particles with

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more loosely stacked layers and higher oxidation tendency. Raman results were in agreement

24

with primary particle nano-structure analysis based on the HRTEM images. Furthermore, soot

25

particles from different fuels exhibited different concentrations of amorphous carbon and

26

structural defects.

27



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Aviation soot emissions have become a significant contributor to particulate matter (PM)

29

emissions in upper troposphere, lower stratosphere and airport areas 1. Ultrafine particles and

30

the secondary organic aerosols (SOA) from aircrafts are the dominant pollution sources in the

31

upper air and have direct consequences for haze weather 2. Furthermore, aircraft particle

32

emissions can cause ice nucleation for cloud formation, which affects solar radiative forcing 3

33

and thus could influence global climate pattern

34

lower airspace than commercial aviation aircrafts, and aviation piston engines (APEs) as the

35

major power units emit soot particles within troposphere which are closer to the ground

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Piston aircraft shipments reached 1,085 units in 2017 (out of 2,324 total general aviation aircraft

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shipments) and are forcast to increase by 0.3% per year in the U.S. by General Aviation

38

Manufacturers Association (GAMA).7 Soot emissions from APEs may gain increasing attention

39

due to the forthcoming aviation emission regulations and huge potential markets triggered by

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gradual airspace openness in developing countries like China 7. APEs have low combustion

41

efficiency and simple analog controls which lead to different emissions characteristics and

INTRODUCTION

4-5.

General aviation aircrafts normally fly in

2 / 21


6-7.

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amounts than the turbine engines. Piston engines emit more carbon monoxide and hydrocarbons

43

and less nitrogen oxide8. However, there is little research to analyze emission differences

44

between piston and gas turbine engines.

45

The depletion of fossil fuel resources, the steadily increasing cost of crude oil and the

46

requirment for energy independence have given impetus to the search for alternative aviation

47

fuels. Alternative fuels can reduce particulate matter (PM) emissions with little impact on

48

aircraft engine operation and performance 9. The second International Civil Aviation

49

Organization (ICAO) conference on aviation and alternative fuels in 2017, with the aim of

50

developing an ICAO vision on aviation alternative fuels, encouraged further development of

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aviation alternative fuels 10. A ‘single fuel policy’ was proposed

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diesel or kerosene) could be widely used to replace currently mainstream AVGAS (aviation

53

gasoline) for APEs due to safty and logistical concerns 12. Other promising alternative aviation

54

fuels include Fischer-Tropsch (F-T) fuels and biofuels. The F-T synthesized fuels, which have

55

been certified in civil aviation (mainly gas turbine engines) for decades 13, exhibit properties

56

substantially similar to historically refined kerosene, because specifications (such as D7566 and

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D1655) guide the production of the synthesized fuels that are compositionally similar to the

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conventional kerosene. Another paraffin-based alternative fuel (Hydrotreated Ester and Fatty

59

Acids, HEFA) is produced via hydrotreatment of biomass sources and is also chemically similar

60

to F-T fuels 14-15. Furthermore, pentanol as a high-carbon alcohol has the virtues of larger energy

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density and better miscibility with hydrocarbons compared with low-carbon alcohols 16-17. The

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blends of pentanol and hydrocarbon aviation fuels could be considered as an alternative aviation

63

fuel and have gradually gained acceptance 18. In terms of aviation kerosene, previous studies 3 / 21


11

and heavy fuels (such as


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mainly used Jet A or Jet A-1 type (common commercial aviation fuels in the U.S.), but RP-3

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was rarely investigated, which is widely used in Chinese aviation industry. It is desirable to

66

expand the database of RP-3 because of the noticeable difference between RP-3 and well-

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studied kerosenes in terms of aromatic hydrocarbon content and flash point

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assess the potential effects of alternative aviation fuels on environment and health, thoroughly

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investigating the morphology and nano-structure characteristics of their PM emissions is crucial,

70

because these characteristics of particles are closely linked to their ice nucleation potential (ice

71

freezing microphysics) and oxidative reactivity

72

understanding of soot formation 4.

