Instrumentation for diesel particulate matter emissions research

S.E. Mischler, A.D. Bugarski & J.D. Noll

National Institute for Occupational Safety and Health, Pittsburgh Research Laboratory, Pittsburgh, PA, USA

ABSTRACT: Measurement and sampling of diesel particulate matter in mine air presents a challenge due

to the complexity of the diesel aerosol. The results of a series of tests carried out by the National Institute for

Occupation Safety and Health, Pittsburgh Research Laboratory, in an underground mine were used to evaluate

several measurement methods that are currently used to characterize particulate matter emitted by diesel-powered

equipment. This paper presents an overview of these techniques and examples of the results along with a

discussion of the advantages and information gained by each technique. The measurement methods discussed

include particle size measurements using a scanning mobility particle sizer, total particulate matter measurements

using a tapered elemental oscillating microbalance, a size selective sampling method for workplace and personal

exposure assessment and a size-selective high volume sampling method for carbon analysis.

1 INTRODUCTION

Measurement and sampling of diesel particulate matter (DPM) presents a challenge due to the complex

nature of diesel aerosols. There are a number of

methods for DPM measurements and each method’s

relevance is dependent upon the information required.

For instance, the Environmental Protection Agency

(EPA) defines DPM as the mass of material collected

on a filter at a temperature of 52◦C or less after dilution of exhaust with air (EPA, 2002). The EPA is

interested in defining the concentrations of DPM in

ambient air. The Mine Safety and Health Administration (MSHA) currently regulates (MSHA 2005) the

exposure of underground metal/nonmetal miners to

DPM (MSHA, 2005) based upon the mass based concentration of elemental carbon (EC). EC was found

to be a suitable surrogate for DPM in underground

metal/nonmetal mines, since diesel engines are practically the only source of submicron EC particles in

this occupational environment (MSHA, 2005). Other

measurement methods for DPM in occupational environments have also included, respirable particulates

(<3.5μm), smoking corrected respirable particulates

and combustible respirable particulates among other

methods (EPA, 2002).

The mass measurement methods discussed above all

collect the DPM on a filter, which is then sent to a laboratory for mass determination. There are also methods

available for almost real-time DPM measurements.

Jimriska et al. (2004) used a tapered element oscillating microbalance (TEOM) to continuously measure

PM2.5during a study of diesel bus emissions. In this

same study, a scanning mobility particle sizer (SMPS)

was also used to measure semicontinuous size distribution and particle number concentration of the DPM.

Kittleson (2004) used a photoemission aerosol sensor (PAS) to measure diesel particulate emissions.

These measurements were made when the engine was

operated at five steady-state conditions. The author

compared the PAS measurements with results from a

SMPS, a diffusion charger and a condensation particle

counter.

In this paper, the results of a series of comprehensive tests carried out by the National Institute for

Occupation Safety and Health, Pittsburgh Research

Laboratory, in an isolated zone of an underground

metal/nonmetal mine, will be used to evaluate several sampling and measurement methods that are able

to characterize particulate matter emitted by dieselpowered equipment. The results from measurements

using a SMPS, and TEOM as well as results from a

high volume and low volume filter method will be

discussed and compared.

2 METHODOLOGY

These tests were conducted in an isolated zone, a

long underground mine entry ventilated by fresh air

(see Figure 1). Isolated zone tests were designed to

be a compromise between the genuineness of in-situ

measurements of concentrations and the repeatability

and accuracy of the emission measurements obtained

under research laboratory conditions. These tests

allowed the operation of vehicles under conditions and

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Figure 1. Isolated zone.

over duty cycles that closely mimic actual production

duty cycles in an area that was not contaminated by

emissions from other vehicles as would occur in tests

conducted in real production areas. In addition, artifacts usually generated under laboratory conditions

while attempting to simulate real-life conditions and

processes do not compromise the results of isolated

zone tests. A detailed description of the isolated zone

methodology can be found in Bugarski et al. (2006a

and 2006b).

Simultaneous measurements using each of the sampling methodologies described above were used to

measure DPM concentrations downstream of the isolated zone (see Figure 1) as the vehicle was operated

over a simulated duty cycle between the two load/dump

points. The results obtained from tests conducted for

two types of control technologies, water-fuel emulsions and diesel particulate filters, were used for this

analysis.

3 INSTRUMENTATION

A description of various methods used in this study

to collect particulate samples and directly measure

concentrations of particulates is given below.

