Relationship between Elemental

Carbon, Total Carbon, and Diesel

Particulate Matter in Several

Underground Metal/Non-metal Mines

J. D. NOLL,* A. D. BUGARSKI,

L. D. PATTS, S. E. MISCHLER, AND

L. MCWILLIAMS

U.S. Department of Health and Human Services, Public

Health Service, Centers for Disease Control and Prevention,

National Institute for Occupational Safety and Health,

Pittsburgh Research Laboratory, 626 Cochrans Mill Road,

Pittsburgh, Pennsylvania 15236

Elemental carbon (EC) is currently used as a surrogate

for diesel particulate matter (DPM) in underground mines

since it can be accurately measured at low concentrations

and diesels are the only source of submicrometer EC in

underground mines. A disadvantage of using EC as a

surrogate for DPM is that the fraction of EC in DPM is a

function of various engine parameters and fuel formulations,

etc. In order to evaluate how EC predicts DPM in the

underground mining atmosphere, measurements of total

carbon (TC; representing over 80% of the DPM) and EC were

taken away from potential interferences in four underground

metal/non-metal mines during actual production. In a

controlled atmosphere, DPM mass, TC, and EC measurements

were also collected while several different types of

vehicles simulated production with and without different

types of control technologies. When diesel particulate filters

(DPFs) were not used, both studies showed that EC

could be used to predict DPM mass or TC. The variability

of the data started to increase at TC concentrations

below 230 μg/m3 and was high (>(20%) at TC concentrations

below 160 μg/m3

, probably due to the problem with

sampling organic carbon (OC) at these concentrations. It

was also discovered that when certain DPFs were used, the

relationship between DPM and EC changed at lower

DPM concentrations.

Introduction

Long-term exposure to elevated concentrations of diesel

exhaust is a concern because diesel particulate matter (DPM)

is believed to be a possible carcinogen (1-3). Exposure to

elevated concentrations of diesel exhaust has also been linked

to health effects such as eye and nose irritation, headaches,

nausea, and asthma (4-6). Measurements have shown that

underground miners can be exposed to over 100 times the

typical environmental concentrations of diesel exhaust and

over 10 times the concentrations that are measured in other

work environments where diesel engines are common (7-

9).

In the United States, the Mine Safety and Health Administration (MSHA) has promulgated rules (10-14) limiting

DPM concentrations to which underground metal/non-metal

miners are exposed. In general, the rule stipulates using quarts

fiber filters to collect DPM (15-17) and then analyzing the

filters for elemental carbon (EC) and organic carbon (OC)

content using NIOSH method 5040 (18-20). The total carbon

(TC) content on a filter is obtained by adding EC and OC.

Initially, TC was considered by MSHA to be the most

appropriate surrogate for DPM because it accounts for over

80% of the particulate matter in diesel exhaust (21-22).

However, other sources, commonly present in underground

mines, can interfere with the TC analysis (12, 14). These

contaminants include EC and OC found on mineral dust,

environmental tobacco smoke, and oil mist. EC and OC

contamination from mineral dust has been shown to be

effectively removed using size-selective samplers (15-17, 23-

25). Unfortunately, these size-selective samplers are not

effective in removing the submicrometer aerosols from

cigarette smoke or oil mist. Because cigarette smoke and oil

mist cannot always be avoided when taking personal samples,

and because these contaminants only interfere with the OC

analysis, MSHA proposed using submicrometer EC as a

surrogate for DPM. There are no other known sources of

submicrometer EC present in the metal/non-metal mining

environment.

One potential issue with using EC as a surrogate for DPM

is that the EC fraction of DPM may change depending upon

factors such as engine duty cycle and fuel type, etc. For

example, Burtscher et al. showed a black carbon (EC) to total

mass ratio for DPM sampled from the tailpipe that ranged

from 45 to 100%, depending upon the engine load conditions

(26). The portion of EC in DPM in underground mining

atmospheres could potentially vary, depending on how much

engine conditions vary from day to day and mine to mine.

