AT-EAR NOISE LEVELS UNDER THE HELMET: A FIELD STUDY ON NOISE
EXPOSURE OF YOUNG MOTORCYCLISTS
A. Ali1,3,*, R. M. Hussain2, M. Abdullah1, N. C. Dom1
1Department of Environmental Health and Safety, Faculty of Health Sciences, Universiti
Teknologi MARA, Selangor Malaysia
2Department of Medical Imaging Technology, Faculty of Health Sciences, Universiti
Teknologi MARA, Selangor Malaysia
3Department of Environmental Management and Policy, Faculty of Engineering, Balochistan
University of Information Technology, Engineering and Management Sciences, Quetta,
Published online: 24 February 2018
At-ear noise exposure assessments of motorcyclists, with the function of speed, would be
unsafe as on-road data acquisition has certain constraints including the operations and
portability of appropriate instrument. Currently, there are no standardized protocols and
methods for measuring the noise under motorcycle helmets. Furthermore, standard
permissible noise emission levels for commuter motorcyclists are also not defined. Therefore,
this study was aimed to investigate the motorcycle noise exposure assessments in realistic
environment among young riders. A personal dosimeter was utilized to calculate the daily
noise exposure level (LAeq, 8h) under three different standards including: OSHA-HC
(Occupational Safety and Health Administration, Hearing Conservation), OSHA-PEL
(Permissible Emission Level) and ACGIH/NIOSH (American Conference of Governmental
Industrial Hygienists/ National Institute of Occupational Safety and Health). The study design
consisted of noise assessment of riders (age range:19 to 25 years) at-ear under the open-face
helmet in-realistic situation (main road to the motorway) motorcycling in dry weather
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A. Ali et al. J Fundam Appl Sci. 2018, 10(3S), 218-231 219
Personal dosimeter results (n=52) revealed the average noise exposure level of 93.64 dBA,
92.51 dBA, 95.29 dBA for OSHA-HC, OSHA-PEL and ACGIH/NIOSH respectively. The
mean Time-Weighted Average (TWA) was 76.82 dBA, 75.69 dBA, 85.16 dBA for OSHA-
HC, OSHA-PEL and ACGIH/NIOSH respectively. Under the ACGIH and NIOSH standard,
the TWA for motorcyclists is at hazardous limits, which requires further investigations
associated with health effects on riders. Standardized methods and configurations should be
set for assessing noise exposure related to the motorcycling.
Keywords: Motorcycle noise, Wind noise, Dosimeter, OSHA, ACGIH
Motorcycles are recognized as a convenient form of transport as it causes less damage to the
road surface, lessens traffic congestion and consumes less fuel than motorcars. Motorcycling
carries obvious and some less obvious hazards, where noise exposure and its related health
effects are one of the less obvious hazards (Binnington et al., 1993). Quieter machines have
been developed by the manufacturers with increasingly faster motorcycles, but aeroacoustics
noise stands more important for motorcycling and helmet design (Jordan et al., 2004). The
unavoidable component associated with motorcycling is noise, which has been studied though
numerous studies (Kennedy et al., 2014).
Since late 80’s, it has been noted that motorcycle riders are exposed to noise levels above 90 d
BA at 50 km/h (30 mph), which increases with increasing speed up to 105 dBA at 115 km/h
(70 mph)(Jordan et al., 2004). Just over 20 years, noise has been recognized as hearing hazard
due to motorcycling noise inside the helmet. Motorcyclists’ noise exposure is unique and
greatly influenced by the transmission through the helmet (Kennedy et al., 2014). Numerous
studies investigated the noise sources, such as wind flow around the helmet, the sound of an
engine and the combined windscreen generates interaction that sound at-ear to the rider
(Carley et al., 2011; Jordan et al., 2004). The discrepancies between various motorcycling
speeds and its associated noise exposure reported in previous studies were explained by
Carley et al., (2011) as an external factor such as wind speed, engine, windscreen, helmet type
and riding position.
