4th International Conference on Advances in Civil Engineering 2018 (ICACE 2018)

19 –21 December 2018

CUET, Chittagong, Bangladesh
www.cuet.ac.bd

ASSESSMENT OF NOISE LEVEL AND ITS IMPACTS ON HEALTH

IN DIFFERENT INDUSTRIES LOCATED IN KHULNA CITY

D. Banik1, M. S. Islam2 & M. H. Mohaimin1*

1
Undergraduate Student, Department of Civil Engineering, Khulna University of Engineering &
Technology, Khulna-9203, Bangladesh
2
Professor, Department of Civil Engineering, Khulna University of Engineering & Technology,
Khulna-9203, Bangladesh
*Corresponding Author: hasibmohaimin@gmail.com

ABSTRACT
Noise pollution is an alarming environmental breakdown issue nowadays. Recent industrialization
around the world caused an abrupt increase in noise level compared to the past. This study aims at the
industrial noise pollution and health effects of it on workers in various industries. Five different types
of industries around Khulna city were selected and investigated thoroughly. Sound level was measured
by an environmental meter and noise pollution indices L10, L50, L90, NC, NEI, Leq, and Lnp were
calculated. Two different questionnaire surveys were carried out for workers in each industry and for
families living adjacent to the industries. It has been seen that the jute and power generation industry
exceeds the 90 dB noise level limit described by OSHA. According to the questionnaire survey, 68%
of total 75 workers had headache, 50.67% were annoyed, 29.33% were suffering from insomnia and
33.33% feel dizziness due to this noise. However, a Chi-square test was conducted to check the
significancy of the effect of noise on worker’s health. With a significance level of p ≤ 0.05, chi-square
test shows that the physiological and psychological effects of this noise including annoyance, headache,
nervousness, dizziness and speech interference are statistically significant than insomnia and
stressfulness.

Keywords: industrial noise, noise pollution indices, health risk of noise, noise standard, questionnaire
survey on noise pollution

INTRODUCTION
Sound is a fundamental kind of energy which is produced by the oscillation and vibration of the
particles. It remains pleasant until it doesn’t create disturbance in usual life. Today’s world is an
improved, civilized and industrialized world. But it’s a matter of fact that industrialization and
civilization came up with abnormal increase of sound level upon human race. When sound level exceeds
a certain limit beyond human’s tolerance, it is called noise rather than normal sound. Noise pollution
has increased with an alarming rate in last 100 years and it’s doubling after every ten years (Pandey,
1992). As the problem is being more severe day by day, necessary steps must be followed to mitigate
the noise pollution and its effects on human body as well. Noise pollution assessment in various
countries including the treatment is being conducted with great importance (Kovalchik, Matetic, Smith,
& Bealko, 2005). Many experts are forced by this minacious pollution issue to sit together and sort this
problem out (Jansen G., 1992). For a developing country like Bangladesh, the amount of noise pollution
occurring in different sectors mainly in industries are comparatively high and rate of assessing noise
level with efficient noise removal facilities is comparatively low. Industries create a huge noise
pollution with its rotors, wheels, cutting machine, electrical machines, driller, crusher (Al-dosky, 2014).
As for Bangladesh, Khulna is a city with numerous industries of various categories. This study was
conducted to picturize the condition of noise pollution in different types of industries located in Khulna
city and to check if the sound level exceeds the permissible limit of sound level which is 90 dB described

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by Occupational Safety and Health Administration (OSHA). This study also shows the effect of noise
pollution on worker’s health and on adjacent families who work in and live around of these industries.
For Bangladesh, the assessment of noise level and removal of workplace noise pollution is very needy
at this time. This study opens a scope to assess the sound level of different workplaces subjected to
noise pollution and to take necessary measures to control the increasing noise level.

METHODOLOGY

Study Area
Five industries of different categories were selected around Khulna city, Bangladesh. The main
categories were electrical equipment, cement, heavy metal, agriculture-based and power generation
industries. The industries are located at khalishpur, lobon chora, shiromoni and shipyard road on the
bank of Bhoirob river of Khulna. This study was conducted during the month of April, 2018.

