NASA/TM-2001-211226

NASA’s Atmospheric Effects of Aviation

Project

Results of the August 1999 Aerosol Measurement

Intercomparison Workshop, T-38 Aircraft Sampling Phase

W. Randy Cofer III, Bruce E. Anderson, and V. S. Connors

Langley Research Center, Hampton, Virginia

C. C. Wey and T. Sanders

Glenn Research Center, Cleveland, Ohio

E. L. Winstead

SAIC, Hampton, Virginia

D. Pui and Da-ren Chen

University of Minnesota, Twin Cities, Minneapolis, Minnesota

D. E. Hagen and P. Whitefield

University of Missouri-Rolla, Rolla, Missouri

October 2001
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NASA/TM-2001-211226

NASA’s Atmospheric Effects of Aviation

Project

Results of the August 1999 Aerosol Measurement

Intercomparison Workshop, T-38 Aircraft Sampling Phase

W. Randy Cofer III, Bruce E. Anderson, and V. S. Connors

Langley Research Center, Hampton, Virginia

C. C. Wey and T. Sanders

Glenn Research Center, Cleveland, Ohio

E. L. Winstead

SAIC, Hampton, Virginia

D. Pui and Da-ren Chen

University of Minnesota, Twin Cities, Minneapolis, Minnesota

D. E. Hagen and P. Whitefield

University of Missouri-Rolla, Rolla, Missouri

October 2001
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Space Administration.
iii

Contents

Nomenclature . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . v

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

2. Participants, Instrumentation, and Affiliations. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2

2.1. Workshop Facilitor. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2

2.2. NASA Langley Research Center Group . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2

2.2.1. Participants. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2

2.2.2. Instrumentation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3

2.3. NASA Glenn Research Center Group . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .4

2.3.1. Participants. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4

2.3.2. Instrumentation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4

2.4. University of Missouri-Rolla Group . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5

2.4.1. Participants. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5

2.4.2. Instrumentation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5

2.5. University of Minnesota Group . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4

2.5.1. Participants. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5

2.5.2. Instrumentation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6

3. Field Tests . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6

4. Results and Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7

5. References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13
v

Nomenclature

AEAP Atmospheric Effects of Aviation Project

CNC condensation nuclei counter

CPC condensation particle counter

DMA differential mobility analyzer

EAC electrostatic aerosol classifiers

EI emission index

EP engine power

GMD geometric mean diameter

GRC John H. Glenn Research Center

LaRC Langley Research Center

LPC laser particle counter

MASS Mobile Aerosol Sampling System

NDIR nondispersive infrared

nASA nanometer aerosol size analyzer

PAGEMS Particulate and Gaseous Emissions Measurement System

PNC particle number concentrations

PSL Particle Simulation Laboratory

SASS Subsonic Assessment Program

SMPS scanning mobility particle sizer

UMN University of Minnesota

UMR University of Missouri-Rolla
1. Introduction

Because commercial aviation is anticipated to increase substantially in both volume and extent

during the next two decades (Boeing 1996; Baughcum, Sutkus, and Henderson 1998) and aircraft represent a unique source of anthropogenic emissions (inasmuch as they are routinely emitted above the

boundary layer), the need to better understand their environmental impact is clear. NASA’s Atmospheric Effects of Aviation Project (AEAP) addresses this need. A major component of the AEAP—the

Subsonic Assessment Program (SASS)—was formed with the goal of characterizing the effects that the

current fleet of commercial aircraft have on atmospheric chemical and radiative processes, and what

effect they may have in the coming years, as air traffic increases (Friedl 1997). Aircraft are prolific

sources of both soot and sulfate particles to the upper troposphere and lower stratosphere (Fahey, Keim,

and Chan 1995; Anderson, Cofer, and Brunke 1998; Anderson, Cofer, and Hudgins 1998; Miake-Lye

et al. 1998; Karcher and Fahey 1997). These particles may have an impact upon climate through direct

absorption/reflectance of solar radiation (Pueschel et al. 1992); by altering cirrus cloud formation,

reflectance, or duration; or by providing additional surface area upon which heterogeneous chemical

processes, such as ozone destruction, can occur. Because of their potential to perturb these important

atmospheric processes, the AEAP has placed a high priority upon gaining an increased understanding of

particle formation and growth processes within aircraft plumes and upon characterizing the particulate

emissions of turbine engines (Friedl 1997).

To accurately assess the atmospheric effects of aircraft-generated particulates as well as to develop

and test predictive models for aircraft emissions, the number density, size, and composition of aerosols

within engine exhaust and aging plumes must be understood and well characterized. Thus, the AEAP

has funded several individual groups to make observations within a number of different measurement

venues including behind aircraft in-flight, parked in run-up areas, as well as downstream of turbine

engines mounted in test cells. Because the soot and sulfate particles within fresh plumes typically range

from a few to a few tens of nanometers in diameter, measurement approaches are very limited. Butanolbased condensation nuclei counters (CNCs) have been used in most aircraft emission studies (e.g.,

Hagen et al. 1998; Anderson, Cofer, and Brunke 1998; Anderson, Cofer, and Hudgins 1998; Fahey,

