February 2011 

NASA/TM–2011-217059 

Alternative Aviation Fuel Experiment (AAFEX) 

B. E. Anderson, A. J. Beyersdorf, C. H. Hudgins, 

J. V. Plant, K. L. Thornhill, E. L. Winstead, and 

L. D. Ziemba 

NASA Langley Research Center, 

Hampton, Virginia 

R. Howard 

ATA, Arnold Engineering Development 

Center, Arnold AFB, Tennessee 

E. Corporan 

Air Force Research Laboratory, 

Wright Patterson AFB, Ohio 

R. C. Miake-Lye, S. C. Herndon, 

M. Timko, and E. Woods 

Aerodyne Research, Inc., 

Billerica, Massachusetts 

W. Dodds 

General Electric Aircraft Engines, 

Cincinnati, Ohio 

B. Lee and G. Santoni 

Harvard University, Cambridge, Massachusetts 

P. Whitefield, D. Hagen, and P. Lobo 

Missouri University of Science and 

Technology, Rolla, Missouri 

W. B. Knighton 

Montana State University, Bozeman, Montana 

D. Bulzan, K. Tacina, and C. Wey 

NASA Glenn Research Center, 

Cleveland, Ohio 

R. Vander Wal 

Pennsylvania State University, 

University Park, Pennsylvania 

A. Bhargava 

Pratt and Whitney, East Hartford, Connecticut 

J. Kinsey 

U.S. EPA, Research Triangle Park, 

North Carolina 

D. S. Liscinsky 

United Technologies Research Center, 

East Hartford, Connecticut
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NASA/TM–2011-217059 

Alternative Aviation Fuel Experiment (AAFEX) 

B. E. Anderson, A. J. Beyersdorf, C. H. Hudgins, 

J. V. Plant, K. L. Thornhill, E. L. Winstead, and 

L. D. Ziemba 

NASA Langley Research Center, 

Hampton, Virginia 

R. Howard 

ATA, Arnold Engineering Development 

Center, Arnold AFB, Tennessee 

E. Corporan 

Air Force Research Laboratory, 

Wright Patterson AFB, Ohio 

R. C. Miake-Lye, S. C. Herndon, 

M. Timko, and E. Woods 

Aerodyne Research, Inc., 

Billerica, Massachusetts 

W. Dodds 

General Electric Aircraft Engines, 

Cincinnati, Ohio 

B. Lee and G. Santoni 

Harvard University, Cambridge, Massachusetts 

P. Whitefield, D. Hagen, and P. Lobo 

Missouri University of Science and 

Technology, Rolla, Missouri 

W. B. Knighton 

Montana State University, Bozeman, Montana 

D. Bulzan, K. Tacina, and C. Wey 

NASA Glenn Research Center, 

Cleveland, Ohio 

R. Vander Wal 

Pennsylvania State University, 

University Park, Pennsylvania 

A. Bhargava 

Pratt and Whitney, East Hartford, Connecticut 

J. Kinsey 

U.S. EPA, Research Triangle Park, 

North Carolina 

D. S. Liscinsky 

United Technologies Research Center, 

East Hartford, Connecticut

National Aeronautics and 

Space Administration 

Langley Research Center 

Hampton, Virginia 23681-2199 

 

February 2011 
Available from: 

NASA Center for AeroSpace Information 

7115 Standard Drive 

Hanover, MD 21076-1320 

443-757-5802 
iii

Table of Contents

1.00 Project Description and Executive Summary ......................................................................... 1

2.00 INTRODUCTION .................................................................................................................. 6

3.00 PROJECT DESCRIPTION..................................................................................................... 8

3.01 Project Objectives................................................................................................................... 8

3.02 Aircraft Engines and APU ...................................................................................................... 9

3.03 Fuels ............................................................................................................................... 10

3.04 Experiment Site..................................................................................................................... 12

3.05 Participants............................................................................................................................ 13

3.06 Measurements....................................................................................................................... 15

3.07 Site Layout............................................................................................................................ 20

3.08 Sample Probes and Inlets...................................................................................................... 22

3.09 Downstream Sampling......................................................................................................... 29

3.10 APU Sampling ...................................................................................................................... 31

3.11 Aircraft Fueling..................................................................................................................... 32

3.12 Engine Test Runs.................................................................................................................. 34

3.13 Engine Power Settings.......................................................................................................... 40

4.00 OVERVIEW OF RESULTS................................................................................................. 42

4.01 Engine Performance and Certification Gas Emissions......................................................... 42

4.02 Trace Gas Emissions............................................................................................................. 44

4.03 Plume Chemistry................................................................................................................... 46

4.04 Greenhouse Gas Emissions................................................................................................... 49

4.05 Nonvolatile Particle Emissions............................................................................................. 50

4.06 Volatile Particle Emissions................................................................................................... 56

4.07 Auxiliary Power Unit (APU) Gaseous and PM Emissions................................................... 62

4.08 Sampling System Assessments............................................................................................. 65

5.00 FINAL REMARKS AND RECOMMENDATIONS ........................................................... 69

6.00 ACKNOWLEDGEMENTS.................................................................................................. 71

7.00 REFERENCES ..................................................................................................................... 72

8.00 LIST OF APPENDICES....................................................................................................... 73
iv

APPENDIX A: Engine Performance and Gaseous Emissions..................................................... 74

APPENDIX B: Effects of Alternative Fuels on CO and NOX Emissions Performance.............. 88

APPENDIX C: VOC Emissions from Jet Aircraft Engines Burning Alternative Fuels............... 97

APPENDIX D: Measurements of nitrous acid in commercial aircraft exhaust.......................... 119

APPENDIX E: Aircraft Emissions of Methane and Nitrous Oxide during theAlternative Aviation 

Fuel Experiment.................................................................................................. 133

APPENDIX F: Investigations of Plume Chemistry during AAFEX.......................................... 153

APPENDIX G: Gaseous And Non-Volatile Particulate Matter Emissions Measurements In 

CFM56 Engines – AAFEX Project..................................................................... 163

APPENDIX H: Concentrations and Physical Properties of Exhaust Particles from Aircraft 

Engines Burning Standard and Synthetic Fuels: AAFEX Results...................... 179

APPENDIX I: Influence of Ambient Temperature on the PM Emissions at the Engine Exit.... 225

APPENDIX J: Aircraft Engine Particulate: Macro- Micro- and Nanostructure by HRTEM and 

Chemistry by XPS............................................................................................... 236

APPENDIX K: Composition of Gas Turbine Engine Combustion Volatile Particle Material .. 260

APPENDIX L: Microphysical Evolution of Gas Turbine Engine Combustion Particles .......... 280

APPENDIX M: Determination of the Emissions from an Aircraft Auxiliary Power Unit (APU) 

during the Alternative Aviation Fuels EXperiment (AAFEX)........................... 288

APPENDIX N: Insights Into The Combustion Chemistry Within a Gas-Turbine Driven Auxiliary 

Power Unit .......................................................................................................... 321

APPENDIX O: Spatial Variation of PM Emissions at the Engine Exit ..................................... 336

APPENDIX P: Sampling System Effects On Particle Emission Measurements........................ 349

APPENDIX Q: Instrument Inter-Comparison............................................................................ 394
1

1.00 Project Description and Executive Summary

The rising cost of oil coupled with the need to reduce pollution and dependence on foreign 

suppliers has spurred great interest and activity in developing alternative aviation fuels. 

Although a variety of fuels have been produced that have similar properties to standard Jet A,

detailed studies are required to ascertain the exact impacts of the fuels on engine operation and 

exhaust composition. In response to this need, NASA acquired and burned a variety of 

alternative aviation fuel mixtures in the Dryden Flight Research Center DC-8 to assess changes 

in the aircraft’s CFM-56 engine performance and emission parameters relative to operation with 

standard JP-8. This Alternative Aviation Fuel Experiment, or AAFEX, was conducted at NASA 

Dryden’s Aircraft Operations Facility (DAOF) in Palmdale, California, from January 19 to

February 3, 2009 and specifically sought to establish fuel matrix effects on: 1) engine and 

exhaust gas temperatures and compressor speeds; 2) engine and auxiliary power unit (APU) gas 

phase and particle emissions and characteristics; and 3) volatile aerosol formation in aging 

exhaust plumes. A secondary goal of the study was to evaluate the role of ambient conditions in 

regulating volatile aerosol emissions. Managed by the Combustion sub-element of NASA’s 

Subsonic Fixed-Wing Program, AAFEX received additional sponsorship from the U.S. Air 

Force, the Federal Aviation Administration (FAA) and the U.S. Environmental Protection 

Agency (EPA). Groups from Air Force Research Lab at Wright-Patterson, Air Force Arnold 

Engineering Development Center, Aerodyne Research Inc., Carnegie-Mellon University, 

Harvard University, Missouri University for Science and Technology, Montana State University, 

NASA Langley and Glenn Research Centers, and the University of California at San Diego 

provided support and measurement expertise. Measured engine parameters included N1, N2, 

fuel flow, and exhaust gas temperature. Gas phase measurements included the standard ICAO 

certification species (CO2, CO, NOx, and THC) along with SO2, HONO, methane isotopes, 

speciated hydrocarbons, hazardous air pollutants (HAPS), and oxygenated compounds. 

Measured particle parameters included smoke number; number density, size distribution and 

total and nonvolatile mass; black carbon morphology, composition and total mass; volatile 

aerosol speciation and mass; and particle cloud-forming tendency. Participants made duplicate 

measurements of many aerosol and trace-gas species, which facilitated an assessment of the 

relative differences in emission data sets collected by the different groups in separate test venues. 

During AAFEX, the aircraft was parked in an open-air run-up facility and complete sets of gas

and particle emission measurements were made as a function of engine thrust. To delineate 

fuel-matrix related changes in emissions from those caused by variations in ambient conditions, 

samples were alternately drawn from the exhaust of the left inboard engine (#2), which always 

burned JP-8, and the right inboard engine (#3), which burned either standard JP-8 or one of the 

four test fuels: a Fischer/Tropsch (FT) fuel prepared from natural gas; an FT fuel made from 

coal; and 50:50 blends of each FT fuel with JP-8. To examine plume chemistry and particle 

evolution in time, samples were drawn from inlet probes positioned 1 and 30 m downstream of 

the aircraft’s engines. To sample more aged plumes, instruments were also placed in trailers 

parked on the northeastern edge of the ramp to measure aerosol and gaseous properties in air 

drawn from a common inlet mounted ~145 m behind the aircraft. At ground idle thrust 

conditions, a mobile laboratory vehicle periodically profiled the exhaust plume from 30 to 300 m 

downstream to examine temperature/time-dependent changes in particle and reactive gas 

composition and concentration. In addition, the 1-m rakes included multiple gas and aerosol 
2

inlet tips, which allowed emissions to be mapped across the breadth of the engine exhaust plane 

to establish the extent of the core-flow region within the near-field plume. Taking advantage of 

the broad diurnal variation in air temperature in the Mojave Desert, tests were conducted in the 

early morning and at mid-day to examine the effect of ambient conditions on gas phase and 

volatile aerosol emissions. 

From detailed analyses presented in the attached appendices and observations made in the field, 

the following general conclusions can be drawn.

Aircraft Performance and Maintenance Issues

• Burning FT fuel did not appreciably affect the DC-8’s CFM-56 engine performance. Once 

corrected for density and heating values, the fuel flow rates required to produce any 

particular N1 (low fan speed) setting were almost identical for JP-8 and the tested FT fuels, 

suggesting that the alternative fuels offer no advantage or penalty in terms of fuel economy. 

• The FT fuels exhibited higher combustion efficiencies than JP-8 at low power settings 

indicating that they are in general less polluting. 

• The aromatic-free FT fuel caused fuel-system seals to shrink, which resulted in fuel leaks in 

the aircraft #3 main tank and the two tanker trucks that were used to store/deliver the pure 

Shell and Sasol fuels. The leaks went away after introduction of JP-8 or blended fuel.

• Exhaust samples drawn from within 20 cm of the #3 engine centerline at mid-power settings 

were contaminated with volatile aerosol formed from engine oil emanating either from the 

engine’s central vent tube or from a leaky turbine seal; appreciable amounts of oil were not 

seen in 1-m samples collected 15 cm off the #2 engine centerline or at high engine thrust 

levels.

Exit plane engine emissions when burning standard JP-8 Fuel

• CO and THC emissions from the DC-8’s two inboard engines were somewhat elevated above 

ICAO certification values at idle, whereas NOx emissions were within the acceptable range 

at all thrust settings. 

• At mid to high power settings, the DC-8’s port-side (#2) engine produced higher levels of

NOx and nonvolatile particulate matter (PM ) number and mass emissions than the starboard 

(#3) engine. Detailed analysis showed that at thrust settings above idle, the #2 engine 

exhaust gas temperatures were significantly higher and that when plotted as functions of 

exhaust gas temperature (EGT), emission parameters from the two engines collapsed onto 

single curves. The higher EGTs produced by the #2 engine are possible signs of engine 

component aging. 

• The DC-8’s #3 engine emitted higher levels of CO, hydrocarbons and nonvolatile aerosols 

during AAFEX compared to the Aircraft Particle Emission Experiment (APEX-1), which 

was conducted during spring 2004, just after the aircraft’s engines had been overhauled to 

repair damage incurred during a volcanic plume encounter. This, along with the observation 

that the engine’s EICO at 7% idle greatly exceeded the ICAO certification value, suggests the 

engines’ emission performance had degraded during the period between the two experiments.

• CO and hydrocarbon emission indices were highly sensitive to throttle setting at low engine 

powers, as values often increased by a factor or two or more in going from 7% (the ICAO 

certification setting) to 4% idle. Since engines are operated at the lowest possible fuel flows 
3

when the aircraft are not in motion, this finding has implications for modeling air quality in 

airport terminal areas.

• The engines emitted log-normally distributed nonvolatile (soot) particles with mean 

diameters that ranged from about 15 nm at idle to 35 nm at takeoff thrust. Number emission 

indices (EIn) varied from 0.3 to 1 x 1015 kg-1 and were a maximum at the ground idle and 

takeoff thrust and a minimum at 30 to 45% power. Black carbon mass emission indices 

(EIbc) varied from about 10 mg kg-1 for mid-power settings to over 100 mg kg-1

at takeoff 

thrust. 

• Engine gas phase and nonvolatile PM emissions decreased significantly with increasing 

ambient temperature. Indeed EI values for many hydrocarbon species decreased by a factor 

of two as temperatures warmed from 0 to 15oC. PM number and black carbon EIs exhibited 

temperature coefficients (dEI/dT) that respectively ranged from -2 to -6 x 1013 kg-1oC-1 and -

0.4 to -2 mg kg-1oC-1

. As a percentage of the mean value, temperature coefficients were 

largest at idle and declined with increasing engine power. 

Fuel Effects on nonvolatile PM and Gas-Phase Emissions

• Relative to JP-8, burning alternative fuels generally reduced engine CO, THC and NOx 

emissions. The reductions were greatest for FT-1, which decreased NOx and CO EIs by up 

to 10% at high power and idle, respectively. At low power settings, THC emissions from 

FT-2 fuels were slightly higher than from JP-8.

• HAPS emissions were significantly lower for FT fuels. For example, at idle EI-benzene was 

about five times smaller for FT-1 compared to JP-8.

• Burning 50% blends of JP-8 and the FT fuels did not produce significant reductions in 

certification gas species emissions.

• Engine PM emissions were substantially reduced when burning the FT fuels. The effects 

were greatest for FT-1, where nonvolatile EIn and EIbc values were factors of 200 and 20 

lower at idle than corresponding JP-8 values, but were also quite notable for FT-2, which 

exhibited EIn and EIbc that were factors of 35 and 20 lower than JP-8 at mid power settings. 

• The blended fuels produced similar, but disproportionally large PM emission reductions. 

Ratios of JP-8 to Blend EIs varied from 2 to 9 for nonvolatile number and 2 to 22 for black 

carbon. Reduction benefits were greatest at 45% power and a minimum at idle and takeoff 

thrust.

• The reduction benefits of burning FT fuels decreased with increasing power so that the JP-8 

to FT-1 EI ratios for nonvolatile number and black carbon mass were respectively 4 and 7 at 

the 85% thrust setting. Smoke numbers at takeoff power were two to three times lower for 

the FT fuels than JP-8.

• Nonvolatile particles produced from burning the FT fuels were noticeably smaller and more 

compact than those generated by JP-8 combustion. For example, at 85% power, respective 

geometric mean diameters for FT-1, FT-2 and JP-8 were about 50, 55, and 75 nm, and 

corresponding densities were 1.45+0.1 g cm-3

, 1.2+0.15 g cm-3, and 0.92+0.08 g cm-3. 

• Concurrent lab studies show that the FT particles contain more oxygenated species than those 

generated by burning JP-8, which suggests they would form more active cloud condensation 

nuclei.

• Considering all fuels burned:

• The range between idle and high thrust nonvolatile number EIs decreased considerably 

with increasing fuel end point and aromatic content and decreasing hydrogen content. 
4

• At any given power setting, EIn and EIbc linearly increased with aromatic content and 

decreased with hydrogen content.

• Correlation coefficients with fuel properties were greater for EIn than for EIbc, suggesting 

that the variability in EIn was better captured by variability in fuel composition than was 

the variability in EIbc. 

• For both EIn and EIbc, the best correlations with all examined fuel properties were 

observed at idle (4 %) and takeoff (100 %) thrust settings.

Volatile Aerosols

• Low-volatility species condensed in the cooling exhaust plume to form nucleation mode

aerosols with mean diameters in the 10 to 25 nm size range, so that at 30-m downstream, EIn

values were more than an order of magnitude greater than measured at the engine exit plane, 

regardless engine power setting or fuel composition. 

• Results from AAFEX and other recent studies indicate that the volatile aerosols are 

composed of sulfate, lube oil and lube-oil related substances, hydrocarbons, and aromatics 

species. 

• Because of the greater amounts of organic aerosol precursors emitted and lower relative 

plume temperatures, volatile mass emissions were largest at idle, accounting for more than 

90% of EIm under most conditions

• For JP-8, volatile aerosol emissions decreased with power, but still dominated total number 

EIs and represented a significant fraction of total mass EIs at take-off thrust. 

• Volatile aerosol EIn and EIm values at idle were an order of magnitude or more lower for the 

FT fuels than JP-8, which suggests that the combustion emissions, not lube oil, are the 

primary source of volatile aerosol precursors.

• The propensity of low volatility gas-phase species to form new aerosols (nucleate) or to 

deposit onto the surface of existing soot particles depended on both plume soot 

concentrations and ambient conditions, with cold temperatures and low soot loading favoring 

nucleation and warm temperatures and high soot loading favoring soot surface deposition. 

• Volatile aerosol formation was heavily dependent on ambient temperature, as EIm values 

typically deceased by a factor of two when temperatures warmed from 0 to 15oC. 

• The mean size of nucleation mode particles depended on engine thrust, ambient temperature,

and plume age, with sizes increasing with downstream distance and decreasing temperature 

and engine power.

• Volatile aerosol number EIs varied according to fuel sulfur content so that under the same 

engine and ambient conditions, JP-8 > Blends > FT-1~FT2.

• Volatile aerosol mass emissions varied according to fuel sulfur content and hydrocarbon 

complexity so that JP-8 > Blend-2 > Blend-1 > FT-2 > FT-1.

Plume Chemistry

• The DC-8’s CFM-56 engines were a weak source and sink of CH4 at low (<15% of 

maximum thrust) and high (>30%) power settings, respectively. AAFEX results suggest 

that for a typical flight profile, the aircraft would destroy significantly more CH4 than it 

created. 

• N2O emissions were relatively constant with power and typically in the 50 to 100 g hr-1 in 

mode range. 
5

• Greenhouse gas emissions (CO2, CH4, and N2O) were not significantly influenced by fuel 

composition. 

• In downstream sampling, HONO EIs increased by a factor of six in going from idle to 

takeoff power and were not sensitive to ambient temperature, solar insolation or fuel 

composition. The results suggest that HONO is primarily created within the combustor, not 

in the downstream plume.

• H2O2 was observed for the first time in an engine plume. EIs were 0.43+0.31 g kg-1 at idle, 

but decreased to below detection limits at higher power settings.

• Ozone production was observed for the first time in a fresh (< 60 s old) engine exhaust 

plume. 

• Net conversion of NO to NO2 was observed in some cases and chemical circumstances 

suggest that this occurred through reaction with peroxy radicals, which in turn are formed 

through reactions of OH and VOCs

• A detailed chemical analysis suggests that exhaust plume OH concentrations were ~2 x 107

molecules cm-3

, which, when compared to typical background values, suggests VOC 

oxidation rates were elevated during the first minute of plume evolution. 

APU Emissions

• When both were operated at low power, the DC-8’s APU emitted about 25 times more black 

carbon mass per kg of fuel burned that one of its CFM-56 engines.

• Unlike for the engine, APU gas and PM emissions decreased with increasing engine power 

as indicated by exhaust gas temperature. For JP-8, EIn and EIbc respectively dropped from ~5 

x 1015 kg-1 and ~500 mg kg-1 at minimum load (cockpit power) to 2.5 1015 kg-1 and 200 mg 

kg-1 at maximum load (full air conditioning and bleed air). Similarly CO and THC emissions 

also declined by respective factors of 2 and 7 as power was increased from minimum to 

maximum.

• Burning FT-2 fuel did not significantly affect NOx emissions, but lowered CO and THC EIs 

by averages of 9 and 37%, respectively, when compared to JP-8 emissions.

• Compared to JP-8, FT-2 fuel drastically reduced the APU’s PM emissions. Indeed, average 

EIn and EIbc values were respectively factors of 6 and 13 lower when burning the alternative 

fuel.

• APU FT-2 nonvolatile PM emissions were smaller and had higher mass densities compared 

to JP-8 emissions. 

Sampling and Measurement Observations

• At low engine powers, FT-fuel nonvolatile PM number and black carbon emissions were 

very low and presented a measurement challenge for the SMPS and MAAP sensors.

• THC measurements made using standard FID sensors don’t accurately measure oxygenated 

species, which account for a significant fraction of VOCs at low engine powers. It is thus not 

possible to obtain closure between THC and summated hydrocarbon measurements.

• The transmission efficiency of PM sampling lines degrade with use and can appreciably alter 

measured emission parameters

• Although volatile aerosol number EIs quickly reached equilibrium in fresh exhaust plumes, 

low volatility species continued condense in time so that 30-m EIm values increased during 

sample transport through sampling long lines. 
6

• Nonvolatile PM EIs were sensitive to sample dilution, possibly because of inertial 

enrichment of large particles at low inlet tip velocities.

• Exhaust plume gaseous and PM emissions were homogeneously distributed within ~10 cm of 

the engine centerline.

• Nonvolatile PM number and mass EIs measured at 30-m were always larger than 1-m values, 

possibly because of thermophoretic and turbulent eddy impaction losses occurring within the 

1-m inlet probes.

• Nonvolatile PM EI measurements performed on 1-m aerosol-probe samples diluted at the 

inlet tip and gas probe samples diluted 1.5-m downstream were essentially identical, which 

suggests that existing sampling equipment used in engine certification tests can be modified 

to yield representative particle number and mass EI data. 

2.00 INTRODUCTION

Since 1970, the U.S. has had to import oil from other countries to meet its energy production 

needs. This situation often places our country in a weak position when negotiating political and 

diplomatic agreements and forces us to do business with unstable or totalitarian regimes. It

leaves us economically vulnerable to fluctuations in supply and open to the threat of embargoes. 

Shortages of oil may also constrain the growth of some economic sectors, with the aviation 

industry being a case in point. These factors, coupled with recent oil price increases and the 

heightened awareness that global fossil fuel production may be at or near its peak, has spurred 

significant interest in developing alternative, domestically-produced fuels for the nation’s 

transportation sector. A wide variety of alternative liquid fuels are now being tested or used for 

powering internal combustion engines, with ethanol being the most popular and, because of the 

food vs. fuel debate, the most controversial. 

For the aviation industry, the options for "drop-in" replacement fuels are more limited because of 

the narrow energy density (i.e, Joules/Liter), viscosity, thermal stability and corrosion property 

standards that must be met for economically powering the existing aircraft fleet. Alcohol-based 

fuels are unsuitable for aviation because of their low energy density and potential for corroding 

fuel system components. Research and development is presently focusing on converting 

hydrocarbon feedstocks into kerosene using the Fischer-Tropsch (FT) process, which is the basis 

for the Sasol fuels produced in South Africa. Plants are now operating that convert either 

natural gas or coal into synthetic fuels that meet Jet A standards but have improved viscosity and 

thermal stabilities. These properties extend the fuels’ use to lower temperatures, result in lower 

fuel system deposits, and allow them to be stored for long periods of time. In addition, FT fuels 

are essentially aromatic-hydrocarbon and sulfur free, which means their use results in much 

lower soot and sulfate aerosols emissions, making them particularly attractive for use in 

mitigating aircraft impacts on local air quality and climate. The downside to these fuels is that 

they are not sustainable in the long term (natural gas and coal deposits are limited) and their 

manufacture produces significant amounts of CO2 (about 1.8 times more than standard jet fuels), 

which must be captured or permanently sequestered to circumvent possible climate impacts. 

Also, there are presently no U.S.-based manufacturers that produce these fuels.

The search for renewable aviation fuels that have essentially no direct impact on atmospheric 

CO2 levels has focused on bio-oils such as those produced naturally by palm trees, soybeans, 
7

corn, and algae. These products are already being used to power diesel vehicles, but they have a 

number of drawbacks for use in aircraft engines, including a tendency to gel at relatively high 

temperatures, poor thermal stability, and the fact that they are grown in competition with food 

crops (i.e., recent increases in ethanol fuel production within the U.S. has caused corn prices to 

more than double in the last two years). Researchers have found that hydro-treated bio-fuels or 

80:20 blends of Jet A and biofuel meet current fuel standards (a Virgin Airlines aircraft recently 

made a well-publicized flight fueled by such a mixture), but Daggett et al. (2004) and others 

warn that sufficient land is not available to support large-scale biofuel production from standard 

farm crops and that an efforts to increase acreage may come at the sacrifice of rainforests and 

other ecosystems that are critical in maintaining the Earth’s climate system. This factor has led 

the European Union to abandon programs to develop "fuels from food" and for the U.S. to place 

more emphasis on bio-fuels that can be produced from saltwater plants. Supporting this effort, 

NASA Glenn Research Center in Cleveland, OH has initiated a pilot program to investigate, 

refine, and optimize techniques for growing saltwater algae and halocytes and work with 

commercial partners on procedures to efficiently convert these plants into biostocks suitable for 

jet fuel production. Researchers estimate that large-scale production of algae-based bio-jet fuels 

may commence within the next 10 years.

In tandem with research on sources and manufacturing of alternative aviation fuels, engine and

aircraft manufacturers along with the federal government have conducted tests to assess the 

impact of alternative fuels on engine performance and emissions. Because of its interest in 

gaining fuel security, stable sources of supply, and emission reductions at bases located within 

U.S. EPA non-attainment areas, the U.S. Department of Defense (DOD) has taken a lead this 

work, conducting ground-based and in-flight tests on stand- and wing-mounted military aircraft 

engines. However, the bulk of these tests have been conducted on older engine technologies,

such as those that power helicopters and the B-52 bomber (Corporan et al., 2007), and the results 

may not be particularly applicable to modern commercial engines. And while engine 

manufacturers have investigated the effects of alternative fuels on performance and emissions of 

selected engines, results of the tests are proprietary and thus not available for public use. 

Clearly, additional alternative fuel tests on modern commercial engines are required to produce 

an open-access data set that can be used, for example, to guide technology development, refine 

fuel specifications, and assess environmental impacts.

In addition to uncertainties in alternative fuel impacts, other important questions related to 

commercial aircraft emissions and their effect on air quality and climate remain unanswered. 

Through tests conducted during EXCAVATE (Anderson, 2003), the APEX series (i.e., Wey et 

al., 2007), and UNA-UNA (Lobo, 2008), a fairly good understanding of gas-turbine soot 

emissions and how they vary with combustor design and thrust setting has been gained. Data 

gathered in these studies also suggest that sulfur and organic compounds condense very rapidly 

within aging exhaust plumes to form volatile aerosols or coatings on soot particle surfaces and 

that the formation of new particles can be suppressed by reducing fuel-sulfur content. However, 

the fraction of fuel sulfur that is oxidized to sulfuric acid and the exact sources and composition 

of the volatile organic species are highly uncertain. Data detailing how ambient conditions 

influence volatile aerosol formation as well as primary pollutant (i.e., soot, hydrocarbons, CO, 

and NOx) emissions is also scarce. In addition, a recent study shows that airports may be 

significant sources of hazardous gas-phase air pollutants, such as benzene, formaldehyde, and 
8

naphthalene—very few data are available to assess the aircraft contribution to this potential 

problem.

The knowledge gap regarding aircraft particle emissions may inhibit expansion and construction 

of airport facilities in EPA non-attainment areas because the impacts of these activities on local 

PM2.5 levels cannot be accurately assessed. In an attempt to bridge this gap, the FAA 

correlated available soot emission data with engine-specific smoke numbers from the ICAO 

archives to develop a "First Order Approximation" (FOA, Wayson et al. 2007), which provides 

an estimate of aircraft soot mass emissions at standard engine thrust settings. Terms to estimate 

the mass of volatile emissions arising from fuel sulfur, unburned hydrocarbons and engine oil 

have been incorporated in recent FOA versions, but the magnitudes of these contributions are 

highly speculative, possibly over-conservative, and certainly need to be verified through 

comparison with careful measurements of aged exhaust plumes sampled under a variety of 

ambient conditions.

To address the needs outlined above, NASA conducted the Alternative Aviation Fuel 

Experiment (AAFEX) at NASA Dryden Flight Research Center Aircraft Operations Facility 

(DAOF) in Palmdale, CA during between January 20 and February 4, 2009. AAFEX used the 

NASA DC-8 to test the effects of coal- and natural gas-derived FT fuels and ambient conditions 

on the aircraft’s CFM56 engines’ emissions and performance. The tests focused on the aircraft’s 

right inboard engine, which was sampled extensively during the spring 2004, NASA-sponsored 

Aircraft Particle Emission Experiment (APEX-1; see Wey et al., 2007 for details), and thus has a 

well-documented performance and emission profile. Although the CFM56 is of somewhat older 

vintage, it is the most widely used engine within the current commercial fleet (almost all B737 

use some versions of this engine) and is likely representative of the combustor technology that 

will be used for at least the next decade. We thus anticipate that the acquired data set will have 

broad relevance to current studies of air quality and engine technology. 

The purpose of this document is to provide an overview of the AAFEX experiment as an 

introduction to the more detailed reports contributed by the individual investigative groups that 

are attached as appendices. We describe the test objectives, source aircraft, fuels, test setup, the 

exhaust sampling system, and ambient conditions. A sample test run is described and a 

summary of the test schedule provided. We briefly describe the contents of each of the attached 

appendices and conclude by providing recommendations for future research.

3.00 PROJECT DESCRIPTION

3.01 Project Objectives

The AAFEX science team was established several months ahead of the field deployment, which 

provided the opportunity for mission objectives and experiment plans to be thoroughly vetted by 

a panel of experts. After much discussion, the experiment plan was optimized to:

• Evaluate whether and how the alternative fuels affect engine performance or produce any 

notable degradation of engine or fuel system components

• Determine the effects of alternative fuels and ambient conditions on black carbon and gas 

phase emission indices (EIs) and characteristics as measured within 1 m of the engine’s

exhaust plane.
9

• Establish the composition, origin, and temperature-dependent concentrations and formation 

rates of the volatile aerosols that condense in the engine’s exhaust plume as it ages and mixes 

with background air; determine how fuel composition influences these processes.

• Establish emission factors for the aircraft’s auxiliary power unit (APU) and determine how 

these factors change with ambient conditions and fuel composition

• Evaluate the performance of new black carbon-measuring instruments relative to that of more 

proven techniques. 

• Compare particle number, size, and mass emission measurements made by separate groups to 

ascertain the expected range of relative uncertainty in EI values in data sets collected in 

previous test venues.

3.02 Aircraft Engines and APU

The NASA Dryden DC-8 was used as the AAFEX emissions source. This aircraft was originally 

built by McDonell Douglas, and NASA purchased it from Eastern Airlines in the mid-1980s to 

use as a flying laboratory to support Earth science research and satellite validation activities. 

The aircraft is typically flown < 1000 hrs/year, which means it has a relatively low number of 

hours on the engines and airframe. The DC-8 is equipped with four CFM56-2C1 gas-turbine 

engines, which are certified at 22,000 pounds thrust; the nominal operating characteristics of 

selected CFM56 engines are provided in Table 1.

The DC-8’s engines were totally re-built in 2000 when turbine damage was detected after the 

aircraft flew through a thick cloud of volcanic dust during the SOLVE mission, which was based 

in Kiruna, Sweden. Emissions from the DC-8’s right inboard engine were documented in detail 

during the spring 2004, NASA Aircraft Particle Emission Experiment (APEX; Wey et al., 2006). 

Gas phase EIs recorded at 7, 30, 85, and 100% of maximum thrust during APEX were consistent 

with those archived by ICAO from certification tests, suggesting that the DC-8 engines were 

operating within the manufacturers specifications and also that ground based tests of this nature 

can provide broadly representative results. 

Table 1. Operating Characteristics of CFM56 Engines

During APEX, the DC-8 engines were run for over 30 hours while the aircraft was in a 

parked/chocked position without encountering any significant problems. However to prevent 

2-C1 2A-2&3 2-B1

TAKEOFF CONDITIONS (sea level)

Max. takeoff (lb) 22,000 24,000 22,000

Airflow (lb/sec) 788 817 784

Bypass ratio 6.0 5.9 6.0

IN-FLIGHT PERFORMANCE (installed)

(35,000 ft-Mach = 0.80-ISA)

Max. climb thrust (lb) 5,400 5,760 5,450

Overall pressure ratio at max. climb 31.3 31.8 30.5

Max. cruise thrust (lb) 4,980 5,760 4,970

Cruise SFC (Bucket)(lb/lb hr). 0.671 0.657 0.648

CFM56 engine models Engine Parameters
10

undue stress on the aircraft wings and brakes, runtimes at 85 and 100% thrust were restricted to 

about 4 and 2 minutes, respectively, and to avoid compressor stalls, power levels were 

maintained below 40% when winds exceeded 5 mph from directions 90 to 270 degrees off the 

aircraft heading. These same limitations were in effect during AAFEX.

Sometime after its original manufacture, the DC-8 was retrofitted with a Honeywell Model 

GTCP85-98CK APU to provide power for stand-alone, ground-based operation. This APU 

delivers a portion of its compressor (bleed) flow to the combustor and the rest to the aircraft for 

environmental control, generator operation, engine start, etc. Essentially a low bypass gasturbine engine, the APU is located in the forward baggage compartment and exhausts out the 

starboard side, just ahead of the wing spar. It has the following specifications:

• Single can combustor

• Two-stage centrifugal compressor

• Single stage radial inflow turbine

• Bleed air flow: 58 kg/min at 220 °C exhaust gas temperature (EGT) and 0 kW shaft work

• Maximum shaft work: 149.2 kW

• Maximum EGT: 621 °C

The APU draws fuel from the aircraft #2 main tank, which is also the principle supply for the #3 

engine. Fuel flow to the APU varies according to the work demands of the aircraft systems and 

is not a parameter that can be monitored or adjusted by the operator. For this reason, the APU 

emissions were tested at several different load settings and the emissions was assessed as a 

function of exhaust gas temperature, which is known to be proportional to fuel air ratio. 

3.03 Fuels

Five different fuels were tested during AAFEX: a standard JP-8 (or baseline) fuel obtained from 

the fuel dump at Dryden Air Force Base; a Fischer-Tropsch (FT) fuel synthesized from natural 

gas (FT1) by Shell corporation and provided by the Air Force Research Lab (AFRL); an FT fuel 

prepared from coal by Sasol (FT2), also supplied by AFRL; and 50:50 blends of FT1 and FT2 

with JP-8. A 25,000 gal aliquot of the JP-8 was obtained before the mission and stored in on-site 

tankers so that a single batch of baseline fuel could be used throughout the tests. The FT fuels 

were shipped to the Dryden Aircraft Operations Facility (DAOF) and stored on-site in rented 

tankers. DOAF tankers that were subsequently used to store, transfer and blend the fuels were 

drained and steam cleaned prior to use. A lubricity additive was added to each FT fuel to ensure 

that their use would not cause any issues with the aircraft or tanker fuel pumps. Fuel samples 

were drawn from the right inboard-engine drain line before and after each test run and were 

analyzed for a variety of properties, including sulfur and aromatic content, by the Air Force 

Research Lab (AFRL), Wright-Patterson fuels lab.

The properties of the five fuels as determined from the AFRL tests are summarized in Table 2; 

carbon spectra for FT1 and JP-8 fuels are exhibited in Figure 1 to emphasize the significant 

differences in hydrocarbon composition of the two fuels. Table 2 results indicate that the two FT 

fuels are essentially sulfur free, the minor amounts of contamination (~20 ppm) probably being 

introduced from residual JP-8 in the fuel pumps or transfer lines. The FT fuels also contain zero 

(FT1) or only minor amounts (FT2) of aromatic hydrocarbons, which is reflected in their higher 
11

hydrogen contents and H/C ratios as compared to JP-8. Their low aromatic, olefinic, and longchain hydrocarbon (i.e., Figure 2) contents also lead the FT fuels to have much lower specific 

gravities than JP-8. The heats of combustion for the FT fuels are slightly higher (~2%) than for 

JP-8, but this advantage is offset by the much lower FT fuel specific gravities. The physical and 

compositional properties of the blended fuels are, to within measurement precision, averages of 

those for the JP-8 and FT fuels.

Table 2. Fuel Properties

TEST JP-8 FT1 FT1 Blend FT2 FT2 Blend

Sulfur (ppm) 1148 19 699 22 658

Aromatics (%vol) 18.6 0 8 0.6 9.1

Distillation, deg C

IBP 158 157 156 160 158

10% 176 162 166 167 170

20% 184 164 170 170 175

50% 207 170 183 180 190

90% 248 186 232 208 233

EP 273 206 264 231 263

Residue (%vol) 0.8 0.9 1 1 0.8

Loss (%vol) 0.8 0.9 1 0.9 0.9

Flash Point, deg C 46 41 43 42 46

API Gravity 41.9 60.2 50.5 54 47.9

Freezing Point, deg C -50 -54 -60 <-80 -60

Viscosity, mm2/s 4.7 2.6 3.3 3.6 4.1

Cetane Index 41 58 46 51 45

H Content (%mass) 13.6 15.5 14.5 15.1 14.3

Naphtalenes (%vol) 1.6 0 0.8 0 0.8

Heat of Combustion (MJ/kg) 43.3 44.4 43.8 44.1 43.8

Olefins (%vol) 0.9 0 0.6 3.8 3.3

Fuel H/C ratio 1.88 2.19 2.02 2.12 1.99

Specific Gravity 0.816 0.738 0.777 0.763 0.789
12

Figure 1 Analysis of standard JP-8 and FT-1, the natural gas fuel that was used during AAFEX.

3.04 Experiment Site

AAFEX was conducted at the Dryden Aircraft Operations Facility (DAOF), which is operated by 

NASA's Dryden Flight Research Center and is located in Palmdale, Calif., about 70 miles 

northeast of downtown Los Angeles. The leased facility is adjacent to the Palmdale Regional 

Airport and consists of 210,000 square feet of hanger space and an equivalent amount of space 

for offices, labs, conference rooms and storage for spare equipment, flammables, and hazardous 

chemicals. While some laboratory tests and instrument checkouts were conducted in the hanger, 

actual engine test runs were performed on the large outdoor aircraft test facility located just north 

of DOAF, which is accessed via a seldom-used taxiway (Figure 2). This facility was used in 

previous years for conducting on-wing tests of military aircraft engines; it is at least 300 m and 

typically cross-wind from the access road and parking lot, so that automobile pollution and 

exhaust from other aircraft is not a problem for emission characterization studies. The concrete 

staging area associated with the facility is approximately 150 m wide by 300 m long and is 

equipped with three sets of office buildings/control rooms along with stadium-style lighting, 

water hydrants, and a variety of power outlets.
13

Figure 2. Aerial photograph of the NASA DAOF Hanger and engine run-up area at the Palmdale 

Regional Airport.

3.05 Participants

Table 3 lists the principle investigators and consultants that contributed either measurements or 

analysis support to AAFEX. These participants were supported by NASA (AEDC, DFRC, 

LaRC, GRC, Penn State, and UTRC); FAA (ARI, MST, MSU); U. S. Air Force (WPAFB) or 

their own parent organizations (Boeing, EPA, GE, and Pratt and Whitney). 
14

Table 3. AAFEX Participants

Organization POC Role

AEDC Robert Howard 

Robert.Howard@arnold.af.mil

Project Engineer, Sampling probes 

and heated lines; Smoke Number

ARI Rick Miake-Lye 

rick@aerodyne.com

NOx, CO, Hydrocarbons, aerosol 

composition, BC mass

Boeing

Steve Baughcum 

Steven.L.Baughcum@boeing.co

m

Science advisor, observer

Carnegie Mellon 

University

Allen Robinson

alr@andrew.cmu.edu Hydrocarbon volatility and speciation

EPA John Kinsey 

kinsey.john@epamail.epa.gov Aerosol Mass and Composition

GE Willard Dodds 

Willard.Dodds@ae.ge.com

Engine Performance/Operation 

Advisor

Missouri S&T Phil Whitefield 

pwhite@mst.edu Aerosol Physical Properties

Montana State U Berk Knighton 

Knighton@msu.edu Speciated Hydrocarbons

NASA DFRC Frank Cutler 

frank.w.cutler@nasa.gov Aircraft Operations

NASA GRC Changlie Wey 

changlie.wey@nasa.gov

Certification gases, SO2, O2, H2O, 

NMHCs; Black Carbon 

NASA GRC Dan Bulzan 

Dan.L.Bulzan@nasa.gov Project Manager, Test Conductor

NASA LaRC Bruce Anderson 

bruce.e.anderson@nasa.gov

Project Scientist, Bulk Aerosol 

Composition/Physical Properties, 

Black Carbon Mass

Penn State U Randy Vander Wal Black Carbon Morphology and 

Composition

Pratt and 

Whitney

Anuj Bhargava 

anuj.bargava@pw.utc.com

Science advisor, instrument/group 

inter-comparison lead

U. California 

San Diego

Terri Jackson

tjackson@ucsd.edu Sulfate Aerosol Isotopes

UTRC David Liscinsky 

LiscinDS@utrc.utc.com

Aerosol Physical Properties; 

instrument comparisons

AFRL/WPAFB Edwin Corporan 

edwin.coporan@wpafb.af.mil

Aerosol Physical Properties, BC Mass, 

Smoke Number, PAH

Notes: AEDC=Arnold Engineering Development Center, Tullahoma, TN; ARI=Aerodyne 

Research, Inc., Bedford MA; AFRL=Air Force Research Lab at Wright Patterson AFB, OH; 

EPA=U.S. Environmental Protection Agency at Research Triangle Park, NC; GE=General 

Electric Commercial Aircraft Engines, Cincinnati, OH; MST=Missouri University for Science 

and Technology, Rolla MO; DFRC=Dryden Flight Research Center; GRC= Glenn Research 
15

Center; LaRC=Langley Research Center; Pratt and Whitney Commercial Engines, East Hartford, 

CT; UTRC=United Technologies Research Center, East Hartford, CT.

Primary project leadership was provided by Bruce Anderson (science), Robert Howard 

(engineering), Dan Bulzan (management), and Frank Cutler (aircraft operations). However, the 

final objectives, experiment plan, and operational procedures were established in consultation 

with science team members, project stakeholders, and the aircraft support team. Input from GE 

and Boeing was particularly valuable in test planning, as these companies provided proprietary 

information on engine, fuel, and airframe issues and helped to define engine-operating

parameters for the alternative fuels and for changing ambient conditions. The contributions of 

many other groups were critical to the success of AAFEX: AEDC designed, constructed and 

installed the 1-m aerosol and gas sampling probes and rakes and the 30-m instrument enclosure; 

Missouri University for Science and Technology (MST) designed, constructed, installed, and 

operated the sample selection system; WPAFB supplied the FT fuels and performed the postmission fuel analyses; and the DC-8 ground crew, headed by Mike Bereda, provided timely and 

enthusiastic support in installing the sampling systems and operating the aircraft engines during 

the extensive test runs. 

AAFEX investigators included groups that had participated in EXCAVATE (Anderson et al., 

2003), APEX-1 (Wey et al., 2007), APEX-2, APEX-3, the PW308 alternative fuel experiment

and a variety of other previous engine emissions tests. Their participation guaranteed that the 

emissions would be thoroughly characterized and documented. However, note that AFRL, MST, 

NASA LaRC, and the United Technologies Research Center (UTRC) provided similar 

measurements of particle number and size, while ARI, LaRC, and UTRC use the same 

techniques to measure BC mass. This overlap provided an opportunity to inter-compare 

measurement results and to help establish the expected range of uncertainty between data sets 

collected by the individual investigators in separate test programs.

3.06 Measurements

A comprehensive suite of measurements was required to address the very challenging objectives 

outlined in section 3.01. Listed in tables 4 and 5, these included detailed measurements of gas 

and aerosol parameters on samples drawn from inlets placed at 1, 30 and 145 m behind the 

aircraft engines as well as onboard the Aerodyne Research, Inc (ARI) mobile laboratory as it 

profiled the engine plumes during a number of low power engine tests. The measurements are 

divided into those linked to specific fixed sites or moving vehicles (Table 4) and ones made on 

the common aerosol sampling manifold and 1-m gas sampling probes (Table 5). Table 4 also

lists a variety of ancillary measurements, which were needed to establish links between engine 

thrust and emission characteristics, to elucidate plume dynamics, and to evaluate the impact of 

alternative fuels on engine performance. Key among these was the aircraft operating parameters. 

To acquire these data and because the aircraft avionics lacked digital outputs, the test conductor 

sat in a jump seat behind the aircraft operator, read the analog displays, mentally averaged values 

during stable operating periods, and manually recorded the key parameters during each of the 

411 test points conducted during AAFEX. The resulting data set includes for each engine: fan 

speed (N1), core speed (N2), fuel flow rate (WF), and exhaust gas temperature (EGT). 

Similarly, APU EGT was recorded during the fuel tests involving that emission source. Ambient 

temperature and pressure data provided by a portable weather station erected and operated 
16

continuously at the site were used to correct N1, N2 and WF to standard day conditions. The 

weather station additionally logged relative humidity and wind speed/direction; this information 

was relayed through wireless transmission to the DC-8 cockpit and where it was both handrecorded by the test conductor and used in real time by the aircraft operators to determine 

whether crosswinds exceeded the range for safe engine operation. Other ancillary 

measurements included temperature and pressure on the left and right 1-m rakes and the right 30-

m sampling inlet and temperature and winds on the ARI van. These data were subsequently used 

to calculate plume mach number and velocity as a function of downstream distance from the 

engine exit planes.

A variety of detailed aerosol and gas phase measurements were performed on samples collected 

using individual sampling probes/inlets. Carnegie Mellon University (CMU) used a large-bore 

probe mounted on the R1 stand to collect sample on filters for offline determination of organic 

compounds using a technique that involves slowing ramping the sample temperature and 

identifying the evaporating compounds using a GC/MS system. The resulting data can be 

coupled with a model to predict the partitioning of the VOCs between the gas and aerosol phase 

at any prescribed plume age and ambient condition. UCSD used the nearby "button-hook"

probe (see section 3.08) to supply exhaust flow to a high-volume sampler to collect quartz-fiber 

filters for sulfur isotope analysis, with the hope that sulfate formed from fuel sulfur contaminants 

would have distinctly different isotopic ratios than background aerosols and thus be a powerful 

tool for delineating aircraft from other sulfate aerosol sources in complex urban airsheds. 

As in APEX-1, 2 and 3, the U.S. EPA approached AAFEX as an opportunity to establish engine 

emission profiles for dilute exhaust plumes as a function of engine power, ambient conditions 

and, this time, fuel composition. To address this objective, they made measurements 

exclusively on samples collected using a matched pair of inlets/sampling lines positioned 30 m 

behind the #2 and #3 engine exit planes (see section 3.08 for details). Their instrument suite 

included capability for determining particle number, size, total mass, black carbon mass and 

sulfate aerosol mass. 

To investigate sample line effects and plume chemistry or to provide longer integration times for 

slower responding sensors, small suites of instruments were set up to make continuous 

measurements on the R30 and R145 inlets and inside the UTRC deathbox. A primary focus was 

measurements aerosol number and size, since these are useful indicators of particle formation 

and growth. Black carbon was also measured on R30 and R145 samples to provide a second 

means (other than CO2) of normalizing plume dilution. Filter samples for isotopic analysis were 

collected as were data from a portable CCN counter, the latter to examine how the solubility of 

the soot particles varied with power, fuel composition, and plume age. A pair of Particle-IntoLiquid Samplers (PILS) attached to a total organic carbon (TOC) analyzer and liquid sample 

collection drew sample from R30 to provide 4-min resolution measurements of water-soluble 

organic carbon and ion species concentration, respectively. Instruments to determine aerosol 

volatility, hygroscopic properties and sulfate aerosol loading were additionally deployed to 

sample from R145. Gas phase measurements were also emphasized at this location, in particular 

those of methane isotopes and species such as HONO and H2O2 that are important for 

characterizing oxidative processes in the engine exhaust plume. The UTRC EEPS was the 

critical instrument inside the deathbox: its output was compared to an identical instrument 
17

located in the NASA truck to investigate the impact that long sample-line residence times on 

aerosol number, size and total volume.

As mentioned in section 3.08, the ARI van had a portable power source and was often 

disconnected from the primary aerosol sampling manifold during extended ground-idle operation 

periods to profile the chemical and aerosol characteristics of the right engine exhaust plume as a 

function of distance behind the aircraft. On a few occasions, the van was parked >0.5 km 

downwind of the aircraft to sample the aged plume at high engine thrust levels during JP-8 runs. 

The van carried a comprehensive suite of chemical and aerosol sensors that included a single 

particle aerosol mass spectrometer (AMS) to determine volatile aerosol composition, a protontransfer reaction mass spectrometer for non-methane hydrocarbons, and a tuneable diode laser 

spectrometer for CO, formaldehyde and other tracer species. The van payload was, at times, 

supplemented with the UTRC EEPS to provide more detailed information on particle formation 

and growth in the expanding/cooling plume. The van instruments were connected to an external 

inlet through a short length of sample line so that the resulting measurements were relatively free 

of sampling-system induced biases. Thus the van’s measurements were also valuable in 

establishing the effects of line losses and chemistry on observations recorded on samples drawn 

through much longer lengths of tubing. 
18

Table 4. Measurements made at individual locations, single probes or on moving vehicles.

Location/sample Parameter Instrument Group

Aircraft N1, N2, Fuel Flows, 

EGT Cockpit Displays NASA

Experiment Site T, P, winds, humidity Weather station NASA

1 m Rakes

Temperature Thermocouple AEDC

Total Pressure Pressure Transducer AEDC

Volatile Organics Filter/offline analysis CMU

Sulfate Isotopes Filter/offline analysis UCSD

30 m EPA inlets

Particle Number, Size CPC, SMPS, APS EPA

Aerosol Mass QCM EPA

Sulfate Mass TECO Sulfate Analyzer EPA

Black Carbon MAAP EPA

Surface PAH PAS 2000 EPA

SO2 Pulsed Fluorescence EPA

CO2 NDIR EPA

Right 30-m 

Probe and 

Deathbox

T, dP Thermocouple, pitot tube NASA

Particle Number, Size CPC, EEPS UTRC, NASA

Sulfate Isotopes Filter/offline analysis UCSD

Black Carbon EC/OC NASA

Cloud Condensation 

Nuclei DMT CCN NASA

Bulk Aerosol 

Composition PILS/TOC, PILS/IC NASA

CO2 NDIR NASA

145 m inlet

Particle Number, Size CPC, SMPS, DMS-500, 

OPC

NASA, UTRC, 

MST

Nonvolatile Number, 

Size CPC, SMPS, OPC NASA, UTRC

Black Carbon MAAP UTRC

Sulfate Mass TECO Sulfate Analyzer NASA

Cloud Condensation 

Nuclei DMT CCN NASA

Particle Hygroscopicity SMPS/Humidifier MST

Sulfate Isotopes Filter/offline analysis UCSD

CO2 NDIR ARI

HONO, HOHO, CH4 TILDAS ARI/Harvard

Aerodyne Van

T, P, winds, humidity weather station ARI

Particle Number, Size CPC, SMPS, EEPS ARI, UTRC

Black Carbon MAAP ARI

Single Particle 

Composition AMS ARI

CO2 NDIR MST

CO, NO, NO2, O3, etc. TILDAS, TECO ARI

Hydrocarbons, HAPS PTRMS ARI/MSU
19

Table 5 measurements were recorded by instruments located in the equipment trailers parked off 

the aircraft’s right wing from exhaust samples drawn through sampling systems depicted in 

Figures 3 and 4. On the gas lines, certification gas measurements (NOx, CO, CO2, and THC) 

were made using ICAO accepted sampling techniques and instruments; these were important for 

evaluating engine operation and establishing how emissions changed with fuel composition and 

ambient conditions. The sulfur dioxide and O2 measurements were included to allow real-time 

fuel sulfur content and fuel-air-ratio determinations. Fourier-transform, infrared spectrometertype, multi-gas analyzers provided additional information on speciated hydrocarbon 

concentrations, whereas smoke numbers were determined by both AEDC and AFRL using 

conventional sample collection and analysis techniques. Total aerosol and black carbon masses 

were measured in the more concentrated samples using a tapered-element oscillating 

microbalance (TEOM) and laser-induced incandescence instrument, respectively. Polyaromatic 

hydrocarbon (PAH) concentrations were assayed using the conventional filtercollection/extractive analysis method well as with an online instrument that purports to measure 

surface bound PAH using an UV ionization/electrometer technique (ECO 2000).

The most comprehensive set of gas-phase and aerosol measurements were made on samples 

provided by the "aerosol" sampling system. These included multiple determinations of particle 

number, size, and black carbon content as well as unique measurements of particle composition, 

PAH content, surface area, and black carbon morphology. Note that several BC sensing 

instruments were deployed, mainly to determine whether they are straightforward to use, provide 

reliable and consistent data, and are insensitive to changes in soot morphology and coatings. 

The Multi-Angle Aerosol Absorption Photometer (MAAP) instrument was the primary black 

carbon standard as it was specified for use in characterizing BC emission from Joint-Strike 

Fighter engines (PW135) by the "Interim Test Method," which has subsequently been approved 

by the EPA as a substitute for "Method 5" determinations of aircraft particle emissions. 

However, the MAAP calibration is not well established for aircraft emissions and its response is 

known to vary as particles accumulate surface coatings. AAFEX measurements at multiple 

sampling distances allowed us to determine the severity of this problem and to evaluate whether 

any of the new instruments yielded better results. Three different types of instruments were also 

used to establish particle size distributions: SMPS, EEPS and DMS-500. In this case, the SMPS 

was assumed to be the "standard" while the EEPS and DMS-500 instruments were used to 

provide fast response measurements for the exhaust mapping and plume chemistry experiments.
20

Table 5. Measurements made on multi-source sampling manifolds.

Sample 

Line Parameter Instrument Group

Aerosol

(1R, 1L, 

30R, 30L)

Dilution flow, sample 

pressure

Misc. MST

Particle Number, Size CPC, SMPS, EEPS, 

DMS

AFRL, MST, NASA, 

UTRC

Nonvolatile Number, Size Heated CPC, SMPS MST, NASA

Black Carbon Mass

MAAP ARI, NASA, UTRC

EC/OC NASA

PASS-3 NASA

Black Carbon Morphology Electron Microscope Penn State

Surface PAH PAS 2000 AFRL, NASA

Single Particle 

Composition AMS ARI

Cloud Condensation 

Nuclei CCN counter NASA

Surface Area TSI EAD NASA

CO2 NDIR AFRL, ARI, MST, 

NASA, Navy

CO, NO, NO2, etc. TILDAS ARI

Hydrocarbons, HAPS PTRMS ARI/MSU

Gas

(1L, 1R)

CO2, CO, NOx, THC, 

SO2, O2

Conventional Gas 

Analyzers NASA

Certification Gases, 

NMHCs MGA AFRL, NASA

Smoke Number Filter, reflectance 

meter AFRL

Particle Mass TEOM AFRL

PAH Filter/offline analysis; 

ECO 2000 AFRL

Black Carbon Mass EC/OC AFRL

Artium LII NASA

3.07 Site Layout

Figure 3 is an aerial photograph of the test site taken on January 30, during the middle of the 

mission. During initial setup, the aircraft was parked and chocked on the western edge of the B1 bomber test area (see Figure 2 for a large-scale view), facing into the prevailing winds. 

Afterward, the equipment vehicles were driven onto the ramp and carefully positioned off the 

aircraft’s right wingtip to minimize sampling line lengths between the diagnostic instruments and 

the right inboard engine. 
21

Figure 3. Aerial photograph of the experiment site with the equipment trailers for each of the 

participating groups indicated. Note the portable weather station located ~50 m ahead of the 

aircraft, on the far edge of the pad. Photo taken on January 30, 2009 by the DC-8 pilots while 

flying the DFRC King Air.

The aerosol sample selection box and sample dilution controls were located in the MST trailer, 

hence it was positioned on a line extending perpendicular from the inboard engine exhaust plane; 

the other trailers were arranged to either side of the MST trailer to minimize the lengths of tubing 

connecting the individual investigator’s aerosol instruments to the common sampling manifold

(see section 3.08 below). Similarly, the primary gas-phase monitoring instruments were located 

in the AEDC trailer, thus it was situated so as to minimize the gas sample line lengths. 

Power was supplied to the trailers from 440 VAC, 3-phase outlets and a bank of 120 VAC 

outlets located on the superstructure of bomber test station 1 (Figure 2). A portable "skid" was 

supplied by the USEPA to divide the 3-phase power into the single-phase, 208 VAC needed by 

many of the experimenters (i.e., NASA, MST, AFRL, and ARI). Water for cooling the 1-m 

sampling rakes was obtained from a high-pressure outlet also located on the test pad. A wireless 

weather station was erected on the edge of the ramp, upwind of the aircraft to monitor wind 

direction and other meteorological parameters. For convenience, portable toilets were installed 

behind the row of vehicles. Light for nighttime operations was provided by banks of "stadium"

lights located along the north edge of the test area. Communications between the aircraft and 

equipment shelters was provided by a wired, centrally located intercom system provided by 

Missouri University for Science and Technology. One person in each group was required to 

wear a headset during the tests so that changes in the test plan or notification of emergency 

situations could be quickly communicated. 
22

3.08 Sample Probes and Inlets

To prevent placing excessive torque on the DC-8 airframe, both inboard engines are operated at 

approximately the same fuel flow rates at all times. Thus, under the assumption that both 

engines exhibited approximately the same emission characteristics and taking advantage of the 

independent fuel delivery systems onboard the plane, it was possible to burn a baseline fuel 

(standard JP-8) in the non-test engine and sample its exhaust periodically to assess the effects of 

changing ambient conditions on emissions characteristics and to provide a "calibration" standard 

for judging alternative fuel impacts on the exhaust composition of the test engine. Figure 4 

provides a coarse schematic of the sampling system that was installed behind the DC-8 to 

facilitate this test procedure. Important components included: four sample inlet rakes/probes 

that were bolted to the concrete pad at 1 and 30 m behind each engine; fire valve boxes that were 

used to select sample from the different probe tips on the 1-m rakes; a sample selection valve 

box located in the MST trailer; and various lengths of tubing that transported sample to 

diagnostic instruments located in experimenter trailers. 

The multi-probed sample inlet rakes were the most complex and costly elements of the sampling 

system. Shown in Figures 5 and 6, these were positioned behind each of the two inboard 

engines, about 10 cm off the center lines (to avoid drawing sample from the crankcase vent) and 

within 1 exhaust diameter downstream of the exhaust plane. Both rakes contained vertical 

arrays of gas and aerosol probes mounted in alternate slots on 3.2 cm spacing. The left (#2) 

engine rake (L1, Figure 5), identical to those deployed during APEX-1, was mounted at a 45o

angle to provide additional clearance below the engine-mounting pylon. The L1 rake stand was 

bolted to the tarmac so that the probes were about 4 inches off the centerline and 1 m 

downstream of the crankcase vent tube. L1 was populated with water-cooled inlet probes 

(Figure 7) and sensors of the style used during APEX-1 (Wey et al., 2006); these were designed 

by Robert Hiers and Robert Howard of the Air Force’s Arnold Engineering Development Center 

(AEDC) for use in sampling emissions from military aircraft engines. 
23

 

Figure 4. Diagram of the near-field gas and aerosol sampling systems. The heated gas sample 

transport tubes are indicated in red, the unheated aerosol in blue.

The inset in Figure 5 shows the L1 probe/sensor layout, with a thermocouple mounted in the top 

slot, followed in descending order by two particle probes, four gas probes, two more particle 

probes, a fifth gas probe, a second thermocouple and a ram pressure tap. The particle probes 

were designed to allow introduction of a concentric flow of dilution gas just downstream of the 

tip (see Figure 7) to prevent water and volatile aerosol condensation and suppress particle 

coagulation processes within the sample flow. The aerosol probes have 1-mm inlet diameters 

and the flow is gradually expanded into 8.5-mm or 9.5-mm O.D. tubing downstream of the 

dilution zone. The "gas" probes have 1.27-mm diameter tip openings, which rapidly expands to 

the internal diameter of thin-walled tubing a few inches back from the inlet tip. The probes and 

rakes are constructed from 316 Stainless Steel and were found to maintain integrity throughout 

the many hours of testing conducted during APEX-1. Subsequent tests have shown that the 

aerosol probes transmit particles with 80% or better efficiency over the size range (10 to 300 nm) 

typically associated with aircraft particle emissions. The gas probes were installed in positions 

near the engine centerline with the intent of collecting samples of essentially identical 

composition for analysis by the two gas-phase measurement groups (NASA and AFRL). The 

four particle probes were connected to a valve box and were alternately sampled during the 

exhaust mapping experiment to examine the variability of emission parameters across the #2 

engine exit plane.
24

Figure 5. Sampling stand and inlet rake used behind the left inboard (#2) engine; inset shows 

arrangement of gas (G) and particle (P) probes and sensors (thermocouple and pressure tap) in 

the water-cooled rake.

The more complex right engine rake (R1) was developed by AEDC with support from the

Strategic Environmental Research and Development Program (SERDP) for use in characterizing 

emissions from the Joint-Strike Fighter, a military aircraft with afterburner capability. Pictured 

in Figure 6, this rake has a very small frontal profile (i.e., low drag) and was mounted on a 

traversing table, which made it possible to move the rake in discrete horizontal increments across 

the exhaust plane to examine crank-case emissions emanating from the center vent tube as well 

as to establish the variability of emission parameters across the breadth of the engine. 

A close-up photograph and probe/sensor placement diagram for R1 is shown in Figure 8. The 

R1 rake body had multiple channels in the leading edge to allow circulation of cooling water. 

Note that R1 supported eight gas probes and six dilution probes, with the gas probes being 

divided between NASA, AFRL and ARI. The R1 probes were internally similar to the L1 

probes, but lacked outer jackets for cooling water circulation. A vertical bar was attached to the 

translation stage just outboard of R1 to support three additional large-diameter, "gas"-type inlet 

probes. These were used to supply high flows of undiluted air directly to the UCSD and CMU 

teams for filter sample collection. 
25

Figure 6. The traversing rake (R1) used to sample emissions behind the right inboard (#3) 

engine.

Figure 7. At left, cross-sectional diagram of AEDC dilution probe showing the sample, water 

and diluents flow paths around the inlet tip. APEX-1 style gas and aerosol inlet probes used in 

L1 shown at right.
26

Figure 8. Closeup of R1 showing the "button-hook" and two, large-diameter inlet probes 

mounted adjacent to the multi-probe rake in the lower left-hand corner. The diagram at right 

shows the placement of gas (G) and particle (P) probes in the primary rake.

Thermocouples were affixed to the outside of R1 to record exhaust gas temperatures; impact 

pressure was measured on the R1 pitot tube as well as on the individual gas probes when they 

were valved-off from the sample flow line. These data were used to estimate plume velocity

and, in conjunction with co-located CO2 measurements, to determine which of the probes were

located within the core flow exhaust flow. The R1 traversing stand was bolted to the tarmac 

such that the probe tips were about 1 m behind the center-body of the engine—this gave more 

than 30 cm clearance between the top of the rake and the lowest point of the engine-mounting 

pylon. 
27

Figure 9. At left, the identical inlet probes and tripod stands used to sample exhaust emissions at 

30-m behind the DC-8’s #2 and #3 engines. The image at right shows the 1.9- and 5-cm inlet 

tubes used to deliver sample to the community aerosol sample manifold and EPA trailer, 

respectively.

Pictured in Figure 9, the left and right 30-m sample inlets, L30 and R30 respectively, were 

attached to heavy-duty steel tripods, which were in turn bolted to the concrete pad using lag 

screws and lead anchors. Two separate inlets were used on each stand: the EPA inlet which was 

constructed of 5-cm diameter stainless steel sanitary tubing and the community aerosol inlet, 

which used 1.9-cm seamless, electro-polished, stainless steel tubing. Because R30 was used to 

sample emissions from the primary test engine, it was instrumented with a pitot tube and a 

thermocouple to allow determination of plume velocity and temperature. It also was equipped 

with a port for introducing of dry N2 dilution gas near the probe tip to investigate sample line 

chemistry, moreover to address the question of whether a majority of the volatile aerosol mass 

forms during sample transport through the long sample lines. 

Figure 4 shows the layout of the gas and aerosol sample transport systems. As can be seen in the 

diagrams of Figures 5 and 6, separate gas inlet probes were used to supply sample to NASA and 

AFRL instruments. The NASA probes on the 1-m rakes were connected with 2-3 m long, 

insulated 6.3-mm stainless tubing to heated valve boxes located at the base of the stands; the 

boxes were designed to force a small amount of purge gas out of each non-selected probe tip. 

Sample flow from the two valve boxes was transported through heated 9.5-mm stainless 

temptrace tubing to heated sample selection valves located ~1-m from the diagnostic instruments 

housed in the AEDC trailer. Total line lengths for the L1 and R1 sampling probes were less than 

the 70-ft limit specified for ICAO certification tests. Flow from the AFRL sampling probes was 

transported through 6.3-mm stainless temptrace line to a 6-port, heated valve box located near 

the Aircraft’s right wing tip, then through additional 6.3-mm heated lines to gas and aerosol 

sensors located in the AFRL trailer. 
28

Figure 10. Aerosol selection and distribution system located in the MST trailer. Critical flow 

orifices were teed off the 30-m sampling lines and plumbed to a vacuum pump to draw a 

continuous flow through the lines to reduce stagnation problems and the time necessary to 

establish equilibrium concentrations.

Exhaust air collected using L1 and R1 particle probes was transported through 2 to 3 m of 9.5-

mm stainless tubing to unheated, 6-port valve boxes located at the base of the rake stands. These 

boxes also directed dilution air to the individual probes through 6.3-mm stainless tubing and 

contained bypass flow valves, which delivered purge-gas flow to the probe tips that were not in 

use. Sample flow from the two 6-port valve boxes was transported through 1.9-cm stainless 

tubing to a multiport automated sampling manifold located in rear of the MST trailer (Figure 10). 

Overall transport tubing lengths were about 40 m for the #2 engine and 23 m for #3; this yielded 

sample residence times that, depending on sample line pressure and dilution flow rates, varied 

from about 5 to 15 seconds. The 30-m community inlets were connected to the sample manifold 

using a combination of unheated 1.9-cm stainless and 1.9-cm, conductive PTFE tubing; the lines

were attached to the concrete pad in areas where it passed beneath the engine plume with adel

clamps and lead anchors. Transport line lengths for L30 and R30 were 46 m and 38 m, which 

resulted in nominal sample residence times of 12 to 20 seconds. The 30-m EPA inlets were 

connected with 5-cm diameter stainless steel, sanitary tubing to an electrically-actuated selection 

valve located just outside the group’s trailer. A high volume (1.1 m3

/min) of sample was drawn 

through the selected inlet using a Roots blower attached to the terminal end of the sample line; a 

9.5-cm stainless tube inserted into the 5-cm sanitary tubing just ahead of the blower was used to 

deliver sample flow to the EPA instrument suite.

All lines, valves, and inlet probes were thoroughly cleaned and inspected prior to use. Pressure 

and vacuum leak checks were performed on both the gas and aerosol systems with the goal of

reducing the leakage rate to < 0.1% of total flow. In addition, integrity of the aerosol transport 

system was checked by placing High Efficiency Particulate Air (HEPA) filters on the inlet 

probes and counting the number of particles in flow drawn from the downstream manifold; 

values <10 cm-3 are generally acceptable, assuming ambient counts are on the order of 104

cm-3. 
29

3.09 Downstream Sampling

To study the effects of sampling lines on volatile aerosol formation and nonvolatile aerosol 

characteristics, instruments were placed in a sturdy enclosure that was bolted to the tarmac 

immediately behind R30. Nicknamed the "death box" because of its precarious position within 

the engine exhaust plume, the enclosure shown in Figure 11 was designed and constructed by 

AEDC and consisted of a 5-cm aluminum angle framework with 6.3-mm aluminum sides and 

top. Its components were screwed together with 1⁄4-20 bolts spaced about 20-cm apart on the top 

and sides. Lock washers were installed on the bolts after many of those holding down the top 

backed out and were blown down the tarmac during the initial engine tests. The Deathbox 

instruments (see Table 3) drew samples through a 1-m long, 9.5-mm diameter stainless tube that 

faced forward and was affixed to the side of R30. Power cables and RS232 signal wires were 

run out to the box from the NASA truck; data from the instruments were monitored and recorded 

by an operator sitting in this location.

Figure 11. R30 with the "Death-box" instrument enclosure bolted to the tarmac immediately 

downstream.

Figure 12 shows that trailers and inlets that were set up about 145 m behind the DC-8 engine 

exhaust plane to examine the composition of engine exhaust as it further aged and mixed with 

background air. The trailer shown on the right of the figure was supplied by MST and contained 

gas phase instruments fielded by ARI and Harvard; the left-hand "toy-hauler" trailer was 

provided by NASA Dryden and used to house aerosol instruments operated by MST, NASA, and 

UTRC. Aerosol samples were collected from the exhaust plume using a 5-cm sanitary-pipe inlet 

provided by the EPA. A small blower was attached to the distal end of the 5-cm stainless-steel 

line to draw a continuous flow of sample through a section of tubing positioned just below the 

toy-hauler window that contained a number of 9.5-mm Swagelok fittings for withdrawing 

samples from the primary flow. Short lengths of 9.5-mm or 13.2-mm OD stainless tubing were 

connected to the fittings and used to deliver sample to the suite of aerosol instruments (see Table 

4 for a list) housed in the toy-hauler and to a small set of conventional gas analyzers located in 

the other trailer. A separate inlet was used to collect gas samples for the more sensitive,

Harvard/ARI diode-laser spectrometer instruments. Shown in the inset within Figure 12, this
30

probe was designed to deliver calibration gases near the inlet tip and to reduce sample pressure to 

better preserve reactive gas species such as HONO and H2O2 during transport through the long 

sampling lines. 

Figure 12. Downstream equipment trailers with the 145-m inlet shown in the foreground and 

inset photo.

Additional downstream exhaust composition measurements were made during a number of the 

engine tests using the ARI mobile laboratory. Shown in Figure 13, the lab drew air samples 

through a 1.9-cm Swagelok chassis fitting mounted just above the windshield on the driver’s 

side. Power was supplied power by a portable diesel generator hitched behind the van. Carrying 

the instruments listed in Table 3, the van was de-coupled from the main aerosol sampling system 

during the "intermission" idle runs and used to perform a series of plume penetrations starting as 

far down stream as possible and gradually closing to within a few meters behind L30 and R30. 

The van operators were careful to avoid sampling the van and generator exhaust plumes and 

were required to move the van out of the near-field exhaust plume once the high-engine-power 

testing resumed. 
31

Figure 13. ARI mobile laboratory with diesel generator hitched to the back.

3.10 APU Sampling

As described above, the APU is located in the forward baggage compartment and is essentially a 

small, low-technology, gas-turbine engine. When powered, its exhaust is mixed with bleed air 

and blown out through a shuttered port on the starboard side of the aircraft, just ahead of the 

wing spar. The APU exhaust duct is angled downward so that the blast hits the tarmac about 10 

m out from the aircraft fuselage. The inlet probes shown in Figure 14 take this into 

consideration and were designed and positioned to collect sample in the center of the exhaust 

plume. As can be seen in the photo, the inlets were constructed on site and consisted of stainless 

steel tubing strapped to a vertical stand with hose and adel clamps. The gas sample inlet was

constructed from an insulated 1.9-cm diameter, insulated stainless steel "Y" (with one leg 

capped) that connected to a heated sample line <1-m downstream of the tip. The heated tubing 

transported sample to the NASA gas-instrument rack in the AEDC trailer and met the length, 

diameter, and temperature requirements for engine-emission certification tests. Community 

aerosol samples were also collected using a 1.9-cm diameter stainless "Y", but here dilution gas 

was injected into the leg of the "Y" facing away from the exhaust port to prevent particle 

coagulation and water condensation. The diluted sample was transported through unheated, 1.9-

cm diameter flexible PTFE and stainless tubing to the aerosol sample distribution manifold 

located in the MST trailer. The EPA collected aerosol samples through a separate 1⁄2-in

diameter, unheated stainless tube that ran directly to their instrument suite; a Swagelok "T" was 

placed in the tube near to the base of the inlet stand and used to inject dry N2 dilution gas to 

reduce condensable gas concentrations and prevent particle coagulation. 
32

Figure 14. The photo on the right shows the inlet probes used for sampling exhaust from the 

DC-8 APU. On the left, members of the AAFEX science team erect the inlet stand and adjust 

its position to align the probes with the exhaust flow.

3.11 Aircraft Fueling

Figure 15 shows a diagram of the DC-8 fuel system. The fuel capacities for the tanks are: 1 and 

4 mains, 3100 gals each; 1 and 4 alternates, 1740 gals; 2 and 3 mains, 4700 gals; center auxiliary, 

4400 gals; and forward auxiliary, 2100 gals. Valves isolate the tanks from one another so that it 

is possible to run each engine from a separate fuel tank. During AAFEX, JP-8 was loaded in the 

center and #2 main tanks and the test fuel was pumped into the #3 main tanks, which allowed us 

to burn JP-8 in the #2 engine and alternative fuel in #3. This made it possible to contrast the 

emissions from the two engines to more accurately delineate ambient- from fuel-related changes 

in emission characteristics.
33

Figure 15. DC-8 fuel system.

Aircraft fueling was accomplished using the following available fuel tanker assets:

• FT1 tank truck (Air Force)

• FT2 tank truck (Air Force)

• Truck A, Fueling capable with 5,000 gal volume, 4,500 usable (NASA – K&A)

• Truck B – Fuel/defuel capable with 5,000 gal volume, 4,500 usable (NASA – K&A)

• Truck C – Fuel/defuel capable with 5,000 gal volume, 4,500 usable (NASA – K&A

• 8,000 gallon Tanker (NASA – K&A)

• 1,000 gallon Fuel Bowser (NASA – K&A) – all fuel in Bowser handled as waste fuel

• 4,000 gallon Waste Fuel Truck (NASA – Health & Safety)

Prior to the AAFEX, Air Force tanker trucks arrived on site carrying the FT1 and FT2 fuels; 

these stayed on site for the duration of the mission. Fuel remaining in the aircraft tanks from 

previous operations was drained into the 8,000-gallon tanker to be reused after AAFEX. Fuel 

trucks A, B, and C were drained and cleaned and had their fuel filters replaced. Dryden 

purchased 20,000 gallons of a single batch of JP-8 fuel from Air Force Plant 42 at Edwards AFB. 

Using truck A to pick the fuel, 15,000 gallons of the JP-8 was transferred into the DC-8 centerand #2 main tanks. Transferring directly from the Air Force tanker trucks, 3,500 gallons of the 

FT1 and FT2 fuels were loaded onto fuel trucks B and C, respectively. Neither of the FT fuels 

were loaded onto the aircraft prior to test initiation because of concern (justified) that long 

exposure to the aromatic-hydrocarbon-free fuels would cause fuel system seals to shrink and 

create leaks.
34

Fuel samples were collected from the #3 main fuel drain before and after each of the test runs 

listed in Table 6 below. The samples were subsequently shipped to the AFRL fuels lab at 

Wright Patterson AFB and analyzed for the parameters listed in Table 2 above. 

At the conclusion of the initial JP-8 tests (runs 1-4 in Table 6), fuel was transferred from the #3 

main into the outboard main and alt fuel tanks and residual fuel in the pumps and fuel lines was 

drained into the bowser truck, which was subsequently dumped into the waste fuel truck. Next, 

3,000 gallons of FT1 was transferred into the #3 main from fuel truck B. To prepare for the 

upcoming "blended" fuel test, 800 gallons of FT1 was transferred into the truck B from the AF 

tanker and was topped off with 1,300 gallons of JP-8 from truck A and was circulated for 15 

minutes to create a 50:50, FT1:JP-8 mixture. 

At the end of the FT1 tests (5 and 6), the residual fuel in #3 main was drained into the bowser 

truck and was replaced with blended fuel from truck B. When the blended fuel run (7) was 

complete, the residual fuel was transferred to aboard tanks and the fuel pumps and lines were 

drained into the bowser truck for disposal. 

Just prior to test 9, 3,000 gallons of FT2 fuel was transferred from truck C into the #3 main tank. 

Afterward, 500 gallons of FT2 from the AF tanker and 1,300 gallons of JP-8 from truck A were 

added to truck C to create the 50:50 blend. After test 10 was aborted due to a fuel leak on #3 

main, residual FT2 fuel was drained into the bowser truck for disposal and was replaced with 

3,000 gallons of the FT2-JP-8 blend. 

During tests 12 and 13, JP-8 fuel was burned in the #3 engine. To balance the fuel load and 

provide enough fuel to complete the tests, an additional 1,500 gallons of the same batch of JP-8 

was purchased from the Edwards AFB and loaded into the #3 tank from fuel truck A. During 

test 13, blended fuel from one of the alt tanks was burned in the #2 engine to reduce waste and 

conserve JP-8.

The DC-8 APU draws fuel from the #2 main tank. After APU emission test 15, it was thus 

necessary to transfer JP-8 from the #2 tank to an outboard tank, drain the sumps into the bowser 

truck, and load the #2 main with ~500 gallons of FT2.

At the conclusion of all tests, fuel trucks B and C were drained into the waste truck, cleaned, and 

then had their filters replaced. All FT or blended fuel remaining on the DC-8 was drained into 

the waste truck and replaced with JP-8 from truck A. Afterward, the engines and APU were run 

at idle for 15 minutes to purge the fuel lines and pumps of residual FT and blended fuel.

3.12 Engine Test Runs

About 30 minutes prior to engine start, a short briefing was held to review the test objectives, test 

matrix and safety procedures. The crew and test conductor (Dan Bulzan) then boarded the 

aircraft and established communications with the distributed investigators via headset. Once all 

participants were ready, the crew started the APU, which was subsequently used to motor the #2 

engine. Once both inboard engines were stable at ground idle, the test conductor announced the 

beginning of the overall test point and recorded engine fuel flows, temperatures, fan speeds, etc. 
35

As operators of the community aerosol sampling manifold, MST selected the aerosol sampling 

probe, adjusted sample dilution flow (if necessary), announced when aerosol concentrations were 

stable, and logged the start time of the data point. After two minutes of sampling time, the 

project scientist (PS) polled the investigators to determine whether their sampling requirements 

had been satisfied. When all agreed, the MS requested that engine power be adjusted to that 

required for the next data point and the process described above was repeated. If at any time a 

safety issues arose, testing was halted and the engines were shut down as quickly as possible.

Table 6 lists the engine and APU test runs that were conducted during AAFEX; Table 7 and 

Figure 14 provide the meteorological context of the tests. In all, 16 separate tests were 

performed between January 27 and February 2, with 13 focusing on engine emissions and 3 

sampling exhaust from the APU as it burned either JP-8 or FT-2. The tests required almost 35 

hours of DC-8 engine operations and just over 3 hours of separate APU runtime. 

As indicated in the Table 6, test 1 was a "shakedown" run to assess the integrity of the sampling 

system and to check for problems with the sampling protocol, dilution procedures, etc. During 

this and all subsequent tests, observers were stationed at strategic locations to quickly identify 

and communicate to the aircraft operators any problems that arose with either the engines or 

sampling system installation. Video cameras were also used to monitor the integrity of the rakes 

and inlet probes from within the AEDC equipment truck. Any time loose or vibrating 

equipment were spotted, the engine was shutdown as quickly as possible and potential remedies 

were discussed and implemented. 

After a installing additional tie-downs on sampling lines that either came loose or showed 

excessive movement during the shakedown test, test 2 was conducted to examine the distribution 

of emissions across the #2 and #3 engine exhaust planes to establish which of the aerosol and gas 

probes resided within the core region of exhaust and to determine which locations were 

susceptible to engine oil contamination. Aerosol and gas phase measurements were made on 

samples drawn from each of the L1 and R1 probe tips at power settings of 4, 30, and 65% of 

maximum rated thrust. In addition, R1 was translated laterally to characterize emissions to the 

left and right of the #3 engine center. As expected, results indicated that core flow extended out 

to ~10 in from the engine axis and that positions near the central vent tube were often 

contaminated engine oil. Oil contamination was particularly notable near the #3 engine 

centerline, possibly because the engine had a leaky seal that produced a slow drip of oil when it 

wasn’t in use. In any case, based on results of this mapping test, R1 and L1 were positioned 4 in 

to the left of engine center and probe tips 3 and 4 of each rake were selected for use in the 

subsequent emission characterization studies. 

Test runs 3-6 and 8-13 focused on characterizing the DC-8 engine emissions as a function of fuel 

composition and ambient temperature. Duplicate tests of the pure fuels (JP-8, FT-1, and FT-2) 

were conducted under warm and cold conditions to observe plume chemistry over the broadest 

temperature range possible. In addition, engine #2 burned JP-8 throughout the emissions 

characterization tests, which provided the opportunity to examine exhaust composition and 

plume chemistry under a wide variety of ambient conditions. 
36

Table 6. Aircraft Engine and APU Test Runs

Test 

No.

Test 

Date Test Objective Aircraft 

Engine

Engine 

Fuel

Engin

e 

Start

Engine 

Shutdown Sampled Thrust Levels (%)

1 26-Jan Equipment 

Shakedown

#2 JP-8 14:01

15:00

4, 45

#3 JP-8 14:03 4, 7, 30, 45, 65, 85, 100

2 26-Jan Exhaust Mapping

#2 JP-8 16:02

19:20

4, 7, 30, 45, 65, 85

#3 JP-8 16:04 4, 7, 30, 45, 65, 85, 100

3 27-Jan JP-8, warm 

conditions

#2 JP-8 12:38

15:46

4, 7, 30, 45, 65, 85

#3 JP-8 12:43 4, 7, 30, 45, 65, 85, 100

4 28-Jan JP-8, cold 

conditions

#2 JP-8 5:59

9:28

4, 7, 30, 45, 65, 85

#3 JP-8 6:03 4, 7, 30, 45, 65, 85, 100

5 28-Jan FT-1, warm 

conditions

#2 JP-8 12:35

15:54

4, 7, 30, 45, 65, 85

#3 FT1 12:39 4, 7, 15, 30, 45, 65, 85, 100

6 29-Jan FT-1, cold 

conditions

#2 JP-8 5:41

8:36

4, 7, 30, 45, 65, 85

#3 FT1 5:45 4, 7, 15, 30, 45, 65, 85, 100

7 29-Jan APU, JP-8 Fuel APU JP-8 12:34 13:57 EGT = 350, 610 °C

8 30-Jan FT-1/JP-8 Blend

#2 JP-8 6:14

9:38

4, 7, 30, 45, 65, 85

#3 FT1/JP8 6:19 4, 7, 15, 30, 45, 65, 85, 100

9 30-Jan FT-2, warm 

conditions

#2 JP-8 10:48

13:41

4, 7, 30, 45, 65, 85

#3 FT2 10:51 4, 7, 15, 30, 45, 65, 85, 100

10 31-Jan FT-2, cold 

conditions

#2 JP-8 5:57

7:03

4, 7, 30, 45, 65, 85

#3 FT2 5:42 4, 7, 15, 30, 45, 65, 85, 100

11 31-Jan FT-2/JP-8 Blend

#2 JP-8 8:28

10:59

4, 7, 30, 45, 65, 85

#3 FT2/JP8 8:31 4, 7, 15, 30, 45, 65, 85, 100

12 31-Jan JP-8, warm 

conditions

#2 JP-8 12:49

15:18

4, 7, 30, 45, 65, 85

#3 JP-8 12:52 4, 7, 15, 30, 45, 65, 85, 100

13 2-Feb JP-8, cold 

conditions

#2 JP-8 7:12

8:38

4, 7, 30, 45, 65, 85

#3 JP-8 7:14 4, 7, 15, 30, 45, 65, 85, 100

14 2-Feb Sampling System 

Tests

#2 FT/JP-8 9:37

12:07

4, 7, 30, 45, 65, 85

#3 JP-8 9:40 4, 7, 15, 30, 45, 65, 85, 100

15 2-Feb APU, JP-8 APU JP-8 14:12 15:23 EGT = 345, 365, 475, 550, 555, 610 °C 

16 2-Feb APU, FT2 APU FT2 15:40 16:37 EGT = 360, 475, 550, 555, 620 °C 
37

Table 7. Meteorological Conditions during the AAFEX Test Runs

Start End Ambient T (deg F) Ambient %RH WSPD KNTS WDIR Solar Rad (W/m2) P 

(mB)

Test 

# Test Objective Date Time Time Med Min Max Med Min Max Med Min Max Med Med Min Max Med

1 Shakedown 26-Jan 13:52 15:00 8.7 8.1 9.3 48.0 45.6 51.6 15.3 12.6 21.9 292 528 266 650 925

2 Mapping 26-Jan 15:57 19:15 4.7 3.4 7.5 58.6 51.2 64.1 20.6 12.0 31.7 282 0 0 250 927

3 JP-8 Warm 27-Jan 12:34 15:34 9.3 8.6 10.2 22.9 18.6 28.0 5.8 1.4 14.0 45 609 343 738 939

4 JP-8 Cold 28-Jan 5:53 9:25 -1.0 -4.1 4.2 62.4 53.1 69.8 3.9 1.2 8.7 246 128 0 485 938

5 FT1-Warm 28-Jan 12:35 15:49 13.9 11.3 15.2 23.6 20.8 27.8 3.9 0.8 6.7 321 580 286 726 935

6 FT1-Cold 29-Jan 5:34 8:34 0.9 -0.9 5.3 60.9 53.8 69.7 6.7 0.7 12.2 316 14 0 325 937

7 APU-JP8 Test 1 29-Jan 12:58 13:50 17.4 16.8 17.7 14.7 11.9 18.9 12.7 9.8 16.3 58 677 608 729 936

8 FT1/JP-8 Blend 30-Jan 6:07 9:36 3.4 -0.9 9.4 47.8 30.3 57.3 4.6 1.1 10.3 222 182 0 529 938

9 FT2-Warm 30-Jan 10:45 13:45 16.8 12.7 18.2 22.2 18.3 28.9 6.6 1.9 12.4 57 734 656 755 937

10 FT2-Cold 31-Jan 5:35 7:05 -1.2 -2.6 0.3 70.5 65.1 79.4 2.6 0.5 5.9 209 0 0 18 932

11 FT2/JP8 31-Jan 8:25 11:00 10.9 7.1 14.6 38.9 30.6 54.3 4.4 0.5 9.3 318 554 304 717 933

12 JP-8 

Warm/Mapping 31-Jan 12:55 15:20 18.9 17.5 20.1 20.0 17.2 23.7 2.9 0.7 5.8 175 616 405 740 930

13 JP8 Cold 2-Feb 7:10 8:36 5.5 0.9 6.6 45.4 41.8 54.7 3.1 0.5 7.3 241 198 39 351 938

14 Dilution/Probe 

Comp 2-Feb 9:40 12:10 12.8 9.6 16.3 29.3 22.5 34.1 6.3 3.0 10.9 330 720 555 773 938

15 APU-JP8 2-Feb 14:11 15:25 20.1 19.5 20.6 8.1 6.9 9.5 7.5 5.3 9.9 60 520 403 621 934

16 APU-FT2 2-Feb 15:35 16:40 19.6 19.2 20.0 9.4 7.8 12.0 5.6 4.0 8.4 54 252 133 368 934
38

Figure 16. Ambient temperature recorded by the portable weather station that was deployed to 

the AAFEX experiment site. The blue trace corresponds to the times during which the indicated 

experiments were being conducted.

Figure 17. Typical test matrix for the fuel characterization studies.
39

Figure 15 shows a typical experiment matrix for the fuel characterization tests. The power 

settings followed an up and down stair-step pattern with idle runs at the start, middle and end to 

assess variations in the engine’s emission characteristics over time and with changing ambient 

conditions. In cases where the #3 engine fuel was changed just before testing, a 5-min run at 

30% power was included just after engine start to clear the fuel pumps and supply lines of fuel 

from the previous test. Exhaust concentrations of SO2 were monitored in these cases to 

determine the engines emission exhibited characteristics of the new fuels. 

Aerosol sample was typically drawn from L30 during engine start-up (because as noted in table 

6, the #2 engine was started first) while purge air was expelled out each of the 1-m rake tips. 

Once the engines were stable at 4% thrust, sample was alternately drawn for ~3 min from each of 

the inlet probes. Samples from the 1-m rake tips were diluted with dry nitrogen to achieve a 

dilution ratio of about 10:1 as judged from sample CO2 mixing ratio. Once satisfactory 

measurements had been acquired from each sampling probe/rake, engine thrust was increased to 

the next power setting and the sampling process was repeated. Power settings of 4, 7, 15, 30, 

45, 65, 85 and 100% of maximum rated thrust were typically included in test matrix and were 

accessed in the stair-step pattern shown in Figure 15. After a brief "intermission" at 7% power to 

allow participants to adjust equipment and take a comfort break, the power progression was 

repeated in reverse, but only allowing time to sample from R30 and R1. Note also that the 2-

min limit on operating the engines at takeoff thrust only allowed time to drawn sample from R1 

and R30 during the two high power engine runs. 

As shown in Table 6, the fuel characterization tests typically required about 3 hours to complete. 

The exceptions were test 10, where the fuel system developed a leak and testing was suspended 

after the first set of power settings was complete, and test 13, where sampling was restricted to 

L30 and R30 to examine plume chemistry under cold conditions.

During AAFEX and previous engine emissions tests, a number of questions arose regarding 

sampling system design, the effects of the sampling probes on gas and particle concentrations 

and properties, and the source of differences between various measurement teams. Test run 14 

and a portion of run 13 were designed to address some of these questions including: 

• Is it necessary to dilute aerosol samples near the probe tip (i.e., use a special "particle"

probe), or can dilution gas be injected into sample collected by a standard gas probe at 

some point downstream?

• Does anisokinetic sampling affect large particle concentrations at high engine powers?

• Can the differences between the NASA and AFRL gas phase measurements be attributed 

to differences in probe location?

