Environ. Sci. Technol. 2007, 41, 6828-6835

Role of Lubrication Oil in Particulate

Emissions from a Hydrogen-Powered

Internal Combustion Engine

ARTHUR L . MILLER,*

* Corresponding author phone: (509) 354-8028; fax: (509) 354­

8099; e-mail: ALMiller@cdc.gov.

, †

MATTHEW C . HABJAN, †,§

† National Institute for Occupational Safety and Health.

§ Gonzaga University.
 

CHRISTOPHER B . STIPE, ‡

‡ Seattle University.
 

AND

GILBERT G . AHLSTRAND |

| University of Minnesota.
 

National Institute for Occupational Safety and Health,
 

Spokane, Washington 99207 Mechanical Engineering
 

Department, Seattle University, Seattle, Washington 98122,
 

Mechanical Engineering Department, Gonzaga University,
 

Spokane, Washington 99258, and College of Biological
 

Sciences Imaging Center, University of Minnesota,
 

St. Paul, Minnesota 55108
 

Recent studies suggest that trace metals emitted by

internal combustion engines are derived mainly from

combustion of lubrication oil. This hypothesis was examined

by investigation of the formation of particulate matter

emitted from an internal combustion engine in the absence

of fuel-derived soot. Emissions from a modified CAT 3304

diesel engine fueled with hydrogen gas were characterized.

The role of organic carbon and metals from lubrication

oil on particle formation was investigated under selected

engine conditions. The engine produced exhaust aerosol with

log normal-size distributions and particle concentrations

between 105 and 107 cm-3 with geometric mean diameters

from 18 to 31 nm. The particles contained organic

carbon, little or no elemental carbon, and a much larger

percentage of metals than particles from diesel engines. The

maximum total carbon emission rate was estimated at

1.08 g h-1

, which is much lower than the emission rate of

the original diesel engine. There was also evidence that

less volatile elements, such as iron, self-nucleated to form

nanoparticles, some of which survive the coagulation

process.

1. Introduction

Evidence suggests that particulate matter produced in

internal combustion engines results in harmful health effects

(1, 2). The causal mechanisms have not been clearly

identified, anditispossible thattracemetals ormetal-bearing

ultrafines may play a role (3, 4). Therefore, it is critical to

understand the origin and fate of metals and the physical

processes related to nanoparticle formation in engines.

Previous research focused on the origin and fate of metals

during diesel engine combustion (5, 6). This study expands

on that research by generating particles under conditions

where soot availability is very low.

It is well documented that internal combustion engines

produce soot particles during the combustion process (7, 8).

FIGURE 1. Hydrogen-powered vehicle and experimental setup.

Soot particles provide significant surface area forinteraction

with other combustion byproducts, including organic compounds, ash, and metals (9, 10). Earlier studies of engine

emissions often focused on the relative amount of elemental

and organic carbon emitted because both are derived from

the combustion of hydrocarbon fuels and oils.More recently,

studies have focused on the contribution of lubrication oil

to the particle-formation process (11) and, in particular, the

role of lubrication oil additives in particle formation (5, 12).

Under normal diesel engine operation, trace metals are

vaporized and adsorbed or condensed onto the surface of

soot particles (5). The origin of the metals may be from trace

metals in the fuel or from the metallic fuel additives in the

fuel used for diesel particulate filter regeneration. However,

more typically,the metals in exhaust particles originate from

lubrication oil that is spread onto the cylinder walls by the

piston rings or that enters the combustion chamber via

reverse blow-by of the rings (13). This is evidenced by data

showing measurable levels of metallic lube oil additives in

bulk diesel particulate matter (DPM) samples (14). Other

recent data demonstrate a correlation between the mass of

calcium and organic carbon (OC)in bulk particulate samples

because of their common origin in the lubrication oil (15).

The latter is consistent with previous diesel particulate data

showing that OC is derived from hydrocarbons associated

with lubrication oil (11). In diesel engines, the combustion

of lubrication oil contributes to particle formation by

increasing the amount of semivolatile hydrocarbon species

available fornucleationuponexiting the tailpipe.Inaddition,

the (metallic) ash residues combine with soot particles, and

in some cases where the metal-to-carbon ratio is high, metal

vapors self-nucleate inside ofthe engine to form a population

of metal-rich nanoparticles (5, 16).