In reported literature, a difference exists between sound pressure level with a function of
riding speed (Kennedy et al., 2013). Numerous studies adopted varies measurement
techniques under controlled study designs both for on-track and for wind-tunnel tests, while
realistic situation assessments are scarce. The various instruments adopted for this purpose
were: DAT (Digital Recording Tape) (Harvey et al., 2002; Ross, 1989; Kennedy et al., 2011;
A. Ali et al. J Fundam Appl Sci. 2018, 10(3S), 218-231 220
Jordan et al., 2004), SLM (Sound Level Meter) (Carley et al., 2010; Jordan et al., 2004;
Violini et al., 2015), DAQ system (Kennedy et al. 2011)(Kennedy et al. 2013) and multiple
memory noise logging dosimeter (Binnington et al., 1993; McCombe et al., 1993).
Noise measurements inside a motorcycle helmet, while traveling at speeds of up to 120km/h,
is not an easy task (Harvey et al., 2002). Measuring of sound level at various speeds would be
unsafe and on-road data acquisition are problematic due to rider’s safety along with
portability of appropriate instrument. There are no standardized protocols and methods for
measuring the noise under motorcycle helmets (Jordan et al., 2004), while the standard
permissible noise emission level for commuter motorcyclists are also not defined.
Therefore, this study was aimed to investigate the realistic environment motorcycle riding
noise exposure assessment among young riders through personal dosimeter and to calculate
their daily noise exposure level (LAeq, 8h) under three standards: OSHA-HC (Occupational
Safety and Health Administration, Hearing Conservation), OSHA-PEL (Permissible Emission
Level) and ACGIH/NIOSH (American Conference of Governmental Industrial Hygienists/
National Institute of Occupational Safety and Health).
MATERIALS AND METHOD
A field study to assess motorcycling noise under helmet was carried out at Universiti
Teknologi MARA, Puncak Alam campus, Malaysia. The participants were undergraduate
students, aged between 19 to 25 years, who rode the motorcycle as primary means of
transportation. Total participants recruited in the study were 52. Inclusion criteria set for the
study consisted of participants exhibiting helmet-riding behavior and motorcycle capacity
ranging from 100 cc to 150 cc. Study procedure and design was approved by Faculty’s
(Health Sciences) Internal Ethical Committee (600-FSK (PT.5/2)), Universiti Teknologi
At-ear noise exposure level of riders under the helmet during motorcycling was measured by
pocket size dosimeter: 3M Noise ProTM, model: Noisepro DLX, Sound Pro Quest technology.
Sound level calibrator, model: QUEST/Type was used for pre-calibration before each
monitoring session. After the monitoring session, dosimeters were post-calibrated followed
by the transfer of the data into the spreadsheet. Participant’s personal use of motorcycles and
helmets were compensated them with vouchers, which covered fuel consumption and
A. Ali et al. J Fundam Appl Sci. 2018, 10(3S), 218-231 221
participation incentive. All participants wore an open-face helmet with the visor closed as
shown in Figure 1a. A structured questionnaire was used to obtain the general demographic
information of the participants (age, semester and gender), data related to motorcycling
(license no, motorcycle registration no, helmet type, motorcycle brand, engine capacity) and
test day information (weather condition, test starting and ending time and date).
The dosimeter (shown in Figure 1b) used for assessment had simultaneously three virtual
dosimeters settings, which were calibrated on occupational standards for possible comparison
of noise exposure limits associated with motorcycling. Table 1 presents the three integrators
in the instrument with configuration settings of logging interval of one minute, time-weighted
slow and criterion time 8 hours. The virtual dosimeters first and second were based on the
Occupational Safety and Health Administration (OSHA) criteria (Gilbertson and Vosburgh,
2015). The first virtual dosimeter was programmed to noise threshold of 80 dBA, criterion
level of 90 dBA, and an exchange rate of 5 dB, which is based on OSHA-HC requirement.
The second virtual dosimeter was programmed without noise threshold, criterion level of 90
dBA and exchange rate of 5 dB, based on OSHA -PEL. The third virtual dosimeter was based
on ACGIH criteria, programmed with 80 dB threshold, 85 dBA criterion level and the
exchange rate of 3 dB (Code of Federal Regulations Title, 29). Threshold defines the point
where the measured decibel levels will not be included in the dosimeters noise level
calculations. Below the threshold value, the decibel levels are replaced with a value of 0 dBA
(Tingay and Robinson, 2014).