To address the gas vs. aerosol probe question, prior to run 14 gas probe #3 on R1 was replumbed to introduce a stream of dry N2 about 1 m downstream of the inlet tip. Sample and 

dilution lines were then plumbed into seldom-used ports on the 6-port aerosol sample selection 

box at the base of the probe stand. During the subsequent engine test, MST switched back and 

forth between the gas probe 3 and the adjacent particle probe 3 to obtain comparative particle 

number, size, and composition measurements. 
40

Isokinetic sampling issues were addressed during run 14 by measuring particle size distributions 

on R1 at 65 and 85% thrust as the dilution flow was varied. Increasing dilution flow reduces the 

differential pressure across the inlet tip, resulting in a greater mismatch between the exhaust 

plume and inlet flow velocities. Sample dilutions were varied by factors of 4 and 8 at 65 and 

85% power, respectively.

The initial part of test 12 explored whether the systematic differences seen between NASA and 

AFRL measurements could be caused by differences in probe location coupled with 

inhomogeneous distributions of species across the engine exhaust plume. The test involved 

making emission measurements from R1 probes as the rake was translated 20, 10, 5, and 0 cm 

off the #3 engine centerline. Data were recorded over the same stair-step power sequence 

shown in Figure 15. 

Tests 7, 15 and 16 were conducted to determine emission factors for the DC-8 APU and to 

examine how those factors changed with fuel composition. Because the APU fuel flow could 

not be changed in a systematic manner, different power settings were accessed by changing the 

APU workload and monitoring the EGT as a measure of engine thrust. Four operating modes 

were selected that yielded EGTs of approximately 360, 475, 550 and 660o

C: 1) idle or generator 

mode; 2) minimum air conditioning (A/C) pack; 3) medium A/C pack; and 4) motor engine. For 

a variety of reasons, only test modes 1 and 4 could be implemented during test 7. Tests 15 and 

16 included sampling in all modes as the APU burned JP-8 and FT-2 fuels, respectively. Full 

sets of aerosol measurements were recorded by all groups, but because of plumbing limitations, 

gas phase sampling was only performed by NASA and AEDC. Sampling procedures and 

protocols were similar to those employed in the aircraft engine tests. The test conductor 

coordinated load settings with APU operator, MST controlled sample dilution and called out the 

start of each run when CO2 mixing ratios had stabilized, and the PS monitored progress of the 

experiment groups in meeting measurement objectives and issued requests for new power 

settings to the test conductor. 

3.13 Engine Power Settings

The NASA DC-8 has an analog cockpit without readouts of the various pressures and 

temperatures that control the combustion process. The test point thrust settings therefore had to 

be set based on cockpit instrumentation, which limited the options to fuel flow and fan speed. If 

PM are primarily formed in the combustor, we ideally would have set fuel flows to replicate 

exactly the same combustor pressure, inlet temperature, fuel air ratio, airflow, and humidity each 

time we wanted to characterize emissions at a certain engine thrust setting. If ambient 

temperature, pressure, and humidity were always the same, either fuel flow or fan speed would 

be equally effective to set the points. However, there were big swings in ambient temperature 

during the test and combustor inlet conditions (pressure, temperature, fuel flow, and fuel air 

ratio) could not be exactly replicated as the ambient temperature changed. We note that as 

temperature increases, the air is less dense, so more airflow, pumped to a higher pressure and 

temperature, is needed to achieve a given level of thrust. These effects are not huge, 

but experience from fuels tests at GE indicate that changes in emissions due to variation in 

ambient temperature can be of the same magnitude as changes due to fuel properties.
41

Figure 18. Engine power as a function of first-stage, fan speed. The vales displayed in the box 

at left were used to set thrust levels during AAFEX.

On a warm day, if thrust level is set with fuel flow, combustor inlet pressure and fuel flow will 

be close to ISA levels, but combustor inlet temperature and fuel air ratio will be higher than ISA 

levels. If fan speed is used as the controlling parameter, fuel flow and combustor inlet pressure 

will be low, but combustor inlet temperature and fuel air ratio will be closer to ISA levels. Based 

on an analysis of APEX-1 test results which showed that fan speed came closest to replicating 

combustor inlet temperature and fuel air ratio and because the cockpit gauge could be read more 

accurately, AAFEX adopted the approach of setting thrust as a function of N1, the low-pressure 

compressor fan speed. This approach also allowed thrust settings to be set without considering 

how the different fuel density and heating values of the FT fuels affected fuel flow rate.

Figure 17 provides a plot of thrust as a function of N1 and shows the values that were selected to 

access thrust settings of 4 (ground idle), 7, 30, 45, 65, 85, and 100% of maximum RPM; a value 

of N1=37.5 was used for the 15% power point that was included in some of the test runs. 
42

4.00 OVERVIEW OF RESULTS

Measurement results obtained by AAFEX participants are included in the attached appendices. 

The sections below summarize important findings from these reports in a variety of areas 

including fuel and ambient temperature effects on engine performance and emissions, the effects 

of the sampling system on the emission measurements, and instrument performance. 

4.01 Engine Performance and Certification Gas Emissions

Appendix A, contributed by Wey and Bulzan from NASA GRC, describes the engine operating

data that was recorded in the aircraft cockpit and examines fuel effects on both standard-day, 

heating value-corrected engine performance parameters and certification gas emissions as 

measured with a conventional instrumentation suite. As shown in Figure 19, very little 

difference was observed in the levels of JP-8 and FT fuels required to produce the N1 (low speed 

fan) settings that corresponded to 4, 7, 30, 45, 65, 85 and 100% power points, suggesting that the 

alternative fuels offer no advantage or penalty in terms of fuel economy. However, the FT fuels 

exhibited higher combustion efficiencies at low fuel flow rates (Figure 19, right panel), 

indicating they are in general less polluting. Moreover, the only problem found in using the 

aromatic-hydrocarbon-free FT fuels is that they caused fuel system seals to shrink, which 

resulted in fuel leaks; the leaks went away soon after blended fuel was introduced to the tanker 

or aircraft fuel tanks. 

Figure 19. Fuel flow rate corrected to standard day conditions and fuel heating value versus N1 

(left) and fuel combustion efficiency as a function of corrected fuel flow rate (right). Data are 

for the DC-8, right inboard engine and are presented and discussed more thoroughly in appendix 

A.

Appendix A goes on to note that the FT fuels reduced NOx, CO, and total hydrocarbon (THC) 

emissions. As shown in Figure 20, the reduction in NOx is quite notable, especially for the FT1 

fuel at high engine powers. 

Fuel Flow, pph

0 2000 4000 6000 8000

Combustion Efficiency, %

95

96

97

98

99

100

101

FT2 Blend

FT1 Blend

FT2 (Sasol)

FT1 (Shell)

JP8
43 

Figure 20. NOx emission index plotted versus corrected N1(right) and CO emission index 

plotted versus corrected fuel flow rate (left). The "C" points correspond to ICAO certification 

values for the CFM56-2C engine. 

Figure 21. Exhaust gas temperature as a function of fuel flow rate (left panel) and EIm-NOx as a 

function of exhaust gas temperature (right panel) for the port and starboard engines studied 

during AAFEX. Plot taken from appendix B.

Appendix B, contributed by Aerodyne Research Inc., also examines fuel effects on the CO and 

NOX emissions data measured using quantum cascade laser and chemiluminescence instruments, 

respectively. After developing a protocol for analyzing emissions performance data for 

combustion of alternative jet fuels that accounts for fuel energy differences compared to JP-8, 

the authors found that, compared to JP-8 combustion, combustion of the FT fuels reduced EImNOX by 5-10% at high power and reduced EIm-CO by as much as 10% at idle. Further analysis 

showed, however, that the pollution reduction benefit of FT1 was significantly greater than that 

of FT2. The authors also note that for engine powers greater than 30%: NOx emissions increase 

with ambient temperature; EIm-NOx has similar slopes with respect to ambient temperature for 

N1, corrected

0 20 40 60 80 100

EINOx (g/kg-fuel)

0

5

10

15

20

C

C

C

C

FT2 Blend

FT1 Blend

FT2 (Sasol)

FT1 (Shell)

JP8

Fuel Flow, pph

0 2000 4000 6000 8000 10000

EICO (g/kg-fuel)

0

20

40

60

80

100

120

C C C

C

FT2 Blend

FT1 Blend

FT2 (Sasol)

FT1 (Shell)

JP8

800

700

600

500

400

Exhaust Gas Temperature (°C)

0.2 0.4 0.6 0.8 1.0

Fuel Flow (kg sec-1)

JP-8 data only

1m data only

"warm" data only

 stbd engine

 port engine

25

20

15

10

5

0

EIm-NOx (g kg-1

)

400 500 600 700 800

Exhaust Gas Temperature (°C)

JP-8 data only

1m data only

"warm" data only

 stbd engine

 port engine
44

the various fuels; and at any given temperature, the EIm-NOx value for FT1 was always less than 

for JP-8. The ambient temperature dependence of EIm-CO was similar for all fuels studied and 

was strongest for 4% thrust and nearly absent for power settings greater than 30%. Appendix B 

also notes that when both engines burned JP-8 fuel, the portside engine generated greater NOx

and less CO emissions than the starboard engine. By examining simultaneous engine operating 

parameter measurements, the authors show that the differences in emissions were caused by the 

propensity of the portside engine to have higher exhaust gas temperatures (EGT) than the 

starboard engine at fuel flow rates above idle (see appendix B). They further observe that the 

two engines operated at different fuel flow rates and fan speeds (N1 and N2) to achieve the same 

nominal thrust level and suggest that the overall differences in emissions and operational 

characteristics are consistent with predictions from an aircraft engine aging model described in 

recently published literature. 

4.02 Trace Gas Emissions

Aircraft are a significant source of hydrocarbon species and hazardous air pollutants that can 

impact local air quality. To evaluate the effect of alternative fuels and ambient conditions on 

these emissions, Montana State University and ARI deployed a tunable infrared laser differential 

absorption spectrometer (TILDAS) and highly sensitive proton transfer reaction mass 

spectrometer (PTR-MS) to assay a large suite of VOCs including formaldehyde, acetaldehyde, 

methanol, ethene, propene, benzene, toluene, phenol, styrene and naphthalene that together 

account for about 50% of the total nonmethane hydrocarbon emissions from a typical engine 

burning JP-8. Results of these measurements are presented in appendix C. 

Figure 22. Comparison of ethene-nomalized EIs measured at AAFEX with respect to those 

reported by Spicer et al. (1994). Plot taken from appendix C.
45

Figure 22 summarizes the fuel dependencies for a number of important species; the values are 

normalized to EIs for a similar engine as reported by Spicer et al. (1994). The authors indicate 

that ethene EIs were fortuitously similar for the three different fuels and that for JP-8, AFFEX 

values for all species were within +35% of those reported in the earlier work. They further 

indicate that FT1 and FT2 engine exhaust had very different composition and that aromatic 

emissions are reduced, but not eliminated during FT1 fuel combustion, which, because FT1 was 

devoid of aromatic components, indicates that aromatic compounds were being formed during 

the combustion process. The discussion indicates that C1-C3 species (principally formaldehyde, 

ethene, propene and acetaldehyde) account for >70% of the measured mass emissions for all 

fuels. The authors further observe that a significant fraction of the emissions were contributed 

by carbonyl species (i.e., formaldehyde), which are not effectively measured by the instruments 

used for THC emission certification. In addition, they note that the EIs for all measured species 

were lower for FT1 than FT2, which is consistent with the lower relative THC EI reported for 

FT1 in Appendix A. FT2 emissions of C3 and C4 hydrocarbons species are noted to be 

substantially higher than for JP-8, and partially offset the reduced aromatic emissions for that 

fuel. A more detailed analysis shows that the total measured hydrocarbon emission ratios in 

units of ppbC/ppmCO2 for JP-8, FT1 and FT2 were 2.79, 2.17, and 3.74, respectively, which 

indicates that for total VOC emission the fuels rank FT1 < JP-8 < FT2, a surprising result since 

both the alternative fuels were anticipated to burn much cleaner than JP-8. 

Appendix C also examines the temperature dependencies of the hydrocarbon emissions and finds 

that for all measured species and at low power settings, EIs always increased with decreasing 

ambient temperature. As an example, Figure 23 shows plots of ethene and formaldehyde (and 

total particle mass) emissions versus ambient temperature constructed from data acquired during 

AAFEX and several previous missions; values are normalized to the EI measured at 288 K. For 

both species, values increased by about a factor of two in going from 288 to 273 K; similarly, 

normalized values declined by ~50% as temperature increased from 288 to 303 K. These 

observations underscore the need for specifying the ambient temperature range when reporting 

aircraft engine hydrocarbon emission parameters. 

DC-8 starboard engine hydrocarbon emissions measurements from AAFEX and APEX-1 are 

additionally compared in appendix C. The authors note that the ratio of ethene emissions at 4% 

and 7 percent power was about 2 during AAFEX and 3 to 5 during APEX-1. They suggest that 

differences in actual power settings between the two experiments could explain the dissimilarity 

in the emission ratios. However, the authors also note that the DC-8 engines were re-built just 

prior to the 2004 APEX-1 mission whereas they had been in service for five years prior to 

AAFEX. A more detailed analysis shows that total hydrocarbon emissions at 7% power and 

288 K and in terms of ppbC/ppmCO2 was ~2.79 during AAFEX as opposed to ~1.8 during 

APEX-1. This, along with the observation that AAFEX 7% EICO values were substantially 

higher than ICAO certification values (58.5 versus 30.7 gkg-1, respectively), indicates that the 

starboard engine emissions performance had substantially degraded during the period between 

the two experiments.
46

Figure 23. Plot of normalized (to corresponding EIs measured at 288 K) emissions versus 

ambient temperature take from appendix C. The units to the three x-axes starting from bottom 

are F [not U], C, and K. The large green points with red cores represents aerosol mass emissions 

as measured with an Electrical Exhaust Particle Sizer (EEPS). Plot is from appendix C.

4.03 Plume Chemistry

Appendix D, contributed by Harvard and ARI, examines nitrous acid (HONO) and nitrogen 

oxides (NOx) emissions measured approximately 140 m downwind of the grounded aircraft using 

an advance quantum cascade-laser spectrometer and chemiluminescence instruments, 

respectively. They found that HONO EIs increased approximately six-fold from idle to take-off 

conditions, but leveled off between 60 and 100% engine power reflecting the point at which 

HONO production (reaction between NO and OH) and loss (reaction with OH and HONO selfreaction) reached equilibrium. The authors note that HONO EIs observed at the 140 m trailer 

showed no particularly dependence on fuel type regardless of engine power setting, and unlike 

NOx emissions, did not vary with ambient temperature. A suggested explanation for the 

temperature independence is that the dominant HONO production and loss mechanisms 

(reactions with OH) are insensitive to temperature, which may be the case if the OH radical was 

the limiting reactant and its production had no temperature dependence. HONO EIs were also 

found to be invariant with solar insolation, which indicates insignificant photochemical loss or 

production within the exhaust plume. To the authors, this, along with a lack of dependence on 

wind speed or direction (factors that effect plume age), suggests that HONO was produced 

primarily within the engine, a result that is consistent with previous investigations. 
47

The speciation of NOy within the exhaust plume at 140 m is also examined in appendix D (see 

Figure 23). The authors found that HONO to NOx ratios increased from 3% at idle to 7% at 

mid-power settings before decreasing to less than 4% at maximum thrust. They note these 

observations are at odds with results from previous studies which report ratios of around 7% at 

idle that monotonically decrease to values that are a factor of 3 lower than AAFEX ratios at 

maximum thrust. In addition to the simple explanation that these differences could be due to 

differences in engine types or ages, the authors suggest that problems with the previous data sets 

caused by sampling losses due to thermal dissociation, adsorption on metal probe/tubing 

surfaces, HONO self-reaction at high mixing ratios or poor thermal control leading to cis to trans 

conversion, or incomplete HONO formation linked to sampling near the engine exit plane could 

account for the disparity in the observations. 

Figure 24. HONO EIs from the Aircraft Particle Experiment 3 (APEX-3, black), corrected for 

linestrength (grey), overlaid on top of observations from AAFEX (red). Emission indices for 

NO2 (blue) and NO (green) from APEX3 are added on top of that of HONO. Taken from 

appendix D. 

A bonus feature of appendix D is the first reported measurements of H2O2 EIs in an aircraft 

exhaust plume. During AAFEX, the investigators serendipitously discovered absorption lines 

for this species in TDL spectra and quickly devised a calibration scheme to allow for quantitative 

measurements. Although offering a variety of caveats regarding the precision and accuracy of 

the measurement, they report EIs of 0.43+0.31 (2s) g H2O2 kg fuel burned at idle and that values 

decrease to below detection limits at power settings greater than 20% of maximum rated thrust. 

From the observed power dependency and other AAFEX gas-phase specie observations, the 

authors suggest that HO2 not OH is the primary H2O2 precursor in aircraft exhaust, which is an 

important finding that validates a proposed mechanism for HOx production in combustion 

plumes. 

Appendix E, contributed by ARI, Harvard and MSU, further explores plume chemistry using a 

variety of measurements recorded in the ARI Moble Laboratory (AML) as it made multiple 
48

plume penetrations at downwind locations. The investigators note that, unlike most combustion 

sources, idling aircraft emit NOx primarily in the form of NO2, which can lead to greater ambient 

levels of both O3 and NO2 than primary NO emissions. Drawing from the AML AAFEX data 

set, they provide several examples (see Figure 25) that show O3 production in aged idle plumes 

and O3 depletion in high thrust plumes where NO dominates the NOx budget. Although 

anticipated, these were, to the investigators’ knowledge, the first observations of O3 generation in 

a fresh aircraft engine exhaust plume. 

Figure 25. Time series of C2H4, O3, NO, and NO2 measured downwind of the NASA DC-8 

during high engine power (up until 13:01) and low engine power (after 13:01). Taken from 

appendix E. 

From the slope of a [NO2]+[O3] versus [NOx] plot the investigators also infer there was net 

conversion of NO to NO2 in some of the fresh exhaust plumes and suggest this occurs through 

NO reaction with HO2 and RO2 (peroxy) radicals, which in turn are formed through the reactions 

of OH and VOCs with OH radicals. It is noted that H2O2, which is formed primarily by HO2

self-reaction, is elevated at idle, consistent with the observed net oxidation of NO to NO2 at low 

engine power settings. The investigators then present a detailed analysis of peroxy radical 

sources in the exhaust plume, which concludes by suggesting that inclusion of these species 

within air pollution models is important for making accurate predictions of aircraft operations on 

local air quality. AAFEX AML observations are also used to assess the concentration of OH 

within aging exhaust plumes. Because OH was not directly measured, the authors infer its 

concentration by examining the ratios of highly reactive VOC species whose OH reaction rates 

are very well established. Examining plumes ~60 second in age, they calculate OH 

concentrations of ~2 x 107 molecules cm-3, which, when compared to nominal daylight 
49

background OH concentrations of 1 to 10 x 106 molecules cm-3

, indicates that the rate of VOC 

oxidation was elevated within the first minute of plume evolution. 

Figure 26. Emission indices in terms of mass per unit time in mode for methane (top) and 

nitrous oxide (bottom) as functions of engine power and time in mode. Taken from appendix F.

4.04 Greenhouse Gas Emissions

Engine emission indices for the green house gases methane (CH4) and nitrous oxide (N2O) are 

reported in appendix F and were determined by investigators from Harvard and ARI using 

advanced diode-laser spectrometer systems sampling aged exhaust through a special, low 

pressure inlet positioned 143 m behind the aircraft. These measurements are important because 

non-CO2 gases, primarily CH4 and N2O, but also including trace quantities of other halocarbons, 

together represent roughly 60% of the total forcing due to carbon dioxide (CO2) alone. Results 

of the AAFEX measurements are shown in Figure 26. The investigators note that for JP-8 

combustion at idle (4% and 7% of maximum thrust) the DC-8 engines emit both CH4 and N2O at 

a rate of 168 + 155 mgCH4(kgFuel)-1 and 114 + 47 mgN2O(kgFuel)-1

, respectively. Variability 

in the CH4 EIs is attributed to differences in engine operation history, background variability, 

and limited plume sampling cases as a result of unfavorable winds. At higher thrust levels, i.e. 
50

operational modes corresponding to greater fuel flow rates and higher engine combustion 

temperatures, they report that exhaust methane concentrations were lower than ambient 

concentrations (shown as negative EIs in Figure 26). Average emission indices for JP-8 fuel 

combusted with engine thrusts greater than 30% of maximum were -53.8 + 33.2 mgCH4(kgFuel)-

1 and 32.2 + 17.5 mgN2O(kgFuel)-1

, where the negative sign for methane indicates consumption 

of atmospheric methane in the engine. Methane and nitrous oxide EIs for the FT fuels are noted 

as being statistically indistinguishable from those for JP-8. For a typical flight profile (includes 

taxi, takeoff, cruise, et cetera), the investigators calculate that aircraft destroy significantly more 

methane than they create. From the AAFEX observations, they further conclude that an airline 

industry shift in fuel usage (i.e., from petroleum to synthetic fuels) will not affect global CH4 and 

N2O budgets.

4.05 Nonvolatile Particle Emissions

Appendix G, contributed by the Air Force Research Laboratory (AFRL), and appendix H, from 

the NASA Langley Research Center (LaRC), summarize the characteristics and concentrations 

of particulate matter emitted from the DC-8’s CFM56 engines as they burned each of the five 

test fuels under varying atmospheric conditions. Appendix G also presents gas phase emission 

measurement results and a discussion of the JP-8 and FT fuel properties as determined from

analyses of samples collected during the AAFEX campaign. Appendix I, from Missouri 

University of Science and Technology (MST), examines the effect of ambient temperature on 

nonvolatile particle emission indices. Results presented in these Appendices are based on 

measurements provided by CN counters, SMPS-type instruments, a smoke meter, and thermaloptical filter analysis. Appendix J, contributed by Penn State University (PSU), discusses 

results of electron microscope analyses of black carbon particles captured on impactors during 

AAFEX. 

Figure 26. Nonvolatile particle number (left) and black carbon mass (right) emission indices for 

the port and starboard inboard engines on the DC-8 as they burned JP-8 fuel. Left panel from 

appendix G, right panel adapted from appendix H.

Appendices G and H first examine JP-8 emissions and note that the DC-8’s left (#2) engine 

emitted higher PM number and mass emissions than the right (#3) inboard engine (see Figure 

26). The differences were particularly apparent at medium thrust settings (30 to 65%), where the

0.0E+00

2.0E+14

4.0E+14

6.0E+14

8.0E+14

1.0E+15

1.2E+15

0% 20% 40% 60% 80% 100%

EIn (#/kg-fuel)

Engine Power

1m Left Engine

1m Right Engine

0 20 40 60 80 100

0

20

40

60

80

100

120

 1 m Left Engine

 1 m Right Engine

Black Carbon EI (mg/kg)

Engine Power %
51

left engine emitted two to five times more PM mass than the right engine. Noting the wide 

spatial variation in PM emissions observed behind the #3 engine during the emission mapping 

test, the appendix H authors suggest the observed emission differences could be caused by 

having the inlet probes placed in different relative positions behind the two engines. However, 

they acknowledge that left engine black carbon emissions were also enhanced relative to the 

right engine in samples collected 30-m downwind, which contradicts the theory that spatial 

variations contributed to the observed emission differences. Appendix H authors also note the 

differences in EGT readings between the engines and show that the EIn and EIbc values collapse 

onto a single curves when plotted as functions of EGT; this finding is consistent with appendix B 

results, which suggest that higher combustor temperatures may have caused the left engine to 

produce greater amounts of black NOx at any particular power condition than the right engine. 

Regardless of the explanation, all investigators agree that the #2 engine was more polluting of 

the two from both a gas-phase and aerosol standpoint.

Figure 27. Comparison of nonvolatile particle emission parameters for DC-8's #3 engine burning 

JP-8 fuel as measured during APEX-1 and AAFEX. Adapted from Appendix H.

Figure 28. Nonvolatile particle number (left) and black carbon mass (right) emission indices as 

functions of percent maximum thrust for the starboard engine as it burned each of the indicated 

fuels. Adapted from Appendix H.
52

Appendix H also compares AAFEX starboard engine PM emission observations with 

corresponding measurements made during the spring 2004, APEX-1 study; results are shown in 

Figure 27. The investigators note the similarity in emission trends between the two campaigns, 

but point out that EIn values were higher at all power settings during AAFEX. They propose that 

a portion of the enhancements could be caused by differences in the 50% cut sizes (7 vs. 10 nm) 

of the two particle counters deployed to the experiments. Ambient temperatures differences are 

also considered to be a factor as it was about 10oC warmer during APEX, which, as discussed 

below, would tend to reduce PM emissions. Differences in instrument characteristics (PSAP vs. 

MAAP) and ambient temperatures are also suggested as possible factors contributing to the 

disagreement in EIbc measurements. In the end, however, the report recognizes the possibility 

that the AAFEX soot emissions were higher simply because the engines had aged almost five

years between the two missions.

Fuel effects on engine nonvolatile PM number and mass emissions are examined in detail within 

appendices G and H. Results from the two investigations are in good agreement and indicate 

that burning alternative fuels greatly reduced PM emissions from the DC-8’s starboard engine 

(see Figure 28). To exemplify the reductions more clearly, appendix H introduces an "emissions 

benefit" value, which is simply the ratio of the JP-8 to alternative fuel emission index for any 

particular emission parameter and power condition; for example, an emission benefit of 10 for 

PM number emissions means that EIn was reduced by a factor of 10 by burning the selected test 

fuel as opposed to JP-8. Figure 29 shows the power dependent emission benefits for PM 

number and black carbon mass emissions associated with burning each of the tested fuels. As 

pointed out in both appendices, FT1 provided the greatest PM reductions; indeed at idle, EIn was 

about 200 times lower for FT1 than Jp-8. Its relative number reduction benefit deceased 

monotonically with power to about 4 at 85% of maximum thrust. FT2 showed similar, but 

slightly lower emission reductions, but its number emission benefit peaked around 50 at 

medium-thrust levels and deceased to around 20 and 4 at 4% and 85% power, respectively.

Figure 29. Relative reduction in PM number (left) and black carbon mass (right) emissions from 

burning each of the alternative fuels in the DC-8's right inboard engine. Adapted from appendix 

H.

As shown in Figure 29, mass emission benefits of the two pure alternative fuels peaked at around 

30 in the 45 to 65% power range and exhibited relative minima at 7 and 85% power. PM 

number and mass emission benefits of the blended fuels also varied with power, but for 

unexplained reasons, were seldom 50% of the values calculated for the pure FT fuels. 
53

Appendix G takes a close look at fuel impacts on elemental carbon (EC) emissions and smoke 

numbers at climb and takeoff thrust settings (Figure 30). The authors note that at 85% power, 

there was no significant difference between the FT1 and FT2 EC EIs, but that both were 

substantially lower than JP-8 values. Surprisingly, EC EIs for the blended fuels were only 

slightly higher than the FT-fuel values. The investigators also derived volatile organic carbon 

(OC) aerosol emission indices from analysis of collected filter samples and found values at 85% 

power that were 60% lower for the FT fuels than JP-8. For smoke numbers, FT1 values were 

consistently lower than those for FT2 and values for both fuels doubled in going from 85 to 

100% thrust. At 85% thrust, smoke numbers were respectively reduced by ~83 and 72% when 

burning FT1 and FT2 as opposed to JP-8. 

Figure 30. Elemental carbon emission indices (left) and smoke numbers (right) for the various 

fuels and high engine powers. From appendix G.

Appendices G and H independently examine fuel effects on nonvolatile PM size and conclude 

that, in general, the FT particles were smaller than those generated when burning JP-8. The two 

reports differ, however, regarding fuel-size effects in the 4 to 30% power range. The authors of 

appendix G indicate that FT geometric mean diameters were larger in the 4 to 30% power range 

than JP-8 values, which contradicts findings from their earlier studies. In contrast, appendix H 

investigators observed 5 to 10% and 15 to 20% smaller FT GMD values at idle and takeoff thrust 

levels, respectively, and note that volume mean diameters (VMD) were 20 to 40% smaller for 

the FT fuels across the entire power envelope. They explain that at low power settings, 

measured FT PM emissions were very low and potentially contaminated with background 

particles; background particle impacts were reduced by limiting the size range over which 

emission parameters were calculated. This approach, coupled with lower transmission line 

losses and the removal of nucleation mode particles and surface coatings by use of a thermal 

denuder, perhaps explains why LaRC (appendix H) GMD values were systematically 5 to10 nm 

lower than those reported by AFRL (appendix G). 

The appendix H authors also point out that black-carbon mass densities were greater for the FT 

fuels than for JP-8. Over the 65 to 100% thrust range, they report effective density values 

derived from ratio of black carbon to nonvolatile particle volume of 1.45+0.1 g cm-3 for FT-1, 

1.2+0.15 g cm-3 for FT-2, 1.1+0.1 g cm-3 for Blend-1, 1.05+0.15 g cm-3 for Blend-2, and 

0.92+0.08 g cm-3 for JP-8. These results are consistent with previous work and suggest that the 

0

2

4

6

8

10

12

14

16

JP-8 FT1 (Shell) FT2 (Sasol)

Smoke Number

85% 100%

0

20

40

60

80

100

120

85%85%

85%85%85%85%85%85%

FT-1 Neat FT-2 Neat FT-1 Blend FT-2 Blend JP-8 JP-8 JP-8 JP-8

EC EI (mg/kg-fuel) 

Engine Setting/Fuel
54

black carbon particles generated from FT fuel combustion are much more spherical and compact 

than particles produced by burning JP-8.

The temperature dependence of JP-8 black carbon emissions is examined in detail within 

appendix H. The authors indicate that, similar to CO and THC emissions (see appendices A-C), 

nonvolatile PM number and mass decrease monotonically with increasing temperature at all 

power settings. They further perform a linear regression analyses between the PM emission 

parameters and temperature and find good correlations in most cases (for example, see Figure 

31). The regression slopes vary with engine power and range from about -0.6 x 10-14 kg-1oC-1 at 

ground idle to -0.2 x 10-14 kg-1oC-1 at takeoff thrust for EIn and from 0.4 mg kg-1oC-1 at taxi to -2 

mg kg-1oC-1 at climb. Thus at ground idle, the nominal EIn value of 20 x 10-14 kg-1 would 

increase by 33% (6 x 10-14 kg-1

) if ambient temperature dropped by 10oC. Similarly, the nominal 

EIbc of ~100 mg kg-1 for 85% power would increase by 20% (20 mg kg-1) if temperatures 

dropped by the same amount. 

Figure 31. EIn (top left) and EIbc (bottom left) at 85% power plotted as functions of ambient 

temperature. Power-dependent slopes derived from regression of EIn and EIbc on temperature 

are shown in the right top and bottom panels, respectively. Error bars are the 1sigma standard 

deviation of the linear fits. The temperature dependence for 100% power is not shown because 

there too few data points. 
55

Appendix I also examines ambient temperature effects on nonvolatile PM emission indices and 

mean particle size. By examining the mean ratio changes at widely separated temperatures, they 

show that the JP-8 and FT-1 emission parameters exhibited statistically significant changes with 

temperature in over 90% of the cases studied. They further note that the FT1 emission 

parameters appeared to vary more strongly with temperature than did the JP-8 parameters, but 

additional analyses fail to provide statistical support for this observation. 

Appendices G and H explore possible causes for the fuel-dependent differences in nonvolatile 

PM emissions. The AFRL investigators examine the range in PM number emissions as a 

function of fuel end point (EP, defined as the temperature at which all distilled fuel is recovered) 

and find, as indicated in Figure 32, that the range between idle and high thrust EIs decreased 

considerably with increasing EP—there was no correlation between EP and the EIs at any 

particular power setting. 

Figure 32. Nonvolatile particle number EI as a function of fuel end point (left) and black carbon 

EI as a function of fuel hydrogen content (right). Plots adapted from appendices G (left) and H 

(right).

Based on a results from modeling studies of gas turbine soot emissions, the Langley investigators 

assess the relationships between fuel components and PM number (EIn) and black carbon (EIbc) 

and find very high linear correlations (r2 > 0.7 in most cases) between the emission parameters

and fuel hydrogen (see Figure 32), aromatic and naphthalene contents, and H/C ratios. They 

also note the following (abstracted from appendix H):

• At all power settings, EIn and EIbc increased with aromatic content and decreased with 

hydrogen content.

• The variability in EIn decreased with increasing aromatic content and decreasing hydrogen 

content. For example, EIn for JP-8 (highest aromatics, lowest hydrogen) varied about 60% 

between idle and takeoff thrust whereas those for FT-1 (lowest aromatics, highest hydrogen) 

varied by almost two orders of magnitude.

• In general, correlation coefficients with fuel properties were greater for EIn than for EIbc, 

suggesting that the variability in EIn was better captured by variability in fuel composition 

than was the variability in EIbc. 

• For both EIn and EIbc, the best correlations with all examined fuel properties were observed at 

idle (4 %) and takeoff (100 %) thrust settings; correlation coefficients were a minimum at 30 

and 45 % power.

1.00E+12

1.00E+13

1.00E+14

1.00E+15

1.00E+16

200 220 240 260 280

EIn (#/kg-fuel)

Fuel End Point (Deg C)

4% 7% 30%

45% 65% 85%

FT Shell

FT Sasol

JP-8
56

• Slopes for EIn linear regressions were greatest at the 4 % thrust setting, suggesting that 

absolute EIn values were most sensitive to variable fuel properties at aircraft idle. 

• Slopes for EIbc linear regressions were greatest at the 100 % thrust setting, suggesting that 

absolute EIbc values were most sensitive to variable fuel properties at aircraft takeoff. 

• EIn and EIbc appear to be better correlated with fuel aromatic than hydrogen content at all 

thrust settings, however the fuel components did not vary independently so these results are 

only suggestive of observed relationships. 

Figure 33. Results from afternoon JP-8 engine test showing EIn (left) and EIv (right) as functions 

of distance behind the aircraft. Taken from appendix H; similar plots for EIn are shown and 

discussed within appendices G and I.

4.06 Volatile Particle Emissions

As aircraft engine exhaust plumes cool and mix with background air, low volatility species such 

as sulfuric acid, engine oil, and unburned hydrocarbons condense to either form new aerosols 

though homogeneous nucleation or to coat the surface of existing soot or background aerosol 

particles. Gaining a better understanding of the composition and the factors that control the 

formation and growth of these volatile aerosols was a major AAFEX objective. The fuel and 

temperature-dependent physical characteristics and concentrations of the volatile aerosols in 

aged exhaust plumes as measured with particle counting-type instruments are discussed in 

appendices G and H. Results of ARI, aerosol mass spectrometer-based, volatile aerosol 

composition studies are presented in appendices K and L. 

All AAFEX reports agree that volatile aerosols formed very rapidly within diluting exhaust 

plumes and that, for JP-8 fuel (which contained ~1200 ppm sulfur), EIn values were at least a 

factor of five greater at the downstream sampling inlets than observed in the hot exhaust directly 

behind the engines. For example, Figure 33 shows 1-, 30- and 145-m PM emission 

measurements plotted as functions of engine power. Although the data were recorded on a 

relatively warm afternoon, EIn values increased by factors of 10 to 20 in going from 1 to 30 m; 

Aerosol volume EIs (EIv) also increased significantly, particularly at low thrust settings. As 

described in appendix H, the downwind-increases in EIn and EIv are attributed to volatile aerosol 

formation and are the greatest at low power when emissions of gaseous precursors are greatest 

and plume temperatures are the lowest. As shown in Figure 34, at the exhaust plane the 

particles are comprised of a single soot mode, while an additional nucleation mode, peaking at 
57

15 to 25 nm in the volume (10 to 20 nm in number) distribution is only observed downwind. At 

low power, this nucleation mode dominates the PSD in downstream samples. As power increases 

the nucleation mode decreases and the soot mode increases with the soot mode dominating at 

high power. Very little variation is observed in the soot mode volume between each distance. In 

contrast, significant variability is observed for the nucleation-mode, as the peak-diameter and 

integrated volume each increase with increasing distance (from 30 m to 145 m, Figure 34), 

suggesting that gas-to-particle conversion and particle growth is also occurring. This is also 

evident from Figure 33, as EIv is greater at 145 m than at 30 m. Differences in EIn are most 

significant between 1 m and 30 m, as the exhaust plume is cooling and particle nucleation is 

most prevalent. The difference between 30-m and 145-m EIn is much less, suggesting that 

nucleation processes are still occurring but are less significant after 30 m.

Figure 34. Size distributions (dEIv/dlogDp, mg kg-1

) as a function of sampling 

probe and engine power setting for JP-8 fuel. More uncertainty is observed with 

increasing probe distance due to increasing dilution correction factors. Figure 

taken from Appendix H; similar PSD plots are presented and discussed within 

Appendices G and I.

AAFEX investigators note that volatile aerosol formation and growth was heavily dependent

ambient temperature. Figure 35 from appendix H shows JP-8, 30-m EIn and EIv values for the 

7% power setting plotted as functions of temperature; also included are plots of powerdependent, temperature coefficients for the two emission parameters derived from the slopes of 
58

linear regression analyses. At all power settings, the volatile PM EIs decreased monotonically 

with increasing temperature. Temperature coefficients (dEI/dT) were greatest at ground idle 

(where the largest amount of condensable material was available in the plume) and generally 

larger for volatile PM volume than number. For example, at 4% power, a 10o

C change in 

temperature produced ~30 and ~60% changes in EIn and EIv, respectively. This observation is 

consistent with the idea that volatile aerosol number populations quickly reach an equilibrium 

between formation and coagulation while total volatile aerosol mass continues to grow through 

nucleation, coagulation and direct gas-phase condensation on existing particles. This concept 

may also explain why EIn values in the aged JP-8 high thrust plumes were relatively high 

(compared to idle plumes), despite there being less material available for condensation.

Figure 35. Total aerosol number (top left) and volume (bottom left) emission indices for JP-8 as 

functions of ambient temperature. Plots at right display the power dependent temperature 

coefficients for EIn (top) and EIv (bottom). Adapted from appendix H.

The temperature and age dependent growth of the volatile aerosols is further exemplified in 

Figure 36, which is extracted from appendix L and exhibits mean particle diameter data recorded 

in the ARI mobile laboratory during multiple downwind penetrations of a JP-8, ground-idle 

exhaust plume. The size distribution mode is seen to increase both with distance downstream 

(which is equivalent to plume age) and with decreasing temperature. The authors note that the 

larger sizes associated with colder temperatures may be caused by more rapid volatile aerosol 
59

nucleation and growth or by enhanced concentrations of condensable material in exhaust or by 

some combination of the two. 

Appendix H examines fuel effects on volatile aerosol concentrations and characteristics in 

exhaust plumes sampled at 30 m behind the aircraft. The authors state that at low power, FT-1 

total EIn (and EIm) values were an order of magnitude lower than from JP-8, but still were 

enhanced above 1-m values. They suggest that this may be due to the slight sulfur 

contamination or to nucleation of semi-volatile hydrocarbons at the relatively cold ambient 

temperatures. They further note that Blend-1 total EIn values were similar to JP-8 values despite 

the factor of two difference in sulfur content between the fuels. By way of explanation, they cite 

a study by Timko et al. (2010) which used modeling analysis to show that the reduced 

availability of soot surface area in the blended fuel exhaust causes new particle formation to be 

favored over condensation of volatile material onto soot mode particles. They propose that 

during AAFEX volatile particle populations reached equilibrium between formation by 

nucleation and loss through coagulation that made the overall particle number densities vary 

independently from fuel sulfur content. To support this contention, the authors note that JP-8 

nucleation-mode mean diameters were significantly larger than corresponding Blend-1 diameters 

in the 30-m samples at all power settings. Additional analysis shows that FT-2 and its blend 

formed considerably more volatile aerosol in aging exhaust plumes than FT-1; this is consistent 

with the comparatively higher total hydrocarbon emissions associated with the FT-2 fuel. 

Figure 36. EEPS number density-based, nucleation mode diameter data obtained during early 

morning idle plume penetrations. The "X" axis represents meters downstream of the engine exit 

plane and indicates that the subject data were recorded between 50 and 200 m behind the aircraft. 

Plot taken from appendix L.

Appendices K and L, contributed by Aerodyne, discuss the composition of volatile exhaust 

particles as measured using an Aerodyne, time-of-flight, Aerosol Mass Spect (AMS), which is 

capable of determining the size-dependent concentrations of both sulfate and organic aerosols. 
60

Both appendices couple AAFEX results with measurements from previous field experiments to 

provide a broader and more substantiated interpretation of the observations. Appendix L 

additionally includes results from mass spectral analyses conducted on vaporized JP-8 and FT-2 

fuels and from AMS studies of the PM generated when the fuels were combusted at ambient 

pressure in a laboratory diffusion flame burner. 

In appendix L, the authors note observing that: 1) for aged plumes (>100 sec), EIm-organic 

ranges from 50 – 150 mg kg-1 (idle conditions, 275 K); 2) the aromatic signature identified at 30 

m perseveres or even increases at 50 m and beyond; and 3) EIm-organic scales with EI-CO. 

They acknowledge that the larger EIm-organic values are partly due to recent improvements in

AMS sensitivity to nucleation mode particles, but point out that growth of nucleation mode 

particles during aging also leads to increased instrument sensitivity and, in turn, higher EImorganic. They finally note that the more recent EIm-organic values are in much better agreement 

with volatile aerosol mass EIs inferred from volatile aerosol size distribution measurements and 

indicate that further analyses are needed to identify whether particular organic species 

preferentially condense in the plume and to evaluate the effects of dilution and processing time 

on EIm-organic values. 

Appendix K takes a comprehensive look at volatile aerosol composition and how fuel 

composition, engine technology, combustion conditions, and ambient temperature influence 

organic aerosol partitioning and mass emission indices. From mass spectral analysis, the 

investigators note that the JP-8 and FT fuels were fundamentally much different and that JP-8 

contained much higher concentrations of large aromatics and heavy hydrocarbons that are likely 

to be PAH precursor species. Their diffusion flame studies showed that pyrene was the 

predominant PAH species emitted when burning all fuels under relatively lean conditions, but 

that PAH emissions in general were substantially lower from FT-2 than JP-8. The authors 

observed that, in addition to fuel composition, PAH emissions for all fuels were highly 

dependent on fuel air ratio. In rich flames, all fuels produced PM with relatively higher oxygen 

content, but on a percentage basis, FT-2 levels were greater than JP-8 (16% versus 11% of total 

organic aerosol emissions). The authors indicate that because of its higher oxygen content, the 

FT-2 volatile aerosols would likely be more soluble than JP-8 PM emissions and hence make 

better cloud condensation nuclei. 

To gain insight into the composition and characteristics of gas turbine PM emissions, appendix K 

authors performed a positive matrix factorization (PMF) analysis on recent AMS data sets. 

They found that the organic aerosol emissions could be grouped into five basic types: lube oil, 

siloxane (from sampling system out-gassing), hydrocarbons, aromatics, and an unknown 

category that scaled with lube oil. They found that at all power settings lube oil dominated total 

organic PM emissions from RB211 engines, but that hydrocarbons and aromatics (incomplete 

combustion products) accounted for 60% or more of EIm-organic for a CJ6108A turbojet engine

(an example of 50-year-old engine technology). For a CFM56-3B1, which is similar to the 

engine tested during AAFEX, lube oil and the lube-oil-like compounds composed between 50 

and 70% of EIm-organic across the power range, whereas products of incomplete combustion 

accounted for about 45 and 30% of the organic PM emissions at idle and high thrust levels, 

respectively. The ratio of hydrocarbon to aromatic PM emissions varied between engines and 

power settings, but was typically lowest at idle and greatest at medium to high thrust settings.
61

Appendix K also presents and discusses AAFEX EIm-sulfate and EIm-organic values derived 

from AMS measurements. Figure 37, adapted from the report, shows how these two parameters 

varied as functions of engine power, fuel composition and ambient temperature. As the authors 

note, the dependence of the EIs on fuel composition is readily apparent. For JP-8, EIm-sulfate 

varied from about 1 mg kg-1 at idle to nearly 4 mg kg-1 at take-off. In contrast, EIm-sulfate for 

both pure FT fuels was below detection limits (0.2 mg kg-1 for these tests) regardless of power or 

ambient conditions. EIm-sulfate for the blended FT fuel was intermediate to the pure FT fuels 

and JP-8, though closer to the FT data. Increasing power increased EIm-sulfate, most likely 

because of the power dependence of EIbc and the better ability of the AMS to quantify soot sized 

particles (and/or their coatings) than nucleation/growth mode particles. Temperature was also 

important. As temperature increased, so too did EIm-sulfate. This counter-intuitive finding is 

likely due to the competition between nucleation (favored at low temperature) and soot coating 

(favored at high temperature) – and the relative sensitivity of the AMS to nucleation particles 

(low) and soot particles (high). Consistent with these observations, EIm-sulfate for the port 

engine is greater than the starboard engine just as EIm-soot for the port engine is greater than for 

the starboard engine.

Figure 37. Sulfate (left) and organic (right) aerosol emission indices plotted as functions of fuel 

flow rate. Adapted from appendix K.

For organic PM emissions, the authors point out that EIm-organic depends on fuel composition, 

engine power, and ambient conditions (see right panel of Figure 37). The dependence of EImorganic on the engine (port or starboard) is weaker than for EIm-sulfate. Taking the other three 

variables in turn: 1) fuel: EIm-organic is greater at all power conditions for JP-8 than for the FT 

fuels or the blended fuel; 2) temperature: EIm-organic increases with decreasing ambient 

temperature; 3) power: consistent with APEX results, EIm-organic decreases from 0-15% 
62

(plotted as fuel flows ranging from 0 to 0.3 kg sec-1

) and then increases from 65-100% (0.6 to 1 

kg sec-1

). Quantitatively, EIm-organic for JP-8 fuel at idle and low ambient temperature reaches 

a value of nearly 15 mg kg-1; the authors attribute this large value to the low ambient temperature 

of the test and the relatively low efficiency of the CFM56-2C1 combustor when operated near 

idle.

To explore the mechanisms responsible for regulating the partitioning of the volatile aerosol 

species between the nucleation and soot modes, appendix K examines the ratio of EIm-sulfate to 

EIm-organic as a function of engine power and ambient temperature. For JP-8, the ratio exhibits 

an increasing trend with power under both cold and warm ambient conditions. At idle, the 

volatile PM is dominated by organic material, which constitutes more than 90% of the total 

mass. At take-off thrust in warm conditions, the ratio of organic to sulfate PM is nearly 1:1. The 

authors note that at power settings greater than 4%, the ratio of sulfate to organic depends on 

ambient temperature. They further indicate that higher ambient temperatures favor EIm-sulfate 

and correspondingly lower EIm-sulfate to EIm-organic ratios. Two explanations are proposed: 1) 

lower ambient temperatures decrease combustion efficiency, thereby increasing the amount of 

organic precursors available to form organic PM or 2) decreasing temperature shifts sulfate 

material preferentially to the nucleation mode (and away from the soot mode) where it is not 

detected efficiently by the AMS. The investigators present a series of compositionally-resolved 

size distributions that support these explanations and note that the observation that the nucleation 

mode may have a different ratio of sulfate to organic material than the soot mode is new and 

potentially important for understanding aircraft emissions at cruise altitude conditions. 

Figure 38. Total hydrocarbon (left) and CO (right) emission indices for JP-8 (red squares) and 

FT-2 (blue diamonds) for the APU plotted as functions of exhaust gas temperature. Adapted 

from appendix M.

4.07 Auxiliary Power Unit (APU) Gaseous and PM Emissions

Emissions from the DC-8’s APU were also characterized during AAFEX and are discussed in 

appendices H and M. As noted above, the APU is essentially an old-technology, turbo-jet 

engine that operates at relatively low combustion temperatures. Because it was not equipped 

with fuel flow meters, emission parameters are examined as functions of exhaust gas 

temperature, which was varied by adjusting the generator, air handling or bleed air demands of 

the aircraft. Nominal EGT set point values were 360 (idle), 475, 550 and 620o

C (full load); for 
63

comparison, EGT for the DC-8’s starboard engine varied from approximately 400°C at idle to 

716°C at takeoff thrust. Fuel composition effects on APU emissions were evaluated by 

alternately burning either standard JP-8 or the FT-2 fuel. Ambient conditions were relatively 

constant and essentially the same during the three APU test runs, so it is not possible to assess 

temperature effects on the APU emissions.

Appendix M summarizes results from APU gas phase emission measurements conducted by 

EPA, NASA, AFRL, and ARI. The investigators found that EI-SO2 was relatively constant with 

APU load and that JP-8 values were significantly greater than those from FT-2; this is not 

surprising, because the JP-8 contained ~1200 ppm sulfur impurities as opposed to the FT-2’s 22 

ppm. Actual values ranged from 1.5-1.8 g kg-1 for JP-8 fuel and 0.13-0.15 g kg-1 for FT-2. It is 

noted that use of the alternative fuel reduced SO2 emissions by an average of 92%. The authors 

further report that total hydrocarbon (THC) emission indices (Figure 38, left plot) decreased 

exponentially with EGT from about 1.4 g kg-1 (for JP-8) at idle (EGT = 350oC) to ~0.25 g kg-1 

at full APU load (EGT = 610oC). FT-2 EI-THC values were an average of 37% lower than 

those calculated for JP-8. Carbon monoxide EIs (Figure 38, right plot) were also found to 

decrease with power from ~30 g kg-1 at idle to 12 g kg-1 at full APU load; observed FT-2 EICO values were on average 9% lower than corresponding JP-8 values. NOx emission indices 

varied only slightly around a central value of 4.5 g kg-1 and were relatively insensitive to fuel 

type and operating conditions. 

The characteristics and concentrations of APU PM emissions receive considerable attention in 

both appendix H and M. Figure 39 summarizes the overall observations. For both fuels, EIn

and EIbc values were a maximum at idle and decreased with increasing APU load. 

As noted in appendix H, from a PM standpoint, the APU was much more polluting than the DC8’s CFM-56 engines. For JP-8 at idle, APU EIn and EIbc values far exceeded those from the DC8’s starboard engine and, unlike for the high-pass engines on the DC-8, APU PM emissions 

decreased with increasing power (see Figure 39). Indeed, both EIn and EIbc values declined by 

more than a factor of two as the APU load was increased from minimum (cabin lights and 

avionics only) to maximum (air handler operation plus providing bleed air to spin the DC-8 

control engine). Since the APU fuel-air-ratio increased with thrust (similar to the aircraft 

engine), the decreasing emissions can’t be attributed to rich combustion conditions at idle. 

Improved combustion efficiency or increased combustor pressure with thrust are other factors 

that could influence the emission behavior of the APU. 
64

Figure 39. APU nonvolatile PM EIn (top left), EIbc (top right), geometric mean diameter (bottom 

left) and volume mean diameter (bottom) right for JP-8 (red squares) and FT-2 (green squares) 

plotted as functions of exhaust gas temperature. Taken from appendix H.

Regarding PM size, appendix H notes that for JP-8 at idle, GMDs and VMDs were respectively 

32.9 versus 21.2 nm and 92.8 versus 57.0 nm for the APU compared to DC-8’s starboard engine.

Similar to then engines, FT-2 particles were smaller compared to PM emissions from JP-8. 

Overall, particle size varied with EGT such that APU GMD and VMD values decreased slightly

with increasing load (Figure 38), which is opposite to the trends exhibited by the DC-8’s

engines. However, even at the highest load/thrust settings, APU particles were still 20 to 30% 

larger, on a volume-basis, than those emitted by the DC-8 engines. Appendix H authors also 

point out that the APU particles were more fractal and less dense than those emitted by the 

engines. For example, density values for JP-8 fuel combustion obtained by taking the ratio of 

EIbc (from the MAAP) to EIv (from an SMPS) averaged 0.51±0.02 g cm-3 for APU compared to 

0.92±0.08 g cm-3 for the engines at thrust settings greater than 65 %. It also notes that FT-2 

particles were smaller compared to emissions from JP-8. APU PM emissions are likely more 

similar in size, density and fractal nature to soot emissions from older, turbo-jet aircraft engines. 

Both appendices emphasize the remarkable reduction in APU PM emissions associated with 

burning the FT-2 fuel. Appendix H points out that average FT-2 EIn and EIbc values were 

respectively factors of 6 and 13 lower than those for JP-8, but were still significant and 

comparable to JP-8 EIn and EIbc from the DC-8 engines. APU FT-2 combustion also produced 

significantly smaller particles compared to JP-8; at idle GMD was 32.9 and 21.5 nm for JP-8 and 
65

FT-2, respectively, and VMD was 92.8 and 63.2 nm, respectively. APU FT particles were more 

dense than APU JP-8 particles with average density values of 0.60±0.06 g cm-3 as opposed to 

0.51±0.02 g cm-3 for JP-8. 

Appendix N, contributed by Penn State University, examines the morphology and detailed 

chemistry of soot particles generated by the APU. The author notes that synthetic fuels 

composed of paraffinic species delay the onset of particle formation and growth by absence of 

dehydrogenated species and aromatics. This permits increased fuel-air mixing, increased 

formation of oxygenated intermediates and production of alkyl intermediates containing an odd 

number of carbon atoms, in addition to dehydrogenated molecules and aromatics. He further 

states that these species will increase the concentration of cyclopentadienyl radicals and 

aromatics incorporating them, such as naphthalene. Such compounds incorporated into graphene 

segments give rise to curvature and result in fullerenic nanostructure. The degree or content of 

fullerenic structure is here postulated to correlate with level of partial premixing. Nanostructure 

comparisons as a function of engine power supports this postulate as increased fuel concentration 

with increased (required) power decreases the level of partial premixing, both local and global. 

The result is a lesser content of fullerenic nanostructure, as observed by HRTEM. Comparisons 

between the FT and JP-8 fuels provides further support in that for the same power level, soot 

from the JP-8 fuel contains less fullerenic nanostructure, reflecting its substantial aromatic 

content, that accelerates soot formation which minimizes the impact of partial premixing. 

Differences in aggregate size between the two fuels at each power level are consistent with this 

interpretation. Therein soot nanostructure preserves a record of the gas phase species 

contributing to its formation and growth and can be used as an in situ tracer of the early 

combustion chemistry within the engine.

 

4.08 Sampling System Assessments 

Appendix O examines the variability of PM emissions across the starboard engine exhaust plane 

to address the question of whether single point sampling can yield EI values equivalent to 

multipoint averages. 

Appendix P summarizes AAFEX efforts to assess the impact of the sampling lines and inlet 

probes on measured particle emission parameters. The report examines results from focused 

experiments and conducts analyses to: determine size-dependent sampling line transport 

efficiencies; evaluate particle formation and growth within the 30-m sampling lines; determine 

PM spatial variability across the engine exhaust plane; evaluate particle losses in the 1-m inlet 

probes; and examine whether samples collected with modified gas inlet probes yield 

representative PM emission measurements. 

Loss of particles to sampling system components is always a concern in aircraft engine emission 

tests. To assess these losses, the last official day of AAFEX was devoted to evaluating the sizedependent transmissions efficiencies of the four primary sampling lines. Appendix Q presents 

the results and notes that after 35 hours of engine testing, up to 50% of particles of all sizes were 

lost in some of the long sample transport lines (see Figure 40). It states that the losses were 

greatest in the lines that had been used the most, which suggests that the reduced transmission 

efficiencies were caused by build-up of material on the tubing walls. An analysis of the port 
66

engine black carbon emissions measured downstream from the 30-m inlet indicate the losses 

were modest initially, but increased in time as soot and other contaminants accumulated on 

tubing walls; the analysis further suggests that for the left, 30-m inlet line’s efficiency dropped 

~5%/day over the course of the experiment. A variety of physical processes are explored as 

possible causes for the significant losses of particles in the 100 to 300 nm diameter particles in 

the sampling lines. The most reasonable explanation is that the accumulated material increased 

surface roughness, essentially creating a surface-filter effect that enhanced particle losses 

through interception and turbulent impaction.

Figure 40. Transmission efficiencies for the 1 (left) and 30 m sampling lines as determined after 

the engine tests were complete. Taken from appendix P.

Appendix P examines results from the "Deathbox" experiment to address the question of whether 

a majority of the volatile aerosols seen at 30 m condense in the exhaust plume or during transport 

through the long sampling lines. The authors note that under relatively cold conditions (~0o

C), 

volatile particle nucleation within the aging exhaust plume typically reached equilibrium 

between formation and coagulation before entering the 30-m inlet probe. However, volatile 

particle mass continued to form during the subsequent 16-second transport time within sampling 

lines, potentially increasing calculated mass emission indices by 50 to 75% at high engine 

powers. 

Appendices P and Q address the question of whether point measurements of PM emissions are 

representative of the engine PM emissions as a whole. Appendix O investigators examine data 

acquired throughout the mission to assess the PM emission variability across the engine exit 

plane. They note that the spatial homogeneity was power dependent, with minimum PM 

parameter variability at the highest power and maximum variability at mid power. They also 

found that measured emission indices showed more variability than the size distribution shape 

parameters and note that overall, normalized PM emissions varied from 6 to 70% across the 

limited span of engine exit plane explored in the study. To eliminate the effects of changing 

ambient temperatures and sampling system characteristics, appendix P authors restrict their 

spatial variability assessment to data recorded within a single test, wherein the sampling rake 

was translated in 5-cm increments from 0 to 20-cm off centerline at power settings ranging from 

idle to 85% of maximum thrust. The investigators indicate that non-volatile PM mass and 
67

number EIs were fairly stable and equivalent within 10 cm of centerline, suggesting that single 

point sampling in that region would yield emission parameters broadly representative (within 

20%) of the entire engine. 

Results from a study in which sample dilution ratios were systematically increased to reduce 

inlet tip velocity are also examined in appendix P to evaluate the impact of non-isokinetic 

sampling on calculated PM emission parameters. The authors note that at high engine thrust, PM 

emissions generally increased with freestream to sample inlet velocity ratio, U0/U, suggesting 

that particle populations were being enhanced by virtual impaction. However, the enrichment 

trends did not faithfully follow sub-isokinetic flow predictions and were thus possibly caused by 

other mechanisms.

Figure 41. Total number (top left) and mass (top right) along with nonvolatile number (bottom 

left) and black carbon (bottom right) emission indices plotted as functions of engine power and 

as measured in samples froma particle dilution probe (black squares) and gas probe with dilution 

gas introded 1.5 m downstream of the inlet tip. Taken from appendix P.

Loss of particles within inlet probes and sampling lines is of great concern when sampling hot, 

high-velocity engine exhaust 1 m downstream of the engine exit plane. To evaluate the losses, 

appendix P compares PM emission measurements from the 1- and 30-m inlet probes. The 
68

investigators found that 30-m, non-volatile EIn and EIm were systematically higher for both 

engines than those measured at 1 m, indicating possible particle loss in the 1-m inlets or transport 

tubes; thermophoretic deposition and turbulent eddy impaction are suggested to be possible 

mechanisms that account for these losses.

A portion of one of the later JP-8 test runs conducted during AAFEX addressed the question of 

whether it is possible to make representative PM measurements from standard gas inlet probes. 

The experiment involved comparing PM number and mass EIs measured from adjacent gas and 

particle probes mounted near the engine centerline in the starboard 1-m rake; dry dilution gas 

was introduced concentrically to the particle probes at the inlet tip (see section 3 discussion) and 

to the gas probe samples about 1.5 meters downstream, near the base of the rake stand. Results 

are presented in appendix P and shown in Figure 41. The investigators found that volatile 

aerosols formed in the gas probe samples which cause total PM number and mass EIs to be 

somewhat enhanced in comparison to the particle probe measurements (see top panels in Figure 

41). However, samples first routed through a thermal denuder upstream of the diagnostic 

instruments yielded nonvolatile EIn and EIbc data from the two probes that agreed to within 10%, 

suggesting that existing gas certification sampling probes used by engine manufacturers may be 

modified to yield representative particle number, mass and PSD measurements. 

Figure 42. Instrument comparison data acquired during tests that used a CAST diffusion burner 

as a black carbon source. Figure adapted from appendix R.

4.08 Instrument Comparisons

Appendix Q reports results from a collaborative study performed at the conclusion of AAFEX, 

wherein a portable soot generator was used as an engine surrogate to assess the agreement 

between a variety of instruments used to characterize aircraft PM emissions. A separate 

objective was to evaluate the soot generator as a possible calibration source for field 

measurements. In the test, soot samples of varying concentration were distributed to a number of 

different instruments so that simultaneous measurements could be performed. Although the suite 

of instruments provided the capability of measuring particle concentration, size distribution, and 

mass, the focus of the experiment was to compare instruments that measure BC mass because 

factors other than instrument performance (e.g., line loss) were expected to affect measurements 

of the other parameters. Tested instruments included: (1) several ThermoElectron Multi Angle 
69

Absorption Spectrometer (MAAP) model 5012, (2) an Artium LII-200 Laser Induced 

Incandescence instrument, (3) a Droplet Measurement Technologies Photo-Acoustic Soot 

Spectrometer (PASS-3), (4) a standard Smoke Number instrument, (5) Scanning Mobility 

Particle Sizers (SMPS), and (6) Condensation Particle Counters (CPC). The report notes that 

intra-instrument comparisons of the MAAP (see Figure 42) for the measurement of black carbon 

mass showed that as expected the same instrument analyzing the same sample produces the same 

result. Inter-instrument comparisons (right panel in Figure 42) showed that particle properties 

and instrument factors can influence the results. The removal of volatile particles is a key to 

compare mass and number datasets. The authors note that instrument efficacy can be obtained; 

however, without established instrument calibration methods, traceability is lacking and 

measurement uncertainty remains. They also point out that the commercially available portable 

particle generator based on a well-controlled propane diffusion flame that was used in the test 

produced results which encourage its further assessment as a source for field measurement of 

line loss and instrument calibration.

5.00 FINAL REMARKS AND RECOMMENDATIONS

By all accounts, AFFEX was highly successful in that participants acquired extensive engine 

performance and emissions observations that addressed all test objectives and provide valuable 

insight into the factors that control gas turbine gaseous and PM emissions. Indeed mission data 

are unparalleled in detail and quality and will be particularly useful in developing models to 

predict soot emissions based on fuel composition and for validating both photochemical and 

microphysical models of engine exhaust plume evolution. 

Moreover, AAFEX results are consistent with previous studies and indicate that engines and 

aircraft support equipment burning synthetic fuels generate substantially less PM and HAPS 

emissions than those burning standard petroleum-based fuels. Thus, provided aircraft fuel 

system leak problems can be solved, the tested fuels can be used as drop-in replacements that 

impose no penalty on engine performance, but significantly reduce local air quality and health 

impacts. 

AAFEX success was greatly enabled by experience gained in previous ground-based, on-wing 

engine emission tests including the summer 1999 NASA aerosol instrument workshop (Cofer et 

al., 2000), EXCAVATE (Anderson et al., 2005), and the APEX test series (i.e., Wey et al., 

2007). However, despite being cognizant of the knowledge gained in these experiments, 

additional lessons were learned that could potentially improve future emissions test plans and 

procedures. These primarily relate to exhaust sampling and are listed below.

• Be cautious when using non-metallic aerosol sampling lines. Long lengths of conductive 

PTFE were used in some of the AAFEX sampling lines and are suspected to have 

accumulated surface contamination more quickly than the polished stainless steel.

• Carefully design sample flow systems to minimize tubing exposure to concentrated exhaust 

sample. A large amount of exhaust flow was drawn continuously through the 30-m 

sampling lines at all times during engine runs; this was potentially a cause of the large 

transmission losses observed in the lines at the conclusion of the mission.
70

• Perform frequent sample line leak tests. Several hours of data were partially compromised 

by having small leaks in and around the sample selection valves. Sample systems should 

also be designed to include a minimum of valves and fittings.

• Perform sample line PM transmission tests at frequent intervals; have a procedure in place 

for cleaning lines if losses become excessive. Line loss tests were conducted after all the 

engine emission tests were complete and suggested that up to 50% of PM mass was lost to 

the walls in some cases. Since this would not be the case for clean lines, the question arose: 

when did the losses become evident? An attempt to clean the lines by flushing with water 

appeared to be ineffective.

• Design sample dilution systems to minimize dry N2 requirements. To avoid line 

contamination it is recommended that a small flow (~2 lpm) be blown out unused inlet tips 

rather than drawing large dry N2 flow through unused lines with a vacuum pump.

• When sampling with a single set of probes, be sure to survey emissions across the exhaust 

plume so that areas contaminated with oil leaks or associated emissions can be avoided. The 

DC-8’s #3 engine had an oil leak that apparently produced volatile aerosols in the region 

within 10 cm of its centerline. Several tests were conducted before the source of the volatile 

aerosols was recognized and the sample rake was repositioned to avoid the contaminated 

flow.

• When using cold sampling lines or diluting samples downstream of the inlet tip, a thermal 

denuder should be used to remove volatile aerosols before PM emission parameters are 

measured. On cold mornings, exit plane PM samples sometimes exhibited nucleation mode 

particles formed by condensation of low-volatility species within the cold tubing.

• When sampling emissions from engines burning alternative fuels, make frequent 

measurements of background PM and gas species concentrations. Emissions from these 

fuels are very low, particularly at idle, and 30-m measurements must be corrected for 

background contributions.

• Use large (400 L), high-pressure LN2 tanks to provide dilution gas; the small tanks cannot 

provide adequate flow for 10-fold sample dilution at high engine thrust settings. 

• Be cautious in conducting downstream sampling with mobile vehicles; personnel should be 

exposed to the noxious gases in the exhaust plume for only brief periods of time to avoid 

toxic reactions (headaches, nausea, etc.)

AAFEX measurements and data analysis activities have greatly advanced our understanding of 

fuel and ambient-condition effects on engine black carbon emissions and volatile aerosol 

formation and growth in aging exhaust plumes. The project also brought to light several areas 

where additional research is needed. 

• Improved measurements of volatile aerosol nucleation mode mass and composition are 

required to further develop and validate aerosol microphysical models. The AMS instrument 

used in AAFEX and previous studies is not sensitive to aerosols in this size range and thus in 

many cases it only "sees" a small fraction of the volatile aerosols inferred to be present from 

SMPS-type measurements. 

• Direct measurements of engine-exhaust black carbon mass density are needed to better 

characterize the fractal nature of the particles and how it varies with combustor technology, 

fuel composition, and combustion conditions. In AAFEX, bulk density values were 

calculated from the ratio of MAAP black carbon mass to SMPS volume. A much better 
71

approach is to use an Aerosol Particle Mass instrument, which are now available 

commercially, to measure the mass of monodisperse particles selected by an SMPS.

• Measurements of the soluble components of aged aircraft exhaust plumes are needed to 

evaluate the impact of aircraft emissions on local water quality and clouds. Instruments are 

available for performing these measurements and should be deployed during the next suitable 

engine test or to an airport for an advected plume study.

• Detailed measurements of exhaust plume chemistry for a variety of engine types over a broad 

range of ambient conditions. AAFEX measurements indicate that CFM-56-2C engine 

emission performance is highly dependent on ambient temperature. Additional studies are 

needed to verify that this sensitivity is common and of the same magnitude for all engine 

types. Effects of relative humidity and background aerosol loading should also be explored.

• Better characterization of particle losses in near-field sampling probes. AAFEX results 

suggest that PM number and mass measurements are significantly reduced by particle losses 

occurring within the 1-m inlet probes, possibly by thermophoretic or turbulent eddy 

impaction processes. AAFEX observations also suggest that PM measurements are 

influenced by mismatched freestream and inlet tip velocities. Carefully designed 

experiments are needed to characterize these losses/uncertainties and develop procedures for 

minimizing their effects.

• Non-proprietary design for an efficient thermal denuder that operates at high sample flow (up 

to 10 lpm) rates. Volatile aerosols form in aircraft exhaust samples for a variety of reasons. 

Commercially available thermal denuders remove these aerosols but only at low flow rates 

(~1.5 lpm) and for relatively low-volatile aerosol loadings. A high-flow device that both 

evaporates and removes aerosol precursors would be a greatly advance our ability to 

characterize black carbon particles within aged plumes or samples acquired with gas probes 

and diluted a few seconds after entering the sample transport system.

• A simpler, more robust, and standardized exhaust sampling system. The AAFEX aerosol 

sampling system was a plumbing nightmare of fittings, valves, pumps, and tubing that took 

three days of intensive work by three or more technicians to install. Trade studies should be 

conducted to evaluate the relative sacrifice in PM measurement fidelity associated with 

employing much simpler sampling systems. Emissions researchers should collaborate with 

the SAE E-31 committee that is developing an Aerospace Recommended Practice (ARP) for 

exhaust PM sampling to establish an acceptable system design that capitalizes on existing 

facilities and ensures reproducible results between test venues.

• Calibration standards for particle concentration and black carbon mass. At present, there are 

no direct means of calibrating the instruments used to measure PM number and mass. Such 

calibration standards are critically needed before regulations on engine PM emissions can be 

established.

6.00 ACKNOWLEDGEMENTS

The authors gratefully acknowledge the significant contributions of NASA Dryden personnel to 

AAFEX, particularly the excellent project management provided by Frank Cutler and Ron 

Wilcox and the excellent aircraft and technical support provided by the DC-8 crew, Mike 

Bereda, chief. AAFEX was sponsored by the NASA Fundamental Aeronautics, Subsonic Fixed 

Wing program. Any opinions, findings or conclusions expressed with this report are those of the 

authors and do not necessarily reflect the views of NASA.
72

7.00 REFERENCES

Anderson, B. E. et al., 2005; Experiment to Characterize Aircraft Volatile Aerosol and Trace 

Species Emissions (EXCAVATE), NASA/TM-205-213783.

Timko, M. T., Z. Yu, T. B. Onasch, H.-W. Wong, R. C. Miake-Lye, A. J. Beyersdorf, B. E. 

Anderson, K. L. Thornhill, E. L. Winstead, E. Corporan, M. J. DeWitt, C. D. Klingshirn, 

C. Wey, K. Tacina, D. S. Liscinsky, R. Howard, A. Bhargava, 2010; Particulate 

emissions of gas turbine engine combustion of a Fischer-Tropsch synthetic fuel, in 

review.

Wey, C.C. et al. 2006; Aircraft Particle Emission Experiment, NASA/TM-2006-214382.

Wey, C. C., B. E. Anderson, C. Wey, R. C. Miake-Lye, P. Whitefield, and R. Howard (2007), 

Overview on the aircraft particle emissions experiment, Journal of Propulsion and Power 

23, 898-905.
73

8.00 LIST OF APPENDICES

APPENDIX A: Engine Performance and Gaseous Emissions (NASA GRC)

APPENDIX B: Effects of Alternative Fuels on CO and NOX Emissions Performance: A 

Summary of AAFEX Field Mission Data (Aerodyne)

APPENDIX C: VOC Emissions from Jet Aircraft Engines Burning Alternative Fuels: A 

Summary of the Alternate Aviation Fuel Experiment (AAFEX, MSU/ARI)

APPENDIX D: Measurements of Nitrous Acid in Commercial Aircraft Exhaust (Harvard/ARI)

APPENDIX E: Investigations of plume chemistry during AAFEX (ARI)

APPENDIX F: Aircraft Emissions of Methane and Nitrous Oxide during the Alternative 

Aviation Fuel Experiment (Harvard/ARI)

APPENDIX G: Gaseous and Non-volatile Particulate Matter Emissions Measurements in 

CFM56 Engines – AAFEX project (AFRL)

APPENDIX H: Concentrations and Physical Properties of Particles within the Exhaust of 

Aircraft Engines burning Standard and Synthetic Fuels: AAFEX Results (LaRC)

APPENDIX I: Influence of Ambient Temperature on the PM Emissions at the Engine Exit 

(MST)

APPENDIX J: Soot Particle Morphology and Composition (PSU)

APPENDIX K: Composition of Gas Turbine Engine Combustion Volatile Particle Material 

(ARI)

APPENDIX L: Microphysical Evolution of Gas Turbine Engine Combustion Particles (ARI)

APPENDIX M: Determination of the Emissions from an Aircraft Auxiliary Power Unit (APU) 

during the Alternate Aviation Fuels EXperiment (AAFEX)

APPENDIX N: Insights Into The Combustion Chemistry Within a Gas-Turbine Driven Auxiliary

 Power Unit as a Function of Fuel Type and Power Level Using Soot 

 Nanostructure as a Tracer (PSU)

APPENDIX O: Spatial Variation of PM Emissions at the Engine Exit (MST)

APPENDIX P: Sampling System Effects on Particle Emission Measurements (LaRC)

APPENDIX Q: Instrument Inter-comparison (UTRC)
APPENDIX A

74

APPENDIX A: Engine Performance and Gaseous Emissions

Changlie Wey

ASRC Aerospace Corporation

And

Dan Bulzan

NASA Glenn Research Center

During the Alternative Aviation Fuels EXperiment (AAFEX) test series, engine 

performance was measured by collecting data from the cockpit instrument readouts 

during the experimental tests. Engine speed (N1), fan speed (N2), exhaust temperature, 

and fuel flow readouts were recorded by hand for each of the test points. Nominal engine 

power settings were obtained by adjusting the throttle until the desired value of N1 was 

obtained. Care was taken to make sure that the engine had reached a steady operating 

condition before the data was recorded. 

Since the test series was designed to investigate "cold" and "warm" ambient conditions, 

fairly large variations in ambient, inlet temperature were encountered. In order to 

compare engine performance under all conditions, fuel flows and N1 were corrected to 

standard day conditions of temperature and pressure using data from the weather station 

according to the following [1]:

(1) N1 STD = N1/ , where 

(2) Fuel Flow STD = Fuel Flow/(Delta ) , where Delta = Barometric 

Pressure(mbar)/1013.25.

The engine performance data is provided in tables 1-5 for the JP-8, FT-1, FT-2, FT-1/JP8 blend, and FT-2/JP-8 blend. Fuel flows to the engines were measured with analog, 

mass-flow meters, which have an estimated accuracy of plus or minus 1 to 2 % at cruise 

flow rates and reduced accuracy at lower power conditions [2]. Readout of the fuel flow 

could only generally be read in 100 lb/hr increments. For the very low-power conditions, 

4% and 7%, fuel flow readings for some of the test points were the same, however, the 

engine throttle setting had been reduced slightly. Differences in fuel flow readings at 

these very low-power settings should therefore be viewed with caution. Adjustments in 

fuel flow rate were calculated to account for higher fuel heating values of the FischerTropsch fuel and are also provided in the data tables. For these adjustments, the fuel flow 

was multiplied by the ratio of the heating value of the Fischer-Tropsch fuel divided by 

the heating value of the JP-8 fuel to provide an equivalent JP-8 fuel flow rate. Columns 

labeled with Fuel Flow STD-HV adjust the heating value corrected fuel flow rates to 

standard operating day conditions. Ambient conditions as well as calculated values for 

Theta and Delta are provided.

A comparison of engine rotor speed, N1, versus fuel flow rate is provided in figure 1 for 

the left inboard engine, engine #2, and the right inboard engine, engine #3, for operation 
APPENDIX A

75

on JP-8 fuel at cold ambient conditions. As shown in figure 1, there is a slight difference 

at lower engine power settings between the engines with engine #2 achieving requiring 

slightly less fuel than engine #3. At higher engine power settings, the two engines appear 

to be almost identical. Figure 2 shows the same comparison for both engines operating 

on JP-8 but the data was obtained during operation under warm ambient conditions. The 

results are similar to those previously shown for the cold ambient conditions with engine 

#2 requiring slightly less fuel than engine #3 at lower power conditions. 

Figure 1. Comparison of Engine #2 and Engine #3 performance operating on JP-8 fuel 

at cold ambient conditions.

Figure 2. Comparison of Engine #2 and Engine #3 performance operating on JP-8 at 

warm ambient conditions.

N1 Corrected to Standard Day Conditions

0 20 40 60 80 100

Corrected Fuel Flow Rate, lb/hr

0

2000

4000

6000

8000

10000

#2 Engine, cold

#3 Engine, cold

N1 Corrected to Standard Day Conditions

0 20 40 60 80 100

Corrected Fuel Flow Rate, lb/hr

0

2000

4000

6000

8000

10000

#2 Engine, warm

#3 Engine, warm
APPENDIX A

76

Engine performance for all of the fuels is presented in Figure 3 for engine #3. Only 

engine #3 was operated with the various test fuels during the experimental testing. The 

testing required operation of both engines, however, engine #2 was always operated on 

JP-8. Data from engine #3 for all of the fuels tested is shown and plotted for each date of 

testing so it includes data under both warn and cold ambient conditions for all of the fuels 

except the blends where only one ambient condition was run. All data was corrected to 

standard day conditions, but no adjustments for fuel heating value were made in this 

figure. The increased scatter in the data for the FT-2 fuel on January 30 was probably 

caused by very high tail winds, which were encountered during testing on that day. 

Figure 3. Corrected N1 versus corrected fuel flow rate for all fuels.

Figure 4 presents engine performance data for all of the fuels but the fuel flow rate has 

been corrected for fuel heating value and then corrected to standard day operating 

conditions. As shown in figure 4, the correction for heating value decreases the scatter in 

the data slightly compared to figure 3 and shows very similar results for all of the fuels 

within the accuracy of the speed and fuel flow measurements. Again, the increased 

scatter evident for the FT-2 fuel on January, 30 is probably due to the very strong 

tailwinds encountered during the testing. 

Gaseous emissions measured 1 m downstream of the #3 right inboard main engine are 

illustrated in figures 5-13 for all of the fuels tested. Results are shown for NOx, CO, 

unburned hydrocarbons (HC), combustion efficiency, and SO2. NOx emissions are 

presented in figure 5 as a function of fuel mass flow rate for all of the fuels. No 

corrections have been applied to the measured fuel flow rate in figure 5.

N1 Corrected to Standard Day Conditions

0 20 40 60 80 100

Corrected Fuel Flow Rate, lb/hr

0

2000

4000

6000

8000

10000

1-27 JP-8

1-28 JP-8

1-28 FT-1

1-29 FT-1

1-30 FT-2

1-31 FT-2

1-30 FT-1 Blend

1-31 FT-2 Blend
APPENDIX A

77

Figure 4. Corrected N1 versus heating value corrected fuel flow rate for all fuels.

Figure 5. NOx emissions versus measured fuel flow

Also indicated on the figure with a "C" are International Civil Aviation Organization 

(ICAO) certification values for the engine thrust levels corresponding to idle, descent, 

takeoff, and climbout. As shown in figure 5, measured NOx emissions for all of the fuels 

were slightly below the certification values but fairly similar for all of the fuels. There is 

N1 Corrected to Standard Day Conditions

0 20 40 60 80 100

Corrected Fuel Flow Rate, lb/hr

0

2000

4000

6000

8000

10000

1-27 JP-8

1-28 JP-8

1-28 FT-1

1-29 FT-1

1-30 FT-2

1-31 FT-2

1-30 FT-1 Blend

1-31 FT-2 Blend

Fuel Flow, pph

0 2000 4000 6000 8000 10000

EINOx (g/kg-fuel)

0

5

10

15

20

C

C

C

C

FT2 Blend

FT1 Blend

FT2 (Sasol)

FT1 (Shell)

JP8
APPENDIX A

78

some scatter in the NOx data due to differences in engine operating conditions. At higher 

fuel flowrates, the FT-1 and FT-1/JP-8 blend had slightly lower NOx emissions.

NOx emissions plotted as a function of corrected engine speed N1 are presented in figure 

6. Engine speed was corrected to standard day conditions using equation (1).

Figure 6. NOx emissions for all fuels versus corrected N1

This correction improves the agreement with the certification values, especially at the 

higher power conditions. A slight decrease in NOx emissions with the FT1 fuel and FT-1 

Blend at higher power conditions is evident.

Results for CO and unburned hydrocarbons are presented in figures 7 and 8. Fuel 

flowrates have not had any corrections applied. Results are quite similar for both and 

indicate very low levels at all higher power conditions with sharply increasing values at 

the low-power conditions. The large amount of scatter in the data at lower power 

conditions is caused by inaccuracies in the measured fuel flow rate. In many cases, there 

was no measured difference in fuel flowrate for engine power settings of 7% and 4%. 

Plots of CO and HC versus corrected N1 using equation (1) correlate much better at the 

lower power conditions and this is illustrated in figures 9 and 10. CO and unburned 

hydrocarbon emissions for the F-T fuels are reduced at lower power levels compared to 

JP-8. 

N1, corrected

0 20 40 60 80 100

EINOx (g/kg-fuel)

0

5

10

15

20

C

C

C

C

FT2 Blend

FT1 Blend

FT2 (Sasol)

FT1 (Shell)

JP8
APPENDIX A

79

Figure 7. CO emissions for all fuels versus fuel flow 

Figure 8. Unburned hydrocarbon emissions for all fuels versus fuel flow

Fuel Flow, pph

0 2000 4000 6000 8000 10000

EICO (g/kg-fuel)

0

20

40

60

80

100

120

C C

C

C

FT2 Blend

FT1 Blend

FT2 (Sasol)

FT1 (Shell)

JP8

Fuel Flow, pph

0 2000 4000 6000 8000 10000

EIHC (g/kg-fuel)

0

5

10

15

20

25

C C C

C

FT2 Blend

FT1 Blend

FT2 (Sasol)

FT1 (Shell)

JP8
APPENDIX A

80

Figure 9. CO emissions versus corrected N1

Figure 10. Unburned hydrocarbon emissions versus corrected N1

Combustion efficiency measurements are presented in figures 11 and 12 for engine #3 

operating on all of the various fuels. Since combustion efficiency is derived from CO and 

unburned hydrocarbon emissions, it is greater than 99.9% for all engine power levels 

above 7%. Results at low-power conditions are similar to those previously discussed for 

CO and HC emissions with higher combustion efficiencies for the F-T fuels at lower 

power conditions compared to the JP-8 fuel. As expected, the blends ended up in between 

the two neat fuels in terms of combustion efficiency. 

N1, corrected

0 20 40 60 80 100

EICO (g/kg-fuel)

0

20

40

60

80

100

120

C C C

C

FT2 Blend

FT1 Blend

FT2 (Sasol)

FT1 (Shell)

JP8

N1, corrected

0 20 40 60 80 100

EIHC (g/kg-fuel)

0

5

10

15

20

25

C C C

C

FT2 Blend

FT1 Blend

FT2 (Sasol)

FT1 (Shell)

JP8
APPENDIX A

81

Figure 11. Combustion efficiency for all fuels versus fuel flow 

Figure 12. Combustion efficiency measurements versus corrected N1

Fuel Flow, pph

0 2000 4000 6000 8000

Combustion Efficiency, %

95

96

97

98

99

100

101

FT2 Blend

FT1 Blend

FT2 (Sasol)

FT1 (Shell)

JP8

N1, corrected

0 20 40 60 80 100

Combustion Efficiency, %

95

96

97

98

99

100

101

FT2 Blend

FT1 Blend

FT2 (Sasol)

FT1 (Shell)

JP8
APPENDIX A

82

Figure 13. SO2 emissions for all fuels versus fuel flow 

Sulfur dioxide (SO2) emissions are presented in figure 13. As expected, SO2 emissions 

are directly proportional to the amount of sulfur in the fuel. The JP8 fuel had 1148 parts 

per million of sulfur while the neat F-T fuels had essentially no sulfur. This is reflected in 

the SO2 emissions data with the pure fuels having very low levels of SO2 emissions and 

50/50 blends having about half the SO2 emissions of the pure JP-8. The SO2 emissions 

that were measured from the pure F-T fuels are attributed to contamination issues 

associated with fuel handling. 

Fuel Flow, pph

0 2000 4000 6000 8000

EISO2 (g/kg-fuel)

0

1

2

3

4

5

FT2 Blend

FT1 Blend

FT2 (Sasol)

FT1 (Shell)

JP8
APPENDIX A

83

Table 1. JP-8 engine performance data for engines #2 and #3 

N1 

EGT deg 

C N2

Fuel flow 

lb/hr N1-STD

Fuel Flow 

STD N1 

EGT deg 

C N2

Fuel flow 

lb/hr N1-STD

Fuel Flow 

STD

Tamb-deg 

F BP mBar Theta Delta

1/28/09 4% 21 418 58 800 21.7 892 21 447 58 1000 21.7 1115 27 938 0.939 0.926

1/28/09 7% 25 406 62 900 25.8 1002 25 426 62 1000 25.8 1114 28 938 0.941 0.926

1/28/09 30% 52 479 81 2400 53.5 2668 52 472 81 2600 53.5 2890 30 938 0.945 0.926

1/28/09 45% 63.2 538 83 3400 64.9 3766 63.2 525 83 3600 64.9 3988 33 939 0.949 0.927

1/28/09 65% 74 605 89 4800 75.8 5306 74 600 89 5000 75.8 5527 35 939 0.953 0.927

1/28/09 85% 82.7 693 91 6600 84.7 7298 82.7 689 91 6800 84.7 7519 34 939 0.952 0.927

1/28/09 100% 85 740 93 7100 86.7 7813 85 730 93 7100 86.7 7813 39 939 0.962 0.927

1/28/09 7% 25.2 397 62 900 25.7 989 25 413 62 1100 25.5 1209 40 939 0.963 0.927

1/28/09 100% 85 728 92 7100 86.5 7799 85 723 92 7200 86.5 7908 41 939 0.965 0.927

1/28/09 85% 82.5 695 91 6500 83.9 7136 82.5 688 91 6400 83.9 7026 41 939 0.966 0.927

1/28/09 65% 74.1 599 89 4800 75.3 5266 74.1 593 89 5000 75.3 5485 42 939 0.967 0.927

1/28/09 45% 63.5 526 83 3400 64.5 3728 63.1 519 83 3500 64.1 3838 43 939 0.969 0.927

1/28/09 30% 52.5 469 81 2200 53.3 2411 52.5 463 81 2500 53.3 2739 43 939 0.970 0.927

1/28/09 15% 37 412 77 1500 37.6 1643 37 415 77 1600 37.6 1752 44 939 0.971 0.927

1/28/09 7% 24.8 395 62 900 25.2 985 25.2 416 62 1000 25.6 1095 44 939 0.971 0.927

1/28/09 4% 21 417 58 900 21.3 985 21 447 58 1000 21.3 1094 45 939 0.973 0.927

N1 

EGT deg 

C N2

Fuel Flow 

lb/hr N1 STD

Fuel Flow 

STD N1 EGT N2

Fuel Flow 

lb/hr N1 STD

Fuel Flow 

STD

T amb 

deg F BP mBar Theta Delta

1/31/09 4% 21 465 58 850 20.9 921 20.5 488 58 1000 20.4 1083 66 929 1.014 0.917

1/31/09 7% 24.9 455 62 900 24.7 974 25 472 62 1100 24.8 1191 67 929 1.015 0.917

1/31/09 30% 52.5 522 81 2500 52.1 2706 52.5 503 81 2600 52.1 2814 67 929 1.016 0.917

1/31/09 45% 63.5 572 87 3500 63.0 3785 63.5 556 87 3500 63.0 3785 68 929 1.017 0.917

1/31/09 65% 74 640 91 4700 73.4 5086 74 632 91 4800 73.4 5195 67 929 1.016 0.917

1/31/09 85% 82.5 719 96 6100 81.8 6597 82.5 723 96 6100 81.8 6597 68 929 1.017 0.917

1/31/09 100% 88.5 775 98 7400 87.8 8006 88.5 772 98 7400 87.8 8006 68 929 1.016 0.917

1/31/09 4% 21 457 58 800 20.8 866 20.2 475 58 1000 20.0 1083 67 929 1.015 0.917

1/31/09 7% 25 449 62 1000 24.8 1082 25 468 62 1100 24.8 1190 67 929 1.016 0.917

1/31/09 30% 53 514 81 2400 52.5 2595 53 495 81 2600 52.5 2811 68 929 1.018 0.917

1/31/09 45% 63.5 569 88 3400 63.0 3677 64.5 582 88 3400 64.0 3677 68 929 1.017 0.917

1/31/09 65% 74 645 91 4600 73.4 4976 74 631 91 4800 73.4 5192 68 929 1.017 0.917

1/31/09 85% 82.5 719 96 5800 81.8 6273 82.5 731 96 5800 81.8 6273 68 929 1.017 0.917

1/31/09 100% 88.5 786 98 7400 87.7 8002 88.2 779 98 7400 87.4 8002 68 929 1.017 0.917

1/31/09 7% 25.1 434 62 900 24.9 973 25 449 62 1100 24.8 1190 68 929 1.017 0.917

1/31/09 4% 21.9 459 58 900 21.7 973 20 479 58 1000 19.8 1081 68 929 1.017 0.917

JP-8 Cold Ambient 

Date

Nom. 

Engine 

Power

# 2 Engine # 3 Engine Ambient Conditions

JP-8 Fuel Warm Ambient

Date

Nom. 

Engine 

Power

#2 engine #3 engine Ambient Conditions
APPENDIX A

84

Table 2. FT-1 performance data for engine #3 

N1 

EGT 

deg C N2

Fuel 

flow 

lb/hr

 Fuel 

Flow HVC N1 STD

Fuel 

Flow 

STD

Fuel 

Flow 

STD-HV

T amb 

deg F

BP 

mBar Theta Delta

1/29/09 4% 20.5 451 56 1000 1025 21.0 1109 1137 34 937 0.951 0.925

1/29/09 7% 25 430 62 1100 1128 25.6 1220 1251 34 937 0.951 0.925

1/29/09 15% 37.4 422 75 1700 1743 38.3 1883 1931 34 937 0.953 0.925

1/29/09 30% 52.5 479 80 2600 2666 53.8 2877 2950 35 938 0.953 0.926

1/29/09 45% 63.5 535 85 3400 3486 64.9 3756 3852 36 938 0.956 0.926

1/29/09 65% 74.5 610 89 5000 5127 76.1 5516 5656 38 938 0.959 0.926

1/29/09 85% 83 695 94 6600 6768 84.7 7273 7458 39 938 0.961 0.926

1/29/09 100% 85.4 717 95 7000 7178 87.0 7699 7895 40 939 0.963 0.927

1/29/09 7% 24.9 405 64 1000 1025 25.4 1099 1126 41 939 0.965 0.927

1/29/09 100% 86.1 744 95 7200 7383 87.5 7899 8099 42 939 0.968 0.927

1/29/09 85% 83 701 94 6600 6768 84.4 7239 7423 42 939 0.968 0.927

1/29/09 65% 74 594 90 4800 4922 75.2 5261 5395 43 939 0.969 0.927

1/29/09 45% 64 516 85 3400 3486 64.9 3722 3816 44 939 0.972 0.927

1/29/09 30% 52.9 464 80 2500 2564 53.6 2732 2801 46 939 0.975 0.927

1/29/09 15% 37 414 76 1600 1641 37.4 1746 1791 47 939 0.978 0.927

1/29/09 7% 25 422 64 1000 1025 25.3 1091 1119 48 939 0.978 0.927

1/29/09 4% 20.5 447 58 1000 1025 20.7 1090 1117 49 939 0.980 0.927

N1 

EGT 

deg C N2

Fuel 

Flow 

lb/hr

Fuel 

Flow HVC N1 STD

Fuel 

Flow 

STD

Fuel 

Flow 

STD-HV

T amb 

deg F

BP 

mBar Theta Delta

1/28/09 4% 20.5 477 58 1000 1025 20.5 1086 1114 56 935 0.995 0.923

1/28/09 7% 25 450 64 1100 1128 25.0 1194 1224 57 935 0.996 0.923

1/28/09 15% 37 446 76 1600 1641 37.1 1739 1783 57 934 0.996 0.922

1/28/09 30% 52.5 496 82 2500 2564 52.6 2716 2785 58 934 0.997 0.922

1/28/09 45% 63.2 547 86 3200 3281 63.2 3473 3561 59 934 0.999 0.922

1/28/09 65% 74 627 91 4800 4922 74.0 5207 5339 59 934 1.000 0.922

1/28/09 85% 82.5 709 94 6000 6152 82.5 6509 6675 59 934 1.000 0.922

1/28/09 100% 87.5 768 96 7200 7383 87.5 7811 8009 59 934 1.000 0.922

1/28/09 7% 25 439 64 1000 1025 25.0 1085 1112 59 934 1.000 0.922

1/28/09 100% 87.1 779 95 7100 7280 87.1 7703 7898 59 934 1.000 0.922

1/28/09 85% 82.5 712 94 6200 6358 82.5 6727 6898 59 934 1.000 0.922

1/28/09 65% 74 614 91 4800 4922 74.0 5209 5341 59 934 0.999 0.922

1/28/09 45% 63 534 86 3200 3281 63.0 3472 3560 59 934 1.000 0.922

1/28/09 30% 52.5 476 82 2400 2461 52.5 2604 2671 59 934 0.999 0.922

1/28/09 15% 37.5 435 78 1600 1641 37.5 1736 1780 59 934 0.999 0.922

1/28/09 7% 25.5 447 64 1000 1025 25.5 1086 1113 58 934 0.999 0.922

1/28/09 4% 20.5 478 58 1000 1025 20.5 1086 1114 58 934 0.997 0.922

Date

Nom. 

