Survey of noise in coal preparation plants

Jeffrey S. Vippermana

Department of Mechanical Engineering, University of Pittsburgh, Pittsburgh, Pennsylvania 15261

Eric R. Bauer and Daniel R. Babich

National Institute for Occupational Safety and Health, Pittsburgh Research Laboratory, P.O. Box 18070,

626 Cochrans Mill Road, Pittsburgh, Pennsylvania 15236

Received 14 July 2005; revised 14 August 2006; accepted 1 September 2006

In response to the continuing problem of noise induced hearing loss NIHLamong mine workers,

the National Institute for Occupational Safety and Health NIOSHhas conducted numerous noise

surveys in coal preparation plants. The research, consisting of worker dose monitoring, task

observations, and equipment noise profiling, was completed in eight separate preparation plants.

Worker dose monitoring was conducted for three shifts in most cases. Workers experiencing higher

than allowable doses were task-observed for one full shift to correlate dose to noise sources.

Finally, noise levels on all floors, and in lunch rooms and control rooms, were characterized. Results

indicate that only workers who routinely spend a significant portion of their shift in the plants away

from the control roomsare susceptible to overexposure from noise. Certain pieces of equipment

screens, centrifuges, sieve bendsare the loudest primary noise sources responsible for the worker

noise exposures. © 2007 Acoustical Society of America. DOI: 10.1121/1.2372587

PACS numbers: 43.50.Jh, 43.50.Gf, 43.50.Qp DKW Pages: 197–205

I. INTRODUCTION

Prolonged exposure to noise over a period of several

years can cause noise induced hearing loss NIHL. While

NIHL is the most common occupational disease in the

United States today, with 30 million workers exposed to excessive noise levels,1 the problem is particularly severe in all

areas of mining surface, processing plants, and underground. An early NIOSH analysis of NIHL in miners revealed an alarming prevalence of severe hearing loss.2 For

example, by age 60, over 70% of miners had a hearing loss

of more than 25 dB, and about 25% had a hearing loss of

more than 40 dB. A more recent, 1996 analysis of NIHL in

miners, also performed by NIOSH, showed an apparent

worsening of NIHL.3 This recent analysis of a private company’s 20 022 audiograms indicated that the number of miners with hearing impairment increased exponentially with

age until age 50, at which time 90% of the miners had a

hearing impairment.3 In addition to government researchers,

academics have reported that the “...policies and practices

for preventing occupational hearing loss among miners are

inadequate ...”.4

The Federal Coal Mine Safety and Health Act of 1969

established requirements for protecting coal miners from excessive noise and subsequently, the Federal Mine Safety and

Health Act of 1977 broadened the scope to include all miners, regardless of mineral type.5 Data from more than 60 000

full shift Mine Safety and Health Administration MSHA

noise surveys show that the noise exposure of selected mining occupations has decreased since the 1970s, although the

percentage of miners considered overexposed under current

MSHA noise regulations remains high.6 MSHA found that

the percentage of coal miners with noise exposures exceeding federal regulations, and unadjusted for the wearing of

hearing protection, was 26.5% and 21.6% for surface and

underground mining, respectively.

Despite the extensive work that ensued in the 1970s and

1980s, NIHL is still a pervasive problem, as outlined in Ref.

7. MSHA has published new Noise Health Standards for

Mining.8 One of the changes is the adoption of a provision

similar to OSHA’s Hearing Conservation Amendment.

MSHA concluded in a survey that if an OSHA-like hearing

conservation program were adopted, hypothetically, 78% of

the coal miners surveyed would be required to be in a hearing conservation program.9 Other requirements of the new

regulations are a Permissible Exposure Level PELof

90 dBA LTWA8, no credit for the use of personal hearing

protection, and the primacy of engineering and administrative controls for noise exposure reduction.