3.1 Standard sampling of DPM for carbon analysis

A standard sampling method (SSM) similar to the one

used by the Mine Safety and Health Administration

(MSHA) for DPM compliance monitoring [MSHA

2005] was used to collect DPM samples for carbon

analysis. All samples were collected in triplicate.

The standard sampling method uses a sampling train

consisting of a flow controlled pump, a 10 mm DorrOliver cyclone, and an SKC DPM cassette from SKC,

Inc., Eighty-Four, PA.The SKC DPM cassette contains

a single stage impactor and two stacked 37 mm diameter tissue quartz fiber filters. The pumps are operated

at 1.7 l/min. At this flow rate, only aerosols with an

aerodynamic diameter (D50) smaller than 0.820μm

reached the collection filter (Olson 2001).

The 1.7 l/min sampling flow rate used by this

method is inadequate for obtaining DPM samples in

cases where the concentration of DPM is low and

Figure 2. High-volume sampling train.

sampling times are short. Therefore, this method was

not used to collect samples during the tests on the

filtration systems.

3.2 High-volume (HV) method for sampling DPM

for carbon analysis

A HV sampling method was used to collect DPM

samples. This high volume sampling train, described

in detail elsewhere (Bugarski 2006a), was used to

enhance the collection of samples for carbon analysis

by increasing the sampling flow rate and decreasing the

collection area of the filter. A schematic of the highvolume sampling train is presented in Figure 2. The

sampling flow rate was increased by merging flows

from five preclassifiers, each consisting of a 10-mm

Dorr-Oliver cyclone followed by a U.S. Bureau of

Mines (USBM) single stage diesel impactor, into a single stream. A flow rate of approximately 2.0 l/min was

maintained through each cyclone and impactor pair.

At this sampling flow rate only particles with geometric mean smaller then 0.775μm were deposited on the

filters (Olson 2001).

All five preclassifiers were attached to a symmetrical plenum that distributed a total flow rate of

approximately 10.0 l/min uniformly among the five

streams. Each of the preclassifier assemblies was connected to the plenum chamber by a 1-m long section

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of electrically conductive tubing. The outlet of the

plenum was directly connected to a stainless steel

25 mm diameter filter holder containing two stacked

25 mm tissue quartz fiber filters.

The total sampling mass flow rates were maintained using a mass flow controller in the each of the

three sampling lines from the 25 mm diameter filter

holder. The total volumetric flow rates through each

of the sampling streams were measured periodically

by inserting a bubble flow meter inline, between filter holders and mass flow controllers. The volumetric

flow rates measured during this study were all corrected to ambient conditions. A high volume rotary

vane pump was used to draw the sample though the

filter.

3.3 DPM concentration measurements with a

Tapered Element Oscillating Microbalance

(TEOM) series 1400a ambient particulate

monitor

The TEOM 1400a (Rupprecht & Patashnick Co.,

Albany, NY) draws air through a filter at a constant

flow rate, while continuously measuring the mass

accumulating on the filter and calculating near realtime mass concentrations. The sample stream is drawn

through this filter from a hollow tapered element that

is vibrated at a precisely controlled frequency and

connected to the suction side of the sampling system. The vibration frequency of the tapered element

decreases as particulate mass collected on the filter

increases. By frequently measuring the tapered element frequency, the TEOM calculates the increase in

mass of the sample that has accumulated on the filter.

The concentration of TPM can be calculated by dividing the accumulated mass by the volume of airflow

across the filter during the time period over which the

frequency change is measured.

The flow through the instrument is maintained at

a constant rate by a mass flow controller. The flow

is corrected for temperature and barometric pressure.

The internal instrument temperatures are controlled

to minimize the effects of ambient temperatures. To

prevent condensation and ensure that the sample filter

always collects particulates under similar conditions,

the TEOM intake is heated to maintain the sampling

stream at 50◦C.

During this study, the flow rate on the TEOM was

set at 1.7 l/min. A cyclone and impactor were used as

preclassifiers to the TEOM, allowing only particles

with an average aerodynamic diameter (D50) smaller

than 0.820μm to reach the collection filter. The average ambient concentrations of TPM were recorded and

saved every 10 seconds. The reported average concentrations for a test were obtained from the difference in

filter masses recorded at the same start and stop times

used by the particulate samples for carbon analysis.

3.4 Measurement of size distribution and particle

numbers using a scanning mobility particle

sizers (SMPS)

An SMPS was used to periodically measure size distribution and number of particles in the range between

10 and 392 nm.The SMPS consisted of an electrostatic

classifier (TSI Inc. Shoreview, MN, Model 3080L) and

a Condensation Particle Counter (TSI, Model 3025A).