Keim, and Chan 1995; Twohy, Gandrud, and Weinheimer 1998). Size distributions are obtained either

by using an electrostatic differential mobility analyzer coupled to a CNC (Hagen et al. 1998) or a battery of CNCs with different lower size cutoffs (Anderson, Cofer, and Brunke 1998; Anderson, Cofer,

and Hudgins 1998; Cofer, Anderson, and Bagwell 1998; Brock et al. 2000). For composition information, samples are typically delivered to a pair of identical CNCs, one with an unheated inlet to monitor

total particulate emissions and the other with a heated inlet to evaporate sulfate/water particles to determine the nonvolatile (or soot) particle fraction (e.g., Cofer, Anderson, and Bagwell 1998). Observations

are reported in terms of emission indices (EIs) or the amount of pollutant generated per kilogram of fuel

burned. This is most often determined by taking the ratio of the specific pollutant concentration to that

of a conserved combustion tracer, such as CO2. For aerosols, EIs are reported as the number of particles

generated per kilogram of fuel burned. If size distribution measurements are also recorded, an inferred

mass EI (grams per kilogram of fuel burned) can be estimated by multiplying the calculated aerosol

volume times an assumed aerosol mass density. Gravimetric analysis of aircraft particulate emissions

has not been successful because of the amount of exhaust gas volume required to obtain a measurable

accumulation (weight) of particles on filtering mediums.

Aircraft aerosol EIs have been recorded by AEAP-sponsored investigators. For example, the

University of Missouri-Rolla has reported measurements from behind aircraft operating in run-up areas

(Whitefield and Hagen 1995), in-flight (Hagen, Trueblood, and Whitefield 1992; Hagen et al. 1998),

and in test cells (Whitefield and Trueblood 1993; Wey et al. 1998). The University of Denver has

obtained airborne observations in aged aircraft plumes (Fahey, Keim, and Chan 1995) as well as very
2

fresh exhaust emissions (Brock et al. 2000). The Langley Group has made near-field, airborne measurements behind a variety of aircraft (Anderson, Cofer, and Brunke 1998; Anderson, Cofer, and Hudgins

1998; Anderson, Cofer, and McDougal 1999) as well as recent determinations of EIs in decaying

plumes over the North Atlantic (Anderson et al. 1999).

Unfortunately, a wide variation in aerosol emissions indices and chemical and physical properties

has been reported in the exhausts of subsonic commercial aircraft. Because a significant fraction of

these aerosol measurements has been measured by various independent research teams involved in the

SASS studies, it became necessary to determine if differences in aerosol measurement system

components and/or techniques used by these groups were responsible for the wide variation in particle

concentrations and properties observed in commercial aircraft exhaust. Because the data have, for the

most part, been collected with similar aerosol counters, it appeared doubtful that the discrepancies

would be explained by instrumental differences alone. Other sources of differences between the

observations may include sampling issues, plume age, engine type and condition, environmental

conditions, and fuel sulfur content.

Thus, to evaluate instrumental error as a source of the observed discrepancies, an Aerosol Measurement Intercomparison Workshop was sponsored by NASA’s AEAP/SASS Program. This workshop

took place August 1–14, 1999, at the NASA Langley Research Center in Hampton, Virginia. The first

week of the 2-week workshop was devoted to challenging the core detection elements of the aerosol

measuring instruments with laboratory-generated aerosols. The second week was focused on testing the

efficiency and sensitivity of the measurement systems by sampling the exhaust from an LaRC T-38

Talon aircraft. Invitations to the workshop were issued to all groups that participated as aerosol investigators in SASS-sponsored airborne and ground-based field experiments. The present report is intended

to be a follow-on to the published results from the laboratory phase of the investigation (Cofer et al.

2001). This report summarizes the aerosol measurements made from sampling the exhaust from the

LaRC T-38 Talon aircraft during engine run-ups on the tarmac and addresses some of the aspects of

sampling probe design and protocols.

2. Participants, Instrumentation, and Affiliations

2.1. Workshop Facilitor

Vickie S. Connors

NASA Langley Research Center

MS 483, Hampton, VA 23681

E-mail: v.s.connors@larc.nasa.gov

Tel.: (757) 864-5849; Fax: (757) 864-5841

2.2. NASA Langley Research Center Group

2.2.1. Participants

Bruce E. Anderson

NASA Langley Research Center

MS 483, Hampton, VA 23681

E-mail: b.e.anderson@larc.nasa.gov

Tel.: (757) 864-5850; Fax: (757) 864-5841
3

Wesley R. Cofer III

NASA Langley Research Center

MS 483, Hampton, VA 23681

E-mail: w.r.cofer@larc.nasa.gov

Tel: (757) 864-5835; Fax: (757) 864-5841

Eddie Winstead

SAIC

NASA Langley Research Center

MS 483, Hampton, VA 23681

E-mail: e.l.winstead@larc.nasa.gov

Tel.: (757) 864-4209; Fax: (757) 864-5841

2.2.2. Instrumentation

The ground-based aerosol measurement system (DMA) consists of an electrostatic classifier that

separates aerosols in a sample stream into size ranges and is connected to a TSI Model 3025 Ultrafine

Condensation Particle Counter that counts the particles. A computer controls the classifier voltage

sweep, and particle counts are directed into inversion software that results in the generation of 25 size

bins. Flows are controlled by mass flow controllers. The system determines an aerosol size distribution

from 5 to 250 nm.