Improvements in both mining and noise monitoring

equipment necessitate that new data be taken in order to base

noise control decision making. In many cases, the existing

data are specific to machine type and were obtained for characterizing noise source sound power rather than exposure

assessment. There is also a great range in noise levels for a

given occupation. For example, noise levels for continuous

mining machine operators have a modal value of 90 dBA

and a range that varies from 80 to 105 dBA.10 Yet, at present,

there is insufficient information to explain this variation in

exposure for this and other mining occupations. Specifically,

noise level data are needed that provide a time exposure

history for workers in addition to information on noise

sources. Such information will provide the basis for targeting

and selecting engineering controls, in combination with administrative controls and personal protection equipment, to

reduce noise exposures among the mining workforce. a

Electronic mail: jsv@pitt.edu

J. Acoust. Soc. Am. 121 1, January 2007 © 2007 Acoustical Society of America 197 0001-4966/2007/1211/197/9/$23.00
This study presents a survey and assessment of noise

exposures in eight coal preparation plants from five states.

Results concentrate on the sources of noise exposure, both in

terms of occupations and plant location. Generalizations

about the extent of the noise problem in preparation plants as

well as the noise generating potential of the cleaning equipment are drawn.

II. SURVEY METHODS

A four-phase approach was taken to analyze noise in

coal preparation plants, which included worker dose monitoring, task observations, equipment noise profiling, and reverberation time measurements. Each task is described in

greater detail in the following sections, along with information on plant selection.

A. Plant selection

The number of coal preparation plants in the U.S. totaled

212 for the last census in 2000.11 The average plant capacity

is 1000 tons per hour TPH, with 57 plants exceeding

1000 TPH, and 10 exceeding 2000 TPH. A sample of eight

preparation plants with capacities between 300–2000 TPH

was chosen for this study. The plants were located across the

states of Pennsylvania, Kentucky, Virginia, Illinois, and West

Virginia. They are owned by five different major coal companies that are members of the Noise Partnership, a consortium that was formed to reduce NIHL in the mining industry.

The partnership includes members from government

NIOSH, regulation MSHA, industry Bituminous Coal

Operators Association BCOA, labor United Mine Workers of America UMWA, and professional associations.

Participation in the surveys was voluntary for the plants, but

100% of the plants contacted participated.

B. Equipment and process

Nearly all coal preparation plants employ the same basic

coal cleaning processes of crushing, screening, separation,

flotation, and dewatering drying. In general, the raw feed

enters the plant on one of the upper floors, and flows downward by gravity through the cleaning process. Eventually, the

clean coal and waste are deposited on separate belts on one

of the lower floors for removal to the clean coal storage area

and refuse area, respectively. Finally, the bottom floor usually contains the sumps and pumps used to recycle water and

separation media back to the appropriate equipment on the

upper floors. Specific equipment found in most of the plants

included sieve bends, magnetic separators, froth flotation

cells, banana screens, drain and rinse screens, deslime

screens, heavy media cyclones, coal spirals, centrifuges,

clean coal and refuse conveyors, crushers, heavy media vessels, vacuum filters, and pumps. In addition, since compressed air is used in the cleaning process, the plants have

compressor rooms.

C. Dosimetry

Quest model Q-400 dosimeters were mounted on workers just prior to the start of the shift. Microphones were installed at mid-shoulder as recommended by MSHA,12 and

contained a wind screen. The Q-400 is a type II instrument

and has two independent dosimeters that were programmed

to log A-weighted LAV,LMAX,LMIN, and LPK Ref. 13at 10-s

intervals. One dosimeter was set to record the MSHA permissible exposure limit PELand the other measured the

8-h, A-weighted, equivalent sound level, LAeq8, which could

be used for subsequent analyses. LTWA8represents the

A-weighted constant sound level that over 8 h would result

in the recorded shift dose.13 The MSHA PEL uses a 5 dB

exchange rate ER, a 90 dBA criterion level LC, a 90 dBA

threshold LTHlevel, and an 8 h criterion time, TC. Thus, a

full day’s exposure 100% dosewould occur if a worker is

exposed to a steady noise at the 90 dBA criterion level for

8 h. Mean shift time, T

 ̄, and dose, D ̄, were computed for the

measured data. The mean LTWA8was computed from the

average dose as

LTWA8= LC + Q log D ̄

100, 1

where LC= 90 dBA is the criterion level, Q

=logER/log2or 16.61 for the 5 dB ER. Since shift

times varied from plant to plant, the average LAV was also

computed as

LAV = LC + Q log 8D ̄

100T

 ̄

 . 2

The above means were used to compute following standard

deviations: SLTWA8

,ST, and SLAV.