21,

19-20.

To better

and could enhance the fundamental

73

High-resolution Transmission Electron Microscope (HRTEM) images are commonly used

74

to determine the nano-structure characteristics such as fringe length, fringe separation distance

75

and fringe tortuosity

76

information

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microscopically structural defects of soot samples 25. It was reported that oxidation-promoting

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and oxidation-inhibiting morphological features could be measured by Raman spectrum 26. The

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oxidation rate of soot particles could differ by nearly 400%, depending on the nano-structure

80

of primary particles 27.

24,

22-23.

Raman spectral analysis could also provide soot nano-structural

and could provide detailed information about graphitization degree and

81

Diesel particles have been extensively studied using HRTEM and Raman analysis. Graphitic

82

crystallite structures observed by HRTEM and Raman spectra revealed details of the graphite

83

structures quantitatively 28 and the degree of the crystalline structures increased as the engine

84

load increased. Previous studies demonstrated that the lube oil-derived particles had more

85

disordered structures than diesel particles according to HRTEM images, and more defective 4 / 21


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bands in lube oil-derived particles were revealed by Raman spectrum 29. Aviation particles were

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characterized mainly in the metric of particle mass or number, yet only a few studies focused

88

on the nano-structure characteristics of turbofan aero-engine particles

89

significant difference regarding the combustion systems among the gas turbine engines,

90

vehicular engines and APEs, it is desirable to fill the gap by comprehensively characterizing

91

the nano-structure and reactivity of soot emissions from APEs to better assess their impact on

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climate and environment. To the authors’ best knowledge, there is no open literature on the

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morphology and nano-structure characteristics of soot emissions from APEs. In this study,

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Chinese kerosene RP-3, promising alternative aviation fuels and their blends were used to

95

characterize the APE soot emissions microscopically via HRTEM and Raman spectroscopy.

96



21, 30.

Due to the

MATERIALS AND METHODS

97

Test Rig. Currently, there are two types of APE engines, namely, spark-ignition engines and

98

compression-ignition engines. A two-stroke, compression-ignition aviation piston engine with

99

a supercharging system and a swirl scavenging system was utilized to produce particle

100

emissions. The engine specifications are listed in Table S1 of Supporting Information. The

101

engine was controlled by a transient dynamometer, and the soot sampling was achieved using

102

a modified exhaust pipe with a controlled dilution system including a filter holder (SI Figure

103

S1). Soot samples were collected under two steady conditions at the constant engine speed of

104

1600 rpm with two different engine loads of 2 bar and 8 bar brake mean effective pressure

105

(BMEP). All the PM were sampled at the steady-state after engine warm-up. Soot particles were

106

collected on the quartz fiber filters in an unheated filter holder (GE Whatman, 47mm). We

5 / 21



107

chose three or four areas of each grid (300 mesh, 20-nm-thick carbon lacey) to ensure that the

108

analyzed particles were representative. The microscopic analysis method is explained in

109

Supporting Information.

110

119

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Test Fuels. The properties of diesel, RP-3 kerosene and Fischer-Tropsch and their blends 31-32.

111

were computed according to the literature

Apart from diesel and RP-3, three different

112

blends, namely, R80P20 (80% RP-3, 20% pentanol by volume), R60P40 (60% RP-3, 40%

113

pentanol by volume) and R75F25 (75% RP-3, 25% Fischer-Tropsch in volume) were prepared.

