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E-mail: said.shojaee71@gmail.com, s233161@stud.spmi.ru
DOI: 10.22104/AET.2024.6922.1899
COPYRIGHTS: 2024 Advances in Environmental Technology (AET). This article is an open access article distributed under the terms
and conditions of the Creative Commons Attribution 4.0 International (CC BY 4.0) (https://creativecommons.org/licenses/by/4.0/)
Advances in Environmental Technology 11(1) 2025, 91-115.
Journal home page: https://aet.irost.ir
Noise climate assessment in ceramic industries (Iran) using acoustic
indices and its control solutions
Saeed Shojaee Barjoee*a, Vladimir Rodionova, Amir Masoud Vaziri Sereshkb
aDepartment of Industrial Safety, Faculty of Mining, St. Petersburg Mining University of Empress Catherine II, St.
Petersburg, Russia.
bDepartment of Occupational Health, School of Public Health, Shahid Sadoughi University of Medical Sciences,
Yazd, Iran.
A R T I C L E I N F O
A B S T R A C T
Document Type:
Research Paper
Article history:
Received 6 June 2024
Received in revised form
16 December 2024
Accepted 17 December 2024
This study aimed at providing a framework for prioritizing workplaces in terms
of noise control in the ceramic industry, as exposure to industrial noise has long
been recognized as an occupational hazard. A TES-1354 device was used to
measure the noise level. The WHC continuous noise index was used to calculate
the amount of noise pollution brought on by process equipment. Finally, the
industry's workplaces were prioritized for noise control using the noise control
prioritization index (NCPI), which considers three factors: the number of
individuals exposed, the duration of exposure, and the weighting factor based
on the intensity of exposure to noise. The sound pressure level (SPL) values in
the studied industry were measured between 69 and 93.70 dB (A).
Furthermore, 20.53% of all measured stations were in the high-risk limit (SPL
≥ 85 dB(A)), while 79.47% fell within the safe range (69 ≤SPL<85 dB(A)). For
stone crushing workplace, WHC continuous noise index values were found to
be near 1, indicating unpleasant working conditions for workers. Additionally,
the highest value of NCPI was estimated for the stone crusher workplaces. Our
findings indicate that the stone crusher workplace is the priority for noise
emission control.
Keywords:
Ceramic Industry
Sound Pressure Level (SPL)
Earmuffs and Earplugs
Continuous Noise Index of
WHC
Noise Control Prioritization
Index (NCPI)
1. Introduction
Although industries are vital to a region's economy
because they create jobs and revenue, their
negative effects on workers' health can lower their
standard of living [1-3]. Exposure to harmful
factors in the workplace has long been an
important issue of industrial health [4-6].
Industrial noise is one of the strongest physical
factors that can negatively impact a worker [7,8].
Mass production in industrial settings calls for huge
machines and production lines that emit excessive
amounts of noise [9,10]. Industrial noise is no
longer just background noise in this day and age;
for numerous workers, it is an everyday reality that
shapes their experiences and long-term health [11-
13]. Industrial noise can range from a bothersome
92 S. Shojaee Barjoee et al. / Advances in Environmental Technology 11(1) 2025, 91-115.
level to one that can seriously harm the auditory
system. Therefore, it becomes crucial to keep noise
levels within allowable limits to guarantee safety
and boost industrial systems' dependability [14,15].
The International Labor Organization (ILO) reports
that occupational diseases claim the lives of 2.3
million workers globally each year [16-18]. The ILO
research states that noise pollution in the
workplace is just one of several contaminants that
might cause occupational illnesses [14,19,20].
Beyond just harming ears, excessive workplace
noise also impedes communication, lowers quality
of life, and lowers productivity [21,22].
Globally, the production of ceramic is growing at a
rate of 300 million m2 annually, and by 2020, it will
surpass 10 billion m2. Due to this extraordinary
pace of expansion, the number of raw materials
needed annually to meet worldwide demand is
anticipated to be 230 million tons per year. Iran has
a lengthy history regarding its ceramic industry. In
2020, Iran ranked as the sixth producer of ceramics
after China, India, Brazil, Vietnam, and Spain,
contributing 2.8% of the global production [23,24].