Asymmetric standard deviations for dose were computed from LTWA8values as

SD

± =  100T

 ̄

TC

10LTWA8±SLTWA8

−LC/Q. 3

This unconventional practice prevented the dose dispersions

from being negative, as would occur if computed in the usual

way. The M samples of LAV data were also postprocessed to

produce cumulative dose plots for each shift as

Dk= 100

TS

TC



i=1

k

10LAVi−LC/Q, 4

where TS= 10 s is the sampling time, and i,k are discrete

time indices.

D. Task observations

Detailed time-at-task observations were conducted for

each job classification. Note that for most jobs, the worker is

required to move throughout the plant performing various

tasks. A crew of technicians and mining engineers monitored

three shifts for each job classification. As the worker moved

or changed activities, the shift time and activity were logged,

along with any comments from the observer. The observation

resolution can be as fine as 10 s, as with the dosimeter logging. These observations were later used to determine the

noise exposures for certain activities as well as exposures

within the plant.

198 J. Acoust. Soc. Am., Vol. 121, No. 1, January 2007 Vipperman et al.: Noise survey in coal preparation plants
E. Equipment noise profiling

Sound level measurements Leqwere made throughout

the plant in order to determine the distributed noise levels. A

measurement grid was established, with measurements occurring approximately every 1.5–6 m, depending upon the

density of the noise sources within the floor. Two different

instruments were used to measure data: Quest model 2900

type IIsound level meters SLMand/or a Brüel and Kjær

B&K2260 investigator type I. Measurements typically

included A-weighted, C-weighted, and linear overall sound

levels and linear 1/3-octave band levels, which were

A-weighted in postprocessing. The instruments were

mounted on a tripod, with the microphones 1.5 m from the

floor approximate ear height, angled at 70° from horizontal,

and facing the noise source as per the manufacturer’s recommendations. A slow response time with an averaging time of

30 s was also employed. The instruments were fieldcalibrated at the start and end of each shift and undergo

annual NIST-traceable calibrations. Postprocessing included

spatially interpolating linear sound pressures to create noise

contour plots, and determining the average Leq in the vicinity

of specific types of equipment. Sound levels were taken from

grid points nearest to the equipment, typically within a few

meters. Average values were computed from linear Leq quantities as was done in Eq. 2. Standard deviations are computed from the dBA levels.

F. Reverberation time measurements

Reverberation time measurements were conducted in

two typical plants while they were shut down for extended

maintenance. The measurements could be used to determine

whether treating walls of the plant with absorptive materials

could be expected to significantly reduce the noise levels in

the plant. Tests were completely automated in accordance

with the ISO-140 standard14 by the BZ7404 building acoustics software package installed on the B&K 2260 Investigator. A B&K 2716 bridging amplifier drove the B&K 4296

omnidirectional sound source in order to generate high levels

of pseudorandom noise at one location of the plant floor. At

another floor location, the B&K 2260 Investigator measured

the decay in all 1/3-octave bands after abruptly switching off

the noise source. The instrument measures either T20 or T30

reverberation times time for the noise to decay 20 or 30 dB,

respectively, in each 1/3-octave bandand extrapolates to the

more characteristic T60 reverberation time time to decay by

60 dB. Three combinations of source/receiver locations

were measured on each floor where either the source or the

receiver was moved between measurements.14 At each

source/receiver location a total of 5 decay times were measured and averaged together by the instrument to find the

average T60 time.

The Sabine formula15 was used to compute the overall

change in reverberation times when absorptive treatments

covered varying percentages of the walls. These were converted to the Sabine absorption coefficient, , by also taking

into consideration the room volumes and surface areas. Next

the room constants, both with R1and without R0acoustical treatments, were computed from the absorption coefficients. Assuming distances far from the source, the theoretical maximum reduction in sound pressure was computed as

LP  − 10 log

R1

R0

. 5

III. SURVEY RESULTS

A. Coal preparation plant characteristics

All the plants were of similar construction; steel I-beams

covered by either single ply corrugated steel sheeting or twoply sheeting with insulation in between the plies, and concrete or steel grating floors. Table I summarizes the specific

characteristics of each plant, including raw feed capacity,

reject rock, number of floors, and total square footage. Reject is potentially important since rock is harder than coal

and thus typically produces more noise.