It is necessary to investigate the relationship between DPM

and EC in underground metal/non-metal mines to determine

how well EC can be used to predict DPM concentrations

across the industry. This will become especially important

in 2008 when the exposure limit for underground metal/

non-metal miners changes to the final exposure limit of

160 μg/m3 TC. MSHA plans on using EC as a surrogate for

this final rule but has not yet determined the TC to EC

conversion factor to be used to convert 160 μg/m3 TC to a

comparable EC concentration.

In this study, we investigated the relationships between

DPM and EC concentrations, and TC and EC concentrations,

using results obtained through a series of tests conducted in

an isolated zone in a metal mine. Additionally, the relationship between TC and EC concentrations was evaluated using

results obtained from samples collected in two stone and

two metal underground mines during actual production. This

research will add to the current knowledge on the relationship

between DPM and EC and may assist MSHA and other

researchers in formulating proper conversion factors between

the two.

Experimental Procedures

Testing Procedures. Isolated Zone Tests. Ambient concentrations of EC, TC, and DPM were measured during a series

of tests in an isolated zone. The isolated zone, a section in

a metal mine that is isolated from the remaining parts of the

mine, was designed so that the only source of DPM and

gases in the zone was from the vehicle being tested. A detailed

description of the isolated zone is given in reports by Bugarski

et al. (27, 28).

Six vehicles were used to test the emission control

technologies (list of vehicles and control technologies in

* Corresponding author phone: 412-386-6828; fax: 412-386-4917;

e-mail: JIN1@cdc.gov.

Environ. Sci. Technol. 2007, 41, 710-716
papers by Bugarski et al. (27, 28)). Each vehicle was operated

with and without emission control technologies. The vehicles

were operated in the zone over simulated production duty

cycles described in the reports by Bugarski et al. (27, 28).

During those tests, triplicate particulate samples for

carbon analysis were collected upstream and downstream

of the vehicle in the zone using a high-volume (HV) sampling

method (air collected at 8.5 lpm with a 0.8 μm cutpoint

(method described in detail in papers by Bugarski et al. (26,

27)). In parallel, the DPM concentrations were measured at

the same locations (upstream and downstream) using a

tapered element oscillating microbalance (TEOM; Thermo

Electron, East Greenbush, NY). To avoid collecting mineral

dust, a classifier, consisting of a Dorr Oliver cyclone followed

by a Bureau of Mines (BOM) impactor, was attached to the

inlet of the TEOM. The TEOM measures the mass of material

collected on a filter element mounted on a hollow tapered

vibrating pedestal. To prevent condensation and ensure that

the sample filter always collects particulates under similar

conditions, the intake to the tapered element is heated and

the sampling stream through the filter is maintained at 50 °C.

The reported TPM concentration for each test was obtained

from the net gain in mass that occurred over the same time

period as that of the OC/EC sampling. Test equipment and

procedures are described in detail in the reports by Bugarski

et al. (27, 28).

Mine Surveys. The samples for carbon analysis were

collected in two stone and two metal mines during normal

mining production using the standard sampling method

(described in the next section). The samples were analyzed

using NIOSH method 5040.

The following precautions were taken to minimize the

effects of potential interferences, such as cigarette smoke

and oil mist: (1) area sampling stations were located in the

mine returns, away from any potential sources; (2) a tandem

filter correction (described later in this paper) was applied

to correct for the adsorption of vapor-phase OC; (3) finally,

only samples containing over 40 μg of TC were included in

this data set to further minimize the potential effects on the

TC to EC relationship from contributions of non-DPM OC

(TC ) OC + EC).

In addition to the area samples, seven personal samples

were included in this data set. Because these samples were

collected in areas where the average TC concentrations were

greater than 900 μg/m3 (i.e., areas with high DPM concentrations), any potential contamination from non-diesel

sources should have a minor effect on the TC to EC

relationship (29).

In each stone mine, triplicate samples were taken each

day over a 3-day period. This procedure was repeated for

each fuel type: No. 2 diesel, 50% recycled grease biodiesel,

10% PuriNOx mixture (a water emulsified fuel produced by

Lubrizol, Inc., of Wicklifffe, OH), and 20% PuriNOx mixture.

Diesel oxidation catalysts were used on all equipment in the

stone mines.