It is one of the world's top producers of ceramics,
thanks to the availability of abundant mines that
provide raw materials [23]. Despite the ceramic
industry's significant contribution to Iran's
economic expansion, employee safety and the
standard of the work environment have received
less attention [25]. Approximately thirty percent of
the 10,000 workers in Iran's more than 150 ceramic
businesses endure dangerously high levels of noise
at work [26]. Experts and decision-makers, as well
as workers in the ceramics industry, are concerned
about the negative health effects of industrial
noise. Ceramic workers have a significant rate of
noise-induced hearing loss, according to several
studies. Numerous other studies have found a link
between blood pressure (hypertension) and noise
exposure levels. The majority of ceramic industry
machinery during the manufacturing process
produces noise as an unintended result of its
operation [27]. In the ceramics industry,
mechanical operations like cutting, pressing,
sifting, crushing stone, and riveting pose a serious
risk to worker health [28]. The high decibel levels of
these equipment are not limited to the immediate
area around the machine operators; they also
negatively impact the surrounding weather's
acoustic environment and pose a risk to other
workers [10]. The noise produced by this equipment
was louder than the 85 dB (A) standard [26,29].
The noise could be mostly low- or high-frequency,
with unpleasant and jarring temporal noise
patterns [30].
Industrial noise management is one of the most
important measures for protecting the health of
workers in the ceramics industry. Measuring noise
pressure and noise-related indices are the primary
methods used to investigate noise pollution in the
ceramics sector. Thus, the first stage in creating
programs that can offer primary source control
solutions is to examine the indices of noise pollution
[31]. Establishing a useful framework for
identifying noise sources in ceramic industry
workplaces can be facilitated by using these indices
to identify safe and harmful limits [32]. In this
study, the noise climate in the ceramic industry
was investigated using the continuous noise index
of WHC. The workplaces were then ranked
according to the three parameters of noise
exposure level, exposure time, and weighting
factor using the noise control prioritization index.
2. Literature review
The increased noise levels found in industrial
settings have attracted the interest of scientists
studying the effects of excessive noise exposure on
the auditory system and the potential for noise-
induced hearing loss (NIHL) [8,33]. It is important
to note that there are various methods for
measuring and characterizing non-industrial and
industrial noise [34]. Numerous descriptors are
available to correlate people's responses to
different noise sources. There is widespread usage
of statistical descriptors of sound levels, such as
sound pressure levels exceeding n% of the
measuring period (Ln). The L10, L50, and L90 forms
of the Ln statistical descriptors are the most widely
used ones. These stand for the sound pressure
values that were surpassed, respectively, for 10%,
50%, and 90% of the measurement period.
Similarly, the range over which the sound level
varies during the measuring period is known as the
noise climate (NC) [35]. In reviewing some other
papers, a number of popular models for measuring
noise exposure are given, claiming that all noise
pollution indicators are based on the time integral
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93
of squared frequency-weighted sound pressure
over a stated time interval.
Some short-period noise indicators have also been
developed: LAeq, 1min, and LAeq, 5min. However,
they are rarely used. Fernández et al. evaluated six
ambient noise indices, including LAeq, 5 min, LAeq,
30 min, and LAeq, 60 min, based on LAeq during
brief periods of time. The exposure% and severity%
indexes, which are used to summarize the
assessment of the environmental noise throughout
any selected time frame (including day, evening,
and night), were produced by a fuzzy model using
these six indicators as inputs [36]. Alayrac et al.
conducted a study to determine noise annoyance
indices for consistent and ongoing industrial noise
sources. They considered the spectrum
characteristics of each perceptual category when
evaluating different noise annoyance indices [37].
Mardani et al. attempted to assess the quantity of
noise generated at the South Pars gas platforms for
the first time. In this study, the noise spectrum was
63 Hz~8000 Hz, as indicated by the sound power
level (PWL) and sound pressure level (SPL) indices
[38]. By employing three indicators of noise
pollution level (LNP), acoustic climate (NC), and
noise exposure index (NEI), Sahu et al. were able to
assess the levels of noise pollution in a non-
industrial area of India [39]. Table 1 provides an
overview of the metrics that were created to assess
noise exposure in publications.