Engine 

Power

# 3 Engine Ambient Conditions

FT-1 Cold Ambient

Date

Nom. 

Engine 

Power

#3 engine Ambient Conditions

FT-1 Warm Ambient 
APPENDIX A

85

Table 3. FT-2 performance data for engine #3.

N1 

EGT 

deg C N2

Fuel 

Flow

Fuel 

Flow HVC N1 STD

Fuel 

Flow 

STD

Fuel 

Flow 

STD-HV

T amb 

deg F

BP 

mBar Theta Delta

1/31/09 4% 20 459 58 950 968 20.6 1063 1083 30 932 0.944 0.920

1/31/09 7% 24.5 436 62 1050 1069 25.2 1175 1197 30 932 0.944 0.920

1/31/09 15% 37 429 76 1600 1630 38.1 1789 1822 31 932 0.945 0.920

1/31/09 30% 52.5 485 81 2500 2546 53.9 2791 2842 32 932 0.948 0.920

1/31/09 45% 63 532 84 3400 3463 64.5 3786 3856 35 932 0.953 0.920

1/31/09 65% 74 600 89 4800 4889 75.7 5337 5436 36 932 0.956 0.920

1/31/09 85% 83 692 93 6500 6620 84.7 7213 7347 38 932 0.960 0.920

1/31/09 100% 85.5 706 94 6800 6926 87.1 7532 7671 40 932 0.963 0.920

1/31/09 7% 24.8 408 64 1000 1018 25.2 1106 1127 41 932 0.966 0.920

N1 

EGT 

deg C N2 N1 STD

Fuel 

Flow 

lb/hr

Fuel 

Flow HVC

Fuel 

Flow 

STD

Fuel 

Flow 

STD-HV

Tamb 

deg F

BP 

mBar Theta Delta

1/30/09 4% 20.6 479 58 20.5 1000 1018 1078 1098 62 937 1.005 0.925

1/30/09 7% 25.3 456 64 25.2 1100 1120 1186 1208 63 937 1.007 0.924

1/30/09 15% 37 454 76 36.9 1600 1630 1725 1757 63 936 1.008 0.924

1/30/09 30% 53 506 82 52.8 2500 2546 2694 2744 64 936 1.009 0.924

1/30/09 45% 63 544 86 62.7 3600 3667 3878 3950 64 936 1.010 0.924

1/30/09 65% 74.5 632 92 74.1 4800 4889 5170 5266 64 936 1.010 0.924

1/30/09 85% 83 733 95 82.6 6400 6518 6899 7026 65 935 1.011 0.923

1/30/09 100% 88 763 98 87.5 7400 7537 7978 8126 64 935 1.010 0.923

1/30/09 7% 25 442 64 24.9 1000 1018 1078 1098 64 935 1.010 0.923

1/30/09 100% 88 803 96 87.5 7800 7944 8407 8563 65 935 1.011 0.923

1/30/09 85% 83 746 95 82.5 6800 6926 7322 7457 66 935 1.013 0.923

1/30/09 65% 74 639 92 73.5 4800 4889 5167 5263 66 935 1.013 0.923

1/30/09 45% 60 534 86 59.7 3200 3259 3449 3513 65 935 1.011 0.923

1/30/09 30% 52 486 82 51.7 2500 2546 2694 2743 65 935 1.012 0.923

1/30/09 15% 37.5 442 78 37.3 1600 1630 1724 1755 65 935 1.012 0.923

1/30/09 7% 25 454 64 24.8 1100 1120 1185 1206 66 935 1.013 0.923

1/30/09 4% 20 485 58 19.9 1000 1018 1077 1096 66 935 1.013 0.923

Date

Nom. 

Engine 

Power

#3 Engine Ambient Conditions

FT-2 Cold Ambient

Date

Nom. 

Engine 

Power

#3 Engine Ambient Conditions

FT-2 Warm Ambient
APPENDIX A

86

Table 4. FT-1/JP-8 engine performance data for engine #3.

Table 5. FT-2/JP-8 engine performance data for engine #3.

N1 EGT N2

Fuel 

flow 

lb/hr

Fuel 

Flow HVC N1 STD

Fuel 

Flow 

STD

Fuel 

Flow 

STD-HV

T amb 

deg F

BP 

mBar Theta Delta

1/30/09 4% 20 460 58 1000 1012 20.4 1104 1117 37 938 0.957 0.926

1/30/09 7% 25 430 62 1100 1113 25.5 1213 1227 38 938 0.960 0.926

1/30/09 15% 37 431 78 1700 1720 37.7 1867 1888 41 939 0.966 0.927

1/30/09 30% 52.7 483 81 2500 2529 53.6 2743 2774 42 939 0.967 0.927

1/30/09 45% 63.1 532 83 3500 3540 64.0 3829 3874 45 939 0.973 0.927

1/30/09 65% 74.3 617 90 5000 5058 75.3 5466 5529 46 939 0.974 0.927

1/30/09 85% 82.5 699 93 6500 6575 83.5 7097 7179 47 939 0.977 0.927

1/30/09 100% 86.5 738 95 7200 7283 87.5 7858 7949 47 939 0.978 0.927

1/30/09 7% 24.9 416 62 1000 1012 25.2 1091 1103 48 939 0.979 0.927

1/30/09 4% 20.2 456 58 1000 1012 20.4 1090 1103 48 939 0.980 0.927

1/30/09 100% 87.5 767 93 7500 7587 88.4 8174 8269 49 939 0.980 0.927

1/30/09 85% 82.5 699 91 6600 6676 83.3 7190 7274 49 939 0.981 0.927

1/30/09 65% 74.2 602 90 4800 4855 74.9 5225 5285 50 939 0.983 0.927

1/30/09 45% 63.5 540 85 3500 3540 64.0 3807 3851 51 939 0.984 0.927

1/30/09 30% 53 477 81 2600 2630 53.4 2827 2859 51 939 0.985 0.927

1/30/09 15% 37 427 78 1600 1618 37.3 1738 1758 52 939 0.986 0.927

1/30/09 7% 25 435 62 1100 1113 25.2 1194 1208 53 939 0.988 0.927

1/30/09 4% 20 456 58 1000 1012 20.1 1086 1098 53 939 0.988 0.927

Ambient Conditions

FT-1/JP-8 Blend

#3 Engine

Nom. 

Engine 

Date Power

N1 

EGT 

deg C N2

Fuel 

Flow 

lb/hr

Fuel 

Flow HVC N1 STD

Fuel 

Flow 

STD

Fuel 

Flow 

STD-HV

T amb 

deg F

BP 

mBar Theta Delta

1/31/09 4% 21 467 58 1000 1012 21.1 1094 1106 52 933 0.986 0.921

1/31/09 7% 25 443 64 1100 1113 25.2 1202 1216 53 933 0.988 0.921

1/31/09 15% 37 436 76 1600 1618 37.2 1747 1768 53 933 0.989 0.921

1/31/09 30% 52.5 489 82 2600 2630 52.8 2838 2871 54 933 0.990 0.921

1/31/09 45% 63 539 86 3400 3439 63.3 3708 3751 55 933 0.991 0.921

1/31/09 65% 74.5 620 90 4800 4855 74.8 5234 5294 55 933 0.992 0.921

1/31/09 85% 82.7 702 94 6400 6474 83.0 6976 7056 55 933 0.993 0.921

1/31/09 100% 87.5 747 96 7400 7485 87.7 8059 8152 56 933 0.994 0.921

1/31/09 7% 25.5 428 65 1000 1012 25.5 1088 1100 57 933 0.997 0.921

1/31/09 100% 87.5 761 96 7400 7485 87.6 8044 8137 58 933 0.998 0.921

1/31/09 85% 82.9 701 94 6400 6474 82.9 6950 7031 59 933 1.000 0.921

1/31/09 65% 74.1 605 90 4800 4855 74.1 5215 5276 60 932 1.001 0.920

1/31/09 45% 63 529 86 3400 3439 62.9 3693 3735 60 932 1.002 0.920

1/31/09 30% 52.8 478 82 2500 2529 52.7 2713 2745 61 932 1.003 0.920

1/31/09 15% 37 428 76 1600 1618 37.1 1746 1766 55 932 0.993 0.920

1/31/09 7% 25 440 64 1000 1012 24.9 1085 1097 61 932 1.004 0.920

1/31/09 4% 20.5 472 58 1000 1012 20.4 1086 1098 62 931 1.005 0.919

Ambient Conditions

FT-2/JP-8 Blend

#3 Engine

Nom. 

Engine 

Date Power
APPENDIX A

87

References

[1] Yechout, T., Morris, S., Bossert, D. and Hallgren, W., "Introduction to Aircraft Flight 

Mechanics: Performance, Static Stability, Dynamic Stability, and Classical Feedback 

Control, AIAA Education Series, 2003

[2] Willard Dodds, General Electric Aircraft Engines, personal communication
APPENDIX B

88

APPENDIX B: Effects of Alternative Fuels on CO and NOX Emissions 

Performance

A Summary of AAFEX Field Mission Data

Michael T. Timko, Scott C. Herndon, Ezra C. Wood, W. Berk Knighton, Richard C. 

Miake-Lye

Aerodyne Research, Inc.

45 Manning Road

Billerica MA 01821

Abstract

We report CO and NOX emissions measurements for gas turbine engine combustion of 

JP-8 and two Fischer-Tropsch (FT) synthetic fuels. Compared to JP-8 combustion, 

combustion of the FT fuels reduces EIm-NOX by 5-10% at high power and reduces EImCO by as much as 10% at idle. Increasing temperature increases EIm-NOX at high power 

and decreases EIm-CO at low power. We outline a protocol for analyzing emissions 

performance data for combustion of alternative jet fuels that accounts for fuel energy 

differences compared to JP-8.

Introduction

The cost and availability of petroleum-based transportation fuels and the environmental 

impacts of petroleum fuel combustion motivate a search for alternatives. Because of the 

demanding requirements of air transportation, replacing petroleum jet fuels (Jet-A, JP-8, 

and similar) is a particular challenge that will require better characterization of many 

different aspects of fuel supply and usage.1

 Alternative fuel combustion products is one 

area that requires greater attention. Previous studies have shown dramatic decreases in 

particulate material (PM) emissions when petroleum jet fuels are replaced with synthetic 

jet fuels synthesized via the Fischer-Tropsch (FT) process. A primary objective of the 

Alternative Aviation Fuels EXperiment (AAFEX) was to document the emissions 

performance for a CFM56 engine for both petroleum jet fuel (JP-8) and two FT fuels –

one derived from a natural gas feedstock (termed FT1) and the other derived from coal 

(termed FT2). Additional components of the AAFEX test were to characterize physical 

and chemical evolution of the exhaust plume and to quantify the effects of ambient 

temperature on emissions performance. 

In total, six teams contributed to the experimental effort and a comprehensive suite of 

measurements was performed. In this report, we summarize our findings on NOX and 

CO emissions performance. Additional reports summarize hydrocarbon emissions and 

speciation, exhaust plume evolution, and NOX speciation.

Data Collection Method and Experimental Protocol

The port (engine #1) and starboard (engine #2) CFM56-2C1 engines mounted on the 

NASA DC-8 aircraft served as the test engines. The complete test matrix included 
APPENDIX B

89

measurements at 1 m and 30 m from the engine exit plane, under "cold" (270-280 K) and 

"warm" (280-295 K) ambient conditions, and for five different fuels. Different ambient 

temperature conditions were sampled by performing tests at night and during the 

afternoon. Coincidentally, the relative humidity of the "cold" tests was much higher than 

during the "warm" tests, and we took steps, outlined below, to remove the influence of 

humidity on NOX emissions performance. Additionally, measurements were routinely 

made at 143m from the engine exit plane and occasionally using the Aerodyne 

Laboratory as a mobile platform. Here, we summarize data collected at the 1 m and 30 m 

locations only; the Aerodyne Laboratory was disengaged from the sampling manifold 

during the FT1/JP-8 blended fuel tests, therefore we do not report data for that fuel here. 

Table 1 provides NASA fuel analysis summary data for the five fuels tested. Standard 

data collection methods and experimental protocol were followed during the AAFEX 

test. Wey et al.2 summarize the methods used for a previous emissions study and no 

substantial differences were introduced into the Wey et al.2 testing and sampling protocol. 

Table 1. Summary of Relevant Fuel Properties.

Fuel Source Densitya (g cm-3) Heat of 

Combustiona

(MJ kg-1)

EIm-CO2

b

(g kg-1)

JP-8 petroleum 0.815 (1) 43.3 (1) 3160

FT1 Shell, natural 

gas

0.768 (0.942) 44.4 (1.025) 3090

FT1/JP-8 0.793 (0.972) 43.8 (1.011) 3130

FT2 Sasol, coal 0.761 (0.933) 44.1 (1.018) 3110

FT2/JP-8 0.789 (0.967) 43.8 (1.011) 3140 a

density and heat of combustion data reported by NASA GRC personnel.

b EIm-CO2 calculated using Air Force Research Lab fuel analysis data.

Data Analysis Method

Figure 1 provides EIm-NOX data measured at 30 m for the five different fuels for both 

"warm" and "cold" test conditions. Clear but minor (<20%) effects of both ambient 

temperature and fuel composition are apparent in Figure 1. However, we caution that 

Figure 1 has not been corrected for differences in fuel energy content and ambient 

conditions. Additionally, detailed analysis (reported below) revealed some discrepancies 

between the port and starboard engines and the 1- and 30-m sample probes. Therefore, 

Figure 1 must be interpreted with care. Although the observed effect is minor, it was 

sufficiently large to motivate a more careful analysis of NOX emissions. 
APPENDIX B

90

Figure 1. EIm-NOX data for the test fuels measured at 30 m.

Making quantitative comparisons of emissions performance for different fuels requires 

careful analysis to remove the effects of fuel energy content differences, ambient 

conditions, etc. The data plotted in Figure 1 have already been corrected for combustion 

differences resulting from differing carbon/hydrogen ratios of the various fuels using the 

EIm-CO2 values provided in Table 1. In addition, we used the following data analysis 

refinements to attempt to bring the emissions performance of the test fuels to the same 

baseline:

1. Fuel flow data were normalized by fuel energy content (provided in Table 1) 

using the equation:

2. EIm data were converted into "energy" EIs using the equation:

We note that the units of energy-EIs are pollutant mass per fuel energy content –

rather than pollutant mass per fuel mass.

3. NOX data were corrected for differences in ambient humidity using the 

relationship recommended by Wey et al. (2007) following the advice of GE 

technical staff:

where hs is the specific humidity of ambient air measured as kg of water per kg of 

dry air. A NASA meteorology data station, located less than 50 m from the test 

engines, collected ambient temperature, pressure, and relative humidity data that 

were used to make the ambient humidity correction.

combustion, fuel X

combustion, JP 8

H

energy normalized fuel flow measured fuel flow

H −

∆ = ∆

( ) ( )

combustion, fuel X

EI species Y energy EI species Y H − = ∆

E I NO humidity corrected E I NO measured exp 19 h m X − = ( ) m X − − ( )   ( s 0.00629)  
APPENDIX B

91

4. During data analysis, we recognized that 1 m and 30 m EI data sometimes 

exhibited systematic biases. We provide additional information in the Appendix 

documenting the effect. At this time, the source of the bias is unclear. Potential 

contamination of the 30-m sampling line or improper determinations of ambient 

trace gas concentrations may both play a role. In any event, NOX and CO have 

typically been observed to depend marginally – if at all – on sampling location. 

Since our current hypotheses implicate only the accuracy of the 30-m data taken 

during AAFEX, we restrict our data report for NOX and CO to the 1-m rake.

5. The emissions performance of the port and starboard engines was very different 

throughout the test. Since the port engine was used only for JP-8 and the

starboard engine was used for both JP-8 and the FT fuels, we restrict our analysis 

to the starboard engine. The Appendix provides more details on the emissions 

performance differences in the port and starboard engines.

6. To improve interpretability, "warm" emissions performance data were retained in 

plots of EIs vs. fuel flow rates. When EIs are plotted vs. ambient temperature, all 

available data are retained.

With the exception of the humidity refinement, we have treated NOX and CO data 

identically. In all cases, we have not at this time corrected for ambient temperature 

and/or humidity using the standard Boeing Fuel Flow Method (BFFM). Continuing work 

will focus on resolving the discrepancy between the 1m and 30 m and applying the 

BFFM correction factor.

NOX Emissions Performance

The left panel of Figure 2 is a plot of NOX emissions performance as a function of energy 

normalized fuel flow rate. The corrections and refinements described previously make 

interpretation of the general features of the NOX performance data straightforward. First, 

FT1 fuel combustion reduces EIm-NOX by about 10% for fuel flow rates greater than 0.6 

kg sec-1 (i.e., >65% power). The NOX reduction associated with FT1 fuel is less than 5% 

for fuel flow rate less than 0.6 kg sec-1

. Second, the NOX reduction associated with FT2 

fuel is smaller than for FT1 fuel and the difference is smaller than our estimated limits of 

experimental uncertainty and reproducibility (±5%). Third, as documented by the right 

panel of Figure 2, increasing ambient temperature increases EIm-NOX for power greater 

than 30%. At a given temperature, EIm-NOX has similar slopes with respect to ambient 

temperature for the various fuels and EIm-NOX for the FT1 fuel was always less than for 

JP-8.
APPENDIX B

92

Figure 2. NOX emissions performance corrected for fuel energy content and ambient 

relative humidity as a function of fuel flow rate (left panel) and ambient temperature 

(right panel).

The 5-10% NOX reduction that we observed during AAFEX is consistent with two 

previous tests of natural-gas FT fuels emissions performance: 1) Pratt & Whitney on a 

PW308 engine (Florida) and 2) GE on a CFM56-7 engine (Ohio). While operating at 

85% power, EIm-NOX for the PW308 engine was reduced by about 7% for FT fuel 

combustion (Shell, natural gas) relative to JP-8. Interestingly, EIm-NOX at idle was 

greater for the FT fuel tested for the PW308 engine, though the difference may be due to 

experimental noise. During the CFM56-7 test, EIm-NOX was reduced by 11% for FT fuel 

combustion (natural gas, Syntroleum) relative to Jet-A1. No previous tests examined 

combustion of the coal-based FT fuel (FT2) studied during AAFEX.

CO Emissions Performance

Figure 3 provides plots of EIm-CO as a function of energy content fuel flow rate (left 

panel) and ambient temperature (right panel) for 4%, 7%, and 30% power. The left panel 

of Figure 4 indicates roughly a 10% decrease in EIm-CO for FT1 fuel combustion relative 

to either JP-8 or the FT2 fuel. The left panel of Figure 3 shows the expected dependence 

of EIm-CO on ambient temperature and supports the conclusion that EIm-CO is greater for 

JP-8 and FT2 fuel combustion than FT1 fuel at all ambient temperatures studied during 

AAFEX. Just as was the case for EIm-NOX (see Figure 2), the ambient temperature 

dependence of EIm-CO is similar for all the fuels studied. The temperature dependence 

of EIm-CO is strongest for 4% thrust and is nearly absent (to within our measurement 

capability) for powers greater than 30%.
APPENDIX B

93

Figure 3. CO emissions performance corrected for fuel energy content as a function of 

fuel flow rate (left panel) and ambient temperature (right panel).

Previous measurements of EIm-CO emissions performance for FT fuels conflict. During 

the PW308 test, EIm-CO at 7% was 30% lower for combustion of the Syntroleum natural 

gas FT fuel compared to JP-8. During the CFM56-7 tests, EIm-CO was 30% lower for 

Shell natural gas FT fuel combustion compared to Jet-A; however, EIm-CO was the same 

for FT fuel and Jet-A1, making interpretation of the CFM56-7 EIm-CO data ambiguous. 

In summary, the AAFEX data indicate that EIm-CO may be reduced slightly for FT1 fuel 

combustion relative to JP-8 and we therefore conclude that the AAFEX data are more 

consistent with the PW308 test data.

Appendix

The discrepancies between 1-m and 30-m and port- and starboard-engine data are 

provided here.

Sample Rake Discrepancy

Figure A1 contains corrected EIm-NOX plotted as a function of energy normalized fuel 

flow rate for the 1 m and 30 m sampling locations. The 1 m EIm-NOX data are 

systematically lower than the 30 m data. To simplify interpretation, Figure A1 is 

restricted to the port engine. We attribute the discrepancy to one of two phenomena: 1) 

improper accounting of the ambient background or 2) contamination of the 30-m 

sampling line. 
APPENDIX B

94

Figure A1. Sample rake discrepancy for EIm-NOX observed at AAFEX. Data restricted 

to JP-8 combustion on the port engine.

For the 30-m samples – but not the 1-m samples – ambient background air influences the 

measured trace gas concentrations. If trace gas concentrations in the ambient air were not 

recorded accurately, then a systematic error might be expected in the 30-m data. 

Standard operating procedure is to sample ambient air just prior to and just following the 

engine test and to average these measurements to provide the ambient trace gas 

concentrations. During AAFEX, this method of ambient air sampling was not always 

possible because of a range of factors not in our control. We will continue to work to 

identify suitable periods of ambient air sampling to remove the potential for biases 

introduced into the EI calculations.

In terms of contamination, the sample lines were exposed to differing levels of soot and 

other emissions during the tests. As a result, chemical processing that may have occurred 

in the sampling lines may have been different in the 1 m and 30 m sample lines. To 

remove potential contaminants, the sample lines were flushed with water midway through 

the test. Water flushing may have inadvertently introduced additional discrepancies 

because of retained moisture and/or differences in cleaning efficiency. At this time, we 

can neither conclusively confirm nor deny potential contamination during transport 

through the sample lines and will continue to evaluate the data to arrive at the firmest 

conclusion possible. 
APPENDIX B

95

Port and Starboard Engine Discrepancy

The left panel of Figure A2 plots EIm-NOX as a function of energy content normalized 

fuel flow rate. The port engine consistently has higher EIm-NOX than the starboard 

engine; the difference is greatest for flow rates greater than 0.6 kg sec-1 (power > 65%). 

Likewise, EIm-CO was lower for the port engine than the starboard engine (data not 

shown here). The difference between the two engines will not likely ever be known; 

however, in the right panel of Figure A2 we provide a plot that may provide some clues. 

Figure A2 is a plot of EIm-CO as a function of EIm-NOX in log-log space. When plotted 

in as in Figure A2, the NOX/CO behavior of the two engines collapses onto a universal 

curve – at least to within the limits of experimental uncertainty and reproducibility. 

Figure A2. EIm-NOX as a function of energy normalized fuel flow rate (left panel) and 

EIm-CO as a function of EIm-NOX (right panel).

The right panel of Figure A2 implicates combustion temperature as the difference 

between the port and starboard engines. CO emissions are expected to decrease with 

increasing combustion temperature, whereas NOX emissions should increase with 

increasing combustion temperature – all other factors being held equal. We did not have 

the capability to measure combustion temperatures during AAFEX, but we did measure 

exhaust gas temperatures. Consistent with our hypothesis, the left panel of Figure A3 

shows that the port engine exhaust gas temperature was always greater than the starboard 

engine. The right panel of Figure A3 is a plot of 1-m EIm-NOX data as a function of 

exhaust gas temperature for the port and starboard engines. Interestingly, Figure A3 

indicates that the port engine emits slightly more NOX than the starboard engine for 
APPENDIX B

96

exhaust gas temperatures greater than 700 °C and that the starboard engine emits more 

for exhaust gas temperatures less than 600 °C. In addition to systematic differences in 

exhaust gas temperature, the two engines also operated at different fuel flow rates and fan 

speeds (N1 and N2) to achieve the same nominal thrust level. These additional factors 

are consistent with the aicraft engine aging model proposed by Lukachko and Waitz3 and 

may explain the ambiguous trends captured in the right panel of Figure A3. Therefore 

based on Figures A2 and A3, we conclude that differences in combustion temperature 

may play a role in the CO and NOX emissions differences observed for the port and 

starboard engines. Additional analysis is required to determine whether differences in 

combustion temperature alone can explain the different CO and NOX emissions behavior.

Figure A3. Exhaust gas temperature as a function of fuel flow rate (left panel) and EImNOX as a function of exhaust gas temperature (left panel) for the port and starboard 

engines studied during AAFEX.

References

1. Rye, L.; Blakey, S.; Wilson, C. W., Energy & Environmental Science 3, (1), 17-27.

2. Wey, C. C.; Anderson, B. E.; Wey, C.; Miake-Lye, R. C.; Whitefield, P.; Howard, R., 

Journal of Propulsion and Power 2007, 23, (5), 898-905.

3. Lukachko, S. P.; Waitz, I. A. In Effects of engine aging on aircraft NOx emissions, 

International Gas Turbine Exhibition, Orlando, FL, 1997; Orlando, FL, 1997.
APPENDIX C

97

APPENDIX C: VOC Emissions from Jet Aircraft Engines Burning Alternative 

Fuels

A Summary of the Alternate Aviation Fuel Experiment (AAFEX)

W. B. Knighton,a S. C. Herndon,b E. C. Wood,b M. T. Timkob and R. C. Miake-Lyeb

a

Department of Chemistry and Biochemistry

Montana State University

Bozeman, MT 59717

b

Aerodyne Research Inc.

Billerica, MA 01821

Introduction

Instabilities in the cost and supply of crude oil has spurred interest in developing liquid 

fuels from alternative feed stocks, including biomass, natural gas and coal. Alternate 

aviation fuels have been produced from coal and natural gas using the Fischer-Tropsch 

(FT) process. The chemical composition of these FT fuels is substantially different than 

conventional aviation fuel (kerosene) in that they are essentially free of sulfur and 

aromatic hydrocarbons. Previous studies have demonstrated that these FT fuels result in 

substantially lower particulate matter (PM) emissions, which makes them attractive for 

reducing the impact of aviation emissions on the environment. Less is known about the 

gaseous emissions from these alternative fuels. The Alternative Aviation Fuels 

EXperiment (AAFEX) was conducted to characterize the PM and gaseous combustion 

emission products from FT fuels in aviation gas turbine engines.

This report focuses on the VOC emissions performance related to fuel type and ambient 

temperature. Other teams contributed to this experimental effort and a comprehensive 

suite of gaseous and PM measurements were performed. Those results are summarized 

in other reports.

Experimental 

The AAFEX measurement campaign was conducted in January 2009 at the Dryden Flight 

Research Center using the CFM56-2C1 engines mounted on the NASA DC-8 aircraft. A 

primary objective of this test was to document the changes in the combustion exhaust 

emissions between conventional JP-8 fuel and two FT fuels; one derived from natural gas 

(FT1) and another derived from coal (FT2). To delineate the influence of ambient 

conditions on the exhaust emissions, the port inboard engine burned JP-8 fuel while the 

starboard engine burned one of the alternative fuels. Exhaust samples were alternatively 

drawn from either engine from dedicated probes located at 1m and 30m from the engine 

exit. The VOC measurements discussed in this report were made using the 1m dilution 

probe. The desert location experiences wide diurnal variations in ambient temperature 

and tests were conducted early in the morning (cold 270-280K) and again in the 

afternoon (warm 280-295K) to examine the influence of ambient conditions. 
APPENDIX C

98

A suite of VOCs including formaldehyde, acetaldehyde, methanol, ethene, propene, 

benzene, toluene, phenol, styrene, and naphthalene were measured. Formaldehyde and 

ethene were measured by tunable infrared laser differential absorption spectroscopy 

(TILDAS). The remaining species were measured by chemical ionization spectrometry 

using a proton transfer reaction mass spectrometer (PTR-MS). A complete description of 

the TILDAS and PTR-MS techniques and their application to measurement of VOCs in 

jet engine exhaust is provided in our previous papers.1,2 Additional information 

regarding the quantification details of the PTR-MS can be found in Appendix I. VOC 

measurements were continuously recorded, TILDAS (1-hz), PTR-MS (0.3-hz), 

throughout the testing. The times series concentration data is then averaged over the 

appropriate time intervals that are defined when the engines were under stable operations. 

These averaged VOC concentrations were converted to emission ratios (ER) by dividing 

them by their appropriately averaged CO2 concentrations. Emission indices are 

computed via Eq. 1:

 (1)

 

Where and are the molecular weights of the component (X) and CO2, 

respectively. is the emission index of CO2, which is 3160 g/kg, 3090 g/kg and 3110 

g/kg for JP-8, FT1 and FT2 fuels, respectively. 

Results and Discussion

VOC emissions scaling – decoupling fuels effects from the influence of engine power 

and ambient temperature

VOC emissions from jet aircraft engines exhibit a strong inverse non-linear dependence 

with engine power.1-4

 Ambient temperature also exerts a strong influence with colder 

temperatures leading to higher emissions. Under static ambient conditions, constant 

pressure, temperature, and relative humidity, combustor inlet conditions (combustor 

pressure, inlet temperature, fuel flow, and fuel air ratio) could be set to provide 

reproducible engine operating conditions. In practice, ambient conditions are not 

constant and these changes make it impossible to replicate combustor inlet conditions. 

To a first order approximation, the variations in the emissions due to variability in engine 

power, ambient temperature, and fuel structure are all about the same order of magnitude. 

This is demonstrated in Figure 1, where the EIs for ethene and formaldehyde are plotted 

as a function of engine power. This figure illustrates that all of the emissions decrease 

rapidly with increasing power and that colder temperatures generally lead to higher 

emissions. It is not immediately obvious from the data shown in these figures how to 

quantify the changes in emissions that are related to fuel composition. Our previous 

work on VOC emissions has shown that we can delineate exhaust composition changes 

from the effects of temperature and engine power through a normalization process. We 

call this normalization process "emission scaling", because we have observed that 

virtually all of the VOC exhaust emission components scale in a near-linear relationship 

with respect to one another.1 This emission scaling relationship is demonstrated in 

EI X (gx kg fuel)= ERX mole x mole ( CO2 )[MWx MWCO2 ]EICO2 gCO2 ( kg fuel)

MWx MWCO2

EICO2
APPENDIX C

99

Figure 2, where we have taken the EI data in Figure 1 for formaldehyde and ethene and 

plotted the formaldehyde EIs versus the ethene EIs. The marker styles in Figure 2 

indicate the different fuels and are colored to reflect ambient temperature conditions. 

This figure nicely illustrates that the emissions of these two components scale linearly 

and that the different fuels produce different amounts of formaldehyde relative to that of 

ethene. 

Figure 1. Variation of ethene and formaldehyde emissions with engine power. Marker 

styles indicate fuel type and marker colors reflect ambient temperature.

Figure 2. Emissions scaling plot of formaldehyde versus ethene. 
APPENDIX C

100

We use the slopes of the lines fitted to the data shown in Figure 2 to quantify the amount 

of formaldehyde emitted per unit of ethene. This same procedure has been applied to all 

of the other measured VOCs. These normalized emissions can then be used to build a 

chemical speciation profile for each fuel. These ethene normalized emissions and the 

correlation coefficients, R, from the linear regressions are summarized in Table 1.

Table 1. Compound EIs normalized to ethene for the three fuels used at AAFEX. 

JP8 FT 1 FT 2

Compound R R R

ethene 1 ------ 1 ------ 1 ------

formaldehyde 0.752 0.996 0.602 0.998 1.06 0.998

methanol 0.112 0.996 0.087 0.996 0.158 0.993

propene 0.382 0.996 0.34 0.993 0.74 0.998

acetaldehyde 0.274 0.993 0.245 0.987 0.422 0.998

butenes + acrolein 0.351 0.997 0.289 0.996 0.659 0.999

acetone + propanal 

+ glyoxal

0.135 0.997 0.129 0.985 0.358 0.994

a

mass 71 0.229 0.999 0.18 0.998 0.504 0.996

benzene 0.12 0.996 0.018 0.941 0.056 0.994 a

mass 85 0.106 0.998 0.089 0.998 0.259 0.993

toluene 0.057 0.999 0.004 0.931 0.022 0.997

C8H10 + C7H6O 0.093 0.997 0.005 0.803 0.023 0.986

C9H12 + C8H8O 0.101 0.991 0.0045 0.114 0.017 0.868

C10H12 + C9H10O 0.061 0.986 0.0058 0.547 0.012 0.549

C11H14 + C10H12O 0.032 0.983 0.0036 0.423 0.0074 0.655

naphthalene 0.028 0.951 0.01 0.935 0.02 0.911

methylnaphthalenes0.012 0.83 0.014 0.976 0.018 0.8

dimethylnaphthalenes0.009 0.518 0.017 0.982 0.019 0.892

styrene 0.026 0.994 0.002 0.681 0.0053 0.94

phenol 0.051 0.975 0.013 0.823 0.028 0.842 a GC/PTR-MS analysis indicates that mass 71 and mass 85 represent multiple 

compounds which include the isomeric alkenes C5H10 and carbonyls C4H6O, C6H12

and C5H8O respectively. Specific identities have not been determined. 

 

VOC Exhaust Emission Speciation versus Fuel Type

The normalized emissions reported in Table 1 can be examined in relation to other data 

sets, such as Spicer3 or our previous APEX results1,2, provided that ethene has been 

EI x

EIC2H 4

EI x

EIC2H 4

EI x

EIC2H 4
APPENDIX C

101

measured. Figure 3 shows a comparison of the present JP8 measurements with those 

reported by Spicer. In this figure, a value of 1 indicates that our ethene-normalized 

emissions are equal to those computed from Spicer. Inspection of this figure shows that 

the present JP8 measurements are within +/- 35% of those reported by Spicer, which we 

consider to be excellent agreement. 

Figure 3. Comparison of ethene normalized EIs measured at AAFEX with respect those 

reported by Spicer et al.3 for JP-5.

Figure 3 shows that there are some striking differences in the chemical composition of 

the exhaust produced with the different fuels: 1) The two FT fuels appear to have very 

different exhaust compositions. 2) The aromatic emissions from the FT fuels are reduced 

but not eliminated. Before we proceed further with our discussion on these fuel effects, 

we note that direct comparison of normalized emissions can be misleading if the absolute 

magnitude of the compound (ethene) to which the other compounds are scaled to changes 

significantly with the different fuels. As will be shown later, the ethene EIs are roughly 

equivalent for all of the fuels. This fortunate consequence allows us to use the results 

shown in Figure 3 to highlight the differences in the chemical speciation between the 

different fuels. 
APPENDIX C

102

An obvious difference between the alternate fuels and JP8 is the significant reduction in 

the emission of aromatic compounds with the FT fuels. This result might have been 

anticipated since the liquid FT fuels have very low aromatic contents. What might not 

have been expected is that the aromatic emissions are not eliminated in the FT1 fuel, 

which is essentially devoid of any aromatic compounds in the liquid fuel. This result 

indicates that these aromatic compounds are being formed during the combustion 

process. A broad range of literature exists regarding the formation of aromatic 

compounds in engines and flames with respect to fuel structure ( e.g. Zhang et al.5, 

Schulz et al.6 ) and discussion of that literature is beyond the scope of this report. What 

can be concluded is that the aromatic emissions don’t scale in direct proportion to the 

aromatic content of the liquid fuel. 

Figure 3 indicates that the chemical speciation profiles are very different for the two FT 

fuels. The VOC emissions from the FT1 fuel are lower than those for the FT2 fuel for all 

of the measured compounds. The FT1 emissions are also lower than those measured for 

JP8. In contrast, the reduction in the aromatic emissions in the FT2 fuel appears to be 

offset by enhanced emissions of C3 and C4 compounds. These results suggest, but do 

not prove, that the total VOC emissions are lowest for FT1 fuel and greatest for FT2 fuel.

Because only a limited subset of the measured VOCs are shown in Figure 3, we now 

examine the chemical speciation profiles from the perspective of all of the data reported 

in Table 1. The exhaust composition for each fuel displayed as a pie chart in Figures 4-6. 

In these charts, mass57 represents the sum of butenes + acrolein, mass59 represents the 

sum of acetone + propanal + glyoxal, and other aromatics represents the sum of all of the 

aromatic compounds excluding benzene and naphthalene. These charts assume that the 

VOC emissions reported in Table 1 sum to 100%, a condition that is clearly not met. For 

JP5 fuel, Spicer reports that they were able to identify approximately 70% of the nonmethane carbon in the exhaust. We estimate that the components listed in Table 1 

represent approximately 75% of carbon identified by Spicer. We note that there are 

compounds in Table 1 such as methanol and most of the larger aromatics (mass121, 

mass135 and mass149) that are not included in Spicer’s list of identified compounds. 

Conservatively, we estimate that the chemical components listed in Table 1 represent 

better than 50% of total non-methane organic carbon within the exhaust produced by JP8. 

The bulk of remaining mass is presumed to be from alkanes, which are not measured by 

either the TILDAS or PTR-MS. The relative distributions are useful and will remain valid 

provided that the emissions measured in Table 1 reflect a near constant fraction of the

actual total. 
APPENDIX C

103

Figure 4. Distribution of the measured exhaust components for JP8 fuel. 

Figure 5. Distribution of the measured exhaust components for FT1 fuel.
APPENDIX C

104

Figure 6. Distribution of the measured exhaust components for FT2 fuel.

Figures 4-6 clearly indicate that small molecular weight components (C1-C3) constitute 

the majority (>70%) of the measured mass emissions for all fuels. The distribution of 

these emissions is roughly equally divided between alkenes (fuel cracking products) and 

carbonyl compounds (partially oxidized products). Exhaust produced from FT2 fuel 

contains a greater proportion of carbonyls to alkenes (1.05), FT1 fuel (0.76) favors alkene 

production, while JP8 fuel (0.86) falls between the two alternate fuels. The significant 

presence of carbonyl compounds in the exhaust has several important consequences. One 

is that the aldehydes such as formaldehyde and acetaldhyde are important air toxics. 

Second, total hydrocarbon (HC) emissions are typically measured using a flame 

ionization detector (FID), which essentially "counts carbon atoms", but does not count 

carbons to which an oxygen is attached. Thus the FID is essentially blind to 

formaldehyde and methanol and only records about half of the carbon from acetaldehyde. 

This result has important consequences with respect to comparing total HC emissions to 

total VOC emissions. 

Absolute VOC Emissions – Influence of fuel type, engine power and ambient 

temperature

A major objective of the AAFEX campaign was to determine how the VOC emissions 

from the alternative fuels compare to those produced from conventional JP8 fuel. In this 

section we will examine in detail how the ethene emissions are influenced by fuel type, 

engine power and ambient temperature. Figure 7 shows plots of the ethene EIs versus 

ambient temperature for the three fuels under two power conditions.
APPENDIX C

105

Figure 7. Effect of ambient temperature on the ethene EI under two low-power 

conditions. Highlighted point represents the average ethene EI at 288K.

 

Temperature Dependence

Figure 7 shows that EI of ethene is strongly dependent on engine power and ambient 

temperature, but it exhibits a weaker dependence on fuel type. The effects of engine 

power and temperature are similar in magnitude such that the low temperature (270K) 

7% power points overlay with the high temperature (290K) 4% power points. To aid in 

the discussion of the power and fuel dependencies, we will address the temperature 

dependence first. Lower ambient temperatures lead to higher emissions. The 

temperature effect is strongest at 4% power where the ethene EI’s change by about a 

factor of two over the ambient temperature range of 270 – 290 K. The temperature 

dependence appears to be slightly less pronounced under the higher 7% power condition. 

The strong temperature dependence makes it difficult to directly compare measurements 

made at different temperatures. Thus we need to create a standard temperature condition 

to which we can normalize all of our data sets. We have set 288K as our standard 

temperature. Different data sets are normalized to 288K by dividing each EI by the EI 

value measured at 288K. The 288K EIs for ethene are labeled in Figure 7. Figure 8 

shows a plot of these temperature-normalized EIs versus temperature for AAFEX and 

several other measurement campaigns. This figure shows that the present measurements 

made at 270 – 290 K merge with our previous measurements made at 287 – 305 K during 

APEX. The inclusion of both formaldehyde and ethene measurements is allowed 

because the emissions scaling phenomena demonstrates that all VOCs have the same 

temperature dependence. 
APPENDIX C

106

Figure 8. Plot of temperature normalized emissions versus ambient temperature. The 

units to the three x-axes starting from bottom are F [not U], C, and K.

Engine Power Dependence

VOC emissions are known to have a strong non-linear dependence on engine power.2-4

This dependence is clearly demonstrated in Figure 1. In Figure 7 we observe that the 

AAFEX ethene EI at 4% power (1.65 g/kg) is approximately two times larger than the 

7% power (0.85 g/kg) condition. We note that this power dependence is substantially 

reduced from what was observed at APEX. At APEX the EIs of ethene and the other 

VOCs generally decreased by a factor of 3x-5x when the power was increased from 4% 

to 7%.2

 Our preliminary analysis suggests that this difference may be due to the 

differences in the actual power conditions, although we can’t rule out the effect of engine 

age. At APEX the engines had just been rebuilt and so these engines had been in-service 

for five years prior to the testing at AAFEX. 

To further address the power dependence anomaly, we examine in greater detail how 

emissions measurements made at AAFEX for JP8 fuel compare with those made at 

APEX and with ICAO engine certification data. One can’t directly compare VOC EI 

values to total HC EI’s because the VOC EI’s include the mass of oxygen while the total 

HC EI value expresses the HC emissions in terms of gram-equivalents of CH4 per kg of 
APPENDIX C

107

fuel. To alleviate this problem, we have converted the data in Table 1 and the total HC 

EI’s to carbon emission ratios (ERC) expressed as ppbC per ppm CO2 at 288K. The 

conversion from EIx to ERC is accomplished via Eq 2. Note that the ERC are not equal 

for all of the fuels because they have different values. 

 (2)

Table 2. Carbon emission ratios (ppbC/ppmCO2) computed at 7% power from 

data shown in Table 1 assuming the 288K EIm-Ethene = 0.85 g/kg 

Compound JP8

ERC

FT1

ERC

FT2

ERC

ethene 0.850 0.865 0.859

formaldehyde 0.297 0.243 0.425

methanol 0.041 0.033 0.059

propene 0.323 0.294 0.636

acetaldehyde 0.147 0.135 0.231

butene + acrolein 0.260 0.219 0.495

acetone + propanal + gyloxal 0.065 0.064 0.176

mass71 0.194 0.156 0.433

benzene 0.109 0.017 0.052

mass 85 0.090 0.077 0.222

toluene

0.051 0.004

0.020

C8H10 + C7H6O

0.083 0.005 0.021

C9H12 + C8H8O 0.090 0.004 0.015

C10H14 + C9H10O 0.054 0.005 0.011

C11H16 + C10H12O 0.028 0.003 0.007

naphthalene 0.026 0.009 0.019

methylnaphthalene 0.011 0.013 0.017

dimethylnaphthalene 0.008 0.016 0.018

styrene 0.024 0.002 0.005

phenol 0.039 0.010 0.021

sum 2.79 2.17 3.74

The data for JP8 fuel in Table 2 was computed at 7% power so that we can our 

measurements to ICAO database emissions and to the measurements reported by 

Yelvington et al. at APEX. Yelvington reports a similar list of exhaust components to 

that shown in Table 2 and compares the sum (ERC-VOC) to total HC (ERC-HC) 

measurements made using a continuous FID instrument. The ICAO database lists the 

EICO2

ERC = EI X (g x kg fuel) EICO2 gCO2 [ ( kg fuel)][MWCO2 MWX ][Carbon#][1000mmole mole]
APPENDIX C

108

total HC emission index for the CFM56-2-C5 engine at 1.83 g/kg, which represents an 

ERC of 1.59 ppbC/ppmCO2. Table 3 summarizes the relevant ERC data from the 

AAFEX, APEX and ICAO data sets and includes EIm-CO from AAFEX and ICAO. The 

data in Table 3 for ERC-VOC and ERC-HC at APEX was taken directly from Yelvington 

et al. and has not been normalized to 288K. The APEX data set represents an average 

and was collected at higher ambient temperatures (287 – 305 K).

Table 3. Carbon emission ratios and EIm-CO for CFM56-2-C5 engine at 7% power 

from different sources. 

AAFEX

ERC-VOC

APEX

ERC-VOC

APEX

ERC-HC

ICAO

ERC-HC

AAFEX

EIm-CO

ICAO

EIm-CO

2.79 1.31 1.16 1.59 58.5 30.7

Some initial discussion of the APEX data set is warranted. We note that APEX ERCVOC and ERC-HC values are quite similar and that the VOC value is actually greater 

than total HC measurement. This similarity must be considered as accidental because the 

VOC measurements don’t include any of the alkane exhaust component. The FID, 

however, only records the HC component of the exhaust and does not accurately account 

for components containing oxygen. Apparently the reduction in the FID response due to 

the presence of compounds like formaldehyde or methanol in the exhaust offsets the 

omission of the alkanes from the VOC sum. The difference between the APEX ERC-HC 

and the corresponding ICAO measurement is primarily due to a temperature effect, since 

the ICAO value is determined at a lower temperature (288K). Normalizing the APEX 

ERC-HC to the ICAO value would suggest a 288K temperature corrected APEX ERCVOC value of 1.80. 

The ERC-VOC measurement taken at AAFEX is substantially larger than that observed at 

APEX. The differences in exhaust chemical composition and temperature between the 

AAFEX and APEX data sets cannot account for this disparity. Examining the CO 

emission observed at AAFEX with the ICAO value also shows a large discrepancy. 

Scaling our AAFEX ERC-VOC number by the ratio (30.7/58.5) leads to a corrected VOC 

ERC of 1.46. This corrected value is now in line with our previous APEX measurement. 

While this discussion does not identify the source, engine power variations, or engine 

age, it certainly suggests that the difference is real and is not a measurement artifact.

Fuel Dependence

The sums in Table 2 for the different fuels provide a direct estimate of how the total VOC 

emissions vary between fuels. These estimates assume that the ethene emissions are 

similar for all three fuels and that the chemical composition of the exhaust shown in 

Table 2 accounts for a constant fraction of the actual exhaust emissions. The latter 

assumption cannot be interrogated fully in the absence of a full chemical speciation 

profile. The first assumption can be addressed by examining the data shown in Figure 7. 

The ethene EIs for the different fuels generally overlap with one another, particulary in 

the case of the JP8 and FT2 fuels. The ethene emissions from the FT1 at 7% power do 

appear to be generally higher, by maybe 20%. If we assume that the ethene EIs are the 

same for all of the fuels, then the VOC emissions from FT1 fuel are 28% lower than JP8 
APPENDIX C

109

fuel and FT2 fuel is 34% higher than JP8. Allowing the ethene EI in FT1 fuel to increase 

by 20% would increase the VOC emissions to 2.6 ppbC/ppmCO2, which is only 7% 

lower than the JP8 fuel. The FT2 288K ethene EI would need to be 0.65 g/kg to make its 

VOC emissions equivalent to that of JP8. The data in Figure 7 does not support such a 

reduction. In light of additional information we can conclude that the total VOC 

emissions rank in the order FT1 < JP8 < FT2. 

Sample Line Perturbations

Reliable sampling of engine exhaust gas matrix represents one of the most important and 

difficult challenges. APEX style emissions tests require the use of extensive sample lines 

in order to transport and deliver a common sample to all of the participants. A 

consequence of this sampling strategy is that exhaust gas is exposed to long lengths of 

stainless steel tubing. Organic compounds, particularly those with low vapor pressures, 

interact with the walls of the sample line, which affects the delivery efficiency of these 

compounds to the measurement instrumentation. These sample wall interactions lead to 

poor temporal correlation between the affected substrate and other exhaust gas 

components, such as CO2 the primary combustion tracer, that are efficiently transported 

through the sample system. An example of this is shown in Figure 9, where the 

naphthalene signal has been overlaid onto the ethene time series. In this figure the 

naphthalene response lags behind the ethene response during the transition between test 

points and then slowly approaches to a steady state concentration. 

Figure 9. Naphthalene time series illustrating temporal distortion due to its retention in 

the sample lines. 
APPENDIX C

110

For this illustrated case, the naphthalene signal nearly reaches its equilibrium value by the 

end of the test point. With respect to other compounds, we have found that the extent of 

this phenomenon is related to the components vapor pressure. Compounds having lower 

vapor pressures have more pronounced temporal distortion. A consequence of this effect 

is that the measurements exhibit a dependence on the previous sample history. 

Measurements are affected any time the sample concentration changes dramatically but 

are most apparent when the sample concentration goes from a high value to a low value. 

To help reduce the bias of these sample line interactions on the final data product, we 

have employed a new algorithm to compute the average test point concentration, which is 

described in Appendix II.

Improvements in sampling strategy are needed if we want to understand the role low 

volatility compounds have on the formation and growth of aerosol particles. In this 

section we examine how the measurement of low volatility compounds might be 

improved. An obvious first thought would be to increase the duration of the test points. 

Increasing the time will improve the precision of the measurements by ensuring that the 

gas phase concentrations achieve a true steady state value. Unfortunately, the steady 

state concentration reflects an equilibrium between gas phase and condensed or adsorbed 

naphthalene and this equilibrium condition is dependent on the surface composition of 

the sample line and temperature. Control of these variables may not be entirely possible 

in an APEX style test. Even if control of these variables could be achieved, it is unlikely 

that we would be able to ascertain how surface composition and temperature affects the 

results. The only reliable way to eliminate sample line perturbations is to eliminate the 

sample line. While this can’t be accomplished explicitly, these sample line effects can be 

reduced by moving the instruments to the exhaust plume rather moving the exhaust 

sample to the instruments. Techniques such as the EEPS "death box" and the Aerodyne 

mobile laboratory demonstrated this sample strategy during AAFEX. The improvement 

in time response for naphthalene measured while the Aerodyne mobile lab was deployed 

downrange of the aircraft is shown in Figure 10. In this mode of operation the sample 

line is a short 3-m section of 0.5" OD Teflon line. The reduction in sample line length 

leads to a time response of naphthalene of ~10 seconds as compared with ~100 seconds 

in the main sampling system. While these downrange measurements become challenging 

because of the low sample concentrations, the improvements achieved due to improved 

sampling integrity provide the best conditions to study gas-to-particle processes.
APPENDIX C 

111 

Figure 10. Downrange measurement of naphthalene showing the improvement in time 

response due to the reduction of sample line perturbations. 

References 

(1) Knighton WB, Rogers TM, Anderson BE, Herndon SC, Yelvington PE, MiakeLye RC. Journal of Propulsion and Power 2007; 23, 949. 

(2) Yelvington PE, Herndon SC, Wormhoudt JC, Jayne JT, Miake-Lye RC, Knighton 

WB, Wey C. Journal of Propulsion and Power 2007; 23, 912. 

(3) Spicer CW, Holdren MW, Riggin RM, Lyon TF. Ann. Geophys.-Atmos. 

Hydrospheres Space Sci. 1994; 12, 944. 

(4) Wey CC, Anderson BE, Wey C, Miake-Lye RC, Whitefield P, Howard R. 

Journal of Propulsion and Power 2007; 23, 898. 

(5) Zhang HR, Eddings EG, Sarofim AF. Environmental Science & Technology

2008; 42, 5615. 

(6) Schulz H, De Melo GB, Ousmanov F. Combustion and Flame 1999; 118, 179. 
APPENDIX C

112

Quantification using the PTR-MS 

The concentrations of the VOC exhaust emission components, R, are deduced from 

measured ion intensities using relationships derived either from reaction kinetics or 

calibrated response factors. The methods used to quantify the concentrations of VOCs in 

jet engine exhaust have been previously described in detail by Knighton et al.1 A brief 

overview of these methods is provided here along with a tabulation of the pertinent 

quantification information relevant to the measurements made at AAFEX. Sensitivity 

response factors are derived from calibration experiments performed using a certified 

multicomponent gas standard that were conducted periodically throughout the campaign. 

Compounds for which gas standards were not available were quantified using reaction 

rate constants taken from Zhao and Zhang.2

Compounds quantified from calibrated response factors utilize Eq. 1, which describes the 

relationship between the volumetric mixing ratio (VMR) expressed in ppbv and the 

response factors.

VMRR = 1

SR

 

  

 

  I RH+

I H 3O+ + XR •I H 3O+ ( H 2O)

 

 

  

 

 

  

T

300

 

   

  

2

2

P

 

   

  

2

 (1)

I RH+ , I H 3O+ , and I H 3O+ ( H 2O) represent the measured ion intensities in counts per second 

(cps). SR represents the calibrated response factor expressed as cps/ppbv per 1-million 

reagent ions, which is referred to as ncps. XR is a correction factor that compensates for 

differences in the detection and reaction efficiency of the H3O+

(H2O) versus the H3O+

reagent ion. The drift tube temperature (T) and drift tube pressure (P) are included in this 

expression to account for small changes in the reaction time and gas number density that 

occur when we operate outside the standard conditions of 300K and 2 mbar.

For compounds where calibration standards were not available, concentrations were 

calculated from an expression derived from standard reaction kinetics, Eq. 2.

VMRR = I RH+ BF

I H 3O+ + I H 3O+ ( ( H 2O))kct

 

 

 

 

 

 

 

 

109

Ntot

 

  

 

  (2)

In the case of Eq. 2, I RH+ , I H 3O+ , and I H 3O+ ( H 2O) represent transmission corrected ion 

intensities. BF is the product ion fraction fraction, t is reaction time, defined by the drift 

time of the reagent ions, kc is the reaction rate constant, 109 is the conversion factor to 

ppbv and Ntot is the total number density of the sample within the drift tube reaction 

region. 

Table 1 provides a compilation of the response factors, reaction rate constants and 

product ion branching fractions used quantify the reported VOC concentrations. 

Quantification notes provide more specific information on which quantification equation 
APPENDIX C

113

was employed and other relevant details. Some compounds are reported as sums, 

because they exist in a variety of structural isomers and/or there are other compounds 

present that possess the same nominal molecular weight (isobars) that cannot be resolved 

using a quadrupole mass spectrometer. The quantification notes indicate whether a 

weighted average or single compound response factor or reaction rate constant is 

assumed. The rational for these choices has been discussed previously in Knighton et al.1

Table 1 Compounds monitored within the engine exhaust and pertinent quantification information 

Compound Ions formed 

(abundance)

Quantification Note SR

(ncps)

XR reaction rate 

constant 

(ml/s)

x109

methanol 33(100%) Eq, 1 19.6 0.18 2.33

propene 41(23%) 43 (77%) Eq. 1 – see text 12.4 -0.12 1.58

acetaldehyde 45(100%) Eq. 1 33.8 0.34 3.36

butenes 57(100%) Eq. 2 – weighted 

average rate constant

summed with acrolein

- - 1.73

acrolein 57(100%) Eq. 2 – weighted 

average rate constant

summed with butenes

- - 3.35

acetone 59(100%) Eq. 1 - weighted 

average response factor

summed with propanal 

and glyoxal

36.4 0.48 3.00

propanal 59(100%) Eq. 1 - weighted 

average response factor

summed with acetone 

and glyoxal

36.4 0.48 3.44

glyoxal 59(100%) Eq. 1 - weighted 

average response factor

summed with actone 

and glyoxal

36.4 0.48 1.34

acetic acid 43(34%) 61(66%) Eq. 2 m/z 61 BF = 0.66 - - 2.27

benzene 79(100%) Eq. 1 25.2 -0.21 1.97

toluene 93(100%) Eq. 1 33.3 0.05 2.12

phenol 95(100%) Eq. 2 - - 2.52

styrene 105(100%) Eq. 1 36.9 0.35 2.33

o,m,p-xylene 107(100%) Eq. 1

p-xylene calibration

summed with 

ethylbenzene and 

benzaldeyhde

36.9 0.33 2.26-2.32

ethylbenzene 79(12%)107(88%) Eq. 1

p-xylene calibration

summed with xylenes 

and benzaldehyde

36.9 0.33 2.25

benzaldehyde 107(100%) Eq. 1

p-xylene calibration

summed to xylenes and 

ethylbenzene

36.9 0.33 4.12

C9H12 isomers + 

C8H8O isomers

121 (100% assumed) Eq. 1

1,2,4 trimethylbenzene 

calibration

37.8 0.37 2.4 – 3.9
APPENDIX C

114

naphthalene 129(100%) Eq. 2 - - 2.59

C10H14 isomers + 

C9H10O isomers

135 (100% assumed) Eq. 2

C10H14 reaction rate 

constant

- - 2.5

methylnaphthalenes 143(100%) Eq. 2 - - 2.7

C11H16 isomers + 

C10H12O isomers

149(100% assumed) Eq. 2

C11H16 reaction rate 

constant

- - 2.6

dimethylnaphthalenes 157(100%) Eq. 2 - - 2.9

Aircraft engine exhaust also contains a number of other known compounds, which are 

detectable using PTR-MS, but can’t be specifically quantified due to the presence of 

other compounds within the exhaust matrix whose identities have not yet been confirmed. 

In effort to retain as much information as possible about the total mass balance, it is 

desirable to be able to estimate the amount of material present in the exhaust beyond 

what is accounted for in Table 1. For ion masses where their respective neutral 

precursors can’t be identified, these ions are quantified using Eq. 2 assuming a reaction 

rate constant of 2x10-9 ml molecule-1

sec-1. Contributions from these ion masses are 

designated by their respective mass number. Two ion masses, m/z 71 and m/z 85, 

contain a significant amount a spectral intensity and are quantified assuming that their 

molecular weights are 70g/mole and 84 g/mole respectively. 

Interpreting the PTR-MS mass spectrum relies heavily on knowing what compounds are 

present in the exhaust matrix and their ion chemistry, because ion mass is not a unique 

indicator of compound identity. In our initial paper, we utilized the exhaust composition 

reported by Spicer et al.3 to predict which compounds could be quantified. The accuracy 

of compound identities reported in Table 1 depends on how well we know both the 

chemical composition and the ion chemistry associated with each compound. For 

example, does the ion intensity measured at m/z 57 reflect only the presence of the 

butenes (C4H8) and acrolein (C3H4O)? To address this question and others, we have 

interfaced a gas chromatograph to the PTR-MS. Chromatograms are recorded for a 

specified ion (single ion chromatograms). These single ion chromatograms help us 

determine how many different compounds contribute to the spectral response. All 

compounds present in the engine exhaust matrix are not amenable to GC analysis, i.e. 

acetic acid, and any interpretation of the ion signals must remain cognizant of this fact. 

Below we discuss our GC/PTR-MS results for most of the ion mass assignments listed in 

Table 1. The information provided in this discussion is restricted to exhaust 

measurements made from engines burning conventional fuels. Most of measurements 

discussed were taken from a F-100 engine although a limited number were taken from 

CFM56-2 engine at AAFEX. An implicit assumption is that the exhaust composition in 

not affected by differences in engine technology. The body of our work1,4-6 suggests 

strongly that this is the case. 

Summary of GC/PTR-MS analyses

Mass 43

Propene is quantified from the signal measured at m/z 43. Acetic acid and larger alkenes 

produce fragment ions that are detected at this mass. In our previous work we estimated 
APPENDIX C

115

that 68% of the ion signal measured at m/z 43 was attributable to propene.1

 We have an 

improved understanding on how to quantify propene. We now directly correct for the 

acetic acid contribution. Under our experimental conditions acetic acid expresses 52% of 

its m/z 61 signal at m/z 43 allowing us to directly adjust the total m/z 43 signal by this 

amount. GC/PTR-MS analysis of the m/z 43 signal reveals that 85% of peak area in the 

chromatogram is due to propene. Two other peaks are observed in the m/z 43 

chromatogram account for the remaining 15% of the peak area. Acetic acid does not 

elute off of the column and thus is not observed in the chromatogram. Propene is 

quantified from the adjusted m/z 43 response: I propene

m/ z43 = Itotalm/ z43 − 0.52* I

m/ z61 ( )•0.85.

Mass 45

Acetaldehyde produces the only peak observed in the m/z 45 single ion chromatogram. 

Mass 57

Single ion chromatograms obtained for m/z 57 indicate that 1-butene and acrolein are the 

predominate engine exhaust products (>90%) detected at this mass. The chromatogram 

suggests that only 1-butene is present, but the chromatographic resolution is poor enough 

that the isomeric 2-butenes could be unresolved and contained within the 1-butene peak. 

Quantification of these peak area responses confirms that the butenes and acrolein are 

present in roughly equimolar proportions. This result is consistent with results reported 

by Spicer et al.3

Mass 59

The single ion chromatogram obtained for m/z 59 produces a single broad peak. Given 

that all three compounds detected at this ion mass have similar boiling points; glyoxal 

323K, propanal 322K and acetone 329K, it seems likely that our chromatographic 

column does not provide sufficient resolution to resolve these components. This is 

essentially a null result and we treat ion signal at m/z 59 as if all three compounds are 

present in the proportions reported by Spicer et al.3

Mass 71

The single ion chromatogram for m/z 71 generally produces 4-5 distinct peaks. Based on 

comparison of retention times obtained with known standards, one of these peaks has 

been indentified as methacrolein. There is one peak that elutes prior to methacrolein, 

which suggests the presence of one of pentene isomers. The remaining peaks all elute 

after methacrolein. Crotonaldehyde, a known exhaust emission component3

, has a higher 

boiling point than methacrolein and is most likely responsible for one of the other peaks.

Mass 79

Benzene is the only peak significant peak observed in the m/z 79 single ion 

chromatogram. The single substituted alkyl benzenes, ethyl, propyl, and butyl etc. all 

produce m/z 79 as fragment ion7

, but their contributions to the overall m/z 79 are very 

small <5%. 
APPENDIX C

116

Mass 85

The single ion chromatogram for m/z 85 produces a number of distinct peaks ranging 

from 5 – 6 with a number of smaller features. None of these peaks have been definitively 

identified, but by analogy with the interpretation of mass 71 suggests a mixture of 

alkenes and aldehydes. 

Mass 93

The single ion chromatogram for m/z 93 reveals that toluene is the dominant component 

detected at this mass. The toluene peak accounts for at least 80 – 90% of the total peak 

area. The other peaks in this chromatogram have much longer retention times, which 

suggests that they are fragment ions produced from larger alkylated toluenes. These GC 

results provide a reasonable explanation for why our previous measurements of toluene 

have typically been larger than that reported by Spicer et al.3 No correction has been 

applied to our toluene data to date. 

Mass 105

The single ion chromatogram for m/z 105 indicates that only styrene is detected at this 

mass. 

Mass 107 

The single ion chromatogram for m/z 107 shows 4 peaks. Three of these peaks reflect 

the presence of the 4 C8H10 isomers; ethylbenzene and the three xylene isomers. Note 

that the meta- and para-xylene isomers can’t be resolved and are detected as single 

chromatographic peak. The 4th peak in the chromatogram has a significant longer 

retention time, and we ascribe the presence of this peak to benzaldehyde. 

Mass 121 and Mass 135

The single ion chromatograms for these ion masses show a mixture of semi-distinct peaks 

and unresolved humps, which reflects the presence of a significant number of 

compounds. Mass 121 is attributed to both the C9H12 and C8H8O compounds, which can 

exist as up to 8 alkyl-substituted aromatics and 5 substituted aromatic carbonyls. While 

Mass 135, which we attribute to both C10H14 and C9H10O compounds can exist as more 

than 30 different aromatic compounds. One does not expect to see all of the possible 

isomeric forms expressed nor is there great value in identifying all of the specific 

isomers. There would be value of separating the aromatic hydrocarbons from their 

oxygenated isobars. Our chromatographic system cannot do this as it lacks the capability 

to efficiently transfer these large relatively low volatility compounds onto the 

chromatographic column. We note for these compounds that we have significant 

retention and loss of material in the sample valve. This leads to peak broadening, loss of 

chromatographic resolution and ultimately the total loss of signal. Lower volatility 

compounds, such as naphthalene, cannot be successfully analyzed by GC using our 

existing interface. 
APPENDIX C

117

NO+ MS

The PTR-MS can be adapted to employ NO+ as the reagent ion by switching the reagent 

ion source gas from water to dry air. The full details on this mode of operation are 

provided in Knighton et al.8 The instrument was configured to operate in the NO+ mode 

during the first two days of the AAFEX campaign. NO+ reacts via a charge transfer 

reaction, Eq. 3, with compound having ionization energies lower than 9.26 eV:

NO+ + R  k → R+ + NO (3)

This technique provides greater measurement specificity as only the diene and aromatic 

hydrocarbon exhaust components fit this criterion. This technique was designed 

specifically for the measurement of 1,3-butadiene, an important air toxic. 

Calibration and quantification of the ion signals of the NO+ MS are similar to that 

described above for the PTR-MS. Compound response factors are provided in Table 2. 

Volumetric mixing ratios (VMR) expressed as ppbv are computed using Eq. 4: 

VMRR = I R+

I NO+

 

 

  

 

 

  

106

SR

 

  

 

  T

300

 

   

  

2

2.1

P

 

   

  

2

 (4)

Where I R+ and I NO+ represent the measured ion intensities and SR is the sensitivity factor 

expressed in ncps. The drift tube temperature (T) and drift tube pressure (P) are included 

to account for changes in the reaction time and gas number density that occur when we 

operate outside of these standard conditions. 

Table 2. Compounds monitored within the engine exhaust using the NO+ MS. Ion products and 

compound response factors measured at E/N = 104 Td. 

Compound Ions formed (abundance) SR (ncps)

1,3-butadiene 54 (~100%) 12.3

benzene 78 (100%) 12.7

toluene 92 (100%) 19.6

styrene 104 (100%) 22.1

C2-benzenes (sum of o,m,pxylene and ethylbenzene106 (100%) 23.5

naphthalene 128 (100%) 22.5a

a calibration factor calculated assuming a reaction rate constant of 2x10-9 ml molecule-1 sec-1

GC/PTR-MS has been used to examine the single ion chromatograms at m/z 54, m/z 78, 

m/z 92, m/z 104 and m/z 106. The C2-benzenes (m/z 106) show 3 peaks corresponding 

to o-xylene, m,p-xylene and ethylbenzene while other masses only show one peak. These 

results confirm the mass assignments made in Table 2. The purity of the m/z 128 ion 

signal has not been established for naphthalene. While there is no doubt that naphthalene 

reacts with NO+ to form an ion at m/z 128, there are potential interferences to this

measurement. NO+ can react with alkenes via an insertion mechanism to produce ions of 

the type C2H2n-1HNO.9 1-heptene is a known jet engine exhaust component and could 
APPENDIX C

118

possibly interfere with the measurement of naphthalene. We intend to investigate this 

potential interference. 

(1) Knighton WB, Rogers TM, Anderson BE, Herndon SC, Yelvington PE, MiakeLye RC. Journal of Propulsion and Power 2007; 23, 949.

(2) Zhao J, Zhang RY. Atmospheric Environment 2004; 38, 2177.

(3) Spicer CW, Holdren MW, Riggin RM, Lyon TF. Ann. Geophys.-Atmos. 

Hydrospheres Space Sci. 1994; 12, 944.

(4) Herndon SC, Rogers T, Dunlea EJ, Jayne JT, Miake-Lye R, Knighton B. 

Environmental Science & Technology 2006; 40, 4406.

(5) Herndon SC, Wood EC, Northway MJ, Miake-Lye R, Thornhill L, Beyersdorf A, 

Anderson BE, Dowlin R, Dodds W, Knighton WB. Environmental Science & 

Technology 2009; 43, 1730.

(6) Yelvington PE, Herndon SC, Wormhoudt JC, Jayne JT, Miake-Lye RC, Knighton 

WB, Wey C. Journal of Propulsion and Power 2007; 23, 912.

(7) Warneke C, De Gouw JA, Kuster WC, Goldan PD, Fall R. Environmental Science 

& Technology 2003; 37, 2494.

(8) Knighton WB, Fortner EC, Herndon SC, Wood EC, Miake-Lye RC. Rapid 

Communications in Mass Spectrometry 2009; 23, 3301.

(9) Diskin AM, Wang TS, Smith D, Spanel P. Int. J. Mass Spectrom. 2002; 218, 87.
APPENDIX D

119

APPENDIX D: Measurements of nitrous acid in commercial aircraft exhaust

Ben H. Lee1, Greg W. Santoni1, Ezra C. Wood2, Scott C. Herndon2, Richard C. MiakeLye2

, J. William Munger1, Steven C. Wofsy1, J. Barry McManus2, David D. Nelson2, 

Mark S. Zahniser2

1 Harvard University, Cambridge, Ma

2 Aerodyne Research, Inc., Billerica, Ma

Abstract

The Alternative Aviation Fuels Experiment (AAFEX), conducted in January of 2009 in 

Palmdale, California evaluated aerosol and gaseous emissions from a DC-8 aircraft 

equipped with CFM56-2C1 engines alternating between traditional and synthetic fuels. 

This study examines the emissions of nitrous acid (HONO) and the sum of nitrogen 

oxides (NOx) measured approximately 140 m downwind of the grounded aircraft. The 

emission index (EI) for HONO increases approximately six-fold from idle to take-off 

conditions but plateaus between 60% and 100% engine power setting, as opposed to that 

of NOx, which increases continuously. HONO EI did not exhibit a dependence on fuel 

type (traditional, synthetic, synthetic blend), ambient temperature, relative humidity, or 

presence of sunlight, while NOx EI showed a positive dependence on ambient 

temperature at maximum rated engine thrust. Additionally, hydrogen peroxide (H2O2) 

was identified in exhaust plumes emitted during idle conditions. Chemical reactions 

responsible for emissions and comparisons to previous studies are discussed. 

Introduction

Exhaust emissions from aircraft are pertinent to global climate change and air quality [1]. 

This is a particularly pressing concern given the projected increase in air travel over the 

coming decades [2]. While the International Civil Aviation Organization (ICAO) 

monitors the emissions of many trace gases including nitrogen oxides (NOx) from every 

class of commercial aircraft, nitrous acid (HONO) specifically is not one of these gases. 

Moreover, while the impact of aircraft NOx (= NO + NO2) emissions on regional ozone 

levels and NOx burden has been studied [3-5], the effects of aircraft HONO emissions on 

atmospheric chemistry particularly on the HOx (= OH + HO2) budget are not well known.

HONO emitted from aircraft is a reservoir for HOx and NOx as it photo-dissociates to 

nitric oxide (NO) and the hydroxyl radical (OH), the main atmospheric oxidant. In the 

upper atmosphere, where the OH number density is low, HONO emitted from aircraft 

may influence the local oxidative capacity along flight corridors. In the lower 

troposphere, nighttime buildup and subsequent photolysis of HONO is the dominant OH 

source in the early morning. Recent daytime ground-level measurements in urban, rural 

and even remote environments have shown levels far exceeding those expected under 

photo-stationary state, indicating a yet-unidentified HONO source, which may 

significantly contribute to daytime HOx budgets. In order to determine OH contribution 

from HONO photolysis, the strengths of all HONO sources including homogeneous, 

heterogeneous, photo-induced reactions and direct emissions need to be accurately 

quantified and their controlling factors characterized.
APPENDIX D

120

The Fischer-Tropsch process – though highly energy- and cost-intensive – can reduce the 

need for foreign oil because the main ingredients are readily available feedstock, such as 

coal, natural gas and bio-oils. In addition, FT-derived fuels do not contain aromatichydrocarbon and sulfur, resulting in emissions that are lower in soot and sulfate aerosols. 

However, few studies have looked at emissions from the combustion of these fuels by 

typical commercial aircraft engines. We present here the emission indices of HONO, NOx

and H2O2 determined through reference to emitted carbon dioxide (CO2). 

Methods

During AAFEX, a DC-8 aircraft was chocked on the runway at NASA’s Dryden Flight 

Research Center in Palmdale, California. Two engines – one on either side of the aircraft 

– were fired for each experiment, lasting a few hours during which the engine power was 

varied to simulate idle to take-off conditions. The left inboard engine was supplied with 

traditional JP8 fuel, while the right inboard engine alternated between traditional, two 

different synthetic Fischer-Tropsch fuels and blends of both. Experiments were 

conducted from before sunrise to late afternoon over a span of a week to utilize the wide 

range in ambient conditions to test their impact on emission characteristics. Composition 

and mixing ratios of particles and various trace gases were measured at 1 m and 30 m 

behind both engines [Anderson et al., 2010, in preparation], and also 140 m downwind, 

which is the focus of the present study.

Mixing ratios of HONO, H2O2, nitrous oxide (N2O) and methane (CH4) were measured 

simultaneously by a tunable infrared laser differential absorption spectrometer (TILDAS) 

utilizing a single continuous-wave mode quantum cascade laser operating near the 1275 

cm-1 spectral region [6, 7]. Figure 1 shows typical one-second spectra observed while 

sampling plumes emitted during 7% (a, b) and 85% (c, d) rated engine thrusts. For 

AAFEX, the scanning window was less than 0.2 cm-1 and repeatedly tuned at just over 3 

kHz. The laser linewidth was less than 0.002 cm-1, hence not the limiting factor in 

determining the lineshape. Sampled air flowed through an astigmatic multi-pass 

absorption cell in which infrared laser beam traversed a total path of 210 m [8]. An 

absorbance precision of less than 6×10-6 Hz-1/2 in one second was achieved in the field, 

which translated to detection limits (S/N = 3) of 450 ppt (pmol/mol), 1200 ppt and 900 

ppt for HONO, H2O2 and N2O, respectively, in one second. Complete details regarding 

the instrument and HONO linestrength quantification are provided by Lee et al.

[manuscript in preparation]. Results for N2O, along with 12CH4 and 13CH4 isotopologues 

measured by a second TILDAS instrument connected in series with this system are 

presented by Santoni et al. [manuscript in preparation].

Special attention was paid to the sampling procedure to minimize attenuation and artifact 

formation on inlet and tubing surfaces for reactive species such as HONO and H2O2. A 

siloxyl-coated quartz inlet – used previously by Herndon et al. [9] to measure formic acid 

and formaldehyde – with a built-in critical orifice with a 0.04’’ (1 mm) diameter 

immediately reduced the sample pressure by at least a factor of two. The sample 

subsequently traveled through approximately 40 feet (12.2 m) of 3/8’’ OD PFA Teflon 

tubing to a siloxyl-coated 5.0 L glass multi-pass sampling cell in which the pressure was 
APPENDIX D

121

maintained at around 30 torr. The sample residence times in the inlet, tubing and cell 

were calculated to be on average 0.3, 0.2 and 1.2 seconds, respectively, given a 

volumetric flow-rate of ~10 liters per minute. It was determined from introducing HONO 

along with CH4 (an inert gas) at the end of the eight-day campaign that there was 

undetectable loss or interaction of HONO with the inlet/tubing/cell surfaces. Figure 2 

shows the time responses (e-folding time determined by an exponential fit of the rise and 

fall of HONO and CH4 mixing ratios during injection tests) of the two gases were 

virtually identical, indicating that HONO response time was determined only by physical 

mixing and was not affected by chemistry. Gaseous HONO was generated using 

hydrochloric acid vapor passed over sodium nitrite powder as described by Febo et al.

[10]. 

A similar test for H2O2 could not be conducted because a steady source was not available. 

However, it is not inconceivable that there was some loss of H2O2 given that the Henry’s 

law constant for HONO is 50 atm M-1 compared to 82,000 atm M-1 for H2O2 [11, 12]. In 

addition, the near overlap between HONO and H2O2 absorption lines at around 1275.82 

cm-1 (figure 1a, 1c) resulted in artificial enhancement of the retrieved H2O2 mixing ratios 

in the presence of high HONO absorbance. This was not observed when H2O2 was 

scanned near the 1275.98 cm-1 region (figure 1b, 1d), where its absorption lines were free 

of overlap. These effects, as a result, limit the accuracy of H2O2 measurements during 

AAFEX. We observed no evidence of H2O2 significantly affecting HONO mixing ratios. 

Routine calibrations were not performed in the field, but instead measurements relied on 

the accuracy of linestrengths. Peak positions for mid-infrared HONO absorption were 

obtained from high-spectral resolution Fourier Transform Infrared Spectroscopy 

[Herman, personal communication]. The effective linestrengths – referring to the total 

(cis + trans) HONO absorption given by the absorption by one isomer – were obtained by 

calibrating measurements of cis (1660 cm-1) and trans-HONO (1275 cm-1) individually 

by TILDAS against measurements of NO by ozone chemiluminescence following the 

complete reduction of HONO to NO by heated molybdenum catalyst [Lee et al., in prep]. 

Preliminary results show that previous measurements used linestrengths that were high 

by a factor of about 2.5 (discussed below). The linestrengths for N2O, CH4, H2O2 and 

water vapor were obtained from the High Resolution Transmission (HITRAN) molecular 

absorption database [13]. 

NOx mixing ratio – defined here as the sum of NO and NO2 – was measured using 

molybdenum catalysis ozone chemiluminescence (ThermoElectron 42i). We assume 

negligible amounts of other reducible nitrogen oxide species such as HONO and nitric 

acid to which this technique is sensitive, partly based on observations and assuming 

sampling loss due to use of particle filters and long sampling tubing at ambient pressures. 

The mixing ratio of CO2 was measured using a non-dispersive infrared absorption 

spectrometer (Li-Cor 6262). The flowrate through both instruments was approximately 

0.5 liters per minute, resulting in a time response (1/e) less than one second for both 

instruments. 
APPENDIX D

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We report emission indices (g of species per kg of fuel consumed) calculated as the slope 

of the linear fit relative to CO2 corrected for the average mass of CO2 emitted per mass of 

the fuel consumed. This method is more robust in downwind plumes with highly variable 

mixing ratios than the background-subtracted ratio of the average mixing ratio to CO2 

[14]. Note that the EI for HONO and H2O2 are scaled by their respective molecular 

masses, while EI for NOx is reported using the molecular mass of NO2.

ERx is the emission ratio of species X defined as the correlation slope with respect to CO2

and 3,160 g CO2 per kg fuel is the CO2 emission index of JP8 fuel [reference]. 

Figure 3 (a, b) shows 1 hertz time-series of HONO, NOx, H2O2 and CO2 mixing ratios 

measured in the 140 m downwind trailer. Note that all gases co-vary together in time. 

This is also reflected in the correlation of that same plume of HONO, NOx and H2O2

versus CO2 mixing ratios (figure 3c).

Results and Discussion

HONO, NOx and HONO/NOx

Figure 4 (a, b) shows the emission indices for NOx and HONO plotted as a function of 

rated engine thrust for each of the 12 experiments conducted during AAFEX. Whereas 

the EI for NOx increases continuously from idle to 100% rated engine thrust, the EI for 

HONO levels off between 60% and 100% reflecting the point at which HONO 

production (reaction between NO and OH) and loss (reaction with OH and HONO selfreaction) become balanced. 

Emission indices of HONO observed at the 140 m trailer show no sufficient evidence of 

fuel type dependence regardless of engine setting (figure 5). The EI for NOx likewise did 

not exhibit a dependence on the type of fuel consumed (figure 5), which is in contrast to 

observations made at the 30 m location where EI values for FT fuels were lower than 

those for JP8 fuels by as much as 10% [Timko et al., manuscript in preparation]. This was 

likely due to a combination of limited instrument precision and the difference in the EI 

due to fuel type being less than experimental reproducibility. Note that the variability in 

the emission indices of individual plumes observed for a particular experiment exceeds 

10% (figure 5). It is also possible, though unlikely, that exhaust from only the left engine 

fueled with JP8 was sampled at the downwind site for the entire duration of AAFEX.

EI for NOx exhibits a positive dependence on ambient temperature (negative on relative 

humidity) only at the highest rated engine thrusts (figure 6), consistent with the ICAO 

database [reference]. The emission indices for HONO do not show the same dependence 

(figure 6), but may be masked by instrument precision. It is also possible that the 

dominant HONO production and loss processes (reactions with OH) are insensitive to 

ambient temperatures, which may be the case if the OH radical was the limiting reactant 

and its production had no temperature dependence. Moreover, HONO EI is not affected 

by the presence of sunlight, which is indicative of insignificant photochemical loss or 
APPENDIX D

123

production during transport from engine to the downwind sampling location. Likewise, 

wind speed or wind direction had no effect on HONO EI, all suggesting that production 

took place predominantly within the engine as also observed by Tremmel et al. [15], 

which found much of the HONO formation occurs prior to engine exit. However, we note 

that the ambient variables could not be adjusted in a controlled manner, hence, it is 

possible, though unlikely, that some effects could counteract one another.

Figure 4d shows HONO to NOx ratios ranging from 3% to 7% depending on engine 

setting during AAFEX. Tunnel studies of on-road vehicles show HONO to NOx ratios 

typically range between 0.29% (California, USA) and 0.80% (Wuppertal, German), with 

diesel-powered engines emitting a higher ratio than their gasoline-powered counterparts 

[16, 17]. Similarly at AAFEX, the HONO to NOx ratio of a plume emitted from a dieselpowered generator was 0.82% (figure 7). Previous field studies have inferred in situ 

photochemical production of HONO in the atmosphere from observing urban HONO to 

NOx ratios in excess of 0.8%, assuming the NOx signatures are predominantly vehicle 

emission derived. These results from AAFEX, along with observations of HONO to NOx

emission ratios from biomass burning ranging from 3% to 20% [reference], suggest direct 

combustion sources need to be better constrained in order to apportion HONO source 

strengths in the atmosphere. 

HONO in aircraft exhaust has been previously measured [18-24]. In two dedicated engine 

tests measuring HONO and NOx from similar engine types, the observed HONO to NOx

ratios were within range of those observed during AAFEX [23, 24]. However, in those 

studies the ratios consistently decreased from as high as 7% at engine idle to 0.5% at 

maximum thrust, whereas at AAFEX the HONO to NOx ratios increase from 3% at idle 

to as high as 7% around cruise setting where it begins to decrease with increasing engine 

thrust (figure 4). Moreover, emission indices of HONO from those two previous studies 

agree well (after correcting for linestrengths) at low idle thrust to those observed here but 

are lower by a factor of about three at higher engine settings (figure 8). The discrepancies 

may simply be explained by difference in engine type and age, both of which can 

influence aircraft NOx emissions [25]. However, the good agreement under certain 

circumstances (figure 6) suggests that previous campaigns suffered from sampling loss at 

high engine thrust because of thermal dissociation, adsorption on metal probe/tubing 

surface, HONO self-reaction at high mixing ratios, or poor temperature control leading to 

a cis to trans conversion. Another possible reason for the differing observations may be 

incomplete HONO formation. If a significant amount of aircraft HONO is produced post 

engine exit from the reaction between NO and OH, it may explain the lower HONO to 

NOx ratio and HONO EI at high engine thrust in the previous campaigns when 

measurements were made close to the engine. This, however, is inconsistent with our 

findings here and in previous reports [15]. 

H2O2

Hydrogen peroxide was identified in aircraft exhaust emitted during low idle thrust 

(figure 1). As observed for NOx and HONO, there is no evidence of EI dependence on 

ambient temperature, presence of sunlight, or fuel type. The AAFEX averaged emission 

index at idle thrust is 0.43 +/- 0.31 (2σ) g H2O2 per kg fuel and decreases to below 
APPENDIX D

124

detection limit at rated engine thrusts greater than 20% (figure 4c). The first ten 

experiments during AAFEX, however, exhibit a finite EI at higher engine thrusts because 

of spectroscopic interference from HONO absorbance, as mentioned above. Plans for 

future deployments call for measuring H2O2 in a more optimal spectral location or 

operating at lower sampling pressures to minimize spectral overlap at the expense of 

instrument precision. Though this was the first spectroscopic measurement of H2O2 in 

aircraft exhaust, the reported values for H2O2 from AAFEX should be qualified because 

of the yet uncharacterized potential for attenuation during sampling.

However, we can still comment qualitatively on our observations. Gaseous H2O2 can be 

formed by the self-reactions of HO2 and OH. That the emission index trend with respect 

to rated engine thrust observed during AAFEX follows that of CO (produces HO2 from 

reaction with OH and O2) and is opposite to that of HONO (formed by the reaction 

between NO and OH), strongly suggests HO2 and not OH is the H2O2 precursor in aircraft 

exhaust, as proposed by Wood et al. and Arnold et al. [23, 26]. Tremmel et al. considered 

the sum of the enhancements of OH, HONO and nitric acid (HNO3) measured downwind 

in an aircraft exhaust plume as the lower limit of the total HOx generated in an engine, 

neglecting all other OH loss pathways [15]. Our findings at AAFEX suggest the reaction 

between OH and CO and subsequent HO2 self-reaction to generate H2O2 represents an 

additional HOx loss at low engine thrust. H2O2 is, however, a HOx reservoir species like 

HONO thus will photo-dissociate once emitted to release two OH molecules. 

Summary

We report here the emission indices for gaseous HONO, NOx and H2O2 from the AAFEX 

campaign, a dedicated engine experiment measuring emissions from a DC-8 aircraft 

utilizing two CFM56-2C1 engines fueled by traditional and synthetic fuels. The emission 

indices for HONO and NOx increase with rated engine thrusts, while that of H2O2

decrease to below detection limit at engine settings greater than 20%. We did not observe 

at the downwind sampling location strong evidence to support an EI dependence on fuel 

type (tradition, synthetic or blends of the two) for any of the gases, but this may not have 

been discernible with current instrument precision and experiment setup given the mixing 

of plumes of different origins. Changes in ambient temperatures (270 to 293 K) or 

presence of sunlight, likewise, did not have an influence on emission indices of HONO 

and H2O2. HONO EI observed at AAFEX are higher by at least a factor of 2.5 than those 

previously reported because of incorrect linestrengths. Moreover, HONO EIs at the 

higher engine settings in those studies were underestimated by another factor of three, 

likely because of sampling losses. We also report for the first time spectroscopic 

measurements of H2O2 in aircraft exhaust, however, the values reported here represent 

lower limits because of possible sampling losses. 

These observations from AAFEX were made from one particular aircraft equipped with 

one engine type. Although HONO EI and HONO to NOx ratios measured at cruise 

altitude from completely different airframes and engine types fall in the range observed 

during AAFEX [15, 27], emissions are likely to vary depending on numerous factors 

such as engine type, age, aircraft payload and certainly engine thrust. Consequently, 

scaling up using EI observed from one experiment is an unrealistic representation of real-
APPENDIX D

125

world scenarios, which calls for additional measurements under widely varying 

conditions at ground as well as at altitude to better model the impact of these emissions 

on the oxidative capacity of the atmosphere.

Acknowledgements

This research was funded by the Partnership for AiR Transportation Noise and Emissions 

Reduction (PARTNER) Center of Excellence (jointly sponsored by the FAA, NASA and 

Transport Canada) via Missouri University of Science and Technology, the National 

Science Foundation (Atmospheric Chemistry, proposal number 0813617) and by the 

Transportation Research Board Graduate Research Award. The authors greatly 

acknowledge W. Berk Knighton of Montana State University and Michael T. Timko and 

Zhenhong Yu of Aerodyne Research Inc.

Figure 1. One-second spectra observed in aircraft exhaust emitted during 7% (a, b) and 

85% (c, d) rated engine thrust. The above snapshots at idle and take-off conditions 

represent CH4, N2O, HONO and H2O2 values of 2000, 335, 10, 35 ppb and 1875, 325, 75, 

5 ppb, respectively. For most of AAFEX, the spectral window shown in a) and c) was 

scanned, save for one day when the window in b) and d) was scanned. The filled-in color 

areas are simulations of the retrieved mixing ratios. 
APPENDIX D

126

Figure 2. Mixing ratios of CH4 and HONO observed during a typical injection of 

calibration gas. Time response (1/e) – determined by an exponential fit of the increase 

and decrease of the mixing ratios versus time – are averages of six injection tests.

Figure 3. Mixing ratios of CO2, NOx, HONO and H2O2 measured 140 m downwind of 

the aircraft in plumes emitted during 85% (a) and 7% (b) rated engine thrust. Correlation 

plots (c) of NOx, HONO and H2O2 versus CO2 for the same time periods from (a) and (b).
APPENDIX D

127

Figure 4. Emission indices (EI = g per kg of fuel) for NOx (a), HONO (b) and H2O2 (c) 

are plotted against rated engine thrust, along with HONO to NOx ratio (d). Each colored 

plot, totaling 12 in all, represents a single experiment conducted with JP8, FischerTropsch (FT) or blends of fuels under warm or cold conditions. Each marker represents 

the experiment average at that particular engine setting.
APPENDIX D 

128 

Figure 5. Emission indices of individual plumes for NOx (a) and HONO (b) parsed by 

rated engine thrust (color: blue = 4%, green = 30%, orange = 65%, red = 85%) and fuel 

type (symbols), plotted against ambient temperature. 

Figure 6. Emission indices of individual plumes for all of AAFEX sampled at 100% 

rated engine thrust for NOx (a), HONO (b) and HONO to NOx ratio (c). 
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129

Figure 7. A time-series of HONO and NOx measured a) from a diesel-powered generator 

during AAFEX. Scatter plot b) between HONO and NOx shows an emission ratio of 

0.82%.

Figure 8. Observed emission indices of HONO observed at the Aircraft Particle 

Experiment 3 (black), corrected for linestrength (grey), overlaid on top of observations 

from AAFEX (red). Emission indices for NO2 (blue) and NO (green) from APEX3 are 

added on top of that of HONO.
APPENDIX D

130

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APPENDIX E: Aircraft Emissions of Methane and Nitrous Oxide during 

theAlternative Aviation Fuel Experiment

Gregory W. Santoni1, Ben H. Lee1, Ezra C. Wood2, Scott C. Herndon2, Richard C. 

Miake-Lye2, Steven C. Wofsy1, J. Barry McManus2, David D. Nelson2, Mark S. 