The primary goal of this study was to investigate the

formation of combustion-generated particles derived from

lubrication oil in the absence of fuel-produced soot. This

was accomplished by an examination of the emissions from

a hydrogen-fueled internal combustion engine because it

does not produce fuel-derived soot during the combustion

process. This study’s findings may increase current knowledge about the role of lubrication oil in particle-formation

dynamics as engine technology improves andcleanerinternal

combustionengines aredeveloped.The results arenotmeant

to be used in direct comparison with other engine types but

rathertodemonstrate the formationofparticlesderivedsolely

from lubrication oil. The secondary goal was to study how
the number concentration and size distribution of the

lubrication-oil-derived particles depend on the engine loading condition. This goal is of particular significance because,

in2008,theMining Safety andHealthAdministration(MSHA)

plans to phase in a final particulate matter rule limiting

exposure of metal and nonmetal underground miners to 160

μg m-3 of total carbon (TC) (17). In addition, the current

regulated limit for particulate matter emission by any

underground source in underground coal mines is 2.5 g h-1

(18).Presently,many approaches, includingparticulate filters

and low sulfur fuels, are being considered to achieve the

regulated limits; this study investigated the viability of

hydrogen-powered engines to achieve the regulated levels

of particulate matter.

2. Experimental Procedure

The experiment was conducted using a CAT 3304 engine

which had been modified to burn hydrogen gas.In its normal

configuration,this engine is a 7-liter, 85-HP, 4-cylinder diesel

engine. Modifications included equipping the engine with

a spark ignitionsystem, lowering the compressionratio,turbo

charging, and adding an aftercooler and a parallel fuelinduction system (19). The engine was installed in an EIMCO

model 975mineutility vehicle calledtheZeroEmissionUtility

Solution or “ZEUS” (20). Recently, the ZEUS was employed

in the first demonstration of a hydrogen-fueled internal

combustion engine vehicle in an underground mine at the

Stillwater Mine in Nye, Montana (21, 22).

During our study, emissions were monitored underthree

engine-operating conditions: low idle,torque stall, and high

load. To attain the high load condition, the vehicle was run

ona chassisdynamometer atwheel loadingof 28hp, although

the actual engine load was greater because of differential

and transmission friction. The low idle and torque stall tests

were conducted without the aid of the dynamometer to

simulate typical conditions forfield testing ofmining vehicles

(23, 24). The torque stall was initiated by shifting the vehicle

into high gear, setting the brakes and depressing the

acceleration pedal manually to maintain 1500 rpm.

For all tests, a portion of the raw exhaust was cooled and

diluted using an ejector-type dilutor (25). The dilution ratio

was cold-flowcalibratedtobe approximately 10:1.Thediluted

aerosol was routed to a multiport sampler (Figure 1), which

provided a common source of well-mixed and aged aerosol

for concurrentmeasurementswithmultiple instruments.The

multiport sampler consisted of a baffle to spread and mix

the incoming air, a plenum (sampling) chamber, and a

vacuum chamber. The two chambers were separated by a

sealing plate in which multiple critical orifices were installed

to provide controlled flow forinstruments and filter samples.

Additional sampling ports were located in the walls of the

plenum. A gauge was connected to the vacuum chamber

and monitored to ensure critical flow through the orifices,

while the aerosol temperature was monitored at both the

tailpipe and in the multiport sampler. The residence time of

the particles in the sampling system was approximately

15 s.

2.1. Measurement and Analysis Methods. The emitted

particulate matter was measured and characterized using

four measurement approaches, based on the following

characteristics of the particulate matter: particle number

concentrations and size distributions, elemental and organic

carbon concentrations, particle morphology, and particle

elemental chemical composition. The instrument setup is

depicted in Figure 1. The instrumentation and the purpose

of each measurement technique are described in the following sections.