114

Kerosene has less carbon atoms, lower distillation temperature range, lower cetane number and

115

lower viscosity than diesel. Meanwhile, kerosene has better atomization compared with diesel

116

due to its lower viscosity, surface tension and density. Pentanol was added to RP-3 to increase

117

the viscosity and the oxygen content. The primary properties of the five test fuels are listed in

118

Table 1. Table 1 Fuel properties of the baseline diesel, RP-3, Pentanol, Fischer-Tropsch and the test blend fuels. Diesel RP-3 Pentanol R80P20 R60P40 FischerFuel types Tropsch Carbon number per molecule C16-C23 C8-C12 C5H12O --C9-C20 or chemical formula Viscosity (mm2/s) 4.13 1.28 2.89 1.602 1.924 2.1261 Density (g/cc) 0.83 0.79 0.815 0.803 0.806 0.7561 Cetane number 56.50 42.00 20-25 37.6-38.6 33.2-35.2 67.2 Lower heating value (MJ/kg) 42.68 43.43 35.06 41.731 40.044 -Oxygen content (wt%) 0.00 0.00 18.18 3.636 7.272 5.617 Latent heating (kJ/kg) 270 -308 ---Surface tension (10-3 Nm-1) 27.50 23.60 24.7 23.82 24.04 -Sulphur (%) 0.50 0.30 0.00 0.24 0.18 0.00 Boiling point (℃) T10=223 T10=172.8 138 ---T50=266 T50=194.9 ---T90=311 T90=224.4 ----

R75F25 C9-C20 1.5315 0.76 49.2 -1.405 --0.00 ----

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Raman Experiments. A Raman spectrometer (Horiba Jobin-Yvon LabRAM HR800) was used for

121

analyzing soot samples deposited on quartz filters. The excitation laser of 633 nm was Ar-ion type. A

122

low laser power of 1.36 mW was used to eliminate overheating. The diameter of the laser spot was 2 6 / 21


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μm and the slit size of the fully focused laser beam was 25 μm. Each spectrum was obtained from two

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repetitive 10 s accumulation. The Raman spectra were obtained with the range between 800 to 2000

125

cm-1. Statistical analysis was based on three areas for each sample.

126

For samples that were collected on filters, a large number of Raman spectra were obtained and

127

averaged to obtain the mean values. Quantifying the five bands of Raman spectra provided detailed

128

information about the chemical composition of soot emitted from APEs. All Raman spectra were

129

processed by the embedded ‘Lebspec5’ software, which also performed curve fitting for determining

130

the spectral parameters. Figure 1 illustrates a typical spectrum after baseline correction and the fitted

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curve with the combination of four Lorentzian-shaped G, D1, D2, D4 bands at about 1580, 1340, 1620,

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1180 cm-1 and the Gaussian-shaped D3 band at about 1500 cm-1 33. Table 2 presents physical meanings

133

of the bands.

134 135 136

Figure 1. Typical Raman spectrum and curve fitting for diesel particles at 2 bar BMEP. Table 2. Spectroscopic origins of the Raman spectra bands Band

Center

Formula

Origin

D1

1350cm-1

Lorentzian

Defects occurring at the vibrational mode involving A1g-sym metry (graphene layer edges) or A2 transition 34

D2

1620cm-1

Lorentzian

Associated with the disordered graphitic crystal (E2g-symmet ry and surface) 33

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D3

1500cm-1

Gaussian

Related to the amorphous carbon content (such as functional groups and organic molecules) 33, as well as the internal vibrational modes of tiny graphitic crystals related to the C– C stretching and edge carbons 21.

D4

1200cm-1

Lorentzian

Related to the vibrations of sp2- and sp3-hybridized carbon bonds, A1g symmetry (disordered graphite lattices), ionic impurities, and C-C and C=C stretching vibrations of polyenes 35-36.

G

1580cm-1

Lorentzian

The ideal graphitic crystal stretching mode 34.