Zahniser2

1 Harvard University, School of Engineering and Applied Sciences and Department of 

Earth and Planetary Sciences, Cambridge, Ma

2 Aerodyne Research, Inc., Center for Aero-Thermodynamics and the Center for 

Atmospheric and Environmental Chemistry, Billerica, Ma

Abstract

The radiative forcing of non-CO2 greenhouse gases, primarily methane (CH4) and nitrous 

oxide (N2O) but also including trace quantities of other halocarbons, together represent 

roughly 60% of the total forcing due to carbon dioxide (CO2) alone. Given the concerns 

over anthropogenic impacts on climate change and the predicted growth of the aviation 

industry, quantifying methane and nitrous oxide emission factors from aircraft is 

important for assessing future impacts of aviation on the Earth’s radiative balance. The 

contribution of methane to total organic compound emissions is also of interest, as mass 

conservation during combustion requires carbon balance. Given recent developments of 

new alternative aviation fuels, comparing emission factors and speciation of total organic 

compounds in aircraft exhaust is necessary to benchmark these new fuels and their 

potentially distinct emissions characteristics against traditional kerosene-based fuel. Fuelbased emission indices for CH4 and N2O were quantified from the CFM56-2C1 engines 

aboard the NASA DC-8 aircraft during the Alternative Aviation Fuel EXperiment 

(AAFEX), conducted in early 2009. The measurements of JP-8 fuel combustion indicate 

that at low thrust engine states (idle and taxi, or 4% and 7% maximum thrusts) the 

engines emit both CH4 and N2O at a rate of 168 ± 155 mg CH4 (kgFuel)−1 and 114 ± 47

mg N2O (kgFuel) −1, respectively. At thrust levels higher than idle and taxi, the modes 

corresponding to greater fuel flow rates and higher engine combustion temperatures, 

methane concentrations in engine exhaust were lower than ambient concentrations. 

Average emission indices for JP-8 fuel combusted with engine thrusts greater than 30% 

of maximum were -53.8 ± 33.2 mg CH4 (kgFuel) −1 and 32.2 ± 17.5 mg N2O (kgFuel ) −1

, 

where the negative sign for methane indicates consumption of atmospheric methane in 

the engine. Emission indices for the alternative aviation fuels, including two synthetic 

Fischer-Tropsch fuels with varying sulfur content, were statistically indistinguishable 

from those for JP-8.

Introduction

Methane is a radiatively active gas in Earth’s emission spectrum, roughly 25 times more 

effective on a per-molecule level than CO2 in terms of its integrated greenhouse effect at 

hundred-year timescales (Lelieveld et al. 1998). Nitrous oxide has an even larger permolecule global warming potential, roughly 300 times higher than CO2 on these 

timescales. This is partly because its atmospheric lifetime is ~120-years, compared to the
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134

~9-year methane lifetime (Denman et al. 2007). The concentration of these two species 

in the atmosphere is determined primarily by a balance between surface sources and 

atmospheric losses. The atmospheric destruction of methane is dominated by reaction 

with the hydroxyl radical (Quay et al. 1999) while loss of atmospheric nitrous oxide 

mostly proceeds via stratospheric photodissociation (Prather 1998). Since 1750, when 

atmospheric methane concentrations hovered around 700 nmol /mol , anthropogenic 

activities have increased methane abundances to 1850 nmol /mol (Denman et al. 2007). 

Methane growth rates leveled off in the mid-1980s and early part of the 21st century 

(Lassey et al. 2007), but recent studies have shown renewed growth (Lelieveld 2006;

Rigby et al. 2008). In that same time period, the atmospheric abundance of nitrous oxide 

has increase from 270 nmol /mol to its present value of 320 nmol /mol (Fluckiger et al.

1999).

Quantifying the impact of the airline industry on climate change must include accurate 

accounts of CH4, N2O, and CO2, given their radiative importance and long atmospheric 

lifetimes. Many studies have quantified the emission of CO2 in aircraft engines (Brasseur 

et al. 1998), but fewer have examined methane and nitrous oxide emissions. Direct 

aircraft emissions of these species have the potential to affect global budgets. Nitrogen 

oxide emissions also indirectly decrease the lifetime of methane in the atmosphere via 

chemical feedbacks involving ozone and the hydroxyl radical (OH) (Denman et al. 2007). 

A competing effect exists with carbon monoxide emissions, as feedbacks with CO and

OH can increase methane’s atmospheric lifetime (Prather 1996). Aircraft emissions are 

also noteworthy in that they affect chemical composition at altitude. This is readily 

apparent in cloud contrails, but is also of interest given atmospheric dynamics and known 

loss mechanisms.

Previous studies have highlighted the large variability of methane concentrations seen at 

the exit of engines operating at different conditions. Spicer et al. (1992, 1994) were 

among the first to give detailed aircraft exhaust emission concentrations for a variety of 

organic species in military and commercial aircraft engines. Wiesen et al. (1994) 

examined methane and nitrous oxide emissions from different commercial jet engines 

using different fuels during the AERONOx campaign. The finding emphasized in these 

studies was the consumption of atmospheric methane at high engine thrust conditions, the 

production of methane at low-power conditions, and the production of N2O irrespective 

of engine mode. The findings suggested that aircraft emissions had negligible impacts on 

the global CH4 budget. They also found that N2O emissions were smaller than those of 

lower-temperature combustion power plants (Laird and Sloan 1993) and concluded that 

aircraft emissions of N2O also had a negligible impact on the global N2O budget.

Methane emissions at idle and taxi conditions, however, varied by 500%. The general 

trend was that methane was produced at these modes, but estimates varied based on 

engines and fuels consumed. Spicer et al. (1994) showed enhancements of upwards of 9

μmol /mol in undiluted exhaust, roughly five times ambient concentrations, whereas

Spicer et al. (1992) measured methane concentrations of 1.8 μmol /mol in the exhaust,

most of which was presumably from the ambient air flushed through the turbine engines. 

Currently, the ambient concentration of methane is approximately 1.8 μmol /mol, though 
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135

it was closer to 1.7 μmol /mol in 1992 (Dlugokencky et al. 1998).

While there has been a consensus on the overall trends, a more complete quantitative 

assessment of methane emission factors as a function of engine thrust has remained 

poorly constrained. AAFEX provided a means to quantify non-CO2 greenhouse gases 

emission data, in addition to other gaseous and particulate pollutants, for a variety of 

fuels, engine operating powers, and ambient conditions. Analysis of the AAFEX dataset 

is intended to guide the aviation industry in addressing the most important emission 

issues associated with alternative fuels.

Isotopic information is potentially useful in answering questions about methane 

consumption and production in the aircraft. Methane sources can be categorized as 

bacterial, biomass burning, or thermogenic (Quay et al. 1999). Each of these sources has 

a characteristic isotopic composition that differs from the isotopic composition of 

ambient methane: δ13CCH4 = -47.5 ‰ relative to vienna pee dee belemnite (VPDB). 

Bacterial methanogenesis is dominated by two pathways: methylated substrate 

methanogenesis and CO2 reduction. Carbon reduction by hydrogen fractionates

according to its kinetic isotope effect (KIE) that discriminates against 13C leading to 

δ13CCH4 as low as -110 ‰ (Whiticar 1999). Fermentation of methylated substrates has a 

lower KIE fractionation depending on the substrate, leading to δ13CCH4 on the order of -

50 ‰ -60 ‰. The δ13CCH4 observed in samples is very much dependent on the δ13C of 

the methylated substrate and CO2 precursors, which are in turn dependent on the 

cumulative fractionation associated with prior reactions. Thermogenic sources, primarily 

associated with fossil carbon combustion, are more enriched in 13C and have isotopic 

compositions around -20 ‰ to -30 ‰.

Advances in laser and detector technology have allowed for greater sensitivity in highresolution absorption spectroscopy (Nelsonet al. 2008; Tuzsonet al. 2008). Zahniseret al.

(2009) provide a description of the spectrometer used at AAFEX to measure 12CH4 and 

13CH4 at two distinct spectral lines with precisions of 0.6 nmol/mol and 6 nmol/mol, 

respectively. A similar instrument operating at a different spectral region was used to 

measure N2O and HONO, with precisions of 0.3 nmol/mol and 0.15 nmol/mol, 

respectively. With a high duty cycle due to continuous wave operation and a relatively 

small sampling cell volume operated at low pressure, these instruments provided high 

frequency measurements of methane, nitrous oxide, and the isotopic composition of that 

methane.

Methods

AAFEX was a comprehensive test of the effects of synthetic Fischer-Tropsch (FT) fuels 

on the trace gas and particle emissions of gas turbine engines. The tests were performed 

in Palmdale, California on the same CFM56-2C1 engine studied during APEX-1(Wey et 

al. 2006). AAFEX included three chemically distinct fuels: JP-8, a Fischer-Tropsch (FT1) fuel derived from a natural gas feedstock and synthesized by Shell, and a second 

Fischer-Tropsch (FT-2) fuel derived from a gasified coal feedstock and synthesized by 

Sasol. The JP-8 fuel contained 1200 ppm sulfur, while the sulfur contents of the two 

Fischer-Tropsch fuels were 20 ppm (Sasol) and less than 17 ppm (Shell). In addition to 
APPENDIX E

136

the pure fuels, 50/50 (by volume) blends of the fuels were tested. During all tests, 

engines 2 and 3 (the two engines closest to the fuselage) were active and were sampled at 

1 m and 30 m probes. Engine 2 (inboard left engine) served as a reference as it burned 

JP-8 for the entire test duration while engine 3 (inboard right engine) burned either JP-8 

or the synthetic fuel depending on the test day. Advected plumes of emissions were 

sampled downwind of the plane at the 150 m probe. Figure 1 shows the layout of the 

sampling trucks, trailers and inlets relative to the aircraft. The daily AAFEX test 

activities are summarized in Table 1.

The majority of instrumentation at AAFEX was located on the starboard side of the 

plane. In Figure 1, the top left insert shows the NASA DC-8 which was chocked on the 

runway. The downwind trailers housed instrumentation to measure CH4, CO2, O3, NOx, 

HONO, N2O, and particulates, and were positioned 150 m away from the engine output 

in the direction of the predominant wind. This positioning was critical to measure

advected plumes of engine exhaust at low-power conditions when exit velocities of 

engine emissions did not have sufficient momentum to reach the downwind trailer inlets. 

The lower-left insert of the figure shows the inlet in relation to the aircraft and lowerright insert shows the configuration of the particulate and gas phase inlets mounted to a 1-

meter tripod. The inlet was designed to eliminate the need of a filter which is critical for 

the HONO measurement, but it also eliminated potential contamination of the CH4 and

N2O measurements. These precisions for the 12CH4 and 13CH4 measurements were 50% 

worse than lab performance because of alignment instabilities from the lack of trailer 

conditioning and the requirement of keeping the trailer closed during aircraft engine 

operation. Simultaneous measurements of CO2 were made using a commercially 

available Licor LI-6262 infrared gas analyzer. By making highly time-resolved 

measurements of methane and CO2, the concentrations of each are quantified in both the 

exhaust plume and in the background air unaffected by the exhaust. This measurement 

technique was particularly important during early morning measurements before

atmospheric convection fully mixed the planetary boundary layer. Strong methane 

sources nearby resulted in ambient mixing ratios on the order of 2.5 μmol /mol during 

night-time inversions, as measured overnight during the AAFEX day off (tTable 1).

Results

Figure 2a shows time series data from January 26, 2009 showing the different 

correlations between carbon dioxide, methane, and nitrous oxide concentrations. During 

idle conditions, CH4 plumes of 30 nmol /mol correspond to 70 μmol /mol CO2 plumes. 

At 30% thrust conditions, this relation changes noticeably, with larger 200 μmol /mol 

CO2 plumes corresponding to methane depletions of 20 nmol /mol . Fuel-based emission 

ratios in units of nmol /mol CH4 per μmol /mol CO2 can be calculated by regressing CH4

against CO2 in individual plumes, as shown in Figure 2b. Fuel-based emission indices 

can be calculated according to Herndon et al. (2004):

The factor of 3160 g CO2 (kgF uel ) −1 represents the stoichiometric calculation of CO2

produced per kilogram of JP-8 fuel consumed assuming complete combustion given a 
APPENDIX E

137

particular hydrogen to carbon ratio. This ratio is 13.7% hydrogen by weight for JP-8 (Vay 

et al. 1998; Brasseur et al. 1998). Corresponding fuel analyses were carried out for FT-1 

and FT-2 fuels, resulting in CO2 emissions ratios of 3090 and 3110 g CO2 (kgF uel )

−1

,

respectively. An identical calculation is carried out for nitrous oxide by substituting N2O

in the place of methane and accounting for the molecular mass differences. These 

emission indices of methane and nitrous oxide were calculated for 1480 plumes at 

various engine thrust modes, of which only the plumes with a variance on the regression 

smaller than 0.2 were used (n= 1103) in subsequent analysis.

Figure 3 shows the individual plume distributions of emission indices binned by fuel type 

for each of engine power conditions along with ambient temperature values for each 

plume. It is immediately apparent that the number of plumes observed at low-power 

conditions is much fewer than those at higher engine thrusts. This is not surprising for 

two reasons: a) advection of the plumes of engine exhaust was facilitated by the wind

velocities generated at higher thrusts, and b) the prevailing winds were not favorable on 

all but the first day of AAFEX when only JP-8 fuel was measured. Figure 3 also 

illustrates the broader distributions observed at idle and taxi conditions in comparison 

with those at higher engine thrusts. Figure 4 shows box and whisker plots for methane 

and nitrous oxide emission indices as well as undiluted carbon dioxide concentrations 

observed at the engine exhaust plane (EEP) (Yelvington et al. 2007). Two sample T-tests 

were performed between each fuel (JP-8 vs FT-1, JP-8 vs FT-2, and FT1 vs FT2) at each 

of the 7 engine thrust conditions. Of the 21 population comparisons for methane, 5 were 

significant at the p=0.05 level, but the mean p-value was 0.30. For nitrous oxide, 10 of 

the 21 tests had p-values below .05, but the mean p-value was 0.15. 

An explanation of the greater range of emission indices at idle and taxi conditions is 

further illustrated with subsamples of aircraft exhaust taken during each test flight and 

analyzed with the same instrumentation while the aircraft engines were off. Aircraft 

exhaust from the 1 m probe was flushed into 2-L steel canisters during each test flight and 

then diluted down with ultra-high purity helium. These subsamples were then overblown 

across the inlet of the spectrometers to validate the emission ratios calculated from the 

advected plume data. Figure 4 shows the emission indices calculated from these 

subsamples. Only cans where the carbon dioxide and methane values reached a steady 

value were used, as these represented the mixing ratios of those compounds in the can. 

Corrections were made for the dilution by multiplying the methane values with the ratio 

of CO2 values observed at the EEP to the concentrations measured while overblowing the 

inlet. Emission indices could then be calculated for these subsamples by dividing the 

corrected methane exhaust values by the CO2 EEP values from Figure 4. The 

corresponding emission indices are shown in Figure 5 for the 11 canisters collected in 

this way. We focused the measurements on idle conditions and high-power conditions 

because these were where previous studies have dissagreed. Canisters 1 and 2 were both 

sampled from the same inlet at 7% engine thrusts, the first being sampled while the 

engine was starting from a cold state, and the latter was sampled after the engine had 

operated for 40 minutes at higher thrusts. The engine history, therefore, has an important 

effect on methane emission indices, and this in part explains the variability seen in 

advected plume derived emission indices, similar to other hydrocarbon emissions. Figure 
APPENDIX E

138

4 also includes the 1-m subsample data superimposed on the range of advected plume 

data observed. Canisters 2 and 3 are outside the range of this plot, however. Additionally, 

the emission indices at 100% thrust calculated from subsamples could never be less than 

zero, as the subsamples at 100% thrust contain no methane, and the methane measured in 

those samples from the QCLS is within the detection limit of methane. The plume EIs are 

negative only because the engine is consuming atmospheric methane, and in the absence 

of atmospheric methane, these EIs would also be zero.

Figure 6 shows emission rates for N2O and CH4 at percentage maximum thrusts that 

correspond to the main operational modes - idle, approach, climb-out, cruise, and takeoff. The measured, fuel-based emission indices (g N2O (kgFuel )

−1

) have been converted 

to an absolute emission rate (gN2Ohr−1

) using the fuel flow rates noted from the cockpit 

during the test. The analysis for JP-8 fuel is representative of the Jet-A fuels currently 

used throughout the world. Emission rates for FT-1 and FT-2, which are also shown in 

Figure 6 were indistinguishable from those for JP-8 fuel, though we note that N2O

emission indices for FT-1 are consistently higher than JP-8 while those of FT-2 are 

lower. No apparent trend is present in the methane emission data. Since the aircraft test 

was conducted on the ground, the cruise mode measurement may not be completely

representative of in-flight emissions because of the reduced pressure and temperature at 

cruising altitude.

The total amount of methane emitted or consumed during a hypothetical landing take-off 

cycle or an entire flight can be calculated by multiplying the above emission rates by the 

time-in-mode for each segment of a flight. Table 2 shows this calculation using the timein-modes for a standard International Civil Aviation Organization (ICAO) landing takeoff cycle and one hour of cruise. These times, and their corresponding thrusts, are subject 

to significant variability that can affect the results for an actual landing take-off cycle. 

The results indicate that there are net methane emissions during this hypothetical flight, 

but that even just 1-hour of cruise conditions (65% thrust) leads to far more atmospheric 

methane destruction. Accounting for the variability of the inputs to these calculations 

(e.g., ICAO idle vs. ground idle, time spent in cruise, etc), it is evident that the aircraft 

operations have a net negative direct impact on atmospheric methane concentrations. A 

more accurate calculation would require methane emission indices measured from 

aircraft at actual cruise altitude rather than at the surface as measured during AAFEX. 

Even for a relatively short flight, however, consumption at cruise is much larger than 

production at idle.

Conclusions about the isotopic composition of methane produced in jet-engines are 

difficult because of the range of observed methane values typically seen 150 m

downwind of the source. Taking the isotopic composition of JP-8 fuel to be -40% and 

assuming no fractionation during methane production means resolving a 7% shift over a 

range from 0 to 1/1800 nmol /mol on an inverse scale, as is typically used with Keeling 

plots (Pataki et al. 2003). This corresponds to resolving a 0.115% shift over a 30

nmol/mol range in advected plumes which are typically observed on the order of seconds. 

With in-field 1-sec instrument precision of 3%, isotopic interpretations are difficult to 

make because of the sampling. Fewer diluted plumes sampled closer to the aircraft engine 
APPENDIX E

139

combined with better temperature control would have allowed for better measurements of 

the 13CH4 absorption line. Similarly, isotopic analysis of the subsamples taken at the 1-m 

probe and diluted with He were impossible because a) subsamples taken at high engine 

powers had no methane in them and b) subsamples taken at low engine powers were 

diluted by a factor of ∼70 such that the mixing ratios present in the subsamples were all 

below 500 nmol /mol, well outside of the dynamic range of calibrated 13CH4

concentrations for this instrument.

Future aircraft measurements of the isotopic composition of methane emitted in aircraft 

exhaust could help answer several questions about the chemistry occurring in the engine, 

potentially distinguishing methane produced in the engine from background atmospheric 

methane. A closer probe sampling location to ensure a larger range of observed methane 

mixing ratios would be necessary. The mean engine exhaust plane methane concentration 

at idle and taxi conditions was 8.3 μmol /mol, calculated from dilution corrections of the

CH4 emission ratios using the EEP CO2 distributions in Figure 4.

Discussion

A discussion of this work in context of previous studies is helpful. Wiesen et al. (1994) 

and Heland and Schafer (1998) are the only studies to our knowledge to present nitrous 

oxide emissions data, while methane emission data has been characterized by a total of 7 

studies to date. The results of past studies and the present AAFEX work are summarized 

in Tables 3 and 4. Mean engine exhaust concentrations of methane and nitrous oxides 

determined in these studies are shown in Figure 5. These different methods of presenting 

emissions observations can be compared by normalizing the concentrations with CO2

data according to Equation 1.

Nitrous oxide aircraft emissions data is limited. Wiesen et al. (1994) presented a mean 

nitrous oxide emission index of 0.11 g N2O (kg fuel)−1 ± 0.0098 across all thrust settings. 

This was not corrected for ambient nitrous oxide concentrations, which, if accounted for, 

would decrease the average emission index by ~30\% to a value closer to .077 g N2O (kg 

fuel)−1, still slightly higher than the value of 0.064 g N2O (kg fuel)−1 ± 0.0035 in the 

present study. The trend of increasing nitrous oxide emissions with increasing thrust 

appeared to be reversed at AAFEX. Beyond the obvious differences attributed to the fuel 

and engines used, nitrogen oxides (NOx) can convert to N2O in these engine plumes, 

especially in the presence of acid aerosols (Wiesen et al. 1994). This might affect 

advected plume data but the present agreement with Wiesen et al. (1994), which 

measured nitrous oxide offline from exhaust filled cylinders, suggests that these effects 

are small. NOx data was not presented in the Wiesen et al. (1994) study, so it is 

impossible to compare those effects. Such a mechanism could explain the differences in 

emission indices at lower thrusts seen at AAFEX, as these plumes had longer lifetimes 

than those sampled at higher powers, when advection was aided by larger engine exit 

velocities.

Heland and Schafer (1998) were the only other study to present data on nitrous oxide 

emissions of aircraft exhaust. They measured using an passive FTIR spectrometer that 

relies heavily on good spectroscopic parameters for the various absorbers present, 
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140

calibration of blackbody emission spectra, and good background spectra to normalize out 

the absorption due to molecules present in the instrument aperture but not in the plume. 

They reported an emission index for higher-thrust levels of 1.3 g N2O (kg fuel)−1 a full 

order of magnitude greater than those of Wiesen et al. (1994) and this study, but also state 

that nitrous oxide mixing ratios were below the detection limit at idle power conditions. 

The engine probed in this study is the same as that of AAFEX, and therefore the large 

discrepancy between the emission ratios reported, as well as the lack of data at idle

conditions when nitrous oxide emissions have been shown not significantly different 

from other power conditions, call into question the instrument precisions of nitrous oxide 

possible with a passive spectrometer.

Other studies mention nitrous oxide aircraft emissions but do not report data. Vay et al. 

(1998) measured contrail plumes behind a T-39 and a B-757 aircraft but did not report 

the nitrous oxide data. They claim that N2O was found not to be an important exhaust 

constituent. Zheng et al. (1994) examined 20 plumes of NOy, 5 of which correlated to 

CO2 spikes seen during the Airbone Arctic Stratospheric Expedition. Of those five 

plumes, they found no significant increases for either nitrous oxide or methane.

Nitrous oxide emission indices during AAFEX most closely resemble those measured by 

Wiesen et al. (1994) despite being consistently lower at higher thrusts, and provide 

another constraint on the nitrous oxide budget. Scaling up the emission rate of nitrous 

oxide from the ~20 billion gallons of fuel consumed by the airline industry annually, 

results in a yearly N2O flux of ~4 GgN2Oyr−1 roughly .025 % of the total source term of 

17.7 TgNyr−1 (Denman et al. 2007).

Methane, in contrast to N2O, is a net atmospheric sink term, consuming roughly 3.5 

GgCH4yr−1, completely negligible in terms of the global source and sink terms, each on 

the order of 580 TgCH4yr−1 (Denmanetal.2007). Spicer et al. (1992) were among the first 

to report detailed organic species as well as CO, CO2, and nitrogen oxides for aircraft 

engine emissions. The 1992 paper published data using JP-4 fuel in F-101 and F-110

engines used primarily on the B1-B and F-16 airplanes, respectively. The 1994 paper 

focused on engines used in more commercial transport aircraft such as the Boeing 737, 

the CFM-56 and TF-39. Interestingly, the core engine of the CFM-56 is the same as that 

of the F101 engine used in the 1992 study, but it seemingly produced very different 

methane emissions, particularly at idle. This could be explained by the differences in

methane emissions observed between idle conditions on a recently started engine, versus 

those from an engine in the same idle power condition after having run at high-power 

conditions.

Wiesen et al. (1994) report positive emission indices at all powers but also present 

exhaust concentrations. Their emission indices are positive at high thrusts only because

CH4 is present in the air used in the aircraft engines. Background atmospheric 

concentrations of species must be used when determining emission ratios. This was not 

possible given their extractive sampling technique, but their emission indices are 

misleading because background air samples were never characterized. Only the exhaust 

concentrations are used in the study comparisons presented in Figure 7.
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141

The NASA EXperiment to Characterize Aircraft Volatile Aerosol and Trace-species 

Emissions (EXCAVATE) sought to further expand the sparse data set of organic 

emissions from roughly 300 commercial aircraft engines in use. Anderson et al. (2006) 

measured methane to a 1-sec precision of 1 nmol /mol on the Rolls Royce RB211-535E4 

engine using JP-5 fuel with two sulfur contents (810 and 1820 μmol /mol S) and reported

methane emission concentrations as well as upper limits of emission indices. They chose 

not to report possibly negative emissions indices, as these represent consumption of 

methane, but present exhaust concentrations of methane that are similar to ambient values 

around 1.8 μmol /mol . Their emissions indices are dependent on the instrumental 

accuracy, which they report as 1% (as opposed to precision of .1%) meaning that nearly 

all of their reported exhaust methane concentrations are within 20 nmol /mol of ambient 

methane concentrations. In contrast with this direct exhaust canister sampling, the 

advected plume method employed in this study relies only on the instrument precision, as

it is the relative changes in methane that determine emission indices, once normalized to

CO2 values. Our instrument precision is .027%. The emission indices during low power 

of JP-8 fuel during the AAFEX mission were higher by an order of magnitude than 

during the EXCAVATE mission,

most likely attributable to the different engine, fuel, ambient operating conditions, and 

engine history before sampling. EXCAVATE low-power findings most closely resemble 

those of Spicer (1992), while AAFEX low-power results are more similar to those of 

Spicer (1994).

One research question that persists in many of these studies is whether the findings were 

representative of actual flight conditions. Vay et al. (1998) sought to answer this during 

the SUCCESS (Subsonic Aircraft: Contrail and Cloud Effects Special Study) campaign 

by sampling CO, CH4, N2O, and H2O from inlets aboard the NASA DC-8 (the same 

plane used as the emission source in AAFEX) flying behind a T-39 and B-757 aircraft. 

Both high and low sulfur content fuel (675 and 75 μmol /mol S) exhaust was sampled 

and the reported 1-sec precision of their methane analyzer was 1 nmol /mol . They 

reported that 81% of the plume crossings observed showed anticorrelation with the CO2

data, showing that atmospheric methane was being consumed during in situ observations. 

Their reported emission indices ranged from -1.6 to 1.2 g CH4 /kg fuel, with the positive 

values attributed to transient engine conditions (i.e. changing from 65% to 85% 

maximum thrust). The range of values observed at AAFEX were much smaller in 

magnitude than the -1.6 value, though we note that only 12 plumes were quantified in

Vay et al. (1998). Their findings further validate previous ground based methane exhaust 

emission studies. Furthermore, Wiesen et al. (1994) showed that methane depletion at 

high power was observed from aircraft both at a ground-level test facility and at a special 

altitude-simulation test cell. It is important to note that aviation NOx emissions at altitude 

have a greater potential to impact global methane budgets than the levels of methane 

emissions quantified in these various studies, whether positive or negative (Denman et al.

2007).

The results from the Aircraft Particle Emissions eXperiment (APEX) reported positive 
APPENDIX E

142

methane emission indices at higher engine power (Wey et al. 2006). Methane was 

measured with a multi-gas analyzer. Because of its relatively broad spectroscopic 

resolution, this instrument does not have the specificity to methane that other

measurement techniques have, and may have been subject to interference from other 

species present in the exhaust. The data from APEX does not agree with that reported by

Spicer et al. (1992), Spicer et al. (1994), Vay et al. (1998), Anderson et al. (2006),

Wiesen et al. (1994), or the current results from AAFEX.

Spicer et al. (2009a) also present methane emission indices for both a C-130 aircraft and 

a F-15 aircraft. The corrigendum to the study (Spicer et al. 2009b) that noted an error in 

the algorithm used to calculate emissions factors decreased the methane emission factors 

by ∼15% for the C-130 and changed the sign on the F-15 factors. Only the F-15 emission 

indices are presented in Figure 7 as the emission factors for the C-130 aircraft are so high 

that corresponding methane exhaust concentrations at all power settings would be on the

order of 20-30 μmol /mol well beyond the range of the figure. Pure exhaust 

concentrations can be calculated by multiplying emissions ratios (Equation 1) by the 

difference between CO2 values at the EEP and ambient values, and adding ambient 

concentrations to those values. We also note that their equation for determining emission 

factors effectively removes the CO2 concentrations measured from the emission factor 

calculation by assuming that all of the fuel carbon is converted to either CO2, CO or other 

hydrocarbons. Because the equation then depends on the emission factors of other 

chemical species, many of which have much lower measurement precisions, these values 

are not directly comparable to other methane emission indices, which may be an 

additional reason why the C-130 values are completely beyond the range of expected 

emission indices and exhaust concentrations.

Although low-power emissions of methane seem to vary by almost an order of 

magnitude, with the exception of Spicer et al. (2009b), these studies agree on the methane 

consumption at power conditions greater than idle and taxi, by far the predominate mode 

of engine operation. Data presented here further confirms methane emission results from 

previous aircraft exhaust studies, and highlights the lack of effects alternative fuels will 

have on these greenhouse gases. We observe methane depletion during engine operating 

states higher than 7% maximum thrust and conversely methane production at ground idle 

and taxi conditions when aircraft engines are less efficient at combusting fuel. Canisters 

taken from the 1 m inlets further suggest that, similar to other hydrocarbon emissions, 

methane production efficiency can vary based on the history of the engine, with a colder 

engine producing more methane than a warmer one at equal thrusts.

Conclusion

This AAFEX study, in context with previous methane and nitrous oxide exhaust studies, 

provides another robust constraint on long-lived, greenhouse-gas emissions of 

commercial aircraft engines in operation today. Furthermore, the quantification of 

methane emissions is important for understanding the speciation of organic emissions at 

low powers. Because engine certification for hydrocarbon emissions requires uses of

Flame Ionization Detector which measures a wide variety of hydrocarbons without 

speciation detail, relating this certification hydrocarbon data to speciated measurements 
APPENDIX E

143

must take into account the contribution of methane. Proper accounting of speciated 

hydrocarbons help inform the correct proportions of individual compounds that 

contribute the most risk to human health and welfare. The measurement precisions of 

both methane and nitrous oxide presented in this study are the best to date; more than two 

times better than previous studies. By considering a representative flight profile, the net 

contributions to global methane from aviation due to direct methane emissions are 

negative, indicating a net methane consumption. However, the role of NOx emissions at 

altitude have a greater potential to affect the global methane budget than direct methane 

emissions, whether positive or negative, at the levels quantified in studies to date. 

Analysis of the different fuels used at AAFEX also shows that the global methane and 

nitrous oxide budgets will not be affected by an airline industry shift in fuel usage.

Acknowledgements

Parts of this reasearch are supported by the Department of Energy, Small Business 

Innovation Research Award DE-FG02-07ER84889, the PARTNER Center of Excellence 

(jointly sponsored by the FAA, NASA and Transport Canada) via Missouri University of 

Science and Technology, and the National Science Foundation Graduate Research 

Fellowship Program. The authors also greatly acknowledge W. Berk Knighton of 

Montana State University, Michael T. Timko and Zhenhong Yu of Aerodyne Research 

Inc., and Changlie Wey of ASRC Aerospace Corp.

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APPENDIX E

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APPENDIX E

148
APPENDIX E

149
APPENDIX E

150
APPENDIX E

151
APPENDIX E

152
APPENDIX F

153

APPENDIX F: Investigations of Plume Chemistry during AAFEX

Ezra C. Wood1, Scott C. Herndon1, H. Ben Lee2, Michael Timko1, Zhenhong Yu1, W. 

Berk Knighton3, Richard C. Miake-Lye1

1 Aerodyne Research, Inc., Billerica MA

2 School of Engineering and Applied Sciences, Harvard University, Cambridge MA

3 Department of Chemistry, Montana State University, Bozeman MT

Introduction

Understanding the chemistry of aircraft exhaust plumes is important in order to 

understand the transformations of VOCs/HAPs from the engine exhaust plane to the 

airport fence line and beyond, the timescale of formation of "secondary" particles that 

require oxidation to form (e.g., formation of sulfate aerosol from SO2), and the formation 

and/or destruction of ozone (O3) in the plume. 

During the AAFEX campaign, various aspects of plume chemistry were investigated with 

the Aerodyne mobile laboratory (AML). The focus was on chemistry in the plume of 

exhaust while the engines were operated at low thrust (idle) because of the potential to 

identify observable changes in the VOC speciation and NOx-ozone chemistry.

Methods

In order to address plume chemistry, the Aerodyne mobile laboratory (AML) detached 

from the probe sampling system several times and sampled the exhaust plume 

approximately 60- to 200-m downwind of the DC-8. At high powers (above 15% rated 

thrust), the AML remained stationary and at least 150 m downwind of the engines. When 

the engines were operated at ground idle thrust, the AML drove on the tarmac and 

intercepted the exhaust plume at various locations. An example map of the mobile lab’s 

measurements are shown below, colored by the formaldehyde concentration:

Figure 1. Downwind measurements with the truck were performed on 1/26/2009, 

1/30/2009 (05:25 – 10:14), 1/31/2009 (11:42 – 15:18), and 2/2/2009 (07:00 – 08:45).
APPENDIX F

154

The instrumentation onboard the AML are described in companion reports. The key 

measurements aboard the AML for these studies are listed below:

Table 1. Instrumentation aboard the AML used for the measurements in this report.

Species Instrument Time 

response 

(sec)

Ozone (O3) 2B-Tech UV absorbance 

sensor at 254 nm

2

Nitric oxide 

(NO)

Thermoelectron 42i 

chemiluminescence sensor

1

Nitrogen dioxide 

(NO2)

QC-TILDAS (quantum 

cascade – tunable infared 

laser differential absorption 

spectrometer)

1

Ethene (C2H4) QC-TILDAS 1

Additionally, hydrogen peroxide (H2O2) and nitrous acid (HONO) were measured at the 

"150 m" trailer using the QC-TILDAS described in the companion report by Lee et al.

Results and Discussion

The main findings from the plume studies are summarized below.

1. O3 is formed in ground idle exhaust plumes

Most NOx is emitted in the form of NO. For example, NOx emissions from fossil-fuel 

fired power plants and vehicular traffic in the US consist of over 95% NO (Ban-Weiss et 

al. 2008; Ryerson et al. 2001), with the remainder NO2. NOx emissions from idling 

aircraft engines are an exception; depending on engine type and thrust level, the NOx

emitted consists of 70% to over 95% NO2 (Wood et al. 2008; Wormhoudt et al. 2007). 

This has ramifications for both ozone and NO2 pollution emitted from aircraft, since 

primary NO2 emissions lead to greater ambient concentrations of both O3 and NO2 than 

do primary NO emissions. We examined NOx-O3 chemistry in fresh exhaust plumes from 

the NASA DC-8 CFM56-2C engine using the downwind measurements. 

Primary NO emissions lead to decreases in ambient O3 because of the reaction

NO + O3 → NO2 + O2. (1)

Primary NO2 emissions lead to net formation of O3 because of the photolysis of NO2:

NO2 + light + O2 → NO + O3 (2)

Since NOx is emitted primary in the form of NO at high engine power (~climb-out to 

take-off), ambient O3 that is entrained into the exhaust plume reacts rapidly with the NO, 
APPENDIX F

155

leading to decreased O3 concentrations. Conversely, the primary NO2 emissions from 

low-power engine operation lead to increases in [O3]. Both of these cases are shown in 

figure 1 below. From 12:58 to 13:00, the mobile lab intercepted exhaust from the engine 

operating at high power and observed O3 concentrations that were ~20 ppb lower than the 

background concentration of 38 ppb. From 13:01 to 13:04, occasional exhaust plumes 

from the engine operating at low engine thrust (idle) were sampled by the mobile 

laboratory. In these low-power plumes, O3 was elevated up to 20 ppb above the 

background concentration.

Figure 1. Time series of C2H4, O3, NO, and NO2 measured downwind of the NASA DC8 during high engine power (up until 13:01) and low engine power (after 13:01).

The ethene concentrations are shown because they are a good indication of when the 

engines were operated at low thrust. Although the above results are expected based on the 

known emission indices of NO and NO2 and basic atmospheric chemistry, the formation 

of O3 in a fresh (aged less than minutes) combustion plume is unique to our knowledge. 

A second example is shown in figure 2. 
APPENDIX F

156

Figure 2. Formation of O3 in idle exhaust plumes.

Ozone sensors based on the absorption of UV light at 254 nm are known to suffer from 

interferences because of other species (gas or particle) that absorb or scatter in the same 

spectral region (Dunlea et al. 2006). Figure 3 below demonstrates that for the 

measurements at AAFEX, such interferences were not a significant problem. Figure 3 

plots O3 vs. C2H4, which is an indicator of low-power engine exhaust (along with all 

VOCs; the choice of C2H4 is mostly arbitrary). The data are color-coded by time of day. 

Data taken after 6:00 pm show no correlation between O3 and C2H4, which is expected 

because in the absence of sunlight O3 cannot form in the plume. Since enhanced O3 was 

only observed while there was still daylight (around 4:00 pm in Figure 3), we conclude 

that under the conditions sampled, interferences in the O3 measurement were negligible.

Figure 3. Enhanced O3 concentrations in the exhaust plumes were only observed during 

daylight, indicating that the O3 signal recorded by the 2B-tech O3 sensor were actually 

from O3 and not interfering species.
APPENDIX F

157

2. Peroxy radical chemistry is active in low thrust plumes

If the initial NO2 /NOx ratio is 1 and the only transformations that occur in the plume are 

the photolysis of NO2 and subsequent formation of ozone, then any O3 formed in the 

plume would be at the expense of NO2. That is, the quantity ([NO2]+[O3])/[NOx] would 

always equal 1, since an increase in O3 would correspond to an equal decrease in NO2. 

For the time period shown in Figure 2, the correlation between [NO2] + [O3] and NOx is 

graphed in figure 4: 

.

Figure 4. Correlation of ([O3] + [NO2]) with NOx. The high slope infers intraplume 

oxidation of NO to NO2 by peroxy radicals.

Since the slope actually exceeds 1 (and is equal to 1.09), it is evident that there was net 

conversion of NO to NO2 in the plume, as inferred from one limited idle plume observed 

at night during APEX3 (Wood et al., 2008). The NO oxidation is mostly likely from the 

following reactions:

NO + HO2 → NO2 + HO (3)

NO + RO2 → NO2 + RO (4)

Where "RO2" represents an organic peroxy radical (e.g., CH3OO). These organic peroxy 

radicals are formed from the oxidation of VOCs by reaction with the hydroxyl radical 

(OH):

RH + OH → R· + H2O (5)

R· + O2 + M → RO2 + M (6)
APPENDIX F

158

This VOC oxidation (i.e., combustion) is most rapid in the combustor of the engine, of 

course, but continues into the plume. 

Figure 5 shows the correlation of [O3] + [NO2] with [NOx] for all downwind sampling:

Figure 5. Correlation of ([O3] + [NO2]) with NOx for all downwind observations during 

AAFEX

The lower slopes (0.06 to 0.09) correspond to observations at high engine power. These 

slopes are very similar to the initial NO2/NOx emission ratio observed during probe tests. 

This indicates that the reactive peroxy radical chemistry is limited to low-power 

operation.

3. Formation of H2O2 in the plume

The measurements of H2O2 at the 150 m trailer represent, to our knowledge, the first ever 

measurements of H2O2 in the exhaust plume of any type of combustion source. The H2O2

observed can have two sources: direct emissions from the engine and plume chemistry. In 

both cases, the dominant formation reaction is likely to be self reaction of HO2:

HO2 + HO2 → H2O2 + O2 (7)

This reaction is hastened by water vapor. The emission indices observed for the entire 

AAFEX campaign are shown in figure 6:
APPENDIX F

159

Figure 6. Dependence of H2O2 emission indices on engine power (from Lee et al. 2010).

The most noticeable trend is the decrease of H2O2 EI with engine power. There is no 

discernable trend of H2O2 emission indices with fuel type or ambient temperature. That 

H2O2 EIs are highest at low-power is consistent with the intraplume conversion of NO to 

NO2 described earlier, which is largely a result of the reaction of HO2 with NO. The 

combustion model described in Wood et al. (2008) predicts H2O2 EIs of 0.036 g/kg fuel 

at 7% thrust – several times lower than the observed values (0.1 to 0.3 g/kg). This result 

suggests that either the model is not describing the combustion processes adequately or 

that a large portion of the H2O2 observed was formed in the plume itself.

4. HOx sources in the plume

The data presented above suggest that the concentrations of peroxy radicals (organic 

"RO2" radicals and the hydroperoxy radical HO2) in the plume are highly elevated above 

ambient values. Radical concentrations depend on the radical initiation rates, the 

propagation rates, and the termination rates. In this section we investigate the overall 

radical initiation rate and the propagation of the central OH radical. Calculations of the 

propagation and termination rates of the HO2 and RO2 radicals are more complicated 

because they require knowledge of the absolute radical concentrations. This is a topic for 

further study.

A. Radical initiation rates

The radical initiation rates (HOx production rate; "P(HOx)") are plotted in figure 7. The 

following reactions are included. Radical species (not counting NO which is a relatively 

stable species) are colored in red:

HONO + hν → HO + NO

HCHO + hν → H + CHO (which forms 2 HO2 radicals)

CH3CHO + hν → CH3 + CHO
APPENDIX F

160

alkenes + O3 → products + OH + R/HO2

Figure 7. HOx sources in the exhaust plume at low engine power as a function of 

dilution. 

Conditions for these calculations:

solar zenith angle = 30°

HCHO EI = 0.4 g/kg (corresponds to ~20° C operation for the CFM56-2C1 engine)

HONO EI = 0.1 g/kg

[O3]ambient = 50 ppbv

Typical ambient P(HOx) values vary from 0.1 to 2 ppt/s. The total calculated value of 

P(HOx) does not decrease to 1 ppt/s until the exhaust has diluted by a factor of 2000. 

P(HOx) is several orders of magnitude higher than ambient before the exhaust is diluted 

by a factor of 100. 

B. Propagation and termination of the OH radical

Reactions of the highly reactive OH radical either count as radical propagation or radical 

termination reactions. Reaction of OH with closed-shell molecules such as VOCs leads to 

further radicals (HO2, RO2), whereas reactions with other radicals (including NO and 

NO2) terminate the cycle. The overall OH reactivity is defined by the following equation:

OH reactivity = 

where X is the concentration of each species with which it reacts and kOH + X are the 

reaction rate constants. Figure 8 shows the absolute OH reactivity values and the wedges 

of the pie chart represent the species that dominate reaction with OH. Of the main 

∑[ ] +

i

i OH Xi X k
APPENDIX F

161

wedges, the only reaction that is a radical termination is reaction with NO2, which forms 

HNO3. All other reactions propagate the radical chain cycle. The relative size of the NO2

reaction increases with dilution because of the inverse dependence of the reaction rate 

with ambient temperature. 

Figure 8. OH reactivity of exhaust (ground idle) as a function of dilution.

Overall, the reactions of OH favor propagation rather than termination. For comparison, 

the highest OH reactivities observed in ambient air are ~100 s-1, observed only during a 

small time window of the morning in Mexico City (Shirley et al. 2006) – an exceptionally 

polluted place. These calculations by themselves do not quantitatively predict HO2 or 

RO2 concentrations, but when combined with the O3 and H2O2, observations do indicate 

that such chemistry cannot be ignored by air pollution models for accurate predictions of 

the impact of airports on air quality. 

5. The concentration of OH in the plume

While a direct measurement of OH in the diluted exhaust plume is elusive, it is possible 

to estimate the product of the OH concentration and the reaction time by investigating the 

reactions of VOCs with different OH reactivities. Consider ethene (C2H4) and 1,3-

butadiene (C4H6). The rate constant for the reaction of OH with benzene (1.2×10-12cm3

molecule-1s

-1

) is 56 times slower than the rate constant for the reaction of OH with 1,3-

butadiene (6.7×10-11cm3 molecule-1s

-1

). Thus as the plume reacts, the ratio of 1,3-

butadiene to benzene is expected to decrease as both species react with OH (making the 

safe assumption that neither VOC is formed by other reactions). The ratio of the two 

compounds is quantitatively related to the integrated OH exposure time Δt[OH] by the 

following equation:
APPENDIX F

162

where the k values are the rate constants for reaction with OH. At ground idle, the molar 

[C4H6]/[C6H6] ratio was 1.51 observed using the probe sampling but only 1.37 observed 

downwind when the AML detached and sampled exhaust downwind. At 7% idle, the two 

ratios were 0.95 (probe) and 0.87 (downwind). Both sets of values, when plugged into the 

above equation, give a value of Δt[OH] of 1.2 ×10 8 molecules OH · s/cm3

. With an 

estimate of 60 seconds for the total reaction time (Δt), this gives an estimate for the 

average OH concentration of 2×107 molecules/cm3

. For comparison, ambient OH

concentrations during daytime are usually in the range 1×106 molecules/cm3 to 1×107

molecules/cm3. This indicates that the rate of VOC oxidation is elevated within the first 

minute of plume evolution. 

References

Ban-Weiss, G. A., McLaughlin, J. P., Harley, R. A., Kean, A. J., Grosjean, E., and 

Grosjean, D. (2008). "Carbonyl and Nitrogen Dioxide Emissions from Gasolineand Diesel-Powered Motor Vehicles." Environ Sci Technol, 42, 3944-3950.

Dunlea, E. J., Herndon, S. C., Nelson, D. D., Volkamer, R. M., Lamb, B. K., Allwine, E. 

J., Grutter, M., Ramos Villegas, C. R., Marquez, C., Blanco, S., Cardenas, B., 

Kolb, C. E., Molina, L. T., and Molina, M. J. (2006). "Technical note: Evaluation 

of standard ultraviolet absorption ozone monitors in a polluted urban 

environment." Atmos. Chem. Phys., 6(10), 3163-3180.

Ryerson, T. B., Trainer, M., Holloway, J. S., Parrish, D. D., Huey, L. G., Sueper, D. T., 

Frost, G. J., Donnelly, S. G., Schauffler, S., Atlas, E. L., Kuster, W. C., Goldan, P. 

D., Hubler, G., Meagher, J. F., and Fehsenfeld, F. C. (2001). "Observations of 

ozone formation in power plant plumes and implications for ozone control 

strategies." Science, 292(5517), 719-723.

Shirley, T. R., Brune, W. H., Ren, X., Mao, J., Lesher, R., Cardenas, B., Volkamer, R., 

Molina, L. T., Molina, M. J., Lamb, B., Velasco, E., Jobson, T., and Alexander, 

M. (2006). "Atmospheric oxidation in the Mexico City Metropolitan Area 

(MCMA) during April 2003." Atmos. Chem. Phys., 6, 2753-2765.

Wood, E. C., Herndon, S. C., Timko, M. T., Yelvington, P. E., and Miake-Lye, R. C. 

(2008). "Speciation and Chemical Evolution of Nitrogen Oxides in Aircraft 

Exhaust near Airports." Environ Sci Technol, 42, 1884-1891.

Wormhoudt, J., Herndon, S. C., Yelvington, P. E., Miake-Lye, R. C., and Wey, C. 

(2007). "Nitrogen Oxide (NO/NO2/HONO) Emissions Measurements in Aircraft 

Exhausts." Journal of Propulsion and Power, 23(5), 906-911.

ln([ ] /[ ] ) ln([ ] )/[ ] ) ( ) [ ] 4 6 6 6 C4H6 t C6H6 t = C4H6 o C6H6 o + kC H +OH − kC H +OH ∆t OH
APPENDIX G

163

APPENDIX G: Gaseous And Non-Volatile Particulate Matter Emissions 

Measurements In CFM56 Engines – AAFEX Project

Edwin Corporan1, Matthew J. DeWitt2, Christopher Klingshirn2

1

Air Force Research Laboratory, Fuels and Energy Branch 

Wright-Patterson AFB, OH 45433 USA. edwin.corporan@wpafb.af.mil

2

University of Dayton Research Institute, 300 College Park, Dayton, OH 45469 USA

Abstract

Gaseous and particulate matter emissions were measured from a CFM56 engine burning 

two Fischer-Tropsch (FT) alternative (non-petroleum) jet fuels derived from coal and 

natural gas, and blends at 50% by volume of each fuel with JP-8. Detailed chemical 

analysis of the fuels was performed to provide insight into their performance and to infer 

potential impacts on engine emissions. Chemical analyses show that the alternative fuels 

were comprised of mostly paraffinic compounds (synthetic paraffinic kerosenes – SPKs) 

at varying relative concentrations and contained negligible heteroatom content and were 

mostly aromatic free. Engine tests demonstrated that the SPKs (neat and blended with JP8) produced significantly lower non-volatile particulate matter (soot) and had negligible 

effects on gaseous emissions relative to baseline JP-8 fuel. Measurement of the 

downstream exhaust plume showed a nucleation mode for particle formation, which 

increased the relative particle emission index. Initial analyses show a potential impact of 

fuel end-point temperature on particulate emissions at several low-power engine 

conditions. It was observed that the FT fuel with the higher end-point temperature 

produced significantly higher non-volatile particulate emissions; however, further 

research is warranted to verify this impact as only two fuels were evaluated.

Introduction

The growing demand and reduced supply of petroleum products combined with the 

instability in petroleum-rich countries results in high uncertainties and volatility in the 

cost of energy, particularly transportation fuels. As a result, efficient energy technologies 

and the development of alternative energy options, such as fuels from domestic 

alternative sources, have become a national priority. Alternative transportation fuels are 

desirable both from an energy security and environmental perspective as the 

preponderance of imported oil is converted to liquid transportation fuels. In the United 

States, liquid fuel production is roughly 200 billion gal/year, with gasoline, diesel, and jet 

fuel being produced in approximately a 70/20/10 ratio. Thus, domestically-produced 

alternative fuels could increase energy security. Domestic alternatives for gasoline 

(ethanol) and diesel (biodiesel) exist, but no operational alternative jet fuels are currently 

being produced in the United States. Alternative aviation fuels are also of interest for 

mitigating environmental impacts of fuel use, both on the global (climate change) and 

local (airport) air quality level. Although aviation contributes only 2% to global CO2

emissions1

, the U.S. Air Force (USAF) and the aviation industry are committed to 

contributing to potential solutions. Alternative aviation fuels are being sought as "drop-
APPENDIX G

164

in" replacements for current aircraft, requiring no modification to equipment, aircraft 

operations, handling, or transportation. This rules out ethanol (due to safety, 

performance, handling, and material compatibility issues) and biodiesel (due to low 

temperature and combustion performance, and storage stability issues).

Initial U.S. efforts in developing alternative aviation fuels focused on Fischer-Tropsch 

(FT) fuels produced from coal, biomass, and/or natural gas. Coal-derived "iso-paraffinic 

kerosene" (IPK) produced by Sasol in South Africa was approved for aviation use in 

blends up to 50% in Jet A-1 (on a producer-specific basis) in 1999. Generic FT 

"synthetic paraffinic kerosene" (SPK) was approved for use in blends up to 50% by vol. 

with JP-8 in MIL-DTL-83133F2 in 2008 and in blends with Jet A in ASTM D7566 

("Specification for Aviation Turbine Fuels Containing Synthesized Hydrocarbons")

3 in 

August 2009 (supported by a Research Report outlining the properties of SPK4). The 

USAF has been very active in the evaluation, demonstration, and certification of FT fuel 

blends from natural gas and coal. To date, U.S. military aircraft such as the B-52, C-17, 

and B-1B have been certified for use of a 50/50 (by volume) JP-8/FT blend. Other 

aircraft (i.e., F-22, KC-135, F-15, C-5, T-38) have already undergone flight tests and are 

scheduled to be certified on the FT blend in the near future. The next alternative fuel 

being studied for military/commercial certification is "hydrotreated renewable jet" (HRJ), 

which is a hydrocarbon aviation fuel produced from animal fat/vegetable oils 

(triglycerides) by hydroprocessing. This fuel has also been called bio-SPK and "green 

jet." The ASTM D7566 specification is structured to support various classes of 

alternative fuels (in Appendices), with HRJ anticipated to be added in the near future as 

more data become available. It is anticipated that fuel produced from ligno-cellulosic 

feedstocks will also be added at a future date.

∫Techniques For Chemical And Physical Analysis 

The chemical composition and physical properties of the alternative fuels were evaluated 

to provide improved insight into their performance and to infer potential behavior during 

implementation. The analyses included evaluation of JP-8 specification properties and 

non-standard analysis such as Gas Chromatography/Mass Spectrometer (GC/MS), Gas 

Chromatography with a Flame Ionization Detector (GC/FID), and High Pressure Liquid 

Chromatography (HPLC). 

Emissions Evaluations

Emissions Instrumentation

PM and gaseous emissions were sampled from the engine exit plane using water-cooled 

probes and transported to the analytical instruments via unheated lines. PM samples were 

also collected approximately 30 meters downstream of the engine exit to study plume 

characteristics, particularly PM evolution; however, this summary will focus mostly the 

engine exit plane emissions. The PM sample stream at the engine exit (mostly nonvolatile) was diluted with nitrogen near the probe tip to prevent water condensation, 

minimize particle losses in the sample lines and prevent saturation of the particle 

counting instruments. The PM sample line was at room temperature. PM measurements 
APPENDIX G 

165 

were corrected for dilution, based on the raw and diluted CO2 measurements. The PM 

emissions were characterized using conventional aerosol instruments. A TSI Model 

3022A Condensation Particle Counter (CPC) was used to provide a count of particles per 

unit volume (particle number (PN)), a TSI Model 3936 Scanning Mobility Particle Sizer 

(SMPS) with a nano-differential mobility analyzer (DMA) to obtain the particle size 

distribution from 5-150 nm, and a Rupprecht & Patashnick Series 1105 Tapered Element 

Oscillating Microbalance (TEOM) was used to obtain real-time particle mass emissions. 

The low particle mass for these engines was below the TEOM detection limits, and thus 

TEOM data will not be discussed herein. An in-house designed and built smoke machine 

was used to collect soot samples for determination of the engine Smoke Number per SAE 

ARP 1179.4 Gaseous emissions were sampled with undiluted probes and transported 

through heated lines kept at 150°C per the SAE ARP 1256.5

 Major and minor gaseous 

species were quantified using an MKS Multi Gas 2030 Fourier Transform Infrared 

(FTIR) based analyzer and total unburned hydrocarbons were quantified using a CAI 600 

Heated Flame Ionization Detector. A non-disperse infrared analyzer measured the CO2

for the diluted samples from the particle instruments. 

Gaseous and PM emissions were sampled using probes located at the engine exit plane. 

A diagram of the probes that were set up is shown in Figure 1. Three undiluted probes 

(Gas) were used for smoke number and gaseous emissions measurements. The sample 

lines were individually connected to a valve box, which directed the sample from a 

particular probe to the smoke sampler, gas analyzer or to a vent tube. The PM sample 

was captured with two probes and was diluted at the probe tip (PM) to minimize particle 

loss and reduced the particle concentration to allowable levels for the CPC. 

Figure 1. Setup of gas and particle probes. Red line shows engine centerline. 

AFRL Smoke or Gas (#4)

(two ganged probes)

NASA GRC Gas

AFRL Smoke or Gas (#6)

NASA GRC Gas

PM

AEDC Smoke

AFRL TEOM

AFRL EC/OC

UC-SD/CMU

AR

PM

AFRL Smoke or Gas (#2)

Dist from Ground Probe Probe

(inches) Port # Type

76.5 4     RP1     

75.0 5    RP2    

73.5 6 RG4

72.0 7 RP3

70.5 8 RP4

69.0 9 RG5

67.5 10    RP5    

66.0 11     RP6     

64.5 12 RG6

63.0 13 RG7

61.5 14 RG8

60.0 15 RG9

58.5 16 RG10
APPENDIX G

166

Test Data And Discussion

Chemical And Physical Analysis Of Fuels

Fischer-Tropsch Fuels

The Sasol (FT2 coal-derived) and Shell (FT1 natural gas-derived) fuels were produced 

via indirect liquefaction using FT synthesis. During indirect liquefaction, the feedstock is 

partially oxidized either via gasification or steam reforming to produce synthesis gas

(carbon monoxide and hydrogen). The synthesis gas (syngas) is fed to an FT reactor 

where it is converted into higher molecular weight hydrocarbons. The Sasol SPK (also 

referred to as Iso-Paraffinic Kerosene (IPK)) is produced via polymerization of C3 and C4

olefins followed by hydrotreating and fractionation to produce a fuel with the desired 

boiling range.6 This process results in an SPK with a very high degree of branching. The 

Sasol fuel was the first synthetic fuel to be approved as a blend feedstock (DEF STAN 

91-91 fuel specification).7 The Shell SPK was produced via the Shell Middle Distillate 

Synthesis (SMDS) process.8 The SMDS process produces long-chain paraffins from 

syngas in multi-tubular fixed bed reactors, followed by hydrocracking, isomerization and 

fractionation. The Shell SPK fuel is a very narrow-cut kerosene compared to a typical 

JP-8. 

Various physical and chemical properties of the alternative fuels and 50% by vol. blends 

were evaluated and compared to a specification JP-8. The fuels were sampled from the 

aircraft wing tank before and after the test series. Selected fuel specification properties 

for the post-test samples are shown in Table 1. In general, all SPKs evaluated had zero to 

very low aromatic content, negligible sulfur, lower density and higher hydrogen content 

compared to conventional JP-8. 

Gas chromatograms of JP-8 and the neat FT fuels with the n-paraffin peaks identified are 

shown in Figure 2. As shown in Figure 2 and Table 1, the Shell and Sasol fuels are much

narrower than conventional JP-8. Results of the hydrocarbon type analyses, performed 

using ASTM D6379 and D2425, are shown in Tables 2 and 3 and a comparison of the nparaffin content of the fuels is shown in Table 4. As noted previously, the alternative 

fuels are primarily comprised of normal and branched paraffins with low or negligible 

aromatic content. Based on knowledge of the processing techniques employed for the 

FT-derived fuels, it was expected that these fuels would be solely comprised of paraffinic 

compounds and free of aromatics. It appears that aromatic compounds found in the Sasol 

FT fuel was produced during the upgrading steps of the FT products. Improved control 

of the fuel upgrading process parameters will likely eliminate the production of aromatic 

compounds in these fuels if deemed necessary. As shown in Table 1, properties of FT/JP8 blends exhibit a mostly linear dependence with volume percent for all properties except 

the freeze point for the Shell FT. This non-ideal behavior for the freeze point has been 

observed with the Shell FT fuel in previous studies.8
APPENDIX G

167

Table 1. ASTM Specification Tests of Fuels Evaluated

Figure 2. Gas Chromatograms of Alternative Fuels

TEST JP-8 FT Shell (FT1) FT1 Blend FT Sasol (FT2) FT2 Blend

Sulfur (ppm) 1148 19 699 22 658

Aromatics (%vol) 18.6 0 8 0.6 9.1

Distillation

IBP (deg C) 158 157 156 160 158

10% 176 162 166 167 170

20% 184 164 170 170 175

50% 207 170 183 180 190

90% 248 186 232 208 233

EP 273 206 264 231 263

Residue (%vol) 0.8 0.9 1 1 0.8

Loss (%vol) 0.8 0.9 1 0.9 0.9

Flash Point deg C 46 41 43 42 46

Specific Gravity 0.82 0.74 0.78 0.76 0.79

Freezing Point deg C -50 -54 -60 <-80 -60

Viscosity 4.7 2.6 3.3 3.6 4.1

Cetane Index 41 58 46 51 45

Hydrogen Content (%mass) 13.6 15.5 14.5 15.1 14.3

Naphtalenes (%vol) 1.6 0 0.8 0 0.8

Heat of combustion (MJ/kg) 43.3 44.4 43.8 44.1 43.8

Olefins (%vol) 0.9 0 0.6 3.8 3.3

Fuel H/C ratio 1.88 2.19 2.02 2.12 1.99
APPENDIX G

168

Table 2. Aromatic Species Analysis by ASTM D6379 for Alternative Fuels

Aromatics (vol.%) JP-8 Shell FT Sasol FT

Mono-aromatics 17.6 <0.2 0.4

Di-aromatics 1.1 <0.1 <0.1

Total Aromatics 18.7 <0.2 0.4

Total Saturates 81.3 >99.8 99.6

The Shell FT fuel showed a mild degree of branching and was comprised of a much 

higher n-paraffin concentration than found in typical petroleum-derived jet fuels. High 

concentrations of long n-paraffins can result in poor low-temperature properties; 

however, the narrow distillation range with relative low carbon numbers (< C13) produces 

a fuel with a sufficient freeze point.8 On the contrary, the Sasol fuel had no detectable nparaffins with a sufficiently high degree of branching (e.g., tri- and tetramethylparaffins). The absence of n-paraffins results in an extremely low freeze point for 

the Sasol SPK. 

Table 3. Hydrocarbon Type Analysis by ASTM D2425 for Alternative Fuels

Hydrocarbon Type (vol.%) JP-8 Shell FT Sasol FT

Paraffins (normal + iso) 50 > 99 88

Cycloparaffins 31 <1 12*

Alkylbenzenes 12 <0.4 0.4

Indans and Tetralins 5 <0.4 <0.4

Indenes and CnH2n-10 0.6 <0.4 <0.4

Naphthalene <0.4 <0.4 <0.4

Naphthalenes 1 <0.4 <0.4

Acenaphthenes <0.4 <0.4 <0.4

Acenaphthylenes <0.4 <0.4 <0.4

Tricyclic Aromatics <0.4 <0.4 <0.4

Total 100 100 100

*D2425 may over predict cycloparaffins for highly branched SPKs 

The USAF approved the use of blends of SPK produced via FT-synthesis with 

conventional JP-8 provided that the required SPK and final blend properties are satisfied 

as detailed in MIL-DTL-83133F. In addition, ASTM also recently approved the use of 

FT-derived SPK in commercial Jet A and Jet A-1 as detailed in ASTM D7566-09. Both 

specifications allow a maximum of 50% by volume of SPK to be blended with 

conventional jet fuel. Selected properties for both the neat SPKs and the resulting fuel 

blend for each specification are shown in Table 5.
APPENDIX G

169

Table 4. Weight Percent of n-Paraffins for Alternative Fuels

n-Paraffins (wt.%) Carbon No. JP-8 Shell FT Sasol FT

n-Heptane C7 0.10 0.012 <0.001

n-Octane C8 0.34 1.63 <0.01

n-Nonane C9 1.21 22.4 <0.05

n-Decane C10 3.48 25.1 <0.03

n-Undecane C11 4.24 3.78 <0.02

n-Dodecane C12 3.71 0.29 <0.01

n-Tridecane C13 2.84 0.003 <0.01

n-Tetradecane C14 1.79 0.001 <0.01

n-Pentadecane C15 0.87 <0.001 <0.005

n-Hexadecane C16 0.27 <0.001 <0.003

n-Heptadecane C17 0.089 <0.001 <0.001

n-Octadecane C18 0.024 <0.001 <0.001

n-Nonadecane C19 0.008 <0.001 <0.001

Total n-Paraffins 19.0 53.3 <0.2

C7-C9 1.7 24.1 <0.06

C10-C13 14.3 29.2 <0.1

C14-C16 2.9 <0.003 <0.02

C17-C19 0.12 <0.003 <0.003

Table 5. Comparison of Selected Neat SPK and Blend Properties in US Military and 

Commercial Fuel Specifications

MIL-DTL-83133F ASTM D7566-09

Min Max Min Max

Requirements for Neat SPK

Aromatic (vol %) ― 1.0 ― 0.5

Density @ 15°C (kg/L) 0.751 0.840 0.730 0.770

Flash Point (°C) 38 68 38 ―

Freezing Point (°C) ― -47 ― -40

Cycloparaffin (mass %) ― ― ― 15

Distillation Temp (°C)

10% recovered 157 205 ― 205

50% recovered 168 229 ― Report

90% recovered 183 262 ― Report

Final ― 300 ― 300

T90-T10 (°C) ― ― 22 ―

Requirements for Petroleum and SPK Blend

Aromatic 8.0 25.0 8.0 ―

T50-T10 (°C) 15 ― 15 ―

T90-T10 (°C) 40 ― 40 ―
APPENDIX G

170

The general properties for the neat SPKs are similar for both specifications as each limit 

the maximum aromatic content while ensuring a minimum volatility range. The major 

difference between the SPK specifications is the allowable fuel density range, where the 

military minimum limit is 0.751 kg/L while the commercial is 0.730 kg/L. It should be 

noted that the Shell FT fuel did not satisfy the minimum military SPK density limit and 

barely satisfied the minimum volatility distribution. These properties will need to be 

addressed in subsequent formulations to meet the required fuel specifications. Both 

blend specifications require a minimum aromatic content of 8.0% by volume. This limit 

is specified to ensure that required "Fit-for-Purpose" (FFP) properties are maintained for 

the blends. Research is on-going to better define this lower limit. 

Engine Emissions

CFM56 Particle Number Emission Index 

JP-8 Fuel

The average particle number emission indices (EIn) (number of particles per kg-fuel) for 

each engine burning JP-8 for the 1 m sampling location are shown in Figure 3. EIn values 

(uncorrected for line losses) ranged between 3.0e14 – 1.1e15 particles/kg-fuel (95% 

confidence level). The EIn for both engines are observed to follow the same trends as a 

function of engine power setting, with statistically significant higher values for the left 

engine at 40 and 60% power. EIn data for emissions collected at 30 m are shown in 

Figure 4. As observed, the trends as a function of power setting are significantly 

different than for the 1 m sampling as the EIn are relatively constant at engine powers 

above 7%, while for the 1 m measurements EIn increased as a function of power for 

engine power above 45%. 

Figure 3. Particle number EI (not corrected for line losses) measured at 1 m from engine 

exit plane for CFM56 engines operated with JP-8 

0.0E+00

2.0E+14

4.0E+14

6.0E+14

8.0E+14

1.0E+15

1.2E+15

0% 20% 40% 60% 80% 100%

EIn (#/kg-fuel)

Engine Power

1m Left Engine

1m Right Engine
APPENDIX G

171

Although the actual particle number was lower at the 30 m location because of the natural 

sample dilution, the EIn were 5-15X higher than at 1 m due to the transformation of 

volatile compounds (i.e., hydrocarbons and sulfur species) into particles as the plume 

cooled with surrounding air. This difference in EIn between PM at 1 m and 30 m was 

significantly higher at low-engine power because of the higher concentration of volatile 

species. 

Figure 4. Particle number EI (not corrected for line losses) measured at 30 m from 

engine exit plane for CFM56 engines operated with JP-8

FT Fuels

EIn data at the 1 m probe for the engine burning the Sasol (FT2), Shell (FT1) and baseline 

JP-8 fuels are shown in Figure 5. Significantly lower particulate emissions are observed 

with the FT fuels compared to JP-8. Nearly two orders of magnitude lower EIn were 

observed at 4-45% engine power for both fuels. Smaller relative differences were 

observed at higher power. These results are consistent with previous measurements on 

T63, T701C and research combustors operated on neat FT fuels.9-11 Lower EIn are 

observed for most cases with the Shell FT compared to the Sasol FT, however, the 

differences are significantly lower between the FT fuels than between JP-8 and the FT 

fuels. Similar to test results on JP-8, EIn measurements at 30 m relative to 1 m were 

significantly higher (up to 80X) at low engine power. This is noteworthy considering the 

FT fuels were free of sulfur compounds, which are considered a major contributor to 

volatile PM. This suggests that volatile hydrocarbons may have as much or higher 

contribution to volatile PM formation as sulfur species. Further research in this area is 

warranted. 

Average EIn data for all engine settings for the three neat fuels as a function of fuel end 

point (EP) are shown in Figure 6. The fuel EP is the defined as the temperature at which 

all distilled fuel is recovered (see Table 1). No clear trend of EIn at each power setting as 

0.0E+00

3.0E+15

6.0E+15

9.0E+15

1.2E+16

1.5E+16

1.8E+16

0% 20% 40% 60% 80% 100%

EIn (#/kg-fuel)

Engine Power

30m Left Engine

30m Right Engine
APPENDIX G

172

a function of fuel EP is observed. However, it is clear that the higher fuel EP (JP-8) 

shows a more condensed range of EIn than the two FT fuels, which show a wider range of 

EIn values. This is a limited set of data; therefore, additional research with other nonaromatic alternative jet fuels with different EP is warranted to verify the impact and 

trends of fuel EP on engine EIn and soot production propensity.

Figure 5. Particle number EI (not corrected for line losses) measured at 1 m from engine 

exit plane for CFM56 engines as a function of engine power and fuel type

Figure 6. Particle number EI (not corrected for line losses) measured at 1 m from engine 

exit plane for CFM56 engines as a function of engine power and fuel end point

1.00E+11

1.00E+12

1.00E+13

1.00E+14

1.00E+15

1.00E+16

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

EIn (#/kg-fuel)

Engine Setting

JP-8 R (27 Jan - 48 F)

FT1 (28 Jan - 56 F)

FT2 (30 Jan - 60 F)

1.00E+12

1.00E+13

1.00E+14

1.00E+15

1.00E+16

200 220 240 260 280

EIn (#/kg-fuel)

Fuel End Point (Deg C)

4% 7% 30%

45% 65% 85%

FT Shell

FT Sasol

JP-8
APPENDIX G

173

Particle size distribution data (acquired with the SMPS) show single mode lognormal 

distribution trends for all fuels and conditions considered when sampling at the 1 m probe 

position. Shown in Figure 7, are the size distribution curves for the 65% engine setting 

for JP-8 operation at both 1 m and 30 m locations. Dual mode distributions are evident in

the 30 m samples with the original 1 m peak, at approximately 34 nm, and a new 

nucleation peak, at approximately 13 nm. The particles formed due to nucleation 

chemistry in the exhaust plume result in the significantly higher total EIn as discussed 

previously. The average particle diameter for the 1 m data for each fuel as a function of 

engine setting are displayed in Figure 8. Larger mean particle diameters are observed for 

the neat FT fuels at the 4 and 7% settings, while smaller particles were produced with the 

FT fuels at the higher power settings. No clear trend was observed for engine conditions 

between 30-65%. These results disagree with previous research, which has shown 

consistently smaller particles for all engine powers with FT fuels relative to JP-8.9-11

Sampling differences (e.g. heated vs. unheated sampling lines) may explain the 

discrepancies of these observations.

Figure 7. Particle size distribution sampling at 1 m and 30 m

Engine tests conducted at different ambient temperatures (e.g. 30°F morning 60°F 

afternoon) show significantly higher EIn at lower ambient temperatures. This behavior 

was consistent with all fuels tested and was mostly prevalent at lower engine power. 

Poorer fuel vaporization and/or condensation of volatile species may explain the higher 

concentration of particles. Average CFM56 engine smoke numbers for settings of 85% 

and 100% power for the three neat fuels are shown in Figure 9. Smoke numbers at lower 

1.00E+12

1.00E+13

1.00E+14

1.00E+15

1.00E+16

1 10 100 1000

dN/dlog Dp EI

Particle Diameter (nm)

CFM56 @ 65% JP-8 30m L JP-8 30m R

JP-8 1m L JP-8 1m R
APPENDIX G 

174 

engine settings with the FT fuels were below the measurable detection limit and not 

reported here. Average reductions of ~75% are observed at 85% and ~ 60% for 100% 

power for the FT fuels compared to JP-8. Consistent with EIn data, the Shell FT 

produced slightly lower SN than the Sasol FT. 

Figure 8. Average mean particle diameter for JP-8 and alternative fuels 

Figure 9. CFM56 engine smoke numbers at 85% and 100% power for neat fuels 

0

5

10

15

20

25

30

35

40

45

50

0% 20% 40% 60% 80% 100% 120%

Average Mean ParticleDiameter(nm)

Engine Power

JP‐8 R

50% FT Sasol

50% FT Shell

FT Sasol

FT Shell

0

2

4

6

8

10

12

14

16

JP‐8 FT1 (Shell) FT2 (Sasol)

Smoke Number

85% 100%
APPENDIX G

175

Elemental and organic carbon (EC and OC) mass were estimated by performing off-line 

programmed temperature oxidation of collected soot samples using a LECO Multiphase 

Carbon Analyzer. Elemental carbon mass EI (oxidizes at temperatures > 350°C) for the 

85% engine setting for the engine operating with the neat fuels and blends are shown in 

Figure 10. As shown, the EC mass EI was significantly lower (up to 70%) with the FT 

fuels (both neat and blended). Negligible differences in EC mass EI were observed 

between the FT fuels. The total mass EI and relative volatile fraction for the fuels are 

shown in Table 6. Significantly lower total (~65%) and organic (volatile) carbon mass 

were generated with FT fuels. The lower volatile fraction of JP-8 relative to the FT and 

FT blends is mainly due to the significantly higher EC production with JP-8. It was 

observed that at 100% power, OC/EC fractions of the fuels are similar to the 85% power; 

however, the difference in total carbon between JP-8 and the FT fuels is substantially 

lower (only 20% compared to 65% lower at 85% power).

Figure 10. Elemental Carbon Emission Index for CFM56 Engine at 85% Power

Table 6. PM Mass via Carbon Burn-off Methods – CFM56 at 85% Power

Gaseous Emissions

The average impact of the FT fuels on CO and NOx EI are shown in Figures 11 and 12. 

The error bars represent one standard deviation of an average of seven measurements for 

0

20

40

60

80

100

120

85%85%85%85%85%85%85%85%

FT-1 Neat FT-2 Neat FT-1 Blend FT-2 Blend JP-8 JP-8 JP-8 JP-8

EC EI (mg/kg-fuel) 

Engine Setting/Fuel

Fuel Total PM Mass (mg/kg-fuel) EC Mass (mg/kg-fuel) Volatile Fraction

JP-8 152 98 35%

FT Blends 60 35 41%

FT Neat 52 29 44%
APPENDIX G

176

the FT fuels and 20 for JP-8. It is observed that the CO EI for all engine conditions were 

very similar between the FT fuels and JP-8. Slightly lower NOx EI were observed with 

the Shell FT at the 100% power condition, while minimum differences are shown 

between fuels for most conditions. As anticipated, lower sulfur emissions (not shown) 

were produced with the FT fuels relative to JP-8 which is attributed directly to the total 

sulfur content in the fuels.

Figure 11. CO EI for CFM 56 Engine operated with JP-8 and two FT fuels

Figure 11. NOx EI for CFM 56 Engine operated with JP-8 and two FT fuels

0

20

40

60

80

100

120

4% 7% 30% 45% 65% 85% 100%

CO EI (g/kg-fuel)

Engine Setting

JP-8

Shell FT

Sasol FT

0

5

10

15

20

25

4% 7% 30% 45% 65% 85% 100%

NOx EI (g/kg-fuel)

Engine Setting

JP-8

Shell FT

Sasol FT
APPENDIX G

177

Summary

The gaseous and particulate matter emissions from a CFM56 engine operating with two 

FT fuels and JP-8 were evaluated. Detailed chemical analysis of the alternative fuels 

show that they are mainly composed of paraffins with negligible or no aromatic or sulfur 

species. Emissions data demonstrate that the two FT fuels produced significantly lower 

soot emissions, which is consistent with results from previous testing on research 

combustors and turbine engines. Negligible differences in gaseous emissions between 

the FT and JP-8 fuels were observed. Significant volatile particle nucleation occurred in 

the plume with both FT fuels and JP-8, which highlights the importance of the organic 

fraction on volatile particle emissions. In general, the impacts of these fuels on PM 

emissions agree with previous measurements on vastly different engine types, which 

increases confidence that similar results/trends will be observed in other turbine engines.

Acknowledgements

The authors gratefully acknowledge the assistance of Joe Mantz from UDRI and Tom 

Greene of Taitech Inc. during the engine tests. Appreciation is also extended to Linda 

Shafer, Rhonda Cook, and David Brooks of UDRI for the analysis of fuel and soot 

samples. The efforts of UDRI were supported by the USAF under contract F33615-03-2-

2347.

References

1. Intergovernmental Panel on Climate Change Special Report, "Summary for 

Policymakers – Aviation and the Global Atmosphere," 1999.

2. MIL-DTL-83133F, "Detailed Specification, Turbine Fuel, Aviation, Kerosene Type, 

JP-8 (NATO F-34), NATO F-35, and JP-8+100 (NATO F-37)," released 11 April 

2008.

3. ASTM D7566-09, "Standard Specification for Aviation Turbine Fuel Containing 

Synthesized Hydrocarbons," approved 1 Sept 2009.

4. SAE 1970, "Aircraft Gas Turbine Exhaust Smoke Measurement," SAE Aerospace 

Recommended Practice ARP 1179, SAE, Warrendale, PA USA, 1970.

5. SAE 1971, "Procedure for the Continuous Sampling and Measurement of Gaseous 

Emissions from Aircraft Turbine Engines," SAE Aerospace Recommended Practice 

ARP 1256, SAE, Warrendale, PA USA, 1971.

6. Moses, C.A., Stavinoha, L.L. and P. Roets, "Qualification of SASOL Semi-Synthetic 

Jet A-1 as Commercial Jet Fuel," Report No. SwRI 8531, Southwest Research 

Institute, San Antonio, TX, 1997.

7. Defense Standard 91-91, Turbine Fuel, Aviation Kerosene Type, Jet A-1 NATO 

Code: F-35

Joint Service Designation: AVTUR, released 8 April 2008.

8. Bauldreay, J.M., Heins, R.J. and J. Smith, "Synthetic Jet Fuels and Their Role in the 

Future," Proceedings of the 8th International Conference on Stability and Handling of 

Liquid Fuels, Steamboat Springs, CO, 2003.

9. Corporan, E., DeWitt, M., Klingshirn, C., Striebich, R, S., Cheng, M.D., "Emissions 

Characteristics of Military Helicopter Engines Fueled with JP-8 and a FischerTropsch Fuel," Accepted in Journal of Propulsion and Power, 2010. 
APPENDIX G

178

10. Kahandawala, M., DeWitt M., Corporan, E., Sidhu, S., "Ignition and Emission 

Characteristics of Surrogate and Practical Jet Fuels", Energy & Fuels, 2008, 22 (6), 

3673-3679 

11. Corporan, E., Edwards, T., Shafer, L., DeWitt, M.J., Klingshirn, C., Zabarnick, S., 

West, Z., Striebich, R., Graham, J., Klein, J., "Chemical, Thermal Stability, Seal 

Swell and Emissions Characteristics of Jet Fuels from Alternative Sources,"

Proceeding of the 11th International Conference on Stability and Handling of Liquid 

Fuels, Prague, Czech Republic, 2009.
APPENDIX H

179

APPENDIX H: Concentrations and Physical Properties of Exhaust Particles from 

Aircraft Engines Burning Standard and Synthetic Fuels: AAFEX Results

Luke D. Ziemba, Andreas J. Beyersdorf, Charles Hudgins, David Liscinsky, K. Lee 

Thornhill, Edward L. Winstead, and Bruce E. Anderson

NASA Langley Research Center

Hampton VA 23662

1.0 Summary

The NASA Alternative Aviation Fuel Experiment (AAFEX) was conducted in January 

2009 at the Dryden Aircraft Operations Facility (DAOF) in Palmdale, California to assess 

the impact of alternative jet fuels on aircraft engine and auxiliary power unit (APU) 

emissions. For the engines, five different fuels were tested under variable atmospheric 

conditions. The fuels included two synthetic kerosenes manufactured from natural gas 

(FT-1) and coal (FT-2) feedstocks using the Fischer-Tropsch process. This report 

examines the particle emissions from the NASA DC-8’s two inboard, CFM-56 engines 

and establishes how exhaust particle number, size, mass and composition change as a 

function of fuel composition, plume age and ambient temperature. We also contrast 

particle emission parameters measured in exhaust from the APU as it burned pure FT-2 

and standard JP-8 fuel. For the aircraft and APU, both black carbon and volatile aerosol 

emissions were substantially reduced from synthetic fuels compared to standard jet fuel.

 2.0 Background

Alternative sources of aviation fuel are being investigated as a means of increasing 

domestic production, increasing fuel security, and stabilizing prices. Research efforts 

have primarily focused on developing "drop-in" replacement fuels that meet ICAO 

(International Civilian Aviation Organization) specifications and can be burned in aircraft 

with little or no modification to the propulsion or fuel storage and delivery systems. 

Although several viable fuels have been produced, very few studies have been conducted 

to evaluate the effects of the fuels on gas turbine engine performance and emissions. The 

few studies that have been conducted used military engines and evaluated fuel blends 

(Corporan et al., 2007; Cheng et al., 2009). Additionally, absolute emissions factors from 

engine manufacturer-sponsored testing are not publically available (Timko et al., 2010). 

Thus, additional testing is required to fully characterize alternative-fuel emissions from 

aircraft in various environmental conditions for incorporation into future air quality and 

climate models. 

AAFEX was designed to help fill this information gap. A multi-agency, NASAsponsored project, AAFEX was conducted at the DAOF in January 2009 and used the 

agency’s DC-8, which is equipped with four CFM-56-2C engines, to evaluate alternative 

fuel impacts on aircraft operation and emissions. AAFEX also sought to examine 

dynamic plume chemistry and volatile aerosol formation as a function of fuel 

composition and ambient conditions. A total of five fuels were tested: standard JP-8, two 

synthetic fuels produced from natural gas (FT-1) and coal (FT-2) using the FischerTropsch reformulation process, and two blends formed by mixing equal volumes the FT 

fuels and JP-8. The pure Fischer Tropsch (FT) fuels were essentially free of aromatic 
APPENDIX H

180

hydrocarbons and sulfur impurities (Cheng et al., 2009) and were thus expected to 

produce much lower soot and sulfate aerosol emissions. The overall test involved 

characterizing the trace-gas and aerosol components in exhaust samples collected at three 

distances (1 m, 30 m, and 145 m) behind the NASA DC-8 aircraft as its CFM-56 engines 

burned each of the fuels and operated at power levels ranging from ground idle to full 

takeoff thrust. For each pure fuel (JP-8, FT-1 and FT-2), duplicate tests were conducted 

in early morning and afternoon to observe changes in emission characteristics as a 

function of ambient temperature. The tests also included examining JP-8 and FT-2 

emissions from the aircraft’s Auxiliary Power Unit (APU) operating under varying loads. 

In all, 13 engine and 3 APU tests were conducted, encompassing a total of 34 and 3 hours 

of engine and APU run-time, respectively.

The NASA Langley Research Center Aerosol Research Group (LARGE) participated in 

AAFEX by providing both project leadership and by conducting particle characterization 

studies. Our group operated an extensive suite of instruments in the NASA truck and in a 

community sampling trailer. This report describes the LARGE experiment and examines 

the characteristics of particulate matter (PM) emissions from the DC-8 as a function of 

fuel type and ambient conditions. A detailed description of the LARGE instrument suite 

and sampling system is included, and emission indices and calculated particle parameters 

are discussed. Results from a control test comparing JP-8 emissions from the DC-8’s two 

inboard engines are reported and are discussed with respect to results from the previous 

APEX-1 (Aircraft Particle Emissions Experiment) campaign. Effects of fuel type on the 

non-volatile particle emissions are examined. Lastly, the formation and growth of 

volatile particles in engine exhaust as a function of fuel type and ambient temperature is 

discussed and APU emission tests results are presented.

3.0 Experimental Methods

3.1 Testing Protocol

DC-8 emissions testing was performed on the two inboard engines. A schematic of the 

test setup is shown in Figure 1. The left inboard engine (#2) was supplied JP-8 fuel and 

was used as a standard for direct comparison with emissions results from alternative fuels 

and will be referred to as the "control engine." The right inboard engine (#3) was 

supplied alternative fuels and will be termed the "test engine." The rationale for this 

approach was to use emission data from the control engine for evaluating fuel-related 
APPENDIX H

181

Figure 1. Diagram of DC-8 testing setup. Samples were taken from 1-, 30-, and 145-m 

probes mounted behind both the control engine (left, inboard), which burned only JP-8 

fuel, and the test engine (right, inboard), which burned JP-8 and alternative fuels. Probe 

distances are not drawn to scale.

changes in the test engine emissions, as well as to collect a large data set for evaluating 

the role of ambient conditions on both gas- and particle-phase emissions. The "test 

engine" also was operated with JP-8 fuel in order to determine emission differences 

between the two engines. Test conditions for each sampling test are presented in Table 1. 

Included are the test objectives, fuel-type for each engine, engine start and stop times, 

and the engine power settings at which data were taken.

Samples were transported from each of the probe tips shown in Figure 1 to analytic 

instrumentation designed specifically for characterization of aerosol physical and 

chemical properties. Details regarding the sample distribution system are found in the 

AAFEX overview document (Anderson et al., 2010). Briefly, a "community" sampling 

manifold was connected through valves to each of the 1- and 30-m inlet probes and was 

used to deliver samples to each of the participating groups. A separate line was installed 

to deliver samples to the test engine 30-m inlet so that the instrumentation could make 

continuous PM measurements to compare with similar measurements being logged in a 

ruggedized enclosure (known as the "death box") mounted directly behind the inlet in 

order to assess sampling line particle loss (see Appendix P for more details on line loss 

experiments). 
APPENDIX H

182

Table 1. AAFEX Tests

Test 

No.

Test 

Date

Test 

Objective

Aircraft 

Engine

Engine 

Fuel

Engine 

Start1

Engine 

Shutdown1 Sampled Thrust Levels (%)

1 26-Jan Equipment 

Shakedown

control JP-8 14:01

15:00

4, 45

test JP-8 14:03 4, 7, 30, 45, 65, 85, 100

2 26-Jan

Samplingprobe 

Mapping

control JP-8 16:02

19:20

4, 7, 30, 45, 65, 85

test JP-8 16:04 4, 7, 30, 45, 65, 85, 100

3 27-Jan JP-8, warm 

conditions

control JP-8 12:38

15:46

4, 7, 30, 45, 65, 85

test JP-8 12:43 4, 7, 30, 45, 65, 85, 100

4 28-Jan JP-8, cold 

conditions

control JP-8 5:59

9:28

4, 7, 30, 45, 65, 85

test JP-8 6:03 4, 7, 30, 45, 65, 85, 100

5 28-Jan FT-1, warm 

conditions

control JP-8 12:35

15:54

4, 7, 30, 45, 65, 85

test FT-1 12:39 4, 7, 15, 30, 45, 65, 85, 100

6 29-Jan FT-1, cold 

conditions

control JP-8 5:41

8:36

4, 7, 30, 45, 65, 85

test FT-1 5:45 4, 7, 15, 30, 45, 65, 85, 100

7 29-Jan JP-8 Fuel APU JP-8 12:34 13:57 EGT = 350, 610 °C

8 30-Jan FT-1/JP-8 

Blend

control JP-8 6:14

9:38

4, 7, 30, 45, 65, 85

test Blend-1 6:19 4, 7, 15, 30, 45, 65, 85, 100

9 30-Jan FT-2, warm 

conditions

control JP-8 10:48

13:41

4, 7, 30, 45, 65, 85

test FT-2 10:51 4, 7, 15, 30, 45, 65, 85, 100

10 31-Jan FT-2, cold 

conditions

control JP-8 5:57

7:03

4, 7, 30, 45, 65, 85

test FT-2 5:42 4, 7, 15, 30, 45, 65, 85, 100

11 31-Jan FT-2/JP-8 

Blend

control JP-8 8:28

10:59

4, 7, 30, 45, 65, 85

test Blend-2 8:31 4, 7, 15, 30, 45, 65, 85, 100

12 31-Jan JP-8, warm 

conditions

control JP-8 12:49

15:18

4, 7, 30, 45, 65, 85

test JP-8 12:52 4, 7, 15, 30, 45, 65, 85, 100

13 2-Feb JP-8, cold 

conditions

control JP-8 7:12

8:38

4, 7, 30, 45, 65, 85

test JP-8 7:14 4, 7, 15, 30, 45, 65, 85, 100

14 2-Feb Line-loss 

testing

control JP-8 9:37

12:07

4, 7, 30, 45, 65, 85

test JP-8 9:40 4, 7, 15, 30, 45, 65, 85, 100

15 2-Feb APU, JP-8 APU JP-8 14:12 15:23 EGT = 345, 365, 475, 550, 555, 

610 °C 

16 2-Feb APU, FT2 APU FT-2 15:40 16:37 EGT = 360, 475, 550, 555, 620 °C 

1

Local, Pacific Standard Time

For the 145-m probe, the velocity of the engine exhaust plume was insufficient to keep 

the sampling probe in the plume as cross winds would shift the plume away from the 

probe. In order to have sufficient sampling times, sampling was performed from a lagged 

aerosol grab (LAG) chamber that captured air samples at two to three minute intervals for 

subsequent sampling. The LAG chamber was installed directly behind the test engine at 

the 30-m probe. Three-way solenoid valves isolated the LAG chamber from the 

continuous flow line during instrument sampling. When a plume was detected from the 

145-m probe (determined by a spike in particle number concentration), the chamber was 
APPENDIX H

183

flushed with sample air and then isolated for analysis. When not in use, bypass flow 

maintained a constant flow through the LAG sampling system.

The initial test (1) was conducted to determine whether the sampling system was properly 

installed and to evaluate sample dilution and delivery procedures (Table 1). Data from 

this test were not finalized and hence are not presented in the sections below; all other 

Langley data were quality assured, finalized and submitted to the AAFEX project 

archive. Test 2 included sampling from multiple inlet probes on each of the 1-m rakes to 

map the distribution of emissions across the control- and test-engine exit planes to 

establish which of the six possible probes on the rakes were positioned in the core 

exhaust flow to provide the most representative particle emission factors. Engine tests 3 

through 6 and 8 through13 were performed to examine fuel and ambient temperature 

effects on emission parameters. Tests 7, 15, and 16 were performed to specifically 

address emissions from the APU. Test 14 focused on sampling issues, and the primary 

focus was on particle loss to the walls of the inlet tubing. Results from this test are 

discussed in Appendix P of this document.

Figure 2. Example experiment matrix for the AAFEX emission characterization tests

A typical sampling procedure for AAFEX emissions testing is provided below and is 

presented in Figure 2. At engine start, the community sampling system was typically 

connected (via a valving system that is described in the AAFEX overview report) to the 

control-engine 30-m inlet probe for characterization until the engine was spun-up and had 

stabilized at ground idle (4%). The sampling system was then connected to the testengine 30-m inlet to characterize the emissions through its start-up sequence. Once both 

engines were stable at 4% power, the valving box for the community manifold (located in 

the Missouri University for Science and Technology trailer) was again set to draw air 

from the control engine, 30-m probe and the beginning of the initial test point was 

recorded. After approximately three minutes, the valves were set to draw sample from 

the control-engine, 1-m inlet probe and, after emissions had stabilized (based on CO2

mixing ratio), three minutes of data collection ensued. After this pattern was completed 

for the test engine at 1 m and 30 m, the next power setting was requested and the 

sampling process repeated. Data were typically acquired for both engines at 4, 7, 30, 45, 
APPENDIX H

184

65, and 85% of maximum revolutions per minute (RPM) and additionally at 15 and 100% 

thrust for the test engine. To obtain better sampling statistics for the test-engine 

emissions and after a brief intermission at 7% thrust, the power sequence was repeated in 

reverse order, starting at 100% thrust and stepping downward through the power points 

until ground idle was reached.

3.2 Instrumentation

A robust suite of instrumentation was deployed for AAFEX to characterize aerosol 

chemical and physical properties. The specific parameters measured by these instruments 

along with their precisions and accuracies are listed in Table 2; brief descriptions are 

provided below. For completeness, the full instrument suite is introduced, but only a 

subset of measurements are analyzed and discussed in this report. AAFEX provided a 

helpful test setting for the development of instrumentation not considered in this report. 

Figure 3 shows a diagram of the Langley Research Center (LaRC) aerosol instrument 

suite that was used to characterize PM in samples drawn from the community-sampling 

manifold. Figure 4 shows a diagram of the LaRC aerosol instruments that sampled from 

the test engine 30-m inlet probe. Figure 5 shows a plumbing diagram for the LaRC 

aerosol instruments installed in the 145-m trailer.