2.1.1. Particle Number Concentrations and Size Distributions. Number-weighted particle size distributions were

measured using a fast mobility particle sizer (FMPS Model

3091, TSIInc, St. Paul, MN). The FMPS incorporates multiple

electrometers along the length of a differential mobility

analyzer (DMA) (26). The DMA size-selects the particles

according toelectricmobilitydiameter, andthe electrometers

measure the number concentration at each size simultaneously. A particle size distribution was obtained every

second during the tests within the 5.6-560 nm range. The

FMPS inlet was connected to the multiport sampler, and it

extracted a flow of 10 L min-1 continuously. A cyclone with

a designed cutoff of 1.0 μmwas installed atthe inletto remove

particles that were much larger than the range of detection.

2.1.2. Elemental and OrganicCarbonConcentrations. The

mass concentration of elemental and organic carbon (EC

andOC)inthe exhaust aerosolwasderivedfromfilter samples

using theNIOSHstandardmethod5040 (27),modifiedslightly

with respect to sampling flow rate. Samples were collected

on 37 mm prebaked quartz filters mounted in plastic

cassettes. To maximize the mass of particulate for the

relatively short tests (approximately 20-30 min), the flow

rate through the filters was set at 22.1 L min-1 for all tests,

using a critical orifice in line with the filter cassette in the

multiport sampler. A filter sample was collected for each

test, and the values for EC and OC were derived from

analytical results (Table 1).

TABLE 1. Summary of Number Concentration (NC) and Particle

Size for Three Engine Conditions

geometric

mean exhaust mean

mean NC

(particles cm-1)

RSD

(%)

mobility

diameter

(nm)

gas

temp

(°C)

engine

speed

(RPM)

EC

(mg m-3)

OC

(mg m-3)

low idle 2.5 × 105 4.3 31 150 800 0.027 0.404

torque

stall

3.5 × 106 23.7 19 315 1500 0.173 1.55

high

load

7.7 × 106 12.1 18 345 1900 0.310 2.87

2.1.3. Particle Morphology. Particle morphologies were

determined using transmission electron microscopy (TEM)

to image samples collected on 3 mm diameter, silicone

monoxide-filmed grids. Most samples were collected using

an electrostatic precipitator (ESP), which was built in-house

and modeled after the Rochester design (28). The ESP was

connected to the multiport sampler, and the flow was

supplied by a GilAir5 pump (Sensidyne Inc, Clearwater, FL)

at approximately 1 L min-1. Samples collected in this way

offer a representative picture of the various particle morphologies and their relative frequency of occurrence, albeit

biased toward the larger sizes because ofthe size-dependent

charging efficiency of the ESP. In addition, samples were

also collected by attaching TEM grids onto the latter five

stages of a 13-stage micro-orifice uniform deposition impactor (NanoMOUDI, MSP, Shoreview, MN).

2.1.4. Particle Elemental Chemical Composition. The ESP

and MOUDI samples were also used to investigate the

elemental composition of the various particle types using a

combination of TEM and energy-dispersive spectroscopy

(EDS). The following protocol, designed to be performed

manually by a microscopist, was developed to qualitatively

characterize the aerosol from a TEM grid sample: (1) Select

areas of the TEM grid and tabulate the size and morphology

of all particles in the designated area. (2) Identify “typical”

particle morphologies using this tabulated information. (3)

Estimate/count the prevalence of each particle type. (4)

Analyze several particles of each type using EDS and combine

the spectra using a qualitative technique (see section 3.4) to

approximate the elemental compositionfor eachmorphology

type. (5) Choose a typical particle of each type and create a

high magnification TEM image and an EDS spectrum for

that particle.
It is important to note that this protocol is not meant to

be robustly quantitative; rather, it is a simple and quick

qualitative characterization of the sampled aerosol. All grid

samples were analyzed using a FEI CM12 TEM with EDAX

Power MX EDS capability. Background-corrected spectra

were obtained by subtraction of the substrate support film

background spectra from particle spectra.

3. Results and Discussion

The results of the analyses are presented here in four

subsections that correspond to the four analysis methods

outlined in the previous sections. The test results for

each of the three engine conditions are summarized in

Table 1.