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HRTEM Measurements. Soot samples were analyzed using a high-resolution TEM (JEM-2100F,

138

Japan), operating at 200kV with a spatial resolution of 0.23 nm. The maximum magnification of TEM

139

images was 1,500,000×. Soot was deposited on TEM grids (20-nm-thick carbon lacey coated Cu grids,

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Spi Supplies). The TEM image processing regarding the fringe characteristics (such as the fringe

141

distance, length, tortuosity and separation distance) was achieved using an in-house MATLAB code

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developed by following the existing algorithm

143

distributions were obtained by quantifying over two hundred primary particles of each aggregate

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particle using the in-house MATLAB-based software. Four or five locations were randomly chosen

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on each filter. Part of the particle-loaded filter was extracted in a beaker with ethanol solution. Then

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the filter was placed in an ultrasonic oscillator bath for over 30 minutes. The filter was taken out from

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the solution and 7-8 drops of the colloidal solution were placed on the TEM grid (300 mesh, 20-nm-

148

thick carbon lacey) and then dried in the beaker under gentle air flow and light. In this study, the fringe

149

length was treated as the size of the carbon layer 38, fringe distance was defined as the straight-line

150

distance between the two ends of a carbon layer, and the fringe tortuosity was characterized as the

151

ratio between the fringe length and the fringe distance. The mean distance between two adjacent layers

152

was measured as the fringe separation distance 38, which was illustrated in Figure 2 (c).

37

as shown in Figure 2. Primary particle size

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154 155 156

Figure 2. Post-processing of HRTEM images via fringe analysis: (a) the original image; (b) the fringe skeleton image; (c) the metrics of fringe characteristics.

157



RESULTS AND DISCUSSION

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Soot Morphology and Nano-structure Characteristics. Figure 3 shows the HRTEM images of

159

soot particles from the engine at 8 bar BMEP for three different fuels (RP-3, R80P20 and R75F25).

160

Volatile organic compounds (VOC) overwhelmed particulate matter emissions at low engine load of

161

2 bar BMEP, hence the soot fraction was too small to reveal nano-structure information. Figure 3

162

illustrates that similar grape-like aggregates of APE soot particles were observed regardless of

163

different fuels. These aggregates were the collection of small primary particles of 10-30 nm. The

164

images of R80P20 soot particles (e.g. Figure 3b) featured the smallest aggregate particles. Figure 4

165

shows that the size of the R80P20 primary particles ranged from 15 to 25 nm and was smaller than

166

those from the other two fuels, which suggests that pentanol fuel addition may have promoted the

167

oxidation of primary particles and hence reduced the primary particle size. The partially oxidized soot

168

may experience further oxidation, leading to the reduction of the primary particle size and more

169

compacted soot particles through the detachment of the chain-like branches from large aggregates 39.

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R75F25 generated slightly smaller primary particles than RP-3 which might be attributed to the fact

171

that F-T fuel addition with lower aromatics content suppressed soot formation due to the reduction of

172

soot precursor polycyclic aromatic hydrocarbons (PAHs)

40-42.

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Smaller particles tend to be more


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reactive than bigger ones because of their lower volume to surface ratio, in other words, smaller

174

particles are more likely to experience oxidation which further modifies the morphological and nano-

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structural properties 27, 43.

176 177 178

Figure 3. TEM images of representative soot particles and their morphological analysis: (a) RP-3, (b) R80P20, (c) R75F25.

179 180

Figure 4. Size distributions (by frequency obtained via number counting) of the primary particles.

181

Close inspection of the primary particles demonstrated typical core-shell morphology with

182

amorphous (core) and crystalline (shell) regions. The core amorphous region featured turbostratic

183

structure while crystalline domains consisted of distinguishable layers of platelets 44. The TEM images

184

showed that the fuel type did not influence the internal structure of primary particles to an appreciable

185

extent. But oxygenate fuel addition seemed to cause the occurrence of multiple inner cores within a

186

single primary particle, which might be attributable to immediate coalescence prior to a bigger particle

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being formed from a single core via surface growth 45. Figure 5 also shows that the cores of primary

188

particles generally have higher particle reactivity than that of the outer shell, because the carbon streaks 10 / 21


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in the core is shorter than that formed in the shell 27, 38. Among all the test fuels, the soot particles of

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R80P20 exhibited shorter and more tortuous fringes than RP-3 and R75F25 (Table 3).

191 192 193 194

Figure 5. HRTEM images of representative soot primary particles which have sizes close to the average value for each fuel illustrating nanostructure: (a) RP-3, (b) R80P20, (c) R75F25.