Table 2. In Situ Aerosol Instrumentation

Measured Parameter Instrument Measurement Range Response

(seconds) Precision

Nonvolatile CN Particle 

Number TSI 3022A Dp > 0.01 μm 1 20%

Total CN Particle Number TSI 3775 Dp > 0.004 μm 1 20%

Aerosol Size Distribution DMA w/TSI 

3776 Dp: 0.009 - 0.310 μm 60 5% size, 25% conc.

Nonvolatile Aerosol Size 

Distribution

DMA w/TSI 

3025 Dp: 0.009 - 0.310 μm 60 5% size, 25% conc.

Aerosol Size Distribution TSI EEPS Dp: 0.006 – 0.295 μm 1 20%

Cloud Condensation Nuclei CCN Dp: 0.02 – 1.0 μm 1 10%

Aerosol Size Distribution UHSAS Dp: 0.06 – 1 μm 1 5% size, 20% 

conc.

Aerosol Size Distribution MetOne OPC Dp: 0.3 – 10 μm 1 20% size, 25% 

conc.

Soluble Aerosols PILS w/IC > 10 ng m-3 180 20%

Soluble Organic Aerosols PILS w/TOC 0.03 ppb (liquid) 4 20%

Black Carbon Mass MAAP >100 ng m-3 1 12%

Black Carbon Mass SP2 > 1 μg m-3 1 20%

Black Carbon Mass PASS-3 40 ng m-3 1 20%

NDIR CO2 mixing ratio LI-COR 0 – 10000 ppm 1 0.5%

Total Particle-Bound PAH PAS 2000 ~ 0.3 – 1 g m-3 10 20%

Particulate SO4

2- Thermo SPA > 0.50 μg m-3 sulfate 1 10%

Total Aerosol Length TSI EAD 0.01 – 2500 mm cm-3 1 10%
APPENDIX H

185

Instruments highlighted in bold are the focus of this report. An explanation of issues 

associated with unhighlighted instrumentation is given in Section 3.6. 

Figure 3. Plumbing diagram for instruments on the common aerosol inlet line at 1 m

Figure 4. Plumbing diagram for instruments on the aerosol inlet line at 30 m behind the 

test engine
APPENDIX H

186

Figure 5. Plumbing diagram for instruments on the aerosol inlet line at 145 m behind the 

test engine.

3.2.1. Particle Number Concentration

Total aerosol concentrations were monitored with a TSI 3775 CPC. At low 

concentrations (0 to 5×104

cm-3), an optical detector counts individual pulses produced as 

each particle passes through the sensing zone. For very high particle concentrations, 

5×104 to 1×107 cm-3, the model 3775 transitions from the single-count mode to a 

photometric mode where the total light scattered from the particles is used to determine 

concentration. This transition is particularly important because the exhaust samples often 

had particle number concentrations exceeding 1×106 cm-3, even after a ten-fold dilution. 

This CPC has a 50% cut size of approximately 4 nm and a response time of 5 seconds.

The fraction of particles with diameter greater than 7 nm that are volatile at temperatures 

below 3500C were monitored with a TSI 3022A CPC, which has a photometric, 

ensemble sampling mode that extends its dynamic range up to 1x107 cm-3. This CPC has 

a 50% cut size of approximately 7 nm and a response time of 5 seconds.

3.2.2. Particle Size Distribution

The scanning mobility particle sizer (SMPS) measures the size distribution of particles 

using an electrical mobility detection technique that couples a differential mobility 

analyzer (DMA) and condensation particle counter (CPC). The SMPS uses a bipolar 

charger (210Po) in the electrostatic classifier to give the particle population a known 
APPENDIX H

187

charge distribution. The particles are then classified according to their ability to traverse 

an electrical field as the voltage is monotonically increased. One SMPS consisting of a 

long electrostatic classifier column with a TSI model 3776 CPC detector measured 

particle size distributions from 0.003 to 0.310 μm mobility diameter. A second SMPS 

consisting of a long electrostatic classifier column with a TSI model 3025 CPC detector 

measured non-volatile particle size distributions for the same size range by heating the 

sample to 350°C prior to DMA classification. Both SMPSs were operated at 60-second 

resolution with a sheath:aerosol flow rate ratio of 10:1. 

The Engine Exhaust Particle Sizer (EEPS) is a fast-response, high-resolution instrument 

that measures size distribution and number concentration of engine exhaust particle 

emissions in the range from 0.006 to 0.560 μm at 1-sec time resolution. Particles enter 

the instrument through a 1-μm cyclone. The particles are given a known positive charge 

distribution using a corona charger. The charged particles enter the measurement region 

near the center of a high-voltage electrode column and are transported between two 

concentric columns surrounded by HEPA-filtered sheath air. A positive voltage is 

applied to the electrode with increasing voltage towards the bottom of the electrode. This 

creates an electric field that repels the positively charged particles outward according to 

their electrical mobility. The outer cylinder consists of a stack of detector electrode rings 

electrically insulated from each other and connected to highly sensitive electrometers. A 

particle with higher electrical mobility strikes an electrometer closer to the inlet where it 

transfers its charge and is detected. A particle with lower electrical mobility strikes an 

electrometer lower in the stack. This multiple detector arrangement allows for 

simultaneous concentration measurements of multiple particle sizes.

The DMT Ultra High Sensitivity Aerosol Spectrometer (UHSAS) is an optical-scattering, 

laser-based aerosol particle spectrometer system for sizing particles in the range from 

0.055 μm to 1.0 μm diameter with size binning of 100 channels. The size of the particle 

is determined by measuring the light scattering intensity and using Mie scattering theory 

to relate this intensity to the particle size. The design of the scattering optics and the high 

intensity of the illuminating laser permit the detection of particles at 1-second time 

resolution.

The MetOne Optical Particle Counter (OPC) is an optical-scattering, laser-based aerosol 

particle spectrometer system for sizing particles in the range from 0.3 μm to 10 μm 

diameter into 8 channels. Particle size is determined by measuring light-scattering 

intensity and using the Mie scattering theory to relate this intensity to the particle size by 

a similar method as that used for the UHSAS. Sampling has a fast response at 1-second 

resolution.

3.2.3. Cloud Condensation Nuclei 

The DMT CCN counter measures the concentration of particles that form cloud droplets 

at a specified temperature and water supersaturation, referred to as cloud condensation 

nuclei (CCN). The instrument design consists of a cylindrical, continuous-flow, thermalgradient diffusion chamber employing a novel technique of generating a supersaturation 

by establishing a constant, streamwise temperature gradient so that the difference in 
APPENDIX H

188

water vapor and thermal diffusivity yield a quasi-uniform centerline supersaturation. 

Ambient sample is introduced into the instrument, split into sheath and aerosol flows 

(typically with a sheath-to-aerosol flow ratio of 10:1). The sheath flow is filtered, 

humidified and heated, and surrounds the sample with particle-free air that constrains the 

particles to the centerline of the flow chamber within the CCN column. A positive 

temperature gradient is applied to the CCN column in the streamwise direction. Water 

vapor supersaturation is generated within the CCN column, where the particles grow by 

condensation. The supersaturation is varied between 0.1% and 2%. Particles are 

considered droplets when they are large enough for detection by an OPC at the exit of the 

CCN column. The OPC has been specially designed for the CCN and utilizes side 

scattering technology for the particle sizing. A diode laser is used as the light source with 

a wavelength of 660 nm. The particle sizing range is from 0.75 to 10 microns in 20 bins 

and sampling frequency is 1 second.

3.2.4. Aerosol Absorption and Black Carbon Concentration

A Multi-Angle Absorption Photometer (MAAP) measures black carbon (BC; here used 

interchangably with elemental carbon, EC) by determining the aerosol light absorption at 

670 nm from the simultaneous measurement of light passing through and scattered back 

from particle-loaded glass fiber material. Additional detectors placed at defined 

scattering angles enable the determination of the proportion of the decrease in transmitted 

light attributed to absorbance rather than scattering by the particle sample and filter 

media. The data inversion algorithm is based on a radiation transfer method and 

therefore takes into account multiple scattering from the deposited aerosol and between 

the aerosol layer and the filter matrix. The absorption by aerosols is empirically related 

to black carbon content. The uncertainty of the absorbance is ± 12% at 1-second 

resolution.

As an instrument calibration check, black carbon concentrations measured with the 

MAAP were compared to filter-based black carbon determined by an OC/EC aerosol 

analyzer (Sunset Laboratory Inc., Tigard, OR). A linear regression of the two methods 

(Figure 6) showed that the EIbc measured using the MAAP were typically greater by 

15%. This is likely the result of interference in the filter based measurement by organic 

carbon. Processing error in the OC/EC split point increases with high loadings of organic 

carbon (as observed in engine exhaust). 

The DMT Photoacoustic Soot Spectrometer (PASS-3) is a sensitive, high-resolution, fastresponse instrument for measuring the absorption coefficient of aerosol particles. It 

provides a real-time, in-situ measurement of black carbon. It uses three wavelengths 

(red, green, and blue) to enhance measurement capabilities. The PASS-3 instrument 

measures light absorption by aerosols using the photoacoustic method, quantifying the 

sound pressure produced in an acoustic resonator caused by light absorption. The lower 

detection limit for light absorption is 0.4 Mm-1

, which corresponds to an elemental 

carbon mass density of ~40 ng m-3 assuming efficiency for light absorption of 10 m2g-1.
APPENDIX H

189

Figure 6. Black carbon mass emission indices (EIbc, mg kg-1) found by the MAAP and 

filter analysis. Calculation of emission indices is discussed in detail below.

The DMT Single Particle Soot Photometer (SP2) is designed to measure the mass and 

mixing state of individual black carbon particles based on the laser-induced 

incandescence (LII) technique. Particles enter the sample cavity of the SP2 and pass 

through the beam of a diode-pumped Nd:YAG laser (1.06 μm wavelength) where they 

scatter or absorb light. Particles that contain light absorbing material, at the wavelength 

of the laser, are heated as they pass through the beam and reach a temperature at which 

they incandesce and emit light at a wavelength that is proportional to the incandescence 

temperature. Four optical detectors are used. One detector is optically filtered to pass 

only the 1064 nm radiation to measure the scattering signal from all particles. Two 

photomultiplier tube (PMT) detectors measure the incandescence signal in the visible 

region. These channels are optically filtered to pass broadband light nominally from 400 

to 800 nm and narrow band light nominally from 600 to 800 nm in wavelength. The ratio 

of the signals from these two detectors allows the color temperature of the incandescing 

particles to be calculated, providing assurance that the measured particles are elemental 

carbon. A fourth detector allows measurement of the leading edge of the scattering 

signal. This can be used to analyze the mixing state of the incandescing particle.

3.2.5. Total Particle-bound PAH

The Photoelectric Aerosol Sensor (PAS 2000) works on the principle of photo-ionization 

of particle-bound PAH. Using an Excimer lamp, the aerosol flow is exposed to UV 

radiation. The Excimer lamp offers a high intensity, narrow band source of UV radiation. 

The wavelength of the light is chosen such that only the PAH coated aerosols are ionized, 

while gas molecules and inorganic aerosols remain neutral. The particles that have 
APPENDIX H

190

surface-adsorbed PAH molecules emit electrons that are subsequently removed when an 

electric field is applied. The remaining positively charged particles are collected on a 

filter inside an electrometer where the charge is measured. The resulting electric current 

establishes a signal which is proportional to the concentration of total particle-bound 

PAH.

3.2.6. Aerosol Length

The TSI model 3070A Electrical Aerosol Detector (EAD) measures a unique aerosol 

parameter called total aerosol length. Reported in units of mm cm-3, aerosol length is the 

product of the particle number concentration and average geometric diameter. 

Theoretically, this aerosol length falls between number concentration and surface area. 

The operating principle of the EAD is based on diffusion charging of sampled particles, 

followed by detection of the aerosol using an electrometer.

3.2.7. Water-soluble Aerosol Chemical Composition

The Particle-Into-Liquid Sampler (PILS) collects airborne particles by impaction and 

concentration into a small stream of high purity water, producing a solution 

representative of the water-soluble aerosol composition. This is accomplished by mixing 

the sample flow with a smaller turbulent flow of steam. Rapid, adiabatic cooling of the 

warmer turbulent stream by the cooler sample flow gives a high supersaturation of water 

vapor. The aerosol particles grow into droplets large enough to be collected by an 

impactor. Two identical PILS samplers were deployed. With one PILS, the droplets are 

collected to produce a continuous liquid flow for online analysis of soluble organic 

carbon using the Total Organic Carbon (TOC) Analyzer as a detector. The Seivers TOC 

Analyzer utilizes a gas permeable membrane that selectively passes only the CO2

produced from the UV/persulfate oxidation of organics in the liquid sample stream. TOC 

sampling frequency has 4-second resolution. With the other PILS, the droplets are 

collected for each sampling period (nominally 180 seconds) in vials, which are later 

analyzed in the laboratory for selected anions, cations and water soluble organics by ion 

chromatography (IC).

The Model 5020i Sulfate Particulate Analyzer (SPA) combines a continuous sulfate 

(SO4

2-

) to sulfur dioxide (SO2) converter and a trace-level pulsed fluorescence SO2

analyzer to provide real-time, 1-second resolution, measurements of sulfate aerosol. The 

measurement is based on the conversion of sulfate particles to gas phase SO2 in a hightemperature converter module. The SO2 formed in the converter module is directed to an 

analyzer module where it is continuously measured using a pulsed fluorescence 

technique. The pulsed fluorescence measurement operates on the principle that SO2

molecules become excited by absorbing ultraviolet (UV) light at one wavelength and then 

emit UV light at a different wavelength when decaying back to a lower energy state. The 

SPA quantifies sulfate by comparing the signal produced when aerosol loaded sample air 

is drawn directly into the converter to a background signal that is produced when the 

sample stream is run through a high-efficiency particulate aerosol filter that removes the 

sulfate before conversion. The difference in signal between the filtered and unfiltered 
APPENDIX H

191

sample is attributed to sulfate particles in the unfiltered sample stream. By routinely 

switching between the filtered and unfiltered sample streams, the instrument readings can 

be continuously adjusted or corrected for changes in background signal that would be 

produced by SO2 or other interfering gases.

3.2.8. Carbon Dioxide

Carbon dioxide is measured using a LiCor differential, non-dispersive, infrared (NDIR) 

gas analyzer. The CO2 measurements are based on the difference in absorption of 

infrared (IR) radiation passing through two gas-sampling cells. The reference cell is used 

for nitrogen containing no CO2, and the sample cell is used for the sample of unknown 

CO2 concentration. Infrared radiation is transmitted through both cell paths, and the 

output of the analyzer is proportional to the difference in absorption between the two.

3.3 Calculated Parameters

Data acquired from the LaRC instruments were corrected for sampling pressure and 

dilution in order to calculate the secondary variables listed in Table 3. Values for aerosol 

mass were found by integrating volume-size distributions (calculated from measured 

number concentrations assuming spherical particles) provided by the EEPS or SMPS 

instruments over a specific size range and then multiplying the resulting volumes by an 

appropriate aerosol mass density. Because the particles sampled during AAFEX were 

often a superposition of soot and condensed sulfates and hydrocarbons with poorlydefined morphologies, we assumed a mass density of 1 g cm-3

. Absorption coefficients 

measured by the MAAP were processed using Aerodyne Research Inc. algorithms (Onasch 

et al., 2009) and converted into a mass of black carbon using a mass absorption coefficient 

of 6.6 m2g-1 (Petzold et al., 1998).

Table 3. List of parameters derived from experimental measurements

Parameter Symbol Units Temporal

Resolution

Estimated

Precision

Aerosol Volume V μm3 cm-3 1 or 60 s 25%

Total Aerosol Mass M mg m-3 1 or 60 s 50%

Geometric Mean Diameter GMD or Dg nm 1 or 60 s < 2 nm

Volume Mean Diameter VMD nm 1 or 60 s < 2 nm

Geometric Standard Deviation σg -- 60 s --

Number Emission Index EIn kg-1 1 s 20%

Total Mass Emission Index EIm mg kg-1 1 or 60 s 30%

Black Carbon Mass Emission Index EIbc mg kg-1 >10 s 20%
APPENDIX H

192

Aerosol size statistics were derived from the measured size distributions using formulas 

discussed by Hinds (1999). The number "mode" corresponds to the peak in the size 

distribution when plotted as a function of dN/dLogDp vs. Dp. The geometric mean 

diameter (GMD) is found using the following formula:

Eq. 1

where dni, Di, and dlog(Di) are the number density, mean diameter, and normalized width

of the ith size channel. Similarly, the volume mean diameter (VMD) is calculated using 

the formula

Eq. 2

where vi is the total volume calculated for the ith channel as given by vi = ni · · di

3 / 6. 

Assuming the aerosols are log normally distributed in a single mode, i.e., unimodal, the 

geometric standard deviation (σg ) of the size distribution is given by

Eq. 3

In conjunction with the GMD, the geometric standard deviation is useful for modeling 

aerosol emissions and represents the broadness or spread of the log normal function in 

that 95% of the particles within a log normal distribution fall within the size range 

defined by the following expression: 

Emission indices (EIs) are fundamental parameters used to describe the amount of 

pollutants emitted by a combustion source per unit of fuel consumed. Values were 

calculated for aerosol number density, mass and black carbon as follows:

Eq. 4

[ ]























 ⋅

=

∑

∑

=

=

=

=

max

min

max

min

i D

i D

i i

i D

i D

i i i

(dn /dlogD )

(dn /dlogD ) log(D )

GMD exp

[ ]























 ⋅

=

∑

∑

=

=

=

=

max

min

max

min

i D

i D

i i

i D

i D

i i i

(dv /dlogD )

(dv /dlogD ) log(D )

VMD exp

[ ( ) ]

0.5 i D

i D

2

i i

g (N 1)

n log(D ) log(GMD)

σ exp

max

min

























−

⋅ −

=

∑

=

=

exp(log(GMD) (2log( ))) ± σ g

[ ] 















⋅ ⋅ ⋅ 













 = −

CO2

air

2

2

1

X

ρ M

M EI CO

ΔCO

ΔX EI (kg fuelburned)
APPENDIX H

193

Where ∆X (in number- or mass-based units) and ∆CO2 (in ppmv) are the enhancements 

above background concentration for parameter X and CO2, Mair and MCO2 are the molar 

masses of air and CO2, respectively, and ρ is the density of air. For our calculations, we 

either used the measured carbon fractions or assumed the fuel contained ~86% carbon by 

mass, which yields an EI[CO2] of approximately 3160 (g CO2) (kg fuel burned) -1. 

As discussed in the AAFEX overview document, low-pressure fan speed (N1) was the 

parameter used throughout the experiment for setting engine power levels. GE 

Commercial Engines provided a table of nominal N1 values for each of the desired power 

levels. The aircraft operators subsequently used these data to adjust fuel flow rates to 

obtain the proper N1 power settings. Figure 7 shows the relationship between fuel flow 

and engine power setting, and highlights the variability as a function of ambient 

temperature. Power or thrust is a linear function of fuel flow, but the fuel flows vary (by 

more than 1200 lbs. hr-1 at 85 % thrust and as little as 600 lbs. hr-1 at 15 % thrust). 

Results from previous experiments (APEX, Aircraft Particle Emissions Experiment) 

indicate that engine emissions vary more closely with fuel flow rather than with 

percentage power. Some comparisons discussed in later sections used engine power 

setting for ease of calculations, but where possible, emission parameters are presented as 

a function of fuel flow. Hence, both parameters are included with the archived data sets. 

3.4 Instrument Calibration

Instrument calibration was carried out frequently to ensure accurate and robust 

instrument performance. Two types of gas-phase instruments were deployed by Langley 

during AAFEX: an SO2-based sulfate aerosol monitor and several nondispersive-infrared 

CO2 analyzers. The flow and pressure sensors associated with these instruments were 

calibrated in the laboratory before deployment and checked periodically during the 

mission by comparison with a dry cell flow calibrator and ambient pressure monitor, 

respectively. The pulsed fluorescence SO2 instrument was calibrated periodically using 

dry nitrogen to establish zero response and a NIST-traceable SO2 standard was used to set 

the instrument gain over the expected range of concentrations.
APPENDIX H

194

Figure 7. Plot of fuel flow versus power in terms of percentage of maximum RPM for 

the control engine for all the test points conducted during AAFEX. Points are colored 

according to ambient temperature.

The CO2 instruments were calibrated on a daily basis using dry nitrogen as a zero 

reference and a pair of calibration gases with nominal 5000 and 1000 ppm mixing ratios 

for span. A CO2 instrument comparison between NASA, ARI, EPA and MST was 

conducted during AAFEX, which revealed that the primary CO2 instrument was 

somewhat nonlinear over the broad response range. A polynomial correction equation 

was derived and applied to the LARGE data before calculation of emission factors 

discussed below. 

Because absolute standards are lacking, aerosol-instrument calibration efforts focused 

primarily on ensuring that the instruments were operating at the proper flows and 

pressures and were exhibiting the proper size registration for particles of a known size. 

This effort involved checking all instrument flows with a dry-cell calibrator prior to the 

mission and conducting checks on a daily basis throughout the experiment. For pressure, 

instruments were delivered a constant calibration aerosol and their response was 

monitored as a function of pressure to ensure the indicated concentrations changed as 

expected and the instrument plumbing was free of leaks. In addition, once the sampling 

systems in Figures 3 through 5 were installed, they were frequently operated at subambient pressure while sampling cabin air through a high-efficiency particle filter to 

ensure that system and instrument plumbing was completely leak-free. For the size 

calibration, NIST-standard latex spheres were mobilized with an aspiration generator, 

size-selected with a TSI DMA, then assayed by the SMPS, EEPS, UHSAS and OPC 

instruments. During the mission, SMPS, EEPS and CPC data were examined on a 

continual basis to determine continuity in number and size response. 
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3.5 Data Processing 

The aerosol data recorded during AAFEX were influenced by a variety of noise and 

artifact sources including rapid pressure or dilution changes and instrument saturation. 

To reduce these effects, the data were carefully screened to remove time periods when 

sampling system pressure was unstable or when species concentrations were changing 

rapidly (based on variations in CO2 mixing ratio). In addition, for particle volume and 

size statistics calculations, integration of SMPS and EEPS size distributions excluded 

particles larger than 150 nm diameter at lower engine powers to reduce the contribution 

of background aerosols. Individual SMPS size distributions, because of the longer time 

response of the instrument, were discarded if particle concentrations (from a CPC) 

changed more than 10% during the time period of the scan. Number concentration data 

greater than 9×106 cm-3 and 5×106 cm-3 for the TSI-3775 and TSI-3022A instruments, 

respectively, were excluded to eliminate the effects of instrument saturation. Similarly, 

data associated with individual electrometers exceeding their range of sensitivity on the 

EEPS were removed. 

Prior to the mission and in order to miniaturize the systems, the power supplies on the 

two DMAs in the SMPS systems used to derive total and non-volatile aerosol mass were 

replaced in favor of much smaller, programmable units. Unfortunately, these supplies 

had non-zero offsets (approximately 15 VDC) that caused the SMPS scans to exhibit 

artificially high particle counts at sizes below 10 nm when the particle populations were 

affected by nucleation-mode aerosol. These artifacts had very little impact on volumebased size distributions or calculated integrated volume but caused the number-based size 

distributions to exhibit a nucleation-mode artifact (potentially where none were present) 

and the SMPS integrated number concentration to exceed that measured using CPC 

instruments. Thus, particle size statistics (GMD, VMD) were only calculated for sizes 

greater than 11 nm. 

The MAAP data was reprocessed after the mission using the ARI algorithm (Onasch et 

al., 2009), which yields 1-second resolution black carbon concentrations and extends the 

instrument range to accurately detect much higher mass loadings. However, the Langley 

MAAP instrument failed to record data at exactly 1-second intervals, which caused the 

ARI software to introduce brief periods of diverging concentrations into the output data 

set. These fluctuations were removed by hand-editing the black carbon data in view of 

simultaneous CO2 and pressure records.

3.6 Instrumental Difficulties 

Much of the instrumentation suite deployed during AAFEX was in early stages of 

laboratory characterization; subsequently, the performance of a variety of the Langley 

instruments was not ideal. These instruments are not highlighted in Table 2 and will not 

be the focus of this report but will be more efficiently utilized for future field 

deployments based on the valuable experience gained during AAFEX. A summary of the 

problems, solutions, and effects on data interpretation and analysis for these instruments 

is included here.
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196

AAFEX was the first deployment of the LARGE PASS-3. This instrument is designed to 

measure aerosol absorption coefficients in the background atmosphere, where 

concentrations of interfering gas-phase species are typically quite low. Initial data 

processing used a mass absorption efficiency of 6.6 m2

g-1 to convert absorption 

coefficients to black carbon mass. For the red detection channel, this yielded BC 

emission indices that were a factor of two lower than those from the MAAP; for the blue 

and green detection channels, the values were several orders of magnitude too high. An 

examination of the PASS-3 data set with simultaneous certification-gas measurements 

suggested that the instrument’s shorter wavelength channels are highly sensitive to 

interference from NOx and potentially organic species. Although less severely, the red 

channel was also subject to interference, as absorption coefficient variability was 

observed independent of MAAP variability. The PASS-3 data for the propane-burner 

tests were highly correlated with black carbon mass from the MAAP over a broad range 

of concentrations, suggesting that in the absence of NOX and gas-phase organic 

contamination, the PASS-3 performance was satisfactory. Still, because of these 

problems the PASS-3 data were not used to establish the engine emission characteristics 

for this report. 

AAFEX was also the first field deployment for the SP2 instrument, with the goal of 

single particle measurements of soot size from 100 nm to 500 nm diameter and 

determination of coating thicknesses of aged exhaust particles. However, because of 

instrumental complexities, the data quality was unsatisfactory and will not be presented 

here. SP2 characterization, calibration, and intercomparison will be a focus of future 

laboratory and field deployments to best utilize its robust capability. 

The LARGE instrument suite also included a photoelectric sensor to provide a measure 

of surface-bound PAH. Data from this instrument tended to correlate with black carbon 

observations over short time scales, but was also apparently influenced by relative 

humidity. For this reason, the PAH sensor data, although available on request, is not 

presented in the following discussions. The PILS instrument was set up to measure TOC 

and collect aerosol samples at a 4-minute integration time for subsequent IC analysis. In 

most cases, species concentrations in these samples were at or near the detection limit. 

Similarly, quartz-fiber filter samples collected from the 30-m, test engine inlet probe 

yielded potentially meaningful EC/OC measurements only at high engine powers or 

when JP-8 fuel was burned. 

3.7 Line Losses and Impact of Background Aerosols

As discussed in Appendix X of the AAFEX report, particle losses to sampling system 

components profoundly influenced the observed particle concentrations and 

characteristics. Tests conducted after the mission indicated that up to 50% of the 

particles collected using the control engine 30-m inlet probe were lost during transport to 

the community sample distribution manifold. This was approximately 20% more than 

from the test engine 30-m inlet and approximately 50% more than from the control 

engine 1-m inlet. There was also evidence that the losses increased over time, as debris 
APPENDIX H

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and coatings built up within the long sampling lines. These time-varying, differential 

losses make it difficult to compare emissions from the two engines and to evaluate the 

evolution of particles between the 1- and 30-m sampling locations. However, for a 

variety of reasons not least of which was to avoid confusion, the AAFEX science team 

agreed to archive data without corrections for transmission losses. Where appropriate, 

the discussions below point out and take into consideration the potential impacts of line 

losses. Please refer to Appendix X for a robust treatment of particle line loss. 

Another factor that potentially influenced aerosol emission indices and size statistics 

were contributions from background aerosol. Particle number EIs were typically less 

susceptible than mass EIs, since the engine generated high numbers of particles 

regardless of the fuel supply. For the JP-8 fuel tests, background particle number and 

mass concentrations at both 1 m and 30 m were several orders of magnitude lower than in 

the exhaust plume and were hence not a significant interference. However, for the FT 

fuel tests, background and exhaust aerosol loadings were often of the same order of 

magnitude, particularly at low engine powers. It was not possible to completely remove 

the effects of background aerosols because, even if the concentrations and characteristics 

of particles in the engine inlet were measured, they would undoubtedly undergo radical 

changes when passing through the engine’s hot section. For this reason, we did not 

subtract background from the measured aerosol concentrations, but were careful to 

restrict SMPS volume integrations to the appropriate size ranges and to remove data that 

appeared to be heavily impacted by external sources. 

Table 4. Fuel Properties

JP-8 FT-1 Blend-1 FT-2 Blend-2

Sulfur (ppm) 1148 19 699 22 658

Aromatics (% vol) 18.6 0 8 0.6 9.1

Hydrogen Content (% mass) 13.6 15.5 14.5 15.1 14.3

Naphtalenes (% vol) 1.6 0 0.8 0 0.8

Olefins (% vol) 0.9 0 0.6 3.8 3.3

Fuel H/C ratio 1.88 2.19 2.02 2.12 1.99

3.8 Fuel Properties

Table 4 presents selected results from the post-mission analyses of fuel samples collected 

from the test engine supply line that were conducted by AFRL at Wright Patterson Air 

Force Base (AFB). Complete results are presented in Table 2 of the AAFEX overview 

document (Anderson et al., 2010). Blend-1 and Blend-2 were made prior to the 

campaign by mixing equal parts (by volume) of JP-8 and FT-1 and FT-2, respectively. 

The first column lists the pertinent characteristics of the JP-8 fuel purchased from 

Edwards AFB. Note that the JP-8 contained 1148 ppm sulfur, 18.6% aromatics, and 

1.6% naphthalene compounds. In contrast, the FT fuels contained less than 25 ppm sulfur 

(probably introduced during handling or mixing with residual fuel in the aircraft), less 

than 1% aromatic compounds, and 0 % naphthalenes. The hydrogen contents of the fuels 

are also significantly different, reflecting the much higher aromatic and PAH content of 

the JP-8 and the predominance of n-alkanes in the FT fuels. These differences were 
APPENDIX H

198

predicted to have substantial effects on both soot emissions and formation of volatile 

aerosols in the engine exhaust plume.

4.0 Results and Discussion

A complete set of the Langley particle emissions data from the 418 engine and 18 APU 

test points conducted during AAFEX is available on the project web site. Included are 

ambient temperature, ambient humidity, exhaust plume CO2 enhancement, and a variety 

of emission indices for aerosol number, volume, and mass. Size distributions and size 

statistics (i.e., GMD, VMD) obtained with SMPS-type systems are also archived. Note 

that none of the archived data has been corrected for line losses or background aerosol 

interference. The following section summarizes these results regarding fuel and 

temperature effects on emission parameters.

4.1 Inboard Engine Emission Comparison

Because engine particle and gas emissions are known to vary considerably with 

temperature, AAFEX took the approach of using simultaneous measurements of PM 

emission from a test engine burning JP-8 fuel to evaluate fuel-related changes in the 

control engine PM emissions, the assumption being that the emission characteristics of 

the two engines would be identical and that these characteristics would exhibit the same 

ambient temperature dependence. To validate this assumption, tests 3 and 4 were 

conducted to measure emissions from the two engines both burning standard JP-8. 

During all the emission characterization tests, samples were drawn from the 1-m and 30-

m inlets at power settings of 4, 30, 45, 65, and 85% of maximum RPM. 

Results from these tests are shown in Figures 8 and 9 and Tables 5 and 6. Nonvolatile 

EIn from the two engines (Figure 8, first two columns of Table 5) were highly variable, 

primarily because of ambient temperature effects, but it appeared that on average, the 

control engine exhibited slightly higher values at most power settings than the test 

engine. An examination of particle size distributions revealed that increased numbers of 

particles in the 10 to 20 nm size range accounted for the observed enhancements. This 

point is reinforced by the GMD and VMD versus fuel flow plots of Figure 7, which 

indicate that nonvolatile particles emitted from the test engine were on average smaller 

on both a number and volume basis than those from the control engine. Still, EIn values 

compared well between both engines considering potential differences in line loss and 

general measurement uncertainty.
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199

Figure 8. Comparison of emission parameters for control and test engines on 1-m probes 

on the afternoon of 27 January and morning of 28 January. Both engines burned JP-8 

during this test.

Figure 9. Comparison of emission parameters for control and test engines on 30-m 

probes on the afternoon of January 27 and morning of January 28. Both engines burned 

JP-8 during this test.

While the EIn are in relatively good agreement, EIbc for the control engine was two to 

four times greater at mid-power settings (30, 45, 65%) than those for the test engine. It is 

possible that the differences are an artifact caused by placement of the inlet rakes at non-
APPENDIX H

200

representative positions in the engine exhaust planes. Note that very little variation in 

EIbc was observed between samples drawn from the six inlet tips on the control-engine 

rake during the exhaust mapping test (Test #2 in Table 1). On the other hand, EIbc varied 

by a factor of two as a function of sampling position behind the test engine, but even the 

largest values at mid-power settings were still a factor of two lower than the control 

engine average. Thus it appears that, even though the two engines are of approximately 

same age and received the same maintenance and servicing, the control engine simply 

produced more soot at the mid-power settings. 

Table 5. Comparison of non-volatile particle emission indices (EIn) measured from 1-m 

probes. 

Engine Non-volatile Particle Number EI (×1014 kg-1)

Power 

(%)

JP-8 JP-8 FT-1 Blend-1 FT-2 Blend-2

Control 

Engine Test Engine

4 9.9 8.8 0.05 3.7 0.45 3.8

7 7.7 4.3 0.05 1.2 0.25 2.2

15 -- 0.16 0.56 0.08 0.66

30 5.3 3.6 0.05 0.73 0.12 0.69

45 5.4 2.9 0.08 0.58 0.12 0.43

65 7.3 4.4 0.76 2.2 1.2 2.7

85 7.3 7.1 2.0 4.0 2.1 4.8

100 -- 6.9 2.8 4.8 2.5 5.5

All values are averages and have been divided by 1×1014 for presentation.

Table 6. Comparison of black carbon mass emission indices (EIbc) measured from 1-m 

probles.

Engine Black Carbon EI (mg kg-1)

Power 

(%)

JP-8 JP-8 FT-1 Blend-1 FT-2 Blend-2

Control 

Engine Test Engine

4 18.9 13.1 0.9 3.8 0.7 3.4

7 6.3 7.9 1.0 3.2 1.1 4.2

15 0.4 0.9 0.4 1.2

30 25.0 9.1 1.1 2.2 1.2 1.8

45 36.1 8.1 1.2 1.4 2.0 1.3

65 79.9 27.7 2.4 10.5 3.5 14.1

85 95.8 82.7 10.7 34.1 14.8 48.8

100 102.7 24.1 50.5 22.7 66.9

All values are averages.

Figure 9 provides plots of 30-m number and mass emission indices for the two engines 

during the comparison tests (Tests 3 and 4), again with both the control and test engines 
APPENDIX H

201

burning JP-8. At this sampling distance the number emissions are dominated by 

nucleation mode aerosols formed from the condensation of sulfuric acid and low 

volatility organics. The variability in the data at any particular engine power is caused by 

changes in ambient temperature, and will be discussed in depth in Section 4.7. Note that 

the total aerosol mass emissions from the two engines are comparable at low and high 

thrust settings, but differ at mid-power settings by approximately the same levels as seen 

in the EIbc plot of Figure 8 (approximately 30-50 mg kg-1). EIn appears to be greater for 

the test engine, but this difference is presumed to be caused by enhanced nucleation mode 

aerosol losses in the longer (46 m length compared to 38 m, respectively) sampling line 

connecting the control engine 30-m inlet with the common aerosol sample distribution 

manifold. Overall it appears that the test engine produces less nonvolatile particle mass 

emissions at middle-power settings, but that condensation processes occurring in the two 

plumes are of comparable magnitude. 

4.2 JP-8 Emissions Comparison: AAFEX versus APEX-1

The emission characteristics of the DC-8’s #3 engine (used as the test engine during 

AAFEX) was extensively documented during the Aircraft Particle Emission Experiment 

(APEX-1), which was conducted at NASA Dryden during May 2005 (Wey et al., 2007; 

Wey et al., 2008; Onasch et al., 2009). Similar to AAFEX, APEX-1 sought to establish 

particle emission profiles for the aircraft’s CFM56 engine as a function of fuel 

composition, but in this case, the fuel variables were sulfur and aromatic hydrocarbon 

content. APEX-1 employed sampling rakes, inlet probes and sample transport lines that 

were similar to those used during AAFEX. Langley took part in this study, deploying 

many of the same instruments used during AAFEX to determine particle size 

distributions and number and mass EIs. Figure 10 shows a comparison of results from 

the two studies, where the APEX-1 data are an ensemble average of all measurements 

acquired from the 1-m sampling rake, regardless of fuel type, and the AAFEX data 

include only results from the JP-8 fuel tests.

Figure 10. Comparison of non-volatile particle emission parameters for DC-8's #3 engine 

burning JP-8 fuel as measured during APEX-1 and AAFEX.

Note that all parameters show similar trends but differ to varying degrees in magnitude. 

Instrumental differences can account for some of these discrepancies. The CPCs 
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202

deployed during AAFEX had slightly smaller 50% cut-sizes than the CPCs used in 

APEX-1 (7 vs. 10 nm, respectively). We estimate that this can account for about 20% of 

the difference in EIn at low-power settings where the GMD values are around 15 to 20 

nm. Similarly, black carbon concentrations were measured with a MAAP instrument 

during AAFEX, as opposed to a Particle Soot Absorption Photometer (PSAP) during 

APEX-1. The PSAP deployed by ARI during APEX-1 tends to overestimate black 

carbon emissions compared to the MAAP (deployed during AAFEX), which can explain 

why the apparent APEX-1 EIbc are higher at takeoff thrust. Differences in ambient 

temperature could have contributed to the differences in EIs between the two studies 

(APEX-1 was conducted during May when the average daily temperature in the 

Palmdale/Edwards AFB region is about 10o

C warmer than during the January time frame 

of AAFEX). An engine oil leak and engine aging may also have contributed to slightly 

higher particle number and mass emissions at most power settings during AAFEX than 

observed during APEX-1. Still, the comparison of EIn and EIbc during AAFEX and 

APEX yields strong similarity in the trend and magnitude of emissions and thus the 

engine performance did not change significantly between sampling campaigns. 

Figure 11. Particle emission characteristics for JP-8, FT-1, and Blend-1 at 1-m probe.
APPENDIX H

203

Figure 12. Particle emission characteristics for JP-8, FT-2, and Blend-2 at 1-m probe.

4.3 Alternative Fuel Effects on Particle Emissions: 1-m Probe

The analysis presented in Section 4.1 suggests that although there were differences in PM 

emissions between the control and test engines, the overall trends and characteristics of

the emissions were similar. Section 4.2 showed that the emissions have not changed 

considerably from the APEX campaign (2005) to the current AAFEX campaign. This 

allows the use of #3 engine emissions data as a test engine for decoupling ambient 

temperature and fuel-related changes compared to the control engine emissions. This 

section examines results from tests 5 to 6 and 8 to 11, wherein the composition of exhaust 

from the two inboard engines was characterized as the right engine burned the various 

test fuels and the left engine was supplied the standard JP-8 baseline fuel. 

Tables 5 and 6 compare non-volatile particle number and mass emission indices, 

respectively, for the different fuels and engines. Figure 11 and Figure 12 show fuel flowdependent plots of average EIs and particle size statistics for each of the fuels in 

comparison to simultaneous measurements from 1-m probes of the same parameters from 

the control engine burning JP-8. PM emissions from the test engine, burning FT fuels, 

were substantially reduced compared to emissions from the control engine burning JP-8. 

This finding is consistent with previous studies (Corporan et al., 2007; Dewitt et al., 

2008; Timko et al., 2010) and can be attributed to the higher hydrogen content, lack of

aromatics, and lack of sulfur in the synthetic fuels. 
APPENDIX H

204

A major goal of AAFEX was to examine the benefits of replacing current fuels (JP-8) 

used in commercial aircraft with pure or blended alternative fuels. To quantify the 

emissions characteristics of such a switch, an emissions benefit was defined as 

Eq. 5

where X denotes the alternative fuel (FT-1 or FT-2) or blend (Blend-1 or Blend-2). Y 

denotes an emissions parameter, and for this report, only particle number concentration 

emissions indices (EIn) and black carbon mass emissions indices (EIbc) are considered. 

Here, increased emissions benefit indicates a larger gap between the EI for JP-8 and the 

EI for the alternative fuel. Emissions benefit was calculated for both EIn and EIbc as a 

function of engine power and is shown in Figure 13 and Figure 14. For example, a 

particle number emissions benefit value of 100 for FT-1 fuel at 30 % engine power 

represents a JP-8 EIn that is 100-fold- greater than FT-1 EIn. Likewise, this emissions 

benefit corresponds to a 99 % reduction in EIn emissions when switching from JP-8 to 

FT-1. Note that all particle number and black carbon emissions-benefit values are greater 

than unity, indicating that at all engine power settings JP-8 emissions exceeded those 

from FT fuels and blends. 

Figure 13. Particle number emissions benefit as a function of engine power for each 

alternative fuel and mixture. Note the logarithmic y-axis scale. Measurements taken 

from 1-m probe. 

The greatest emissions benefit was associated with burning the FT-1 fuel, which had the 

highest hydrogen, lowest aromatic hydrocarbon, and lowest sulfur contents of all the 

fuels tested (Table 4). At low engine powers, nonvolatile EIn values for FT-1 were two 

orders of magnitude lower than for JP-8 and thus the emissions benefit was significant. 

The FT-1 emissions benefit for particle number decreased with engine power but was still 

2-3 at climb and takeoff thrust levels (Figure 13). For FT-2, Blend-1, and Blend-2, the 

particle number emissions benefit was significant throughout but was greatest at 45 % 

thrust level and was slightly reduced at idle thrust and significantly reduced at takeoff 

thrust settings. 

Y, X

Y,JP 8

EI

EI

emissions benefit − =
APPENDIX H

205

In terms of PM mass emissions, EIbc values were similarly reduced. The black carbon 

emissions benefit (Equation 5) for FT-1 and FT-2 was greatest at the 65% thrust level (33 

and 23, respectively and was minimized at 7 % and 85 % [figure 14]). The peak black 

carbon emissions benefit for Blend-1 and Blend-2 was shifted to the 45% thrust level. 

The black carbon emissions benefit at idle (4 % thrust) may be underestimated because 

the corresponding MAAP signals (black carbon mass) for the FT fuels were barely 

Figure 14. Black carbon emissions benefit as a function of engine power for each 

alternative fuel and mixture. Note the logarithmic y-axis scale. Measurements taken 

from 1-m probe.

detectible and were not corrected for background soot contributions. Number 

concentration enhancements in the FT fuel exhaust were much more robust but still 

somewhat variable (10-20%) due to contributions from background sources.

A diminishing emission benefit of the FT-1 fuel with engine power is consistent with 

previous observations (Corporan et al., 2007; Timko et al., 2010) and can be attributed to 

changes in the dominant soot formation mechanism with combustion flame temperature. 

At low combustion temperatures, condensation reactions involving aromatic 

hydrocarbons proceed at much faster rates than reactions involving n-alkanes. As the 

combustion temperature increases, the fragmentation and polymerization of both 

aromatic and alkane species compete with aromatic condensation, so the initial fuel 

composition has much less impact. This effect is clearly depicted in the low-power black

carbon emissions benefit shown in Figure 14 for pure FT fuels and with their blends. 

But, the significant benefit observed at high power cannot be explained in this manner. 

Thus, fuel aromatic content is likely a key factor in regulating soot production, but 

additional work is necessary to understand soot formation from pure and blended 

alternative fuels more fully. 

Differences in the primary particle size drive the differences in PM number and mass 

reduction ratios discussed above. The GMD and VMD plots shown in Figure 11 and 
APPENDIX H

206

Figure 12 indicate that burning FT-1, and FT-2 fuels and respective blends produced 

smaller particles in comparison to JP-8 at all engine powers. Overall, for the 100% FT 

fuels, GMD differences were 5 to 10% at idle and 15 to 20% at takeoff thrust; VMDs 

were reduced 20 to 40% across the entire power range. The change in size with fuel 

composition is more clearly observed in the particle size distributions (PSDs) shown in 

Figure 15, which depict particle diameter-normalized EIn as a function of diameter for 

each of the fuels at 7, 65 and 85% of maximum thrust. Note that the PSD modes shift to 

smaller sizes as the fraction of FT fuel is increased. For example, the particle emissions 

size distribution at 85 % thrust peaked in dEIn/dlogDp at 28.9 nm, 22.5 nm, and 19.5 nm 

for JP-8, Blend-1, and FT-1, respectively. 

At idle, a large fraction of the particle population is smaller than the instrument detection 

limit, hence GMDs calculated from the PSDs are larger than the modal diameter; at 65 

and 85% thrust, the effects of instrument sensitivity are reduced and the calculated GMDs 

and modal diameters correspond more closely. This explains why the relative difference 

in GMD between the fuels appears to increase with power, while the differences in VMD 

remain relatively constant. Regardless, a 20% reduction in particle size corresponds to a 

~50% decrease in particle volume. Note that reduced particle size with fraction of FT 

fuel was observed in several recent studies (Corporan et al., 2007; Timko et al., 2010) 

and is related to the lack of the large aromatic hydrocarbon species that promote soot 

formation and growth in FT fuel. 

Figure 15. Number EI-based particle size distributions for the JP-8 fuel compared to 

particle size distributions for FT-1 and Blend-1 (top) and FT-2 and Blend-2 (bottom) 

fuels at 7, 65, and 85% power. All data are from 1-m probe.

 

Related to changes in particle size are changes in soot density. Timko et al. (2010) 

observed that FT fuel combustion in gas turbine engines produces less fractal and more 

dense soot particles. Effective density (ρeff), which takes into account both the chemical 

density and the particle shape for particulate fuel emissions, was calculated by 
APPENDIX H

207

Eq. 6

where EIbc is from the MAAP and EIv is from the SMPS. For AAFEX over the 65-100% 

power range ρeff values were 1.45+0.1 g cm-3 for FT-1, 1.2+0.15 g cm-3 for FT-2, 1.1+0.1 

g cm-3 for Blend-1, 1.05+0.15 g cm-3 for Blend-2, and 0.92+0.08 g cm-3 for JP-8. 

The alternative fuel blends also produced reductions in non-volatile PM number, mass 

and size when compared to combustion of standard JP-8 (Figure 11 and Figure 12). 

However, the reductions were typically different than would be predicted from averaging 

the emission parameters from the individual fuels, which would be expected since the 

blended fuels were produced by simple mixing of equal volumes of JP-8 and FT fuels. 

For example, at 30% engine power both PM number and mass were reduced by 75 to 

80% when burning Blend-1 as opposed to JP-8. At takeoff thrust, EIn and EIm decreased 

30 and 50%, respectively. It appears that soot emissions are nonlinear with fuel aromatic 

content and/or hydrogen content, particularly at low engine power. This is explored in 

more detail below. 

The above discussion highlighted the impacts of burning FT-1 and the FT-1/JP-8 blend 

on engine PM emissions compared to traditional JP-8. Because of the similar 

composition of the two synthetic fuels, we found that FT-2 and its blend had qualitatively 

similar effects on reducing the number, mass and size of particle emissions. For 

example, the trends in emission parameters shown in Figure 10 for FT-1 are almost 

identical to those exhibited in Figure 11 for FT-2. Likewise, the size shifts in PSDs with 

fraction of FT fuel for FT-1 and FT-2 (see Figure 15) are quite similar. 

(g cm ) EI

EI particle effective density (ρ ) 3

v

bc

eff

− =
APPENDIX H

208

Figure 16. Comparison of FT-1 and FT-2 effects on engine PM emission characteristics 

at 1-m probe.

However, Figure 13 and Figure 14 highlighted significant differences in number- and 

black carbon-based emissions benefits between FT-1 and FT-2. The differences in pure 

alternative fuels are specifically compared in Figure 16. Both PM number and mass EIs 

were slightly higher for FT-2 at most power settings. This is especially evident at low 

engine power (and fuel flow) where the particle number emissions benefit (Figure 13) is 

an order of magnitude greater for FT-1 than for FT-2 and the EIn for FT-2 is an order of 

magnitude greater than for FT-1 (Figure 16). This benefit diminishes with increasing 

engine power. The black carbon emissions benefit and FT-2/FT-1 EIbc difference 

exhibits the opposite trend, increasing with increasing engine power when the total black 

carbon emissions (Figures 11 and 12) become most significant. This benefit is negligible 

at low engine power (Figure 14). Differences in the particle size for FT-1 and FT-2 

emissions are less distinct. Nonvolatile particles associated with burning FT-2 tended to 

be slightly larger (with respect to both GMD and VMD) than those from FT-1 

combustion (Figure 16).
APPENDIX H

209

Figure 17. Particle EIn and EIbc as a function of fuel aromatic content (top) and fuel 

hydrogen content (bottom). All data are from the test engine 1-m probe. 

The differences in PM emission characteristics observed between the two fuels are 

expected given with the current understanding of soot formation and growth in gas 

turbine engines. Several studies have shown that the soot production is inversely 

proportional fuel hydrogen content. For example, Sampath et al. (1986) successfully 

modeled the soot emissions from a PT6A-65 engine using hydrogen content as the sole 

fuel-related parameter. Rosfjord (1987) also found a linear relationship between 

hydrogen content and soot formation in the combustion zone of a high-pressure lab 

burner but found better correlations when a term for dicyclic aromatic content (DA, i.e., 

naphthalenes) was added to his empirical soot prediction equation. Chin and Lefebvre 

(1990a, 1990b) also developed an empirical expression for predicting gas turbine soot 

emissions, but they used smoke point (SP; the height above a laminar diffusion flame 

where visible smoke begins to form) along with DA as the principle variables. Other 

researchers note that fuel soot formation was negatively correlated to SP (i.e. Gulder et 

al., 1989), a parameter that tends to vary inversely with hydrogen content. However, by 

studying fuels with identical hydrogen contents but different SP values, Gulder et al. 

(1990) concluded that SP and H content are complimentary rather than interchangeable 

predictors of soot formation. 

The fuel analysis conducted by AFRL on the AFFEX fuels included determination of 

hydrogen content, H/C ratio, olefins, total aromatics, and naphthalenes (see Table 4). 
APPENDIX H

210

Taking the above discussion into consideration, we note that FT-2 had lower hydrogen 

(15.1 vs 15.5%), higher alkene (olefin, 3.8 vs. 0%) and higher aromatic (0.6 vs. 0%) 

content than FT-1, all of which suggests that it should exhibit the greater sooting 

tendency and thus greater EIn and EIbc.

To explore further the relationship between fuel composition and soot emissions, the 

power-dependent EIn and EIbc for the five fuels and fuel aromatic and hydrogen contents 

are presented in Figure 17. Additionally, a linear regression analysis was performed to 

explore the relationship between EI and fuel composition and the resulting statistics are 

presented in Table 5 and Table 6 for EIn and EIbc, respectively. Note the small sample 

size (N=5) for this analysis. The following results are suggested: 

• EIn and EIbc at all power settings increased with aromatic content and decreased 

with hydrogen content.

• The variability in EIn decreased with increasing aromatic content and decreasing 

hydrogen content. For example, EIn for JP-8 (highest aromatics, lowest hydrogen) 

varied about 60% between idle and takeoff thrust whereas those for FT-1 (lowest 

aromatics, highest hydrogen) varied by almost two orders of magnitude. These 

findings are consistent with temperature dependence of soot formation, which is 

discussed in more detail below.

• EIn and EIbc were both well correlated with each fuel property. In general, 

correlation coefficients were greater for EIn than for EIbc, suggesting that the 

variability in EIn was better captured by variability in fuel composition than was the 

variability in EIbc. 

• The best correlations were observed for idle (4%) and takeoff (100%) thrust settings 

for relationships between both EIn and EIbc with all fuel properties; correlation 

coefficients were minimized for 30% and 45% thrust settings. 

• Slopes for EIn linear regressions were greatest at the 4% thrust setting, suggesting 

that absolute EIn values were most sensitive to variable fuel properties at aircraft 

idle. 

• Slopes for EIbc linear regressions were greatest at the 100 % thrust setting, 

suggesting that absolute EIbc values were most sensitive to variable fuel properties 

at aircraft takeoff. Note that low black-carbon mass emissions at low engine thrust 

may have affected this result. 

• Particle emissions appear to be better correlated with fuel aromatic than hydrogen 

content at all thrust settings for both EIn and EIbc. Note that fuel contents do not 

vary independently, so these results are only suggestive of observed relationships. 

Correlation coefficients for naphthalene were similar to those for total aromatics. 
APPENDIX H

211

Table 7. Statistics for linear regression analysis for EIn as a function of fuel chemical 

composition. Slopes and correlation coefficients are given for EIn with aromatic content, 

hydrogen content, hydrogen-to-carbon ratio, and naphthalene content for each thrust 

power setting. The average values for each chemical property are also provided. 

Aromatics 4 % 30 % 45 % 65 % 85 % 100 % Average

slope 0.47 0.18 0.14 0.19 0.28 0.24 0.25

r

2 0.99 0.87 0.84 0.99 0.99 0.96 0.94

Hydrogen 4 % 30 % 45 % 65 % 85 % 100 % Average

slope -4.68 -1.75 -1.37 -1.94 -2.80 -2.44 -2.50

r

2 0.95 0.77 0.72 0.97 0.96 0.94 0.88

H/C ratio 4 % 30 % 45 % 65 % 85 % 100 % Average

slope -28.54 -10.59 -8.31 -11.84 -17.11 -14.92 -15.22

r

2 0.94 0.75 0.71 0.96 0.95 0.93 0.87

Naphthalene 4 % 30 % 45 % 65 % 85 % 100 % Average

slope 5.24 1.99 1.58 2.12 3.11 2.73 2.79

r

2 0.98 0.83 0.79 0.96 0.98 0.97 0.92

Table 8. Statistics for linear regression analysis for EIbc as a function of fuel chemical 

composition. Slopes and correlation coefficients are given for EIbc with aromatic content, 

hydrogen content, hydrogen-to-carbon ratio, and naphthalene content for each thrust 

power setting. The average values for each chemical property are also provided. 

Aromatics 4 % 30 % 45 % 65 % 85 % 100 % Average

slope 0.64 0.40 0.32 1.34 3.82 4.35 1.81

r

2 0.91 0.80 0.66 0.99 0.98 0.98 0.89

Hydrogen 4 % 30 % 45 % 65 % 85 % 100 % Average

slope -6.18 -3.83 -3.03 -13.46 -38.76 -43.88 -18.19

r

2 0.80 0.69 0.56 0.94 0.95 0.94 0.81

H/C ratio 4 % 30 % 45 % 65 % 85 % 100 % Average

slope -37.47 -23.15 -18.28 -82.00 -236.32 -267.53 -110.79

r

2 0.78 0.67 0.54 0.93 0.94 0.93 0.80

Naphthalene 4 % 30 % 45 % 65 % 85 % 100 % Average

slope 7.09 4.41 3.44 14.93 42.60 48.79 20.21

r

2 0.87 0.76 0.60 0.96 0.95 0.96 0.85
APPENDIX H

212

4.4. Volatile Aerosol Formation: 30-m and 145-m Probes

At the extreme temperatures of the exhaust plane, aerosols are composed completely of 

soot. These emissions are represented by the 1-m probe sampling documented in the 

Section 4.3. However as the plume ages, temperature decreases allow partitioning of 

gaseous compounds in the exhaust to the particulate phase forming volatile aerosols. This 

either occurs via the formation of nucleation-mode particles (typically with diameters less 

than 30 nm) or condensation onto soot-mode particles (with a diameter of between 50 and 

200 nm). Samples taken from the 30-m and 145-m probes represent aged aircraft 

emissions and are discussed here.

4.4.1. Downwind JP-8 Sampling

In order to determine the effects of plume aging, sampling was performed at various 

distances downstream of the engine (with distance being used as a proxy for age). For the 

1-m and 30-m probes, the same instruments were used with sample alternating between 

the two distances. However, differences in the inlets cause variation in particle 

transmission efficiency (Appendix P) with greater efficiency typically seen for the 30m 

inlet. Thus, care must be used when comparing the downwind and exhaust plane data.

Emission indices were calculated based on Equation 4. EIn at 1 m were calculated from a 

CPC. At the 30-m probe, the particle number concentration was above the limits of the 

CPC, so the EEPS was used to determine EIn. Size distributions and volume emission 

indices (EIv) were calculated from the SMPS size distributions at 1 m and 30 m. EIbc

were measured continuously at 30 m by a MAAP and sporadically through the analysis of 

quartz filters by a OC/EC Aerosol Analyzer (Figure 6). 

Figure 18. Results from test 12 showing EIn (left) and EIv (right) as a function of 

distance for JP-8 emissions.

Sampling was also performed 145 m behind the test engine. Due to the distance behind 

the engine, sampling of the engine exhaust was sporadic with interspersed periods of 

background and plume sampling. In order to find the emission indices, aerosol 

measurements during plume periods were plotted versus CO2 to give the ratio of the 

emission indices. The emission index was then found based on the known emission index 

of CO2. Because of uncertainties in the wind direction of the sampling, only data from 
APPENDIX H

213

tests when JP-8 was burned in both engines is used at the 145 m probe. A CPC allowed 

for the determination of particle number concentration during tests 3, 4, 12, and 13, and a 

SMPS measured size distributions and was used for calculating EIv during tests 12 and 

13.

Figure 19. Size distributions (dEIv/dlogDp, mg kg-1

) as a function of 

sampling probe and engine power setting for test #12 using JP-8 fuel. 

More uncertainty is observed with increasing probe distance because of 

increasing dilution correction factors.

A subset of results from the 145 m measurements are summarized in Figure 18; EIn and 

EIv as a function of engine power are shown and compared to values for 1-m and 30-m 

sampling. The downwind-increases in EIn and EIv are attributed to volatile aerosol 

formation and are the greatest at low power when emissions of gaseous precursors are 

greatest. Changes in particle size as a function of sampling probe are shown in Figure 19 

as EIv-weighted PSDs from test #12 on 27 January at 1, 30, and 145 m. At the exhaust 

plane the particles are comprised of a single soot mode (Figure 19, top panel), while an 

additional nucleation mode is only observed downwind. At low power, this nucleation 

mode dominates the PSD. As power increases the nucleation mode decreases and the soot 

mode increases with the soot mode dominating at high power. Very little variation is 

observed in the soot mode volume between each distance. Significant variability is 

observed for the nucleation-mode, as the peak-diameter and integrated volume each 

increase with increasing distance (from 30 m to 145 m, Figure 19), suggesting that gas-
APPENDIX H

214

to-particle conversion and particle growth is also occurring. This is also evident from 

Figure 18, as EIv is greater at 145 m than at 30 m. Differences in EIn are most significant 

between 1 m and 30 m, as the exhaust plume is cooling and particle nucleation is most 

prevalent. The difference between 30-m and 145-m EIn is much less, suggesting that 

nucleation processes are still occurring but are less significant after 30 m. 

Figure 20. EIn measured at 1 m (left) and 30 m (right) for all tests, colored by ambient 

temperature. Note the different y-axis scales for each plot.

4.4.2 Temperature Dependence of JP-8 Emissions 

Analysis of EIn at 30 m from all tests yielded large variability in values is observed. This 

is primarily the result of ambient temperature effects on combustion and plume aging. As 

ambient temperature decreases a clear increase in EIn is observed at 30 m (Figure 20, 

right), which is likely the result of enhanced rate of new particle formation. As a 

comparison, the temperature dependence (denoted by the coloring in Figure 20) of EIn

measurements at 1-m are also provided in Figure 20 (left). Note that EIn at 30 m are 

much greater than at 1 m, by more than an order of magnitude, because of particle 

nucleation downwind of the combustor. Additionally, the temperature dependence at 1 m 

is less distinct compared to 30 m measurements, suggesting that nucleation processes, 

and not changes in the soot formation mechanism, drive the observed temperature 

dependence at 30 m. 

To focus on the change in number concentration at 30 m, a linear fit of EIn versus 

temperature is performed for each power (for example, Figure 21, right). The y-intercept 

(and its error) gives the emission index at 0°C (and its error), while the slope (and its 

error) gives the temperature dependence (and its error) in kg-1 °C-1. The EIn at 10°C can 

then be calculated. 10°C is chosen as a reference because it is the midpoint of the 

ambient temperature range during AAFEX. The EIn (10°C) at 30 m decreases with 

power (Figure 22, right) as a result of decreasing precursor hydrocarbon emission (which 

results in less new particle formation). The 30-m temperature dependence is greatest at 

low power (4 and 7 % thrust) and is relatively constant (but still negative) at higher 

powers. 
APPENDIX H

215

Figure 21. EIn at 1 m (left) and 30 m (right) as a function of ambient temperature at 7% 

(top) and 85% (bottom) power. Note the different y-axis scales on each plot.

For comparison, the same analysis was performed for 1-m data. EIn at 1 m are 

significantly lower than at 30 m, and the temperature dependence (for 7% and 85 % 

power settings) had more variability (Figure 21, left) compared to measurements at 30 m. 

Still, a negative correlation was obtained for all power settings, which is shown in Figure 

23 (left). Note that the temperature dependence (linear regression slopes) are much 

smaller than at 30 m, but a similar trend was observed; the largest temperature 

dependence was observed at low power and fairly constant and slightly negative 

temperature dependence at higher engine power. 

This temperature dependence analysis was also performed with respect to EIbc at 30 m 

and at 1 m (for comparison). EIbc at 10°C and the temperature dependence for both 1-m 

and 30-m probe measurements are shown in Figure 23. An increase in soot is observed as 

the engine-power increases with similar EIbc values for both probes. Differences are 

attributed to increased line loss in the 1-m probe, as theoretically the EIbc should not vary 

with probe distance or plume age. The trend in temperature dependence is less clear 

compared to the EIn analysis but is similar for both probe distances. For both probes, a 

dependence of similar magnitude was observed at high engine power where 

concentrations are the largest. A negative temperature dependence was also observed at 

the lowest power setting for the 30-m probe and not the 1-m probe, and may be the result 

of erroneous interpretation of low concentration data at this power setting. The 

temperature and engine power dependence of black carbon measurements is likely the 

result of variable combustion conditions in the engine.
APPENDIX H

216

Figure 22. EIn at 1 m (left) and 30 m (right) at 10°C (kg-1

, top) and its temperature 

dependence (kg-1 °C-1, bottom) as a function of engine power. Error bars are the 1 sigma 

standard deviation of the linear fits. The temperature dependence for 100% power is not 

shown because there too few data points. Note the different y-axis scaling for the left and 

right panels.

Figure 23. EIbc at 1 m (left) and 30 m (right) at 10°C (mg kg-1

, top) and its temperature 

dependence (mg kg-1 °C-1 ,bottom) as a function of engine power. Error bars are the 1-

sigma standard deviation of the linear fits. The temperature dependence for 100% power 

is not shown because there are too few data points. 
APPENDIX H

217

4.4.3 Temperature Dependence of Nucleation and Soot Modes; Soot Mode Coating

The aerosol measurements shown in Figure 19 clearly are a composite of both 

nucleation-mode particles and soot-mode. The soot mode is composed of black carbon 

with a potential coating of volatile organic compounds. In order to determine the 

importance of these components, the nucleation and soot modes are fitted (for example, 

Figure 24). The 30-m volatile aerosol volume corresponding to the soot mode is found by 

fitting the data between 50 and 200 nm. This is subtracted from the total size distribution 

to find the residual which is then fit to determine the volume corresponding to the 

nucleation mode. Because the 1-m PSDs did not exhibit the same bimodal trend, only the 

soot mode was fit. The EIv and temperature dependence for the nucleation and soot 

modes is shown in Figure 25. Nucleation-mode mass is greatest at low power and fairly 

constant at higher powers, a trend similar to 30-m EIn shown in Figure 22. Conversely, 

the soot mode particles increase as power increases, with a similar trend and magnitude 

as EIbc in Figure 23, since black carbon makes up the majority of the soot mode volume. 

Temperature effects for the nucleation-mode and soot-mode EIv are most significant at 

low and at high power, respectively, again analogous to EIn and EIbc at 30 m.

Figure 24. Representative size distribution at 65% power for the 30-m probe with fitting 

of the nucleation and soot modes.

The soot mode EIv (Figure 24, right) is composed of black carbon and a possible volatile 

coating and exhibits a similar trend in EIv as EIbc found by the MAAP (Figure 22). 

However, in order to compare the soot EIv and EIbc, the density of the black carbon must 

be known. At the exhaust plane, the aerosol is composed entirely of soot. Using the 1-m 

SMPS and MAAP data, a black carbon effective density of 0.93 ± 0.02 g cm-3 for the JP8 fuel was determined (see discussion above). Assuming this density is constant, black 

carbon volume for the 30-m MAAP samples is determined. These values agree with the 

total soot-mode aerosol volume (found by the SMPS) to within ±15 mm3 kg-1 suggesting 

an upper limit of 15 mm3 kg-1 for the volume of the soot-mode coating. This is consistent 

with data from the aerosol mass spectrometer which found soot-mode organic mass 
APPENDIX H

218

emission indices on the order of 5 mg kg-1 (5.4 mm3 kg-1 assuming a soot density of 0.93 

g cm-3

).

Figure 25. Nucleation mode (left) and soot mode (right) EIv for the 30-m probe at 10°C 

(mm3 kg-1) and its temperature dependence (mm3 kg-1 °C-1) as a function of power. Error 

bars are the 1 sigma standard deviation of the linear fits.

4.4.4 Comparison of JP-8 and Alternative Fuel Emissions at 30-m Probe

Figure 26 compares total PM number and volume EIs measured in samples from the test 

engine 30-m inlet probe and illustrates the impact of fuel composition on volatile aerosol 

formation and growth in downstream engine exhaust. At low engine powers, total EIn

values for JP-8 were enhanced by a factor of 40 to 50 above corresponding 1-m values 

(comparing EIn from Figure 26 to Figure 11 and Figure 12), which indicates that 

nucleation and growth of new particles occurred quite rapidly as the plume cooled and 

diluted with background air. EIn decreased with power as more surface was available for 

condensation (for example, EIm in Figure 26) and decreasing amounts of condensable 

organic gas were available for new particle formation. The JP-8 EIm was significantly 

higher than 1-m values at all power settings regardless of ambient conditions. 
APPENDIX H

219

Figure 26. Number (left) and mass (right) emission indices at 30-m for JP-8, FT-1, and 

Blend-1. Data are only shown for ambient conditions where temperature was greater 

than -1°C and less than 7°C.

FT-1 total EIn values were substantially lower than from JP-8, but still were enhanced 

above 1-m values. This difference is potentially due to the slight sulfur contamination or 

to nucleation of semi-volatile hydrocarbons at the relatively cold ambient temperatures. 

Blend-1 total EIn values were similar to JP-8 values despite the factor of two difference in 

sulfur content between the fuels. This result is not unusual; Timko et al. (2010) observed 

higher relative EIn in a plume generated by combustion of 50% synthetic fuel. From 

modeling analysis, they showed that the reduced availability of soot surface area in the 

blended fuel exhaust caused new particle formation to be favored over condensation of 

volatile material onto soot mode particles. Competition between the decreased 

condensation sink and decreased new particle formation potential (from reduced sulfur 

content) results in complex interpretation of the data that requires additional modeling 

effort. Here, we believe that volatile particle populations reached equilibrium between 

formation by nucleation and loss through coagulation that made the overall particle 

number densities vary independently from fuel sulfur content. This is supported by our 

observations that JP-8 nucleation-mode mean diameters were significantly larger than 

corresponding Blend-1 diameters in the 30-m samples at all power settings. 

4.5 APU Emissions

The DC-8’s APU is essentially a small turbo-jet engine (Honeywell Model GTCP85-

98CK) that was manufactured in the 1960s and was expected to produce much greater 

EIs than the aircraft’s CFM-56 engines. Tests 7, 15, and 16 were conducted to 

characterize emissions from the APU as it burned JP-8 and FT fuel under typical 

operational loads. For the tests, an inlet probe was positioned approximately 10 cm 

below the APU exhaust port, which is located on the starboard side of the aircraft, just 

ahead of the wing spar. Exhaust samples were diluted with dry nitrogen just inside the 

inlet tip and drawn into a community sample distribution manifold in the same manner 

implemented during the aircraft engine tests. APU load was varied by drawing power 

from the unit to drive aircraft electrical systems and air handlers and to start an engine. 

Exhaust gas temperature (EGT) was used to indicate APU load. EGT varied from 
APPENDIX H

220

approximately 350o

C at idle to greater than 610oC when bleed air was used to spin one of 

the aircraft’s engines (for comparison, EGT for the DC-8’s test engine varied from 

approximately 400°C at idle to 716°C at takeoff thrust). Typical samples contained 1000 

to 2000 ppm CO2 and particle number densities in the 10-5 to 10-6 cm-3 range, well within 

the concentration range of the diagnostic instruments. The individual set points were 

fairly reproducible and stable allowing representative data to be obtained with each of the 

fuels tested.

Figure 27 shows particle emission indices and size statistics for the APU as it burned JP8 and FT-2. Corresponding volume-based PSDs are displayed in Figure 28. Note that 

data from test 7 are excluded from the plots because the operators were unable to access 

the full range of test loads on the APU on that day. Also, tests 15 and 16 were conducted 

back-to-back over a 2.5-hour period with ambient temperature remaining fairly constant; 

thus the trends in EI as a function of engine load (EGT) and fuel composition should not 

be influenced by changes in engine inlet temperature or pressure. These analyses 

demonstrate the significant reduction in EIn and EIbc observed by burning FT-2 compared 

to JP-8 at all engine loads and that the resulting aerosols are significantly smaller in 

diameter. 

Figure 27. PM emission characteristics of the DC-8 APU as it burned standard JP-8 and 

FT-2 as a function of EGT (a proxy for engine load). Plots include data from tests 15 and 

16 only.
APPENDIX H

221

Emissions indices are summarized in Figure 29 as average values for all DC-8 and APU 

sampling with JP-8 and FT-2 fuels. From a PM standpoint, the APU is much more 

polluting than the DC-8’s CFM-56 engines. JP-8 APU emissions far exceeded those 

from the DC-8 for EIn (8.4x1015 and 7.2x1014 kg-1, respectively) and for EIbc (326 and 44 

mg kg-1, respectively). APU to DC-8 EIs varied with engine load. For example, when 

burning JP-8 at idle (350 EGT) the APU EIn and EIbc were about 6 and 35 times higher, 

respectively, than corresponding values for the DC-8. Moreover, the ratio between APU 

and engine EIs was greatest at idle and decreased significantly with power. Unlike for 

the high-pass engines on the DC-8, the normalized APU PM emissions decreased with 

increasing power (for example, the JP-8 EIn and EIbc trends in Figure 27). Indeed both 

EIn and EIbc values declined by more than a factor of two as the APU load was increased 

from minimum (cabin lights and avionics only) to maximum (air handler operation plus 

providing bleed air to spin the DC-8 control engine). Since the APU fuel-air-ratio 

increased with thrust (similar to the aircraft engine), the decreasing emissions can’t be 

attributed to rich combustion conditions at idle. Improved combustion efficiency or 

increased combustor pressure with thrust are other factors that could influence the 

emission behavior of the APU.

Figure 28. APU volume-based PSDs as a function of EGT for JP-8 (dashed lines) or FT2 (solid lines).

Overall, PSDs for APU emissions resulted in larger diameter particles than from the DC8 (Figure 29). For JP-8, GMDs were 32.9 and 21.2 nm for the APU and DC-8, 

respectively, and VMDs were 92.8 and 57.0 nm for the APU and DC-8, respectively. 

FT-2 particles were smaller compared to emissions from JP-8 but again were 

coincidentally comparable to the JP-8 GMD and VMD from the DC-8. Particle size also 

varied with engine load and APU GMD and VMD values decreased slightly with 

increasing load (Figure 28), which is opposite to the trends observed in DC-8 engine PM 

emissions (Figure 11). However, even at the highest load/thrust settings, APU particles 

were still 20-30% larger, on a volume-basis, than those emitted by the DC-8 engines. 

The APU particles were also much more fractal and less dense than those emitted by the 

engines. For example, density values for JP-8 fuel combustion obtained by taking the 

ratio of EIbc (from the MAAP) to EIv (from an SMPS) averaged 0.51±0.02 g cm-3 for 

APU compared to 0.92±0.08 g cm-3 for the engines at thrust settings greater than 65 %. 
APPENDIX H

222

APU PM emissions are likely more similar in size, density and fractal nature to soot 

emissions from older, low-pass aircraft engines.

However, the DC-8’s APU and engines were similarly characterized by significnat PM 

emission-reduction benefits from burning FT fuel (Figure 27 and Figure 29). FT-2 

average EIn values were reduced compared to JP-8 for the APU (8.4x1015 and 1.4x1015

kg-1

, respectively, a factor of six), but were still significant and comparable to JP-8 EIn

and EIbc from the DC-8. A reduction by a factor of 13 was observed for average EIbc. 

APU FT-2 combustion also produced significantly smaller particles compared to JP-8; 

GMD was 32.9 and 21.5 nm for JP-8 and FT-2, respectively and VMD was 92.8 and 63.2 

nm, respectively. APU FT particles were more dense than APU JP-8 particles, with 

average density values of 0.60±0.06 g cm-3 as opposed to 0.51±0.02 g cm-3 for JP-8.

 

Figure 29. Comparison of average PM emissions from DC-8 and APU testing for JP-8 

(red) and FT-2 (green) fuels.

5.0 Summary

Engine power dependent aerosol emissions were characterized using an extensive suite of 

instrumentation. Sampling protocol and inlet configuration was specifically designed to 
APPENDIX H

223

focus on a robust comparison of emissions from standard JP-8 jet fuel and four 

alternative jet fuels and to assess dynamic aging processes as aircraft emissions are 

diluted and cooled to ambient atmospheric conditions. The alternative fuels selected

were prepared by the Fischer-Tropsch (FT) process from natural gas and from coal 

feedstocks. The two inboard engines aboard the NASA DC-8 were used for testing and 

each produced a very similar emissions signature. Thus, one engine was used as a 

control and the other a test engine for assessing alternative fuel emissions.

Emissions from pure FT fuels were characterized by significantly reduced EIn and EIbc

compared to emissions from JP-8, and emitted particles were smaller and more dense. 

The largest emissions benefit for EIn is gained at low engine power. Consequently, a 

switch to FT fuels may be most beneficial to ground-level air quality improvement given 

the development of new air quality standards based on a shifting emphasis from particle 

mass to particle number concentration. The largest emissions benefit for EIbc is gained in 

the middle range of engine power (65% thrust level) and thus the benefits of FT fuels, on 

a black carbon mass basis, may be greatest at cruise altitudes. Thus, the use of FT fuels 

may have significant climate effects as black carbon plays a critical role in atmospheric 

dynamics and cloud formation processes (Koch and Del Genio, 2010) by both absorbing 

light and acting as an ice nucleus. 

By comparing emissions from JP-8, the two pure FT fuels, and the JP-8/FT blends, 

particle characteristics were found to vary directly with changes in fuel composition. EIn

and EIbc both varied positively with fuel aromatic content and were inversely correlated 

with hydrogen content. 

Downwind sampling resulted in emissions with very different properties at the engine 

exhaust plane compared to those sampled at two distances downwind. Initial emissions 

are characterized by a single soot mode comprised exclusively of black carbon. As the

exhaust plume cools and dilutes, new particle formation occurs significantly increasing 

particle number concentrations as well as volatile aerosol volume. The majority of new 

particle formation occurs by 30 m downwind, and number concentration increases are 

considerably smaller between 30 m and 145 m. Still, aerosol sizes continue to increase 

after 30 m because of particle growth and further gas-to-particle conversion. 

The new particle formation is highly temperature dependent as EIn increases with 

decreasing temperature; this dependence is most sensitive at low engine power consistent 

with the largest concentration of organic gas-phase precursors (Anderson et al. 2006). 

Temperature dependence is also observed for EIn and EIbc at the engine exhaust plane, 

suggesting that soot formation inside the engine is also sensitive to ambient temperature 

changes. Aerosol emissions from the aircraft’s APU were significantly greater compared 

to the DC-8 engine emissions. Use of FT fuels in the APU resulted in similar magnitude 

reductions in both for EIn and EIbc as were observed for the DC-8 engines. 
APPENDIX H

224

6.0 References

Anderson, B. E., G. Chen, and D. R. Blake (2006), Hydrocarbon emissions from a 

modern commercial airliner, Atmospheric Environment 40, 3601-3612.

Cheng, M.-D., E. Corporan, M. J. DeWitt, and B. Landgraf (2009), Emissions of volatile 

particulate components from turboshaft engines operated with JP-8 and FischerTropsch fuels, Aerosol and Air Quality Research 9, 237-256.

Chin, J. S., and A. H. Lefebvre (1990a), Influence of fuel composition on flame radiation 

in gas-turbine combustors, Journal of Propulsion and Power 6, 497-503.

Chin, J. S., and A. H. Lefebvre (1990b), Influence of fuel chemical-properties on soot 

emissions from gas-turbine combustors, Combustion Science and Technology 73, 

479-486.

Corporan, E., M. J. DeWitt, V. Belovich, R. Pawlik, A. C. Lynch, J. R. Gord, and T. R. 

Meyer (2007), Emissions characteristics of a turbine engine and research combustor 

burning a Fischer-Tropsch jet fuel, Energy and Fuels 21, 2615-2626.

DeWitt, M. J., E. Corporan, J. Graham, and D. Minus (2008), Effects of aromatic type 

and concentration in Fischer-Tropsch fuel on emissions production and material 

compatibility, Energy and Fuels 22, 2411-2418

Gulder, O. L. (1989), Influence of hydrocarbon fuel structural constitution and flame 

temperature on soot formation in laminar diffusion flames, Combustion and Flame 

78, 179-194.

Gulder, O. L., B. Glavincevski, and M. F. Baksh (1990), Fuel molecular-structure and 

flame temperature effects on soot formation in gas-turbine combustors, Journal of 

Engineering for Gas Turbines and Power-Transactions of the ASME 112, 52-59. 

Koch, D. and A. D. Genio (2010), Black carbon absorption effects on cloud cover, review 

and synthesis, Atmospheric Chemistry and Physics Discussions 10, 7323-7346.

Petzold, A., and A. Dopelheuer (1998), Re-examination of black carbon mass emissions 

indices of a jet engine, Aerospace Science and Technology 29, 355-356.

Rosfjord, J. Role of fuel chemical-properties on combustor radiative heat load (1987), 

Journal of Propulsion and Power 3, 494-501.

Sampath, P., M. Gratton, D. Kretschmer, and J. Odgers (1986), Fuel property effects 

upon exhaust smoke and the weak extinction characteristics of the Pratt and Whitney 

PT6A-65 engine, Jouranl of Engineering for Gas Turbines and Power 108, 175-181.

Timko, M. T., Z. Yu, T. B. Onasch, H.-W. Wong, R. C. Miake-Lye, A. J. Beyersdorf, B. 

E. Anderson, K. L. Thornhill, E. L. Winstead, E. Corporan, M. J. DeWitt, C. D. 

Klingshirn, C. Wey, K. Tacina, D. S. Liscinsky, R. Howard, A. Bhargava, Particulate 

emissions of gas turbine engine combustion of a Fischer-Tropsch synthetic fuel, in 

preparation.

Wey. et al. (2006), An overview of the Aircraft Particle Emission Experiment, NASA 

Technical Manual.

Wey, C. C., B. E. Anderson, C. Wey, R. C. Miake-Lye, P. Whitefield, and R. Howard 

(2007), Overview on the aircraft particle emissions experiment, Journal of 

Propulsion and Power 23, 898-905.
APPENDIX I

225

APPENDIX I: Influence of Ambient Temperature on the PM Emissions at the 

Engine Exit

Donald E. Hagen, Prem Lobo, and Philip D. Whitefield

Center of Excellence for Aerospace Particulate Emissions Reduction Research

G-7 Norwood Hall, Missouri University of Science and Technology, Rolla, MO 65409

Introduction

Several studies have been carried out to characterize emissions from military engines 

(Corporan et al., 2005, 2007) and, more recently, commercial jet engines burning 

alternative aviation fuels (Lobo et al., 2010). NASA spearheaded a study called AAFEX: 

Alternative Aviation Fuels Emissions Experiment, to evaluate the impacts of synthetic 

fuels on commercial aircraft engine gaseous and Particulate Matter (PM) emissions. The 

Missouri University of Science and Technology Center of Excellence for Aerospace 

Particulate Emissions Reduction Research (Missouri S&T COE) was a team member for 

AAFEX. 

The study was and was conducted in January 2009 in Palmdale, CA. The emissions tests 

were performed on the same CFM56-2C1 engine, mounted to a NASA DC-8 aircraft, 

which was studied during APEX-1 (Wey et al., 2007). The aircraft was parked on the 

runway, and emissions samples were extracted at the engine exit plane (1 m), in the near 

field (30 m), and in the advected plume (145m). The primary fuels used in this study 

were: JP-8, a Fischer-Tropsch fuel derived from natural gas (FT1), and a second FischerTropsch fuel derived from gasified coal (FT2). In addition to these fuels, 50:50 blends of 

the Fischer-Tropsch fuels and JP-8 were also studied. 

Instrumentation

The instrumentation onboard the Missouri S&T mobile laboratory to sample emissions at 

the engine exit plane consisted of the Cambustion DMS500, a state-of-the-art fast 

particulate spectrometer, to gather real-time size distribution information and total 

concentration of engine exhaust PM; a scanning differential mobility analyzer (SDMA) 

(TSI model 3071), to measure PM size distributions; a TSI condensation particle counter 

(CPC) (TSI model 3022) to measure total number concentration; a fast response carbon 

dioxide (CO2) detector to monitor sample dilution and establish emission factors. The 

instruments have been extensively used in recent field campaigns to measure PM 

emissions from commercial aircraft engines burning conventional and as well as 

alternative aviation fuels (Lobo et al. 2007; 2010; Herndon et al., 2008).

Methodology

One of the main objectives of the AAFEX campaign was to investigate the effect of 

changing test condition variables such as engine power, ambient temperature, fuel type, 

probe position, etc. on emissions characteristics of the CFM56-2C1 engine. Normally the 

procedure to investigate such dependencies would be to hold all parameters constant 
APPENDIX I

226

except for one, and measure the emissions as that parameter is varied. This procedure 

cannot be followed for ambient temperature. All the testing at AAFEX was conducted 

outdoors, and ambient temperature was dictated by nature. Large temperature variations 

were observed during the campaign, especially between early morning and late afternoon. 

This report summarizes and describes the results of AAFEX, in terms of the influence of 

ambient temperature on total PM emissions at the exit plane of a CFM56-2C1 engine.

In order to study the impact of temperature variation on PM emissions, two subsets of the 

entire AAFEX data set were selected, in which the fuel type and probe position were held 

constant while engine fuel flow (surrogate for power) and ambient temperature varied. 

The first data set chosen was for the reference fuel, JP-8, and the second data set was for 

the FT1 fuel. A third fuel, FT2, was also studied in the campaign. However during the 

time span for the FT2 measurements, the ambient temperature did not spread out over the 

temperature range as uniformly as was the case for JP8 and FT1 and hence this data was 

not incorporated into the following analysis. 

These data sets were organized into the form {Ti, FFi, apni, δapni}, where

FFi denotes the fuel flow during the i-th measurement,

apni denotes the measured value of the n-th aerosol parameter during the i-th 

measurement,

n = 1 refers to Dgn (number-based geometric mean diameter)

n = 2 refers to Dgm (mass-based geometric mean diameter)

n = 3 refers to EIn (number-based emissions index), 

n = 4 refers to EIm (mass-based emissions index).

δapni denotes the uncertainty in the measurement of aerosol parameter apni. 

These aerosol parameters were derived from size distributions measured using a 

scanning differential mobility analyzer.

Consider the group of test points {Ti, FFi, apni, δapni} for a fixed sampling location and 

fuel, but which span a range of ambient temperatures and engine fuel flow rates. A set of 

temperatures {Tj, j=1,2,...,J} and fuel flow rates {FFk, k=1,2,...,K} are selected which 

span the range of temperature and fuel flow rate represented in the data, and where 

possible fall near values where these parameters cluster. Two dimensional interpolation is 

employed to determine values for the aerosol parameter and uncertainty at these selected 

temperatures and fuel flow rates. A linear interpolation is accomplished with the software 

package Matlab, using Griddata and Meshgrid routines. Application of the interpolation 

method to the data set {Ti, FFi, apni, δapni} results in the interpolated data set {Tj, FFk, 

apnjk, δapnjk}. apnjk denotes the interpolated value for the n-th aerosol parameter at 

temperature Tj and fuel flow rate FFk; δapnjk is its associated uncertainty. In summary, for 

a fixed fuel type and sampling location, the data from test point set {Ti, FFi, apni, δapni} is 

interpolated to give aerosol parameter values at prescribed temperatures and fuel flow 

rates {Tj, FFk, apnjk, δapnjk}.

The range of temperatures encountered in the JP-8 data set (28–65°F) was larger than that 

for the FT1 fuel (34–58°F). In order to study the relationship between the temperature 
APPENDIX I

227

dependencies for the different fuels, the JP-8 data was interpolated a second time using 

the same temperatures used for the FT1 analysis. 

Results

Table 1 lists the interpolated emissions results for the FT1 fuel. The average aerosol 

parameters (Dgn, Dgm, EIn, and EIm) and their uncertainties are listed for the 

temperatures (°F): 34, 42, 47, 56, and 58, and fuel flow rates (lbs/hr): 1150, 2778, 3869, 

5385, 6597, and 7685.

Table 1. PM emissions parameters for the FT1 fuel. 

34 42 47 56 58

1150 11.46 ± 0.52 12.82 ± 0.73 15.70 ± 1.51 16.15 ± 1.89

2778 12.99 ± 0.94 13.53 ± 0.99 14.46 ± 0.96 16.09 ± 0.82 17.03 ± 1.82

3869 14.75 ± 1.84 13.93 ± 10.26 15.78 ± 7.77 19.10 ± 3.29 19.84 ± 2.30

5385 17.79 ± 0.42 17.27 ± 0.41 17.18 ± 0.37 17.01 ± 0.31 16.96 ± 0.32

6597 19.50 ± 0.35 20.09 ± 0.40 20.52 ± 0.42 21.25 ± 0.46 21.05 ± 0.38

7685 21.59 ± 0.46 22.59 ± 0.34 23.03 ± 0.37

34 42 47 56 58

1150 142.53 ± 24.21 136.84 ± 29.37 126.60 ± 38.66 125.12 ± 38.56

2778 118.09 ± 19.16 112.30 ± 56.71 108.68 ± 80.19 144.73 ± 24.68 118.32 ± 87.06

3869 39.44 ± 344.86 30.54 ± 240.27 49.32 ± 181.26 83.13 ± 75.06 90.65 ± 51.46

5385 40.75 ± 47.77 47.86 ± 6.30 53.51 ± 6.28 63.56 ± 6.32 65.31 ± 6.62

6597 44.87 ± 1.28 46.18 ± 1.20 47.09 ± 1.17 49.09 ± 1.21 51.73 ± 1.67

7685 52.52 ± 0.74 54.86 ± 0.94 56.75 ± 0.85

34 42 47 56 58

1150 0.173 ± 0.004 0.149 ± 0.003 0.107 ± 0.003 0.100 ± 0.003

2778 0.153 ± 0.007 0.115 ± 0.015 0.097 ± 0.010 0.066 ± 0.001 0.035 ± 0.001

3869 0.032 ± 0.001 0.066 ± 0.001 0.078 ± 0.002 0.100 ± 0.002 0.105 ± 0.003

5385 1.090 ± 0.010 0.777 ± 0.017 0.701 ± 0.015 0.564 ± 0.012 0.528 ± 0.012

6597 2.024 ± 0.018 2.028 ± 0.027 2.062 ± 0.032 2.109 ± 0.040 2.009 ± 0.033

7685 3.243 ± 0.029 3.477 ± 0.022 3.685 ± 0.030

34 42 47 56 58

1150 0.05 ± 0.10 0.06 ± 0.10 0.07 ± 0.10 0.07 ± 0.10

2778 1.59 ± 0.19 0.15 ± 0.11 0.18 ± 0.10 0.26 ± 0.09 0.13 ± 0.08

3869 0.02 ± 0.07 0.12 ± 0.21 0.14 ± 0.18 0.19 ± 0.12 0.20 ± 0.10

5385 1.07 ± 0.07 0.69 ± 0.08 0.67 ± 0.07 0.62 ± 0.06 0.63 ± 0.06

6597 3.10 ± 0.10 3.28 ± 0.11 3.51 ± 0.12 3.91 ± 0.14 3.81 ± 0.13

7685 7.46 ± 0.20 8.91 ± 0.26 10.15 ± 0.29

Fuel flow rate 

(lbs/hr)

Temperature (°F)

EIm (mg/kg fuel)

Fuel flow rate 

(lbs/hr)

Temperature (°F)

Dgm (nm)

Fuel flow rate 

(lbs/hr)

Temperature (°F)

EIn (1014/kg fuel)

Dgn (nm)

Fuel flow rate Temperature (°F)

(lbs/hr)
APPENDIX I

228

Table 2a lists the interpolated emissions results for the JP8 fuel. The aerosol parameters 

(Dgn, Dgm, EIn, and EIm) are given for the temperatures (°F): 28, 38, 45, 52, and 65, 

and fuel flow rates (lbs/hr): 1150, 2778, 3869, 5385, 6597, and 7685.

Table 2a. PM emissions parameters for JP-8 the fuel 

Table 2b lists another set of interpolated emissions results for the JP-8 fuel. The aerosol 

parameters (Dgn, Dgm, EIn, and EIm) are given here for the same temperatures used for 

28 38 45 52 65

1150 14.78 ± 0.14 14.51 ± 0.20 14.54 ± 0.26

2778 16.77 ± 0.54 17.51 ± 0.71 17.25 ± 0.59 16.04 ± 0.58 14.79 ± 0.42

3869 18.00 ± 0.79 17.85 ± 0.83 17.11 ± 0.63 16.09 ± 0.47 13.83 ± 0.54

5385 24.44 ± 0.32 24.25 ± 0.86 23.45 ± 1.08 23.96 ± 1.34 23.57 ± 0.37

6597 27.53 ± 0.55 27.89 ± 0.50 28.14 ± 0.46 28.39 ± 0.43 28.86 ± 0.36

7685 29.90 ± 0.41 30.14 ± 1.29 30.81 ± 1.42

28 38 45 52 65

1150 34.61 ± 3.57

2778 46.12 ± 13.76 47.47 ± 13.85 41.60 ± 7.10 38.56 ± 1.73

3869 49.70 ± 1.62 49.79 ± 2.51 47.80 ± 2.89 37.75 ± 1.41

5385 60.98 ± 0.61 59.49 ± 0.60 57.13 ± 0.61 58.07 ± 0.66 59.18 ± 0.91

6597 69.17 ± 0.71 70.17 ± 0.70 70.87 ± 0.70 71.57 ± 0.69 72.88 ± 0.68

7685 79.93 ± 0.84 81.14 ± 0.70 81.92 ± 0.64

28 38 45 52 65

1150 6.321 ± 0.113

2778 5.734 ± 0.058 6.339 ± 0.076 5.219 ± 0.038 5.088 ± 0.030

3869 3.204 ± 0.028 4.434 ± 0.100 5.217 ± 0.163 5.022 ± 0.077 4.621 ± 0.079

5385 5.870 ± 0.152 6.153 ± 0.143 6.485 ± 0.104 6.305 ± 0.130 4.861 ± 0.142

6597 7.307 ± 0.353 7.756 ± 0.298 8.070 ± 0.260 8.384 ± 0.222 8.968 ± 0.151

7685 13.650 ± 0.382 10.728 ± 0.245 8.957 ± 0.173

28 38 45 52 65

1150 26.80 ± 1.00 18.11 ± 0.69 11.28 ± 0.48

2778 14.46 ± 0.64 6.36 ± 1.92 7.04 ± 2.01 4.32 ± 0.91 2.98 ± 0.13

3869 4.57 ± 0.23 5.69 ± 0.25 6.16 ± 0.37 6.65 ± 0.46 7.00 ± 0.39

5385 19.79 ± 0.68 19.28 ± 0.63 17.71 ± 0.50 19.11 ± 0.60 16.40 ± 0.69

6597 37.36 ± 2.22 41.06 ± 2.03 43.64 ± 1.90 46.23 ± 1.77 51.03 ± 1.52

7685 93.24 ± 4.34 76.09 ± 2.83 68.45 ± 1.98

Fuel flow rate 

(lbs/hr)

Temperature (°F)

EIm (mg/kg fuel)

Fuel flow rate 

(lbs/hr)

Temperature (°F)

Dgm (nm)

Fuel flow rate 

(lbs/hr)

Temperature (°F)

EIn (1014/kg fuel)

Dgn (nm)

Fuel flow rate 

(lbs/hr)

Temperature (°F)
APPENDIX I

229

the FT1 interpolations, 34, 42, 47, 56, and 58°F, and fuel flow rates (lbs/hr): 1150, 2778, 

3869, 5385, 6597, and 7685.