3.1. Particle Number Concentrations and Size Distributions. Low Idle. At the low idle condition, the engine

emitted 2.5 × 105 particles cm-3 (the RSD calculated

from multiple FMPS measurements was (4.3%), with a

geometric mean mobility diameter of 31 nm (Figure 2a and

b). The number concentrations measured by the FMPS

were corrected for the 10:1 dilution of the engine exhaust.

FIGURE 2. Three engine conditions were evaluated: low idle, torque stall, and high load at 28 hp. (Note that actual engine load is greater

because of differential and transmission friction.) (a) Representative particle size distributions for each condition. (b)Number concentrations

over time (after 10 min engine warm-up) for each condition.

The size distribution for the low idle condition is given in

Figure 2a, and the time-dependent number concentration

for the low idle engine condition is shown in Figure 2b. The

average number concentrations and mean electric mobility

diameters for all engine conditions are given in Table 1. The

diameter, number concentration, and mass concentration

of particles for all engine loading conditions are significantly

smaller than for a diesel engine, mainly because of the

lack of soot agglomerates and fuel-derived particles. However, the number concentration of particles is still substantial.

3.1.1. Torque Stall. Particle concentrations for the torque

stall condition (Figure 2b) were less stable than the other

cases, which was partly caused by the inability ofthe operator

to hold the throttle constant. Normally, an engine torque

stall is performed at the maximum throttle setting, but

because this engine has a governor-triggered safety switch

to prevent excess revving, the researchers attempted to hold

the throttle pedal manually at an intermediate setting to

maintain the engine at 1500 rpm. The average number

concentration of particles produced by this condition was

3.5 × 106 particles cm-3 (RSD ) 23.7%) with a geometric

mean electric mobility diameter of 19 nm.
FIGURE 3. (a) TEM image of grid sample shows the range in size and type of particles. (b) Histograms of average rated spectra for four

different particle types. The y-axis represents the qualitative rating scheme described in the text.

FIGURE 4. Agglomerate particle: (a) TEM image and (b) EDS spectrum of this particle showing high C content.

FIGURE 5. Dense sphere particle: (a) TEM image and (b) EDS spectrum of this particle showing metals derived from lubrication oil

additives.

3.1.2. High Load. The average number concentration for

the high load conditions was 7.7 × 106 particles cm-3 (RSD

) 12.1%) (Figure 2b), and the geometric mean electric

mobility diameter was approximately 18 nm. The particle

concentrations emitted under engine load were more scattered than for the low idle condition. The greater deviation

at high load was most likely the result of the unsteadiness

of the engine operation on the dynamometer. Since the

throttle was controlled manually with a foot pedal, there

were variations overtime inthe engine rpm(and thus applied
load) and exhaust gas temperature, which both affect particle

concentration.

3.2. Elemental and OrganicCarbonConcentrations. No

fuel-derived soot forms during hydrogen combustion; therefore, the mass concentration of EC measured in the exhaust

was relatively low (Table 1). This was expected because the

formation of primary particles of elemental carbon (soot)

typically takes place inside a flame where carbon-based fuels

are burned (29). In contrast, the carbon measured in our

tests was concluded to be derived from the lubrication oil.

Furthermore, the EC/OC ratio increased at high load,

suggesting that the higher temperatures in the cylinder

resulted in the more complete breakdown ofthe carbon from

the oil. The evidence that carbon from the lubrication oil is

mostly emitted as OC further confirmed the work of Sakurai

et al. (11). Emissions of organic carbon were comparable to

a diesel engine of similar size (30), while elemental carbon

emissions were extremely low.

The maximum total carbon emission rate for this engine

was 1.08 g h-1 at the high load condition, assuming a

volumetric engine efficiency of 85%. This is much smaller

than the 30 g h-1 of diesel particulate matter emitted from

the original CAT 3304 diesel engine and is also less than the

2.5 g h-1 limit noted in the recent MSHA regulation (18).

3.3. Particle Morphology. To study the morphology and

chemical composition of particles emitted by this engine,

TEM/EDS analysis was performed on samples from the three

different engine conditions: low idle, torque stall, and high

load. For all cases, the morphology ranged widely, as seen

in a typical sample collected on the tenth MOUDI stage,

whichcollectsparticleswithaerodynamicdiametersbetween

56 and 100 nm (Figure 3a).