Table 1. Configuration of integrators
Integrators 1 2 3
Exchange Rate 5 5 3
Time Weighting Slow Slow Slow
dB(A) dB(A) dB(A)
Threshold 80 none 80
Criterion Time 8 hrs 8 hrs 8 hrs
Criterion Level 90 90 85
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The motorcyclists normalized 8-hr time-weighted average (TWA) noise exposure was
calculated using Equation I for OSHA-HC and OSHA-PEL virtual dosimeter. Equation II was
used to calculate the third virtual dosimeter (ACGIH) which used 3db exchange rate
(Gilbertson and Vosburgh 2015).
In Equation I, LOSHA,8h is the normalized 8-hr TWA noise exposure and LOSHA, T is the average
noise level (A-weighted) over the time T. In Equation II, LA8hn stands for normalized 8-hr
TWA noise exposure and Leq, T is the average noise level (A-weighted) exposed during the
time period T.
Testing route was UiTM, Faculty of Health Sciences bus station (D1) to UiTM Perdana (D2).
Prior to the testing ride from D1 to D2 and return, participants filed the data questionnaire
followed by the installation of dosimeter as shown in Figure 1c. The total distanced covered
from D1-D2-D1 was approximately 40 km and 46 minutes.
Calibrated dosimeter (114 dBA) small microphone (Type 2) was placed near the entrance of
the rider’s ear canal, so as not to be in-contact with any other part of the ear. The microphone
was attached to a clip to hold the wire to prevent movement, while a thin microphone cord
attached to the dosimeter. A wire cord was drawn from the front of the rider and clipped at the
front by placing the dosimeter instrument in the front basket of the motorcycle. The safety of
the dosimeter was ensured by covering it with a front cover. The helmet was fixed and
buckled tightly to avoid any displacement of wires and microphone.
The test road consisted of adjoining roads and highway (flat, asphalt road). The selection of
this road was between the designated D1- D2 route to meet the purpose of assessing real-time
exposure level encountered by the young riders on daily basis during their commute.
Adjoining roads consisted of curves, road bumps, and traffic signals, while the highway was a
straight road. The traffic flow is generally from low to medium, depending on the peak hours
of the day such as morning 7-8 and 5-7pm. The timing of the test administration was flexible,
depending on the availability of the participants. Riders own motorcycles were utilized, which
were without windscreen and ranged from engine capacity of 100 cc to 150 cc. For the safety
A. Ali et al. J Fundam Appl Sci. 2018, 10(3S), 218-231 223
reasons, the speed could not be standardized for each kilometre travelled, therefore riders
were instructed to follow the inscribed road speed. All test measurements were carried out in
dry weather condition.
On their arrival, dosimeter data was saved as session number followed by turning it off and
uninstallation of the instrument from the rider. Raw data was later transferred to computer
software i.e. 3M Detection Management Software (DMS) to deliver the measurement of each
session’s report. Data measurement included: Start and stop time, device serial number,
device model type, average A-weighted sound level (LAeq), the exchange rate at 5, dose (daily
personal noise exposure), TWA (time-weighted average), SEL (sound exposure level).
Fig.1. Instruments used for field study: (a) Open-face helmet; (b) Dosimeter and calibrator;
(c) Dosimeter installation on the rider
Dosimeter software generated data was tabulated and logged on excel worksheet, and
statistical analysis was conducted using Statistical Package for Social Sciences, IBM SPSS
(Version 22 Inc., Chicago, IL). Descriptive data of session’s duration, means and standard
deviations and maximum and minimum noise level were computed through frequency chart.
The experimental design consisted of standardized distance travelled but each rider completed
A. Ali et al. J Fundam Appl Sci. 2018, 10(3S), 218-231 224
in varied time duration. To normalize the effect of this time difference, 8-hourly time-
weighted average (TWA) noise exposure level was calculated using EQ I and II. The
descriptive statistics for the normalized 8-hr TWA noise exposure were calculated for all the
three virtual dosimeters. The bar charts were plotted for average TWA noise level (dBA)
against three standards.