B. Worker classifications

In general there are four specific job classifications. The

first class of worker is the “control room operator,” who is

positioned in the enclosed control room and is surrounded by

video monitors and alarms. Typically, this person remains in

the control room the entire shift. A second classification is a

“mechanic/electrician.” This worker is responsible for equipment maintenance throughout the plant and surrounding facilities. His time in the plant varies depending on plant maintenance needs during a particular shift. The worker that

typically spends the entire shift, except for lunch and breaks,

in the plant is the “plant attendant.” This worker’s duties can

be located throughout the entire plant or on specific floors.

This person is generally responsible for checking equipment

operation, making measurements of process variables, and

cleaning. The fourth job class is the “utility worker” whose

job is to help the plant attendants or mechanic/electricians.

Effort was made to determine the total number of workers in

each occupation class for the eight plants, and is presented in

Table II. Note that the same workers may have been surveyed across different shifts. Also, if a sample was considered atypical e.g., partial shift monitoring, it was not included in the analysis.

TABLE I. Characteristics of coal preparation plants surveyed.

Plant

No. State

Raw feed

TPHa



Reject

%

No. of

floors

Total floor

area, ft2

1 PA 1000 31 8 58 200

2 WV 2000 52 6 81 850

3 PA 2000 33 12 142 650

4 VA 1000 27 7 63 350

5 PA 1000 21 10 51 400

6 KY 300 38 5 15 505

7 KY 2000 51 5 75 084

8 IL 1500 38 5.5 31 582

a

Tons per hour.

J. Acoust. Soc. Am., Vol. 121, No. 1, January 2007 Vipperman et al.: Noise survey in coal preparation plants 199
C. Worker noise exposure

Table III provides a statistical summary for three of the

job categories, including the number of samples, N, mean

dose, and asymmetric standard deviation of dose. The

Mechanic/Electrician job class did not have enough samples

N= 3to be statistically relevant, and hence statistical data

are not reported for this class.

D. Noise profiles

The noise was categorized as continuous with high overall levels generally experienced throughout the plant. Figure

1 presents a noise contour plot of the overall A-weighted Leq

measurements from a representative floor. Levels are consistently high and range from 95 to 100 dBA, as indicated by

the scale to the right of the figure. Figure 2 is an example of

a much larger floor, with varying-noise levels 87–104 dBA

and a specific area of higher noise caused by a group of

clean-coal screen-bowl centrifuges. Each plant typically had

one or two floors with more modest levels 90 dBAof

noise. A fairly typical 1/3-octave band spectrum of the noise

in the vicinity within 1–2 mof a raw coal screen is shown

in Fig. 3, where the linearly weighted data are represented by

the black bars and the A-weighted data are represented in

grey. Screens are found to have very relatively high sound

levels.

Figure 4 provides information on the average equivalent

sound levels recorded in the vicinity of various pieces of

equipment surveyed in the plants. They are sorted from quietest to loudest. The equipment type and total number of

unique locations within the eight plants where each type of

equipment was found Nare given in the x axis labels. Standard deviations are also included on the plot where appropriate.

E. Dose/source relationships

The logged LAV values recorded by the dosimeter were

converted to a cumulative dose plot using Eq. 4. The resulting plots were then annotated using the information ob

-tained from the task observations. A representative cumulative dose plot for a utility man serving as a plant attendant is

shown in Fig. 5 and a cumulative dose plot for a mechanic is

provided in Fig. 6. No equivalent plot is given for the control

room operator, since their exposures are generally small.

F. Reverberation time and noise control

The measured areas and volumes for the six measured

floors are given in Table IV. Each floor varies in the number

and type of equipment, as well as room surface area and

overall volume. It is typical for floor plans to get smaller

with respect to the building height. Also given in the last

column of Table IV, is the range for the average absorption

coefficient for each floor in the bandwidth of 250–4000 Hz.

Figure 7 graphically depicts the T60 and absorption coefficient calculations across the 1/3 octave bands for one of the

floors.