Table 2b. PM emissions parameters for the JP-8 fuel calculated at the FT1 interpolation 

temperatures.

Figure 1 shows the dependence of EIn on temperature for fixed fuel flow rates for JP-8 

over its full ambient temperature range. EIn is observed to decrease with increasing 

temperature at the lower fuel flow rate (2778 lbs/hr) and highest fuel flow rate (7685 

34 42 47 56 58

1150 14.97 ± 0.13 14.53 ± 0.23 14.55 ± 0.28

2778 17.22 ± 0.68 17.78 ± 0.60 16.89 ± 0.59 15.85 ± 0.65 15.76 ± 0.68

3869 18.02 ± 0.94 17.54 ± 0.70 16.82 ± 0.59 15.47 ± 0.39 15.11 ± 0.43

5385 24.33 ± 0.64 24.18 ± 1.07 23.66 ± 1.22 23.84 ± 1.04 23.78 ± 0.89

6597 27.75 ± 0.52 28.03 ± 0.48 28.21 ± 0.45 28.53 ± 0.41 28.61 ± 0.40

7685 29.61 ± 0.53 29.80 ± 1.05 30.36 ± 1.45

34 42 47 56 58

1150 43.75 ± 9.93 34.71 ± 2.56

2778 44.60 ± 7.13 50.06 ± 16.77 45.74 ± 11.91 41.17 ± 4.17 40.96 ± 2.71

3869 48.86 ± 1.30 50.20 ± 2.15 49.52 ± 2.76 45.57 ± 2.65 43.83 ± 2.38

5385 60.08 ± 0.60 58.89 ± 0.60 57.43 ± 0.62 58.41 ± 0.74 58.58 ± 0.78

6597 69.77 ± 0.71 70.57 ± 0.70 71.07 ± 0.70 71.98 ± 0.69 72.18 ± 0.69

7685 78.78 ± 0.88 80.63 ± 0.76 81.48 ± 0.67

34 42 47 56 58

1150 5.730 ± 0.086

2778 5.127 ± 0.064 6.834 ± 0.092 6.009 ± 0.064 5.161 ± 0.044 5.132 ± 0.047

3869 3.869 ± 0.047 4.950 ± 0.148 5.395 ± 0.174 4.899 ± 0.078 4.837 ± 0.078

5385 6.040 ± 0.147 6.266 ± 0.140 6.486 ± 0.113 5.861 ± 0.134 5.639 ± 0.136

6597 7.576 ± 0.320 7.935 ± 0.277 8.160 ± 0.249 8.564 ± 0.200 8.654 ± 0.189

7685 13.058 ± 0.448 12.184 ± 0.304 9.757 ± 0.205

34 42 47 56 58

1150 20.29 ± 1.00 14.21 ± 0.57 9.32 ± 0.42

2778 8.46 ± 1.40 8.24 ± 2.49 6.24 ± 1.69 4.11 ± 0.51 4.01 ± 0.31

3869 4.99 ± 0.17 6.17 ± 0.33 6.15 ± 0.40 7.21 ± 0.48 7.16 ± 0.39

5385 19.48 ± 0.65 19.08 ± 0.61 18.36 ± 0.53 18.28 ± 0.63 17.86 ± 0.64

6597 39.58 ± 2.11 42.53 ± 1.96 44.38 ± 1.86 47.70 ± 1.69 48.44 ± 1.65

7685 87.09 ± 4.51 83.95 ± 3.53 70.85 ± 1.36

Fuel flow rate 

(lbs/hr)

Temperature (°F)

EIm (mg/kg fuel)

Fuel flow rate 

(lbs/hr)

Temperature (°F)

Dgm (nm)

Fuel flow rate 

(lbs/hr)

Temperature (°F)

EIn (1014/kg fuel)

Dgn (nm)

Fuel flow rate 

(lbs/hr)

Temperature (°F)
APPENDIX I

230

lbs/hr), whereas it increases modestly with increasing temperature at intermediate fuel 

flow rates 3869 lbs/hr and 6597 lbs/hr. It is independent of temperature at the mid fuelflow rate, 5385 lbs/hr. 

Figure 1. Number based emission index as function of temperature and fuel flow rate for 

JP-8

Figure 2 shows the dependence of EIm on temperature for fixed fuel flow rates for JP-8 

over its full ambient temperature range. EIm shows temperature-fuel flow rate trends that 

are similar to those for EIn.

Figure 2. Mass based emission index as function of temperature and fuel flow rate for 

JP-8

EIn vs Temperature for fixed Fuel Flow rate (JP-8)

0

2

4

6

8

10

12

14

16

20 25 30 35 40 45 50 55 60 65 70

Temperature (°F)

EIn (1014/kg fuel)

1150 2778 3869

5385 6597 7685

EIm vs Temperature for fixed Fuel Flow rate (JP-8)

0.00

0.01

0.02

0.03

0.04

0.05

0.06

0.07

0.08

0.09

0.10

20 25 30 35 40 45 50 55 60 65 70

Temperature (°F)

EIm (mg/kg fuel)

1150 2778 3869

5385 6597 7685
APPENDIX I

231

Data from Tables 1 and 2a can be examined to determine the significance of ambient 

temperature as a variable that influences PM emissions. The two metrics that are useful to 

characterize the strength of temperature with regard to influencing PM emissions are: 

Mcr = maximum change ratio, and Δ% = maximum percent change. 

For a fixed fuel type, fuel flow rate, and aerosol parameter, apn, Mcrn is defined as

Mcrn = |apn(Ta) – apn(Tb)| / (δapn(Ta) + δapn(Tb)), 

where Ta and Tb are the temperatures which give the maximum value this ratio for fixed 

fuel flow rate. 

When Mcrn ≤ 1 the error bars for the two temperatures overlap and the change in 

emissions between the two points is not statistically significant, i.e. there is no significant 

temperature effect for this case. When Mcrn ≥ 1 the error bars for the two temperatures 

do not overlap and there is a statistically meaningful change in emissions, i.e. there is a 

significant temperature effect for this case. 

The parameter Δ% gives the maximum percent change in aerosol parameter apn between 

two temperatures for the fixed fuel flow rate. Tables 3a and 3b present results for Mcr 

and Δ%. For JP-8 combustion (Table 3a) the aerosol parameter Dgn, does not show 

significant temperature change at the lowest and highest fuel flow rates (Mcr < 1), which 

yield percent changes of 2% and 3%. It does produce significant changes, up to 26%, at 

all other fuel flow rates. The mass based geometric mean, Dgm, likewise shows no 

significant temperature dependence at its lowest fuel flow rate, 2778 lbs/hr, but exhibits 

dependence at all higher fuel-flow rates. The emission index parameters, EIn and EIm, 

show significant change, exceeding 100% variation in one case, because of the 

temperature dependency. Hence the influence of temperature is significant and should be 

taken into account in the analysis of PM emissions data before influences of other 

operating conditions, e.g. fuel type, and be determined. For FT1 combustion (Table 3b) 

all aerosol parameters show significant temperature dependence (Mcr > 1), except for 

Dgm at the lower fuel flow rate conditions. Again, the aerosol parameters show large 

percentage changes because of temperature change, with several exceeding 100% 

change. The aerosol parameters for FT1 combustion exhibit a stronger temperature 

dependence than for JP-8 combustion; Δ%(FT1) exceeds Δ%(JP-8) 82% of the time, 

even though the JP-8 data spans a larger range of temperature change.
APPENDIX I

232

Table 3a. Change in emissions from JP-8 combustion due to temperature variation.

ap Fuel Flow rate (lbs/hr) Mcr Δ%

Dgn

1150 0.8 2

2778 2.4 17

3869 3.1 26

5385 1.3 4

6597 1.4 5

7685 0.5 3

Dgm

1150

2778 0.6 21

3869 3.9 28

5385 3.2 7

6597 2.7 5

7685 1.3 2

EIn

1150

2778 11.9 22

3869 17.4 48

5385 6.6 29

6597 3.3 20

7685 8.5 42

EIm

1150 10.5 82

2778 14.9 132

3869 3.9 42

5385 2.5 19

6597 3.7 31

7685 3.9 31
APPENDIX I

233

Table 3b. Change in emissions from FT1 combustion due to temperature variation.

ap Fuel Flow rate (lbs/hr) Mcr Δ%

Dgn

1150 2.1 34

2778 1.8 27

3869 1.2 35

5385 1.1 5

6597 2.2 9

7685 1.8 6

Dgm

1150 0.5 19

2778 0.6 28

3869 0.2 99

5385 1.4 46

6597 2.3 14

7685 2.6 8

EIn

1150 15.9 73

2778 18.8 126

3869 22.4 107

5385 25.6 70

6597 1.4 5

7685 7.5 13

EIm

1150 1.2 141

2778 5.4 171

3869 1.02 165

5385 3.4 52

6597 3.4 23

7685 5.5 31

An important question is whether PM emissions temperature dependency is fuel type 

dependent, i.e. can the temperature dependency be measured for one fuel type and then 

applied to other fuel types, or does the temperature dependency have to be measured 

separately for each fuel. This question can be studied by examining the correlations 

between the emissions for JP8 and FT1. Both of these fuels have data covering a 

common range of temperature and fuel flow rate. Emissions data for this comparison is 

restricted to cases where the aerosol parameters experienced statistically significant 

temperature change and had data available for at least three temperatures. Let CC denote 
APPENDIX I

234

the correlation coefficient between the two sets of temperature dependent data, for fixed 

aerosol parameter and fuel flow rate. Table 4 presents the correlation results for the 15 

cases that satisfied the above selection criteria.

Table 4. Correlation between the temperature dependence of JP8 and FT1 emissions.

ap Fuel Flow rate (lbs/hr) CC

Dgn

1150 1

2778 -0.93

3869 -0.97

Dgm

5385 -0.58

6597 0.33

7685 1

EIn

2778 0.29

3869 0.67

5385 0.36

6597 0.33

EIm

1150 0.89

2778 0.57

3869 0.98

5385 0.83

6597 0.98

The results in Table 4 indicate a lack of consistent correlation between fuel types for the 

aerosol shape parameters, Dgn and Dgm. They exhibit both strong positive and negative 

correlations for various fuel flow rates. The emission index parameters, EIn and EIm, 

show consistently positive correlations. EIm exhibits the stronger correlation, with an 

average correlation coefficient of 0.85. Further study is needed on this issue.

Conclusions

PM emissions data was collected over an ambient temperature range of 28 to 65°F. 

Significant dependencies on temperature were observed, with Mcr’s (maximum ratio of 

PM emission parameter change to experimental uncertainty) averaging 4.9 and 5.4, and 

ranging up to 17 and 26 for JP8 and FT1, respectively. The corresponding percentage 

changes in PM emission parameters due to temperature change, averaged 28 and 54 

percent, and ranged up to 132 and 170 percent, for JP8 and FT1, respectively. The 

correlation between the temperature dependencies for JP8 and FT1 were investigated. 

Fifteen cases exhibited sufficient significant temperature dependence to consider. The 

aerosol shape parameters, Dgn and Dgm, showed no consistent correlation. The emission 

index parameters, EIn and EIm, showed consistently positive correlations, with EIm 

having the stronger correlation with an average correlation coefficient of 0.85.
APPENDIX I

235

Acknowledgements

This work was partly funded by the Federal Aviation Administration (FAA) through the 

Partnership for AiR Transportation for Noise and Emissions Reduction (PARTNER) – an 

FAA/NASA/Transport Canada-sponsored Center of Excellence under Grant No. 07-CNE-UMR Amendments 006 and 007. The authors would like to acknowledge the 

AAFEX team, and NASA DC-8 personnel for substantial contributions to the successful 

execution of this study.

References

Corporan, E., Reich, R., Monroig, O., DeWitt, M., Larson, V., Aulich, T., Mann, M., and 

Seames, W., "Impact of Biodiesel on Pollutant Emissions of a JP-8-Fueled Turbine 

Engine", J. Air & Waste Manage. Assoc., 2005, 55, 940-949

Corporan, E., DeWitt, M., Belovich, V., Pawlik, R., Lynch, A.C., Gord, J.R., and Meyer, 

T.R., "Emissions Characteristics of a Turbine Engine and Research Combustor Burning a 

Fischer-Tropsch Jet Fuel", Energy & Fuels, 2007, 21, 2615-2626

Lobo, P., Hagen, D.E. and Whitefield, P.D., "Comparison of PM emissions from a 

Commercial Jet Engine burning Conventional, Biomass, and Fischer-Tropsch Fuels", 

manuscript in preparation 2010.

Wey, C. C., Anderson, B. A., Wey, C., Miake-Lye, R. C., Whitefield, P., Howard, R., 

"Overview on the Aircraft Particle Emissions eXperiment (APEX)", Journal of 

Propulsion and Power, 2007, 23, 898-905 

Lobo, P., Hagen, D.E., Whitefield, P.D., and Alofs, D.J., "Physical characterization of 

aerosol emissions from a Commercial Gas Turbine Engine", Journal of Propulsion and 

Power, 2007, 23, 919-929

Herndon, S.C., Jayne, J. T., Lobo, P., Onasch, T., Fleming, G., Hagen, D.E., Whitefield, 

P.D., and Miake-Lye, R.C., "Commercial Aircraft Engine Emissions Characterization of 

in-Use Aircraft at Hartsfield-Jackson Atlanta International Airport", Environmental 

Science and Technology, 2008, 42, 1877-18. 
APPENDIX J

236

APPENDIX J: Aircraft Engine Particulate: Macro- Micro- and Nanostructure by 

HRTEM and Chemistry by XPS

R. L. Vander Wal

Pennsylvania State University

Abstract

Carbonaceous particulate emissions from jet engine aircraft are a significant source of 

emissions near urban areas. Available mass measurements and particle numbers are few. 

Absent is any electron microscopic or spectroscopic characterization of the physical 

nanostructure or surface chemistry though both are extremely relevant towards assessing 

impacts of combustion-produced soot upon the environment and assessing health 

impacts. In this report, high-resolution electron microscopy (HRTEM) and X-ray 

photoelectron (XPS) data are presented for particulate emissions from a CFM-56-3 

engine aboard a DC-9 aircraft. Fuels studied included JP-8, Fischer-Tropsch and 50:50 

blends. Power levels were varied from 4% to 100%. Soot aggregate macrostructure, 

microstructure and nanostructure are discussed with respect to combustion conditions. 

Ultrafine particle size distributions at idle and near full power conditions are highlighted 

and compare favorably to reported scanning mobility particle sizer (SMPS) 

measurements. Particle composition as inferred from the XPS ratio for sp2/sp3 carbon is 

compared to results from thermo-optical evaluation of organic and elemental carbon 

analysis at selected powers with excellent agreement. 

The organization of this appendix is as follows:

1. Implications of jet engine produced PM2.5 nanostructure

2. Experimental details

3. Survey of macro- micro and nanostructure with power – comparisons across engine 

power levels by HRTEM

4. Nanostructure survey by lattice fringe analysis

5. Overview of aggregate populations with engine power

6. Summary of microstructure measurements

7. High resolution analysis of nanostructure of aggregate subpopulations with engine 

power

8. Chemistry dependence upon power – XPS analyses

9. Turbulent gas turbine environments

10. Conclusions

11. Acknowledgements

12. References

I. Introduction - Levels of Soot Structure

Relevance to the Environment and Human Health

The effect of particulate emissions upon atmospheric processes has received increasing 

recognition of their multiple roles. Depending upon their surface chemistry they can 

contribute to cloud formation. Soot particles can contribute directly to radiative forcing 

both directly by strongly absorbing solar radiation and indirectly through water-uptake 

and cloud activation [1-3]. The can interact with gaseous chemical species, especially in 
APPENDIX J

237

the near-field plume, and therein play a significant role in heterogeneous atmospheric 

chemistry [4]. 

Health effects associated with soot particles has received increasing recognition [5]. At 

airports emissions from aircraft idling, taxiing, taking-off and landing represent a 

significant source of particles into the surrounding (often urban) environment. 

[6]. Airport personnel and airline crews are exposed to varying degrees as well as the 

general flying public. As evidence, nearly everyone has "smelled" jet engine exhaust 

while outside the airplane. In this exhaust will be incidental combustion byproducts such 

as soot. Although soot aggregates’ size is generally beyond nanoscale, small aggregates 

containing one to a few primary particles (subunits) are less than 100 nm in geometric 

dimension and can penetrate to the deepest regions of the lung, the aveoli. Such deep 

penetration generally precludes their exhalation and results in their entrapment. 

Thereafter the biological response will depend upon their composition and surface 

chemistry.

Jet aircraft are a unique source of such particles, contributing to both ground pollution in 

and around airports but also are the primary source of such particles in the upper 

trophosphere and lower stratosphere [7, 8]. Because of their transitory nature, the 

characteristics of aircraft particle emissions are one of the least quantified relative to 

those from other pollution sources such as power plants, industry and transportation. 

Traditionally an emission inventory is the first step towards assessing a pollution source 

from which regional impacts are assessed by linking with transport models. To develop 

such emission inventories requires measurement of aircraft exhaust mass and particle 

numbers relative to fuel consumption. Concurrently emissions must be microscopically 

characterized to validate the suitability of traditional aerosol instruments given the 

variable nature of the particulate and that corresponding interpretations of mass and 

number distributions are accurate. 

Nanostructure & Chemistry

There are three levels of structure describing the soot particles. The first is aggregate 

morphology, the second is the degree of connectivity between the primary particles 

within the aggregate, and the third is the nanostructure of the individual primary particles. 

These three descriptors provide complimentary measures over a set of hierarchical length 

scales to cover geometry, morphology and atomic layer plane coordination. These are 

the parameters by which conditions of power and fuel are compared. 

Complimentary to high-resolution transmission electron microscopy (HRTEM) for 

physical nanostructure is X-ray photoelectron spectroscopy (XPS) analysis for carbon 

bonding. Moreover it can reveal surface chemistries such as oxygen functional groups 

and their bonding state as well. Nanostructure can be correlated to XPS data for carbon 

bonding leading to a comprehensive picture of particulate variations with engine power. 

HRTEM is particularly valuable given that it can reveal small particles that are difficult 

to observe using traditional aerosol measurement techniques. Both the particulate 
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nanostructure as extracted from the HRTEM data and composition as measured by XPS 

data change with engine power. 

Specific trends were found for each of these measures in response to test conditions and 

are summarized in this appendix. These variations guide inferences regarding the 

combustion conditions and state of mixing as dependent upon the engine power level. 

Supportive background is extracted from the combustion literature of laboratory flames 

and basic aerosol mechanics. 

2. Experimental Details

Table 1 summarizes the composition of the fuels in these tests. As detailed elsewhere in 

this report, engine powers were cycled in a staircase manner with the starboard engine 

running on the selected fuel with the port engine running on JP-8. As indicated, the FT 

fuels are essentially paraffinic in content, differing in their degree of branching (e.g. FTSasol would be characterized by a high degree of branching), whereas only JP-8 has a 

substantial aromatic component. 

Table 1.

n-Paraffins Iso-parffins Cycloparaffins Aromatics

FT-Sasol 87.6 12.0 0.4

FT-Shell 46.7 53.3

JP-8 19.0 31.3 31.0 18.7

Particulate Sampling

The sampling probe provided for direct collection of soot upon a TEM grid. The key 

advantage is the direct collection of the soot from the aerosol phase. This bypasses filter 

collection and therein the need for redispersal upon a TEM grid. Such processes are 

known to cause agglomeration of soot aggregates thereby obscuring individual 

aggregates. To permit HRTEM, lacey TEM grids were used. Further details of the TEM 

grid holder and its insertion into the sampling probe exhaust stream have been 

documented and will be published elsewhere [9].

XPS samples were collected using 400 stainless steel mesh coated with Ti/Au. These 

screens were held in 1.5-inch diameter HDPE filter holders along with a quartz tissue 

filter for added support. These units were inline with and downstream of the TEM 

sampling unit. For most conditions these screens did not appear overtly covered by soot 

with some metallic luster yet visible. The FT fuels did not yield sufficient particulate 

coverage to enable analysis. 

A valve upstream of the TEM sample holders permitted isolation of these units until the 

exhaust stream for the test condition of interest had cleared the line. By this user-defined, 

manual operation, samples were collected for a time somewhat shorter than the nominal 

test duration. Sample holders were periodically cleaned by a combination of wiping and 

swabbing with commercial grade rubbing alcohol. Multiple units allowed for pre-loading 

of TEM grids and gold coated screens for rapid insertion between test points as the 

engine was ramped up and down in power.
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With the primary emphasis being upon microscopy, partial or complete series sample sets 

as a function of engine power were obtained for JP-8 fuel. FT fuels yielded only 

sufficient particulate for these analyses at higher engine power levels as did the blends of 

JP-8 and FT fuels. 

Electron Microsocpy and Spectroscopy

TEM images were taken using a Phillips CM200 having nominal resolution of 0.14 nm 

with Gatan Image Filter (GIF) for digital imaging featuring live Fourier transforms 

having nominal resolution of 0.14 nm. The instrument was operated at 200 keV using a 

LaB6 filament. Gatan image software v. 3.4 was used for microscope operation. 

Generally four to six widely separated regions were examined on each grid primarily to 

ensure representative images and secondarily to ensure even coverage (as an indicator of 

flow uniformity and sampling by deposition). For any given power level, a range of 

nanostructure (variability) was evident across imaged particles, though trends with power 

were visually evident. These image data sets will be summarized in a NASA database. 

Representative images were selected to illustrate the observed trends for this report.

Digital images were acquired and subsequently processed using custom algorithms 

interfacing with the Optimus software package from Media Cybernetics. Selected images 

were analyzed for fringe length, separation and tortuosity as nanostructure parameters. 

Results were generally exported to the program KaleidaGraph for subsequent plotting 

and data analyses. Further details have been reported elsewhere [10].

The PHI 500 Series XPS instrument uses a conventional dual anode X-ray source (Mg & 

Al) with a 200’ hemispherical electron energy analyzer and a multi-channel detector. 

Analyzer electronics have an energy scan range of 0-4800 eV with a resolution of 

0.025eV minimum step size; the lens is an Omni-FocusTM III. The monochromatic Al Xray source has a variable energy range of 4kV to 15 kV with 300 W power in continuous 

operation. The sample stage can be moved and focused in three dimensions. 

High-resolution, multi-plex scans were run for carbon with a minimum of 10 sweeps and 

7 cycles. The resultant high-resolution C1s peak was curve fit using Gauss-Lorenz peaks 

and a Shirley fit. Peak deconvolution was performed via a MATLAB® program after 

setting the background parameters. Peak assignments are indicated in the individual 

spectra, allowing for shifts due to sample charging. Further details on the deconvolution 

procedure will be reported elsewhere [11].

Reproducibility of the high-resolution scans was high with 2-3 scans were taken over 

different sections of the filters. Such data collection was repeated over 2 different 

sessions. Differences in deconvoluted peak intensities were quite small relative to those 

differences observed between each soot sample.

3. Survey of macro- micro and nanostructure with power – Comparisons across 

engine power levels by HRTEM
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Figures 1-3 provide a side-by-side contrast of aggregate size, morphology and 

nanostructure. Details may be found in the captions for the corresponding figures. 

Figures 4-6 provide further comparisons across engine power levels of aggregate 

morphology, primary particle connectivity and nanostructure therein.

1. The soot aggregate morphology is a record of primary particle density and local 

concentration of growth species. As the (growing) aggregate evolves (traverses) over 

different regions of particle concentration and/or mixture fraction, variations in its 

compactness versus openness can occur. Aerosol clustering modes determine the 

morphology (e.g. reaction limited, ballistic or diffusion limited). These dynamics in turn 

depend upon the local concentration of constituent primary particles. High 

concentrations of primary particles result in reaction limited growth to produce a very 

compact aggregate whereas low concentrations lead to diffusion limited growth 

producing an open branched aggregate. In this manner morphology becomes a measure 

of the mixture fraction. 

Of course, as fuel-rich pockets are encountered during the spatial trajectory of the 

aggregate, each with their own fuel-air stoichiometry and resulting primary particle 

density, clusters will reflect such time-varied additions by the radial variation in their 

morphology.

2. Soot microstructure refers to the connectivity of the primary particles. This 

topolological metric reflects the gaps or lack thereof between primary particles. This 

depends upon the occurrence of continued mass growth once primary particles coalesce. 

The degree of connectivity then reflects the time of coalescence relative to growth. Early 

coalescence followed by continued growth leads to virtually unrecognizable primary 

particles (and "dense" aggregates). They become highly merged and are fused together. 

Alternatively late (or delayed) coalescence leads to near-point contact between individual 

primary particles. This results in clear geometric demarcation between them and an open 

branched aggregate form. Clearly intermediate regimes exist as well. Figures 1-6 

illustrate these two extremes. 

4. Nanostructure Survey by lattice fringe analysis

Other aerosol instruments are designed for measurement of aggregate size and these 

results are contained elsewhere in this report. Therein our focus was upon aggregate 

substructure, namely primary particle size and in particular, soot nanostructure. Figure 7 

conveys a HRTEM summary of primary particle nanostructure with engine power level. 

This data set came from an early test run and is observed to be consistent with data 

shown in Figures 1-6, demonstrating consistency of observations. Illustrative lattice 

fringe analyses for lamellae lengths results are summarized in Figure 7b. 

3. Soot nanostructure of course reflects the species available for soot growth. A uniform 

species such as C2H2 will contribute to particle growth via the HACA mechanism. 

Polycyclic aromatic hydrocarbons (PAHs) will contribute by a similar free radical 

addition mechanism. The former species (C2H2) can produce a well-ordered structure 

referred to as graphitic nanostructure. The latter species class (PAHs) is unable to 
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produce contiguous graphene layers given their varied sizes and range of possible 

orientations reflecting several potential radical sites per molecule. This results in various 

types of irregular (disrupted) nanostructure. Variations may include tortuous, chaotic or 

even interwoven lamella. In any event, there is less long-range structure, larger 

separation distance between lamella and less stacking order. 

A variation of nanostructure is the introduction of undulation in the form of curvature or 

tortuosity within lamella. Substantial local curvature in graphene layers arises by the 

incorporation of C5 (cyclopentadienyl) rings [12]. These species are not a fuel 

component. Instead they arise by gas phase chemistry involving oxygen. Partial 

oxidation of ethylene, a pyrolysis product, leads to acetaldehyde. Acetaldehyde is a wellknown combustion intermediate. Such species can be incorporated into aromatics, e.g. 

phenoxy radicals [13]. Its decomposition yields cyclopentadienyl radicals that are then 

incorporated into growing PAHs. Alternatively oxygen can produce odd numbered 

carbon fragments that can build up to C5 rings, e.g. C2 + C3 species. Readily produced 

in radical form and stable at elevated temperatures, cyclopentadienyl radicals readily add 

to growing lamella [14]. Their introduction produces curvature, the well-known 

"macromolecular" example being fullerenes. For this reason, curvature in lamella is 

referred to as fullerenic nanostructure.

With the degree of fullerenic nanostructure dependent upon the concentration of C5 rings 

[12] whose concentration in turn depends upon partial oxidation intermediates, by 

transitive relationship, the degree of fullerenic nanostructure thus depends upon the level 

of partial premixing. Higher premixing will lead to more fullerenic nanostructure or 

primary particles containing more fullerenic nanostructure until the fuel-air ratio becomes 

to low. 

5. Overview of aggregate populations with engine power

A particular advantage of TEM is the direct observation of particles. Differences in 

population size, morphology or microstructure are readily apparent. Traditional aerosol 

instruments are insensitive to particle micro- or nanostructure and generally possess 

cutoffs on the order of 10 nm. TEM examination of particles as deposited directly upon 

the grid revealed not only large aggregates but also a second size distribution composed 

of very small aggregates consisting of generally one to a few subunits, often highly fused 

together. Figure 8 are TEM images at two different magnifications of particulate 

collected from JP-8 using the 30-meter probe at a 4-7% power level. Figure 9 are 

corresponding TEM images at an 85% power level. In each case, the higher 

magnification image focuses upon one of the aggregates from the small-sized population. 

The apparent high-particle number density observed on the TEM grid is consistent with 

data from Corporan, (See Appendix X) who, using the condensation particle counter 

(CPC), measured a 10-22:1 ratio of the emission number index (EIn) for the 30-meter 

probe compared to the 1-meter probe. Such a large ratio suggests that the change 

(increase) in EIn measured using the 30-meter probe is due to condensation of volatiles 

during the transit time in the sampling probe [15]. A much smaller ratio was observed at 

high power, likely reflecting fewer volatile precursors and a lower nucleation rate.
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Lobo et al. speculate that low fuel flow rates correspond to relatively low linear velocities 

in the exhaust flow and hence longer residence times before the flow reaches the 30-m 

probe [16]. More time is then available for nucleation processes to boost the aerosol 

population the small size particle population. At high powers, high velocities and higher 

temperatures (and lower volatile concentrations) preclude nucleation via condensation, 

which is consistent with Corporan’s data (Appendix X) who measured dilution ratios 

based on CO2 using a non-dispersive infrared reflectance (NDIR). This explanation also 

accounts for the drastic decrease in number based emission with increasing engine power. 

[17].

6. Summary of microstructure measurements

Figure 10 presents a summary of the subunit sizes within these two very different 

aggregate distributions. Given a larger ultrafine particle population at the lowest power 

level, size measurements were performed on those samples. Cursory checks revealed no 

significant size difference between primary particles measured at the lowest and highpower levels (q.v. Figs. 8 & 9). 

To address the particle size distribution, Corporan employed a scanning mobility particle 

sizer (SMPS). With the JP-8 fuel, at 4% power two size distributions were observed, one 

with a mean near 15 nm and the other near 60 nm. These two size ranges roughly agree 

with the average as measured directly from those collected upon the TEM grid. At 85% 

power, a second size distribution was also observed on the TEM grids but not observed 

using the SMPS (albeit with a lower deposition density). Given that the second particle 

size distribution was near the size cutoff limit and that this size fraction was not related to 

volatile condensation, its absence from the ELPI spectra suggests a significantly lower 

number density. That there is a change in ultrafine particle size and in overall particulate 

elemental carbon content between low and high power suggests a difference in 

composition and nanostructure, as examined next.

7. High Resolution analysis of nanostructure of aggregate subpopulations with 

engine power

To investigate the origins of the small sized aggregates, high-resolution TEM was 

performed. These results are shown in Figure 11 for both the low and high engine power 

levels. As evident, the particle nanostructure varies greatly between the two data sets. 

An admixture of these nanostructures was observed at intermediate power levels. These 

will be analyzed and reported subsequent to this report.

The particle structure as observed in the HRTEM images suggests particle composition 

that is largely organic carbon at the low power level. The short disconnected and 

randomly oriented lamellae (where recognizable) are of a size consistent with 6 to 10 ring 

PAHs. The high proportion of edge sites suggests termination under atmospheric 

exposure by H-atoms. In contrast, the particles produced at high power demonstrate 

graphitic structure with lamellae of extended length and order. Both features are 

hallmarks of a carbonaceous particle comprised mainly of elemental carbon, consistent 

with the bulk elemental analysis as reported by Corporan in Appendix X of this report.
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8. Chemistry dependence upon power – XPS analyses

As reported for the APEX III campaign [9], XPS can provide a wealth of chemical 

information regarding both heteroatom content in addition to bonding configurations. 

For the single engine power studies in this campaign, changes in particle surface 

chemistry are of great interest for the aforementioned environmental and health 

considerations. Figure 12 shows the XPS data for three selected engine power levels. 

Deconvolution has been applied to the spectrum to resolve the carbon sp2, sp3 

components and oxygen functional groups, as illustrated. A monotonic trend with power 

is observed for increasing sp2 content at the expense of sp3 bonded carbon.

To address composition, Corporan et al. used a LECO Carbon Analyzer to determine the 

relative carbon composition (volatile or non-volatile/refractory). The curves were 

integrated below or above 325C to differentiate the volatile fraction versus non-volatile 

(refractory) carbon fraction. Limited by the collected mass, the lowest power for which 

the volatile fraction was measured was 45%. Here the volatile content was ~ 58%. Our 

XPS data yielded an sp2/sp3 ratio of 1.4 at 65%. This translates into an organic (sp3) 

content of ~ 42%. With the assumption that organic content is synonomous with volatile 

fraction, the agreement between these two very different techniques is remarkable. At 

85% power the LECO measured a volatile content of ~ 35%. Our corresponding XPS 

sp2/sp3 ratio of 2.3 for this same power level implies ~ 30% organic content, in excellent 

agreement. These different surface chemistries are mirrored by our HRTEM and XPS 

results. 

9. Turbulent Gas Turbine Environments

Figure 13 illustrates the complicated sequence of overlapping chemical and physical 

processes underlying soot formation and growth. Figure 14 schematically shows varied 

mixing in the turbulent combustion environment of the jet engine. These figures form the 

basis for the interpretative discussion.

The long graphitic lamella point to continuity of growth conditions and species while 

irregular nanostructure, bordering upon amorphous suggests varied growth environments 

that are insufficient to form ordered graphene layers. While it should not be surprising 

that the two structures originate at different powers, the observation of varied soot 

nanostructure with engine power is a unique observation that has not been reported 

elsewhere. Such variation could be used to aid modeling results of gas phase chemistry 

as reflected by the very different nanostructures. In this manner soot nanostructure offers 

an archeological record of the gas phase chemistry.
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10. Results

Figure 1. To establish the range of contrast of observed particulate emissions, shown 

above are images for the lowest (4-7% and highest (100%) engine power levels. At the 

lowest engine power, 4-7%, many particles, many sizes, were observed. Note the near 

single particles captured directly upon the lacey film. In contrast, at 100% power, the 

largest aggregates were generally less than 200 nm in equivalent diameter. At both 

powers, instead of highly branched morphologies, compact aggregates were prevalent in 

which the primary particles were highly fused.

That individual aggregates were clearly separate and distinct at the higher power levels 

provides an upper bound to their size. Given the potential for aggregate agglomeration 

upon the grid during collection, aggregate sizes are not presented for these conditions 

given this unknown bias at the lower power levels. Other aerosol instrumental measures 

presented elsewhere in the Appendices provide such data.
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Figure 2. Generally highly fused aggregate structures were observed, but with increasing 

power, individual primary particles became increasingly recognizable.

Figure 3. The comparative nanostructure between the two power settings is illustrated. 

At lower power nearly amorphous nanostructure was observed while at high power 

extended lamella organized into parallel stacks was found. The tortuous structure within 

the interior of the latter nanostructure is indicative of nonuniform growth reflecting 

primarily species and secondarily temperature. A variety of growth species would 

account for the irregular structure. In contrast very well defined ribbons around the 

particle perimeter suggests highly uniform growth conditions.

The perimeter of some primary particles (65% power) exhibits evidence of oxidation, not 

surprising given the exhaust conditions.
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Difficult to say whether nanostructure is more well defined at 85% versus 65%, given 

variation. However the fact that internal nanostructure is recognizable is strong evidence 

for continued change in gas-phase chemistry. 

Figure 4. An illustration of changing aggregate size scale and morphology with 

increasing power level. The image at 65% power further illustrate aggregate size 

decrease (containing fewer primary particles) at higher power levels compared to lower 

powers. At 85% power the general trend of decreasing aggregate size is maintained in 

addition to decreasing primary particle. That individual aggregates were clearly separate 

and distinct at the 100% power level provides an upper bound to their size. 
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Figure 5. An illustration of the changing connectivity within the aggregate. While 

individual primary particles are largely undefined at low power, with increasing power 

primary particles become increasingly recognizable. Even at intermediate powers such as 

65%, aggregate microstructure can consist of dense portions with notable lack of subunit 

definition. At 85% power, very distinct primary particles were observed, but generally 

along the aggregate perimeter. The variation in aggregate microstructure with radius (e.g. 

100% power) suggests varying aerosol dynamics. Initial growth produced highly 

coalesced aggregates while individual primary particles formed at later times remained 

separate, only undergoing agglomeration at later times. 
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Figure 6. An illustration of the nanostructure evolution with increasing power level. At 

intermediate powers, recognizable lamella become increasingly recognizable within 

primary particles. In general they are not well ordered or highly stacked but clearly 

measurable. The tortuous structure of the nanostructure at intermediate power levels is 

indicative of non-uniform growth conditions reflecting varied species contributing to the 

particle growth. At higher powers, such as at 65%, very well defined ribbons around 

particle perimeters suggest highly uniform growth conditions. The perimeter of some 

primary particles (65% power) exhibits evidence of oxidation, not surprising given the 

high temperature exhaust conditions. It is difficult to judge whether nanostructure is 

better ordered at 85% versus 65% power, given observed variations at each condition. 

However the fact that internal nanostructure is recognizable is strong evidence for 

continued change in gas-phase chemistry relative to the lowest power level. At 100% 

power graphitic ribbons were common. Yet the overall nanostructure of the primary 

particle is not uniform but irregular, suggesting rather variable growth conditions in 

temperature and species.
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Figure 7. From early survey samples across engine powers, these were selected for

image analysis, based on JP-8 fuel and a 1-meter sampling probe. Consistent with the 

aforedescribed data, there is a progressive increase in nanostructure order with increasing 

power. Going from amorphous at the lowest power, lamella become increasingly distinct 

and organized in stacks with increasing power. At the highest levels, extended lamella 

wrap the particle perimeter. These changes are quantified by the lattice fringe analyses 

shown in Fig. 6b for fringe (lamella) length. 

Figure 7b. Quantification of the HRTEM images can provide several statistical metrics 

describing the nanostructural order. Above are shown histograms of the lattice fringe 

length. There is a progressive change towards more graphitic structure with increasing 

power, but as shown, the level of graphitic nanostructure quickly asymptotes.
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Figure 8a. The most notable find of this sample and those from other tests is the plethora 

of nanoparticles at the lowest power setting, 4-7%. They generally consist of only a few 

individual subunits (aka primary particles), often only one. Their high occurrence is 

evident on the lowest magnification image. These are clearly a health hazard and will not 

be filtered by normal airway mechanisms. The very fact that they survive the 30-meter 

sampling probe demonstrates that they appear remain separate and do not agglomerate.

Figure 8b (continued). A higher magnification image of the (small) individual 

aggregates.
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Figure 9a. Though small particles (< 50 nm diameter) were generally absent at midrange power levels, but were again present at high power settings, though with an 

apparent lower number density, based on observed surface deposition upon the lacey 

grid.

Figure 9b. As illustrated, the small particles at the high power were similar in size and 

number of primary particle subunits relative to those at the low "idle" power level of 4-

7%.
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Figure 10. Variation in primary particle size with power level. There are two very 

different particle size populations based upon visual interpretation of the TEM grids, 

thereby accounting for the two plots.

Figure 11a. Comparative nanostructure of the small aggregates as a function of power. 

The amorphous nanostructure of the particles is made clear by comparison to the adjacent 

lacey grid which is composed of an amorphous carbon film.
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Figure 11b. Unlike the ultra-small particles observed at the low power, those at 85% 

(and 100%) power levels manifested a highly graphitic structure, quite similar to the large 

aggregates. Extended lamella often in stacks was were prevalent, again at the particle 

perimeter, suggesting similarity of growth environments or at least species continuity for 

these small aggregates and large aggregates at later particle growth stages.

Figure 11c. A final image pair to contrast the nanostructure differences observed 

between the low and high power engine levels.
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Figure 12a. Soot surface chemistry for jet engine produced soot using ultra low sulfur 

JP-8 fuel pertains mainly to oxygen functional groups. A high resolution scan over the 

C1s region illustrates the distribution of oxygen functional groups, phenolic, carbonyl 

and carboxylic in addition to differentiating between sp2 and sp3 carbon bonding. The 

ratio of sp2/sp3 can be considered as the ratio of organic to elemental carbon. For this 

low engine power, the carbonaceous particulate is mainly organic, reflecting considerably 

akyl-group (saturated hydrocarbon) content.

Figure 12b. With increasing engine power, the particulate bonding shifts from organic 

to elemental carbon as evidenced by the decrease in sp3 bonding and commensurate 

increase in sp2 carbon bond hybridization.
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Figure 12c. At high engine powers, consistent with the graphitic physical 

(nano)structure revealed by HRTEM, the physical bonding mainly consists of C-C sp2, 

characteristic of graphitic carbon (or graphitic-like lamella). Notably the surface oxygen 

content is far less than at lower engine powers.

Figure 13. The soot formation process is quite complex consisting of several concerted 

processes of fuel pyrolysis, aromatic growth, particle inception, growth and oxidation.
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Figure 14. In reality the fuel-spray within the highly turbulent jet engine will consist of 

recirculation zones, fuel-rich pockets and varying levels of oxidation exposure. These 

spatial regions are conceptually illustrated above.

11. Conclusions

Regarding particulate (soot) macrostructure, in general, power level (fuel concentration 

and mixing) governs local fuel-air equivalence ratio. The implication as suggested by our 

observations is that soot aggregate morphology is a record of primary particle density and 

local concentration of growth species. 

Regarding particulate (soot) microstructure, mixing controls timescale of coalescence 

relative to growth. The implication as borne out by our observations is that early 

coalescence followed by continued growth leads to virtually unrecognizable primary 

particles as they are highly merged and are fused together. This reflects a high 

hydrocarbon concentration, rapid particle nucleation and subsequent growth. 

Alternatively late coalescence leads to near point contact between primary particles. This 

reflects a lower hydrocarbon concentration, with delayed particle formation and 

coalescence.

Regarding particulate (soot) nanostructure, it reflects the species available for growth. 

Fuel-air mixing produces oxygenated intermediates that lead to C5 species introducing 

curvature in nanostructure. A single species such as C2H2 will contribute to uniform and 

ordered growth of carbon lamellae. Alternatively PAHs will contribute by a similar free 

radical addition mechanism but given their varied sizes, will not be able to orderly 

template upon the particle resulting in disrupted nanostructure that can give rise to a 

nanostructure that appears textured, (in which the graphene layers appear "woven"), 

chaotic (where the graphene layers have no orientational order) or amorphous (an 

absence of recognizable graphene segments).
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Results presented here for low engine powers confirm the high relative concentration of 

ultrafine particles as secondary aerosols arising from the condensation of heavy 

hydrocarbons. With a nominal size of ~ 10 nm or less, these nucleation mode particles 

challenge traditional aerosol measurement instruments. In contrast HRTEM is ideally 

suited for their physical characterization. Though abundant in number, collectively this 

size mode contains very little mass. This challenges other traditional analytical chemistry 

techniques. X-ray photoelectron spectroscopy can decipher both elemental composition 

and carbon hybridization state. This latter ability is particularly useful for differentiating 

elemental and organic carbon, a key distinguishing characteristic of nucleation mode 

particles. 

While a particle mode consistent with the nucleation size mode is observed at high engine 

powers, both HRTEM and XPS reveal these particles to be largely elemental carbon. The 

origin of these particles is clearly not secondary nucleation of volatile organics, though 

they are within the "nucleation" size range. These particles either arose by oxidative 

breakup of larger aggregates or perhaps by carbonization of small particles of condensed 

phase organics. Necessarily requiring elevated temperatures, this carbonization would 

have occurred inside the engine. These observations reveal the importance of combining 

electron microscopy and spectroscopy techniques with traditional aerosol measurements.

With regards to environmental implications, the presence of significant oxygen content 

upon the soot surfaces can potentially render them hydrophilic or at the very least aid 

condensation of polar emission species such as NOx and SOx. Both could potentially be 

converted to nitrate and sulfate species. In such a process the soot particles effectively 

heterogeneously catalyze formation of mixed nitrate and sulfate aerosols. 

With regards to human health concerns, the ultra-fine particles (nanoparticles) at the 4-

7% low power (idle) and high power (takeoff) engine levels are clearly a health hazard 

and will not be filtered by normal airway mechanisms. The very fact that they survive to 

the 30-meter probe illustrates that they do not to agglomerate nor deposit upon surfaces 

but remain separate and suspended. Thus the ambient air at and around airports is clearly 

hazardous during normal jet operations.

From these observations we conclude that engine specific conditions that control fuel-air 

mixing and the number and degree of fuel-rich pockets govern carbonaceous aerosol 

production. This does not discount fuel effects that could contribute, but in the absence 

of a sufficient number of reference samples from the FT1 and FT2 fuels, definitive 

conclusions for this report from the present limited data set cannot be reached. 

12. Acknowledgements

The author gratefully acknowledges sample collection during the weeks of field 

campaign testing by Dr. Kathleen Tacina (NASA-Glenn) and overall project coordination 

and experimental assistance and support by Dr. Bruce Anderson (NASA-Langley). 

Vicky M. Bryg (USRA) is acknowledged for TEM and XPS work and fringe analyses 

and Mr. Chung-Hsuan Hunag (Penn State University) for sizing analyses and Dr. 

Corporan (WPAFB) for graciously sharing his experimental data prior to publication. 
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Support for this work was through the NASA Aeronautics Subsonic Fixed Wing (SSFW) 

Program, NASA Cooperative Agreement NNX09AD42A with The Pennsylvania State 

University, at University Park PA.

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Environ. Sci. and Technol. 43:4620-4625 (2009).

6. Samet, J., M., Dominici, F., Curriero, F. C., Coursac, I., and Zeger, A. L., Fine 

Particulate Air Pollution and Mortality in 20 U.S. Cities, 1987-1994, New England 

Journal of Medicine Medical Progress Series, 343, 1742-1749 (2000).

7. Hagen, D. E., and Whitefield, P. D., Particulate emissions in the exhaust plume form 

commercial jet aircraft under cruise conditions, Journal of Geophysical Research, 

Atmospheres, 101, 19551-19557 (1996).

8. Penner, J. E., Lister, D. H., Griggs, D.J. Dokken, D. GJ., and McFarland, M., (Eds.) 

Aviation and the Global Atmosphere, Intergovernmental Panel on Climate Change Rept., 

Cambridge Univ. Press, Cambridge, England, U.K. p. 373 (1999).

9. Vander Wal, R. L., Aircraft Engine Particulate: Macro- Micro- and Nanostructure by 

HRTEM and Chemistry by XPS (Atmospheric Environment, to be submitted).

10. Vander Wal, R. L., Tomasek, A. J., Pamphlet, M. I., Taylor, C. D., and Thompson, 

W. K., J. of Nanoparticle Research 6 (2004) 555-568.

See also, Vander Wal, R. L., Tomasek, A. J., Street, K. W., Hull, D. R., and Thompson, 

W. K., Applied Spectroscopy 58:230-237 (2004).
APPENDIX J

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11. Vander Wal, R. L., Bryg, V. M., and Hays, M. D., XPS Analysis of Combustion 

Aerosols for Chemical Composition, Surface Chemistry and Carbon Chemical State 

(Analytical Chemistry, submitted).

12. P. J. F. Harris, S. C. Tsang, Philos. Mag. A 76:667-677 (1997). 

13. Norton, T. S., The combustion chemistry of simple alcohol fuels, PhD thesis, 

Princeton Univ., Princeton, NJ, 1990. See also, Norton, T. S., and Dryer, F. L., Proc. 

Combust. Inst. 23 (1990), pp. 179–185.

14. McEnally, C. S., and Pfefferle, L. D., Experimental study of nonfuel hydrocarbons 

and soot in coflowing partially premixed ethylene/air flames, Combustion and Flame 

121:575-592 (2000).

15. Wey, C. C., Anderson, B. E., Wey, C., Miake-Lye, R., Whitefield, P., and Howard,

R., Overview on the Aircraft Particle Emissions Experiment. J. of Propulsion and Power, 

23:898-905 (2007).

16. Lobo, P., Hagen, D. E., Whitefield, P. D., and Alofs, D. J., Physical Characterization 

of Aerosol Emissions form a Commercial Gas Turbine Engine. J. of Propulsion and 

Power 23:919-929 (2007).

17. Vander Wal, R. L., Soot Nanostructure: Physical and Chemical Characterization

Invited presentation, APEX III, Cleveland, OH Nov. 29th – Dec. 1st, (2006)
APPENDIX K

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APPENDIX K: Composition of Gas Turbine Engine Combustion Volatile Particle 

Material

M. T. Timko, Z. Yu, S. C. Herndon, E. C. Wood, R. C. Miake-Lye

Aerodyne Research Inc.

Billerica, MA 01821

Author’s note: This Appendix summarizes results from laboratory studies, APEX-3, 

AAFEX, and the Midway Airport 2009 study. This report is based on a Final Report 

submitted previously to NASA describing activities under contract # NNC07CB57C. We 

acknowledge as outstanding issues of further inquiry: 1) the mass balance closure gap 

between integrated SMPS measurements and the AMS, 2) effective density and shape 

factor analysis of the non-volatile soot PM by comparison of SMPS (and/or EEPS) 

mobility diameter data, to AMS vacuum aerodynamic diameter data, to electron 

microscopy data.

Introduction

In this report, we summarize on-going efforts to analyze the composition of volatile PM 

emitted from gas turbine engines. The report describes some of the effects of engine 

technology and fuel composition on volatile PM composition. Specifically, the report 

contains the following

1) raw fuel aerosol mass spectrometer analysis;

2) aerosol mass spectrometer analysis of jet fuel combustion PM emitted from a 

laboratory diffusion flame burner;

3) mathematical analysis of the APEX-3 data set to identify the effects of engine 

technology on volatile PM composition;

4) detailed analysis of the AAFEX data set to identify the effects of fuel composition on 

volatile PM composition.

Raw Fuel Analysis

We used the aerosol mass spectrometer (AMS) to analyze a petroleum jet fuel and 

synthetic jet fuels manufactured using the Fischer-Tropsch (FT) process. For these tests, 

we acquired 2 FT fuels from AFRL, one produced by Syntroleum ("FT-Syntroleum"

fuel), the other by a proprietary Company B ("FT-B" fuel). Figure 1 shows the diffusion 

flame spectra of the three fuels. All three spectra share characteristics common to 

fragmentation of compounds in a hydrocarbon matrix, chiefly the prominent peaks at m/z 

27 and 29, 41 and 43, 55 and 57, 69 and 71, 83 and 85. Because the oxygen content of 

the fuels is negligible, we can confidently assign these peaks to the C2-C6 series. The 

ratio of nearby peaks to one another (e.g., 41 and 43) is a measure of the degree of 

unsaturation of the hydrocarbon fragments, and indirectly, of the parent hydrocarbon 

matrix. For example, m/z = 41 corresponds to the unsaturated molecular ion C3H5

+

whereas m/z = 43 corresponds to the saturated ion C3H7

+

. The two 
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Figure 1. Raw Fuel Particle Mass Spectrometer Data. Aerosol mass spectra of FTSyntroleum, FT-B, and Jet-A jet fuels.

series result from fragments with the formulas CnH2n-1

+ and CnH2n+1+

, respectively, and 

are sometimes referred to as the n = 0 and n = 2 series. The ratios CnH2n+1+ (e.g., m/z 42) 

to CnH2n-1

+ (e.g., m/z 41) series are on the order of 1.5 for both the FT-B and Jet-A jet 

fuels. For the FT-Syntroleum fuel, the ratio is much higher, approximately 2.5. Another 

key difference in the three fuels is that the Jet-A spectrum contains more large ion 

fragments (defined here as m/z > 71) than either FT fuel. Likewise, the FT-Syntroleum 

spectrum contains more large fragments than the FT-B spectrum.

At this point, we attempted to extract molecular information from the differences in the 

two FT fuel mass spectra. As a starting point, we used the results of the AFRL chemical 

analyses of the jet fuels. Interestingly, the AFRL analysis for both the FT-Syntroleum 

and FT-B fuels indicate no difference in their content of olefinic, aromatic, or cyclic 

compounds – the three primary sources of unsaturated compounds in jet fuel mixtures. 

Instead of unsaturation, AFRL indicates that the primary differences between the two FT 

fuels are: 1) the carbon chain distribution of FT-B fuel is narrower than for the FTSyntroleum fuel, with the FT-B fuel distribution centered at C9, C10, and C11, and the FTSyntroleum fuel containing substantial (~5%) components as large as C16; 2) the 

percentage of linear paraffins in much higher in FT-B fuel (53.3 vol%) than FTSyntroleum fuel (17.2 vol%). The increased prominence of large mass fragments (m/z > 

71) in the FT-Syntroleum spectrum is consistent with the larger hydrocarbon chains 

present in the original fuel. The difference between the saturated/unsaturated mass 
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262

spectra of FT-B fuel and FT-Syntroleum fuel is likely due to differences in branching. 

According to McLafferty and Turacek (p 226 of Interpretation of Mass Spectra, 4th Ed., 

1993), we expect that more branching would lead to an increased importance of the 

CnH2n+1 series, consistent with the mass spectra data. Interestingly, the ratios of CnH2n+1

to CnH2n-1 peaks in Jet-A are comparable to FT-B, despite the fact that branching in JetA is comparable to FT-Syntroleum (roughly 18 vol%). The enhanced CnH2n-1 series in 

Jet-A is likely due to the presence of aromatic (15 vol%), cyclic (20%), and olefinic (1%) 

compounds in the Jet-A fuel. Both olefinic and cyclic compounds have enhanced CnH2n-1

signals relative to linear paraffins. 

The extension of the Jet-A mass spectrum to larger masses than either FT fuel is 

consistent with its increased aromatic content. Aromatic compounds tend to be stable 

during ionization and yield a greater percentage of parent ions than olefinic or paraffinic 

compounds. Moreover, like FT-Syntroleum, Jet-A contains substantial mass in larger 

hydrocarbons (~5% in C16). Therefore, the extension of the Jet-A spectrum to mass 

larger than FT-B is likely due to the larger hydrocarbon molecules in the fuel matrix. 

The extension of the Jet-A spectrum beyond FT-Syntroleum may be due to the presence 

of aromatic compounds in Jet-A.

In summary:

1) the increased prominence of the CnH2n+1 series in the FT-Syntroleum spectrum 

relative to FT-B is due to its increased branching ratio (only 17% of its content is 

in linear alkanes compared to 53% for FT-B);

2) the increased prominence of the CnH2n-1 series in Jet-A relative to FT-Syntroleum 

is likely due to the presence of olefins and cyclic compounds in Jet-A;

3) the cyclic/olefinic compounds present in Jet-A balance its high degree of linear 

paraffins resulting in CnH2n+1 series which are comparable to FT-B;

4) the FT-Syntroleum and Jet-A spectra extend to much higher m/z’s than FT-B, 

consistent with the former to fuels containing more long-chain hydrocarbons than 

the former;

5) the Jet-A spectrum extends to slightly higher m/z’s than FT-B, which may be 

consistent with either more long-chain hydrocarbons in the Jet-A fuel or more 

aromatic content in the Jet-A fuel.
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Laboratory Combustion Particles

We performed tests using a laboratory diffusion flame burner and liquid jet fuels (JP-8, 

FT fuel, and a biofuel). Figure 2 provides representative results obtained while operating 

with a very fuel rich (orange) flame. The characteristic peaks of PAH ranging from 

C16H10 to C34H16 are present in the fuel-rich JP-8 diffusion flame spectrum. In contrast to 

HPLC analysis of filter samples during the PW308 tests, which found that fluorene 

(C13H10) and pyrene (C16H10), C22H12 is the dominant PAH formed in the fuel-rich JP-8 

diffusion flame. We wanted to understand two aspects of the PAH data: 1) whether the 

differences between the PW308 data and the laboratory flame data could be attributed to 

differences in combustion conditions or sampling conditions and 2) what effects fuel 

composition might have on the diffusion flame particles.

Figure 2. Particle-bound PAH Formed in Laboratory Burner. Mass spectrometer 

composition data obtained for JP-8 combustion in a laboratory diffusion flame burner.

We performed jet fuel diffusion flame tests for JP-8, three different FT fuels (Sasol, 

Syntroleum, and Shell), and a biofuel. NASA and AFRL technical staff helped us obtain 

the fuel samples for our tests. We performed the tests under fuel lean (blue flame) and 

fuel rich (orange flame) conditions. Figure 3 shows the PAH results for the various fuels 

tested. A drawback to our diffusion flame burner is that it lacks fuel flow and fuel/air 

ratio diagnostics. Qualitatively, the data in Figure 3 seem to have been collected during 

less fuel rich conditions than the data in Figure 2. Comparing the two PAH distributions, 

the very rich conditions tested for Figure 2 produced a broad range of PAH compounds 

whereas less rich conditions tested in Figure 3 produced only the C16H10 pyrene peak. 

The PAH product spectrum shift strongly suggests that combustion conditions play an 

important role in the PAH product spectrum.
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Figure 3. Particle-bound Pyrene Formed in Laboratory Burner. Laboratory diffusion 

flame results for combustion of various fuels highlighting production of the C16H10 PAH.

We analyzed the Figure 3 spectrum quantitatively to verify that it is likely pyrene and to 

compare the effects of fuel composition on PAH production as a function of fuel 

characteristics. The NIST mass spectrum for pyrene is showed in Figure 3; the close 

match in the isotopic pattern recorded by NIST and that measured in the laboratory 

confirms the identification of a C16H10 PAH. Figure 3 carries quantitative content that 

indicates a major difference in PAH production for combustion of the various fuels. The 

relative peak heights of the m/z 202 molecular fragment are labeled in Figure 3 and the 

order is clearly JP-8 >> FT (Sasol) > biofuel. The three FT fuels behaved similarly, and 

pyrene was always the primary PAH product formed for all 5 fuels. Thus, not only do we 

find that changing the fuel/air ratio changes the PAH product distribution, but we also 

find that varying fuel composition can change the quantity of PAH compounds formed. 

Consistent with previous studies, we speculate that the negligible aromatic content of the 

FT fuels leads to their reduced PAH production. The reduced PAH production of the 

biofuel is more confusing since the AFRL assay indicates that it contains 13.1 vol% 
APPENDIX K

265

aromatic content. JP-8 typically contains between about 14-20 vol% aromatic so the 

biofuel is in a similar range to petroleum jet fuel. We speculate that the aromatic 

distribution in the biofuel may be different than in the JP-8 and that specific fuel aromatic 

compounds (e.g., multi-ring aromatic compounds) or other fuel hydrocarbon compounds 

(e.g., naphthenes) may play a disproportionately large role in PAH formation. PAH 

production for biofuel combustion is an interesting as of yet unresolved issue that bears 

further investigation.

We analyzed rich diffusion flame products using high resolution mass spectrometry for 

JP-8, FT Sasol, and biofuel. Figure 4 provides results of the diffusion flame tests. The 

m/z 41 peak is always dominated by C3H5

+ without even traces of the oxygenated 

C2H3O+ fragment, a trend that is consistent with fragment stability patterns. The m/z 43 

peak, however, shows a strong contribution for both C3H7

+ and the oxygenated fragment, 

C2H3O+. The C2H3O+/C3H7

+ integrated peak area ratios increase sharply from 0.44 for 

JP-8 combustion to more than 0.7 for both the biofuel and the FT fuel. The oxygen 

content therefore increases from 11% for the JP-8 combustion particles to 16% for the 

other two fuels. 

Figure 4. High Resolution Mass Spectra of Diffusion Flame Particles. High resolution 

mass spectrometer data for rich jet fuel diffusion flame data for JP-8, a FT fuel, and a 

biofuel.

In addition to fuel composition, fuel/air ratio also plays a role in the oxygen content. A 

very rich JP-8 diffusion flame produced PM with a C2H3O+

/C3H7

+ of about 10%, 

corresponding to an oxygen content of about 2.6%. Therefore, decreasing the fuel/air 
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266

ratio increases the oxygen content of the combustion PM. In terms of physical behavior, 

we anticipate that the biofuel/FT fuel combustion particles produced at lower fuel/air 

ratios would be more hygroscopic than the very rich-flame JP-8 particles. The 

hygroscopicity differences should in turn influence the environmental fate of the 

combustion PM. Extending the detailed high resolution mass spectrometer composition 

information to aircraft particles might prove useful.

Gas Turbine Engine Particle Emissions 

Refined Analysis of APEX-3 Data. 

We have analyzed our APEX-3 volatile PM composition data set using a pattern 

recognition tool termed positive matrix factorization (PMF). Although we originally 

presented preliminary results during the APEX-3 results workshop in November 2006, 

improvements in the PMF algorithm itself, the application of the PMF algorithm to 

volatile PM composition data, and our understanding of the APEX-3 results (largely due 

to our continuing efforts as part of this NRA) made re-analyzing the APEX-3 data set an 

important and productive activity. We include the results here as they provide important 

insight into the effects of combustor technology on volatile PM composition.

PMF is a powerful pattern recognition technique that has been applied to many AMS data 

sets to extract information and apportion a data set between various sources. As an input, 

PMF takes the mass spectrometer signals, the mass spectrometer uncertainties (based on 

statistical averaging), and the number of sources to be assigned. As an output, PMF 

identifies sets of mass spectra signals that tend to track one another. Each of these sets of 

signals potentially represents a separate source or component. We applied the PMF 

algorithm to the APEX-3 data set to identify individual components. Based on a 

preliminary APEX-3 analysis, we knew that PMF should identify siloxanes and 

lubrication oil in the APEX-3 volatile PM composition data. Our chief motivation was 

understanding better what we termed "residual" organic – that is organic PM that can 

neither be classified as lubrication oil nor siloxane. We performed PMF analyses with 3, 

4, and 5 sources, and Figure 5 provides the results of our 5 source PMF analysis. As 

expected, siloxanes and lubrication oil were two of the sources. A source containing 

many features characteristic of aromatic compounds (m/z 77, 91, and 115) was identified 

as was a source that appears to be a typical hydrocarbon based on its m/z 55/57, 69/71, 

81/83, 95/97 features. The final factor we label "unknown". When lubrication oil 

dominates the volatile PM composition (e.g. for RB211-535E4-B engines), the unknown 

source scales with lubrication oil. Otherwise, the unknown source does not contain 

sufficient features to make a strong identification. In some instances, the unknown may 

be a contribution from ambient particles.
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Figure 5. PMF Factors for APEX-3 Data. PMF analysis results for the APEX-3 data set.

The quality of the PMF analysis is reflected in the percentage of the actual EIm-organic 

signal that it fits. In other words, a high quality PMF analysis fit is distinguished by a 

low residual. For 4 of the 9 APEX-3 engines, the residual was less than 10%: the 

CJ6108A on the NASA Learjet, the RB211-535E4-B engines on the Boeing 757 

airframes (2 separate engines), and the CFM56-3B1 engine. The other engines (3 

AE3007 engines and the PW4158) had residuals in excess of 10%. Therefore, we restrict 

our data presentation to the CJ6108A, CFM56-3C1, and RB211-535E4-B engines. We 

present results for the APEX-3 PMF analysis in Figure 6 after dividing engine operation 

into low (<15%), intermediate (>15% and <65%) and high power (>65%) operation. The 

results for the two RB211-535E4-B engines were nearly identical when plotted in the 

Figure 6 format, so we show data for only one of the engines as representative. Several 

features are immediately apparent in Figure 6: 1) as expected, lubrication oil accounts for 

over 90% of the volatile organic PM of the RB211-535E4-B emissions at all powers, the 
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Figure 6. PMF Results for APEX-3 Data. PMF analysis results for three APEX-3 gas 

turbine engines.

fraction remaining is relatively steady with respect to power; 2) the products of 

incomplete combustion (specifically hydrocarbons and aromatics) dominate the CJ6108A 

volatile organic PM composition for all powers, and the fraction decreases with 

increasing power; 3) lubrication oil and products of incomplete combustion make similar 

contributions to the CFM56-3B1 volatile organic PM emissions. The dominance of 

incomplete combustion products in the CJ6108A is consistent with low efficiency 

combustor. The CJ6108A EIm-HCHO was 2500 mg kg-1 at idle compared to 500 mg kg-1

for the CFM56-3B1 and 100 mg kg-1 for the RB211-535E4-B [Timko et al., 2009c]. The 

dominance of lubrication oil in the RB211-535E4-B volatile PM was expected; however, 
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269

our previous estimated placed the contribution at greater than 80%, rather than the 95% 

that we now calculate.

Having performed the PMF analysis to quantify the contributions of lubrication oil, 

siloxane, and un-identified components more accurately than had been done previously 

[Timko et al., 2009a], and having divided the "residual hydrocarbon" category into a 

hydrocarbon and an aromatic fingerprint, we were able to perform additional data 

analysis. Figure 7 contains plots of EIm-organic/hydrocarbon and EIm-organic/aromatic 

for the four APEX-3 engines that provided high-quality PMF data fits. After removing 

the 
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Figure 7. Hydrocarbon and Aromatic Contributions to Volatile PM Mass. EImorganic/hydrocarbon and EIm-organic/aromatic for 4 APEX-3 engines.

lubrication oil contribution, organic PM for all four engines fall in the same range and are 

roughly ordered by EIm-HCHO. In general, EIm-organic/aromatic decreases from 0-15% 

and then increases from 65-100%. EIm-organic/hydrocarbon generally increases with 

increasing thrust. 

Figure 8 contains plots of the same data as shown in Figure 7, but now plotted as the sum 

of the two components (left panel) or their ratio (right panel). The overall trend in the 

organic PM signature is apparent in the left panel to Figure 8 - decreasing from 0-15%, 
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271

reaching a minimum at roughly 30-45%, and then increasing from 65-100%. The dropoff from 0-15% mirrors the decline in trace gas markers for combustor (in)efficiency, 

including EIm-HCHO and EIm-CO. The right panel to Figure 8 plots the ratio of EImaromatic to the sum of the aromatic and hydrocarbon organic PM EIs. Interestingly, all 

four engines follow a similar trend as the fractional contribution of EIm-aromatic 

decreases with increasing thrust from 0-65% and then levels off or increases slightly. 

Quantitatively, the fractional contribution of EIm-aromatic is similar for all four engines, 

varying from 100% for the CFM56-3B1 engine at idle to 35% for the CJ6108A at 85%. 

Interestingly, the least efficient engine, the CJ6108A, generally has the lowest fractional 

contribution from EIm-organic/aromatic of all three engine types.

Figure 8. Comparison of Hydrocarbon and Aromatic Contributions to Volatile PM Mass. 

EIm-organic/hydrocarbon and EIm-organic/aromatic particle composition data from 

APEX-3 plotted as a sum (left panel) and a ratio (right panel).

We considered further the relative ordering of the fractional aromatic contribution to EImorganic, i.e., CFM56-3B1 ~ RB211-535E4-B > CJ6108A. In addition to engine 

technology differences (fuel/air ratio, pressure ratio, combustor temperature – all of 

which are proprietary data), fuel composition differences may be important. Fuel 

aromatic, naphthalene, and olefin content would seem to be the most important fuel 

composition differences that might plausibly explain the data in Figure 8. The fuel 

contents of the four fuels are provided in Table 1. Based on the data in Table 1, either 

fuel aromatic content or fuel naphthalene content may be important for the EImaromatic/organic fractional contribution provided in Figure 8. Fuel aromatic content and 

fuel naphthalene content are roughly proportional to one another, so distinguishing 

between them is not possible. We can reject fuel olefinic content as an important variable 

for this analysis since its value is constant at roughly 0.7 vol%. For both aromatic 

content and naphthalene content, the CFM56-3B1 and RB211-535E4-B engines all have 

similar compositions (about 20 vol% and 1.8 vol%, respectively), but the CJ6108A has a 
APPENDIX K

272

much different composition with lower aromatic (14 vol%) and naphthalene (0.6 vol%) 

contents.

Table 1. Fuel hydrocarbon properties for APEX-3 tests.

Engine Aromatics vol% Naphthalenes vol% Olefin vol %

CJ6108A 14.2 0.57 0.77

CFM56-3B1 18 1.62 0.58

RB211-535E4-B (1) 21.8 1.84 0.76

RB211-535E4-B (2) 20.3 2.04 0.74

Engine technology differences and engine maintenance histories may play secondary 

roles in determining the fractional contributions of aromatic to the overall organic PM 

signature. For instance, the CFM56-3B1 aromatic contribution is greater than the 

RB211-535E4-B contribution at idle, even though the opposite order is predicted by their 

fuel compositions. Moreover, engine technology differences may play an important role 

in the upswing in the fractional aromatic contributions observed at powers greater than 

65%. And, though the differences between the two RB211-535E4-B engines are minor, 

some of that variation may be attributable to poorly characterized differences in engine 

maintenance history – especially given that fuel composition alone would predict a 

stronger fractional aromatic contribution for RB211-535E4-B (1) than (2), and we 

observe the opposite behavior at power >45%.

Analysis of the AAFEX Data Set

The AAFEX campaign provided an opportunity to study organic PM composition and its 

potential fuel dependencies for a much wider range of fuel properties than APEX-3. 

Moreover, unlike APEX-3, a single engine was used, thus removing engine technology 

differences as a potential factor to be evaluated. Specifically during AAFEX, we 

performed trace gas and PM measurements for two CFM56-2C1 engines burning JP-8, a 

FT fuel manufactured from natural gas (Shell), a FT fuel manufactured from coal 

synthesis gas and coal liquids (Sasol), and 50/50 blends of the two FT fuels in JP-8. 

Tests were performed during "cold" ambient conditions (270-275K) and "warm" ambient 

conditions (285-290 K).

Before considering fuel properties and organic PM composition, we first introduce total 

PM mass data. Figure 9 provides AAFEX PM mass data when the engine was running 

JP-8 at cold conditions. Both integrated 30 m EEPS mass data (with an assumed particle 

density of 1 g cm-3

) and 1 m/30 m MAAP soot mass data are shown in figure 9. The 1 m 

and 30 m MAAP masses agree reasonably well for most of the power range, though the 1 

m MAAP mass data are typically 10-25% lower than the 30 m MAAP mass data. We 

suspect that the difference is due to loss in the 1 m probe or sampling line. We have 

observed small discrepancies between 1 m and 30 m MAAP mass data previously; 

however, the AAFEX data set is more detailed than previous data sets and permits a 

cleaner distinction to be made. Interestingly, the port side CFM56-2C1 engine has a 

higher EIm-soot than the starboard engine by as much as 25%. The difference between 

EIm-soot for the two engines is most obvious at 65% power and is almost negligible at 

85% power.
APPENDIX K

273

Figure 9. Total JP-8 PM Mass Emissions. PM mass data for a CFM56-2C1 engine 

burning JP-8 fuel as measured by an EEPS (EIm-total) and a MAAP (EIm-soot).

The EEPS data are a measurement of total PM mass. Under cold conditions, the total PM 

mass measured by EEPS is greater than 100 mg kg-1 at idle and falls to less than 50 mg 

kg-1 at 30%, before increasing to 150 mg kg-1 at 100% power. Agreement between 

EEPS and MAAP at powers greater than 30% is reasonably good and within the range of 

experimental scatter at powers greater than 65%. For 4 and 7% power, the EEPS PM 

EIm-total measurement is much greater than the MAAP EIm-soot measurement, indicative 

of a strong nucleation mode containing roughly 100 mg kg-1 of mass. EIm-nucleation (or 

EIm-volatile) of 100 mg kg-1 is large compared to that obtained in previous tests, and we 

attribute the high value to a) the high fuel sulfur content of the JP-8 fuel (1200 ppm mass) 

and b) the cold ambient conditions prevalent during this test (270 K). The remainder of 

this section is investigates the composition of the volatile PM, beginning with EImsulfate.

Figure 10 plots EIm-sulfate (at 30 m) as a function of engine power for the JP-8 and FT 

fuels for the CFM56-2C1 engine. First, the dependence on fuel composition is apparent. 

For JP-8, EIm-sulfate varies from about 1 mg kg-1 at idle to nearly 4 mg kg-1 at take-off. 

EIm-sulfate for both pure FT fuels is below detection limits (0.2 mg kg-1 for these tests) 

for all power conditions. EIm-sulfate for the blended FT fuel was intermediate to the pure 

FT fuels and JP-8, though closer to the FT data. Power clearly played a role in EImsulfate – consistent with previous work [Onasch et al., 2009; Timko et al., 2009a]. 

Increasing power increased EIm-sulfate, most likely because of the power dependence of 

EIm-soot and the better ability of the AMS to quantify soot sized particles (and/or their 

coatings) than nucleation/growth mode particles. Temperature was also important. As 
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274

temperature increased, so too did EIm-sulfate. This counter-intuitive finding is likely due 

to the competition between nucleation (favored at low temperature) and soot coating 

(favored at high temperature) – and the relative sensitivity of the 

Figure 10. AAFEX Sulfate PM Mass Emissions. EIm-sulfate data obtained during 

AAFEX (left panel) and a summary plot of EIm-sulfate from AAFEX, APEX-1, 2, and 3, 

and the PW308 tests.

AMS to nucleation particles (low) and soot particles (high). Consistent with these 

observations, EIm-sulfate for the port engine is greater than the starboard engine, just as 

EIm-soot for the port engine is greater than for the starboard engine.

Because of the high sulfur content of the JP-8 (1200 ppm) and the negligible sulfur 

content of the FT fuels, AAFEX provides an opportunity to re-visit the fuel sulfur 

conversion analysis performed previously [Timko et al., 2009a]. As suggested in our 

description of the left panel of Figure 10, the AMS provides an incomplete measure of 

total sulfate PM because of its poor detection capability for particles smaller than 50 nm. 

For particle sizes typical of soot (>50 nm), AMS data is nearly quantitative. Therefore, 

we restrict our analysis to 85% and 100% power when EIm-soot is maximized and the 

AMS data is closest to quantitative. Plotting EIm-sulfate (85/100%) as a function of fuel 

sulfur content alongside archival data from APEX-1, 2, and 3, and the PW308 tests 

reveals EIm-sulfate to be a reproducible measurement from campaign to campaign. The 

best fit line between EIm-sulfate and fuel sulfur content is shown. The slope of the best 

fit line, which is also the S(IV) to S(VI) conversion efficiency - remains roughly 0.1%, as 

it was after considering only APEX data. Engine technology does not seem to play a role 

in the conversion efficiency. The 100% FT data and the 50/50 blend data fall on the 

curve for JP-8 and Jet-A, with the exception of the 50% FT (Sasol) blend from AAFEX 

which is low by a factor of about 2. The Sasol blend may be low due to a) the fact that it 
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275

was studied at a maximum power of 85%, whereas the other AAFEX fuels have 100% 

power data or b) an additional fuel related factor that distinguished Sasol blends from 

other FT fuel blends. Of these, the power difference seems more reasonable, but we 

cannot rule out fuel related differences based on our data alone.

Figure 11 contains a plot of EIm-organic measured for the various fuels during the 

AAFEX campaign. As with EIm-sulfate, EIm-organic depends on the fuel, the power 

condition, and ambient conditions. The dependence of EIm-organic on the engine (port or 

starboard) is weaker than for EIm-sulfate. Taking the other three variables in turn: 1) 

fuel: EIm-organic is greater at all power conditions for JP-8 than for the FT fuels or the 

blended fuel, 2) temperature: EIm-organic increases with decreasing ambient temperature, 

3) power: consistent with APEX results, EIm-organic decreases from 0-15% (plotted as 

fuel flows ranging from 0 to 0.3 kg sec-1) and then increases from 65-100% (0.6 to 1 kg 

sec-1). Quantitatively, EIm-organic at idle and low ambient temperature reaches a value 

of nearly 15 mg kg-1 – the highest ever measured during an aircraft test. The high idle 

value of EIm-organic can be attributed to the low ambient temperature of the test and the 

relatively low efficiency of the CFM56-2C1 combustor when operated near idle.

Figure 11. AAFEX Organic PM Mass Emissions. EIm-organic measured during the 

AAFEX campaign.

The ratio of EIm-sulfate to EIm-organic is an interesting quantity, and we plot that ratio in 

Figure 12 for JP-8. For FT fuels, the ratio is not meaningful since EIm-sulfate was below 

detection limits for these fuels. For JP-8, Figure 12 clearly shows that the ratio of EImsulfate to EIm-organic increases steadily with increasing power. At idle, the volatile PM 

material is dominated by organic material which contributes more than 90% of the total 

mass. At take-off, the ratio of organic to sulfate PM is nearly 1:1. Interestingly, the ratio 

of sulfate to organic depends on ambient temperature – at least for powers greater than 

4%. Higher ambient temperatures favor EIm-sulfate. We propose two explanations: 1) 
APPENDIX K

276

lower ambient temperatures decrease combustion efficiency, thereby increasing the 

amount of organic precursors available to form organic PM or 2) decreasing temperature 

shifts sulfate material preferentially to the nucleation mode (and away from the soot 

mode) where it is not detected efficiently.

Figure 12. Comparison of Sulfate and Organic for JP-8. Ratio of EIm-sulfate to EImorganic measured during AAFEX.

Particle size data provide an opportunity to test the two theories forwarded to explain 

Figure 12. Figure 13 provides particle size data for JP-8 obtained at idle (left) and takeoff (right) conditions. Data for warm (top) and cold (bottom) ambient conditions is 

provided. As expected, the particle size distribution obtained at idle peaks at roughly 30 

nm, consistent with a nucleation/growth mode truncated by the AMS sensitivity for small 

particles. Also as expected, the distribution favors organic materials at idle by a factor of 

about 10:1. At take-off, the ratio of sulfate to organic material in the soot mode is 

roughly 1:1. Interestingly, however, at cold conditions we detect a slight peak in the 

sulfate particle size distribution at take-off power that seems to fall in the 

nucleation/growth mode size range (bottom right of Figure 13). The sulfate peak is not 

present in the organic size distribution nor in either distribution at warm conditions. 

Therefore, the cold take-off power data presented in Figure 13 seems to indicate that 

decreasing ambient temperature preferentially drives sulfate material to the 

nucleation/growth mode. We tentatively conclude then that the temperature dependence 

of the EIm-sulfate/EIm-organic ratio at idle is determined by combustor efficiency and at 

higher power by the preference of sulfate material for the nucleation/growth mode at 

lower temperatures. Although the sulfate nucleation peak is not very strong in Figure 13, 

the SMPS data shown in Figure 14 support the observation of a nucleation mode under 

these conditions, though the SMPS shows that the mode peaks at less than 20 nm instead 

of almost 30 nm. The observation that the nucleation mode may have a different ratio of 

sulfate to organic material than the soot mode t is new and potentially important –
APPENDIX K

277

especially at cruise conditions at altitude. For that reason, we plan to continue to analyze 

the AAFEX data to understand better the EIm-sulfate/EIm-organic ratio and its 

dependence on power.

Figure 13. Particle Size Distributions for Volatile PM. Particle size data for volatile PM 

obtained during AAFEX: left, idle conditions, right, take-off; top: warm ambient 

temperature; bottom: cold ambient temperature.

Figure 14. Comparison of SMPS and AMS Particle Size Data. Comparison of the 85% 

power AMS data shown in Figure 13 with the SMPS size distribution data.
APPENDIX K

278

We characterized the composition of the organic PM more carefully by analyzing the 

particle mass spectra we obtained during AAFEX. Figure 14 provides the mass spectra 

results. As in Figure 13 the left panel of Figure 15 contains idle data (4%) and the right 

panel contains high-power data (85%). Data for only cold ambient conditions are 

provided in Figure 14 except for the FT blended fuel which was performed only once at 

warm conditions. All of the spectra presented in Figure 14 contain features consistent 

with a hydrocarbon – apparent from the m/z 41/43, 55/57, 69/71 fragments. At low 

power, JP-8 contains evidence of the APEX-3 aromatic signature – m/z 77, 91, and 115. 

The aromatic signature is nearly absent from the FT fuel mass spectra and decreases 

strongly at high power for all the fuels. Lubrication oil, characterized by the m/z 85, 113 

fragments, is present in all the spectra and dominates the high-power mass spectra. The 

AAFEX mass spectra seem to contain all of the components present in the APEX-3 

spectra, and the aromatic signature is the only feature that seems to be fuel dependent.

Figure 15. AAFEX Particle Mass Spectrometer Data. Mass spectra data obtained during 

AAFEX for idle (left panel) and climbout (right panel) conditions for the various fuels.

We have yet to perform a PMF analysis of the AAFEX data; however, we have 

performed a qualitative analysis of the aromatic signature as shown in Figure 16. On an 

absolute basis (left panel), the quantity of aromatic mass decreases sharply with 

increasing power and is nearly absent from the FT fuel particles. On a relative basis 
APPENDIX K

279

(right panel), the aromatic contribution still decreases with increasing power. But unlike 

the APEX-3 data, all of the fuels seem to follow a similar trend. Clearly, we need to 

continue to analyze the AAFEX composition data to relate it to APEX-3.

Figure 16. AAFEX Aromatic PM Content. Qualitative apportionment of the organic PM 

mass to the aromatic contribution.
APPENDIX L

280

APPENDIX L: Microphysical Evolution of Gas Turbine Engine Combustion 

Particles

M. T. Timko, Z. Yu, S. C. Herndon, E. C. Wood, R. C. Miake-Lye

Aerodyne Research Inc.

Billerica, MA 01821

Author’s note: This Appendix summarizes results from AAFEX, and the Midway Airport 

2009 study (MDW-09). This report is based on a Final Report submitted previously to 

NASA describing activities under contract # NNC07CB57C. We acknowledge as 

outstanding issues of further inquiry: 1) resolution between model estimates and 

experimental measurements of particle characteristics in evolving plumes, 2) mass 

balance closure gaps between SMPS and AMS data sets, 3) evaluation of the importance 

of ambient PM on exhaust PM evolution, 4) importance of sampling line effects (line loss, 

evolution in the line, etc.) to measured PM characteristics.

Introduction

One of the most challenging aspects of studying aircraft PM is that it continues to evolve 

on a 1-sec time scale as the exhaust plume cools and dilutes. We observe this behavior 

during standard dedicated engine tests; almost no volatile PM is detected at 1 m, and the 

detected volatile PM mass increases by a factor of 10 or more at 30 m. Some of the 

observed discrepancy between 1 m and 30 m may be due to the loss of volatile PM 

precursors or volatile PM itself on the sampling probes and transfer lines. Much of it, 

however, seems to be due to gas-to-particle conversion of volatile PM precursors that 

occurs on rapid (<10 sec) timescales. Figure 1 provides 30 m SMPS measurements of 

particle size obtained for JP-8 during AAFEX. The left panel shows number density 

data, while the right shows particle volume data measured at 30 m. At all conditions, a 

size mode peaking at approximately 10-20 nm and consistent with nucleation/growth 

mode particles dominates the number density data. In the volume plot, the contribution 

of nucleation/growth mode particles is still apparent at all powers; however, 

nucleation/growth mode volume dominates only for power <65%. At 1 m (data not 

shown), the nucleation/growth mode is absent. During AAFEX and MDW-09, we 

augmented dedicated engine test measurements with measurements made further 

downfield (>50 m) to understand better microphysical evolution of cooling exhaust 

plumes. 
APPENDIX L

281

Figure 1. AAFEX SMPS Data. SMPS particle size data obtained at 30 m during 

AAFEX for JP-8 combustion.

Plume Results

Figure 2 plots EIn-total as a function of engine power at 1 m, 30 m, and >50 m for the 

AAFEX data set with a JP-8 fuel. EIn-total increases sharply between 1 m and 30 m, by a 

factor of 10 or more (the CPC particle counter saturated at 4/7% for the JP-8 tests at 30 m 

or else the increase between 1 m and 30 m at these conditions would likely be even more 

significant). Moving to >50m, EIn-total increases by another factor of 10. This increase 

is likely due to continuing microphysical evolution of the plume which a) increases the 

size of nucleation/growth mode particles so that a larger fraction can be detected and b) 

increases the number density of nucleation/growth mode particles. Reduced line loss of 

nucleation/growth mode particles (samples extracted >50m required only a short, >5m, 

sample distribution system) may also play a role in the increase in EIn-total observed 

between 30 m and >50m. 
APPENDIX L

282

Figure 2. AAFEX Plume Particle Number Density. EIn-total data obtained during 

AAFEX at 1 m, 30 m, and >50m.

Particle microphysical evolution clearly includes particle growth, as made clear in figures 

3, and 4. In figure 3, we compare SMPS size data obtained during AAFEX for a fresh 

plume (sampled at roughly 60m form the engine) with an aged plume (sampled at 

roughly 150m from the engine). Ambient conditions and engine operation (4% ground 

idle) were similar for the two events. Clearly, the peak in the number density particle 

size distribution has shifted from about 15 nm (fresh plume) to about 25 nm (aged 

plume). Moreover, the relative ratio between the nucleation mode and the soot mode has 

changed with an increasing contribution because of nucleation/growth mode observed in 

the aged plume.

Figure 3. SMPS Plume Data. SMPS size data obtained during AAFEX for a fresh plume 

(left) and an aged plume (right).
APPENDIX L

283

Figure 4 shows EEPS particle size data, which support the conclusions drawn from 

Figure 3. In Figure 4, particle size data for downstream distances ranging from 50-200m 

is shown. At 50m, the peak in the number weighted particle number density size 

distribution is slightly greater than 20 nm. Particle size gradually increases with 

downstream distance, reaching a value of nearly 30 nm for a downstream distance of 

160m. Consistent with an analysis of the PW308 data set, we assert that processing time 

– and not distance per se – is the critical variable for microphysical evolution. However, 

translating downstream distance reliably into process time (which depends on both 

engine excess momentum and prevailing winds) is not straightforward.

Figure 5 plots the peak diameters shown in Figure 4 as a function of distance traveled. 

The importance of downstream distance (or, more likely, aging time) is apparent. The 

data points in Figure 4 are color coded for temperature, revealing a secondary effect of 

ambient conditions; increasing ambient temperature decreases particle size when all other 

factors (aging time, engine power, fuel) are held constant. As with our previous 

observations, we cannot conclude whether this behavior is due to combustor efficiency 

(decreasing with decreasing ambient temperature) or microphysical differences. 

However, based on our previous analysis efforts, a combination of the two factors is 

likely at play.

Figure 4. EEPS Plume Data. EEPS size data obtained during AAFEX for various 

sampling (>50m) locations.
APPENDIX L

284

Figure 5. Particle Size in a Plume. Number density particle size distribution data 

obtained at >50m during AAFEX.

We were able to obtain volatile PM composition data for the first time in evolving 

plumes during AAFEX and later the MDW-09 Airport Study. We credit advances to our 

measurement capabilities made during Year 1 of this contract for the success we had 

during Year 2. Figure 6 provides our most convincing measurement of plume organic 

PM content made during the MDW-09 study. Figure 6 provides time-series plots of 

organic PM, CO2, CO, NOX, and soot. The high degree of correlation between the 

organic PM and CO2 signals provides convincing evidence that we have obtained 

composition data. The low values of soot and NOX and high value for CO during this 

time interval indicate an aircraft engine idle exhaust plume. We obtained idle plume data 

for 9 idle events during the MDW-09 study and several additional idle events during 

AAFEX. We obtained plume data for 6 events characterized as aircraft takeoff during 

MDW-09. 
APPENDIX L

285

Figure 6. MDW-09 Plume Data. Time series data obtained during an idle plume event at 

Midway Airport. 

Analysis of the plume data is on-going, but we have already made three important 

observations: 1) for aged plumes (>100 sec), EIm-organic ranges from 50-150 mg kg-1

(idle conditions, 275 K), 2) the aromatic signature identified at 30 m perseveres or even 

grows at >50 m and 3) EIm-organic scales with EIm-CO. Measuring EIm-organic > 50 mg 

kg-1 brings the volatile PM data into better agreement with the total PM data measured at 

idle during AAFEX and may go a long way in reconciling the data sets. We attributed 

the larger values of EIm-organic obtained for the plume to the growth of nucleation mode 

particles during aging, which in turn leads to increased instrument sensitivity. Figure 7 

provides plume mass spectrometer data obtained during an idling event at AAFEX. Not 

only does the m/z 77, 91, 115 series standout from the background with >10 signal to 

noise, additional members of the family (chiefly m/z 128, 141, and 165) are also 

apparent. We need to continue to analyze this data to understand whether aging plumes 

can become enriched in certain species – presumably those with the lowest vapor 

pressures and presumably due to preferential vaporization of more volatile species. 
APPENDIX L

286

Figure 7. Composition of Plume Particles. Mass spectrometer data obtained during an 

idling plume event at AAFEX.

Based on the representative data shown in Figure 6 and 7, we performed a systematic 

analysis of the MDW-09 idle plume data. Figure 8 shows MDW-09 data in which EImorganic scales with EIm-CO near idle power. Due to the scaling between EIm-organic and 

EIm-CO, we conclude that combustor (in) efficiency seems to play an important role in 

EIm-organic, at least at idle power. We attempted to account for effects of plume mixing 

on gas-to-particle microphysics by rating the points in Figure 8 by above ambient CO2

levels (delta CO2). No trend between EIm-organic and delta CO2 is apparent in Figure 8, 

suggesting that plume dilution plays a secondary role in determining EIm-organic – at 

least for the dilution range we have observed (1200-700 fold). Furthermore, two 

sampling distances were tested at MDW-09 (labeled "1" and "2" in Figure 8) and no 

sampling location influence is apparent in the EIm-organic data, suggesting that 

processing time plays a secondary role in determining EIm-organic – at least for the 

limited, 2-location data set available from MDW-09. Physically, we expect both dilution 

level and processing time will influence EIm-organic and additional studies are merited 

for evaluating these effects.
APPENDIX L

287

Figure 8. Comparison of Organic PM to CO in Plumes. EIm-organic as a function of 

EIm-CO for idle plume events observed during the MDW-09 Airport Study.
APPENDIX M

288

APPENDIX M: Determination of the Emissions from an Aircraft Auxiliary Power 

Unit (APU) during the Alternative Aviation Fuels EXperiment (AAFEX)

John S. Kinsey, U. S. Environmental Protection Agency, Office of Research and 

Development, National Risk Management Research Laboratory, Research Triangle Park, 

NC 27711

Michael T. Timko, Scott C. Herndon, Ezra C. Wood, Zhenhong Yu, Richard C. MiakeLye, Aerodyne Research, Inc., 45 Manning Road, Billerica, MA 01821

Prem Lobo, Philip Whitefield, Donald Hagen, Center of Excellence for Aerospace 

Particulate Emissions Reduction Research, Missouri University of Science and 

Technology, Rolla, MO 65409

Changlie Wey, ASRC Aerospace Corporation, Cleveland, OH

Bruce Anderson, Andreas Beyersdorf, Charles Hudgins, Lee Thornhill, Eddie Winstead 

National Aeronautics and Space Administration, Langley Research Center, Hampton, 

VA.