Table 2 presents the descriptive results of the three virtual dosimeters based on three standard
integrators. The average noise exposure (Lavg) for OSHA-HC was 93.64 d BA (SD=5.37)
ranging from 87.2 to 106.9 d BA. The OSHA-PEL maximum noise exposure was 108.8 d BA
and minimum 83.6 d BA with mean (Lavg) noise exposure of 92.51 d BA (SD = 6.18). The
average noise exposure (Lavg) for ACGIH/NIOSH was 95.29 d BA (SD = 5.62) ranging from
88.8 to 109.8 d BA. The duration of ride ranged between 32 to 61 minutes with mean duration
of 46.98 minutes (SD = 5.84). The 8-hour TWA normalized noise exposures for OSHA-HC,
OSHA-PEL and ACGIH/NIOSH average was 76.82 d BA (SD=5.21; ranging:70.82 - 89.83),
75.69 d BA (SD = 6.03; ranging: 67.03 - 89.74), 85.16 d BA (SD = 5.53; ranging: 78.62-
99.42) respectively. Figure 2 illustrates the comparisons between the three standards average
noise exposure of the participants: (A) OSHA-HC, (B)OSHA-PEL, and (C) ACGIH/NIOSH.
A. Ali et al. J Fundam Appl Sci. 2018, 10(3S), 218-231 225
Table 2. Descriptive analysis of average noise exposure and TWA1 on three standards
93.64 5.37 106.9-87.2
92.51 6.18 106.8-
95.29 5.62 109.8-88.8
46.98 5.84 60-32
8-hr TWA Normalized noise exposure
(OSHA HC) 76.82 5.21 89.83-
(OSHA-PEL) 75.69 6.03 89.74-
(ACGIH) 85.16 5.53 99.42-
A. Ali et al. J Fundam Appl Sci. 2018, 10(3S), 218-231 226
Fig.2. Average noise exposure level of participants on different standards: (A) OSHA-HC2;
(B) OSHA-PEL3; (C) ACGIH4
1 TWA: Time-weighted average
2 OSHA-HC: Occupational Safety and Health Administration-Hearing conversation.
3 OSHA-PEL: Permissible Noise Exposure
4 NIOSH: National Institute of Occupational Safety and Health
Motorcycling average at-ear noise exposure level of the rider under the open-face helmet in
present study was determined to be above 90 dBA on simultaneously all three virtual
dosimeters which is in accordance with previous studies reported (Kennedy et al., 2011)
either on-track assessment (Carley et al., 2011) or through field study on mannequin road
exposures (Kennedy et al., 2011). The average time taken by the riders (n=52) to complete the
test ride was 46.98 minutes which is in accordance to the google map distance/time
calculation, whereas the minimum time utilized was 32 minutes and maximum 60 minutes
which can be attributed to the difference in riding behaviors of the riders. This study consisted
of a large number of riders, which may reflect the average noise exposure experienced by
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motorcyclists through different styles of riding as it has been reported that varying riding
position has different at-ear noise levels to the riders (Carley et al., 2011).
The other factors that influence the noise exposure are different types of helmets used by the
riders, as reported by Ross, 1989 that open face helmets are less noisy with a difference of 7
dB compared to closed-face helmets. Participants in this study wore open-face helmets, but in
case of closed-face helmets the exposure to noise would be much higher than 90 d BA.
It has been also investigated by (Carley et al., 2011) and (Kennedy et al., 2011), that there is a
significant impact of the interaction of helmet with windscreen angle and location on sound
pressure level as well as at-ear noise spectral content. In the current study, the windscreen was
not attached to the participant’s motorcycle.
The studied comparisons on three integrators showed different motorcycle noise exposure
values for a range of different occupational noise exposure standards. The noise exposure in
terms of the sound pressure, to which a rider during the ride would be exposed to, is the same
for all the different integrators. But the average noise level (Lavg) differences between OSHA-
HC (Lavg= 93.64 d BA), OSHA-PEL (Lavg= 92.51 d BA) and ACGIH/NIOSH (Lavg= 95.29 d
BA) demonstrated clearly how a simple variance in the configuration of the integrators can
produce significantly different outcomes. Such differences are attributed to the effects of the
opposing threshold levels, exchange rates, and criterion levels, which combines to provide
different results. The lowest level recorded was 83.6 dBA on OSHA-PEL and the highest
level was recorded at 109.8 dBA on ACGIH/NIOSH standard. This emphasizes the need for
establishing common and standardized measuring protocols for assessing motorcycle noise
exposure levels. The 8-hour TWA average noise exposure above the permissible noise level
was 85.16 dBA for ACGIH/NIOSH standard, which represents a hazardous level for young
Previous studies related to motorcycle noise measurement did not quote the standards of the
studied measurement, therefore, the present results cannot provide a cross analysis. Realistic
situation based noise assessment has not been conducted with larger sample size, besides the
study conducted by Ross, (1983), where he reported differences in sound levels at same speed
while riding in town and motorway and on open roads, also motorcycling leads to increased
noise exposure in closed-face helmet as compared to open-face helmet. Ross also reported
that wet road exposes higher noise levels than dry roads as assessed by DAT method. All
assessments in this study were conducted under dry weather conditions, but hypothetically it
can be presumed that under wet weather conditions noise exposure levels would be greater
than dry weather results.