In one metal mine, where control technologies were not

used and the vehicles were fueled with No. 2 diesel, the

samples were collected once a day over a 4-h sampling period

for 6 consecutive days. In the other metal mine, samples

were collected over one, 2.5-h period when there were no

control technologies on the vehicles. After DPF systems were

installed on some of the vehicles, a second set of samples

was collected for 2 days (involving about 4 h of sampling per

day).

Sampling and Measurement Methods. Standard Sampling Procedure. In the standard sampling procedure, the

sampling train, consisting of a DPM cassette (SKC, Inc., Eighty

Four, PA), a Dorr-Oliver cyclone, and an Elf Escort personal

pump (Mine Safety Appliances Co., Pittsburgh, PA), was used

to collect ambient air samples at 1.7 L/min (liters per minute).

SKC DPM cassettes incorporate an impactor with a 0.8 μm

cutpoint and two quartz fiber filters placed in tandem.

Analytical Methods.NIOSH Method 5040.NIOSH method

5040 was used to determine EC and TC concentrations. A

detailed description of NIOSH method 5040 is found in the

NIOSH Manual of Analytical Methods (20).

Tandem Filter Correction. Quartz filters have been found

to adsorb vapor-phase OC, which is not traditionally recognized as part of DPM or other types of particulate carbon,

and thereby contribute a positive bias in DPM TC results. A

tandem filter correction procedure (30-32) was used to

correct results and account for this phenomenon. This

procedure requires a second filter to be placed behind the

sample filter, resulting in two filters positioned in tandem.

In theory, only the sample filter collects particulate OC but

both filters adsorb about the same amount of vapor-phase

OC. Results from the second filter were therefore subtracted

from the sample filter OC values to correct for the adsorbed

vapor-phase OC.

Data Analysis. A linear regression analysis was used to

evaluate the relationship between DPM and EC and between

TC and EC, where either DPM or TC was the dependent

variable and EC was the independent variable. When the

distribution of the dependent variables showed a significant

departure from normality, a log-linear regression model was

also investigated. If the overall fit of the models did not differ,

only the results of the analyses using the untransformed data

would be presented in this paper.

The coefficient of determination (R2) was computed for

each regression analysis. R2 represents the fraction of total

variation in the values of the dependent variables (DPM or

TC) that can be explained by the linear relationship to the

independent variable (EC).

An F-statistic was also computed for each model. This is

the ratio of the model mean square divided by the error

mean square. For a linear regression, it is used to test the

hypothesis that the slope coefficient (â1) is equal to zero. If

the F-statistic results in a p-value of less than 0.05, this

indicates that the linear model is appropriate for describing

the relationship between DPM and EC or TC and EC.

Diagnostics were used to assess violations of linear

regression assumptions. Studentized residuals (residuals

divided by their standard errors) were calculated to identify

outlying observations. Studentized residuals exceeding a

value of 2.5 provide a way to pinpoint unusually large

residuals. In addition, a Cook’s distance (Cook’s D) statistic

was calculated for each point to determine its influence on

the regression line. The Cook’s D number is the measure of

change in the predicted values upon deletion of that

FIGURE 1. Difference between TC on QQ2 (second filter) and QQ1

(first filter) (TC(QQ1) - TC(QQ2)) on samples taken at the intake in

the mines or upstream in the isolated zone. The difference between

the two filters is small for most cases.
observation from the data set. If the Cook’s D number is

above 1, that data point is considered to be highly influential.

However, this does not necessarily indicate that the point

should not be included in the regression model.

Once the regression equation was determined, the deviation of each point from the regression line was determined

to see how well the equation predicted each data point. The

following equation was used

whereVcalcd is the dependent variable (DPM or TC) calculated

from the regression equation and Vmeasd is the dependent

variable (DPM or TC) measured.