Fig. 1: Industrial areas of Khulna City

Measurement of sound pressure level in industries

The sound level of different locations of various industries was measured by a multi-functional
environmental meter (Model: DT-8820) in decibels. The environmental meter was held at a height of
human ear for several minutes at different spots where the movement of workers and working
magnitude was high. The data was recorded from 8 am to 8 pm each day at a specific industry. Ten
spots of each industry were marked and fixed to repeat the sound measurement at every hour for at least
five minutes. The average sound level of this ten locations at a specific hour shows the overall sound
pressure level of that industry at that hour.

Noise Pollution Indices

Various noise pollution indices like L10, L50, L90 were computed based on gaussian percentile to obtain
the noise level of each industry and to express the magnitude of noise with various important terms like
Noise Climate (NC), Equivalent Continuous Noise Level (Leq), Noise pollution level (Lnp) and Noise
Exposure Index (NEI) (Tripathi et al., 2006). The following equations are used to compute noise
pollution indices,
NC = L10 - L90 (1)
Leq = L50 + [(NC)2/60] (2)
Lnp = Leq + NC (3)
NEI = (t1 / T1) + (t2 / T2) + .......... + (tn / Tn) (4)

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Where, L10 is the sound level exceeding 10% of the total measured time or peak sound level, L50 is the
sound level exceeding 50% of the total measured time or mean sound level and L90 is the sound level
that exceeds 90% of the total read time or residual sound at the background of the workplaces; t1 to tn is
the actual limit of exposure of a corresponding sound level where T1 to Tn is the permissible limit of
exposure of a corresponding noise level. If the value of NEI is greater than 1 in any spot during a
specific hour, the noise exposure level is considered to be as excessive (Hunashal & Patil, 2012).

Questionnaire survey
Two different questionnaire surveys were conducted among the workers and families living just near
the industries to understand the noxious effects of noise on their health. The survey on workers
contained thirty (30) questions about their gender, age, working year, knowledge of noise pollution,
educational background, working hour and shift, responsibilities of industrial authority towards them,
psychological and physiological effects of noise etc. Fifteen (15) workers of an industry were selected
arbitrarily for this questionnaire program. Five (5) families living adjacent to each industry were
questioned about their living year at those areas, physiological and psychological problems, noise effect
on schools nearby and knowledge of permanent hearing loss etc. Physiological and psychological
effects on workers and families include the problems of insomnia, dizziness, annoyance, headache,
disturbance to the peace of mind, nervousness, stressfulness, speech interference, heart problem etc.

Statistical Analysis
All the measured data of sound level at different industries and questionnaire survey data was stored in
Microsoft Excel 2013. Statistical Package for Social Scientists (SPSS) and Chi-square test were opted
for understanding whether the noise effect on worker’s health is significant or not.

RESULT AND DISCUSSION

Noise level measurement

The number of the surveyed industries according to their types, noise level range and mean noise level
in these industries are demonstrated in table 1.

Table 1: Different type of industries, their noise range and mean noise level for 12 hour read-time
Industrial group No. of industry Noise level range Mean noise level
83.63
Electrical Equipment (Cable) 1 80.6~86.67
73.79
Cement Manufacturer 1 72.44~74.98
80.32
Heavy Metal (Shipyard) 1 69.72~88.15
90.78
Agriculture (Jute) 1 88.07~92.59
92.53
Power Generation (Electricity) 1 88.45~96.23

Table 1 interprets that the maximum noise is produced by the power generation industry followed by
jute industry, cable industry, shipyard industry and cement factory. Different noise pollution indices
such as L10, L50, L90, NC, NEI, Leq, and Lnp were calculated for power generation industry and shown in
Figure 2. Figure 2 demonstrates the overall noise atmosphere of a typical industry based on the noise it
produces every day at a specific 12-hour working period interval (8am to 8pm). It shows that the
maximum L10 was observed during working hour as 103 dB in between 3:00-4:00 pm. By same
approach, the maximum L50 and L90 was 96.23 dB and 93.6 dB in between 3:00-4:00 pm. Equivalent
continuous noise level (Leq) uses L50 and NC for interpreting a stationary noise level of same sound
energy from continuously fluctuating sound levels over time (Letters, 2015). Highest Leq was recorded
as 97.7 dB during 3:00-4:00 pm of the evening where the minimum Leq was 88.94 dB at 8 am of the