Robert Howard, Aerospace Testing Alliance, U. S. Air Force Arnold Engineering 

Development Center, TN

Dan Bulzan, Kathleen Tacina, National Aeronautics and Space Administration, John 

Glenn Research Center, Cleveland, OH

Berk Knighton, Montana State University, Bozeman, MT
APPENDIX M

289

1. Introduction

The gas- and particle-phase emissions from the auxiliary power unit (APU) were also 

characterized by the research team as part of the Alternative Aviation Fuels Experiment 

(AAFEX) conducted in January/February 2009. This portion of the program was 

conducted on a time available basis and was organized by the U. S. Environmental 

Protection Agency’s National Risk Management Research Laboratory (EPA) in Research 

Triangle Park, NC. Two tests were performed on the APU. The first test was conducted 

on January 29 with JP-8 fuel and the second test on February 2 using both JP-8 and 

Fisher-Tropsch fuel. The specific organizations participating in the APU tests and the 

lead individual for each organization is shown in Table 1.

Table 1. Participating Organizations

Organization Research Lead(s)

U. S. Environmental Protection Agency-NRMRL, Research 

Triangle Park, NC (EPA)

John Kinsey

Aerodyne Research, Inc., Billerica, MA (ARI) Richard Miake-Lye

Missouri University of Science and Technology, Rolla, MO 

(MST)

Phil Whitefield/Prem 

Lobo

National Aeronautics and Space Administration-Glenn 

Research Center, Cleveland, OH (NASA-Glenn)

Changlie Wey

National Aeronautics and Space Administration-Langley 

Research Center, Hampton, VA (NASA-Langley)

Bruce Anderson

Montana State University, Bozeman, MT (MSU) Berk Knighton

U. S. Air Force, Arnold Engineering Development Center, TN 

(AEDC)

Robert Howard

The following sections describe the APU tested, fuel composition, experimental 

apparatus, test matrix, and the emissions data obtained during AAFEX.

2. Description of APU

The APU tested was a Honeywell (formerly Garrett) Model GTCP85-98CK (Figure 1) 

mounted cross-wise in a forward baggage compartment of the DC-8 (the DC-8 was not 

supplied with an APU as original equipment). This particular APU is an integral bleed 

type where part of the compressor flow is provided to the combustor with the remainder 

supplied as bleed air to the aircraft for use by the environmental control system (ECS), 

for engine start, etc. The APU tested was designed mainly for ground operation and is not 

certified for use at altitude for engine restart. The following are general specifications for 

the APU:

Two-stage centrifugal compressor

Single-stage radial inflow turbine

Shaft work output priority
APPENDIX M

290

Single can combustor

Bleed air flow: 58 kg/min @ 220 °C exhaust gas temperature (EGT) and 0 kW shaft work

Maximum shaft work: 149.2 kW

Maximum EGT: 621 °C

Figure 1. Garrett 85 Series APU and can combustor

In general, APUs are tested in three operating modes each representing a specific load on 

the turbine: (1) no-load (idle); (2) ECS (all air conditioning [A/C] packs operating); and 

main engine start (MES). During AAFEX, however, only Condition 3 could be easily 

identified along with several other lower operating points. Since the lack of engine 

instrumentation prevented an accurate determination of load on the APU or fuel flow, it 

was decided to present all of the emissions data in terms of EGT which was used as an 

indicator of total turbine output. In the future, if more detailed operational data could be 

made available, some of the scatter in the data might be reduced by using a better 

indicator of engine power such as fuel flow or equivalence ratio. The latter could not be 

reliably determined since the undiluted combustion gas concentrations were adversely 

effected by probe position as discussed in Section 4.1 below.

3. Fuel and Lube Oil Composition

During the APU tests, the emissions from two different fuel types were evaluated. These 

fuels included the base JP-8 fuel and Fischer-Tropsch fuel No. 2 (FT-2), which was 

produced from a coal feedstock and purchased from Sasol in South Africa. Nominal 

specifications of both fuels are shown in Table 2. The lubrication oil used in the APU is 

Mobile Jet II which is the same as used in the main engines.

Can Combustor
APPENDIX M

291

Table 2. Nominal Fuel Compositiona

Fuel Symbol

C Fraction H/C 

Ratio Sulfur Aromatics Naphthalenes Olefins

wt/wt mol/mol ppm vol% vol% vol%

Base fuel JP-8 0.8619 1.88 1148 18.55 1.55 1.6

Coal-derived 

Fischer-Tropsch 

fuelb

FT-2 0.8486 2.12 22 0.6 0 3.8

a. All values are for samples collected earlier in the AAFEX campaign. Fuel samples were 

not collected during the APU tests. See Section 6.1 below.

4. Experimental Apparatus

4.1 Sampling System

Experiments to characterize the aircraft’s APU emissions were performed by each group by 

drawing samples through a single probe and a 12.7- or 9.5-mm (outside diameter) stainless 

steel sampling line positioned approximately 0.5 m downstream of the unit’s exhaust port 

(Figure 2). For particle sampling, the sample gas was diluted with dry nitrogen downstream 

of the probe and therefore should represent only the non-volatile PM emissions (Wey et al., 

2007). The sampling lines then ran ~ 23 to 38 m from the probe stand to each trailer where 

instrumentation was located to make the necessary measurements. All sample lines were 

unheated except for AEDC/NASA-Glenn which was kept at a nominal temperature of 150 

oC. Due to time and resource constraints, particle losses through the sample lines could not

determined and thus all data presented here represent uncorrected results. It would be 

expected, however, that the particle losses would be similar to those determined in prior 

testing of this type (Kumar et al., 2008; Liscinsky and Hollick, 2010).

As can be seen in Figure 2, probes used by the various investigators were not exactly colocated. The AEDC probe position, coupled with the high cross winds present during 

testing, may have adversely affected the smoke number and raw combustion gas 

measurements as discussed below.

4.2 Instrumentation

A variety of different instrumentation was used by the various research organizations 

participating in the APU testing during AAFEX. This instrumentation and its operation 

are described in detail elsewhere in this report and other publications such as Kinsey 

(2010) and thus will not be repeated here. Table 3 is a summary of the parameters 

measured and instrumentation used by each group during the two APU tests conducted.
APPENDIX M

292

Figure 2. Probe arrangement at the APU exhaust port

Table 3. Experimental Parameters and Instrumentation.

Parameter Measured Organization Measurement Technique Instrument(s)a

Sulfur dioxide NASA-Glenn UV fluorescence Monitor Lab - ML9850

EPA-NRMRL Pulsed fluorescence analysis 

(diluted)

Thermo Scientific Model 43a

Total hydrocarbons NASA-Glenn Heated FID Signal - 300HM

Carbon dioxide and 

carbon monoxide

NASA-Glenn Non-dispersive infrared 

spectroscopy

Siemens Ultramat 23 

(CO2/CO/O2)

California Analytical Inc -

602P

Carbon dioxide EPA-NRMRL IInfrared absorption Horiba Model VA-3000

MST Sable Systems Model CA-2A

Aerodyne LICOR 7000/LICOR 820

NASALangleyLICOR 7000

Oxygen NASA-Glenn Para-magnetic analysis Siemens Ultramat 23 

California Analytical Inc -

602P

Nitrogen 

oxides/nitrogen 

oxide/nitrogen dioxide

NASA-Glenn Chemiluminescence Eco Physics - CLD 844 M hr

HCHO, NOx, CO, and 

C2H4

Aerodyne infrared absorption Tunable Infrared Laser Diode 

Absorption Spectrometer 

(TILDAS)

EPA

AEDC/NASA-Glenn

MST/Aerodyne/MSU/N

ASA-Langley
APPENDIX M

293

Speciated gas phase 

organic compounds

MSU Photon transfer reaction mass 

spectroscopy (PTR-MS)

Ionicon

PM number 

concentration

EPA-NRMRL Differential mobility 

analyzer/condensation nuclei 

counter (electrical mobility 

diameter < 0.5 μm)

TSI Model 3936 SMPS 

(Model 3080 Classifier + 

Model 3081 long DMA + 

Model 3025a CPC)

MST Condensation nuclei counter TSI Model 3025a CPC

Aerodyne Condensation nuclei counter TSI Model 3025a CPC

NASALangleyCondensation nuclei counter TSI Model 3775 CPC

Particle size 

distribution

EPA-NRMRL Differential mobility 

analyzer/condensation nuclei 

counter (electrical mobility 

diameter < 0.5 μm)

TSI Model 3936 SMPS 

(Model 3080 Classifier + 

Model 3081 long DMA + 

Model 3025a CPC)

MST Scanning differential mobility 

analyzer

TSI Model 3071

NASALangleyDifferential mobility 

analyzer/condensation nuclei 

counter (electrical mobility 

diameter < 0.5 μm)

TSI Model 3071SMPS (long 

DMA)

Electrical mobility analysis TSI Model 3090 EEPS

Smoke number AEDC Optical reflectance Smoke meter

PM black carbon EPANRMRLbReflectometer/radiative scattering Thermo Scientific Model 

5012 MAAP

Aerodyne Reflectometer/radiative scattering Thermo Scientific Model 

5012 MAAP

NASALangleyReflectometer/radiative scattering Thermo Scientific Model 

5012 MAAP

PM surface polycyclic 

aromatic hydrocarbons

EPA-NRMRL Ultraviolet analysis EcoChem PAS 2000

Aerosol chemical 

composition

Aerodyne Aerodynamic lens, particle time 

of flight, and time-of-flight mass 

spectrometer

Aerodyne Aerosol Mass 

Spectrometer (AMS)

a. SMPS = scanning mobility particle sizer; CPC = condensation particle counter; DMA 

= differential mobility analyzer; EEPS = Engine Exhaust Particle Sizer; and MAAP = 

multi-angle absorption photometer.

b. The MAAP data collected by EPA are not reported here since it was found that the 

instrument substantially under-measured the emissions. This under-measurement was 

attributed to the fact that the data generated directly off the instrument was used for 

the calculations as discussed in Kinsey (2010).
APPENDIX M

294

5. Test Matrix

As discussed above, two tests were conducted during AAFEX to investigate the APU 

emissions. The first took place on January 29, 2009 and used the JP-8 base fuel only 

whereas the second was conducted on February 2, 2009 and was run with both JP-8 and 

FT-2 fuel. In these tests, the emissions were monitored with varying load conditions 

based on exhaust gas temperature (EGT). Table 4 presents the recorded EGT and 

corresponding operating modes for these two tests.

Table 4. Experimental Test Matrix

Test Date Fuel Type Engine Load 

Conditiona

EGT 

(oC)

January 29 JP-8

Generator mode 345

Motor Engine #2 610

Generator mode 350

Motor Engine #2 610

Generator mode 345

February 2

JP-8

Generator mode 345

Generator mode 365

Minimum A/C pack 475

Medium A/C pack 555

Motor Engine #2 610

Generator mode 365

Minimum A/C pack 475

Medium A/C pack 550

Motor Engine #2 610

FT-2

Generator mode 360

Minimum A/C pack 475

Medium A/C pack 555

Motor Engine #2 610

Generator mode 365

Minimum A/C pack 475

Medium A/C pack 550

Motor Engine #2 620 a

 A/C = air conditioning. "Motor" indicates when APU bleed is used to spin the engine.

6. Experimental Results

The APU emission indices for sulfur dioxide (SO2), total hydrocarbons (THC), carbon 

monoxide (CO), nitrogen oxides (NOx), speciated gas phase emissions, PM mass and 

number, black carbon, and speciated PM were determined from the measurements. In 

addition, particle size distribution (PSD), number-based geometric mean particle 

diameter (GMD), geometric standard deviation (GSD), and smoke number were also 

determined from the data collected. The following sections provide the experimental 

results obtained by the research team for these parameters.
APPENDIX M 

295

For each pollutant, the experimental results for each group are shown on the same graph 

along with error bars reflecting the standard deviation of the data collected at each power 

condition during the course of each test. Plotting the uncertainty as the standard deviation 

provides information on data reproducibility. Plotting results from various research 

groups side-by-side also provides reliable information on instrument-to-instrument 

reproducibility. We assert, therefore, that the precision of the data set is well defined. In 

a field measurement activity, a number of sources of systematic error, including particle 

line losses and chemical reactions occurring in the long sampling lines, cannot be 

quantified. Likewise, the various research groups used different instrumentation, probes, 

and sampling lines and uncertainty introduced by these differences is included in the data 

set. In the graphs presented below, we make general comparisons of data trends based on 

our estimated precision and provide additional information on data accuracy where 

possible. 

6.1 SO2 Emissions 

Figure 3 shows the SO2 EI results for the APU tests as determined by EPA and NASAGlenn. It is seen that the EIs obtained from both JP-8 and FT-2 fuels remained 

approximately constant as the EGT increased. Also, the data obtained by the two groups 

agree very well. The SO2 EI was about 1.5-1.8 g/kg-fuel for the JP-8 fuel and 0.13-0.15 

g/kg-fuel for the FT-2 fuel. If these EIs are compared to a theoretical 100% conversion of 

sulfur in the fuel to SO2 (e.g., 2.3 g SO2/kg for JP-8), the JP-8 values would be lower than 

expected and the FT values would be higher. Note, however, that fuel samples were not 

collected during the APU tests and the actual fuel sulfur content is not known. Finally, 

according to the EPA data collected, the use of the alternative fuel reduced the SO2

emissions by 92% on average for these tests. 

 

Figure 3. SO2 emission indices determined by EPA and NASA-Glenn (2/2/09 only). 

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

300 350 400 450 500 550 600 650

Exhaust Gas Temperature (o

C)

SO2 Emission Index (g/kg fuel)

NASA JP-8

NASA FT-2

EPA JP-8

EPA FT-2
APPENDIX M

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6.2 Total Hydrocarbon Emissions

Figure 4 provides the THC EIs as calculated from the data collected by NASA-Glenn for 

the APU tests. As shown, the THC EIs decreased rapidly with increasing EGT for both 

fuels with the values ranging from 0.27-1.4 g/kg for JP-8 and 0.14-1.3 g/kg for FT-2 fuel. 

The data also indicate an average reduction of about 37% over all operating conditions 

for the use of FT-2 fuel in this particular APU. Because THC contains contributions from 

a range of VOC sources, each with its own response factor, THC data can be prone to 

systematic error. However, the 37% reduction in THC reported in Figure 4 is a 

statistically significant difference between the fuels and the trend with respect to EGT is 

likewise statistically significant.

Figure 4. THC emission indices determined by NASA-Glenn (2/2/09 only).

6.3 Carbon Monoxide Emissions

The CO EIs determined by NASA-Glenn for the APU are shown in Figure 5. As 

indicated, the emissions decrease linearly with increasing EGT for both fuels with the EI 

ranging from ~12-30 g/kg depending on operating condition and fuel type. In addition, 

only a small reduction (~ 9%) in CO emissions was observed for the use of FT fuel 

during these tests. CO is generally considered to be a robust measurement. Therefore, a 

10% reduction in CO, although modest, is statistically significant.

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

300 350 400 450 500 550 600 650

Exhaust Gas Temperature (o

C)

THC Emission Index (g/kg fuel)

FT-2

JP-8
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Figure 5. CO emission indices determined by NASA-Glenn (2/2/09 only).

6.4 Nitrogen Oxide Emissions

Figure 6 provides the NOx emission indices as derived from data collected by NASAGlenn and ARI. Figure 6 shows that the NOx EIs obtained by each group agree well, 

were fairly consistent across all operating conditions (~ 4.5 g/kg fuel), and varied little by 

fuel type. An average reduction of only 1.9% for the FT fuel was determined from the 

NASA data set. While NOX measurements can be considered robust and reproducible, the 

1.9% decrease observed here for FT fuel is within the bounds of experimental 

uncertainty.

A distinct feature of aircraft exhaust NOX is the high fraction of NO2, especially under 

idle conditions (Wood et al., 2008). We examined the NO2/NOX ratio for APU exhaust 

and plot the data in Figure 7. For the APU, the ratio of NO2 to NOX varies from 0.65 at 

350 °C to 0.25 at 620 °C. The NO2/NOX ratio is, therefore, significantly lower than the 

0.9 measured for a CFM56 engine at idle (Wood et al, 2008). As with total NOX, the 

NO2/NOx ratio data show no statistically significant dependence on fuel composition. 

The decreasing trend of NO2/NOx with respect to EGT is, however, statistically 

significant.

0

5

10

15

20

25

30

35

300 350 400 450 500 550 600 650

Exhaust Gas Temperature (oC)

CO Emission Index (g/kg)

FT-2

JP-8
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Figure 6. NOx emission indices determined by NASA-Glenn and ARI (2/2/09 only).

Figure 7. NO2 to NOx ratios for both test fuels.

2.00

2.50

3.00

3.50

4.00

4.50

5.00

5.50

6.00

6.50

300 350 400 450 500 550 600 650

Exhaust Gas Temperature (oC)

NOx Emission Index (g/kg fuel) 

NASA FT-2

NASA JP-8

Aerodyne JP-8

Aerodyne FT-2

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

300 350 400 450 500 550 600 650

Exhaust Gas Temperature (°C)

NO2/NOx Ratio

JP-8

FT2
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6.5 Speciated Gas Phase Emissions

Speciated hydrocarbon emissions were monitored using the PTR/MS and QCL-TILDAS 

instruments. A range of oxygenates (formaldehyde, acetaldehyde, etc.), alkenes 

(ethylene, propene, etc.), and aromatic compounds (benzene, toluene etc.) were 

measured. Here, we present a subset of the full data set. Figure 8a is a plot of the HCHO 

EI as a function of exhaust gas temperature for JP-8 and FT-2 fuel combustion. The 

HCHO EIs for JP-8 are 10-20% higher than for FT-2 combustion. The reduction in the 

HCHO EI is, therefore, roughly in line with that observed for total hydrocarbons (see 

Figure 4). This is an interesting observation given that the total hydrocarbon flame 

ionization method does not detect HCHO emissions (Spicer et al., 1992). The reduction 

in HCHO emissions associated with FT fuel combustion is therefore consistent with the 

conclusion that the observed 37% decrease in THC emissions was statistically significant. 

Figure 8b plots the benzene EI as a function of exhaust gas temperature. The effect of 

fuel composition on benzene emissions is much stronger than observed for HCHO as 

benzene is reduced by a factor of two when FT-2 fuel replaces JP-8. We attribute the 

large effect of fuel composition on the benzene EI to the fact that JP-8 contains 18.55 

vol% aromatics (presumably dominated by single-ring alkyl chain substituted 

compounds), whereas FT-2 fuel contains 0.6 vol% aromatics. The 2-fold reduction in 

benzene emissions is consistent with previous measurements of benzene emissions for FT 

fuel combustion and with the hypothesis that benzene is formed both by decomposition 

of fuel aromatic compounds ("top down") and recombination of smaller products of 

incomplete combustion ("bottom up") chemical pathways. (Richter and Howard, 2001; 

Zhang et al., 2009; Hansen et al., 2009; Marchal et al., 2009; Tosatto et al., 2009).

In practice, we have found that VOC EIs can be very sensitive to modest changes in 

ambient temperature or aircraft engine fuel flow (Timko et al., 2010a, Yelvington et al., 

2007, Knighton et al., 2007, Herndon et al., 2009). Therefore, the impressive decreases 

in the benzene EI shown in Figure 8b might plausibly be caused by something other than 

differences in fuel composition. More detailed analysis of the benzene to HCHO ratio 

confirms that the benzene reduction is almost certainly due to differences in fuel 

composition and not an experimental artifact. Since, for a given fuel, various 

hydrocarbon EIs tend to vary in scale with one another (Knighton et al., 2007), the ratio 

of one hydrocarbon EI to the next is much more reproducible than the absolute 

hydrocarbon EIs. Plotting individual VOC EIs as functions of HCHO (or C2H4) has been 

a useful tool for characterization of aircraft VOC emissions (Herndon et al., 2009). 

Figure 9 plots the benzene EIm as a function of HCHO. As expected from prior aircraft 

emissions data, the benzene EI varies linearly with the HCHO EI. Interestingly, the slope 

of the best fit line depends on fuel. Specifically, the FT-2 fuel benzene/HCHO slope is 

noticeably less than the JP-8 best-fit slope. We take the data in Figure 9 as confirmation 

that combustion of FT-2 fuel has reduced benzene emissions relative to JP-8 combustion. 
APPENDIX M

300

Figure 8. Emission indices for: (a) formaldehyde; and (b) benzene.

0.00

0.05

0.10

0.15

0.20

0.25

0.30

300 350 400 450 500 550 600 650

Exhaust Gas Temperature (°C)

HCHO Emission Index (g/kg fuel)

JP-8

FT2

0.000

0.005

0.010

0.015

0.020

0.025

0.030

0.035

0.040

0.045

0.050

300 350 400 450 500 550 600 650

Exhaust Gas Temperature (°C)

Benzene Emission Index (g/kg fuel)

JP-8

FT2
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Figure 9. Benzene vs. formaldehyde emission indices.

6.6 PM Mass Emissions

The PM mass emission indices (EIm) calculated from the experimental data obtained by 

MST, EPA, and NASA-Langley are shown in Figure 10a for JP-8 fuel and Figure 10b for 

FT-2. These values were derived from the SMPS PM number concentrations assuming 

unit particle density. 

As shown by Figure 10a, the EIs for JP-8 obtained by the three groups decline linearly 

from about 700 mg/kg fuel to 200 mg/kg with increasing load on the turbine (EGT). In 

the case of the FT-2 fuel in Figure 10b, the mass EIs appear to decrease from 

approximately 80 to 20 mg/kg fuel with rising EGT. For FT-2 fuel combustion, however, 

the decrease in emissions with increasing EGT is more of an exponential function based 

on the data shown. Using the EPA data set, an overall average reduction in PM EIm of 

92% was obtained through the use of the FT fuel. Although EIm measurements showed 

50% variability between the various groups, the effect of fuel on EIm was large enough to 

be statistically significant. If the analysis is restricted to data measured by the same 

instrument, which should remove biases introduced by sampling line losses and 

instrumental differences, the statistical significance of the EIm reduction becomes even 

clearer.

The EPA mass EIs determined on February 2 are plotted in Figure 11 against EGT for 

both fuels along with comparable data collected by the U. S. Air Force for the same 

model APU as determined by Williams and Lee (1985). As shown in the figure, the Air 

Force JP-4 EI falls within the same range as the current EIm values for JP-8 but that for 

JP-5R is over a factor of 2 higher. The latter results are probably due to variations in fuel 

composition between JP-8 and JP-5R. 

0.000

0.005

0.010

0.015

0.020

0.025

0.030

0.035

0.040

0.045

0.00 0.05 0.10 0.15 0.20 0.25 0.30

HCHO Emission Index (g/kg)

Benzene Emission Index (g/kg fuel)

JP-8

FT2
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Figure 10. PM mass EIs (EIm) determined by MST, EPA, and NASA-Langley for: (a) 

JP-8; and (b) FT-2 fuels.

FT-2 Fuel

0

10

20

30

40

50

60

70

80

90

100

300 350 400 450 500 550 600 650

Exhaust Gas Temperature (oC)

Particle Mass Emission Index (mg/kg fuel)

MST

EPA

NASA-Langley (2/2/09)

JP-8 Fuel

0

200

400

600

800

1000

1200

1400

1600

1800

2000

300 350 400 450 500 550 600 650

Exhaust Gas Temperature (oC)

Particle Mass Emission Index (mg/kg fuel)

MST

EPA

NASA-Langley (2/2/09)

(a)

(b)
APPENDIX M

303

Figure 11. Comparison of mass EIs determined by EPA to other experimental results.

6.7 PM Number Emissions

Figure 12 provides the particle number emission indices (EIn) collected by Aerodyne, 

MST, EPA, and NASA-Langley for both JP-8 and FT-2 fuel. For JP-8 in Figure 12a, the 

Aerodyne, MST, and EPA EIs fall within the same range with the NASA results being 

slightly higher. In the case of the FT-2 fuel, however, the data appear to be segregated 

into two groups, with the MST and NASA EIs being generally higher than the EPA and 

Aerodyne results. This is interesting in the fact that the mass EIs shown previously are 

very close to each other regardless of which group collected the data. Possible 

explanations would be different losses of small particles in the sampling system, which 

would affect the EIn but not necessarily the EIm, and differences in the lower size cut of 

the instruments used by NASA/MST and EPA/Aerodyne. In any event, switching from 

JP-8 to FT-2 fuel reduces EIn – a statistically significant result. As with EIm, if the 

analysis is restricted to data measured by a single group, the statistical significance of the 

EIn reduction becomes even stronger. 

Also shown by the data provided in Figure 12, the EIn for JP-8 decreases linearly from 

about 5(10)15 at low EGT to 3(10)15 particles/kg fuel at high EGT. For FT-2, the EIn also 

diminishes linearly with increasing EGT from a high of approximately 1.5 - 3(10)15 to a 

low of 0.5 – 1(10)15 particles/kg depending on which data set is used. Based on EPA data, 

an average 68% reduction in EIn was determined by comparing the FT-2 EIs to the results 

when the JP-8 fuel was used in the same test on February 2.

0

200

400

600

800

1000

1200

1400

1600

1800

300 350 400 450 500 550 600 650

Exhaust Gas Temperature (oC)

Particle Mass Emission Index (mg/kg fuel)

EPA JP-8 (2/2/09)

EPA FT-2 (2/2/09)

Air Force JP-4

Air Force JP-5R
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Figure 12. PM number EIs (EIn) determined by ARI, MST, EPA, and NASA-Langley 

for: (a) JP-8; and (b) FT-2 fuels.

FT-2 Fuel

0.0E+00

5.0E+14

1.0E+15

1.5E+15

2.0E+15

2.5E+15

3.0E+15

3.5E+15

4.0E+15

300 350 400 450 500 550 600 650

Exhaust Gas Temperature (oC)

Particle Number Emission Index (particles/kg 

fuel)

Aerodyne

MST

EPA

NASA-Langley

JP-8 Fuel

0.0E+00

2.0E+15

4.0E+15

6.0E+15

8.0E+15

1.0E+16

1.2E+16

1.4E+16

300 350 400 450 500 550 600 650 700

Exhaust Gas Temperature (o

C)

Particle Number Emission Index (particles/kg 

fuel)

Aerodyne

MST

EPA

NASA-Langley
APPENDIX M

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6.8 Particle Size Distribution (PSD)

The particle size distribution (PSD) of the PM emissions from the APU was determined 

by EPA, MST, and NASA-Langley using electrical mobility analysis (Yeh, 1993). For 

example, Figure 13 provides the EPA PSDs for the APU while burning both test fuels for 

the cold engine condition (increasing power from a cold start). As shown in Figure 13, 

the particle size is generally larger for JP-8 at the various power conditions as compared 

with the FT-2 fuel. A similar observation was also made for the main propulsion engine 

as discussed by Kinsey (2010). 

There are also several interesting features of the PSDs shown in Figure 13 which are 

worthy of note. The distributions tend to broaden or have "shoulders" suggesting the 

presence of one or more minor modes in the range of 30-60 nm for JP-8 and 20-60 nm for 

the FT fuel. These features are mainly present at EGTs > 475 oC for JP-8 and at all power 

levels for FT-2. Possible explanations for the observed features in the PSDs include 

particle microphysics in the long sampling line or ingestion of ambient particles, though 

ingestion of ambient particles seems unlikely given the sampling probe configuration 

(Figure 2).

Probably the best way to compare the PSDs developed from the data collected by the 

various research teams is by plotting the geometric number mean particle diameter 

(GMD) and standard deviation of the PSD against EGT. Figure 14 provides the GMDs 

developed by the three groups for the two fuels tested in the APU. As can be seen, the 

GMDs tend to decrease from about 50 to 20 nm with increasing EGT for JP-8 and 

approximately 30 to 20 nm for FT-2. The EPA values are also generally higher than those 

determined by MST or NASA for both fuels. The higher EPA GMDs observed could be 

the result of increased small particle losses in the sampling line which was considerably 

longer than that used by MST and NASA. When all of the PSD data are considered 

together, switching from JP-8 to FT-2 fuel has only a small effect on particle size. 

However consideration of PSD data within the same organization, as is more reliable 

given group-to-group differences, indicates a statistically significant reduction in particle 

size associated with FT-2 fuel combustion relative to JP-8.

With regard to the GSDs determined for the APU, the data from the three groups are 

shown in Figure 15 for both fuel types. As shown in Figure 15a for JP-8 fuel, the GSDs 

ranged from ~ 1.7 to 2 depending both on EGT and which group collected the data. For 

FT-2 (Figure 15b), the GSDs were substantially smaller ranging from about 1.6 to 1.8 

depending on EGT. In addition, the EPA GSDs shown in Figure 15 are generally smaller 

than the other data collected for both fuel types which again may be due to differential 

small particle losses in the longer EPA sampling line.
APPENDIX M

306

Figure 13. Example differential EIn particle size distributions for APU burning: JP-8 

fuel; and FT-2 fuel.

0.0E+00

1.0E+15

2.0E+15

3.0E+15

4.0E+15

5.0E+15

6.0E+15

7.0E+15

1 10 100 1000

Particle Mobility Diameter (nm)

dEIn/dlogDp (particles/kg fuel)

EGT 345

EGT 365

EGT 475

EGT 555

EGT 610

JP-8 Fuel

0.0E+00

5.0E+14

1.0E+15

1.5E+15

2.0E+15

2.5E+15

3.0E+15

1 10 100 1000

Particle Mobility Diameter (nm)

dEIn/dlogDp (particles/kg fuel)

EGT 360

EGT 475

EGT 555

EGT 610

FT-2 Fuel
APPENDIX M

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Figure 14. Geometric number mean particle diameter for: (a) JP-8; and (b) FT-2.

10

20

30

40

50

60

300 350 400 450 500 550 600 650

Exhaust Gas Temperature (oC)

Geometric Mean Electrical Mobility Diameter (nm)

EPA FT-2

MST FT-2

NASA FT-2

(b)

10

20

30

40

50

60

300 350 400 450 500 550 600 650

Exhaust Gas Temperature (oC)

Geometric Mean Electrical Mobility Diameter (nm)

EPA JP-8

MST JP-8

NASA JP-8

(a)
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308

 

Figure 15. Geometric standard deviation of the PSD for: (a) JP-8; and (b) FT-2.

1.5

1.6

1.7

1.8

1.9

2.0

2.1

300 350 400 450 500 550 600 650

Exhaust Gas Temperature (oC)

Geometric Standard Deviation (-)

EPA FT-2

MST FT-2

NASA FT-2

(b)

1.5

1.6

1.7

1.8

1.9

2.0

2.1

300 350 400 450 500 550 600 650

Exhaust Gas Temperature (oC)

Geometric Standard Deviation (-)

EPA JP-8

MST JP-8

NASA JP-8

(a)
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6.9 Smoke Number

Smoke Number (SN) measurements were acquired using the AEDC probe shown in 

Figure 2. The instrument was operated according to SAE ARP1179, except that

measurements were acquired only at a small spatial region and not spatially 

integrated/averaged across the exit flow field. The SN data should be used with caution 

for comparisons or correlations to particle mass since CO2 measurements were not 

performed on the SN sample line to verify that the sample consisted primarily of APU 

core exhaust. The AEDC probe was also not strictly co-located with other probes and 

there were moderate cross winds during the measurement. Other particle and gas 

measurements are pseudo corrected for by a conversion to emission index which 

essentially ratios the measured data to the CO2 concentration, but not for the smoke 

number measurements.

Figure 16 shows the SN data versus EGT measured by AEDC. According to SAE 

ARP1179, the smoke number measurement is accurate to ±3.0, even though 

measurements for a given smoke meter are usually repeatable to ±1.5 for a constant 

combustion source. As seen in Figure 16, the APU SN measurements were approximately 

constant (within ±2.0) over the range of EGT for each fuel, respectively. 

Figure 16. Smoke Number measurements measured for JP-8 and FT-2 fuel.

0

2

4

6

8

10

12

14

16

300 350 400 450 500 550 600 650

Exhaust Gas Temperature (°C)

Smoke Number (Dimensionless)

JP-8 Fuel (2-Feb)

FT-2 Fuel

JP-8 Fuel (29-Jan)
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6.9 PM Chemical Characterization

6.9.1 Black Carbon Emissions

Figure 17 presents the BC mass EIs as determined by Aerodyne and NASA-Langley for 

both fuels tested as determined using the multi-angle absorption photometer (MAAP) 

developed by Petzold and Schonlinner (2004). As shown, the BC emissions tend to 

decrease linearly for both fuels, with the decline most apparent for JP-8. For JP-8, the 

EIs declined from approximately 450 to 200 mg/kg fuel with increasing EGT with the 

FT-2 EIs decreasing from a high of 80 mg/kg to a low of 20 mg/kg over the same 

operating range. Also note that the BC EIs are very similar to those shown previously for 

the PM EIm which would be expected since the sample was collected at the engine exit 

and thus should represent only non-volatile soot. The data shown in Figure 17 indicate a 

clear and statistically significant reduction in black carbon EI across the entire EGT range 

studied here.

Figure 17. BC emission indices as determined by ARI and NASA-Langley.

The PM BC data reported in Figure 17 are roughly half that reported for the SMPS data 

in Figure 10. The differences between the BC EIs (Figure 17) and the EIm (Figure 10) 

are probably due to a systematic departure from unit density that was assumed to estimate 

EIm from the SMPS data. The reductions in BC emissions from the use of the FT fuel 

were also similar to those determined for the PM EIm which was in the range of about 

90% over all operating conditions.

0

100

200

300

400

500

600

700

800

300 350 400 450 500 550 600 650

Exhaust Gas Temperature (oC)

Black Carbon Emission Index (mg/kg fuel) 

Aerodyne JP-8

Aerodyne FT-2

NASA JP-8

NASA FT-2
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6.9.2 Surface Polycyclic Aromatic Hydrocarbons

During the APU testing, a number of specialized instruments were employed to 

determine the chemical composition of the PM emissions and their resulting emission 

indices. Figure 18 provides EIs for particle surface polycyclic aromatic hydrocarbons 

(PAHs) as determined by EPA using the PAS 2000 instrument. As can be seen from the 

figure, the PAH EIs generally decrease with increasing EGT with the EIs for the FT fuel 

being somewhat lower than those for JP-8 for all engine operating conditions. The PAH 

EIs range from a low of about 30 to almost 2000 μg/kg fuel depending on EGT and fuel 

type. A number of reliability problems have been found with the PAS instrument in other 

studies of this type (Kinsey, 2009) and thus the data shown in Figure 18 should only be 

used to assess trends and not considered as absolute values.

Figure 18. PM surface PAH emission indices as determined by EPA.

6.9.3 Speciated Emissions

The Aerosol Mass Spectrometer (Jayne et al., 2000; Canagaratna et al., 2007; Timko et 

al., 2010b) was also used to chemically characterize the PM emissions from the APU. 

Figure 19 presents the organic and sulfate volatile PM mass EIs for the APU. Several 

features are obvious in Figure 19: (1) the organic EI decreases with increasing EGT; (2) 

the sulfate EI is reasonably constant with respect to EGT, at a value of approximately of 

1.2 mg/kg for JP-8; (3) both the organic and sulfate EI decrease substantially when JP-8 

fuel is replaced with FT fuel with the organic EI being reduced by a factor of 5; and (5) 

the sulfate EI for FT fuel combustion is less than instrument detection limits (here, 

roughly 0.1 mg/kg). The reductions in organic and sulfate PM mass emissions are 

statistically significant with the decrease in the sulfate EI directly related to the 

0

500

1000

1500

2000

2500

3000

300 350 400 450 500 550 600 650

Exhaust Gas Temperature (oC)

PM Surface PAH Emission Index (ug/kg fuel)

JP-8

FT-2
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Figure 19. Mass emission indices vs. EGT for: (a) PM organics; and (b) PM sulfate.

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

1.8

2.0

300 350 400 450 500 550 600 650

Exhaust Gas Temperature (°C)

Sulfate Emission Index (mg/kg fuel)

JP-8

FT-2

0.0

1.0

2.0

3.0

4.0

5.0

6.0

7.0

8.0

300 350 400 450 500 550 600 650

Exhaust Gas Temperature (°C)

Organic Emission Index (mg/kg fuel)

JP-8

FT-2

(a)

(b)
APPENDIX M

313

negligible fuel sulfur content of the FT fuel. For JP-8, the sulfate EI that we measure 

corresponds to roughly 0.03% conversion of fuel sulfur to condensable sulfate. We 

regard this estimate of sulfur conversion to be a lower limit and suspect that sulfur may 

be lost due to condensation onto the sampling line walls either as particle sulfate or gas 

phase sulfuric acid. Particle size distributions (see below) indicate that the majority of 

the PM was likely in a size mode that is well sampled by the AMS; however, PM residing 

in particles smaller than 50 nm will only be partially sampled, and this may contribute to 

the low SO2 to sulfate conversion efficiency that we have measured.

The AMS provides information on the composition of the organic PM emissions. Figure 

20 contains mass spectrometer plots of the APU exhaust particles obtained for JP-8 and 

FT-2 fuel combustion. Focusing first on the comparison of FT-2 fuel and JP-8 (at a 

consistent exhaust gas temperature of roughly 350 °C), both types of PM emissions 

contain m/z 41/43, 55/57, 69/71 features that are consistent with aliphatic hydrocarbons. 

The ratio of the important mass peaks, m/z 55 and 57, is approximately the same for both 

types of combustion particles, consistent with similar branching and/or bond saturation 

for JP-8 and FT-2 fuel combustion PM. The primary difference in the JP-8 and FT-2 fuel 

PM mass spectra is that JP-8 contains the m/z 77, 91, 115 series, whereas FT-2 fuel PM 

does not. The m/z 77, 91, 115 series is typically attributed to aromatic fragments. 

Therefore, the contribution of the m/z 77 series to JP-8 PM and its absence from FT-2 

fuel PM is consistent with the trace gas benzene data shown previously. Comparing JP-8 

PM composition data at the two exhaust gas temperatures (i.e., 345 °C and 650 °C) 

indicates that the aliphatic signature remains while the aromatic signature decreases. 

Interestingly, a new mass indicator, m/z 87, appears in the JP-8 APU PM mass spectrum 

at an exhaust gas temperature of 650 °C. The m/z 87 fragment is not typically attributed 

to either aliphatic or aromatic compounds (McLafferty and Turacek, 1993) and may 

instead be an oxidized hydrocarbon, although that assignment is speculative at this time. 

In previous aircraft measurement campaigns (Timko et al., 2010b), we have frequently 

found evidence of lubrication oil in aircraft PM exhaust. Lubrication oil is readily 

identified by its unusual fragmentation pattern, consisting of m/z 85, 113, 127, and 

sometimes several other masses. Therefore, when an unusual mass spectrum is obtained, 

lubrication oil should be considered as a potential source. However, the APU engine 

used the same lubrication oil as the CFM56-2C1 engine (Mobile II) and the m/z 87 

fragment is not consistent with the aircraft lubrication oil fragmentation pattern (Timko et 

al., 2010b). Therefore, we conclude that the m/z 87 mass fragment observed in the APU 

exhaust is not attributable to lubrication oil – unless the lubrication oil had previously 

undergone substantial oxidation and/or pyrolysis conversion.
APPENDIX M

314

Figure 20. Representative particle mass spectra for APU exhaust PM.

6.9.4 Speciated Emissions by Particle Size

The AMS measures vacuum aerodynamic diameter size distributions that complement the 

electric mobility diameter size distributions discussed above. Figure 21 provides AMS 

size distribution data collected for JP-8 and FT-2 fuel combustion at an exhaust gas 

temperature of 345 °C. The AMS size distribution data for JP-8 combustion exhibits 

clear bimodal behavior. The peak at approximately 60 nm corresponds to soot. The 

peak at 220 nm may correspond to the shoulder observed in the electrical mobility 

diameter data. The 220 nm mode may be from an engine source, or it may be ambient 

aerosol that was ingested into the sample extraction probe. Given the high ratio of 

organic to sulfate present in the 220 nm mode and the positioning of the sampling inlet 

relative to the exhaust outlet, the 220 nm mode is unlikely to be ambient particles. The 

FT-2 fuel combustion data show an apparent peak at approximately 40-50 nm; however, 

the signal/noise ratio is insufficient to be more quantitative. Interestingly, the 220 nm 

peak is absent from the FT-2 combustion data, suggesting either that ingestion of ambient 

air is a random phenomenon or that the 220 nm peak has a combustion origin.
APPENDIX M

315

Figure 21. Vacuum aerodynamic diameter size distribution collected by the AMS for JP8 and FT-2 fuel combustion.

Given the low signal-to-noise of the FT-2 vacuum aerodynamic diameter data, we 

continued our analysis of the AMS size distributions by focusing strictly on JP-8 

combustion data. Figure 22a contains chemically resolved AMS size distribution data 

collected at 345 °C exhaust gas temperature for JP-8 combustion. Both organic and 

sulfate data are shown. The distribution that peaks at 60 nm appears to consist of 

approximately 20% sulfate material and 80% organic material, consistent with the data 

presented in Figure 13, and to be internally mixed. The portion of the size distribution 

that peaks at 220 nm also contain well mixed organic and sulfate components and may 

contain a larger percentage of organic material than the 60 nm peak. 

Figure 22b contains vacuum aerodynamic diameter data for JP-8 combustion as a 

function of exhaust gas temperature. Two modes are apparent in the JP-8 AMS particle 

size data: a primary mode centered at 60 nm; and, consistent with the electrical mobility 

diameter data, a secondary distribution centered at 220 nm. The peak in the primary 

AMS size distribution trends to smaller sizes as exhaust gas temperature increases. The 

primary peak only shifts approximately 10 nm as exhaust gas temperature increases from 

345 °C to 610 °C but the trend is consistent as exhaust gas temperature is incrementally 

increased. Instead of shifting in response to changes in exhaust gas temperature, the 220 

nm secondary peak disappears entirely at an EGT of 610 oC.

0.0E+00

5.0E-03

1.0E-02

1.5E-02

2.0E-02

2.5E-02

3.0E-02

10 100 1000

Vacuum Aerodynamic Particle Diameter (nm)

dlogM/dlogDva/ppm CO2

JP-8

FT2

EGT = 345 °C
APPENDIX M

316

Figure 22. Vacuum aerodynamic diameter size distribution data for JP-8 combustion 

presented as: (a) chemically resolved organic and sulfate material; and (b) organics as a 

function of exhaust gas temperature.

0.0E+00

5.0E-03

1.0E-02

1.5E-02

2.0E-02

2.5E-02

3.0E-02

10 100 1000

Vacuum Aerodynamic Particle Diameter (nm)

dlogM/dlogDva/ppm CO2

EGT = 345C

EGT = 475C

EGT = 555C

EGT = 610C

Organic Size Distribtion JP-8 Combustion

0.0E+00

5.0E-03

1.0E-02

1.5E-02

2.0E-02

2.5E-02

3.0E-02

10 100 1000

Vacuum Aerodynamic Particle Diameter (nm)

dlogM/dlogDva/ppm CO2

Sulfate

Organic

EGT = 345 °C

JP-8 fuel
APPENDIX M

317

7. Conclusions

The following conclusions were reached from the data presented above comparing 

emissions characteristics of the APU burning JP-8 and FT-2 fuels:

• Major reductions in the SO2 emissions were determined for the FT-2 fuel due to 

the lack of sulfur in the fuel. Only small differences were found in the THC, CO 

and NOx emissions, however, between the two fuels tested.

• Significant reductions in both the EIm and EIn were observed for the use of FT-2 

fuel in the APU. These reductions were on the order of > 90% for the EIm and 

68% for EIn, respectively. Differences were found in the EIn data for the four 

research teams participating in the study, with the NASA-Langley results being 

generally higher.

• The sizes of the particles generated by the APU for JP-8 are substantially larger 

than those emitted by the APU burning FT-2 with the GMDs ranging from 20 to 

50 nm depending on EGT and fuel type. Also, the particle size of the APU 

emissions are considerably larger than that observed for main propulsion Engine 3 

burning the same fuel.

• Similar to that found for the EIm, the BC EIs decrease with increasing EGT 

indicating that non-volatile particles were being sampled. However, the BC data 

reported are roughly half of that reported for the SMPS. These differences are 

probably due to a systematic departure from unit density that was assumed to 

estimate EIm from the SMPS data.

• Particle-bound sulfate and organics were both reduced during combustion of the 

FT-2 fuel. Consistent with the reduction in SO2 emissions, particle-bound sulfate 

emissions were reduced by nearly 100%. Particle-bound organics were reduced 

by a factor of 5 as compared to JP-8.

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9. Acknowledgements

Missouri S&T and ARI were funded by the Federal Aviation Administration (FAA)

through the Partnership for AiR Transportation for Noise and Emissions Reduction

(PARTNER) – an FAA/NASA/Transport Canada-sponsored Center of Excellence under 

Grant No. 07-C-NE-UMR Amendments 006 and 007 (Carl Ma, Project Manager). Any 

opinions, findings, and conclusions or recommendations expressed in this paper are those 

of the authors and do not necessarily reflect the views of the FAA.
APPENDIX N

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APPENDIX N: Insights Into The Combustion Chemistry Within a Gas-Turbine 

Driven Auxiliary Power Unit as a Function of Fuel Type and Power Level Using 

Soot Nanostructure as a Tracer

R. L. Vander Wal

Pennsylvania State University

Abstract

Particulate emissions were collected from an Auxiliary Power Unit (APU) directly upon 

transmission electron microscope (TEM) grids for particle characterization by highresolution transmission electron microscopy (HRTEM). Carbonaceous emissions from 

two fuels, a coal-based Fischer-Tropsch and standard JP-8, were compared at three power 

levels each. Differences in soot nanostructure, specifically fullerenic content, illustrate 

changes in the combustion chemistry with engine power level, as do differences in 

aggregate size between the two fuels. As inferred from the soot nanostructure, 

comparison between fuels demonstrates the impact of fuel structure upon combustion 

chemistry.

Introduction

A vast, ground-based infrastructure that is largely unrecognized supports aircraft 

operations. One of the most prevalent, whether as a stand-alone, independent unit for 

smaller aircraft or as built-in units on many jets, is auxiliary power units, APUs. As the 

name implies, these units supply power for lighting, air conditioning, engine starts and 

other electrical needs until the jet engines are operative. With respect to exposure, these 

units pose the greatest particulate emissions hazard to which baggage and freight 

handlers, food service caterers, ground crews, etc. are exposed as these ground support 

personnel work in and around the parked aircraft during operation of the APUs, in 

contrast to having departed prior to aircraft engine operation and jet roll-back. 

Soot archeology

Archeology is uncovering details of the past by examination of relics and artifacts. 

Classification and characterization of objects may be grouped into the generic categories 

of shape, structure and composition. Such details can both date the item as well as permit 

its history to be traced. Archeologists use both large and small tools to pick apart the 

objects and a variety of analytical techniques to characterize structure and composition. 

Significant insights may be gained by combining knowledge gained from archeology 

with that from other fields to obtain a more complete picture of the local environment, 

temporal continuity, or lack thereof, and evolution as affected by external factors. 

Traditionally soot has been viewed as a pollutant or an incidental byproduct of 

incomplete combustion [1]. Recently soot nanostructure has been recognized as a 

valuable characterization goal for its relevance to soot reactivity, e.g. oxidation [2-5]. In 

this proposal, we propose soot archeology as an alternative paradigm to obtain insights 

into the combustion dynamics. Unlike gas phase species, soot nanostructure provides an 

integrated history of the combustion environment. Its radial nanostructure provides a 

timeline reflective of the gas phase chemistry during particle inception, growth and 
APPENDIX N

322

oxidation. Therein soot nanostructure serves as a tracer of the local combustion 

environment. This history is inclusive of chemical origin, growth and partial oxidation. 

Sampling and quenching chemical species within a gas turbine engine is enormously 

challenging as well as implementing non-intrusive optical diagnostics. To date, the 

approach followed is to use exhaust species as a benchmark by which to infer all reaction 

chemistry that ultimately led to their formation. This end-product approach possesses 

extreme sensitivity to extrapolated upstream chemistry, both spatially and temporally. In 

general, single concentration values of end products are non-unique. Other 

supplementary data, however obtained, whether chemical or physical in nature, can help 

to anchor numerical codes and their trajectories [6]. Here we suggest that soot 

nanostructure is one such data type that offers a temporal trace of the combustion 

environment from the fuel nozzle to the exhaust. Presently our results are qualitative and 

quantitative analyses of the HRTEM image data via image analysis algorithms will be 

presented elsewhere. Nevertheless, this non-traditional approach has the potential to 

provide breakthrough insights into both chemistry and fluid dynamics within the gasturbine engine environment as a function of both fuel type and engine power. An 

example of this archeological concept is applied here to the APU emissions as a function 

of power.

Experimental

For reader convenience, pertinent experimental details are repeated here. The sampling 

probe details may be found in the Appendix entitled, "XX", as will the nominal fuel 

compositions. The FT fuel (designated elsewhere in this report as FT2) is a FischerTropsch fuel derived from coal. It contains linear, branched and cycloparaffins the JP-8 

contains these in addition to ~ 18% aromatic content with a very low sulfur content of ~ 

0.8 wt.%.

The APU is located in the forward baggage compartment and is essentially a small, lowtechnology, gas-turbine engine known as a Honeywell Model GTCP85-98CK. When 

powered, its exhaust is mixed with bleed air and blown out through a shuttered port on 

the starboard side of the aircraft, just ahead of the wing spar. This particular APU is 

designed mainly for ground operation and is not certified for use at altitude for engine 

restart. The following are general specifications for the APU: Two-stage centrifugal 

compressor, single-stage radial inflow turbine and single can combustor. Further details 

may be found elsewhere in this report [Overview]. Sampled exhaust was diluted with dry 

N2 to reduce condensable gas concentrations and prevent particle coagulation with the 

TEM grid, directly capturing particulate emissions by impaction. 

For HRTEM imaging at NASA Glenn, soot was deposited on a lacey C/Cu grid by 

depositing a drop of the soot suspension created by ultrasonication in ethanol. TEM 

images were taken using a Phillips CM200 having nominal resolution of 0.14 nm with 

Gatan Image Filter (GIF) for digital imaging, featuring live Fourier transforms having 

nominal resolution of 0.14 nm. The instrument was operated at 200 keV using a LaB6 

filament. Gatan image software v. 3.4 was used for microscope operation.
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323

In general, APUs are tested in three operating modes, each representing a specific load on 

the turbine: (1) no-load (idle); (2) ECS (all air-conditioning [A/C] packs operating); and 

main engine start (MES). During the NASA Alternative Aviation Fuel Experiment 

(AAFEX), however, only condition 3 could be identified along with several other lower 

load points. Since the lack of engine instrumentation prevented an accurate 

determination of load on the APU, it was decided to present all of the emissions data in 

terms of exhaust gas temperature (EGT) that was used as an indicator of total load on the 

turbine.

Results 

Images are divided into three groups, one for each power level of the APU. Within each 

group is a comparison between data for the two different fuels. This data consists of 

HRTEM images at a series of magnifications to illustrate the different size scales of the 

particulate emissions. Each scale is related to the combustion chemistry differences 

between the fuels. 

Figure 1a. Comparison between particulate matter produced at low (generator mode) by 

the APU running on JP-8 or FT2 fuel, as indicated. A vast size and morphology 

difference was observed depending upon which fuel was used. As outlined in the text, 

particles were captured directly upon the TEM grid. Notably very small (ultrafine 

particles) were produced by the FT2 fuel. These aggregates consisting of few primary 

particles were frequent in occurrence, qualitatively comprising ~ 50% of observed 

aggregates.
APPENDIX N

324

Figure 1b. Higher magnification images illustrating the connectivity (microstructure) 

between subunits, i.e. primary particles. That high similarity of particle fusion observed 

suggests that aerosol dynamics governs this structural parameter.

Figure 1c. HRTEM images illustrating the prevalent fullerenic nanostructure in 

particulate derived from both fuels. Curved lamella, in stacks of 2-3 form near spherical 

objects that are often closed or nearly so. Notably their interiors appear to be voids. 

Sizes range from ~ 2 nm to 5 nm which would nominally correspond to C96 and C512 

fullerenes.
APPENDIX N

325

Figure 2a. Comparison between aggregates as captured, produced at the intermediate 

power setting of the APU, "park mode". Images are shown for FT2 and JP-8 derived 

particulate. For these conditions it is more difficult to discern whether significant 

differences in aggregate size or morphology exist between fuels.

Figure 2b. Higher magnification images of aggregate microstructure for the 

corresponding fuels as indicated, at the intermediate power level "park mode". 

Characteristic of particulate from gas turbine engines is the compact, highly fused 

morphology, reflecting reaction limited particle cluster growth. 
APPENDIX N

326

Figure 2c. A further illustration of the fullerenic nanostructure evident in particulate 

from the two fuels. Qualitatively there appeared to be lesser degree of curvature or 

tortuosity in the fringes for the JP-8 fuel. Lattice fringe analysis is expected to quantify 

the differences and will be reported elsewhere.

Figure 3a. Overview of differences in aggregate size and morphology in particulate 

between the two fuels from the APU at high power, "motor mode". Notably very small 

(ultrafine) particles, even some single primary particles are evident for the FT2 fuel. The 

highly compact nature of the aggregates, particularly their central portions is not 

consistent with simple physical agglomeration of aggregates which would be expected to 

result in more open structures with greater interior voids and pockets. Therein it is 

unlikely that the clustering observed for the JP-8 fuel is solely due to agglomeration, 

though our sampling technique does not disallow that possibility. For this reason we do 

not quantify size, but rather couch our observations in terms of morphology.
APPENDIX N

327

Figure 3b. The degree of fusion between primary particle subunits was observed to be 

similar for both aggregates. Apparent differences reflect the primary particles appearing 

to be in a 2-d plane for small aggregates versus being surrounded by other primary 

particles in large aggregates. Therein primary particle number density is the more 

relevant metric and reflects the aggregation dynamics. This is turn will reflect the gasphase density of precursor species and corresponding concentration of primary particles.

Figure 3c. HRTEM images of primary particles from the indicated FT2 and JP-8 fuels. 

Notably the FT2 fuel produces yet fullerenic nanostructure and a higher overall degree of 

tortuosity (or curvature) in the lamellae overall. The loss of fullerenic nanostructure is 

evident in the JP-8 derived fuel that shows few curved lamellae and these with generally 

a low degree of curvature. Smaller curvature may be observed but only lamellae 

appearing as small "arcs", not closed shells or substantial portions thereof. 
APPENDIX N

328

Discussion

The APU unit is a miniature gas turbine engine operating with continuous rather than 

cyclic combustion as in a diesel engine (the later imposing combined temporal and spatial 

variations per cycle). Common to both engine types is that additional fuel is injected to 

realize increased power. By design, this leads to an overall increase in the fuel-air 

equivalence ratio. However, as modeling studies have shown, this measure is not a good 

predictor for soot emission levels [7]. Soot necessarily forms in fuel-rich regions with a 

non-linear dependence upon temperature [8]. Aerodynamics will also change as power 

levels increase [9]. This can change the size and relative spatial locations of fuel-rich 

recirculation zones that help to stabilize the flame. As temperature changes oxidizing 

rates necessarily will change. Nevertheless, such intertwined fluid mixing dynamics and 

temperature fields would be expected to be rather similar for both fuels as a continuous 

fuel spray is used. Different fluid dynamics with changing power levels does explain the 

overall trend of declining fullerenic content as discussed below. To the extent that the 

different fuels produce not only different soot yields at each power level but also soots 

with different nanostructures suggests that the chemistry differences between the fuels is 

responsible for the observed differences in both regards. 

PAH and soot formation sequence

Soot formation begins with the formation of unsaturated hydrocarbons and aromatic 

compounds that form soot precursor particles [10]. Continued growth and carbonization 

leads to recognizable primary particles that undergo further mass growth and aggregates 

through their coalescence, as outlined in Figure 1. Dehydrogenation to form acetylene 

and aromatics followed by radical addition processes are two key pyrolysis reactions for 

paraffinic (saturated) hydrocarbons [11]. By jumpstarting the result of thermal and 

oxidative pyrolysis processes, unsaturated hydrocarbons and aromatics can produce soot 

more readily than paraffinic compounds [12]. Therein the starting fuel has profound 

consequences on the combustion emissions.

While thermal pyrolysis leads to dehydrogenation, oxygen also accelerates soot 

production by increasing the concentration of precursors, as named above [13]. During 

initial oxidation, oxygen extracts H-atoms during oxidation yielding unsaturated 

hydrocarbons. However oxygen will also open new pathways to aromatic formation 

from paraffins by the formation of odd numbered carbon species [14]. Examples include 

allylic and propenyl radicals that can react with C2 to yield C5 rings by direct molecular 

recombination. Finally, some oxygenates such as acetaldehyde, even though appearing to 

be on a chemical path opposite dehydrogenation can react to form oxygenated aromatics 

(e.g. phenoxy radicals) with subsequent elimination to yield C5 membered rings [15, 16]. 

In summary, oxygen alters the concentration and identity of species acting as soot 

precursors and those contributing to additional mass growth.

Rationale to hydrocarbons

Synthetic fuels such as FT derived fuels are composed of paraffins and cycloparaffins. 

Generally they contain no aromatics. Aromatics and acetylene formation occurs only 

through pyrolysis processes which necessarily take time. The lack of initial precursor and 

growth species delays soot nucleation and growth [17]. Additionally, the higher H 
APPENDIX N

329

content slows oxygen-assisted dehydrogenation that produces unsaturated compounds 

such as poly aromatic hydrocarbons (PAHs). Premixing occurs for an increased time 

relative to soot formation and growth processes. Yields of partially oxygenated 

intermediates and odd numbered carbon species increase [18].

Both effects will increase the concentration of cyclopentadienyl radicals and aromatics 

containing C5 membered rings, e.g. naphthalene [19]. C5 membered rings have been 

shown to be integral to fullerene formation by enabling curvature of carbon lamella [20]. 

Therein it is the thermal and oxidative stability of the parent fuel that drives the fullerenic 

nanostructure of soot from a paraffinic fuel.

In contrast, the JP-8 fuel contains a significant fraction of unsaturated hydrocarbons and 

aromatics [Summary]. These species are significantly progressed, chemically, towards 

soot precursors and can directly serve as growth species without further (initial) 

dehydrogenation or oxidative pyrolysis reactions [21]. Soot formation begins upon 

formation of free radicals and H-atoms that continue radical chain propagation processes 

[12, 14, 15, 17, 21, 22]. Concurrently the other pyrolysis processes associated with 

paraffinic species as a component of JP-8 can occur as discussed above but a) the 

presence of unsaturated compounds will compete for oxygen, these species being more 

susceptible to electrophilic species in general [22], and b) the unsaturated compounds can 

directly react with the paraffins to form alkyl substituted aromatics [23]. Through 

inhibition of oxidative pyrolysis and oxygenate formation, (by oxygen scavenging and 

direct reaction with paraffins), the aromatic content of JP-8 fuel causes fullenenic 

precursor concentrations to be lower than for the FT fuel, at least as aided by oxygen 

[24]. Therein the degree of fullerenic nanostructure in the soot decreases. It also 

declines for another reason; with unsaturated hydrocarbons and aromatics initially present 

in the parent fuel, the timescale for soot formation is dramatically cut relative to the pure 

paraffinic fuel. Consequently the degree of partial premixing prior to the onset of soot 

formation is much less. Therein the relative contribution of oxygen assisted soot 

formation (via oxidative pyrolysis reactions) is less and associated fullerenic 

nanostructure is diminished. 

That the FT derived (paraffin-derived) soot yet retains fullerenes and fullerenic 

nanostructure at the intermediate power while the JP-8 does not reflect the combustion 

chemistry dependence upon the nascent fuel. The fact that such structures are present 

attests to the delayed pyrolysis, lack of unsaturated hydrocarbons and aromatics, resulting 

time for increased fuel-air mixing with formation of oxygenated intermediates and odd 

numbered carbon species leading to cyclopentadienyl rings and C5 containing species. 

Notably this occurs at the molecular level prior to soot formation. Conversely, fullerenic 

structure for JP-8 derived soot is largely absent, reflecting its advanced pyrolysis state by 

virtue of high aromatic content in the nascent fuel. At high power, the higher initial fuel 

concentration for both fuels likely impedes the oxygen-assisted pathway towards 

fullerene formation, as witnessed by the reduced fullerenic nanostructure for each fuel, 

but just not at equal rates.
APPENDIX N

330

The inferred offset chemistries are also consistent with the overall lower soot production 

of the paraffinic fuel. This is perhaps the most significant find for green technologies for 

alternative or renewable fuels, e.g. biodiesel etc. or FT. These processes, based upon 

natural gas or coal, naturally produce paraffinic fuels. Their aromatic and naphthenic 

content is negligible. At any given power level emission indices by particle number or 

total particle mass (EIn) and EIm respectively) were lower for the FT fuel than for the JP8 fuel (q.v. Appendix X). As discussed, for a given fuel amount and power level 

(meaning similar aerodynamics and fuel-air mixing levels and temperature 

environments), the lower soot yield and particle number for the FT derived soot can be 

interpreted as reflecting a combination of a lowered rate of soot production and a higher 

rate of soot oxidation for the paraffinic fuel. Fullerenic nanostructure consists of highly 

strained carbon framework [25]. Alternatively, it may be considered as possessing a 

mixture of sp2 and sp3 bonds [26]. By either interpretation, it is more reactive towards 

oxidation as found experimentally and theoretically [2]. Therein the synthetic FT fuel is 

not only greener in their production but also from an emissions perspective.

Necessarily the combustion temperature will vary, as dependent upon both the fuel-to-air 

ratio [27]. Numerous combustion studies have sought to elucidate the relative effects of 

oxygen addition to the fuel stream. Competing factors are dilution that lowers the 

average temperature and premixing, which raises the average temperature [28-30]. 

Changes in the fuel-air ratio and as inferred here, changes in pre-mixing, impose both 

effects. However, changes in combustion temperature have been studied for purposeful 

production of fullerenes by combustion using partial premixing [31]. Not until 

temperatures exceed 2000 K do fullerenes arise by temperature effects [32]. Therein the 

chemical path is notably different as well, with PAHs no longer being thermodynamically 

stable but actually undergoing decomposition [33]. The combustion conditions within 

the turbine are entirely outside this parameter space. Even if temperature was playing 

some role in the production of fullerenic nanostructure, this would only arise by partial 

premixing which is inherent to the rationale set forth here as a necessary condition by 

which to explain the changes in chemistry reflected in the soot nanostructure.

Aggregate Size

The variation of fullerenic content is also consistent with the change in aggregate size. 

Differences in aggregate dimensions are clear from the side-by-side images of deposits 

upon the TEM grid. Given an unknown degree of aggregate-aggregate overlap, only a 

lower bound can be placed upon those derived from the JP-8 fuel, ~ 200 nm. By 

comparison, cursory inspection of aggregates from the FT fuel suggests two vastly 

different aggregate size classes, i.e. a bimodal size distribution. The averages are < 50 

nm and ~ 200 nm for both the low and high power tests based on over two dozen 

measurements. This former class is traditionally referred to as the "nucleation mode." 

These particles are composed of only one to a few primary particles. This bimodal 

distribution is unique to the FT fuel. Interestingly no such ultrasmall size class was 

observed at the intermediate power. The primary particles comprising these two 

aggregates are also significantly different. As summarized in Table 1, the mean size for 

mature aggregates is ~ 20 nm or larger, depending upon power level whereas the primary 

particles within the ultrafine mode aggregates is ~ 15 nm (as no ultrasmall aggregates 
APPENDIX N

331

were observed at the intermediate power, no primary particle sizes could be measured). 

The smaller number of primary particles within aggregates for the FT fuel compared to 

the JP-8 fuel suggests a lowered primary particle concentration, indicative of a lower 

concentration of nucleating species. The smaller primary particle size at the low power 

operation suggests a lower concentration of nucleation and growth species, i.e. PAHs and 

acetylene. This finding is consistent with both the FT fuel composition being devoid of 

aromatics and other unsaturated organics and the delayed onset of soot formation from 

paraffinic fuels compared to those with significant aromatic content.

Table 1. Primary Particle Size Results

Power Level Size, nm (within mature agg.)* Size, nm (in ultrasmall agg.)*

Low 24 +/- 3 15 +/- 3

Intermediate 17 +/- 2

High 19 +/- 2 21 +/- 3

* Size given in nanometers with uncertainty estimated by one Std. deviation.

Similar observations were found for the main engine tests (q.v. Appendix XX). For both 

low and high engine powers, a distinct smaller size class of aggregates was found. Their 

composition (and hence origin) differed, however, as inferred from HRTEM and x-ray 

photoelectron spectroscopic (XPS) analyses. 

Conclusions

Synthetic fuels composed of paraffinic species delay the onset of particle formation and 

growth by absence of dehydrogenated species and aromatics. This permits increased 

fuel-air mixing, increased formation of oxygenated intermediates and production of alkyl 

intermediates containing an odd number of carbon atoms, in addition to dehydrogenated 

molecules and aromatics. These species will increase the concentration of 

cyclopentadienyl radicals and aromatics incorporating them, such as naphthalene. Such 

compounds incorporated into graphene segments give rise to curvature and result in 

fullerenic nanostructure. The degree or content of fullerenic structure is here postulated 

to correlate with level of partial premixing. Nanostructure comparisons as a function of 

engine power supports this postulate as increased fuel concentration with increased 

(required) power decreases the level of partial premixing, both local and global. The 

result is a lesser content of fullerenic nanostructure, as observed by HRTEM. 

Comparisons between the FT and JP-8 fuels provides further support in that for the same 

power level, soot from the JP-8 fuel contains less fullerenic nanostructure, reflecting its 

substantial aromatic content, that accelerates soot formation which minimizes the impact 

of partial premixing. Differences in aggregate size between the two fuels at each power 

level are consistent with this interpretation. Therein soot nanostructure preserves a 

record of the gas phase species contributing to its formation and growth and can be used 

as an in situ tracer of the early combustion chemistry within the engine.
APPENDIX N

332

Acknowledgements

The author gratefully acknowledges sample collection during the weeks of field 

campaign testing by Dr. Kathleen Tacina (NASA Glenn) and overall project coordination 

and steadfast experimental aid and technical input by Dr. Bruce Anderson (NASA 

Langley). Vicky M. Bryg is acknowledged for TEM work and Mr. Chung-Hsuan Hunag 

(Penn State) for sizing analyses and Dr. John Kinsey (U.S. EPA) for graciously sharing 

his experimental data prior to publication. Support for this work was through the NASA 

Aeronautics Subsonic Fixed Wing (SSFW) Program, NASA Cooperative Agreement 

NNX09AD42A with The Pennsylvania State University, at University Park PA.

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APPENDIX O

336

APPENDIX O: Spatial Variation of PM Emissions at the Engine Exit

Donald E. Hagen, Prem Lobo, and Philip D. Whitefield

Center of Excellence for Aerospace Particulate Emissions Reduction Research

G-7 Norwood Hall, Missouri University of Science and Technology, Rolla, MO 65409

Introduction

Several studies have been carried out to characterize emissions from military engines 

and, more recently, commercial jet engines burning alternative aviation fuels. NASA 

sponsored a study called AAFEX: Alternative Aviation Fuels Emissions Experiment, to 

evaluate the impacts of synthetic fuels on commercial aircraft gaseous and particle 

emissions. The Missouri University of Science and Technology Center of Excellence for 

Aerospace Particulate Emissions Reduction Research (Missouri S&T COE) was a team 

member for AAFEX. The study was and was conducted in January 2009 in Palmdale, 

CA. The tests were performed on the same CFM56-2C1 engine studied during APEX-1 

The characteristics of the PM exhaust emissions can be spatially non-uniform over the 

engine exit plane. In this section of the report a methodology to characterize this spatial 

non-uniformity is described, a suitable metric is developed, and results are calculated for 

AAFEX PM emissions data. The analysis uses the derived parameters calculated from 

size distributions measured using a scanning differential mobility analyzer.

Instrumentation

The instrumentation onboard the Missouri S&T mobile laboratory to sample emissions at 

the engine exit plane consisted of the Cambustion DMS500, a state-of-the-art, fastparticulate spectrometer, to gather real-time, size-distribution information and total 

concentration of engine exhaust particulates. Also onboard was a scanning differential 

mobility analyzer (SDMA) (TSI model 3071), a traditional and slower instrument to 

measure aerosol size distributions, a TSI condensation particle counter (CPC) (TSI model 

3022) to measure total number concentration, and a fast response carbon dioxide (CO2) 

detector to monitor sample dilution and establish emission factors. The instruments have 

been extensively used in recent field campaigns to measure PM emissions from 

commercial aircraft engines burning conventional and as well as alternative aviation fuels 

(Lobo et al. 2007; 2010).

Methodology

Here the data reduction methodology is given to compute a metric, σk,var, to characterize 

exhaust spatial non-uniformity from the data collected from the engine mapping run. The 

measurement data set is represented by {apnij, δapnij, Aij}.

apn denotes an aerosol parameter of type n.
APPENDIX O

337

ap1 = number-based geometric mean diameter (Dgn),

ap2 = mass-based geometric mean diameter (Dgm),

ap3 = Geometric standard deviation in the size distribution (Sigma),

ap4 = Number-based emissions index (EIn), and

ap5 = Mass-based emissions index (EIm).

A grid is used to define sampling locations (xi,yj) in the engine exit plane; i denotes a 

horizontal position index, and j denotes sampling tip, i.e. vertical position. Grid locations 

relative to the center of the engine exit plane are given in Table 1.

Table 1. Sampling locations in engine exit plane

i xi(inches) j yj(inches)

3 3.5 3 5

2 2.0 2 3.5

1 0.5 1 2

0 -1.0 0 0.5

-1 -2.5 -1 -1

-2 -4.0 -2 -2.5

-3 -5.5 -3 -4

Let Aij denote the fractional area associated with each probe location; ΣijAij = 1. An area 

and uncertainty weighted average value is calculated for apn. This is our best estimate for 

what the whole engine will produce (engine average) regarding parameter n.

n = (Σijapnij Aij /δapnij

2

)/ (Σij Aij /δapnij

2

)

A normalized (fractional) value is computed for this parameter

bpnij = apnij / n

The normalization allows different types of parameters, e.g. Dgn and EIn, to be coupled 

on an equal basis. Now consider a weighted average normalized global aerosol 

parameter, , to represent the collection of aerosol parameters. An uncertainty and area 

weighted weight function is used:

wnij = wn Aij (apn/ δapnij)

2

.

wn is chosen by the user to give a desired relative weight to each aerosol parameter, e.g. 

w1(Dgn)=1, w2(Dgm)=1, w3(σ)=1, w4(EIn)=2, w5(EIm)=2.

= (Σnij wnijbpnij) / (Σnij wnij) = 1

We are not interested in itself, but rather its variance. The unbiased variance in is 

given by

Variance = (Σnij w’nij (bpnij- )

2

) / (1 – Σnij w’nij

2

) 

w’nij = wnij / Σnij wnij (normalized weight function).
APPENDIX O

338

This can be rewritten as:

Variance = [(Σnij wnij)( Σnij wnijbpnij

2

) – (Σnij wnijbpnij)

2

] / [(Σnij wnij)

2 - (Σnij wnij

2

)]

The standard deviation is taken as the usual square root of the variance.

σvar = (variance)1/2. 

σvar represents the variability (standard deviation) of PM emissions across the engine exit 

plane at the given engine power condition. 

σvar = {[(Σnij wnij)( Σnij wnijbpnij

2

) – (Σnij wnijbpnij)

2

] / [(Σnij wnij)

2 - (Σnij wnij

2

)]}1/2

Results

During the mapping phase of Project AAFEX, 12 grid points were selected for sampling 

at 4% power, 9 points at 65%, and 5 points at 85%. The locations in the engine exit plane 

are depicted in Table 2; the numbers in the grid cells indicate the power settings for 

which measurements were made at the indicated locations.

Table 2. Sampling locations in engine exit plane for mapping.

j i -3 -2 -1 0 1 2 3

-3 4%

-2 4%

-1 4%,65%,85% 65%,85% 65%,85% 4%,65% 65%,85%

0 4%,65%,85% 4% 4% 4% 4%,65%

1 4%,65%

2 4%

3 4%,65%

Measurement data for Dgn, Dgm, Sigma, EIn, and EIm taken at the locations and engine 

powers given in Table 2 were extracted from the master spreadsheet and are given in 

Appendix A. Measurements were taken on different days under different ambient 

temperature conditions, which can influence emissions. To suppress the differences 

associated with day-changes, the data for a given day were normalized to a reference day, 

i.e. the aerosol parameters, averaged over sampling locations were normalized to have the 

same daily average. The following normalization procedure was used:
APPENDIX O

339

Let {apn,pwr,day,loc} denote the data set for aerosol parameter apn for a given engine power 

(pwr), on a given day (day), and sampling location (loc). January 26 was selected as the 

reference day (rday); data from the other days was normalized to its data. 

Let Napn,pwr,day,loc denote the normalized data.

Napn,pwr,day,loc = apn,pwr,day,loc *< apn,pwr,rday,loc >/< apn,pwr,day,loc >,

where < > indicates an average taken over different sampling locations.

The spatially dependent PM emissions data for engine powers 4%, 65%, and 85% from 

Appendix A were processed using the following sets of parameter weight functions (1 

refers to Dgn, 2 – Dgm, 3-Sigma, 4 - EIn, 5 – EIm): (w1 w2 w3 w4 w5) = (0 0 0 1 1), (2 

2 1 5 5), and (1 1 1 1 1 ). For weighting (0 0 0 1 1), the size-distribution shape 

parameters are excluded and only emission indices are included, EIn and EIm, with equal 

weight. For (2 2 1 5 5) the size distribution shape parameters are brought into the 

analysis, with the geometric means having twice the weight as the width parameter, and 

the emission indices having the greatest weights. For (1 1 1 1 1) all, the aerosol 

parameters are included with equal weights. Since the data taken was relatively sparse, 

no attempt was made to define unique areas (Aij’s) to the sampling locations. All the 

areas were set to unity. The results for σvar (representing the variability of PM emissions 

across the engine exit plane at the given engine power condition) vary with different 

weight function choices. The results are given in Table 3. The variability is lowest at 

high power and maximum at the 65% power condition.

Table 3. PM emissions variability (standard deviation) in percent across engine exit 

plane.

Power σvar σvar σvar

(0 0 0 1 1) (2 2 1 5 5) (1 1 1 1 1)

4% 47.0 10.4 6.2

65% 68.9 21.6 14.9

85% 15.3 7.9 5.9

The emission indices have larger variabilities than the size distribution shape parameters. 

The PM emissions variability calculations were repeated at power conditions 4% and 

65% using un-normalized data. These results are shown in Table 4. Here the variability 

is always greater, by an average of 61%.

Table 4. PM emissions variability across engine exit plane using unnormalized data.

Power σvar σvar σvar

(0 0 0 1 1) (2 2 1 5 5) (1 1 1 1 1)

4% 74.8 12.9 7.3

65% 156.2 40.3 22.6
APPENDIX O

340

Conclusions

Spatially resolved PM emissions data was acquired at engine power settings of 4%, 65%, 

and 85%, during Project AAFEX. Most data was taken at low power, 4%. There was a 

good spread in the horizontal and vertical directions, but the sampling points were not 

well distributed; they were primarily taken near the horizontal and vertical centerlines. 

Data was taken on multiple days, introducing ambient temperature dependence into the 

data. A normalization of the data to a reference day temperature was done to suppress the 

effect of ambient temperature changes. The observed variability was power dependent –

minimum variability at the highest power and max variability at mid power. A 

dependence of the variability on how the PM emissions parameters were weighted in the 

analysis was observed. The emission indices showed more variability than the size 

distribution shape parameters. The observed variability in emissions ranged from 6% to 

70%.

Acknowledgements

This work was partly funded by the Federal Aviation Administration (FAA) through the 

Partnership for AiR Transportation for Noise and Emissions Reduction (PARTNER) – a 

FAA- NASA-Transport Canada- sponsored Center of Excellence under GrantNo.07-CNE-UMR Amendments 006 and 007. The authors would like to acknowledge the 

AAFEX team, and NASA DC-8 personnel for substantial contributions to the successful 

execution of this study.

References

Lobo, P., Hagen, D.E., Whitefield, P.D., and Alofs, D.J., "Physical characterization of 

aerosol emissions from a Commercial Gas Turbine Engine", Journal of Propulsion and 

Power, 2007, 23, 919-929.

Lobo, P., Hagen, D.E. and Whitefield, P.D., "Comparison of PM emissions from a 

Commercial Jet Engine burning Conventional, Biomass, and Fischer-Tropsch Fuels", 

manuscript in preparation 2010.
APPENDIX O

341

Appendix L-A

Table A1. Normalized aerosol parameters and their associated uncertainties at locations 

in Table 2 and engine power 4%.

Dgn

j/i -3 -2 -1 0 1 2 3

-3 15.9

-2 16.0

-1 16.4 14.9

0 15.1 16.3 15.6 14.6 14.4

1 14.8

2 14.7

3 16.2

Dgm

j/i -3 -2 -1 0 1 2 3

-3 40.1

-2 35.3

-1 38.9 29.2

0 34.4 29.0 36.9 29.6 28.9

1 25.2

2 24.3

3 45.8

Sigma

j/i -3 -2 -1 0 1 2 3

-3 1.46

-2 1.48

-1 1.48 1.40

0 1.42 1.41 1.43 1.39 1.39

1 1.36

2 1.34

3 1.47

EIn

j/i -3 -2 -1 0 1 2 3

-3 2.41E+15

-2 2.12E+15

-1 8.50E+14 3.31E+15

0 1.83E+15 4.08E+15 3.45E+15 4.43E+15 4.74E+15

1 6.15E+15

2 6.96E+15

3 2.37E+15
APPENDIX O

342

EIm

j/i -3 -2 -1 0 1 2 3

-3 0.0139

-2 0.0121

-1 0.0063 0.0124

0 0.0092 0.0095 0.0155 0.0131 0.0132

1 0.0193

2 0.0205

3 0.0157

δDgn

j/i -3 -2 -1 0 1 2 3

-3 0.30

-2 0.52

-1 0.30 0.51

0 0.50 0.30 0.30 0.55 0.30

1 0.61

2 0.30

3 0.30

δDgm

j/i -3 -2 -1 0 1 2 3

-3 7.89

-2 4.30

-1 9.80 4.30

0 4.30 4.30 5.61 4.30 4.30

1 4.30

2 4.30

3 9.44

δSigma

j/i -3 -2 -1 0 1 2 3

-3 0.016

-2 0.022

-1 0.016 0.028

0 0.025 0.016 0.016 0.016 0.016

1 0.034

2 0.016

3 0.016
APPENDIX O

343

δEIn

j/i -3 -2 -1 0 1 2 3

-3 3.84E+14

-2 6.85E+14

-1 3.84E+14 6.34E+14

0 3.84E+14 3.84E+14 3.84E+14 8.37E+14 3.98E+14

1 9.93E+14

2 3.84E+14

3 3.84E+14

δEIm

j/i -3 -2 -1 0 1 2 3

-3 0.0021

-2 0.0039

-1 0.0021 0.0024

0 0.0021 0.0021 0.0025 0.0021 0.0021

1 0.0044

2 0.0021

3 0.0025

Table A2. Normalized aerosol parameters and their associated uncertainties at locations 

in Table 2 and engine power 65%.

Dgn

j/i -3 -2 -1 0 1 2 3

-3

-2

-1 23.5 22.3 20.8 25.2 20.8

0 21.5 14.1

1 21.9

2

3 16.8

Dgm

j/i -3 -2 -1 0 1 2 3

-3

-2

-1 75.2 70.1 75.4 83.9 69.0

0 65.2 32.0

1 74.1

2

3 56.5
APPENDIX O

344

Sigma

j/i -3 -2 -1 0 1 2 3

-3

-2

-1 1.69 1.64 1.61 1.70 1.64

0 1.68 1.33

1 1.69

2

3 1.50

EIn

j/i -3 -2 -1 0 1 2 3

-3

-2

-1 7.26E+14 5.71E+15 3.80E+15 1.07E+15 4.40E+15

0 1.28E+15 1.96E+16

1 1.45E+15

2

3 1.14E+16

EIm

j/i -3 -2 -1 0 1 2 3

-3

-2

-1 0.0203 0.0500 0.0292 0.0246 0.0326

0 0.0306 0.0629

1 0.0230

2

3 0.0643

δDgn

j/i -3 -2 -1 0 1 2 3

-3

-2

-1 0.21 0.21 0.21 0.21 0.55

0 0.32 0.21

1 0.21

2

3 0.29
APPENDIX O

345

δDgm

j/i -3 -2 -1 0 1 2 3

-3

-2

-1 1.47 1.47 3.07 1.47 1.47

0 1.47 1.47

1 1.58

2

3 2.13

δSigma

j/i -3 -2 -1 0 1 2 3

-3

-2

-1 0.009 0.009 0.009 0.009 0.022

0 0.012 0.009

1 0.009

2

3 0.019

δEIn

j/i -3 -2 -1 0 1 2 3

-3

-2

-1 1.78E+14 1.78E+14 1.78E+14 1.78E+14 3.03E+14

0 1.78E+14 6.29E+14

1 1.78E+14

2

3 4.38E+14

δEIm

j/i -3 -2 -1 0 1 2 3

-3

-2

-1 0.0014 0.0016 0.0021 0.0014 0.0014

0 0.0014 0.0018

1 0.0014

2

3 0.0041
APPENDIX O

346

Table A3. Normalized aerosol parameters and their associated uncertainties at locations 

in Table 2 and engine power 85%.

Dgn

j/i -3 -2 -1 0 1 2 3

-3

-2

-1 27.9 25.9 26.2 26.4

0 16.3

1

2

3

Dgm

j/i -3 -2 -1 0 1 2 3

-3

-2

-1 71.8 71.2 75.4 71.3

0 65.4

1

2

3

Sigma

j/i -3 -2 -1 0 1 2 3

-3

-2

-1 1.78 1.77 1.78 1.77

0 1.73

1

2

3

EIn

j/i -3 -2 -1 0 1 2 3

-3

-2

-1 8.08E+141.43E+151.63E+15 8.43E+14

0 4.13E+15

1

2

3
APPENDIX O

347

EIm

j/i -3 -2 -1 0 1 2 3

-3

-2

-1 0.0578 0.0525 0.0660 0.0617

0 0.0709

1

2

3

δDgn

j/i -3 -2 -1 0 1 2 3

-3

-2

-1 0.44 0.44 1.01 0.44

0 1.00

1

2

3

δDgm

j/i -3 -2 -1 0 1 2 3

-3

-2

-1 0.93 0.93 2.70 0.93

0 1.34

1

2

3

δSigma

j/i -3 -2 -1 0 1 2 3

-3

-2

-1 0.018 0.018 0.041 0.018

0 0.042

1

2

3
APPENDIX O

348

δEIn

j/i -3 -2 -1 0 1 2 3

-3

-2

-1 2.04E+142.04E+143.07E+14 2.04E+14

0 6.52E+14

1

2

3

δEIm

j/i -3 -2 -1 0 1 2 3

-3

-2

-1 0.0018 0.0018 0.0059 0.0018

0 0.0018

1

2

3
APPENDIX P

349

APPENDIX P: Sampling System Effects On Particle Emission Measurements

B. E. Anderson, D. S. Liscinsky, A.J. Beyersdorf, C.H. Hudgins, K.L. Thornhill, M. 

Trueblood, E.L. Winstead, and L.D. Ziemba

1.0 ABSTRACT

To observe PM emissions in both the near- and far-field exhaust regimes, AAFEX 

deployed paired sample inlets at 1 and 30 m behind both DC-8 inboard engines and used 

long, unheated sampling lines to transport diluted sample from the inlets to diagnostic 

instruments housed in trailers or trucks parked just off the aircraft’s right wing. To 

characterize sampling system impacts on the downstream measurements, experiments 

and analyses were conducted to 1) determine size-dependent sampling line transport 

efficiencies; 2) examine particle formation and growth within the 30-m sampling lines; 3) 

determine PM spatial variability across the engine exhaust plane; 4) assess inlet 

collection efficiency as a function of flow velocity; 5) evaluate particle losses in the 1-m 

inlet probes; and 6) examine whether samples collected with modified gas inlet probes 

yield representative PM emission measurements. Important findings include the 

following. 

• After 35 hours of engine testing, up to 50% of particles of all sizes were lost in the 

long sample transport lines. Apparently the losses were modest initially, but increased 

in time as soot and other contamination accumulated on tubing walls. Indeed in the 

longest sampling line, transmission efficiency dropped ~5%/day over the course of the 

experiment.

• Under relatively cold conditions (~0o

C), volatile particle nucleation typically reached 

an equilibrium between formation and coagulation before reaching the 30-m inlet 

probe. However, volatile particle mass continued to form during the subsequent 16-

second transport time within sampling lines, potentially increasing calculated mass 

emission indices by 50 to 75% at high engine powers.

• Nonvolatile PM mass and number EIs were fairly stable and equivalent within 4" of 

centerline, suggesting that single point sampling in that region would yield emission 

parameters broadly representative (within 20%) of the entire engine. 

• At high engine thrust, PM emissions generally increased with freestream-to-sample 

inlet velocity ratio, Uo/U, suggesting that particle populations were being enhanced by 

virtual impaction. However, the enrichment trends did not faithfully follow subisokinetic flow predictions, and were thus possibly caused by other mechanisms.

• Nonvolatile PM emission indices measured from 30-m samples were systematically 

higher than measured at 1-m, indicating possible particle loss in the 1-m inlets or 

transport tubes; thermophoretic deposition and turbulent eddy impaction possibly 

account for these losses.

• PM emission measurements made on samples collected with a special particle probe 

and a gas probe with dilution gas introduced 1.5 m downstream typically agreed to 

within 10%, suggesting that existing gas certification sampling probes used by engine 

manufacturers may be modified to yield representative particle number, mass and PSD 

measurements. 
APPENDIX P

350

The sections below describe each of the sampling experiments and include 

comprehensive discussions of results and possible physical explanations for the observed 

PM measurements. The last section discusses lessons learned and provides a list of 

recommendations for future tests and improved sampling strategies. 

2.0 INTRODUCTION

The methods used to extract and transport PM samples from gas turbine engine exhaust 

to remotely located diagnostic instruments can have profound impacts on measured 

emission parameters. Losses in number and mass can occur through a variety of 

processes occurring on or within the sampling system including: catalytic oxidation on 

hot metal surfaces; turbulent impaction on the inlet probe, bends in tubing or abrupt 

changes in tubing diameter within valves or fittings; turbulent diffusion and inertial 

impaction to tubing walls; thermophoretic diffusion related to temperature gradients; 

particle coagulation or agglomeration; electrophoretic diffusion; and sedimentation. PM 

mass and numbers can also increase from condensation of low volatility gas-phase 

species onto the surface of existing particles; through homogeneous nucleation to form 

new ultra-fine-mode particles; or from inertial enrichment linked to sub-isokinetic 

sampling. Although some of these mechanisms have negligible effects on the submicron 

particles typically emitted by aircraft or can be avoided by using conductive tubing and 

valves and by diluting the samples soon after collection, the effects of others can only be 

dealt with by designing the system to maximize transport efficiency and then conducting 

careful characterization studies of each implementation to quantify the sampling losses 

and develop empirical equations for correcting important emission parameters such as 

number and mass EI. 

NASA has sponsored a number of experiments to characterize sampling system effects 

on aircraft emission measurements. For example, the Aerosol Measurement Workshop 

(AMW) conducted in 1999 at Langley included sampling of PM emissions from the 

NASA Langley T-38 to evaluate the efficiency of two aerosol inlets probes of vastly 

different design (Cofer et al., 2000). Results showed that nanometer-sized particles are 

easily lost to inlet surfaces if dilution air and wall cooling were not implemented in a 

careful fashion and that samples should be diluted soon after collection to prevent 

number losses due to coagulation. 

Using lessons learned during AMW and tests conducted in the propulsion test cell at 

NASA GRC, engineers from Arnold Engineering Development Center (AEDC, Robert 

Howard, POC) designed an inlet probe that introduced a concentric flow of dilution gas 

just downstream of the inlet tip; this probe was evaluated in laboratory tests conducted at 

the University of Minnesota and found to efficiently collect and transport particles in the 

20 to 200 nm size range (Anderson et al., 2005, Appendix A). The probe was deployed 

during the 2002, Experiment to Characterize Aircraft Volatile Aerosol and Trace Species 

Emissions (EXCAVATE, Anderson et al., 2005), where it was found to produce soot 

mass EIs that were comparable to those from samples collected 25-m behind the aircraft 

where flow velocities, temperatures and sample concentrations are much less a problem. 

Sampling line transmission efficiency tests conducted during EXCAVATE suggested that 
APPENDIX P

351

particle losses within the sampling system were consistent with predictions of empirical 

models. 

Miniaturized versions of the AEDC "dilution probes" mounted in a muli-tipped rake were 

used during the Aircraft Particle Emissions Experiment (APEX-1) and were found to 

collect exhaust particles with reasonable efficiency. However, sample line efficiency 

tests conducted at the conclusion of the experiment suggested that more than half of the 

exhaust particles collected from 1-m inlet probes were lost during transport to diagnostic 

instruments (Wey et al., 2006, Appendix I). Later tests conducted on a similar sampling 

system deployed during APEX-3 indicated that the losses were modest and wellcorrelated with empirical model predictions (Anderson et al., 2010). 

These conflicting findings motivated NASA to sponsor a series of experiments to 

investigate sampling system issues. The tests included: 1) an aircraft "start-cart"

experiment in April 2006 at LaRC to evaluate probe design and efficiency; 2) a 

comprehensive line-loss test to assess the transmission efficiency of sampling systems 

used in APEX-1, APEX-3 and the Joint-Strike Fighter (JSF) emissions test; and 3) a 

week-long field deployment at NASA GRC to assess probe collection efficiency, sample 

line transport efficiency and aerosol instrument performance using a Learjet as the 

particle source. Results of these experiments were summarized and presented at the 

2007, American Association for Aerosol Research annual meeting in Reno, Nevada and 

are available in presentation form from the author of this report. Important conclusions 

drawn from these experiments include the following. 

• Sample transport lines should be as short in length as possible and constructed of 

conductive tubing with relatively large ID to minimize pressure drop and diffusive 

losses.

• Sample line bends and connections should be minimized.

• Line losses are best determined by flowing monodisperse test particles down the lines 

and measuring particle concentrations on the up- and downstream ends of the line 

with a single, pressure-corrected condensation particle counter. The use of 

polydisperse particles with a single set of diagnostic instruments is only acceptable 

for quick integrity checks.

• Actively heating sample lines appears to lower transport efficiency by 10 to 20%—

the explanation for this is not obvious, but may relate to thermophoretic losses caused 

by temperature gradients in the lines.

• For most practical sampling systems, loss of < 20 nm diameter particles is severe, but 

loss of 20 – 300 nm particles is modest and can generally be predicted using 

empirical models.

• Losses inside the specially-designed "dilution-probes" are modest at low to mid 

power settings; losses are negligable at high power.

• Immediate dilution of exhaust sample at the inlet tip with ten-fold dilution with dry 

N2 is the best approach for preserving particle size distributions and avoiding 

condensation of volatile aerosol precursors within the sampling lines.

• It may be possible to use gas probes if inlet diameters are reduced to eliminate probe 

tip stagnation and dilution gas is introduced within 1 second after the sample 

collection to prevent particle coagulation. 
APPENDIX P

352

• Water cooling requirements are unclear, but only appear to be necessary for sampling 

low-bypass and military-type engines which exhibit extremely high exhaust gas 

temperatures.