A. Ali et al. J Fundam Appl Sci. 2018, 10(3S), 218-231 228
Noise level above 80 dBA with continuous exposure over an extended period is referred as a
quantifiable risk of hearing damage (McCombe et al., 1994). The temporary hearing threshold
(THTS) is defined as a loss of hearing sensitivity after noise exposure. THTS recovery to
hearing to pre-exposure level depends on the noise spectral content, age of the person
(listener) and level of exposed noise (Quaranta et al., 1998). Periods of noise exposure cause
the transition of THTS to a permanent hearing threshold shift (PHTS), which is defined as the
characteristics of noise-induced hearing loss (NIHL). NIHL may occur from one off-loud
noise exposure such as an explosion, but more commonly it is caused by repeated exposures
to multiple noise doses or continuous loud sounds over a longer period of exposure time, such
as wind noise during motorcycling. The riders noise exposure level is at sufficient level for
developing THTS, but the relevant literature presents inadequate data which has focused
merely on occupational rider’s auditory assessment, whereas, young riders hearing status has
never been investigated. High noise exposures can affect the hearing of such exposed
population that can suffer in hearing sensitivity with the reduction of 30db or more (Kennedy
et al., 2011) and possible distraction (Carley et al., 2010). The hearing ability acts as an early
warning system and swiftly redirects our vision and this gazing shift is critical to assess the
location, direction of travel and speed of approaching vehicles (Brown and Gordon, 2011).
In the literature little work is available on the nature and sources of noise exposed to riders
and its effects other than hearing disabilities, particularly to occupational motorcyclists
(Kennedy et al., 2011). It was shown that high to moderate noise levels hindered reaction
times, impaired attention and reduced perceptual and behavioral response effectiveness
(Brown and Gordon, 2011). It was reported that virtual stimulus paired with an auditory cue
results in more accurate visual perception, increased the risk of accidents and increased level
of stress (young riders)(Perroti et al., 1990; Ali et al., 2016; Ali et al., 2017).
The strength of the study is the larger sample size (participants) and real-time motorcycling
noise exposure assessment on young riders, which has never been investigated. Secondly, it
has provided the baseline of different standards for motorcycling noise exposure levels and
TWA associated with it.
Limitation of this study was non-utilization of other equipment’s such as aerometer and
webcam digital recorder due to safety constraints for assessing the wind speed outside the
helmet and the riders riding position.
A. Ali et al. J Fundam Appl Sci. 2018, 10(3S), 218-231 229
Findings in this study show that the young motorcycle riders are exposed to noise above the
permissible levels based on 8-hourly TWA ACGIH and NIOSH standard. The average noise
exposure level ranged above 90 d BA under three integrators, which showed high noise
exposure associated with motorcycling among young motorcyclists. The differences among
different standards emphasize the need for established protocols and standards for assessing
the noise exposure associated with motorcyclists. Further studies will embark the risk factors
associated with high noise exposures to the rider’s health.
The study was supported by CORE Shah Alam and Faculty of Health Sciences, UiTM
Selangor, Puncak Alam Campus under Award Numbers 600-RMI/DANA 5/3 LESTARI
(3/2015) and 600-RMI/MYRA 5/3 LESTARI (0016/2016). Special thanks to David Judd and
Farhana Ramli for assembling the participants at the test site and handling the installation of
the dosimeter to the riders.
Ali, A., Dom, N.C., Hussain, R.M. and Abdullah, M. (2017). Effect of motorcycling on
salivary noise-induced cortisol among young motorcyclists. Environment-Behaviour
Proceedings Journal, 2(6):269–277.