By observing the morphology of numerous particles with

TEM, we identified five types of particles which were

distinguished by their morphological and chemical characteristics: (1) agglomerates, (2) optically dense spheres, (3)

optically less-dense spheres, (4) core-shell particles, and (5)

nanoparticles.

3.4. Particle Elemental Chemical Composition. EDS

analysis determined the elemental chemical composition of

the five commonparticle types identifiedby theTEManalysis.

The EDS spectra varied from particle to particle, but there

were apparent trends. To elucidate these trends and better

classify the particle types, a method was designed to

qualitatively tabulate the relative abundance ofthe elements

in each spectrum. The method is a simple empirical rating

of the intensity of the spectral X-ray peaks of the detected

elements.Thismethodwas chosenbecause,whenusingEDS,

it is difficult to obtain accurate quantitative analyses (e.g.,

percentage composition by weight of particles of varying

sizes, morphologies, densities, and elemental composition)

without appropriate standards for the elements of interest.

FIGURE 6. Less-dense sphere particle: (a) TEM image and (b) EDS spectrum of this particle showing trace metals from lubrication oil.

FIGURE 7. Core-shell particle with dense core: (a) TEM image and (b) EDS spectrum showing Fe, Ca, and other metals similar to dense

spheres.
Each particle analysis relied on standardized TEM operating conditions.The spectralpeak intensities (peakheights

or X-ray counts) above local background per 60 s analysis

time were assigned one of four values. Each was judged to

be trace (0-25 counts), low (25-50), medium (50-100), or

high (>100) and then assigned a value of 1, 2, 3, or 4,

respectively. Count values were determined by inspecting

each spectrum on the EDS system monitorimmediately after

acquisition. The count values were tabulated, and the EDS

spectra and photographic images ofrepresentative particles

were recorded.In each morphological class,the count values

for each element were summed and divided by the number

of particles in that class to yield an average peak intensity

value ranging from 0 to 4 for each element. The values were

then plotted on a bar graph representing the average rated

spectrum(ARS)observedfor eachmorphological class (Figure

3b). Sixty-four particles were included in this tabulation: 23

agglomerates, 10 core-shell spheres, 17 less-dense spheres,

and14dense spheres.The “nano”-typeparticleswereomitted

from Figure 3b because of the difficulty in detection/

speciation caused by their small mass. Many of the most

common metal species in the averaged rated spectra (Figure

3b) were also evident in the analysis of the lubrication oil

(Table 2). This strongly suggests that these particles were

derived from the lubrication oil.

TABLE 2. Summary of Certified ICP Analysis of the Main

Metals Present in the Lubrication Oil

metal concentration (ppm)

iron 19

lead 6

copper

silicon

18

6

sodium 7

boron 32

zinc 877

phosphorus

calcium

1118

1871

magnesium

molybdenum

72

5

3.5. Detailed Descriptions of Particle Types. The following sections provide detailed descriptions of identifiable

particle types based on the TEM/EDS analysis. For all of the

EDS spectra shown in the following figures, the Si and O

peaks originating from the support film were removed by

subtractionof a spectrumtakenfromthe SiOfilm(normalized

to each spectra’s Si peak), and any residual O is assumed to

be from the particle. The copper peaks produced from the

support grid by electron scattering were likewise subtracted

from particle spectra.

3.5.1. Agglomerates. EDS analysis showed that typical

agglomerate particles (Figure 4) were mainly carbonaceous

and often had traces of elements such as Na, P, K, S, Sn, Fe,

and Zn. The particles of this type were in the 100-400 nm

size range. The morphology and elemental composition of

these particles bearresemblance to diesel soot(5), suggesting

that they are derived in part from the agglomeration of

primary particles of EC(soot). Such particles were infrequent

in the aerosol from the hydrogen-fueled engine, in contrast

to diesel engine combustion, where they are by far the most

common particle type (6).

3.5.2. Dense Spheres. Spherical particles in the size range

of about 30-300 nm (Figure 5) were observed frequently.