The LaRC airborne instrument suite was designed for use aboard an aircraft to provide continuous

measurements of total and nonvolatile aerosol number densities with crude particle sizing. The system

is composed of two ultrafine condensation nuclei counters (TSI Model 3025 CNCs) and two standard

condensation nuclei counters (TSI Model 3760 CNCs). Both types of CNCs have ≈1 Hz response times

and are butanol based. Some evidence of sensitivity of butanol-based CNCs to particle composition has

been reported (Ball, Hanson, and McMurry 1999). Extensive laboratory characterizations and calibrations indicate the ultrafine and standard CNCs have 50 percent size cutoffs at ≈5 and 13 to 15 nm,

respectively, when operated in the flight configuration. To prevent saturating these instruments in the

highly concentrated aircraft exhaust plumes, sample air is withdrawn from a sampling manifold through

a critical flow orifice and immediately diluted by a factor of 10 to 50 with a concentric flow of filtered

cabin air. This process provides the secondary benefit of allowing the CNCs to be operated at constant

sample pressure and volumetric flow. The instruments are arrayed so that one each of the ultrafine and

standard CNCs share a common inlet which can deliver sample either at cabin temperature (≈20°C) or

heated to 150° to 300°C by passage through a 15-cm heat-tape-wrapped tube. This arrangement allows

quantification of total aerosols >5 and >15 nm along with the number of nonvolatile, presumably soot,

particles and, by difference, volatile aerosols in the same size categories.

Supporting (for determination of aerosol EIs) measurements of carbon dioxide concentrations were

determined with a LI-COR LI-6252 CO2 Analyzer, which is a nondispersive infrared (NDIR) spectrometer. The system used infrared absorption of the 4.26-μm CO2 absorption band. Water is an interference

in this spectral region; therefore, the samples were N2 dried (during dilution) before introduction into

the LI-COR.
4

2.3. NASA Glenn Research Center Group

2.3.1. Participants

From Combustion Branch:

NASA Glenn Research Center

MS 5-10, 21000 Brookpark Rd

Cleveland, OH 44135

Fax: (216) 433-8000

Terry Sanders

E-mail: Terry.M.Sanders@lerc.nasa.gov

Tel.: (216) 433-5849

Krishna Kundu

E-mail: Krishna.P.Kundu@lerc.nasa.gov

Tel.: (216) 433-3939

Tom Vanoverbeke

E-mail: Thomas.J.VanOverbeke@lerc.nasa.gov

Tel.: (216) 433-5867

Clarence Chang

E-mail: Clarence.T.Chang@lerc.nasa.gov

Tel.: (216) 433-8561

Joda Wormhoudt

From High Speed Systems Office:

NASA Glenn Research Center

MS 60-6, 21000 Brookpark Rd

Cleveland, OH 44135

Chowen Wey

E-mail: chowen.c.wey@lerc.nasa.gov

Tel.: (216) 433-8357; Fax: (216) 433-6624

2.3.2. Instrumentation

The GRC Particulate and Gaseous Emissions Measurement System (PAGEMS) extractively samples combustion gases from aircraft gas turbine combustors and engines. Differential mobility analyzers

and condensation nuclei counters are used in tandem to characterize the emissions in terms of particulate total concentration, size distribution, and volatility. A suite of gas analysis equipment measures

CO2, NOx, and SO2 levels in the combustion gases. Data can be collected over a wide range of operating conditions, pressures up to 250 psig, particulates 10 to 500 nm in size, 104 to 1013 particles/cm3, and

gas species down to parts per million levels.
5

2.4. University of Missouri-Rolla Group

2.4.1. Participants

D. E. Hagen

Cloud and Aerosol Sciences Laboratory

University of Missouri-Rolla

Rolla, MO 65401

E-mail: hagen@umr.edu

Tel.: (573) 341-4351; Fax: (573) 341-4891

Max Trueblood

Alfred Hopkins

2.4.2. Instrumentation

The Mobile Aerosol Sampling System (MASS) uses extractive sampling from an aerosol source

and delivers the sample to various aerosol characterizing devices: particle (CN) counters, a laser particle

counter (LPC), and one or more Electrostatic Aerosol Classifiers (EAC). The LPC is used for counting

and sizing large particles by using optical techniques; the EAC is used to size particles at the small end

of the size spectrum. A thermal discriminator can be used to remove volatile material from the particles

before characterization. Our TSI Model 3025 Ultrafine CNC counts particles down to 3 nm in diameter.

Holding tanks are used to capture airborne samples for quasi-real-time size distributions. Size distribution data can be acquired for particles in the diameter size range of 7 nm to 5 μm. Concentrations of

total particles (CN), nonvolatile particles, and particles in specific size bands can be continuously measured. The system operation and data acquisition are computer supported.

Previously, the system has been deployed for airborne sampling missions on the NCAR Sabreliner,

the DLR Dassault Falcon 20E, and the NASA DC-8 and for various ground-based field sampling

projects, including the Glenn PSL and flametube facilities, USAF Phillips Laboratory, McDonnell

Douglas, Air France, Pratt & Whitney, and Arnold Engineering and Development Center.