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morning. The highest Leq value of power generation industry exceeds the permissible Leq limit described
by Central Pollution Control Board (CPCB, India 2000) which is 50 dB at best. This exceeding noise
level specifically refers to a stable noise level which is opted from several fluctuating sound levels
which were changing with time during the readings were taken.
120
L50
100
L10
80 L90
Decibels (dBA)

60 NC
40 NEI
20 Leq
0 Lnp
8:00 9:00 10:00 11:00 12:00 1:00 2:00 3:00 4:00 5:00 6:00 7:00 8:00
AM AM AM AM PM PM PM PM PM PM PM PM PM
Time
Fig. 2: Calculated noise pollution indices for power generation industry

The noise pollution index (Lnp) takes both NC and Leq into account to express a clear idea of noise
pollution with fluctuations in stable noise level scale. Besides, Lnp is considered as the best indicator of
psychological and physiological health effects of noise pollution. The maximum magnitude of Lnp was
recorded as 107.1 dB during the time period of 3:00- 4:00 pm and minimum Lnp was 94.3 dB at 8 am
of the morning. From Fig. 2, the maximum sound for power generation industry was observed at 3.00-
4.00 pm and minimum sound was heard and weighed at 8 am of the morning. Lnp and Leq values are
maximum for power generation industries because this type of industries own automated or man-driven
pilot-scale machines that contribute to a huge noise while production is active and running. The adverse
effects and issues of noise pollution lift up to critical situation with the increase of the value of these
noise pollution indices. However, table 2 shows the scenario of Noise climate (NC) and Noise Exposure
Index (NEI) for five surveyed industries of Khulna city of different types.

Table 2: Data on noise pollution indices with respect to Noise Climate (NC) and Noise Exposure
Index (NEI) for different industries of Khulna city at different time period
11a
Time 8am 9am 10am 12pm 1pm 2pm 3pm 4pm 5pm 6pm 7pm 8pm
m
Electrical equipment (Cable) Industry
NC 15.4 12.7 10.1 9.6 8.3 8.8 9.6 6.8 10.5 11.6 8.7 8.7 5.6

NEI 1.07 1.08 1.10 1.14 1.146 1.15 1.07 1.14 1.13 1.11 1.10 1.13 1.07

Cement Industry
NC 23.3 22.3 21.7 22.1 19.4 19.9 19.6 18.3 20.6 21.9 21 20.9 21

NEI .905 .906 .910 .919 .9298 .924 .916 .919 .928 .937 .934 .928 .929
Heavy Metal (Shipyard) Industry
NC 21.9 21.7 14 15.4 15.8 16.8 44.5 21 17.5 17.1 14.3 13.3 11.3
NEI 1.05 1.06 1.063 1.07 1.082 1.09 1.05 1.10 .939 .885 .884 .871 .886
Agriculture (Jute) Industry
NC 18 16.6 18.3 18.2 14.7 17.8 12.9 13.5 12.4 11.5 15.2 9.3 7.9
NEI 1.08 1.10 1.155 1.14 1.157 1.15 1.10 1.14 1.14 1.14 1.12 1.15 1.14
Power Generation (Electricity) Industry
NC 5.4 11.1 8.1 5.8 6 7.7 5.7 3.9 9.4 7.5 7.2 9.6 6.8
NEI 1.04 1.04 1.057 1.08 1.092 1.10 1.10 1.10 1.13 1.12 1.07 1.11 1.06

Noise Climate (NC) values indicate a range of noise level over which the sound level can fluctuate with
noise exposure period and finally expressed in dB (A) which depends on other basic noise level indices
(Kumar & Srinivas, 2015). The maximum NC was observed at shipyard industry as 44.5 dB (A) at 2

16
pm which indicates a wide range fluctuation over maximum to minimum noise level at that specific
hour. Minimum NC value was encountered as 3.9 dB (A) at power generation industry at 3 pm
indicating that the maximum and minimum noise level were close enough during that hour. This close
range of sound level indicates that sound was continuously exceeding the standard noise level limit in
power generation industry for whole 12 hour duration. Noise exposure index (NEI) indicates whether
the locations where noise is being produced are exposed to high noise exposure or not. Practically,
Industries having NEI >1 are exposed to high frequency of noise exposure and workers can feel the
differences of home and workplace’s sound climate after having a long term work experience in these
industries. In this study, NEI is greater than 1 for each industry except cement manufacturing industry
and this implicates that the sound climate of these industries is not just salubrious for worker’s health.