Sample calculations based on Eq. 5were made to determine the potential effectiveness of adding absorptive materials to the walls of the six measured plant floors. The

results were predicted from applying an EAR E-100SM

aluminum-faced, urethane-foam, absorbing-material to various percentages 15%, 40%, and 60%of floor surface areas.

The absorption coefficients for the material are 	0.81, 0.61,

0.73, 0.71, 0.69
 in the 	250, 500, 1000, 2000, 4000
 Hz

1/1-octave bands, respectively. In many cases much of the

ceiling and wall area was amenable to being covered with

material, making the 60% area coverage practical. Predicted

reductions range from 0.9 to 10.6 dB across the bands. The

reductions were then arithmetically averaged across the 250–

4000 Hz 1/1-octave bands and are presented in Fig. 8.

IV. DISCUSSION

Dose and noise survey data from the eight coal preparation plants suggest that overexposures to noise can easily

occur, particularly in plant attendants. Plant attendants are

found to experience significantly higher exposures than other

job categories when examining the data given in Table III.

The mean value nearly equals the citable range and one stanTABLE III. Data summary for job classes.

Job class N D ̄%SD

+ %SD− %T

 ̄

i hLTWA8dBALAV dBA

Plant attendant 22 129 165 101 8:49 91.1 92.0

Control room operator 7 25.4 60.6 17.9 10:23 80.1 78.2

Utility man 7 66.6 102 39.6 9:31 85.5 85.8

TABLE II. Plant jobs surveyed by plant.

Number of employees number surveyed

Occupation Plant 1 Plant 2 Plant 3 Plant 4 Plant 5 Plant 6 Plant 7 Plant 8 Total

Control Rm. Oper. 3031413041323122258

Elec./Mech. 604017390210103020633

Utility Man 9030949081001023418

Plant attendants 319333324332197244625

Total Workers 2111943311242375742688917544

200 J. Acoust. Soc. Am., Vol. 121, No. 1, January 2007 Vipperman et al.: Noise survey in coal preparation plants
dard deviation is more than double the citable dose. Citations

are not issued until the dose exceeds 132%, allowing for the

type II accuracy 2 dBof most noise dosimeters. In contrast, it is found that the control rooms can be considered a

“quiet area,” having only a 22.4% average dose with a positive standard deviation of 60.6% such that D ̄ +SD

+ 132%.

The highest recorded dose for all eight control room operators is 99.6%, which also occurred for the longest shift of

12:26 hours:minutes. In addition, this particular subject

was atypical in that he had responsibilities that required him

to periodically leave the control room and work in noisier

environments. The doses for all utility men surveyed were all

FIG. 1. Example of a high noise floor

containing drain and rinse D&R

screens Plant 5.

FIG. 2. Example of a varying noise

floor.

J. Acoust. Soc. Am., Vol. 121, No. 1, January 2007 Vipperman et al.: Noise survey in coal preparation plants 201
below 105% and averaged 63.5%. Doses within a single

positive standard deviation are just below the 132% citable

level.

Some of the variability in doses was a result of the varying shift durations. Some plants work a standard 8 h shift,

while others work a 12 h shift. This fact was reflected in the

relatively large standard deviations in shift durations for the

control room operator 2:04, plant operator 1:59, and utility man 2:11. The three mechanics surveyed all worked 8 h

shifts, producing a relatively low standard deviation of 0:09.

The time-weighted averages given in Table III provide a normalized representation of the measured doses, since they

were defined as the equivalent continuous 8 h exposure levels that would result in the recorded shift dose. A 100% dose

is equivalent to LTWA8=LC= 90 dBA. LAV measurements are

independent of measurement duration and may be compared

across work shifts of different lengths. Note that LAV

=LTWA8for a 100% dose over an 8 h shift and LAV

LTWA8for shifts under 8 h and vice versa.

The high variability in the noise dose data 60.6%

SD

+ 411%for each job suggests that the practice of

single-shift monitoring is not adequate for characterizing

doses for coal preparation plant workers. The variance can be

attributed to several factors including plant processes, shift

time, plant location, equipment serviced, individual worker

traits, production, age of the plant, and plant construction.

Another important variable that must be taken into consideration was the quality of plant maintenance e.g., effects of

“squeaky belts”, which was found to vary considerably between plants. Equipment noise levels were found to be approximately 8 dBA higher in two such cases. With the exception of shift time, no attempt was made to quantify the

effects of these variables.