The flows of monodispersed aerosol were maintained at 0.6 l/min throughout the study. At the established polydispersed aerosol flow rate of 6.0 l/min, the

inlet impactor had a cut-off point of 460 nm. The condensation particle counter was operated in high-flow

mode to minimize diffusion losses. The samples were

collected using 90-second up-scans and 15-second

down-scans. The instrument was operated using a

dedicated laptop computer and Aerosol Instrument

Manager Software from TSI Inc.

The effects of the tested control technologies on

size distribution and count concentrations of aerosols

in mine air were assessed based on the measurements

conducted while the vehicle was performing the portion of the duty cycle at a point nearest to the location

of the SMPS.

4 DISCUSSION OF RESULTS

In this section the instrument results from the isolated

zone tests will be presented along with a discussion

on the applicability of each type of data. The results

presented are from tests when the vehicle was outfitted

with several diesel particulate filter systems and when

the vehicle was fueled with two blends of a water-fuel

emulsion.

Figure 3 presents the results from the HV, SSM

and TEOM sampling methods observed during the

baseline (#1 diesel/muffler) test as well as tests with

cold-weather (C-W) and warm-weather (W-W) waterfuel emulsions. As discussed previously, the TEOM

results shown here are an average over the sampling

period for the HV and SSM methods.

This figure shows that the HV and SSM methods measured similar EC concentrations. The TEOM

results show concentrations that are higher then the

HV or SSM methods. The additional mass concentrations can be attributed to other DPM compounds

such as organic carbon, metals, and sulfates that are

not measured by the EC analysis. This additional mass

may also contain any particulate, with an aerodynamic

diameter smaller than 0. 820μm, generated during the

transfer of ore/waste rock during the test.

Figure 4 presents the results from the HV and

TEOM sampling methods observed during the baseline test as well as tests when the vehicle was outfitted

with diesel particulate filters.

101
275

90

40

388

207

129

262

99

40

0

100

200

300

400

500

#1 Diesel/Muffler C-W/Muffler W-W/Muffler

Concentrations [μg/m^3]

EC HV TPM TEOM EC SSM

Figure 3. HV, SSM and TEOM results for water-fuel emulsion tests.

105

8 9

31

180

51

43

62

0

20

40

60

80

100

120

140

160

180

200

EC HV TPM TEOM

Concentration (g/m^3)

Muffler Filter 1 Filter 2 Filter 3

Figure 4. HV and TEOM results for filter tests.

The lack of SSM data on Figure 4 suggests one

advantage of the HV method over the SSM. Previous

isolated zone tests using vehicles outfitted with diesel

particulate filters showed that the SSM was not able to

collect enough EC for accurate analysis. However, the

increased collection volume of the HV method allowed

for successful measurement of these lower EC concentrations. In these tests the TEOM DPM measurements

were again higher than the HV EC concentrations.

The TEOM was able to effectively measure the DPM

concentrations during the filter tests.

Figure 5 presents the semi-continuous (one-minute

average) data from the TEOM during the water-fuel

emulsion tests. Kelly and Morgan (2002) compared the

real-time TEOM measurements with the filter based

EPA method and found the ability of the TEOM to

measure the transient values of DPM during testing

to be a major advantage. Likewise, having a semicontinuous stream of data during these tests is an

advantage because this extra data allows for a more

thorough inspection of the test data. Evaluation of

the semi-continuous data presented in Figure 5 shows

the repeatability of the duty cycles during these tests.

0

100

200

300

400

500

600

700

0 1000 2000 3000 6000

#1 Diesel/Muffler C-W/Muffler W-W/Muffler

TPM Mass Concentration [g/cm^3]

Time [s]

4000 5000

Figure 5. TEOM semi-continuous data during the waterfuel emulsion tests.

0

50

100

150

200

250

300

0 1000 2000 3000 4000 5000 6000 7000 8000

Muffler Filter 1 Filter 2 Filter 3

TPM Mass Concentration [ug/cm^3]

Time [s]

350

Figure 6. TEOM semi-continuous data during filter tests.

The semi-continuous data also aids in the detection of

potential problems during the test. For example if at

3000 seconds the TEOM data showed a major spike

or decrease in concentrations, than that is evidence

of a potential problem with the test. Data from the

HV or SSM methods would not obviously show that a

problem occurred.

Figure 6 shows the semi-continuous TEOM data

collected during the filter tests. Again this figure

shows the repeatability of each duty cycle. This data

also shows an interesting aspect of the test using Filter 2.This data shows the DPM concentrations steadily

decreasing during the test, indicating that the filter

efficiency was improving over the duration of the

test. This important piece of information would be

impossible to discern using only the HV or SSM

results.