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to over 200 primary particles for each sample. Fringe parameters are indicative of the graphitization

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degree and oxidation reactivity of carbonaceous soot 27, 38. Shorter fringe length indicates less graphitic

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structures with more edge-site carbon atoms that could have highly reactive bonds with adjacent layers

198

46,

199

reactivity because the edge-site carbon atoms of the graphite layers would be more reactive than those

200

within the basal plane 37. The fringe tortuosity of the carbon crystallites could cause the electron orbits

201

in the micro-crystallites to stack and the electrons to repel each other. Thus a repulsive force between

202

adjacent carbon microcrystals arises. The turbostratic stacking of atomic layer planes results in a slight

203

increase in the interlayer distance due to electronic repulsion between molecular orbitals on the

204

adjacent layers 38.

Table 3 lists the fringe characteristics obtained by applying the fringe analysis algorithm (Figure 2)

in contrast, the longer fringe length with lower population of edge-site carbon atoms reduces

205

Higher tortuosity indicates more curved graphene segments and higher reactivity with weaker

206

bonding force between the carbon atoms 46. Oxidizers could access the edge-site atoms through the

207

interlayer spacing, thus the higher fringe separation the higher reactivity would be

208

fringe length is a metric reflecting the size of the plane derived from high-resolution TEM images.

209

Table 3 shows that most fringes were shorter than 2 nm with the fringe separation distance of 0.33 -

210

0.48 nm. The uncertainties of these fringe parameters were all less than the variation between different 11 / 21


47-48.

In addition,


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samples which means different fuels had noticeable impacts on soot nanostructure.

212 213

Table 3. The diameter distributions of the primary particles generated by different fuels and nano-structure characteristics based on HRTEM images. Fuel

Average primary particle diameter (nm)

Average fring e length (nm)

Average fringe tortuosit y

Average fringe sep aration distance (n m)

RP-3

24.25 ± 2.64

0.86 ± 0.03

1.20 ± 0.04

0.41 ± 0.03

R80P20

15.95 ± 2.81

0.81 ± 0.03

1.24 ± 0.06

0.46 ± 0.02

R75F25

22.71 ± 2.86

1.02 ± 0.04

1.17 ± 0.06

0.36 ± 0.03

214

Figure 6 illustrates the fringe characteristics of the particles generated by different fuels. It can be

215

seen that the fringe lengths for RP-3 and R80P20 are mainly concentrated at 0.5 nm, while the major

216

fraction of R75F25 fringe lengths are around 0.6 nm. The dependence of the fringe tortuosity on the

217

fuel is different, with the peak fringe tortuosity for R80P20 larger than those for the other fuels. The

218

main findings can be drawn from Table 3 and Figure 6 as follows. Firstly, the R80P20 particles had

219

shorter fringe lengths than the RP-3 and R75F25 particles as shown in Table 3. The longer the fringe

220

length, the larger the graphene layer would be. The R80P20 particles had more disordered layers with

221

more edge-site carbon atoms

222

implied larger curvature of the carbon layers within soot particles that might have been arisen from

223

the reaction of 5-membered rings

224

electronic resonance stabilization 49-50 and individual atoms are more susceptible to oxidative attack.

225

It is for the same reason that fullerenes and carbon nanotubes are more reactive than planar graphite

226

50-51.

46.

Secondly, R80P20 particles had higher fringe tortuosity, which

38.

Higher curvature implies weaker C-C bonds due to lessened

227

The increased fringe tortuosity in the deformed graphite layers would lead to weakened covalent

228

bonds between atoms and increased exposure of the atoms to the oxidizers, therefore higher soot

229

reactivity 38, 52. Thirdly, the separation distances of the R80P20 particles were the largest in Table 3,

230

which indicated that the R80P20 particles had the most loosely stacked layers. The separation distance 12 / 21


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was related to the possibility of oxygen to access the edge of the graphite layer. The smaller the

232

distance, the more stable the structure, because less oxygen could access the inner atoms. Therefore,

233

the R80P20 particles were the most likely to be oxidized among the investigated particles.