Results and Discussion

Blanks. At times in the laboratory it has been noticed that

the second filter used to correct for the adsorption of vaporphase OC can be contaminated. The second filter had

significantly higher OC than the first filter for some blank

samples. This could be due to some contamination from the

backing pads used. To see if the second filter was contaminated for the samples in this study, samples from the intakes

of the mine and in the upstream section of the isolated zone

were studied. The concentration of particulate matter at these

sites was very low (at times, even below the limit of detection

for NIOSH method 5040). Therefore, if the second filter was

contaminated, it would have higher OC than the first. If there

was no contamination, then the first and second filter would

either be approximately the same or the first filter would

have a slightly higher OC, depending upon the concentration

of OC particulate. As seen in Figure 1, contamination of the

second filter was not a significant problem. Figure 1 shows

the difference (TC(QQ2) - TC(QQ1)) between the second

and first filter. For 92% of the samples the concentration of

OC on the second filter did not exceed by more than 5 μg/m3

OC that on the first.

Isolated Zone. As seen in Figure 2a, EC could be used to

predict DPM for the conditions set in the isolated zone when

diesel particulate filters (DPFs) were not used. There is a

good overall fit for the linear regression model (p-value is

<0.0001; R2 ) 0.98) between DPM and EC data obtained in

the isolated zone, when diesel particulate filters were not

FIGURE 2. (a) Linear regression chart for DPM vs EC for data from vehicles in the isolated zone study. (b) Percent deviation of the measured

DPM values from the calculated DPM from EC using the equation of the line in a.

% deviation ) (Vcalcd - Vmeasd)

Vmeasd

× 100
used. There was one outlying observation, but it was not

influential. In addition, a log-linear model was investigated

with these data, but the results did not differ significantly

from those obtained using a linear model.

As illustrated in Figure 2a,b, the correlation between DPM

and EC changes when noncatalyzed DPFs (high-temperature

disposable DPF, ceramic DPF followed by DOC) were used

in the isolated zone tests. In general, there is less than a 20%

deviation between measured DPM and calculated DPM from

EC (using the linear equation); however, at the lower DPM

concentrations when noncatalyzed DPFs were used the data

deviated from the line by over 50%. This deviation may have

resulted from the use of noncatalyzed DPFs on the engine

being tested in the isolated zone. DPFs are known to

preferentially reduce EC over other DPM components.

Bugarski et al. (27, 28) found 92, 92, and 70% reductions in

EC corresponding to an 85, 69, and 62% reduction in DPM,

respectively. It is important to note that the catalyzed DPFs

also preferentially reduced EC over the other components of

DPM (over 90% reduction in EC and around 75% reduction

in DPM), but did not seem to affect the relationship between

DPM and EC. This could be because the catalyzed DPFs can

cause the formation of some non-EC DPM (sulfates) (32, 33).

It is also important to note that some of the deviation could

be due to experimental error when measuring at the lower

DPM concentrations.

In this research the ratio between EC and TC was also

analyzed. This EC to TC analysis was initiated for two

reasons: (1) the mining community is interested in finding

a conversion factor between TC and EC (13), and (2) it allows

for a comparison with results from other field studies where

gravimetric analysis was not possible. Figure 3a presents the

regression model using EC to predict TC. The sample points

included in this figure consisted of data collected when (1)

no control technologies were used, (2) diesel oxidation

catalysts (DOCs) were used, and (3) alternative fuels were

used. The initial model contained a datum point that was

highly influential (Cook’s D ) 7); this point was excluded

from the analysis. The subsequent model resulted in an

F-statistic that was significant at p < 0.0001 and an R2 ) 0.99.

These results indicate that the linear model is appropriate

for describing the relationship between TC and EC.

FIGURE 3. (a) Linear regression chart for TC vs EC for data from vehicles in the isolated zone study. (b) Percent deviation of the measured

TC values from the calculated TC from EC using the equation of the line in a.
When certain DPFs were used, the results deviated from

the linear regression and formed another trend. As seen in

Figure 3b, the points deviated from the predicted TC by over

50% when certain DPFs were used. This could have been

because the DPFs in this experiment preferentially reduced

EC over OC (as mentioned previously).