The spheres appeared very dark in TEM images because of

their high density, which mainly consisted of metals, as

indicated by the spectrum in Figure 5b. The metals were

typically of the kind derived from lubrication oil, that is, Ca,

P, Zn, and Mg (Table 2). The high density is likely caused by

theCa content,whichis large comparedtothe signalobtained

from less-dense spheres described insection3.5.3.The dense

spherical particles are likely created from lubrication oil

constituents, but the particle formation pathway is unclear.

One possibility is thatthey are residue particles created from

unburned oil droplets heated enough to evaporate most of

the hydrocarbon species. Another possibility is that they

contain cores of self-nucleated nonvolatile species, like Fe

and Ca, coated with other more volatile species which

adsorbed or condensed onto surfaces as the combustion

products cooled in the exhaust manifold.

3.5.3. Less-Dense Spheres. Particle spheres with a lower

optical density than those described in the previous section

were also commonly observed (Figure 6). These particles

were similarin shape and size to the optically dense particles

but appeared to be lighter in color in the TEM image, which

suggests more transmission of the electron beam through

the particle during imaging. The EDS spectra illustrated that

these particles contained metals from the lubrication oil,

similar to the more-dense spheres discussed previously.

However, the less-dense spheres had a noticeably lower Ca

content, which may have contributed to the apparent lower

density. It is also notable that many of these particles

contained extremely small “nuggets” of dense material.

FIGURE 8. Nanoparticle: (a) TEM image and (b) EDS spectrum showing C and Fe peaks.
3.5.4.Core-Shell Particles. Some particles were composed

of a dense core, high in Fe, Ca, or both, surrounded by a

less-dense shell (Figure 7). This suggests that the particles

mayhave formedwhenvaporizedoilresidue condensedonto

previously nucleated cores as the exhaust gases cooled in

the expansion stroke orthe exhaust system. This is supported

by the observation thatthe halo around the particle in Figure

7a was susceptible to vaporization upon interaction with the

electron beam. The EDS analysis indicated that the lowerdensity material surrounding such cores was relatively high

in the lighter elements derived from lube oil additives (P, K,

Mg, Zn, Na), while the cores were generally high in Fe or Ca.

3.5.5. Nanoparticles. Particles ranging in size from 5 to 50

nm were classified as nanoparticles. The nanoparticles

observed were usually spherical (Figure 8) and composed

mainly of Fe (Figure 8b) or a combination of C and Fe. The

Fe-rich nanoparticles likely self-nucleated early in the postcombustion process while the temperature was still high.

The more carbonaceous nanoparticles likely originate from

homogeneous nucleation of volatile hydrocarbon vapors as

they exit the engine. These processes have been investigated

and described in detail elsewhere (11).

3.6. Particle-Formation Pathways. The preceding identification and description of five prevalent types of particles

supports the hypothesis that elements dissociated from the

lubrication oil during combustion experience a time-dependent gas-to-particle conversion. Afterinitial combustion

and during piston retraction,the various vaporized elements

undergo nucleation or vapor deposition depending on their

volatility, concentration, and the local instantaneous cooling

rate. Such a process would likely begin with gas-to-particle

conversion of pure (elemental) carbon vapors during the

passing of the combustion flame front. There was evidence

of a separate nucleation eventforthe lower volatility metallic

vapors of iron and calcium, probably occurring relatively

early in the combustion process, suggested by the significant

coatings of higher volatility species around iron and calcium

cores. For most particles, the metal-to-carbon ratios were

higher than for those emitted by other internal combustion

engines. This was expected because the combustion of

hydrogen does not produce carbon, although some carbon

is available from the lubrication oil.

Next, adsorption, condensation, and potentially, further

nucleationof metals with higher vapor pressure would occur,

in addition to the conversion of the low-volatility hydrocarbons. The more volatile hydrocarbons likely remain in

vapor form until after piston retraction, when they begin

condensing onto particle surfaces or nucleating homogeneously when the exhaust aerosol cools suddenly during the

dilution process. Results of this work imply that new engine

technologies that reduce soot levels in the engine or include

trace metals in the fuel, may increase both the metal-tocarbon ratio of emitted particles and the generation of metalrich nanoparticles via self-nucleation. The source of metals

for such particle generation could be from fuel impurities,

lubrication oil consumption, metals derived from engine

wear, or metal-containing fuel additives. Because of their

small size and thus efficientlung penetration,the generation

of such metallic nanoparticles may introduce health concerns.