2.5. University of Minnesota Group

2.5.1. Participants

David Pui

Particle Technology Laboratory

University of Minnesota Twin Cities

100 Church St., SE

Minneapolis, MN 55455

E-mail: dyhpui@tc.umn.edu

Tel.: (612) 625-2537; Fax: (612) 625-6069

Da-ren Chen

Po-Shin Lee

Hee-Siew Han
6

2.5.2. Instrumentation

The UMN research instrumentation consisted of a nanometer aerosol size analyzer (nASA) that was

capable of scanning 30 size channels between 3 and 100 nm in a total time of 3 sec. The analyzer

includes a bipolar charger, an extended-length nanometer differential mobility analyzer, and an

electrometer. This combination of components provides particle size spectra at a scan rate of

0.1 sec/channel. Particle concentrations were measured using a TSI Model 3025 Ultrafine Condensation

Particle Counter. An additional TSI Scanning Mobility Particle Sizer (SMPS) was used during the laboratory phase of the polydispersed aerosol intercomparisons.

3. Field Tests

Tests were conducted sampling LaRC T-38-generated exhaust to evaluate the transfer efficiencies

(particle losses) of the complete particle measuring systems of each participating group, assembled in

their typical configuration for sampling aircraft exhaust. Exhaust from the port engine (J85-GE-5H) of

the LaRC T-38 was sampled at power levels ranging from 48 percent (idle) to 100 percent (full military

power). Typically, the port engine was operated at a specified power for 5 min during which sampling

was conducted. Initially, two sampling probes were tested. One was a water-cooled UMR probe used in

many previous studies (Hagen, Trueblood, and Whitefield 1992; Whitefield and Trueblood 1993).

Exhaust samples drawn through the UMR probe were always diluted by a factor of 7. This probe was

tested in both the water-cooled and water-off modes. The other probe tested was a new LaRC hightemperature probe that was never cooled. It has a 0.03-in. orifice through which the sample was drawn

in from the bulk probe flow. Most bulk flow was vented back to the outside air. Flow through the

orifice occurred because the orifice was maintained at a pressure differential of 22 torr; that is, flow on

the downstream side of the orifice (used to acquire our aerosol samples) was controlled at 22 torr lower

than the main probe inner pressure. This condition resulted in a 2.5 L/min flow of exhaust mixing with

our dry N2 diluent at approximately 740 torr. Essentially two dilution factors were used with the LaRC

probe samples during these tests, primarily dependent upon the probe distance from where the engine

exhaust exited the turbine. Dilution factors during these tarmac tests for the LaRC probe were either

≈90:1 at 1 m or ≈30:1 at 9 m behind the engine. A diluted sample was then fed into a common distribution manifold where participating groups could simultaneously determine the aerosol concentrations

and/or size distributions.

The UMN nASA (Han et al. 2000) actually performs better at high particle concentrations because

it uses an electrometer rather than a condensation particle counter (CPC) for detection. As a consequence, the nASA, with exception to the probe evaluations, drew its samples from the LaRC hightemperature probe ahead of the 0.3-in. orifice and had a separate N2 dilution system, typically using

dilutions ranging from 2:1 to 5:1. Because of the unique speed with which the UMN nASA could

sample the exhaust emissions (30 size channels ranging from 3 to 100 nm in 3 sec), UMN could switch

quickly between sampling the UMR and LaRC probe during the dual probe evaluations. In that manner

we were able to evaluate in-probe transmission losses between the UMR and LaRC systems.

Measurements of carbon dioxide concentrations were made by using a LI-COR LI-6252 CO2

Analyzer, which is an NDIR spectrometer. The system used infrared absorption of the 4.26-μm CO2

absorption band. Because water is an interference in this spectral region, the samples were dried and

diluted before introduction into the LI-COR.
7

4. Results and Discussion

In figure 1(a), the results from the 4, 5, 7, and 8 series of runs, at 80, 100, 80, and 100 percent

engine power (EP), respectively, of exhaust samplings on August 10 and 11 are shown. The UMR and

LaRC probes were positioned 1 m behind the engine for all these runs. These results reflect only

the UMN-determined particle concentrations made by switching back and forth from the UMR

and LaRC probes during specific 5-min EP constant runs. Based on these tests, the LaRC sampling

probe can be seen to have demonstrated better particle transmission characteristics than the UMR probe.

The very notable difference in particle number concentrations (PNCs, in particles/cm3) between the

LaRC and UMR probes for test 2, shown in figure 1(a), is probably misleading, if not spurious. The

average UMN PNC determined for 8 independent samplings at 1 m and at 100 percent engine power

was 10.2 ± 5.5 × 107 particles/cm3

. As can be seen, the PNC determined for the LaRC probe by UMN in

test 2 is more than twice that number. Nevertheless, in all cases observed, the LaRC probe had better

(a) Particle number concentrations.

(b) Geometric mean diameter.

Figure 1. Sampling probe evaluations.

0

4 5 7

Test

8

5

10

15

20

25

× 107

LaRC probe

UMR, H2O off

UMR, H2O on

Particle num

ber concentrations

0

4 5 7

Test

8

5

10

15

20

40

25

30

35 LaRC probe

UMR, H2O off

UMR, H2O on

Geometric

mean diameter, n

m
8

transmission characteristics. These tests also strongly indicated that water cooling diminished particle

transmission for the UMR probe.