The characterization of noise sources in the plants was a

complicated task for several reasons. First, the large number

of pieces of equipment and their close proximity to each

other made separating specific noise sources difficult at

times. Next, the openness of the building allowed noise to

propagate between floors. Finally, the measured noise came

from multiple air-borne and structure-borne paths. Air-borne

noise was present as direct noise, generated by the equipment, the process, and motors, and as reflected noise from

the reverberant field building walls, floors, etc.. Structureborne noise paths resulted from equipment vibration and

transfer of that vibration to the buildings structural components, which in turn radiate into the surrounding area. Noise

profiles consisting of area noise sampling on noise contour

plots for all plant floors revealed areas of high and low noise

levels and permitted identification of the equipment generally responsible for the noise. Although levels varied considerably throughout the plant, the patterns of noise in any one

location were judged to be stable.

Figure 4 provides information about the range of sound

levels within the working area surrounding a particular type

FIG. 3. Linear and A-weighted 1/3-octave bands measured near raw coal screens.

FIG. 4. Average overall equivalent sound levels in the

vicinity of various types of mining equipment with 90

percentile confidence bounds shown.

202 J. Acoust. Soc. Am., Vol. 121, No. 1, January 2007 Vipperman et al.: Noise survey in coal preparation plants
of equipment. Average equivalent sound levels measured in

the vicinity of all pieces of equipment are 90 dBA, except

the control room and the motor control center/electrical

rooms unmanned. Thus, spending an 8 h shift in close

proximity to most all coal processing machines would result

in 100% or more dose accumulation. Eleven of the machines

produce overall sound levels above 95 dBA and two are

above 100 dBA sieve bends, 106.5 dBA and a coal silo fan,

108.2 dBA, which would accumulate dose at a much greater

rate.

Noise contour plots were provided to the management of

each plant. This information can be used to develop a plan

for engineering or administrative controls that will mitigate

or avoid worker exposures to these areas. Figures 1 and 2

illustrated that levels tend to be generally high enough

throughout the plant, and that there are a few “quiet” areas

within the plants where workers could spend a whole shift

without overexposure. The wide range of levels 87–

104 dBAin Fig. 2 and the specific area of higher noise near

the centrifuges at the top of the figure illustrate that the noise

from one type of equipment can influence the sound field in

the adjacent area containing quieter equipment. Where such

influence was obvious, data were omitted from the averages

in Fig. 4, but otherwise the effects would be difficult to quantify, since the continuous circuit operation of the plants does

not permit equipment to be operated individually while

loaded with coal. Overall A-weighted levels can easily exceed 100–110 dBA in the vicinity of equipment requiring

attention, illustrating the importance of properly maintaining

equipment.

The typical 1/3-octave band noise spectrum given in Fig.

3 illustrates that the noise was dominant in the lowfrequency bands, particularly the 16 and 31.5 Hz 1/3-octave

bands, which are the subharmonic and driving frequency of

most electric motors throughout the plant. Linearly weighted

sound levels on most floors were routinely over 100–110 dB

in the 16 and 31.5 Hz bands. While this high amplitude,

low-frequency sound can be uncomfortable, it is the

A-weighted sound that is currently used to predict NIHL.13,16

The A-weighted machinery noise has the highest contributions from 500 to 4000 Hz, which are also the bands that are

most contributive to hearing loss.

The cumulative dose plots in Figs. 5 and 6 corroborate

that dose is accumulated at the highest rates when working in

the vicinity of equipment. No accumulation of dose indicates

that the noise levels were below the threshold for the MSHA

PEL. The utility man in Fig. 5 spent much of his shift on

floors 1 and 2, and received a similar rate of dose while on

each floor, albeit at a higher dose while unclogging drains

between 11:00 and 11:50 and 1:00 and 1:35. Although the

mechanic in Fig. 6 received only an 18% dose, the plot reveals that he received nearly 45% of his dose while repairing

the raw coal crusher on floor 9 and approximately 25% while

greasing belt rollers on floors 11 and 12. Had he spent more

time in these or other loud areas, his shift dose would have

been considerably greater.