234 235 236 237

Figure 6. The fringe length and fringe tortuosity histograms analyzed from the primary particles in HRTEM images: (a) Fringe length, (b) Fringe tortuosity. The data with fringe length above 2 nm and fringe tortuosity above 1.52 were truncated because the percentages were too small to be visible on this scale.

238

Raman Spectra of Soot Particles. Raman spectroscopy can be used to characterize crystallite and

239

molecular structures of soot particles 33. Different structural characteristics of PM can be distinguished

240

53 according to the fitted curves from the Raman spectrum (see Figure 1) with different peaks explained

241

in Table 2. It is worth mentioning that the Raman spectra recorded at λ= 633 nm also exhibited second

242

order spectra above 2000 cm-1 Raman shift but only the first order spectra were considered for further

243

analysis.

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244 245 246 247

Figure 7. The area under each band normalized by the total area of all the bands from the fitted Raman spectra. (a) The samples obtained at 2 bar. (b) The samples obtained at 8 bar. The meanings of G (graphite) and D1-D4 (defects) peaks were explained in Table 2.

248

Figure 7 was derived from the Raman spectra of all the sample, which were fitted with five band

249

distributions (the typical first-order Raman spectra of each soot sample can be seen in SI Figure S3).

250

D1 was the most intense band and G and D3 were weaker with D4 and D2 being the weakest. Parent

251

et al.21 studied the soot emissions of a turbofan engine and obtained the band distributions, which

252

showed that the highest intensities occurred at D1 and D3, similar to the RP-3 results in this study.

253

The D3 band at 1500cm-1 was associated with the amorphous carbon, and RP-3 soot exhibited higher

254

amorphous carbon content than other test fuels. The D and G peak positions of different soot samples

255

shifted slightly due to the changes of different combustion products from C-H and C-C. The larger D3

256

band area and smaller D1 band area corresponding to RP-3 indicated that the samples of the traditional

257

fuels had more amorphous carbon and less defects at the graphene layer edges than the samples of the

258

alternative aviation fuels at 2 bar. However, at 8 bar, the samples of the alternative fuels showed less

259

defects at the graphene layer edges and more graphitic crystal (smaller D1 band area and larger G band

260

area) compared with kerosene.

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261 262

Figure 8. Relative intensity and the full width at half maximum (FWHM) obtained from Raman spectra: (a)

263

ID1/IG, (b) D1 FWHM, (c) ID2/IG, (d) ID3/IG.

264

The intensity ratio between D1 and G (ID1/IG) manifests the graphitic crystalline degree of the

265

sample particles, and smaller ID1/IG means that carbon layer has higher structural order of graphitic

266

crystalline 46. Figure 8(a) showed the variation in the ratio ID1/IG of the soot emissions of different fuels

267

at 2 bar and 8 bar BMEP. As the BMEP increased, the average ratio ID1/IG of RP-3 and R80P20

268

particles declined by 20% and 7%, respectively, and the average ratio ID1/IG of R60P40 increased by

269

32%. R60P40 particles had the highest degree of graphitization with the lowest ratio of ID1/IG at 2 bar,

270

while R75F25 particles had the highest degree of graphitization at 8 bar. The mean ID1/IG ratios of all

271

fuels were greater than unity. During the conversion process from amorphous carbon to ideal graphitic

272

lattice, ID1/IG increases initially and then declines 54. Since soot emissions contained much amorphous

273

carbon, the ID1/IG variation were different for soot samples with varying graphitization degrees.

274

Moreover, the ratio ID1/IG could also be used to estimate the fringe length which was proportional to

275

ID1/IG 55.

276

From Table 2 and Figure 8(a), one could conclude that R80P20 particles at 8 bar had the highest 15 / 21



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277

defective structure with the lowest degree of graphitization. In general, the Raman spectra were in

278

agreement with the analysis of nano-structure obtained from HRTEM images.