According to table 1, the magnitude of the noise level clearly showed that the jute and power generation
industry is producing noise that exceeds the standard noise exposure limit of 85 dB for a 8-hour work
shift described by NIOSH (Dotter, 1998). Workers working on high noise exposure spot for a long time
suffer from serious health issues as long term noise exposure gradually makes human body unable to
withstand the high frequency of noise pollution (Res, 2005). This serious scenario provides information
about taking mandatory steps to control noise production such as active noise cancellation, use of ear
protection equipment (EPE) and most importantly, shifting the workers to various locations within the
industry in time to time instead of keeping them exposed to excessive noise exposure for a long period
of time.

Questionnaire survey result

The relation between workplace noise and hearing loss is being observed for many years (Franks, 1988).
To understand the scenario better, total 75 workers of 5 industries were questioned and each of them
participated voluntarily. In this survey, the most irony point of real work zones came out that except
shipyard industry none of this huge industries inspire to use ear protection equipment even don’t show
any interest on protecting workers from this devastating noise hazard. The age variation of workers
remained between 17~60 years. According to the survey, tolerance of this noise increases proportionally
with the working year of a worker. The educational level of workers ranges from class 5 to university
level. The physiological and psychological effects of noise on workers were seen adverse as survey
showed 68% suffers from headache, 50.67% were annoyed of this noise, 29.33% were insomnia patient
and 33.33% experience dizziness due to this noise. 74.67% of them want themselves to be shifted in a
quieter place. It was observed that no industry gives long term medical support to a worker suffering
from noise hazards. While conducting survey on families living adjacent to the industries it was seen
that, all the industries except power generation industry situated at a minimum distance from the
residential area. For this reason, families living adjacent to the power generation industry are the victims
of this huge, gigantic noise for all day and night. Survey showed that families living in this area for
more than twenty years have at least a member who have lost his/her hearing capability for good. It was
also seen that, new families are not interested to buy or rent houses in this area as well.

60 6
No. of workers

40 Suffering
4
No. of families

20
Not 2
0
suffering 0

Health effects Type of industry

Fig. 3: Health effects on worker’s health Fig. 4: No. of families affected with respect to industries

Statistical Results
IBM SPSS 25 was used to carry out the Chi-square test to check the significancy of the physiological
and psychological effects of this industrial noise pollution on worker’s health and the results are
tabulated with standard deviation in table 3. According to this test, health effects for which p ≤ .05 are
significant on worker’s health based on asked questions in “yes or no” answer formation.

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 Table 3: Chi-square values of different health effects of industrial noise pollution and their
significancy to the worker’s health
Relationship between the
Total Asymptotic
Standard types of health effects and
Chi- Significance, Mean Asymptotic
Types of effects Deviation significancy of them based
square p Significance
(σ) on answers of workers p ≤
value (2 sided)
.05
Annoyance 4.669 .031 .051 Significant
Headache 22.443 .000 .062 Very Significant
Insomnia .279 .597 .163 Not Significant
Dizziness 6.926 .008 .165 .06 Significant
Stressfulness .436 .509 .130 Not Significant
Speech
14.460 .000 .062 Very Significant
Interference
Nervousness 7.365 .007 .06 Significant

CONCLUSION
This study mainly shows that we have an alarming issue with industrial noise pollution in Bangladesh
as it had grown so fast in recent years and yet increasing with an abnormal rate. Long term work
experience in noise pollution drives into abnormal breakdown of health and imbalance of the mental
condition of an individual. The condition of industrial noise of Khulna city is not beyond limit but it is
surely unhealthy to work in that noisy environment for long time. Removal of this industrial noise is
not completely possible. Using Ear Protection Equipment (EPE), opting active noise cancellation
method, raising awareness about industrial noise pollution among the workers are the only ways to be
safe from industrial noise. However, industrial authorities should take responsibilities of worker’s
health, give long term medical support in this regard, provide ear protection equipment and make the
use of it mandatory inside the industry premises. This study can be enlarged by assessing noise level
for all the industries throughout the country, educational institutions, residential areas, market places
for the betterment of the people’s health and mind by controlling the noise pollution threat so far.

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