Acknowledgments

The authors thank NIOSH employees Rich Rains, Brian

Stapleton, andPatrickHintz fortheir assistance inconducting

this research.Additionalthanks goes to the SeattleUniversity

Summer Faculty Fellowship for supporting this work. The

findings in this work are those of the authors and do not

necessarily represent the views of the National Institute for

Occupational Safety and Health (NIOSH). The mention of

specific products and manfacturers does not imply endorsement by NIOSH.

Literature Cited

(1) Pope, C. A.; Thun, M. J.; Namboodiri, M. M.; Dockery, D. W.;

Evans, J. S.; Speizer, F. E.; Health, C. W. Particulate air pollution

as a predictor of mortality in a prospective study of U.S. adults.

Am. J. Respir. Crit. Care Med. 1995, 151, 669-674.

(2) Utell, M. J.; Frampton, M. W. Acute health effects of ambient

air pollution: The ultra-fine particle hypothesis. J. Aerosol Med.

2000, 13, 355-359.

(3) Aust, A. E.; Ball,J.C.; Hu, A. A.; Lighty,J. S.; Smith, K. R.; Straccia,

A. M.; Veranth, J. M.; Young, W. C. Particle Characteristics

Responsible for Effects on Human Lung Epithelial Cells; Report

110; Health Effects Institute: Location, 2002; p 65.

(4) Ghio, A. G.; Richards, J. H.; Carter, J. D.; Madden, M. C.

Accumulation of iron in the rat lung after tracheal instillation

of diesel particles. Toxicol. Pathol. 2000, 28, 619-627.

(5) Lee, D. G.; Miller, A. L.; Park, K.; Zachariah, M. R. Effects of trace

metals onparticulatematterformationina diesel engine: Metal

contents from ferrocene and lube oil. Int. J. Automot. Technol.

2006, 7, 667-673.

(6) Miller, A.; Ahlstrand, G.; Kittelson, D. B.; Zachariah, M. R. The

fate of metal (Fe) during diesel combustion: Morphology,

chemistry, and formation pathways of nanoparticles. Combust.

Flame 2007, 149, 129-143.

(7) Flynn, P.; Durrett, R.; Hunter, G.; Loye, A.; Akinyemi, O.; Dec,

J.;Westbrook,C.Diesel combustion: Anintegral viewcombining

laser diagnostics, chemical kinetics, and empirical validation.

SAE Tech Pap. Ser. 1999, 1999-01-0509.

(8) Siegmann, K.; Sattler, K.; Siegmann, H. C. Clustering at high

temperatures: Carbon formation in combustion. J. Electron

Spectrosc. 2002, 126, 191-202.

(9) Lee, D. G.; Miller, A. L.; Kittelson, D. B.; Zachariah, M. R.;

Characterization of metal-bearing diesel nanoparticles using

single particle mass spectrometry. J. Aerosol Sci. 2005, 37, 88­

110.

(10) Skillas, G.; Qian, Z.; Baltensperger, U.; Matter, U.; Burtscher, H.

Influence of additives on the size distribution and composition

of particles produced by diesel engines. Combust. Sci. Technol.

2000, 154, 259-273.

(11) Sakurai, H.; Tobias, H. J.; Park, K.; Zarling, D.; Docherty, K. S.;

Kittelson, D. B.; McMurry, P. H.; Ziemann, P. J. On-line

measurements ofdieselnanoparticle compositionandvolatility.

Atmos. Environ. 2003, 37, 1199-1210.

(12) Barris, M. A.; Reinhart, S. B.; Wahlquist, F. H. The influence of

lubricating oil and dieselfuel on ash accumulation in an exhaust

particle trap. SAE Tech. Pap. Ser. 1991, 910131, 19-28.

(13) De Petris,C.; Giglio, V.; Police, G. Some insights on mechanisms

of oil consumption. SAE Tech. Pap. Ser. 1996, 961216.

(14) Bugarski, A. D. Characterization of particulate matter and

hydrocarbon emissions from in-use heavy-duty diesel engines.