In figure 1(b), results from the same runs are presented in terms of geometric mean diameters

(GMD). The LaRC probe also consistently produced results showing smaller GMDs than the UMR

probe; this suggests that fewer small particle losses occurred with this probe. When the UMR probe was

water cooled, the GMDs determined were even larger. The UMR probe suffered some damage during

the last 100 percent EP run made on August 11, and further tests only involved exhaust samplings by

each group utilizing the LaRC probe.

Figure 2 presents the results of a series of runs conducted on August 12, spanning several EPs, ranging from idle (48 percent) to full military power (100 percent). The LaRC probe was located 1 m behind

the engine. In figure 2(a), the total particle concentrations were derived by summing the particle counts

determined for each size bin. Inversion software resulted in the generation of 30 size bins for the UMN

system, 25 size bins for the LaRC system, and an unreported number of size bins for the UMR system.

Since the LaRC 3022 counts all submicron particles >5–6 nm in diameter, and requires no inversion

technique, PNCs obtained from the LaRC 3022 CPC are also plotted in this figure for comparison. For

the data reported by the different groups, about a 50-percent difference typically existed between the

highest and lowest PNCs. The LaRC system consistently produced higher PNCs than the UMN system.

Likewise, the UMR system consistently produced lower PNCs. When the UMN measurement is used as

the standard, then the LaRC/DMA PNCs typically ran about +20 percent above the UMN-determined

concentrations, and the UMR PNCs ran about −30 percent below the UMN-determined PNCs.

In figure 2(b), GMDs are shown for the same data. The error bars represent the geometric standard

deviation and are only presented for the UMN-determined GMDs. The precision, as would be expected,

is less for the smaller GMDs, ranging from about ±20 percent for 10-nm means to about ±7 percent for

30-nm means. GMDs can be seen to noticeably increase at EP greater than 80 percent. In general, reasonably good agreement existed below 85 percent EP. Both the LaRC and UMN measurements indicated a shift to larger particle sizes at >80% percent power.

A similar test series of exhaust sampling runs was conducted at 9 m behind the engine, the results of

which are shown in figure 3. These tests were conducted on August 12 and spanned the same engine

power range except no run was made at 100 percent power. In figure 3(a), particle concentrations are

shown. There appears to be considerably less agreement among the PNCs determined by the participating groups at 9 m than was observed at 1 m. Frequently these differences were as much as a factor of 2

in the determined PNCs. In figure 3(a), the highest particle concentrations are seen to range between 50

and 70 percent power settings. This result was certainly not in accord with our expectations or with the

results observed with the earlier series run at 1 m. The UMN PNCs determined at 9 m were consistently

higher than determinations made by the other groups. This is also counter to the results during the 1 m

series, where the LaRC PNCs were consistently higher than determinations by the other groups. There

are many possible explanations for the seemingly contradictory observations between the 1- and 9-m

runs. We will speculate on how and why some of these contradictory observations might have occurred

at the end of this section.

In figure 3(b), GMDs are shown for the 9-m data. Error bars represent the geometric standard

deviation and are presented only with the UMN-determined GMDs. Note, that outside of a few of the

UMR determinations at the lower power levels, these data seem to project smaller GMDs for particles

collected at 9 m behind the aircraft than for those determined 1 m behind at equivalent engine powers.

Further explanations and implications of this will be addressed after presentation of emission indices

determined for the 1- and 9-m series.
9

Figures 4(a) and (b) show the EIs based on measured CO2 concentrations determined for the 1- and

9-m data, respectively. The overriding assumption here is that essentially all the carbon emissions from

the burned fuel end up as CO2. Thus, if a large difference between levels of background CO2 and

in-plume CO2 concentrations exist, the difference is attributed to production by fuel combustion. Some

rather substantial differences materialize when these data are compared. First, EIs are higher overall

(by a factor of about 3 to 5) in the 9-m data; this strongly suggests that new particle formation may have

occurred over the 1- to 9-m distance/time interval.

In figure 5, mean CO2 concentrations are shown in parts per million by volume (ppmv) for both the

1- and 9-m series at the appropriate engine powers. It is notable that the CO2 concentrations measured

(a) Particle count.

(b) Geometric mean diameter.

Figure 2. Particle concentrations for T-38 at 1 m behind engine.

0

2

4

6

Total particle count

8

10

12

14

40 50 60 70 80

Engine power, percent

90 100 110

UMN

UMR

LaRC

LaRC 3022

× 107

0

5

10

15

20

25

30

35

40 50 60 70

Engine power, percent

80 90 100 110

UMN

UMR

LaRC

Geo

metric 

mean 

diameter, n

m
10

and shown in figure 5 are about a factor of 10 lower for the 9-m series; this suggests that the mixing

of the exhaust with the atmosphere had increased by about a factor of 10 over the 1- to 9-m sampling

interval.