The results presented thus far are from mass based

measurement methods. However, many researchers

have measured DPM using other metrics including

particle number concentration or surface area. The

advantages and disadvantages of these different metrics for measurement of DPM is currently an area of

much research (Kittleson, 2004). One instrument used

during the current study to measure particle number

concentration was the SMPS.

102
1.0E+01

1.0E+02

1.0E+03

1.0E+04

1.0E+05

1.0E+06

1.0E+07

10

#1 Diesel with Muffler C-W with Muffler W-W with Muffler

dN/dlog(D_p) [#/cm^3]

100 1000

D_p [nm]

Figure 7. SMPS results from the water-fuel emulsion tests.

10 100 1000

D_p [nm]

Muffler Filter 1 Filter 2 Filter 3

1.0E+07

dN/dlog(D_p) [#/cm^3]

1.0E+06

1.0E+05

1.0E+04

1.0E+03

1.0E+02

1.0E+01

Figure 8. SMPS results from the filter tests.

Figure 7 shows the effects of the two water-fuel

emulsions on the aerosol size distributions of the DPM.

The size distributions of the particles observed

during the tests with water-fuel emulsions are characterized by lower geometric mean diameter (GMD)

and higher peak concentrations than the size distributions observed during the baseline test with #1 diesel.

The GMD of the baseline particles was 95 nm, while

the GMD for the cold and warm weather water-fuel

emulsions were 68 and 55 nm, respectively. The peak

particle number concentration for the baseline test

with #1 diesel was 1,065,000/cm3 and was lower than

those observed for cold weather (1,449,000/cm3) and

warm weather (1,324,000/cm3) emulsions. The relative increases in total aerosol number concentrations

were (14%) and (16%) for the cold and warm weather

water fuel emulsions, respectively.

Figure 8 presents the results of the SMPS data

from the filter tests. This data shows that the particle number concentrations were higher for the smallest

particles and lower for the larger particles.The size distributions measured during the Filter 1 test were found

to be characterized with a bimodal distribution having peak concentrations higher than those observed

for the baseline case. The net contribution of the

system to the total particle number was also found

to be 105% higher than that of the muffler.

The effects of Filter 2 and Filter 3 on size distribution and aerosol concentration were found to be quite

Table 1. Summary of reviewed measurement methods.

Method

(Measurement Consideration/

metric) Applications limitation

SSM (1) Personal (1) Long sampling time

(Mass con- sampling. may be required at low

centration) (2) Time integrated DPM concentrations

sampling. (<80 ug/m3).

(2) Delayed results.

HV (1) Time-limited (1) Occupational

(Mass con- sampling at low sampling not possible.

centration) DPM con- (2) Delayed results.

centrations

(< 80 ug/m3).

(2) Time integrated

sampling.

TEOM (1) Near real-time (1) Occupational

(Mass con- sampling. sampling not possible.

centration) (2) Time integrated

sampling.

SMPS (1) Particle size (1) Occupational

(Size distri- distribution sampling not possible.

bution and sampling. (2) Time integrated

particle (2) Real-time sampling not possible.

number con- sampling.

centration)

different. The size distribution of the particles measured during the test with the Filter 2 was characterized

by much lower concentrations in the larger particle

size range. On the contrary, the size distributions of

the particles during the Filter 3 test had significantly

fewer smaller size particles. This is in agreement with

the results of the EC, andTEOM measurements, which

showed higher EC andTPM reductions for Filter 2 than

for Filter 3.

Table 1 presents a summary of the measurement

methods presented in this paper and shows their

appropriate applications and major considerations

and limitations. As can be seen each method discussed has appropriate applications along with certain

limitations.

As shown in Figure 3 and Figure 4, the mass

measurement results provide evidence that both the

water-fuel emulsion and the diesel particulate filters

reduced the airborne DPM concentrations. However,

the SMPS results tell a slightly different story than

that derived from the mass measurements. The SMPS

results for both the water-fuel emulsion tests and the

filter tests show that while the mass is decreasing the

particle number concentration is actually increasing.

Overall, the data in this study emphasize the importance of using instruments that measure different metrics when characterizing DPM and evaluating DPM

control technologies. It is important to realize the

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necessity of measuring several different metrics to

achieve a true understanding of DPM and the effects

of DPM control. As shown, control technologies can

work very well in controlling one metric but actually

increase the concentration of a different metric.

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