Ali, A., Karuppannan, S., Hussain, R.M., Rajan, S., Abdullah, M., Ikhwan, R. and Chinna, K.
(2016). Epidemiological root cause analysis of noise and physio ‐ psycho impacts related to
motorcycle road accidents. Journal of Scientific Research and Development, 3(5), pp.150–
Binnington, J.D., Mccombe, A.W. and Harris, M. (1993). Warning signal detection and the
acoustic environment of the motorcyclist Warning signal detection and the acoustic
environment of the motorcyclist. British Journal of Audiology, 27(6): 415–422.
Brown, C.H. and Gordon, M.S. (2011). Motorcycle Helmet Noise and Active Noise
Reduction. The Open Acoustics Journal, 4(2): 14–24.
Carley, M., Kennedy, J., Walker, I. and Holt, N. (2011). The experimental measurement of
motorcycle noise. In Proceedings of Meetings on Acoustics 161ASA, 12(1): 040002.
Carley, M., Holt, N. and Walker, I. (2010). Noise mechanisms in motorcycle helmet noise.
In Proceedings of Meetings on Acoustics 159ASA, 9(1): 040005.
Gilbertson, L.R. and Vosburgh, D.J. (2015). Patrol Officer Daily Noise Exposure. Journal of
A. Ali et al. J Fundam Appl Sci. 2018, 10(3S), 218-231 230
occupational and environmental hygiene, 12(10): 686-691.
Harvey, H.D., Hetherington, J.O., Woodside, A. and Jordan, C. (2002). Noise induced hearing
loss in motorcyclists. Publication of: Association for European Transport.
Jordan, C., Hetherington, O., Woodside, A. and Harvey, H. (2004). Noise induced hearing
loss in occupational motorcyclists. Journal of Environmental Health Research, 3(2): 70–77.
Kennedy, J., Carley, M., Walker, I. and Holt, N. (2013). On-road and wind-tunnel
measurement of motorcycle helmet noise. The Journal of the Acoustical Society of
America, 134(3): 2004-2010.
Kennedy, J., Holt, N., Carley, M. and Walker, I. (2011). Spectral filtering characteristics of a
motorcycle helmet. In Proceedings of Meetings on Acoustics 161ASA, 12(1): 040001.
Kennedy, J., Holt, N., Carley, M. and Walker, I. (2014). The influence of the acoustic
properties of motorcycle helmets on temporary hearing loss in motorcyclists. Acta Acustica
united with Acustica, 100(6): 1129-1138.
McCombe, A.W., Binnington, J. and McCombe, T.S. (1993). Hearing protection for
motorcyclists. Clinical Otolaryngology, 18(6): 465-469.
McCombe, A.W., Binnington, J. and Nash, D. (1994). Two solutions to the problem of noise
exposure for motorcyclists. Occupational medicine, 44(5): 239-242.
Occupational Noise Exposure, Code of Federal Regulations Title 29, P. 1910. 9. subpart G.
Perrott, D.R., Saberi, K., Brown, K. and Strybel, T.Z. (1990). Auditory psychomotor
coordination and visual search performance. Attention, Perception, & Psychophysics, 48(3):
Quaranta, A., Portalatini, P. and Henderson, D. (1998). Temporary and permanent threshold
shift: an overview. Scandinavian audiology. Supplementum, 48: 75-86.
Ross, B.C. (1989). Noise exposure of motorcyclists. Annals of Occupational Hygiene, 33(1):
Tingay, J. and Robinson, D. (2014). A practical comparison of occupational noise standards.
In INTER-NOISE and NOISE-CON Congress and Conference Proceedings, 249(5): 2600-
Violini, D.G., Peña, R.S.S. and Velis, A. (2015). Time-varying noise control in motorcycle
helmets. Acoustical Science and Technology, 36(4): 333-335.
A. Ali et al. J Fundam Appl Sci. 2018, 10(3S), 218-231 231
How to cite this article:
Ali A, Hussain R M, Abdullah M, Dom N C. At-ear noise levels under the helmet: a field
study on noise exposure of young motorcyclists. J. Fundam. Appl. Sci., 2018, 10(3S), 218-