Before any speculations, explanations, or conclusions are formed from these results, some important differences in the particle measuring systems deployed by the different groups must be carefully

considered. The sampling times required to perform a size distribution analysis were significantly

different. The UMN nASA swept the particle size range of 3 to 100 nm in 3 sec. Thus, during a typical

5-min run at a constant aircraft power, UMN was able to perform many analyses. The LaRC system,

however, required 1 min to scan particles between 5 and 250 nm. This typically resulted in no more than

four analyses being done at each engine power setting. The UMR system scan rate was less important

because UMR filled a 40-L tank, and then withdrew a sample from this tank for their DMA analyses.

The fill time for the tank determined the sampling time interval. If the engine exhausted constant

concentrations and sizes of particles at a given engine power setting, the different sampling time

requirements of the systems should present no problem. We believe that the output from the engine was

(a) Particle count.

(b) Geometric mean diameter.

Figure 3. Particle concentrations for T-38 at 9 m behind engine.

0

2

4

6

8

10

12

14

16

18

20

40 50 60 70

Engine power, percent

80 90 100

UMN

UMR

LaRC 3025

LaRC 3022

× 106

Total particle co

unt

0

5

10

15

20

25

UMN

UMR

LaRC

40 50 60 70

Engine power, percent

80 90 100

Geo

metric 

mean 

diameter, n

m
11

(a) 1 m.

(b) 9 m.

Figure 4. Emission indices determined behind engine.

Figure 5. Mean CO2 concentrations at 1 and 9 m behind engine.

0

1

2

3

4

5

6

7

8

40 50 60 70 80

Engine power, percent

90 100 110

UMN

UMR

LaRC

LaRC 3022

EI

× 1015

0

2

4

6

8

10

12

14

16

18

UMN

UMR

LaRC

LaRC 3022

40 50 60 70 80

Engine power, percent

90 100

EI

× 1015

102

103

104

105

40 50 60 70 80

Engine power, percent

90 100 110

1 m

9 m

CO2 concentration, pp

m

v
12

very nearly constant at a given power setting. We observed little change in measured CO2 concentrations during 5-min constant power runs made 1 m behind the engine, regardless of wind conditions.

However, although the exhaust plume CO2 was relatively insensitive to crosswinds at 1 m, strong

fluctuating crosswinds would move the centerline of the exhaust plume back and forth across the

probe at 9 m. The proof of which was the resulting fluctuations of CO2 concentrations measured during

the 5-min runs. Since the exhaust samples analyzed by each group were from the same probe and the

same instruments had compared well in the laboratory phase of these intercomparisons (Cofer et al.

2001), a likely contributor to the larger discrepancies observed at 9 m was the combination of centerline

plume movement and the different response times of the systems. Behavior such as that just described

would impact 1-min measurements much more than 3-sec measurements.

When the 1- and 9-m runs are compared, some rather surprising observations can be made. First, a

large increase in PNCs (fig. 2(a)) at EP ≥ 90 percent at 1 m occurs. Although there is no 100-percent EP

run at 9 m, the suggestion of such a trend at 95-percent EP is much less conclusive. Second, when PNCs

of the 9-m runs are multiplied by 10 (the atmospheric dispersion/dilution based on the CO2 concentrations shown in fig. 5), the 9-m concentrations exceed the 1-m concentrations. Third, when the 1- and

9-m runs at EP < 85 percent are examined, the 9-m runs actually appear to have higher PNCs, totally

counter to the 1-m results. Likewise, when the EIs determined for the 1- and 9-m runs are compared

(figs. 4(a) and (b)), the same trends are observed.

An attempt is now made to explain how some of the seemingly contradictory PNC determinations

made between the runs at 1 and 9 m might have occurred. It is very clear (fig. 2(a)) that at 1 m and at

EPs of 55 to 85 percent, PCNs do not change significantly and equally clear that at EP > 85 percent,

PCNs increase dramatically. When the corresponding series of EP runs are viewed at 9 m (fig. 3(a)),

PNCs appear to be higher at percent, systematically decrease at EPs between 70 and 80 percent, and then systematically increase again at EPs between 80 and 95 percent. We now speculate on

several factors that could help explain the differences in the observations made at 1 and 9 m. Exhaust

velocity and temperature will vary with EP at any distance from the engine. At idle, exhaust gas temperature is about 520°C. It then drops steadily to about 405°C at 80 percent EP. The temperature then progressively increases to about 640°C at 100 percent EP. Exhaust gas velocity, however, continually

increases with increasing EP. Dilution resulting from entrainment of ambient air increases substantially

as distance from the engine increases as well. In our case, the plume sampled at 9 m had diluted approximately tenfold over that at 1 m. It is our speculation that at 1 m the exhaust plume temperatures were

always above some threshold value limiting new particle formation. Thus, essentially all particles were

soot carbon. Nine meters, however, may be in a transition region for particle formation. The combination of cooling and the forward velocity of the exhaust plume may have generated some interesting

results. Because the rate of exhaust sample arrival time at the probe progressively shortens as EP

increases and the temperature increases, particularly above 80 percent EP, nonsoot particle formation

may have been diminished relative to new particle formation at EP > 80 percent. The increase in PNC

seen in figure 3(a) at EP > 90 percent follows the behavior of the 1-m series of runs.