3. Methodology
A research approach has been applied to satisfy the
study's goals, as illustrated in Fig. 1. The
components of this methodology are explained in
depth in the following sections.
Fig. 1. Flowchart of the Research Methodology.
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Table 1. Metrics to evaluate exposure to noise.
Metric
Metric application and description of variables
Reference
The analysis included an index that considered the A-
weighting, the primary acoustical parameters found,
the overall sound pressure level, and the background
noise level associated with the appearance of the 100
Hz component.
[37]
A general set of criteria is available to evaluate the
degree of noise pollution. The real sound level (l1), the
allowable sound level (L1), and the logarithmic average
of the discrete-instantaneous noise level for a specific
time period (Leq, or equivalent continuous noise level)
are the variables in these equations. T is the calculation
period's duration in hours, and L is the corresponding
noise in an hour (Ti). The noise levels that surpass 10%
and 90% of the entire measurement duration,
respectively, are designated as L10 and L90. These were
employed to assess the level of noise pollution (Lnp),
noise climate (NC), and noise exposure index (NEI).
[39]
Sound pressure and power levels are displayed through
metrics. PWL and SPL stand for pressure level (dB) and
power level (dB) of sound, respectively. W0 and P0 are
reference values, respectively, with W0 = 10-12 and P0 =
2×10-6 Pa, respectively. D is the minimum distance (in
meters) between the source of pollution and the
receptor, and SPLA is the sound pressure level (in
decibels) attenuation of noise in the atmosphere.
[38]
This is how the annual noise exposure and time-
weighted average sound level (TWA) are calculated. C
is the number of hours per year that the participant
reports for the activity; T is the number of hours per
year at which the activity is deemed hazardous using
our REL over a one-year period; L is the duration of
exposure to noise; and D is the exposure dose to noise.
[40]
Impact noise analysis in industries makes use of the
WHI indicator. The parameters involved in these
formulas are as follows: t0 is the reference time, 1 s; 8
h = 8 × 3600 (s) = 28800 (s); LAE is the A-weighted
exposure level for a single event (explosion); and te is
the exposure period, in seconds. The industry sector in
which the Whi = 1 (m2) impulsive noise index hazard in
the workplace exists can be identified using simulation
research on the industrial acoustic model (Shi(1)). The
total sector's area (Sc) is m2.
[10]
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4. Materials and methods
4.1. Description of the ceramic manufacturing
process
The term "ceramics" refers to inorganic, non-
metallic materials that solidify and take on the
required characteristics when heated. Depending
on the intended outcome and the type of
production (industrial or artisanal), there may be
variations in the stages of the ceramic production
process. A schematic of this process is shown in Fig.
2. The tools and procedures used in the
manufacturing of ceramics are briefly described
below.
Raw material procurement: The ceramic
production cycle commences with the preparation
of raw materials. It is important to prepare the raw
materials before they can be processed. The
following materials are utilized to make ceramics:
clay, feldspar, and quartz/silica sand.
Primary and secondary crushing, grinding, and
screening: First-size reduction and homogeneity of
raw materials are usually achieved during the
quarrying process; however, additional processing
is needed to meet the strict technical requirements
of ceramic products. Very hard raw materials are
crushed into smaller sizes using jaw and cone
crushers. Clay particles are often broken up,
flattened, and blended with crushing rollers. The
raw material is sheared, flattened, and nicked as it
passes through pairs of parallel, smooth, hard-
steel rollers that are propelled in opposing
directions. Two rotors that are fastened to
impactors or shoes make up an impact rotor
crusher. They rotate, mixing and disintegrating the
incoming material continually as they turn in the
same direction as one another.
Dry or wet milling (grinding): The production cycle
continues with the grinding and atomization
phases. The above-discussed comminution
procedure usually produces particles that are at
least 2 mm in size. The initial coarse sizes must be
reduced through grinding and atomization to
produce particles with the proper diameter and
particle size distribution for the finished product.
This grinding could be wet or dry. When the end
product does not require extremely high quality
and the raw materials are already very uniform in
terms of shape and hardness, dry grinding is
typically utilized. Wet grinding is suitable for
minimizing the particle size of the mixtures used
and making them as homogeneous as possible.