279

Figure 8(b) illustrates the full width at half maximum of D1 (D1 FWHM) of soot samples. Higher

280

D1 FWHM implied higher levels of chemical heterogeneity and lower degree of crystal structure order

281

56.

282

2 bar to 8 bar which could be attributed to the fact that complete combustion at high engine load

283

resulted in the decrease of intermediate products 57, indicating lower levels of chemical heterogeneity,

284

i.e. the average chemical composition of the copolymer as the function of the molar mass

285

BMEP samples with high degree of graphitic order could be attributed to charring effects which

286

convert organic molecules of high molecular mass into disordered graphite-like structures (charcoal)

287

57.

288

surface which mitigated the oxidation of the ‘core’ soot.

289

The mean D1 FWHM of all alternative fuels soot samples decreased as the BMEP increased from

58.

High

Under low BMEP conditions, there are abundant unburned fuel organic species attached to soot

ID2/IG reflected surface area-to-volume ratio of graphitic crystals, which indicated that ID2/IG could 59.

290

be treated as inversely proportional to the thickness of graphitic crystallites

Figure 8(c)

291

demonstrates that R75F25 and R60P40 particles had higher ID2/IG than other sample particles,

292

suggesting that they had thinner graphitic crystallites than the other sample particles. Thinner graphitic

293

crystallites featured more oxidant activities because high porosity could increase the oxide bonding in

294

graphene layers 57.

295

The origins of D3 band are related to amorphous carbon, and ID3/IG reflects the fraction of the

296

amorphous carbon in soot samples. The mean intensity ratio ID3/IG of RP-3 (0.75) was greater than that

297

of diesel (0.20) at 2 bar as shown in Figure 8(d). Furthermore, the mean intensity ratios ID3/IG of

298

R80P20, R60P40 and R75F25 particles were similar at 8 bar BMEP, yet exhibited large variation at 2

299

bar BMEP. The decrease in ID3/IG (except diesel) implied more ordered crystallite arrangement with 16 / 21


Page 17 of 21

300


gradual oxidation of oxygen functional groups (alcohol group) 29.

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Pentanol addition decreased the combustion duration and protracted ignition delay due to the lower

302

energy density of pentanol compared with the hydrocarbon fuels, which lead to the particles had the

303

highest defective structure with the lowest degree of graphitization. As the BMEP increased, RP-3

304

decreased the degree of graphitization because of its low cetane number and high volatility. The

305

particle oxidation reactivity seemed to be strongly dependent on fuel type and noticeably distinct

306

Raman spectra were observed for different test fuels. Using alternative aviation fuels in APEs,

307

especially adding higher alcohols would alter soot molecular structure and corresponding soot

308

oxidative reactivity, which has consequences for ice nucleation, haze formation and global climate

309

pattern. It is desirable to evaluate the oxidation reactivity of particles emitted from aircraft engines

310

burning alternative aviation fuels in order to comprehensively understand their environmental

311

implications.

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

313

Supplemental information

ASSOCIATED CONTENT

314

The supplemental information is related to this article. Table S1 gives the engine specifications.

315

Figure S1 illustrates the layout of the research engine test rig. Figure S2 lists HRTEM images of

316

representative soot particles. Figure S3 illustrates typical first-order Raman spectra of ten PM samples

317

using the embedded ‘Lebspec5’ software. Figure S4 shows typical Raman spectrum curves for the PM

318

samples from different fuels. Figure S5 shows the Raman spectrum of the quartz filter which was

319

subtracted in pretreatment.

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

AUTHOR INFORMATION

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Page 18 of 21

321

Corresponding Author

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*Tel: +41 44 633 36 21, E-mail: [email protected]

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ORCID

324

Jing Wang: 0000-0003-2078-137X

325

Notes

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The authors declare no competing financial interest.

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

328

This work is funded by National Natural Science Foundation of China (Grants No. 9164119).

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

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Impacts of Alternative Fuels on Morphological and Nanostructural

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