When the GMDs for the two series of runs are examined, placing particular emphasis on the UMN

nASA measurement, the GMDs for each corresponding EP can be seen to be smaller for the 9-m runs;

this is also consistent with the new particle formation speculation. Both the higher PNC EIs and the

smaller GMD observed at 9 m suggest nonsoot small particle formation at 9 m. We believe this nonsoot

fraction of new particles was relatively absent at 1 m.

Finally, when the EIs determined behind the LaRC T-38 in these tarmac experiments are compared

with prior (Anderson, Cofer, and Brunke 1998; Anderson, Cofer, and Hudgins 1998) EI determinations

EP 70 ≤
13

made behind the LaRC T-38 in flight at cruise altitudes, some interesting observations can also

be made. First, based on temperature considerations, we assume that the EIs determined 1 m behind

the LaRC T-38 essentially include no volatile fraction. The nonvolatile EIs at 1 m range from about

2 × 1015 to 6 × 1015 particles generated per kilogram of fuel burned over the interval from 48 to

100 percent EP. The nonvolatile EIs determined several kilometers behind the LaRC T-38 in flight

(Anderson, Cofer, and Brunke 1998) ranged from 0.4 × 1016 to 2 × 1016 particles/kg, over an interval of

65 to 100 percent. However, on the average, the EIs determined in flight were roughly twice as high. It

does not seem reasonable that any new soot carbon would form beyond 1 m aft of the turbine exhaust.

The heater during the in-flight determinations was operated at 150°C, however, and may not have evaporated the larger volatile sulfate particles that formed in the plume. In addition, other nonvolatiles, such

as sulfate salts, might be produced from the exhaust interacting with the atmosphere. The fact that the

particle EIs roughly double going from 1 to 9 m behind the turbine exhaust certainly suggests potential

new particle formation.

5. References

Anderson, B. E.; Cofer, W. R.; and Brunke, K. E. 1998: Airborne Observations of Aircraft Aerosol Emissions:

1—Total Nonvolatile Particle Emission Indices. Geophys. Res. Lett., vol. 25, no. 10, pp. 1689–1692.

Anderson, B. E.; Cofer, W. R.; and Hudgins, C. H. 1998: Airborne Observations of Aircraft Aerosol Emissions:

2—Factors Controlling Volatile Particle Production. Geophys. Res. Lett., vol. 25, no. 10, pp. 1693–1696.

Anderson, B. E.; Cofer, W. R.; Crawford, J.; Gregory, G. L.; Vay, S. A.; Brunke, K. E.; Konda, Y.; Koike, M.:

Schlager, H.: Baughcum, S. L., Jensen, E.; Zhao, Yongjing; and Kita, Kazuyuki 1999: An Assessment of Aircraft as a Source of Particles to the Upper Troposphere. Geophys. Res. Lett., vol. 26, no. 20, pp. 3069–3072.

Anderson, Bruce E.; Cofer, W. Randy, III; and McDougal, David S. 1999: Air Force F-16 Aircraft Engine Aerosol

Emissions Under Cruise Altitude Conditions. NASA/TM-1999-209102.

Ball, S. M.; Hanson, D. R.; and McMurry, P. H. 1999: Laboratory Studies of Particle Nucleation: Initial Results for

H2SO4, H2O, and NH3 Vapors. J. Geophys. Res.—Atmospheres, vol. 104, no. 19, p. 23709.

Baughcum, Steven L.; Sutkus, Donald J.; and Henderson, Stephen C. 1998: Year 2015 Aircraft Emission Scenario

for Scheduled Air Traffic. NASA/CR-1998-207638.

Boeing Commercial Airplane Group 1996: Current Market Outlook, p. 15. (Available through Tim Meskill,

Project Director, Boeing, P.O. Box 3707, MS 76-15, Seattle, Washington 98124.)

Brock, C. A.; Schroeder, F.; Kaercher, B.; Petzold, A.; Busen, R.; and Fiebig, M. 2000: Ultrafine Particle Size

Distributions Measured in Aircraft Exhaust Plumes. J. Geophys. Res., vol. 105, pp. 26,555–26,567.

Cofer, W. R., III; Anderson, B. E.; and Bagwell, D. R. 1998: Calibration and Demonstration of a Condensation

Nuclei Counting System for Airborne Measurements of Aircraft Exhausted Particles. Atmos. Environ., vol. 32,

no. 2, pp. 169–177.

Cofer, W. Randy, III: Anderson, Bruce E.; Connors, V. S.; Wey, C. C.; Sanders, T.; Twohy, C.; Brock, C. A.;

Winstead, E. L.; Pui, D.; Chen, Da-ren; Hagen, D. E.; and Whitefield, P. 2001: NASA’s Atmospheric Effects of

Aviation Project—Results of the August 1999 Aerosol Measurement Intercomparison Workshop, Laboratory

Phase. NASA/TM-2001-210829.

Fahey, D. W.; Keim, E. R.; and Chan, K. R. 1995: Emission Measurements of the Concorde Supersonic Aircraft in

the Lower Stratosphere. Science, vol. 270, no. 5233, pp. 70–74.

Friedl, Randall R., ed. 1997: Atmospheric Effects of Subsonic Aircraft: Interim Assessment Report of the Advanced

Subsonic Technology Program. NASA RP-1400.