We know that the DPFs used in the isolated zone

substantially reduced all DPM components (for example, in

the isolated zone when the data were normalized to a

ventilation rate of 12 000 cfm, the DPM concentration

(measured by TEOM) went from 600 μg/m3 (474 μg/m3 TC)

with no control technology to 170 μg/m3 (53 μg/m3 TC) when

a ceramic DPF, followed by a DOC, was used) (27) and caused

deviations in the DPM and EC relationship at lower concentrations. Therefore, we would expect that if these certain

DPFs were used in an underground mine that the DPM and

EC relationship would not be affected until most of the DPM

was generated from vehicles containing these DPFs. Since

vehicles without DPFs would emit much more DPM than

vehicles with these DPFs, the DPM and EC relationship would

only be affected when a large number of the vehicles in the

mine contained these DPFs. We would also expect the DPM

concentration to be in the lower part of the concentration

range when the DPM and EC relationship would change since

the DPFs substantially reduce DPM. This is what was observed

in the isolated zone.

The isolated zone results showed a linear relationship

between EC and DPM when DPFs were not used; however,

when the equipment was outfitted with certain DPFs, usually

resulting in lower isolated zone DPM and EC concentrations,

the relationship between DPM and EC was affected.

In the isolated zone tests we were limited to just several

vehicles from one mine fleet. The next step was to utilize

information gathered from many vehicles in actual mining

production.

Mine Surveys. In this portion of the study, we sampled

TC and EC concentrations in four operating mines. Due to

the complexity of sampling DPM (interferences and precision

of method, etc.) in real mining conditions, gravimetric

samples could not be taken; therefore, only the relationship

between TC and EC could be evaluated. Since TC represents

over 80% of the DPM (as lower sulfur fuel is introduced, TC

FIGURE 4. (a) Linear regression chart for TC vs EC for data from measuring DPM in the atmosphere of four different mines. (b) Percent

deviation of the measured TC values from the calculated TC from EC using the equation of the line in a.
will become even a larger portion of the DPM), this

relationship gives us an idea of how elemental carbon will

relate to DPM.

As shown in Figure 4a, there is a strong linear relationship

(R2 ) 0.99) between TC and EC. The resulting p-value for the

F-statistic is highly significant (p < 0.0001). As discussed

earlier, a log-transformation of both the dependent and

independent variables was used in a log-linear regression

model; however, because the results were not different from

the untransformed regression model, only the model using

the untransformed data is reported in this paper.

The data show that variability increases at lower TC levels

(below approximately 230 μg/m3). As Figure 4b illustrates,

when the TC concentrations are above 230 μg/m3, the percent

deviation of TC measured from the regression line is (10%

(with 95% of the points being between (9%). Within the TC

range of 160-230 μg/m3 the deviation increases to (25%

(with 95% of the points being between (21%). When TC

concentrations are below 160 μg/m3, the deviation is (40%

(with 95% of the points being between(34%). These increases

in percent deviation may be due to several factors including

interferences (as discussed previously) and sampling error.

For example, the OC interferences avoided by using a

sampling strategy (e.g., cigarette smoke) and error in OC

when using a dynamic blank (e.g., contamination of filters)

will have a larger effect at the lower concentrations. Further

research is necessary to more fully explain the reasons behind

these results.

The data in this paper show that DPM/TC can be

accurately predicted using EC as a surrogate for the concentration ranges reported here. However, the data also show

that the regression model for these data becomes less

dependable at the concentrations of DPM/TC below 160 μg/

m3. It was also discovered that at the lower concentrations

the prediction of DPM from EC may change if certain DPFs

are implemented in a mine. The DPM to EC relationship

needs further study to understand how this relationship may

change when certain DPFs and other control technologies

are used.

The results from both studies are a limited data set. The

four mines included in this study do not necessarily provide

a good representation of all metal/non-metal mines. Thus,

more data are needed to ascertain whether this relationship

is able to be applied to all metal/non-metal mining operations. Future work will also concentrate on the collection of

additional data to gain a better understanding of how and

when control technologies will affect the relationship between

DPM and EC.

Acknowledgments

The authors would like to thank Shawn Vanderslice for

performing some of the analytical analyses. Disclaimer:

Mention of a company name or product does not constitute

endorsement by the Centers of Disease Control and Prevention. The findings and conclusions in this report are those

of the authors and do not necessarily represent the views of

the National Institute for Occupational Safety and Health.

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apbf/pdfs/interim4.pdf.

Received for review June 30, 2006. Revised manuscript received October 11, 2006. Accepted October 31, 2006.

ES061556A