• The optimum inlet probe design is still an open question. However, for purely 

research venues, use of AEDC dilution probes is recommended to maintain 

consistency with previous data sets.

These recommendations were taken into consideration in designing and implementing the 

PM sampling system used in the NASA-sponsored Alternative Aviation Fuel Experiment 

(AAFEX). This mission was conducted at the Dryden Aircraft Operations Facility in 

Palmdale, California during January 2009 and sought to assess the impact of synthetic 

fuels on the NASA DC-8 aircraft’s operations and emission performance and to examine 

the effect of ambient temperature, fuel composition and plume age on volatile aerosol 

formation in downwind exhaust. To address project objectives, a rather complex set of 

rakes, inlet probes and corresponding sampling lines were installed 1 and 30 m behind 

each inboard engine. The left and right 1-m rake bodies supported multiple "gas" and 

"particle" sample inlet probes mounted on 1.25-inch centers and were cooled using high 

pressure water flow. Sufficient dry N2 gas was delivered to the 1-m particle probes to 

maintain sample CO2 concentrations around 2000 ppm, which is a factor of 10 or more 

less than typical values measured in core flow at the exhaust plane. Sampling inlets were 

connected to a central sample distribution manifold using tubing of varying diameters, 

lengths, and surface composition. 

This report presents results from a number of tests or analyses that were conducted to 

characterize and assess the collection and transmission efficiency of the AAFEX exhaust 

sampling systems. We begin in section 3.0 by discussing results from a comprehensive 

"line-loss" experiment that was conducted on February 2, at the conclusion of the 

experiment when the sampling lines had already been used in over 35 hours of engine 

testing. We show size-dependent line penetration curves and compare them to empirical 

model predictions and examine how observed emission parameters changed in time as 

tubing walls became coated with soot and other condensed material. In section 4, we 

compare PM measurements made in an enclosure mounted behind the right 30-m inlet 

with an identical set of measurements made on samples collected from the standard 30-m 

probe and transported through over 30-m of tubing. We continue by examining the 

variation of emission parameters across the #3 engine exhaust plane (section 5) and by 

assessing the impact of flow velocity changes on measured PM emission profiles (section 

6). Section 7 includes a comparison of nonvolatile PM measurements made using the 1 

and 30-m inlet probes. We conclude by assessing efficacy of using gas probes, as 

opposed to dilution probes, to collect exhaust at the 1-m sampling position. 

3.0 ASSESSMENT OF SAMPLING LINE EFFECTS

Figure 1 shows an aerial photograph of the AAFEX experiment site with red lines 

representing the sampling lines that connected the right and left 1- and 30-m (R1, L1, 

R30 and L30) inlet probes to the common sample distribution manifold located in the 

MST trailer. Table 1 lists the tubing diameters, lengths, volumes and calculated 
APPENDIX P

353

residence times for each sampling line; corresponding Reynolds numbers are not given, 

but were calculated to exceed 4000 in all tube sections under typical sampling conditions. 

The list includes the dimensions of all elements within the flow path. For example, for 

L1, sample first passed through a 0.04 inch inside diameter (ID) inlet probe for a distance 

of 2 cm, then into a 1.53 m, 0.25 inch ID transport line to the base of the sampling stand. 

From there it was carried through a 1.94 m length of 0.31 inch ID tubing to a 0.56 inch 

ID, 0.03-m long fitting then through a 1.33-m long stretch of 0.31 inch ID tubing as it 

arrived and passed through the 6-port aerosol sample selection box. Output from the left 

1-m valve box then passed through 35.45 m of 0.62 inch ID stainless tubing before 

reaching the sample selection box in the MST trailer. Overall, the L1 sampling line was 

40 m long and had a 8.4 liter volume that, assuming piston flow, took 6.75 seconds to 

flush at a flow rate of 75 L min-1 (lpm). From Table 1, we see that the overall line 

lengths varied from 24 to 46 m with corresponding calculated sample residence times that 

varied from 3.8 and 7.2 s. Overall residence times measured between inlet tips and 

diagnostic instruments located in the equipment trailers were about a factor of two longer 

at typical flow rates, most likely due to the added tubing lengths required to transport 

sample from the MST trailer to the individual experiment stations. 
APPENDIX P

354

Figure 1. DC-8 with red lines superimposed showing the four sampling lines used to 

transport exhaust from the 1- and 30-m inlets to the sample distribution manifold located 

in the MST trailer.

The sample lines used during AAFEX were primarily constructed from electro-polished, 

seamless stainless steel tubing. However, several 20-foot lengths of 3⁄4-inch OD 

conductive PTFE tubing were used in the 30-m sampling lines and in the 1-m trunk lines 

between the left and right 1-m, 6-port valve boxes and the MST trailer; laboratory tests 

conducted prior to the field deployment indicated that clean, carbon-impregnated PTFE 

and stainless steel have equivalent particle transport characteristics. All tubes, 

regardless of composition, were cleaned and blown free of particle contamination before 

installation. Tests were conducted before and during the engine runs to verify that the 

sampling lines were leak-tight and yielded low particle counts when transporting filtered 

air. 
APPENDIX P

355

Table 1. Characteristics of aerosol sampling lines.

Left 1 M Line

Line Inner Line Tube Residence (s) Residence (s)

Diameter (in) Length (m) Volume (L) 75 lpm 125 lpm

0.04 0.02 0 0 0

0.25 1.53 0.05 0.04 0.02

0.31 1.94 0.09 0.07 0.04

0.56 0.03 0 0 0

0.31 1.33 0.06 0.05 0.03

0.62 35.45 6.9 6.58 3.95

Totals 40 meters 6.9 liters 6.75 4.05

Right 1 M Line

Line Line Tube Residence (s) Residence (s)

Diameter (in) Length (in) Volume (L) 75 lpm 125 lpm

0.04 0.02 0 0 0

0.25 1.55 0.05 0.04 0.02

0.31 1.84 0.09 0.07 0.04

0.56 0.03 0 0 0

0.31 0.54 0.03 0.02 0.01

0.62 19.92 4.8 3.7 2.22

Totals 24 meters 4.8 liters 3.8 seconds 2.3 seconds 

Left 30 M Line

Line Line Tube Residence (s) Residence (s)

Diameter (in) Length (in) Volume (L) 75 lpm 125 lpm

0.62 46 9.03 7.23 4.34

Totals 46 meters 9.0 liters 7.2 seconds 4.3 seconds 

Right 30 M Line

Line Line Tube Residence (s) Residence (s)

Diameter (in) Length (m) Volume (L) 75 lpm 125 lpm

0.62 38.2 7.44 5.95 3.57

Totals 38.2 meters 7.4 liters 6 seconds 3.6 seconds 

Sampling line transmission efficiencies were calculated using the UTRC empirical 

aerosol transport model, which includes terms for thermophoretic, diffusional, 

electrostatic, and inertial losses; results spanning the particle size range for aircraft 
APPENDIX P

356

emissions are shown in Figure 2. Turbulent diffusion is obviously the most important 

loss mechanism, particularly for aerosols smaller than 100 nm in diameter, and is the 

reason the line transport efficiencies drop to ~50% at around 10 nm. Thermophoretic 

and electrostatic losses are negligible in the unheated, electrically conductive sampling 

lines. Inertial losses are small, but more important in the 1-m lines which have 

significantly more bends and abrupt diameter changes. The overall model results 

suggest that transmission losses should be relatively small and comparable for each of the 

four sampling lines. 

Figure 2. Penetration efficiencies of AAFEX aerosol sampling lines calculated using the 

UTRC aerosol transport model (Liscinsky et al., 2010).

Experimental assessments of sample line transport efficiency were conducted on the day 

following the last engine run (February 2, 2009). Our approach was to generate a series 

of mono-disperse particles and use identical sets of diagnostic instruments to measure 

their concentrations on the up- and downstream ends of each sample lines; the ratio of the 

two measurements at each size diameter yielded the particle penetration function. 

Figure 3 shows the experimental apparatus used to perform this task. Its primary 

components were: a tube furnace to generate NaCl particles; a differential mobility 

analyzer (DMA) to select a narrow size range of the NaCl particles; an ejector to draw 

constant sample flow through the DMA then dilute and inject it into the sampling line; 

and identical sets of pressure transducers and particle counters to measure pressure and 

particle number density on the up- and downstream ends of the sample line. Particles 

were generated by passing filtered air over a small ceramic boat filled with NaCl crystals 

that was inserted into the mid-section of the tubular furnace. The furnace temperature 

was adjusted between 590 and 800 o

C to produce NaCl PSDs that best fit the size range 

of interest. The DMA was a custom-made, high flow (up to 40 lpm sheath flow) unit 

constructed by MST and operated with a sample-to-sheath flow ratio of 8. Total flow 
APPENDIX P

357

through the ejector (Fox Valve, Mini Eductor) was monitored with a mass flow meter and 

set using a two-stage pressure regulator on the high-pressure N2 gas supply. A small 

needle valve installed on the vacuum input of the ejector was used to adjust the 

monodisperse sample flow from the DMA. Ejector output was plumbed into the aerosol 

sample distribution manifold located in the MST, then sample inlet selection valves were 

alternately opened to force test aerosols through each of the sampling lines. Total test 

particle flow rate was set to around 70 lpm to match typical flow rates encountered 

during the engine tests. The CPCs (TSI model 3010) and pressure transducers were teed 

into the common sample distribution manifold (i.e., the input end of the sample lines) and 

into the downstream end of the line under test. In bench tests the pressure transducers 

agreed to within 0.5 mb and CNC units to within 3% across their full dynamic range of 

concentrations. 

Figure 3. Instrument setup used to assess sampling line transport efficiency.

A team of three researchers performed the line penetration measurements, with one 

operating the particle generation system and the other two stationed at either end of the 

selected sampling line to read and record particle concentration and sample pressure 

measurements. Digital output from the CNCs were also fed through 100-foot long 

RS232 cables and recorded on a central computer. The procedure involved selecting a 

particle size and then recording about 2-minutes of data once particle concentrations had 

stabilized. Duplicate sets of measurements for particle sizes of 10, 15, 20, 30, 50, 75, 

100, 150, and 200 nm were recorded on each sampling line. Particle counts were 

subsequently corrected for pressure and the downstream:upstream ratios were plotted 

versus particle diameter to reveal the penetration functions. 
APPENDIX P

358

Figure 4. Sample line transport efficiency as a function of particle diameter measured 

using the apparatus shown in Figure 3 for each of the 4 primary aerosol sampling lines.

Test results for the 1- and 30-m sampling lines are shown in the respective left- and righthand plots in Figure 4. Error bars are not shown but are on the order of +10% and +5% 

for particles in the 10-20 and 30-200 nm size ranges, respectively. Note that, except 

perhaps for L1, each of the lines exhibit much lower transport efficiencies at all sizes than 

calculated with the UTRC model (Figure 2). L30 exhibited particularly severe losses and 

the penetration of 100-200 nm particles through 3 of the 4 lines were extremely low, 

which cannot be explained by loses due to inertial deposition. Overall these results were 

unexpected and conflicted with our careful assessments of particle penetration through 

the APEX-3 sampling lines, which fit model predictions within experimental error. 

However, the APEX-3 lines were all stainless steel and had been cleaned just prior to the 

transport efficiency evaluations. As we note above, the AAFEX line-loss tests were 

conducted after the 35 hours of engine emission tests had been completed. 

Indeed, there is evidence that sampling line efficiency decreased over the course of the 

experiment as low volatility gases and aerosols accumulated on tubing surfaces. Figure 

5 shows normalized BC EI as measured on L30 plotted as a function of experiment day, 

with day 0 corresponding to the mapping test that was conducted on January 26. The BC 

values were obtained by dividing the 65 and 85% EIbc data by corresponding data 

obtained during the first set of experiments. The plot has a slope of -0.05, which suggests 

that the sampling line transport efficiency decreased 5% per day. The data also suggest 

that after 7 consecutive days of use, the line was removing about half the material being 

transported through it, which is consistent with the efficiency assessment shown in Figure 

4. Interestingly, the biggest drop in transmission occurred between day 5 and 7. Based 

on a general realization that the 30-m lines were becoming dirty, we flushed both out 

with tap water for approximately 15 minutes on the afternoon of Saturday, Jan 31 (day 5) 

and then used a vacuum pump to draw approximately 25 lpm ambient air through them 

until testing resumed on Monday, February 2. Apparently this "cleaning" led to further 

loss of transmission efficiency.
APPENDIX P

359

Figure 5. Apparent change in black carbon EI of the #2 engine over the course of the 

experiment. 

Re-examining Figure 4, we see that the efficiency trends for the lines are L1 > R1 ~ R30 

> L30. Interestingly, the total "official" sampling times for the lines were: L1=2.0 hrs; 

R1=9.2 hrs; L30=4.2 hrs; R30=6.2 hrs, which suggests that if the losses were caused by 

increasingly dirty tubing, the order should be L1 > L30 > R30 > R1. However, the left 

engine always burned JP-8 (35 hrs), whereas the right burned JP-8 (~24 hrs) and some 

combination of alternative fuel for the remainder of the time. Another complication is 

that, to prevent sample stagnation and reduce the time needed to establish stable 

constituent concentrations, the sample selection box located in the MST trailer was 

designed to draw a low flow of diluted exhaust air through each unused sampling line at 

all times during the tests. To accomplish the task, R30 and L30 were coupled to a 

vacuum pump through critical flow orifices such that ~25 lpm of inlet air was drawn 

through each line throughout the day, regardless of whether the engines were running or 

if the lines were selected for sampling. Thus, if background aerosols contributed 

significantly to the line degradation, we would expect that the ratio of the transport 

efficiencies for L30 and R30 should roughly equal the inverse ratio of their lengths. The 

actual L30:R30 efficiency ratio for the 75-250 nm diameter range is ~1.25 and the 

inverse length ratio is 1.2, a little bit smaller but in the right range. It is likely that the 

added hours of drawing JP-8 emissions through L30 can account for the difference. 

Regarding the efficiency differences in R1 and L1, during engine runs equal amounts of 

dilution air (enough to satisfy the 70 lpm combined demand of AAFEX participants) was 

delivered to the 1-m dilution probe tips at all times, again to prevent stagnation and 

reduce response time. Diluted sample air was then drawn through the transport lines 

back to the sample selection box, either by the combined vacuum produced by 

participants’ diagnostic instruments, or, for the unselected line, by a small vacuum pump 

located in the MST trailer. At engine powers >30% the required dilution gas flow rates 
APPENDIX P

360

were so high that the "selected" sampling line had to be vented to the atmosphere to 

prevent over-pressurizing sensitive diagnostic instruments. The unselected 1-m 

sampling line was not vented, so it is likely that dilution gas was being blown out the 

inlet tip (i.e., the lines were being more or less purged) in high thrust conditions. Other 

factors may have contributed L1’s higher relative transmission efficiency: the left engine 

was never sampled at 100% power and the right engine was "officially" sampled at 85% 

power and above for 141 minutes as opposed to 13 minutes for the left engine. R1 was 

probably a lot dirtier by the end of the mission than L1 and hence should have exhibited 

much lower transmission efficiencies, which indeed was the case.

The above discussion establishes that accumulation of particles and perhaps low volatility 

gases on the inside surfaces of the sampling lines produced corresponding reductions in 

particle transport efficiency. A number of questions now arise including: just how dirty 

were the lines and by what mechanism did this "dirt" influence transport efficiency? 

Consider L30: if we assume an average mass transmission efficiency of 75%, an average 

exhaust-plume soot mass loading of 50 mg m-3

, and an average sample flow rate of 40 

lpm over the 35 hour testing, we calculate that approximately 4.2 g black carbon 

accumulated in the tube over the course the experiment. The deposited mass of volatile 

aerosols and gases and dust may have been several times higher, but is difficult to 

quantify. This BC coating amounts to ~184 σg cm-2 if evenly distributed over the 

surface of the 46-m long, 1.6-cm diameter line. If we assume an aerosol mass density of 

1 g cm-3, the depth of the deposited material would be 0.184 mm, which would reduce the 

inside tubing diameter by ~0.02%. Let us examine how this might affect particle 

transmission efficiency. 

The UTRC transport model predictions presented in Figure 3 are valid for clean, 

conductive smooth-bore tubing at operated at 70 lpm flow rates at 293 K and 1 atm. 

Losses due to turbulent diffusion, turbulent inertial deposition, thermophoretic effects and 

electrostatic interactions are taken into consideration. Deposition of dirt on the tubing 

walls increases surface roughness and reduces tubing diameter and surface conductivity, 

which can potentially influence all but the thermophoretic effect loss process included in 

the model. 

First examining diffusion, Hinds (1982) gives the following equation for fractional 

particle loss (ηd) in turbulent pipe flow:

ηd = exp �

−4 ∙ Vd ∙ L

d ∙ v � � (1)

where v is flow velocity, L and d are the respective pipe length and diameter, and Vd is 

the deposition velocity given by:
APPENDIX P

361

Vd = 0.04 ∙ �v

Re � 1⁄4� ∙ �

ρ ∙ D

ν� �

2/3

(2)

where ρ and ν are respectively air density and viscosity, Re is the tube Reynolds number 

and D is particle diffusion coefficient. These equations predict a 6.5% loss of 100 nm 

particles during transport through a clean L30. Dirty walls could change these results by 

increasing v and Re and reducing d. We note however, these parameters cannot be 

changed independently: a 10% decrease in d produces 10 and 23% increases in Re and v, 

respectively. But even these rather drastic changes only produce an additional 0.5% 

reduction in 100-nm particle transport efficiency. Indeed it would take a 10-fold increase 

in Vd to decrease L30, 100-nm particle transport efficiency to the level seen in Figure 4; 

such a change would completely remove particles < 60 nm in diameter from the flow, but 

would only increase 200-nm particle deposition from 3 to 29%. Thus it appears that the 

enhanced losses cannot be explained by this mechanism.

Another possibility is that the surface contamination altered the electrical characteristics 

of the sampling lines and led to increased losses through electrostatic deposition. Gas 

turbine engine soot emissions can be highly charged and the test aerosols used in the 

above line-loss assessments were singly-charged NaCl particles. The UTRC model 

includes terms for particle image charge and space charge effects and the predicted losses 

for the AFFEX sampling lines are quite small. For example, under typical operating 

conditions only 1 in 1×108, singly-charged, 100-nm particles are lost to L30 tubing walls 

due image and space effects. The model equations don’t consider surface resistance, 

however. Noting that particle penetration through plastic tubing was often quite poor, 

Liu et al. (1985) developed an expression for sampling line transmission efficiency (P) 

that included electric field effects:

P = 1 − A ∙ Z ∙ E

Q� (3)

where A is tubing surface area, Z is particle electrical mobility, E is the induced electric 

field, and Q is sample flow rate. Figure 6 shows results for singly charged particles being 

drawn through a 46-m long, 1.6 cm diameter line at a 70 lpm flow rate (i.e., typical 

operating conditions for L30). Note that a relatively small electric field can effectively 

remove 50% of the100 nm particles in the flow, but at the same time, it completely 

remove particles smaller than 60 nm. Thus these results do not replicate the size 

dependent transmission efficiency of L30 depicted in Figure 4. It is also difficult, if not 

impossible, to induce a constant electric field in even a completely non-conductive tube. 

Liu et al. (1985) were able to charge Teflon tubing by bending it multiple times before 

use, but they also noted that the charge gradually bled off within a couple of hours. For 

AAFEX, it is possible that the PTFE tubing used in some of the lines acquired a charge 

from vibration during high power engine runs, but this would quickly dissipate through 

the conductive outer covering when the stimulus was removed. We thus conclude that 

electrostatic effects cannot satisfactorily explain the reduced transmission efficiencies of 

the dirty AAFEX aerosol sampling lines.
APPENDIX P

362

Figure 6. Modeled L30 transport efficiency as a function of particle size for induced 

electric fields of 1, 10, and 20 V/cm.

Inertial deposition or turbulent eddy impaction is another possible mechanism for 

removing 100-300 nm particles. Baron and Willeke (2005) give the following expression 

for particle loss in turbulent flow:

ηid = exp �

−4 ∙ Vt ∙ L

d ∙ v � � (4)

where the turbulent inertial deposition velocity, Vt, is dependent on the Reynold’s 

number and Stokes number (Stk):

Vt = Stk ∙ Re3/4 (5)

Stk = ρp ∙ dp

2 ∙ Cc ∙ v

1.8 × 109 ∙ ν ∙ d � (6)

where ρp and dp are particle mass density and diameter, and Cc is the particle 

Cunningham Slip Correction Factor, which is a constant for a given particle size and 

working gas. These equations predict that 1 out of every 1×107 100-nm particles would 

be lost during transport through a clean L30. From examining equation 4, we see that the 

only way to increase ηid to 0.5 ( i.e., 50% losses) is to increase Vt by 6 orders of 

magnitude. Working with clean tubing assumptions, this change can only be affected by 

increasing sample flow velocity to mach 1, particle diameter to 5000 nm, or particle 

density to a black-hole-like 1200 g cm-3. The alternative is to assume that dirty walls 

increase surface roughness, effectively increasing Vt by changing the thickness of the 

viscous sublayer adjacent to the tube wall. Im and Ahluwalia (1989) developed a 

dimensionless model for turbulent eddy impaction that took into consideration surface 

roughness induced by accumulation of particles on pipe surface. They indeed showed 

that Vt increases several orders of magnitude and becomes somewhat independent of 
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363

particle size when roughness element heights begin to represent a measureable fraction of 

the pipe diameter. Application of this model is well beyond the scope of the present 

study however.

Another way to characterize the impact of surface roughness is to treat the accumulated 

material on the tubing walls as a highly porous filter. It is possible that the soot was not 

evenly deposited on the tubing walls, but rather agglomerated to form more sparsely 

distributed, chain aggregates that would extend through the viscous sublayer near the 

wall, into the core sample flow. These dendritic structures would then capture 

additional particles through interception, turbulent eddy impaction, etc., and collectively 

become an increasingly efficient filter over time (i.e., Kanaoka, 1989). To evaluate the 

feasibility of this mechanism, let us examine the equation for fibrous filter collection 

efficiency (E) given by Baron and Willeke (2005):

E = 1 − exp �

−4 ∙ η ∙ α ∙ L

π ∙ df ∙ (1x10−4) ∙ (1 − α) � � (7)

where η is the single fiber collection efficiency, α is filter packing density, L is filter 

depth, and df is the fiber diameter. If we solve equation 7 for η = 0.01, df = 1 μm, L = 

4600 cm, and α = 1×10-6 we obtain an overall filter collection efficiency of about 50%, 

which is roughly equivalent to the particle losses through L30. Except for the tubing 

length, the input values are crude estimates, but the result does show that even slight 

accumulation of fiber-like materials on tubing walls can significantly reduce transmission 

efficiency. 

Figure 7. Single fiber efficiency for collecting 100-nm spherical particles. 

Equation 7 reveals that overall filter efficiency is highly dependent on individual fiber 

diameter and collection efficiency. It turns out these two parameters are coupled and also 

dependent on particle size. Figure 7 shows a plot of collection efficiency versus fiber 
APPENDIX P

364

diameter as calculated for 100-nm particles, 600 cm s-1 flow velocity and constant 

packing density using empirical equations developed in Baron and Willeke (2005), which 

include terms for particle loss through diffusion, interception, impaction and gravitational 

settling. Note that 100-nm diameter fibers such as might be envisioned to form from 

soot agglomeration are highly efficient at removing 100 nm particles. Figure 8 shows 

results of additional calculations that were performed to further explore the particle-sizedependent collection efficiencies of individual fibers. Here we varied packing densities 

and filter thicknesses to obtain efficiencies less than 1 for all cases. It is interesting to 

note that the smaller the fiber, the more effectively it removes particles in the 100 – 200 

nm size range. A close inspection of the filter efficiency equations indicates that this is 

caused by increased efficiency for particle removal by interception and impaction. The 

smaller fibers are also less efficient at removing ultrafine aerosols, which is also 

consistent with the observations presented in Figure 4. It thus appears that filtration by 

small dendritic structures growing in time on the tubing walls has the potential of 

explaining the loss of 75 – 250 nm particles in dirty sampling lines. However, more 

laboratory and theoretical work is needed to better understand the deposition of soot to 

sampling lines and to develop strategies to minimize its effects on particle transport.

 

Figure 8. Relative collection efficiency as a function of particle size for 0.5, 1, 2, 5, and 

10 μm diameter fibers.

5.0 AN INVESTIGATION OF PARTICLE FORMATION IN SAMPLING LINES

Early investigations conducted to measure aircraft particle emissions at altitude often 

found that volatile particle number concentrations were greather than soot number 

concentrations by at least a factor 20 in aged engine exhaust plumes (i.e., Anderson et al., 

19978). Modeling studies suggested these nucleation-mode particles are composed of 

sulfuric acid and perhaps organic species and that they form very rapidly as the exhaust 

cooled and mixed with background air at cold temperatures. Volatile particles were first 
APPENDIX P

365

observed in ground-based engine emission studies during the 1999 Aerosol Workshop 

conducted at NASA LaRC (Cofer et al., 2000); there, samples collected 25 m behind the 

exhaust of an idling J85-GE engine were found to contain a large numbers of <20-nm 

aerosols that were not present in samples drawn from a 1-m inlet. Measurements 

conducted during the EXCAVATE experiment confirmed the rapid formation of volatile 

aerosols in aging aircraft exhaust plumes and tied both the mass and number of such 

particles to fuel sulfur content (Anderson et al., 2005). APEX-1 measurements provided 

more details on exhaust plume sulfate nucleation and revealed that low-volatility organic 

species and background aerosols were also involved in the condensation process (Wey et 

al., 2007). Efforts to model volatile aerosol microphysics in ground-based exhaust 

plumes have exposed a conundrum, however: do the volatile particles form and grow 

primarily within the engine exhaust plume during its rapid transport (<< 1 sec) from the 

engine exit to the 30 m sampling probe or during the subsequent 10 to 20 seconds it takes 

to transport the samples through sampling lines to remotely located diagnostic 

instruments. 

To address this question, AAFEX participants designed a relatively simple experiment 

that involved placing sensitive aerosol instruments in a sturdy enclosure positioned 

directly in the plume and subsequently comparing the resulting measurements with data 

recorded by a similar set of instruments sampling off a long sampling line connected to 

the R30 inlet. Nicknamed the "death box" because of its precarious position within the 

engine exhaust plume, the enclosure (Figure 10) was designed and constructed by AEDC 

and consisted of a 2 inch aluminum angle framework with 1⁄4 inch aluminum sides and 

top. Death box instruments included a CPC, EEPS and CO2 analyzer that drew samples 

through a 1-m long 3/8 inch diameter stainless tube that faced forward and was affixed to 

the side of R30. Power cables and RS232 signal wires were run out to the box from the 

NASA truck; data from the instruments were monitored and recorded by an operator 

sitting in this location. Measurements recorded in the death box were compared with 

output from a similar set of instruments located in the NASA truck that drew samples 

from R30 through ~38 m of 0.62-inch ID stainless tubing and 5 m of 0.41-inch ID 

conductive PTFE. We estimate sample residence times were <0.5 sec and 15-20 sec for 

the death box (DB) and NASA trailer (NT) sampling lines, respectively. The two EEPS 

generally agreed to within 10% in number density when sampling from the same aerosol 

source. The CO2 analyzers were calibrated on a daily basis using the same reference and 

span gases.

Although simultaneous DB and NT measurements were recorded during many of the 13 

engine runs conducted during AAFEX, the results from the morning of Jan 28 shown in 

Figure 11 serves to illustrate the general findings. During the test which extended from 

5:53 to 9:25 local time, ambient temperature increased from -4 to 4o

C, winds were steady 

from the west (i.e., aligned with the longitudinal axis of the aircraft) at 1 to 4 m/s and 

relative humidity decreased from 70 to 62%. These conditions are known to promote 

rapid formation of volatile aerosols and as can be seen in Figure 11, this was indeed the 

case. The two plots show total number and mass EIs versus engine power as measured 

from the DB and NT; nonvolatile PM number and mass EIs as measured from R1 

samples using NT instrument suite are also included. The 1-m data were corrected for 
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366

line losses using correction factors derived from Figure 4, R1 data. The NT R30 data set 

were also corrected, but two cases were examined, one each assuming that 50% (solid 

blue squares) and 100% (open blue squares) of the transmission line inefficiencies shown 

in Figure 4 had been incurred by the Jan 28 test date. Assuming that aerosols were 

neither lost nor formed in the short DB sampling line, several characteristics are apparent 

from the Figure 11 plots:

• Death box EIn and EIm are larger than the 1 m probe, showing that a large amount of 

volatile aerosol particles formed in the plume at all engine powers.This indicates that 

sulfuric acid condensation must proceed on millisecond time scales once the plume 

temperature decreases below the species boiling point. 

• At all power settings, DB number EIs are about the same as corrected NT EIs, 

indicating that most of the core nuclei are formed before reaching the 30-m aerosol 

inlet and no new particle formation occurs after this point.

• Mass EIs are larger for the corrected NT than the death box suggesting increasing 

particle mass in the sample line. This suggests that condensation of material onto 

existing particles is favored over nucleation. An increasing fraction of volatile aerosol 

mass is formed in the sampling line as power was increased.

Figure 10. Photographs showing the relative lengths of sampling line used for the aerosol 

instruments located in the deathbox and NASA truck.
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367

Detailed particle size distributions provide additional insight into the microphysical 

processes occurring within the plume and sampling line. Figure 11 presents DB and NT 

particle size distributions (PSDs) plotted in mass EI space to accentuate the modal 

structure of the emissions. Three versions of the NT data are shown: one with no line 

loss corrections (solid blue line), a second with 50% of the Figure 4 corrections applied 

(dashed blue line) and the third with 100% corrections applied (dotted blue line). NT 1-

m PSDs are also shown and were corrected for 100% of the Figure 4 R1 losses. In the 

PSDs, the small-diameter mode represents freshly nucleated volatile aerosols and the 

larger mode is composed of soot with volatile aerosol coatings. From examining these 

plots we can make the following observations:

• At idle, nucleation mode particles completely dominate total aerosol number and mass. 

• The nucleation mode decreases in total mass and shifts to smaller diameters as power 

is increased. This may be due to the reduced availability of volatile material, shorter 

transport times from the engine to the inlet probe, preferential deposition of the 

volatiles on soot rather than in the nucleation mode, or some combination of these 

factors. 

• Particle mass in the 6-10 nm size range appears to be lost in the sampling lines, either 

due to turbulent diffusional deposition or coagulation. 

• The nucleation mode peak generally shifts to larger sizes and becomes broader during 

transport through the sampling line. For example, at 65% power the peak shifts from 

12 to 15 nm and the total mass at 20-nm increases by a factor of 2 to 4. 

• The soot-mode peak in the 30-m total aerosol PSDs always appears at larger diameters 

than in the 1-m samples. For example, at 30 and 45% power, the 1-m soot mode peaks 

at 35 nm whereas the 30-m soot mode peaks at ~60 nm in both the DB and NT spectra. 

Although this may be caused by differential losses between the 1 and 30 m sampling 

lines, it could be a result of the soot particles becoming coated with volatile material.

• The amount of volatile material condensing in the soot mode appears to increase with 

power, probably as condensation onto existing particle surface becomes energetically 

more favorable than forming new aerosols. 

• At idle power settings, a volatile mode is present at ~100 nm that does not correspond 

to the soot mode, but may rather be caused by condensation onto background particles.

• Additional volatile aerosol condenses in both the nucleation and soot modes within the 

sampling lines.
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368

Figure 11. Comparison of death box and NASA Truck particle number and mass EI 

measurements for the #3 engine as it burned JP-8 fuel under cold ambient conditions. 

Values from 1-m probe were corrected for line losses using a polynomial fit to data 

shown if Figure 4. Results from the NT 30-m inlet were corrected for 50% (solid blue 

squares) and 100% (open blue squares). 

Small aerosols are lost to tubing surfaces or undergo coagulation as described in the 

sample line loss section of this report and those losses somewhat explain why the number 

concentration at the outlet is less that the measured particle number at the inlet. But 

significantly there is a large number of small particles present at the inlet. In fact the 

number of particles at the probe inlet is typically 10 to 20 times higher than the number 

of particles measured at close to the engine exit (1m) due to nucleation of volatile 

aerosols in the exhaust plume. In addition the volatile aerosol mass has been reported to 

be greater than BC mass at the 30m location in some cases. The bottomline is that 

volatile material is significant at 30m. 
APPENDIX P

369

Figure 12. Comparison of mass-EI-based size distributions measured behind the #2 

engine on the morning of January 28th as the engine burned JP-8 fuel with 1200 ppm S 

content. The black lines respresent1-m NT EEPS measurements corrected for particle 

losses using data shown in Figure 4. Deathbox values (red lines) are presented without

any correction. The NT 30-m data are shown without correction (blue line) and with 50 

(dashed blue line) and 100% (dotted blue line) of the Figure 4 corrections applied. 

The data in Figures 11 and 12 provide evidence that particle number EIs were mostly 

dictated by processes occurring within the exhaust plume while mass EIs were influenced 

by condensation occurring within the sample lines. Figure 13 examines these issues in 

more detail. The plots were generated by correcting the DB and NT EIs for nonvolatile 

contributions (with 100% R1 line loss corrections) to obtain volatile EIs and then 

allowing DB values to represent the EIs at the 30-m inlet tip. The points are essentially 

given by 100* (DB/(NT*line-loss correction)). With no corrections applied, we see that 

~180 to 200% and 80 to 120% of the aerosol number and mass emissions, respectively 

were present at the 30-m inlet tip. Conversely, if we apply 100% of the Figure 4 lineloss corrections we estimate that 90-100 and 20-60% of the respective volatile aerosol 

number and mass formed in the plume. If we assume the 50% R30 line loss correction 
APPENDIX P

370

is more representative of particle mass transmission half-way through the mission, we 

conclude that, depending on power (which is inversely related to plume residence time), 

from 10 to 60% of the volatile mass formed in the sampling line. Thus sampling line 

effects clearly have to be taken into consideration if a standard is ever established for 

aircraft volatile aerosol emissions. 

Figure 13. Percentage of volatile particle number and mass formed in exhaust plume as a 

function of power calculated by correcting for nonvolatile particle number and mass 

emissions and applying 0 (black line), 50 (blue) and 100% of the R30 line loss 

corrections derived from Figure 4 data.

5. DISTRIBUTION OF EMISSIONS ACROSS THE ENGINE EXHAUST PLANE

Current procedures for certifying gas turbine engine emissions require that emission 

factors be area-weighted averages of measurements made at multiple points across the 

engine exhaust plane. These measurements are often obtained using multi-tipped 

sampling rakes mounted on translation stages, which allow complete mapping of exhaust 

composition at 2-inch vertical and infinite horizontal resolution. Another approach is to 

use cruciform rakes with arms that span the entire exhaust plane and have inlet tips 

spaced to draw area-weighted flow into a converging manifold that delivers a single 

continuous gas stream to diagnostic instruments. In either case, it is very difficult to

adapt the existing sampling probes and inlets to introduce clean, filtered gas near the inlet 

tips to reduce particle concentrations to prevent coagulation and gas-to-particle 

conversion in sampling lines. A possible alternative is to obtain certification species 

measurements at multiple points to evaluate the spatial distribution of the emissions, then 

to make detailed particle measurements at only a single point selected from the gas-phase 

measurements to represent the entire exhaust plane. 

AAFEX evaluated the single-point measurement approach by conducting tests to observe 

the variability of particle emission parameters as a function of distance from engine 

centerline. The experiment was performed on the afternoon of January 31 as the engines 

burned JP-8 fuel in relatively warm and stable conditions. It involved recording 2-3 

minutes of data from particle probe #3 with the rake R1 at 8, 4, 2 and 0 inches to the left 

of the #3 engine centerline. Sample dilution was maintained at a constant rate (when 

possible) so measured CO2 mixing ratios could be used to assess gas-phase homogeneity 
APPENDIX P

371

across the exit plane. Emission indices were calculated using the coincident CO2

measurements. Measurements were made at 4, 7, 30, 45, 65, and 85% of maximum 

rated engine thrust to examine spatial variations in exhaust composition as a function of 

power. 

Figure 14. Emission indices for total number density (left column), nonvolatile number 

density (middle) and black carbon mass (right) at various power settings as a function of 
APPENDIX P

372

horizontal distance from the #3 engine centerline. Data are averages of time series such 

as those shown in Figure 15. Error bars represent ±1 standard deviation.

Results are summarized in Figure 14, which shows plots of PM EIs versus horizontal 

rake offset for the indicated power settings. Measurements of black carbon EI (EIbc), 

total aerosol number EI (EIn) and nonvolatile aerosol EI (EInv) are included. Table 2 

provides the relative percentage deviations of these plots; results for simultaneous CO2

measurement are also included to allow for an assessment of gas-phase species variations 

across the exhaust plane. PM emissions were much more variable across the exit plane 

at all power settings than CO2. For example, discounting the 30% power point where 

sample dilution was changed during the engine transect, CO2 deviated 2.1 to 7.9% across 

the power range whereas EIbc, EIn and EInv varied by 13 to 63%, 10 to 122% and 12 to 

41%, respectively. For EIbc and EInv changes that occurred between the two outermost 

sampling locations were in general responsible for these large deviations. For example, 

at 65% power, both these parameters increased by a factor of two when the rake was 

moved outward from 4 to 8"; a similar trend was observed for 4 and 7% thrust. At 30, 

45 and 85% power, the nonvolatile parameters decreased slightly when the rake was 

repositioned from 4 to 8". The source of these variations is not clear. 

Table 2. Percentage deviation of emission parameters as a function of engine power and 

horizontal distance from the engine centerline. 

Engine Carbon Dioxide Black Carbon Total Number

Nonvolatile 

Number

Power 0 - 8" 0 - 4" 0 - 8" 0 - 4" 0 - 8" 0 - 4" 0 - 8" 0 - 4"

4 5.4 1.4 45 11 18 19 22 1

7 5.1 0.7 63 15 39 42 29 8

30 * 0.9 23 13 43 18 16 5

45 4.1 0.9 58 25 122 93 41 13

65 7.9 0.5 41 12 22 8 19 5

85 2.1 1.3 13 4 10 5 12 6

*Dilution flow changed during horizontal scan. 

Note that EIn exhibited the most overall variability, particularly near the engine center 

line. The cause for this is revealed in Figure 15, which shows a time series of total (cold 

CN) and nonvolatile (hot CN) aerosol number densities recorded at 30% engine power as 

the rake was moved inward, pausing at each of the 4 sampling locations. Beginning at 

4", high frequency spikes were imposed on the cold CN baseline; these increased in 

frequency at the 2" and 0" sampling locations to the point that the signal never returned to 

the baseline value. In contrast, the hot CN measurements were steady throughout the 

time period, indicating that the cold CN fluctuations were driven by nucleation of volatile 

material either in the exhaust plume or within the long sample transport lines. The source 

of this material was most likely an engine oil leak known to the aircraft maintenance 

crew. However, it is also possible the oil mist emanated from the engine’s central vent 

tube, which is used to vent the turbomachinery to the atmosphere. In any case, these 

emissions caused EIn to be a poor proxy for black carbon number emissions, particularly 

near the engine centerline and at medium power settings.
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373

The PM emissions were more uniformly distributed across the exhaust plane at higher 

engine powers. For example, all emission parameters varied less than 15% across the 

entire transect at 85% power. Conversely variability maximized at 45% thrust, where 

EInv exhibited the least horizontal deviation at 41%. For EIn, this spatial variability was 

caused by the aforementioned oil leak; the source of the variation in EIbc and EInv is not 

known, but may be due to fuel-to-air ratio variations within the combustor. 

Reviewing the Figure 14 and Table 2 data, we can draw these conclusions regarding the 

representativeness of single point PM emission sampling:

• Nonvolatile emissions are relatively well mixed within a 4" radius of engine 

centerline. For example, deviations in EIbc and EInv measurements made within 

this exhaust region respectively ranged from 4 to 25 and 1 to 13% over the entire 

power range, which should be acceptable for most purposes. 

• Collected samples should be thermally treated to remove volatile material before 

particle number and size distribution measurements are recorded. Condensation 

of oil and other precursors within the sampling stream can cause aerosol 

parameters to be quite variable and significantly elevated above measurements 

provided by instruments operating with thermal denuders. 

We caution, however that these observations are valid for the NASA DC-8’s #3, CFM-56 

engine as it was operating on the afternoon of January 31, 2009. Additional 

measurements recorded across the exhaust planes of a variety of commercial aircraft 

engines are required to further establish the viability of this measurement approach. 

Figure 15. Time series of hot and cold particle number densities measured from particle 

probe 3 on R1 at 30% engine power as the rake was translated in 2" increments from 8 

inches to the left of center to engine center. The apparent decrease in CN number density 

at 49030 seconds was caused by an increase in sample dilution. The factor of 2 

difference in cold and hot CN values at -8" are mostly caused by particle losses in the 

thermal denuder and differences in the lower size sensitivities (5 versus 8 nm) of the two 

particle counters for used for the measurements. 
APPENDIX P

374

7.0 EFFECTS OF SUB-ISOKINETIC SAMPLING

Previous studies have shown the importance of matching aerosol inlet velocity with free 

stream velocity (known as isokinetic sampling) to avoid inertial enrichment or depletion 

of large aerosol particles in the collected sample flow. This is particularly true when 

sampling from aircraft where inlet and free-stream velocities can be mismatched by more 

than 100 m s-1

. Some researchers capitalize on this effect by operating aerosol inlets at 

very high ratios of free-stream velocity (U0) to tip velocity (U) to enrich large particles in 

the collected sample stream; enhancement ratios of 10 are easily obtained for particles 

larger than 5 μm in aircraft sampling applications. These virtual impactors (VI) can also 

be operated with filtered gas blowing gently out the inlet tip to prevent penetration of 

background air and small particles, while allowing particles with significant inertia to be 

collected. Known as counter-flow virtual impactors (CVI), these inlets are primarily 

used for sampling cloud droplets and ice particles from airborne platforms, but are also 

available for coarse-mode particle sampling in ground-based applications. 

Essentially all the studies examining isokinetic inlet effects have focused on supermicron sized particles while few if any have examined inlet velocity effects on submicron 

aerosol collection. However, theoretical studies suggest that these are subject to 

anisokinetic sampling errors under some conditions. For example, Hangal and Willeke 

(1990) derived the following expression for inlet aspiration efficiency (ηasp) based on 

laboratory studies:

ηasp = 1 + ��U0

U

� � ∙ cosφ − 1� ∙ �3 ∙ Stk�U

U0 � �

−1⁄2

� (8)

Where φ is the angle between the inlet longitudinal axis and the free stream flow 

direction, and Stk is Stokes number as defined in equation 5. The expression was 

validated for Stk values between 0.01 and 100 and for U0/U ratios between 0.01 and 10. 

Figure 16 shows ηasp values calculated from equation 8 for spherical particles with mass 

densities of 1.5 g cm-3 assuming parameters representative of AAFEX sampling at high 

engine thrust (a 1 mm inlet diameter, free-stream velocity of 400 m s-1 and temperature 

of 350o

C).
APPENDIX P 

375

Figure 16. Results of calculations showing the potential enrichment or depletion of 

particles in samples collected using inlet velocities that are significantly mismatched with 

the exhaust stream velocity. 

From reviewing Figure 16, we infer that particles in the size range of those emitted by 

aircraft engine can be substantially enriched if inlet and exhaust stream velocities aren’t 

controlled to within a factor of two under high power sampling conditions. The effect, 

however, should be most noticeable in particle mass, since the enrichment increases 

exponentially with particle size. 

Figure 17. Particle number (left) and mass (right) EIs measured on R1 as inlet tip 

velocity was varied by changing dilution gas flow. 

A short experiment was conducted during AAFEX to investigate anisokinetic sampling 

effects. It involved varying sample dilution ratio while sampling from a single probe at 

constant engine power, the logic being that because of flow restrictions in the probe 

outlet, increased diluent flow would raise pressure inside the inlet thereby decreasing the 

0 50 100 150 200 250 300

1.0

1.2

1.4

1.6

1.8

2.0

2.2

2.4

 Uo/U

 1.2

 1.5

 2.2

 3.5

 5.8

Inlet Aspiration Efficiency

Diameter (nm)
APPENDIX P

376

inlet tip velocity. Indeed, increased dilution gas flow is often used to purge the sampling 

lines during engine starts or to obtain "zero" gas samples for verifying instrument 

calibrations. The test was conducted over a 30-minute period on the morning of 

February 2, when background conditions were stable and the #3 engine was burning JP-8 

fuel at 85% of maximum thrust. As shown in Table 3, five different dilution settings 

were examined with nominal CO2 mixing ratios of 535, 1080, 1913, 2900, and 3700 ppm; 

from an undiluted exhaust CO2 mixing ratio of 34000 ppm, dilution ratios of 

approximately 64, 31, 18, 12 and 9 were calculated. Sample flow rates were calculated 

from the dilution ratios and measured dilution flow rates. An inlet isokinetic flow rate 

(Qiso) of 5.7 standard lpm was estimated assuming: 1) an impact pressure of 20 PSI 

(Robert Howard, personal communication), 2) an exhaust temperature of 350oC, 3) a tip 

diameter of 0.106 cm, and 4) a discharge coefficient of 0.61. Free-stream-to-inlet-tip 

velocity ratios, U0/U, were then calculated from the ratio of Qiso/Qsample. Values varied 

from 1.4 to 5.2, and when compared to Figure 16 results, suggest that anisokinetic 

sampling effects could have affected the corresponding particle measurements.

Table 3. Measured and estimated flow and particle emission parameters from the dilution 

tests.

CO2 Dilution Est. Flow Rates (lpm) Total Number EI Total Aerosol Nonvol. Aerosol Black Carbon EI

ppm Ratio Diluent Sample

U0/

U avg. stdev EIm VMD Eim VMD average stdev

535 64 70 1.1 5.2 1.55E+15 3.99E+13 107.1 79.6 104.6 111.2 96.5 7.7

1080 31 57 1.8 3.2 1.29E+15 1.84E+13 90.5 78.8 73.1 96.4 82.3 4.7

1913 18 45 2.7 2.1 1.21E+15 1.23E+13 80.2 78.2 59.1 89.5 72.0 3.5

2899 12 39 3.6 1.6 1.19E+15 1.36E+13 71.5 76.0 45.7 83.7 61.4 2.4

3686 9 33 4.0 1.4 1.66E+15 5.10E+13 94.4 75.6 59.5 83.9 82.5 2.6

Indeed data shown in Figure 17 and Table 3 do provide some evidence that the 

mismatched inlet /exhaust steam flow velocities impacted the measured particle emission 

parameters in a way that was mostly consistent with the Figure 16 predictions. Note that, 

except for the anomalous points at 3700 ppm CO2, both the mass and number EIs 

increase steadily with velocity ratio, which suggests that reduced inlet velocity potentially 

enriches the sample flow with larger diameter particles. The lowest dilution point 

doesn’t follow the number and mass trends: it was recorded between the 2900 and 534 

CO2 mixing ratio points, so it is unlikely that a change in engine power was the cause. 

Other possibilities include changes in sampling line transmission characteristics at lower 

total flow rates, nonlinear changes in flow dynamics within the inlet tip, and so forth. 
APPENDIX P

377

Figure 18. Change in total mass EI-based size distributions (left) and volume mean 

diameters (right) with change in dilution flow. Data are from the cold SMPS.

The data presented in Figure 18 provides further evidence that sub-isokinetic sampling 

influenced measured emission parameters. The left-hand plot shows PSDs measured by 

the unheated SMPS for each dilution setting and the right-hand plot shows the 

corresponding volume mean diameter of the size distributions as a function of CO2. Note 

that the PSDs increase in integrated area and shift to slightly larger diameters as sample 

dilution and U0/U are increased; corresponding VMDs increase from ~75 to 80 nm in 

going from minimum to maximum sample dilution. Interestingly, both the PSD and 

VMD point for the 3700 ppm CO2 dilution fit the expected trends. 

To further explore the possible effects of anisokinetic sampling, we multiplied the 3700 

ppm PSD of Figure 18 by the aspiration efficiencies shown in Figure 16 (we selected this 

particular PSD to represent the base case because it exhibited the smallest VMD and 

standard deviation). Figure 19 shows the resultant number and mass EIs, where the data 

have been normalized to the respective values for the 2900 ppm dilution case (Table 3). 

Figure 20 presents PSDs and VMDs without additional normalization. Parameters in 

both figures are plotted on roughly the same scales as in Figures 17 and 18 to better 

facilitate comparisons. 

Figures 19 and 20 with 17 and 18, show similar trends in the modeled and observed 

parameters, but, except for VMD, the changes in the calculated parameters are more 

damped. Although the calculated PSDs replicate the observed dilution related 

enhancements in the 200-300 nm size range, the do not exhibit the same progressive 

increases in the peak diameter region. 
APPENDIX P

378

Figure 19. Particle number (left) and mass (right) EIs calculated from product of inlet 

aspiration efficiency vectors and 3700 ppm PSD. Values are normalized to 2900 ppm 

total number and mass values presented in Table 3. 

To better quantify the differences between the observed and calculated values, we can 

calculate the following ratio for each parameter:

dX = (X535 – X2900)observed / (X535 – X2900)calculated (8)

where X is any particular emission parameter and the numerical subscripts denote the 

respective dilution settings. This expression yields values of 3.8, 2.2, and 0.9 for 

number, total mass, and VMD, respectively. The large ratio for EIn is not surprising, 

because sub-isokinetic sampling primarily enriches the larger particle population which 

contributes little to the integrated number density; even doubling U0/U would not 

significantly reduce the dEIn ratio. We suspect the disproportionate increase in observed 

EIn with dilution is caused by decreased line losses at the correspondingly higher sample 

flow rates. For example, using equation 3 we calculate that a 50% flow increase results 

in a 10% reduction in 8 nm particle diffusion losses within R1. Although inertial losses 

increase with flow, losses due to the "filtration" mechanism discussed in section 3 also 

decrease inversely with flow rate. For example, the collection efficiency of a single, 0.1 

μm fiber drops by 25% when flow velocity is increased by 50%. Sample line filtration 

effects may also explain the enhanced dEIm ratio and might explain all the dilution 

related changes seen in the tests. Independent line loss assessments at a variety of 

sample flow velocities are needed to resolve this issue.
APPENDIX P

379

Figure 20. Mass EI based size distributions (left) and volume mean diameters (right) 

calculated from the product of the aspiration efficiency vectors in Figure 16 and the 3700 

ppm PSD. 

In summary, the AAFEX sampling tests produced data that suggest sub-isokinetic 

sampling can influence observed emission parameters at high thrust conductions. The 

experiment results are not conclusive however, as the changes in inlet velocity were 

convoluted with changes in total sample flow, making it difficult to resolve inertial 

enrichment effects from flow velocity related variations in sample line transport 

efficiency. To better resolve the two effects, a more careful experiment is needed in 

which the inlet tip velocity is changed while downstream sample line flow velocity is 

held constant. Since this is difficult to achieve, another approach is to use clean sample 

lines throughout the experiment and determine their size-dependent transmission 

efficiency over the range of experiment flow rates to establish accurate sample line 

correction factors. In either case, it is important to record inlet probe pressure, diluents 

flow rate, total sample flow rate, and exhaust stream temperature, velocity and CO2

concentration. It would also be interesting to repeat the experiment with a variety of 

probes with different tip diameters, as equation 9 predicts that inlet aspiration efficiency 

at any particular velocity ratio is a strong function of inlet diameter. For example, using 

equation 8 we calculate that the inertial enrichment of 300 nm particles at U0/U = 5.2 

drops by ~23% if the inlet tip diameter is increased from 0.1 to 0.2 cm. Moreover, the 

isokinetic sampling issue is a tractable problem, but is not easily addressed in laboratory 

investigations as it requires replication of the free-stream temperatures and velocities that 

are only available at the exit plane of gas turbine engines operating at near takeoff thrust.

8.0 PARTICLE LOSSES TO SAMPLING PROBES 

The above discussion highlighted some of the difficulties inherent in collecting particle 

samples from the exit plane of an engine operating at high thrust. For some engines, 

exhaust velocities reach or exceed mach 1 and this high velocity coupled with high 

temperatures can cause dynamically heated inlet probes to glow cherry red. Indeed, 

high-pressure water cooling is needed simply to ensure the survival of inlet probes/rake 

stands used to sample low-bypass military engines. Exhaust air undergoes dramatic 

changes in velocity, pressure, and temperature as it is drawn into narrow diameter, water-
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cooled inlet probes, which can lead to equally dramatic changes in particle concentrations 

and microphysical properties. For example, tests conducted in the exhaust of a J85-GE 

engine operating at full military power during the AWEX-99 experiment showed that an 

inlet probe with non-optimum dilution and cooling flow introduction could reduce PM 

number EIs by more than an order of magnitude (Cofer et al. 2000) and double the 

diameter at which the PSD peak appeared. However, there is no guarantee that properly 

designed probes operating with minimal cooling and optimal dilution co-flow will 

preserve PM number densities and size distributions. Indeed, the visually-evident 

blackening of the R1 rake and inlet probes over the course of AAFEX (Figure 21) raised 

concerns that internal probe surfaces were acting as a similar particle sink. 

Figure 21. Photographs of the #3 engine sampling rake before (left) and after (right) the 

35 hours of engine runs conducted during AAFEX.

To assess potential inlet losses, we compared back-to-back 30- and 1-m emission 

parameter measurements, assuming that by virtue of the much lower plume velocities and 

temperatures, the 30-m data were less subject to inlet probe effects. Ratios of individual 

mass and nonvolatile particle number EI data pairs, plotted as functions of engine thrust 

for are presented in Figure 22, where the top and bottom panels show results for the right 

(#3) and left (#2) engines, respectively. The data are not corrected for sample line 

transmission efficiency, so horizontal lines representing average transmission line 

transport efficiency ratios are included to provide a reference for evaluating probe 

transmission effects. For example, ratios of twice the reference value indicate that 50% 

of the particle number or mass is removed in the 1-m inlet probe. Inclusion of very lowvalued data from the synthetic fuel run accounts for the wide variability in the #2 engine 

plots. Nonvolatile number EI ratios at low engine powers (≤45%) are also falsely 
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elevated due to reformation of volatile aerosol downstream of the thermal denuder in the 

30-m samples; there is no evidence that this occurred at higher engine powers. 

Similarly, the #2 engine black carbon EI ratios are somewhat enhanced at low engine 

powers because of background contributions to the 30-m synthetic fuel measurements; 

ambient particles had a negligible impact on the JP-8 and high thrust data points. 

Figure 22. Ratios of emission parameters measured at 30- and 1-m behind the right (top) 

and left (bottom) engines, where the red and blue points represent the individual and 

median values, respectively. The top panels (#2 engine) include all data pairs regardless 

of fuel type; the bottom panels for the #2 engine are for JP-8 fuel only. The dashed 

horizontal lines represent the average 30-m/1-m sample line transmission efficiency 

ratios calculated from Figure 3 data. 

Figure 22 shows that over 95% of individual EI ratios reside above the reference lines, 

which indicates that the 1-m inlet probes were much less efficient at 

collecting/transmitting both particle mass and number than their respective 30-m 

counterparts. Many of the points are two to three times their respective reference 

values, suggesting that the 1-m inlet probes were only 33 to 50% efficient under some 

conditions. Discounting the #2 engine 45% data points which were possibly 
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contaminated with engine oil, the losses were apparently more severe at high and low 

engine thrust settings. As noted above, contributions from volatile and light-absorbing 

background aerosols may account for a portion of the apparent 1-m inlet probe losses at 

low power settings. The high thrust losses are real, however, and appear to be in the 30 

to 50% range for both the left and right inlet probes at 85-100% power. 

Probe losses are further exemplified in Figure 23, a series of nonvolatile particle volumeEI-based PSD plots recorded behind the left engine at 85% power on various days 

throughout the experiment. The data are not corrected for line losses, so differences 

between the 30 and 1-m spectra are possibly much greater than depicted. In any case, 

the downstream PSDs invariably exhibit more volume in the 100 to 200 nm size range 

than the 1-m spectra. Particle loss in this size range is usually incurred through either 

turbulent deposition or thermophoresis; the filtration mechanism discussed in section 3 

could also be a factor. Turbulent diffusion is not a good candidate as changes large 

enough to effect 100 nm particles would completely eliminate particles < 60 nm in 

diameter. 

Figure 23. Volume EI size distributions from the 1- (red curves) and 30-m (black) inlet 

probes behind engine #2 as it was burning JP-8 fuel. Data are from 85% power runs 

recorded on consecutive days, starting on January 27 (upper right-hand plot).

Based on arguments presented in Section 3 above, simple turbulent inertial deposition 

also seems like an unlikely explanation. For example, assuming an inlet diameter and 

length of 0.1 and 1 cm respectively, a sample line diameter and length of 0.5 and 500 cm, 

respectively, a tip flow of 7 lpm, and an exhaust temperature of 350o

C, equation 3 

predicts less than a 0.3% loss of 100 nm particles through the inlet up to the sampleselection valve box. If we use a slightly more complicated formula that considers non-
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isoaxial sampling (reference), we still calculate less than 1% losses even if the probe is 

oriented parallel to the engine exhaust plane. 

Thermophoretic deposition is a more likely explanation for some if not all the observed 

probe losses. For example, line-loss experiments conducted during engine tests 

performed at Tinker Air Force Base in 2007 (referred to as the Tinker engine tests) 

showed that heated sampling lines removed 20-30% of particles with diameters larger 

than 75 nm without significantly affecting smaller (<40 nm) particle transmission. Both 

AAFEX 1-m rakes and probes were actively cooled with high-pressure water flow so that 

hot particles entering the inlet experienced large temperature gradients during the first 

few meters of transport. Indeed, the AAFEX 1-m rake plumbing and temperature 

gradients are somewhat similar to those of an apparatus used by Romay et al. (1998) to 

characterize thermophoretic transport losses in turbulent pipe flow. In that experiment, 

particles embedded within gas flow of various temperatures were introduced into a 1-m 

length of 0.5 cm I.D., water-cooled copper tubing. At 35 lpm flow, the investigators 

observed largely size-independent thermophoretic losses of about 0.1% per degree 

temperature difference between the hot gas and cooled tubing. If we extrapolate this 

finding to the AAFEX situation where ∆T was 300 – 400o

C, we predict losses on the 

order of 30 to 40% for the 1-m probes. These values are probably an upper limit 

however, as although tube diameters were about the same, flow rates were typically 

higher (50 – 70 lpm) and the temperature gradients less steep in AAFEX compared to the 

Romay et al. (1998) experiment. However, these authors also observed measureable (3-

10%) losses of 100 to 300 nm particles in cases where ∆T = 0 and Re=1×104

, which 

they attributed to turbulent eddy impaction. The authors also indicate losses due to this 

process as well as themophoresis are exacerbated by having particle concentration 

gradients, which is potentially the case for the particle dilution probes which initially 

sheath the collected exhaust stream with a concentric flow of dry filtered nitrogen gas. At 

high thrust conditions, turbulence levels are also higher in the AAFEX 1-m rakes, with 

Re approaching 20,000 in the 0.55 cm tubing that connects the probes with the valve box. 

Moreover, it appears that significant losses of both particle mass and number occurred 

within the AAFEX particle probes, particular at high engine power settings. 

Circumstantial evidence suggests that the losses are caused by thermophoretic deposition 

and perhaps turbulent eddy impaction, possibly enhanced by concentration gradients 

present just downstream of the inlet tip. Further confirmation and characterization of 

these losses require additional experiments wherein temperatures, flow rates, and sizedependent particle transport efficiency are carefully measured. A systematic laboratory 

study using a replica of the engine probe heated to reproduce engine sampling conditions 

could identify and establish the range of sensitivity of the parameters (i.e., temperature 

gradients, particle size, sample velocity) that control both thermophoretic and turbulent 

eddy impaction losses. Subsequent engine exhaust tests should employ thermocouples 

and pressure ports at various points to carefully measure temperature and pressure 

gradients in the flow path. Both the laboratory and engine exhaust test would benefit 

greatly if coupled with a theoretical component. 
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9.0 COMPARISON OF DOWNSTREAM WITH PROBE-TIP DILUTION

Aircraft engines are recognized as being significant sources of ultrafine particles, thus 

regulatory agencies are moving in the direction of imposing limits on their number and 

mass emissions to mitigate possible human health and climate impacts. Sampling the 

emissions is not a trivial endeavor, however, as the exhaust contains very high 

concentrations of not only black carbon particles, but of aerosol precursor gases as well. 

Thus to accurately measure these emissions, exhaust samples must be diluted very 

quickly to prevent coagulation and formation of new aerosols through condensation of 

low volatility species. To achieve this task, Arnold Engineering Development Center 

(AEDC) has developed special "particle" probes that introduce a concentric flow of 

filtered gas just downstream of the inlet tip, effectively diluting samples within 

milliseconds of collection. Indeed, all of the detailed aircraft particle emission studies to 

date (EXCAVATE, APEX-1-3, UNA-UNA, AAFEX) have used some variation of these 

probes to collect samples for particle measurements. There are several disadvantages to 

using the particle probes, however: they are expensive to construct; they must be 

mounted in specially designed (and expensive) sampling rakes; the rakes are difficult and 

time consuming to install; and the amount of plumbing required leads to bulky, difficult 

to operate and maintain leak-free, rake installations. Because of the high cost and 

inconvenience, engine manufacturer are understandably reluctant to endorse standard 

exhaust particle sampling procedures that require modifying their existing rakes to 

accommodate the special dilution probes. They have challenged the measurement 

community to evaluate whether the dilution probes are absolutely necessary for 

accurately sampling gas turbine engine particle number and mass emission or if modified 

gas probes can yield adequate results.
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Figure 24. Comparison of total (top) and nonvolatile particle emission indices measured 

downstream of the gas (red points) and particle (black) inlet probes on R1.

To address this challenge, AAFEX conducted an experiment to compare particle number 

and mass EIs as measured in samples collected by an adjacent pair of particle and gas 

probes located on the 1-m right engine sampling rake. These water-cooled probes were 

separated by 1.25 inches and mounted very near the engine centerline where particulate 

emissions were uniformly distributed across the engine exit plane (see section 6). For 

the particle probe, exhaust sample was diluted just downstream of the inlet tip with a 

concentric flow of filtered N2 gas and was transported through approximately 3 m of 3/8"

OD tubing to a 6-port valve box. For the gas probe, undiluted sample was collected and 

transported through 1.5 m of 1⁄4" OD stainless tubing to a Swagelok, 1⁄4" to 3/8" reducing 

tee located at the rake-stand base. The 1⁄4" side of the tee was bored out to 1⁄4" and the 

transport tube was inserted though the tee and about 1" into the 3/8" thin-walled stainless 

outlet tube attached to the opposing side; filtered dilution gas was piped into the tee’s 90o

connector and was mixed with sample as a concentric flow at end of the inserted 1⁄4"

transport tube. The resulting diluted sample was transported ~1.5 m through the 3/8"

tube to the 6-port valve box. The diluted particle and gas probe samples shared a 

common flow path from the valve box back to the sample distribution manifold in the 

MST trailer. The lines and valve boxes were unheated. 
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Table 4. Comparison of emission measurements made on the Particle and Gas inlet 

probes.

The probe comparison test was conducted on Monday, February 2, 2009 between 10:15 

and 12:00, local time. Winds were calm, but ambient temperature increased from ~10 to 

~16o

C between the start and end of the experiment. The aircraft was burning sulfur-rich 

(1200 ppm) JP-8 fuel in the test engine (#3) to enhance volatile aerosol formation in 

undiluted samples. The test matrix involved collecting comparative data at 4, 7, 30, 45, 

65, and 85% engine thrust. Standard procedure was to establish stable engine power, 

then alternately draw sample from the two probes by switching valves in the 6-port. 

Sample dilution in each case was adjusted to maintain a nominal 10:1 dilution ratio as 

estimated from measured CO2 mixing ratios. About three minutes of data were recorded 

on each probe before the next condition was requested. 

Results of the study are presented in Figure 24 and Table 4. The data include 

"nonvolatile" and "total" EIs, which refer to measurements made respectively with and 

without thermal-denuders placed in the flow paths leading to the CN counters and SMPS 

systems used to determine particle number and volume concentrations. The total and 

nonvolatile mass EIs were calculated from SMPS integrated volumes assuming a density 

of 1 g cm-3 for both the soot and volatile aerosol particles. A number of points in the 

table represent the average of several individual data points (4, 7, and 65%). At the 85% 

power setting, gas probe measurements were only recorded over a single 3-min interval, 

while particle probe data was collected during 6, 3-minute intervals at different dilution 

ratios to evaluate sub-isokinetic sampling effects on particle concentration and size; the 

particle probe data included in Table 4 and Figure 24 are from the sampling interval with 

a dilution ratio that most closely matched that of the gas probe run. 
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Figure 25. Comparison of volume based size distributions measured downstream of the 

gas (red curves) and particle probes (black) as the #3 engine was operated at 65 (top) and 

85% (bottom) of maximum rated thrust. Plots on the left represent the total (nonvolatile 

+ volatile) emissions, whereas those on the right are for nonvolatile particles only.

From reviewing Figure 24 and Table 4, we see that total aerosol number (EIn-tot) and 

mass (EIm-tot) EIs were significantly higher in the gas probe samples indicating that 

aerosol nucleation and growth was occurring vary rapidly in the 1.5-m, 1⁄4" tube that 

transported undiluted exhaust from the inlet tip to the dilution point. For example, at 

idle, gas probe EIn-tot and EIm-tot values were respectively ~5 and ~1.5 times higher than 

values measured using the particle probe. This pattern was particularly evident at low 

and high power settings and was likely caused by the overwhelming availability of 

condensable material at idle and the propensity of sample to stagnate in the line at higher 

thrust settings.

In contrast to the total aerosol emission parameters, the EIn-nv, EIm-nv and EIbc for the 

gas and aerosol probes were in remarkably good agreement. Figure 25, which shows 

PSDs recorded at 65 and 85% power, provides additional insight into the differences 

between the gas and particle probe measurements. The left-hand plots were recorded on 

unconditioned samples, whereas the righthand plots were obtained on samples that had 
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first passed through a 350oC tube heater. The unconditioned gas probe samples clearly 

exhibit nucleation mode aerosols and substantial coatings on soot mode particles. The 

thermal denuder evaporates the volatile particles and coatings and as a result, the gas and 

particle probe PSDs are almost indistinguishable in peak position and shape. Indeed the 

average percent differences between the gas and aerosol probes EIn-nv, EIm-nv, and EIbc

across all power settings was respectively 3, -1 and -10%, where negative values indicate 

that particle probe measurements are on average greater. The EIn-nv values were 

incredibly close, with only the 4% and 7% idle point differing by more than |3%|; the 

higher gas probe values at lower power settings are caused by reformation of volatile 

particles downstream of the thermal denuder. 

EIbc values differed by a factor of two (12.5±5.5 versus 6.4±2.9 mg kg-1 for the particle 

and gas probes respectively) at ground idle, but the error bars overlapped significantly. 

However, particle probe EIbc values were slightly higher than gas probe values at all 

power settings. Possible causes for this include: enhanced turbulent losses inside the gas 

probe inlet; greater wall losses in the gas lines due to soot build up in the undiluted 

sample line; slight differences in emissions at the two probe locations; or greater line 

losses in the trunk lines leading back to the community sampling manifold. The gas 

probe inlet tip gradually expands from 0.06" to 0.20" ID diameter and flow is 

undoubtedly very turbulent in this region; indeed one can envision turbulent eddies 

forming just inside the inlet tip, which might lead to losses via the eddy impaction 

process described in the section above. In contrast, within the particle probe, the exhaust 

stream is initial confined to within a 0.04" ID capillary before being dumped into the 

center of a sheathing flow of dilution gas; this approach possibly isolates the sample from 

wall contact until the flow is well-established and somewhat stable. Of course, a 

modeling analysis is required to verify whether this is the case or not. As for dirt 

buildup, the transport efficiencies of the individual gas and aerosol lines were not 

measured, but this experiment was conducted at the end of AAFEX when the lines were 

their dirtiest and it is safe to say that particle concentrations were at least a factor of 10 

higher in the gas lines, when in use, than in the particle sampling lines; we thus cannot 

rule this out as a possible explanation. As for differences in probe location, our section 5 

analysis indicates that, discounting the 45% power point, black carbon values varied by 

up to 42% within 4" of the engine centerline; the variations were less at high engine 

power, which is also the case with the Table 4 data. Again excluding the 45% data 

point, EIn-nv only varied by 1-8% within 4" of the engine centerline, which is also 

consistent with the good agreement seen between measurements made of this parameter 

using the gas and aerosol probes spaced 1.25" apart. Thus spatial variations may have at 

least contributed to the slightly higher EIbc observed in the particle probe samples. 

Particle transport losses may also account for a fraction of the difference. Particle probe 

total diluted sample flows (i.e., sample + diluent gas) were up to 50% higher than for the 

gas probe, which should have reduced wall losses due to the lower residence times. This 

possible mechanism should have had a greater impact on particle number than mass, 

which, in view of the almost perfect agreement in gas and particle probe EIn-nv, was not 

the case. However, it’s possible that volatile coatings reduced the mean gas probe 

particle mobility and hence reduced their susceptibility to turbulent diffusive loss, more 

or less canceling out the increased number losses due to lengthier residence times. In 
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turn, this decreased mobility may have increased the loss of larger particles through the 

"filter" effect discussed in Section 3 above. 

Moreover, it is somewhat surprising that the gas and particle EIn-nv values agreed so well 

as particle coagulation was expected to occur in the undiluted section of gas probe line. 

From measured dilution flows (approximately 35 lpm) and sample and exhaust CO2

concentrations (1300-2300 and 22000-36000 ppm, respectively), a calculated 

approximately 28 cm-3 pre-dilution line volume, and an assumed .0013 g cm-3 sample 

density, we calculate that sample remained undiluted for between 0.6 and 0.9 seconds. 

Exhaust nonvolatile particle number densities ranged from 0.2 - 2 x 107 cm-3 at standard 

pressure and temperature conditions. Assuming a polydisperse size distribution with a 

respective mode and standard deviation of 20 nm and 1.6 and using equations developed 

by Baron and Willeke (2005), we calculate coagulative particle losses that range from 1 

to 6.2%, where the worst case is at idle and the best at 45% thrust. Apparently the 

coagulative losses are in the range of particle sizes (3-10 nm) that are almost completely 

removed by turbulent diffusion during sample transport, so their absence cannot be 

detected by downstream instruments. 

Figure 24. Rough schematic of an improved gas-line dilution system.

It is also surprising that for the gas probe, acceptable dilution ratios (14-19 as calculated 

from exhaust and sample CO2 mixing ratios) were obtained across the entire engine 

power envelope using a constant, 35 lpm dilution flow rate; dilution flow requirements 

for the particle probe were much more variable (30-50 lpm). For the gas probe, 

calculated tip flow rates varied from 1.9 to 2.5 lpm (substantially below the 8 lpm critical 

flow calculated for a 0.15 cm orifice at standard temperature and pressure). Inlet flow 

should have increased in proportion to impact pressure, which typically doubles in going 

from idle to takeoff thrust. Clearly, additional modeling and measurement work is 

needed to understand flow dynamics within both the gas and particle probes. 
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We finally note that freestream to gas probe inlet velocity ratios, U0/U, varied from ~2 to 

6, depending on power, suggesting that particle mass may have been artificially enhanced 

in some cases from sub-isokinetic sampling effects. 

In summary, we conclude that standard gas probes can yield representative gas turbine 

engine number and mass EIs and size distribution measurements, provided that the 

exhaust samples are diluted within a couple of meters of the inlet tip and that the diluted 

samples pass through a thermal-denuder immediately upstream of the diagnostic 

instruments to remove volatile material formed during initial transport through the 

undiluted gas line. The introduction of dilution gas must be carefully implemented, 

however, to avoid additional particle loss through turbulent inertial or eddy impaction 

processes at the dilution point or creating a pressure restriction that leads to exhaust 

sample stagnation within the upstream portion of transport tube. Indeed, there is 

considerable room for improvement in the AAFEX gas probe sampling scheme. A more 

optimum design would include dilution system that allows for gas-line bypass flow to 

reduce sample residence time. An example is shown in Figure 24. Here, the bypass line 

is attached to a pump to draw a continuous flow through the gas line to reduce aerosol 

nucleation and coagulation. The bypass line is also pressure controlled at ~1 atmosphere 

so that the dilution gas and diluted sample flows remain constant regardless of engine 

power. This will simplify line loss assessments and eliminate the need to constantly 

monitor and change dilution gas flows, line pressures and vent valve settings. The 

sample line leading into the dilution box should also be heated to prevent water vapor 

condensation and volatile aerosol formation within the undiluted gas sample. 

The question remains as to how long the exhaust samples can remain undiluted before 

coagulation and agglomeration processes significantly change nonvolatile number EIs 

and PSDs. In AAFEX, particle losses due to coagulation were calculated to be minor and 

mostly in the size range that is effectively filtered out during sample transport through the 

long sampling lines. DC-8 exhaust particle concentrations were also relatively low,

peaking at 2×107 cm-3 at idle and coagulative losses were calculated to be 6% for a 1-

second, pre-dilution lifetime. Assuming a nominal PSD mean diameter of 20 nm and 

standard deviation of 1.6, if we increase the particle concentrations to 1×108 cm-3

(corresponds to an EIn-nv of around 5×1015 kg-1

, which is common for older engines) and 

residence time to 5 seconds, we calculate that number densities will drop 65% and the 

mean diameter will shift to 28 nm before dilution air is introduced. 

10. SUMMARY AND RECOMMENDATIONS

AAFEX collected a great deal of information regarding the characteristics and 

performance of the particle sampling installation. Important observations include the 

following.

• Accumulation of soot and volatile materials on sampling line walls can significantly 

reduce particle transport efficiencies, leading to underestimates of both number and 

mass emissions. Continuously drawing sample flow through unused lines contributes 

to the dirt build-up. 
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391

• Particles in the 100-300 nm size range are readily lost to dirty tubing walls, which 

defies explanation by the standard smooth-bore tubing loss mechanisms included in 

the UTRC model. Since easily applied theoretical treatments incorporating surface 

roughness elements are lacking, we postulate that soot deposits to tubing walls to form 

dendritric, fiber-like structures, then invoke filter theory which easily accounts for 

particle loss in this "inert" size range.

• Under relatively cold conditions (~0o

C) and lower power settings, volatile particle 

nucleation typically reaches equilibrium between formation and coagulation before 

reaching the 30-m inlet probe. However, volatile particle mass continues to increase 

during sample-line transport, potentially increasing by 50 to 75% at high engine

powers, depending on how line-loss corrections are applied.

• PM emissions were surprising variabile across an 8 inch span to the left of DC-8’s #2 

engine centerline. For total PM emissions, the fluctuations were linked to oil fumes 

emanating from a leak in the engine nacelle. Nonvolatile PM mass and number EIs 

were fairly stable within 4 inches of the centerline, suggesting that single point 

sampling in that region would yield emission parameters broadly representative 

(within 20%) of the entire engine. 

• At high engine thrust where the plume velocity approached Mach 1, PM emissions 

generally increased with freestream to sample inlet velocity ratio, U0/U, indicating 

particle populations were being enhanced by the inertial effects associated with subisokinetic sampling. However, the enrichment trends did not faithfully follow 

predictions, and were possibly caused by other mechanisms such as improved sample 

line transport efficiency at the higher flow rates needed to produce large U0/U ratios. 

• Nonvolatile PM emission indices measured from 30-m samples were systematically 

higher than measured at 1-m, indicating possible particle loss in the 1-m inlets or 

transport tubes. Because the 1-m inlet probes are cooled, thermophoretic effects must 

be considered and by similarity to previous work, we estimate they could account for a 

large fraction of the observe difference in the 1 and 30-m measurements. Turbulent 

eddy impaction is another possibility, but cannot be evaluated without additional 

testing under appropriate conditions.

• PM emission measurements made on samples collected with a special particle probe 

and a gas probe with dilution gas introduced 1.5 m downstream typically agreed to 

within 10%, suggesting that existing gas certification sampling probes used by engine 

manufacturers may be modified to yield representative particle number, mass and PSD 

measurements. However, the success of this approach is contingent on diluting 

exhaust samples within a few meters of the gas probe tip and placing an efficient 

thermal denuder just upstream of diagnostic instruments to evaporate and absorb 

volatile aerosol components. Sampling from the gas probes may other advantages in 

addition to the obvious lower cost and easier implementation. Optimally-designed 

gas-probe dilution systems will deliver a constant ratio of dilution gas to sample flow, 

greatly simplifying sample system operation and monitoring requirements. This 

approach will also enable use of laminar flow rates in sample lines as only a fraction 

of the exhaust gas passing through the inlet tip need be diluted and transported back to 

the diagnostic instruments; particle diffusive and inertial losses are substantially lower 

in laminar, as opposed to turbulent, pipe flow.
APPENDIX P 

392

AAFEX also provided a valuable learning experience and suggested changes or activities 

that could be implemented to improve future experiments. 

 The loss in sampling line transport efficiency due to increasing wall roughness over 

the course of AAFEX was particularly troublesome. For long term experiments, this 

can be avoided by making daily sampling line efficiency assessments based on the 

fraction of ambient aerosols that penetrate the subject sampling line. This type of 

experiment is easily implemented by drawing representive flows through the lines and 

measuring total particle concentrations on the up- and downstream ends with identical 

particle counters as was done during the end-of-mission line loss evaluation discussed 

in section 3.0 above. Dips in efficiency below a certain threshold value, say 80%, 

would mandate line cleaning or replacement. 

 The 1-m sampling probe losses were probably exacerbated by accumulation of soot on 

the inside surfaces of the probe and transport tube leading to the 6-port valve box. 

The box was designed to deliver dilution gas and draw a small flow through each 

unused probe, which unnecessarily added to the wall contamination. A more 

optimum valve-box design would blow purge gas out each unused particle probe inlet 

tip. 

 For unknown reasons, PM emissions are sensitive to sample dilution at high engine 

powers. A comprehensive sample probe experiment is needed to investigate the 

source(s) of this variability. This requires generating a high pressure particle stream 

and measuring the concentration up and downstream of dilution probe. The dilution 

characteristics of a modified gas probe is also of interest and can be established at the 

same time. 

 Particle losses in the 1-m inlet probe were fairly substantial under some conditions, 

possibly from thermophoretic deposition or turbulent eddy impaction, which are 

difficult to distinguish under actual engine test conditions. Thus, the above probe 

dilution test should also investigate the effect of sample-probe temperature differences 

and include several points at ΔT=0 to investigate impaction losses as a function of 

total probe flow. Again, these tests should be conducted on both the particle and 

modified gas probes. Future engine tests should include temperature and pressure 

measurements at various points in the 1-m sample flow path so that the lab results can 

be extrapolated to actual sampling conditions. 

 AAFEX results suggest that gas probes can be used to collect representative PM 

emission samples. To more firmly establish the viability of this approach, future 

research-style engine tests (i.e., AAFEX-II) should deploy an optimally designed gas 

probe dilution system and perform a more comprehensive comparison of gas and 

particle probe measurements over a broad range of dilution ratios and engine 

conditions. 

References

Anderson, B.E. et al., 1998: Airborne observations of aircraft aerosol emissions II: 

Factors controlling volatile particle production. GEOPHYS. RES. LETT.25 (10): 

1693-1696. 

Anderson, B.E., 2005: An overview of the NASA Experiment to Characterize Aircraft 

Volatile Aerosol and Trace-Species Emissions (EXCAVATE), NASA/TM-2005-

19019. 
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Anderson, B.E., et al., 2010: Aircraft Exhaust Sampling Strategies, NASA TM in 

preparation.

Cofer, W.R., et al., 2001: Results of the August 1999 Aerosol MeasurementIntercomparison

Workshop, T-38 Aircraft Sampling Phase, NASA/TM-2001-211226.

Hangal and Willeke, 1990: Overall efficiency of tubular inlets sampling at 0-90 degrees 

from horizontal aerosol flows, Atmos. Environ., 24A, 2379-2386.

Hinds, W.C., 1999: Aerosol Technology, 2nd Edition, New York, John Wiley and Sons.

Im, K., and R. Ahluwalia, 1989: Turbulent eddy deposition of particles on smooth and 

rough surfaces, J. Aerosol Sci. 20, 431-436.

Otani, Y. et al., 1989: Experimental study of aerosol filtration by the granular bed over a 

wide range of Reynolds Numbers, Aerosol Science and Technology, 10(3), 463-474.

Romay, F. et al., 1998: Thermophoretic deposition of aerosol particles in turbulent pipe 

flow, J. Aerosol Sci., 29, 943-959.

Wey, C.C., et al., 2006: Aircraft Particle Emissions Experiment (APEX), NASA/TM2006-2143822007

Willeke, K. and P. Barron, 2005: Aerosol Measurement, 2nd Edition, New York, John 

Wiley and Sons. 
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APPENDIX Q: Instrument Inter-Comparison

D.S. Liscinsky, B.E. Anderson, Changlie Wey, Anuj Bhargava, Rick Miake-Lye, Edward 

Winstead, Phil Whitefield, Don Hagen and Prem Lobo

ABSTRACT

Requirements and limits for PM metrics demand reliable instrumentation and a 

suitable particle calibration source. Intra-instrument comparisons of the MAAP for the 

measurement of black carbon mass showed that as expected the same instrument 

analyzing the same sample produces the same result. Inter-instrument comparison 

illustrated that particle properties and instrument factors can influence the results. The 

removal of volatile particles is a key to compare mass and number datasets. Instrument 

efficacy can be obtained, however without established instrument calibration methods, 

traceability is lacking and measurement uncertainty remains. A commercially available, 

portable particle generator based on a well-controlled propane diffusion flame, produced 

results which encourage further assessment of this generator as a source for field 

measurement of line loss and instrument calibration.

DISCUSSION AND RESULTS

A collaborative study was performed at AAFEX on Feb 3, 2009 using a portable 

soot generator as an engine surrogate. The objectives of the study were to compare 

instruments and take a first look at this soot generator as a calibration source for field 

measurements. The soot source was distributed to a number of different instruments so 

that simultaneous measurements could be performed. Although the suite of instruments 

provided the capability of measuring particle concentration, size distribution, and mass, 

the focus of the experiment was to compare instruments that measure BC mass because 

line loss measurements were not performed and mean particle sizes ranged from 50 to 

110 nm (typically larger than engine particles). The instruments consisted of: (1) 

ThermoElectron Multi Angle Absorption Spectrometer (MAAP) model 5012, (2) Artium 

LII-200 Laser Induced Incandescence instrument, (3) Droplet Measurement Technologies 

Photo-Acoustic Soot Spectrometer (PASS-3), (4) standard Smoke Number instrument, 

(5) Scanning Mobility Particle Sizer (SMPS), (6) Condensation Particle Counter (CPC).

In AAFEX and several previous studies, intra-instrument comparisons have been 

performed. Since the ThermoElectron Multi Angle Absorption Spectrometer (MAAP)

model 5012 provides an inexpensive, real-time measurement of BC mass, it has received 

much attention. Recent efforts yieded direct comparisons where the same sample was 

delivered to different instruments with different operators. The results of two direct 

comparisons are shown in Figure 1 where the measurements of BC mass from two 

different instruments are plotted against one another. On the left-hand side 

measurements made at AAFEX are compared and, except for one point the agreement, is 

well within +/- 10% (the outlier is a high-power point where the sampling system was not 

well-stabilized during the measurement period). On the right-hand side are 
APPENDIX Q

395

measurements taken at AFRL while sampling a T-63 gas turbine. Again, excellent 

agreement is shown. Additional examples of intra-instrument further confirm that the 

same instrument, given the same sample can produce the same result which is the 

definition of instrument efficacy. Although instrument efficacy is only shown for the 

MAAP, similar results have been shown for practically all standard PM instruments.

Figure 1: Intra-Instrument Comparison of MAAP Measurements of BC mass

Inter-instrument comparisons were performed at AAFEX using a soot generator from 

Jing AG Limited, Switzerland: Model 5202 RSG mini-CAST (Real Soot Generator mini 

Combustion Aerosol Standard). More details can be obtained at 

www.sootgenerator.com. The miniCAST was developed following deployment of the 

CAST (Combustion Aerosol Standard) in 1999 by the Swiss Federal Office of Metrology 

and Accreditation. The CAST has been widely used in Europe, most notably in the 

ongoing UNECE GRPE Particle Measurement Programme (PMP), which is focused on 

the characterization of emissions from diesel engines. Whereas the CAST is quite heavy 

(40kg), the miniCAST is 5 kg and therefore appropriate for field use. Furthermore, the 

output from a combustion source is somewhat more representative of aircraft emissions 

than other calibration aerosols such as salt, polystyrene latex spheres and the like, which 

are typically used in laboratory settings. 

A photo of the Model 5202 RSG mini-CAST and its external flow control system is 

shown in the upper left of Figure 2 along with a simplified schematic of the flow paths to 

illustrate the control features of the miniature co-flow propane diffusion flame (inside the 
APPENDIX Q

396

purple dashed lines). A key to the performance of this unit is accurate flow metering. 

This is handled by 5 independent precise mass flow controllers which are set and 

monitored by computer software. The propane/air diffusion flame generates soot 

particles which are subsequently quenched and diluted inside the unit to avoid soot 

buildup. By controlling the metered fuel to air ratio and quenching rate a range of 

particle size distribution and total particle number can be delivered. However, note that 

this is not a premixed flame, so the metered air to fuel ratio defines a global equivalence 

ratio. The operating condition of the burner is better described by using the fuel to N2 

ratio since introduction of N2 into the fuel flow is used to modify (lower) the flame 

temperature and change the level and rate of soot production.

The utility of the miniCAST is evident due to portability, dynamic range of soot output 

and ease of use. However, it was found that over much of the design space of the device 

the number concentration of generated particles exceeds 1E8/cm3 (and mass loading 

typically exceeds 10mg/m3). At this high number density, particle size/mass distributions 

rapidly evolve because of particle-to-particle collisions. Therefore a secondary dilution 

system is required for this device to be used as a calibration source. A dilution system 

consisting of an off-the-shelf Fox Valve Mini-Eductor was used in the initial evaluation 

of this device. The eductor operates by setting the pressure of the motive air eliminating 

the need to meter a dilution flowrate and discharges a rapidly mixed diluted sample 

stream at a positive working pressure. However it was found that the eductor is so 

efficient (by design) that the dilution ratio could not be varied sufficiently in all cases by 

just changing the motive flowrate, i.e. pressure. A simple solution was to insert a flowlimiting orifice on the suction side of the eductor as shown in Figure 2. Commercial 

diluters such as the Dekati DI-1000 would be logical replacements for the system used in 

the laboratory evaluation described in the following. 

 
APPENDIX Q

397

Figure 2. Schematic description of the Flow Streams of the Model 5202 miniCAST 

Results obtained after AAFEX are shown in Fig. 3 to illustrate typical miniCAST 

reproducibility over time where the left-hand plot is UTRC data and the right-hand plot 

from LaRC data. Over 2.5 hrs the system was found to output a size distribution with a 

GMD that was within 1nm and a variation of concentration within 2%, however the 

output did appear to have a trend which was changing over time possibly because of the 

dilution system. Typical source size distributions used on Feb 3 along with some 

stability info shown in Fig. 4.
APPENDIX Q

398

 

Figure 3. Short-term Stability and Longer-term Reproducibility of the miniCAST

Figure 4. Size distributions used for the AAFEX instrument comparison experiment

Measurements of BC mass are compared in Figure 5. A series of measurements were 

made as the miniCAST combustion air was changed in discrete steps to provide a wide 

1.50E+06

1.55E+06

1.60E+06

1.65E+06

1.70E+06

1.75E+06

1.80E+06

30

31

32

33

34

35

36

37

38

39

40

0 50 100 150 200

Particle Concentration (#/cc)

scan number (elapsed minutes)

GMD (nm)
APPENDIX Q

399

range of BC concentration. The plotted points are averages over the time on point which 

was 10min. Measurements reported by the LII and PASS instruments are compared to 

MAAP and show similar trends although differences in value reported by LII are ~30% 

to ~50% over much of the data with the PASS in better agreement. 

Figure 5. Comparison of MAAP to LII and PASS measurements of Black Carbon mass

Measurements of BC mass are plotted vs. SN in Figure 6. The green line predicts soot 

mass from a correlating expression developed by Med Colket at UTRC which represents 

the best fit to a wide number of reported data sets that infer soot mass from measured 

SNs. The x symbols represent the concentration index calculated from FOA 3.0. The 

measured values tend to be higher than the correlations would predict and the deviation is 

seen to increase as soot loading increases.

Figure 6. Comparison of SN to measured Black Carbon mass
APPENDIX Q

400

The presented measurements of BC mass under steady conditions highlight the difficulty 

of correlating measurements using different instruments. As expected, variation between 

identical instruments was small, however comparison of the results obtained by different 

measurement techniques showed greater variation often on the order of 50%. Some of 

the disagreement maybe attributed to volatile coating of the soot particles produced by 

the miniCAST since both LII and PASS are less sensitive to organic content than MAAP. 

Additional instrument comparisons were performed using the engine data acquired during 

AAFEX. Efficacy was found between sizing instruments although the level of agreement 

was not as good as with the MAAP. In Figure 7 the results of a large number of SMPS 

measurements collected by MS&T and LaRC at AAFEX are compared on a point-topoint basis, i.e. the same sample analyzed by different instruments/operators. Although 

the trend in total number of particles is clearly the same for each instrument and the 

average of all measurements appears to be 1:1, sizable deviations are noted. No line-loss 

corrections have been applied to the data, which may explain some of the deviation 

(different length sample lines, etc.). In addition a comparison of operating conditions 

may uncover slightly different size cut offs. So although the plot illustrates efficacy, 

rigorous comparison of absolute value would be aided by a calibration procedure.

Figure 7. Comparison of Total particle number measured by SMPS

In the left-hand plot in Figure 8 measurements of EImass calculated from thermally 

denuded size distributions obtained using an SMPS and an EEPS from the 1 m sample 

probe at AAFEX are compared to MAAP measurements. The SMPS measurements 

provide the better correlation of EImass with the EEPS correlation indicating a lower size 

distribution, i.e. undersizing compared to SMPS. Slightly different size cut offs may 

have been set for the instruments, which would explain the different trends; however in 

the right-hand plot a comparison of the size distributions confirms that the EEPS 

consistently undersizes. Comparisons such as these illustrate the difficulty in comparing 

results if calibration methods are not established and used. 
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Figure 8. Comparisons of SMPS and EEPS

SUMMARY

As the collection science for PM becomes increasingly more sophisticated, tolerance for 

error and uncertainty is getting smaller. Traceable calibration methodology is required if 

the data collected by the different instruments are to be used in a quantitative analysis for 

setting standards and regulations. One weakness of PM instrumentation (and also in 

evaluation of the sampling system) is the lack of a suitable calibration technique that can 

be easily performed in the field, similar to calibration of gas speciation instruments. A 

calibration methodology would not only help in identifying issues with different 

instruments but would also be useful in resolving other problems, like sample line and 

probe losses, encountered while making particle measurements. 
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Alternative Aviation Fuel Experiment (AAFEX) 

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The rising cost of oil coupled with the need to reduce pollution and dependence on foreign suppliers has spurred great interest and activity in 

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Aircraft fuels; Exhaust gases; Aerosol emissions; Alternative fuels; Aviation

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