Ph.D.Thesis,Mechanical Engineering,WestVirginiaUniversity,

1999.

(15) Okada, S.; Kweon, C.; Stetter, J.; Foster, D.; Shafer, M.; Christensen, G.; Schauer, J.; Schmidt, A.; Silverberg, A.; Gross, D.

Measurement of trace metal composition in diesel engine

particulate and its potential for determining oil consumption.

SAE Tech. Pap. Ser. 2003, 2003-01-0076.

(16) Jung, H.; Kittelson, D. B.; Zachariah, M. R. The influence of a

cerium additive on ultrafine diesel particule emissions and

kinetics of oxidation. Combust. Flame 2005, 142, 276-288.

(17) Diesel Particulate Matter Exposure of Underground Metal and

Nonmetal Miners. Federal Register 66:13 (19 January 2001),

5706-5755.

(18) Diesel Particulate Matter Exposure of Underground Metal and

Nonmetal Miners. Emission Limits for Nonpermissible HeavydutyDiesel-poweredEquipment,Generators, andCompressors.

Federal Register 66:98 (21 May 2001), 27864-27866.

(19) Baker, N.; Houston, L.; Lynch, F.; Olavson, L.; Sandrock, G. A

Clean Internal Combustion Engine for Underground Mining

Machinery: A Technical Assessment and Program Plan; OpenFile Report 86-82, NTIS PB 82-244724, EIMCO Mining Mach.

Int.; U.S. Bureau of Mines: Minneapolis, MN, 1981; p 219.

(20) White, L. Hydrogen fuels underground utility vehicle. Eng. Min.

J. 2004, 68-70.

(21) Bugarski,A.;Mischler, S.; Schnakenberg, G. Effects of alternative

fuels on concentrations of nanometer and ultrafine particles in

underground mines. Presented at the 9th ETH, Conference on

Combustion Generated Nanoparticles, Zurich, Switzerland,

2005.
Received for review April 27, 2007. Revised manuscript received July 5, 2007. Accepted July 18, 2007.

ES070999R

(22) Woodward, C. Safety Control Systems Used in a Hydrogenfueld Mine Vehicle. Presented at the Annual Meeting of the

Society for Mining, Metallurgy, and Exploration, 2006.

(23) McGinn, S.TheRelationshipBetweenDieselEngineMaintenance

and Exhaust Emissions; Technical Report; Noranda Technology

Centre, Diesel Emissions Evaluation Program (DEEP): StLaurent, Quebec, 2000; p 93.

(24) Spears, M. W.	 An Emission-assisted Maintenance Procedure

(EAMP) for Diesel-powered Equipmen; Technical Report 84;

Center for Diesel Research, University of Minnesota: St. Paul.

MN, 1997.

(25) Abdul-Khalek, I. S.; Kittelson, D. B.; Brear, F. The influence of

dilution conditions on diesel exhaust particle size distriubtion

measurements. SAE Tech. Pap. Ser. 1999, 1999-01-1142.

(26) Tammet,H.;Mirme,A.;Tamm,E.Electrical aerosol spectrometer
 

of Tartu University. J. Aerosol Sci. 1998, 29, S427-S428.
 

(27) Birch, M. E. Analytical instrument performance criteria:	 Occupational monitoring of particulate diesel exhaust by NIOSH

Method 5040. Appl. Occup. Environ. Hyg. 2002, 16, 400­

405.

(28) Cheng, Y. S.; Yeh, H. C.; Kanapilly, G. M. Collection efficiencies

of a pointto plane electrostatic precipitator. Am.Ind. Hyg. Assoc.

J. 1981, 42, 605-610.
 

(29) Roessler, D.M.; Faxvog, F.R.; Stevenson,R.; Smith, G.W. Optical
 

Properties and morphology of particulate carbon: Variation
 

with fuel/air ratio. Proc. Int. Symp. Particulate Carbon 1980,
 

57-84.
 

(30) Zifei, L.; Lu, M.; Birch, M. E.; Keener, T. C.; Khang, S. J.; Liang,

F. Variations of the particulate carbon distribution from a
 

nonroad diesel generator. Environ. Sci. Technol. 2005, 39, 7840­

7844.