Hard ceramic spheres tumble within horizontally
placed drums in continuous or batch ball mills to
achieve even finer grinding. They are made up of
revolving rolls that are positioned vertically and
work inside an outer ring.
Spray drying: Following wet ball milling, the raw
material's aqueous suspension (solids content ~ 60
to 70%) is sprayed under pressure to create small
droplets that come into contact with a heated air
stream. Highly homogeneous, roughly spherical,
hollow granules with a moisture content of 5.5 to
7% are produced when the droplets dry. Because of
its excellent flowability, this type of powder makes
it easier to accurately load press dies and press very
large single ceramics.
Pressing: The granules are shaped using this
method, either in granular or powder form, until
they acquire a nearly final shape and, most
importantly, a consistency that permits them to
endure the next processing stages without cracking
or deforming. Granules in a predetermined volume
are charged into die boxes, and pressure is often
supplied from both above and below. Heavy
flywheels and cam action drive the pistons. High
compaction power, high productivity, uniformity,
and ease of adjustment are all possible with
modern hydraulic presses. The process of hydraulic
pressing is commonly used to shape ceramics.
Frits and glazes, glaze preparation: Applying a
crystalline glaze, which can be liquid or powder, or
a covering glaze to ceramics either before or
between the first and second firing stages is known
as glazing. The glazing of ceramics involves the use
of glassy raw materials called frits. Frits are
crystalline solids melted at high temperatures
(1500ºC) and quickly cooled to form vitreous
compounds that are insoluble in water.
Discontinuous drum ball mills are typically used to
grind the frit and additives in the glaze
manufacturing process. The glaze passes through
sieves that vibrate. After that, the parameters of
the aqueous suspension are changed.
Drying: It takes the hottest and driest air to remove
the final few percent of water from the ceramic
body. Gas burners and hot air recovered from kiln
cooling zones are currently the main sources of
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heat for drying ceramics. The drying properties of
ceramic raw materials vary, but for the most part,
they benefit from a warming-up period at high
humidity with little to no moisture loss, followed by
the major drying stage, where the workplaces
come into contact with hotter and drier air.
Firing: The fire step of the production cycle comes
after the drying phase, which is necessary to help
the object shed any remaining moisture and
plasticity so that it may be fixed in its final shape.
Special furnaces are used for firing, which can
continue for many hours and involves temperatures
between 800 and 2000°C. The procedure might
alternatively consist of two steps, and the final
product will have less volume. The end outcome is
determined only by the firing temperature. Any
moisture that remains after clay-based ceramics
are burned in a kiln is driven off at temperatures
between 100 and 200ºC. The typical starting point
for vitrification and the creation of new crystalline
compounds and glassy phases is around 900ºC,
which ends around 1050ºC (for many brick clays) or
1100ºC (for more refractory fireclays).
4.2. Cutting, squaring, and packing
Cutting is a finishing process applied when a
ceramic's final shape with precise dimensions is
successfully created. Cutting techniques, such as
wire electrical discharge machining, laser beam
machining, abrasive water jet machining, and
hybrid machining, have also been applied to cut
ceramics. Therefore, in order to achieve the
appropriate proportions and finishes for ceramics,
cutting processes need to be not only extremely
effective but also carefully selected to preserve the
integrity of the ceramics.
Squaring is a process for standardizing the edges of
ceramics, which are adjusted using a squaring
machine line. One of the functions of the machine
is to smooth and trim the edges so that they are
even, straight, and match the ceramic's
proportions. It's not just squaring the edges of
ceramic surfaces; it's also smoothing them to
remove imperfections and anomalies. The extreme
accuracy with which dry squaring machines are
made guarantees that every ceramic fulfills the
particular dimensional and quality requirements.
Packaging is a process to protect manufactured
ceramics. Ceramics are packed effectively and
safely using a variety of instruments and supplies.
Bubble wrap provides impact protection and
cushioning. Strapping tools are used to apply
strapping bands around larger ceramic items or
pallets for stability during transportation. Utility
knives, or scissors, are used for cutting packaging
materials to size or open boxes. Box cutters are
specifically designed to cut cardboard boxes safely
and efficiently.