Hagen, D. E.; Trueblood, M. B.; and Whitefield, P. D. 1992: A Field Sampling of Jet Exhaust Aerosols. Part. Sci.

& Technol., vol. 10, no. 1–2, pp. 53–63.
14

Hagen, D.; Whitefield, P.; Paladino, J.; Trueblood, M.; and Lilenfeld, H. 1998: Particulate Sizing and Emission

Indices for Jet Engine Exhaust Sampled at Cruise. Geophys. Res. Lett., vol. 25, no. 10, pp. 1681–1684.

Han, Hee-Siew; Chen, Da-Ren; Pui, David Y. H.; and Anderson, Bruce E. 2000: A Nanometer Aerosol Size Analyzer (nASA) for Rapid Measurement of High-Concentration Size Distributions, J. Nanoparticle Res., vol. 2,

no. 1, pp. 43–52.

Karcher, B.; and Fahey, D. W. 1997: The Role of Sulfur Emission in Volatile Particle Formation in Jet Aircraft

Exhaust Plumes. Geophys. Res. Lett., vol. 24, no. 4, pp. 389–392.

Miake-Lye, R. C.; Anderson, B. E.; Cofer, W. R.; Wallio, H. A.; Nowicki, G. D.; Ballenthin, J. O.; Hunton, D. E.;

Knighton, W. B.; Miller, T. M.; Seeley, J. V.; and Viggiano, A. A. 1998: SOx Oxidation and Volatile Aerosol in

Aircraft Exhaust Plumes Depend on Fuel Sulfur Content. Geophys. Res. Lett., vol. 25, no. 10, pp. 1677–1680.

Pueschel, R. F.; Blake, D. F.; Snetsinger, K. G.; Hansen, A. D. A.; Verma, S.; and Kato, K. 1992: Black Carbon

(Soot) Aerosol in the Lower Stratosphere and Upper Troposphere. Geophys. Res. Lett, vol. 19, no. 16,

pp. 1659–1662.

Twohy, C. H.; Gandrud, B.; and Weinheimer, A. 1998: Particle Production Near Cirrus Anvil Outflow in the Upper

Troposphere. Paper presented at the Seventeenth Annual Conference, American Association for Aerosol

Research (Cincinnati, Ohio).

Wey, C. C.; Wey, C.; Dicki, D. J.; Loos, K. H.; Noss, D. E.; Hagen, D. E.; Whitefield, P. D.; Trueblood, M. B.;

Wilson, M. E.; Olson, D.; Ballenthin, J. O.; Miller, T. M.; Viggiano, A. A.; Wormhoudt, J.; Berkoff, T.; and

Miake-Lye, R. C. 1998: Engine Gaseous, Aerosol Precursor and Particulate at Simulated Flight Altitude

Conditions. NASA/TM-1998-208509.

Whitefield, P. D.; and Trueblood, M. B. 1993: Size and Hydration Characteristics of Laboratory Simulated Jet

Engine Combustion Aerosols. Part. Sci. & Technol., vol. 11, nos. 1–2, pp. 25–36.

Whitefield, P. D.; and Hagen, D. E. 1995: Particulates and Aerosol Sampling From Combustor Rigs Using the

UMR Mobile Aerosol Sampling System (MASS). AIAA-95-0111.
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REPORT DOCUMENTATION PAGE

October 2001 Technical Memorandum

NASA’s Atmospheric Effects of Aviation Project

Results of the August 1999 Aerosol Measurement Intercomparison Workshop,

T-38 Aircraft Sampling Phase

WU 622-63-10-70

W. Randy Cofer III, Bruce E. Anderson, V. S. Connors, C. C. Wey,

T. Sanders, E. L. Winstead, D. Pui, Da-ren Chen, D. E. Hagen, and

P. Whitefield

L-18095

NASA/TM-2001-211226

Cofer, Anderson, and Connors: Langley Research Center, Hampton, VA; Wey and Sanders: Glenn Research Center, Cleveland, OH;

Winstead: SAIC, Hampton, VA; Pui and Chen: Univ. of Minnesota, Twin Cities, Minneapolis, MN; Hagen and Whitefield: Univ. of

Missouri-Rolla, Rolla, MO.

During August 1–14, 1999, NASA’s Atmospheric Effects of Aviation Project (AEAP) convened a workshop at the

NASA Langley Research Center to try to determine why such a wide variation in aerosol emissions indices and

chemical and physical properties has been reported by various independent AEAP-supported research teams trying

to characterize the exhaust emissions of subsonic commercial aircraft. This workshop was divided into two phases,

a laboratory phase and a field phase. The laboratory phase consisted of supplying known particle number densities

(concentrations) and particle size distributions to a common manifold for the participating research teams to

sample and analyze. The field phase was conducted on an aircraft run-up pad. Participating teams actually sampled

aircraft exhaust generated by a Langley T-38 Talon aircraft at 1 and 9 m behind the engine at engine powers ranging

from 48 to 100 percent. Results from the laboratory phase of this intercomparison workshop are reported in this

paper.

Aircraft exhaust; Aerosol measurements; Aircraft emissions 21

NASA Langley Research Center

Hampton, VA 23681-2199

National Aeronautics and Space Administration

Washington, DC 20546-0001

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