Reverberation time measurements Table 4may also be

helpful in determining if treating the entire plant would be

helpful for reducing noise levels and exposures. Of the six

floors, floor 5 from the first plant data not presentedhad the

highest absorption coefficients 0.185–0.372, which was

partially attributable to a layer of sand that had accumulated

from sandblasting activities. The second plant had smaller

absorption coefficients in general  ̄

0.087– 0.197than

the first plant  ̄

0.148– 0.372. Floor 10 of the second

plant was the acoustically hardest floor, with absorption coefficients ranging from 0.087 to 0.141. The 1/3-octave measured T60 and  ̄

 spectrums for this floor are given in Fig. 7.

Note from Fig. 7 that the reverberation time decreases and

TABLE IV. Surface areas, volumes, and average absorption coefficients for

each measured floor.

Plant Floor

Surface

area m2



Volume

m3

Avg. absorp. coeff.

0.25–4 kHz

3 5 4400 9400 0.185–0.372

3 8 2300 3900 0.148–0.280

3 11/12 1500 2700 0.150–0.187

5 3 970 1040 0.103–0.197

5 7 1100 1400 0.119–0.182

5 10 1100 1400 0.087–0.141

FIG. 5. Cumulative dose plot for utility man.

FIG. 6. Cumulative dose plot for mechanic.

J. Acoust. Soc. Am., Vol. 121, No. 1, January 2007 Vipperman et al.: Noise survey in coal preparation plants 203
the absorption coefficient increases with frequency, since absorptive materials, whether inherent or introduced, work best

at high frequencies.

The plant floors were found to be acoustically “hard” to

“medium,” and thus some improvements in noise levels were

expected with treatments. Figure 8 shows that predicted reductions can be as high as 8.5 dB. The large predicted reductions are encouraging, however reductions from adding absorptive materials rarely exceed 3–5 dBA in practice.17

Better control than expected was predicted at lower octave

bands, a result of the good low-frequency performance of the

treatment material and relatively small initial absorption coefficients in those bands. Any absorptive materials selected

must hold up to harsh, industrial conditions and meet flammability requirements governed by MSHA.

V. CONCLUSIONS

Noise levels and worker noise exposures in eight coal

preparation plants were assessed as part of a cross-sectional

survey of noise in the mining industry being conducted by

NIOSH. Assessment techniques included noise dosimetry,

task observations, contour mapping of noise fields, and reverberation time measurements. The maps were provided to

plant management to be incorporated into their noise management programs. Overall noise levels were found to range

from 75.9 to 115 dBA throughout the plant. The open construction of the plant provided many direct paths for noise to

propagate between floors. Most areas of the plant except

control rooms, electrical rooms, and motor control centers

were found to have noise levels in excess of 90 dBA, suggesting the noise overexposure will occur if a full 8 h shift is

spent within the plant. Plant maintenance was found to be an

important concern, with A-weighted levels increasing by

8 dB in two cases as a result of squeaky belts or bearings.

These results are corroborated by the dosimetry and task observations of individual workers, although much higher dose

accumulation rates occur when proximal to equipment. For

most occupations, the shift-to-shift variability in noise dose

is large. Most of the variation is due to differences in exposure levels as the worker moves about the plant or shift

lengths 8 h versus 12 h shifts. Depending upon a worker’s

location, the average dose accumulation rates varied between

0.25– 31% / h with instantaneous values being much higher.

Two of the four plant worker categories plant attendant and

mechanic/electricianhad reported shift doses above 132%

the MSHA citable level. The high variability in dose indicates that the current practice of partial or single shift monitoring for compliance may not adequately characterize

worker noise exposures. Reverberation time T60measurements were performed on six floors from two representative

plants. Floors were found to be fairly acoustically “hard,”

suggesting that absorptive-treatments may provide significant control.

ACKNOWLEDGMENTS

The authors would like to thank the following NIOSH

employees who participated in the data collection activities:

Ellsworth Spencer, Tom Ozanich, Gerald Morrow, and Mike

DiMartino and a very special thanks to Dr. Mary Prince, Mr.

Dennis Giardino, and Mr. John Earshen for their helpful suggestions. 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.

1

John R. Franks, Mark R. Stephenson, and Carol J. Merry, “Preventing

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