4.3. Study population and noise source
This cross-sectional analytical study was
conducted in the ceramics sector in Yazd, a
province in central Iran. The informed consent
provided by each participant or the subject's legal
guardian to undertake this research was confirmed
by this study. The statistical population for this
study consisted of all workers in the production
sector. Administrative offices and other workplaces
that were not directly associated with sources of
noise pollution were excluded from the monitoring
scope. Two hundred and one part-time workers
who worked two or three shifts were among the
individuals affected by noise pollution. Each
employee completed a single shift in 7.5 hours. The
study examined the following workplaces: two
stone crusher workplaces (SC1 and SC2), two press
dryer workplaces (PD1 and PD2), two spray ball
milling workplaces (SBM1 and SBMS2), one glazing
workplace (G), two glazing line workplaces (GL1
and GL2), two furnace workplaces (F1 and F2), and
two packaging and squaring workplaces (PS1 and
PS2).
The workforce breakdown for each workplace was
as follows: One glazing unit employed eleven
people; two glazing line workplaces employed
forty-six; two spray-ball milling workplaces
employed twenty-one; two press-dryer workplaces
employed twenty-six; two stone crusher
workplaces employed twelve; two furnace
workplaces employed twenty-eight; and two
packaging and squaring line workplaces employed
forty-six. The primary sources of noise pollution in
these work environments were stirrers, screens, jaw
and hammer crushers, and sieves. Noise from the
equipment was produced all the time in every
workplace. The waveform of the released noise was
nonperiodic. Broadband noise was the main source
of energy distribution. Although the exact distance
between each worker and the noise source varied,
it was generally thought to be 0.5 m.
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Fig. 2. Schematic of the ceramic production process.
4.4. Noise measurements
A preliminary sampling was taken before
researching to ascertain how many noise samples
were needed. In this way, default values of the
parameters were obtained to determine the
adequacy of sampling. Then, it was confirmed that
the sample size satisfied the requirements for
statistical significance in terms of sample
adequacy. The computation of a confidence
interval and margin of error, which were founded
on accepted statistical practices, was required to
assess sample adequacy. Consequently, the
sufficiency of the sampling process was assessed
using Eq. 1:
(1)
where n is the required sample size and Z is the Z-
score corresponding to the desired confidence
level. For 95%, the critical value was considered
1.96, S is the standard deviation (that was obtained
from a preliminary study conducted by the
researchers and was 2), and d is the accuracy of the
estimate (given a sample error of less than 4%). By
using these computations and strictly adhering to
the rules of statistical sampling, it was ensured
that the sample size was sufficient to derive
reliable conclusions from the data [10].
The measuring devices and calibration
requirements were chosen in compliance with
Section III, Chapter 5 of the Occupational Technical
Manual (OTM) and the Occupational Safety and
Health Administration (OSHA) [31]. The frequency-
weighing network's TES-52A noise level meter was
used to evaluate the level of noise pollution. This
device is capable of averaging four consecutive
readings and recording or displaying the average
number. The device was set up to measure sound
levels and display the noise level in dB (A) using an
A-weighting network. In addition, the dimensions
of the site layout and the locations of the
equipment and production machines were
measured using a distometer. The ISO 9612: 2009-
based station method was used to gauge the level
of noise in the workplaces [41,42]. These stations
were put in strategic areas to maximize study
accuracy after first ensuring adequate distribution
throughout the area. A 5 m x 5 m grid of cells was
built up to build the stations using this strategy.
Then, according to where the equipment was
placed, some inaccessible spots in the cell grid were
eliminated. Every measurement was taken in the
center of each grid cell [43]. Overall, it was found
that there were 62, 154, 76, 47, 97, 65, and 79
samples on the stone crusher, spray ball milling,
press dryer, glazing, glazing line, furnace,
packaging and squaring workplaces, respectively.
In this investigation, a total of 580 samples were
used to quantify SPL. In accordance with ISO and
manufacturer standards, instrument calibration
was carried out for every set, both prior to and
following testing [42]. In this way, the TES-52A was
calibrated using the TES-1356 calibrator and
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adjusted using the rule of 3 dB (A) to the allowed
limit of 85 dB (A) in Iran. At a 94 dB (A) sound
pressure level and 1000 Hz frequency, the
calibration was completed [44].
4.5. Continuous noise index of WHC
The WHC continuous noise index was one metric
used to evaluate the degree of noise pollution
created by the process equipment. Kosała &
Stępień [10] applied the index WHC, and the
resulting equation is as follows:
(2)
where S0 is the assessed workplace area (m2), S0i
is the workplace area with noise contours smaller
than 65, 65, 70, 75, 80, and 85 dB (A) (i = 1…. ,6
with curves <65, 65 …., 85 dB (A)), (m2), κ is the
ratio of hazards from continuous noise, defined by
Eqs. 2 and 3:
(3)
(4)
where LAeq is the equivalent A-weighted noise
pressure level (dB (A)), LAeq.Te is the actual A-
weighted noise pressure level over the entire work
shift (dB), Te is the actual working time during the
entire work shift (h), and T0 = 8 hours [45]. Finding
the LAeq's spatial distribution in each workplace is
essential to computing WHC. IDW mapping was
used to determine the spatial distribution of LAeqs
with noise contours smaller than 65, 65, 70, 75, 80,
and 85 dB (A). The WHC index values ranged from
0 to 1, where 0 denoted a favorable acoustic
environment (where the effects of continuous
noise are negligible), and 1 denoted the
detrimental effects of continuous noise.
4.6. Noise mapping
Noise mapping is a modern way to provide a
graphical representation of the noise level
distribution in workplaces [45]. The current study
used a global positioning system (GPS) device to
determine the exact coordinates of each site where
data on noise levels was collected [46]. Next, an
Excel file (.XLS) containing the noise values
measured at each station's coordinates was
created. The noise contour distribution and
mapping were done using Golden Software Surfer,
version 27.1.229 [47,48]. Subsequently, the IDW
method was used to interpolate the LAeqs with
noise contours smaller than 65, 65, 70, 75, 80, and
85 dB (A).
4.7. Noise Control Prioritization Index (NCPI)
The NCPI was used to rank workplaces in order of
importance for reducing noise pollution and worker
exposure to noise. In addition to the noise exposure
values, other considerations in the
conceptualization of this index included the
number of workers exposed to noise in each
workplace, the duration of workers' exposure, and
the weighting factor corresponding to the noise
pressure level. Eq. 4 expresses this process
mathematically:
(5)
where wi is the weighting factor corresponding to
the noise pressure level, pi is the number of workers
exposed to noise for each area within the desired
range of noise pressure levels, parameter ti is the
noise exposure time (h), P is the total number of
workers on all workplaces, and T is the total
exposure time (h). Based on the lowest and
maximum noise observed in each workplace, a
weighting factor was supplied for the construction
of this equation (Table 2). A workplace weight
factor was distributed according to the dose ratio
and adherence to the 3 dB (A) criterion, which saw
an exponential increase in weight with rising noise
pressure. The denominator of the equation was the
total number of workers plus their exposure time at
each workplace in order to normalize the NCPI
data.
4.8. Statistical analyses
Descriptive statistics were computed for the data:
minimum, maximum, mean, standard deviation,
and coefficient of variation. The significance of
variations in the mean noise between workplaces
with a standard value of 85 dB (A) was evaluated
using a one-sample t-test. Duncan's post hoc test
and one-way ANOVA were utilized to assess the
significance of variations in the noise level amongst
workplaces. The data's normality was evaluated
using the one-sample Kolmogorov-Smirnov (K.S.)
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test. IBM SPSS version 26 was used to conduct the
statistical analysis of the data. P values less than
0.05 were deemed significant for differences.
5. Results
5.1. Descriptive statistics of the noise levels
Table 3 displays the findings for the noise levels in
the workplaces, which varied from 72.1 dB (A) to
93.7 dB (A). The mean noise levels were measured
for all workplaces at 81.48 dB (A). The maximum
and minimum noise levels were measured in SC1
and GL1 workplaces, respectively. The results of all
statistical tests are provided in the supplementary
information file. A substantial difference in noise
levels was observed between the workplaces, as
indicated by the one-way ANOVA analysis results
(p value <0.05). In order to compare the mean
noise levels between the workplaces, Duncan's post
hoc test was employed. The results showed that
there was no significant difference between the F1,
PD1, and PS2 workplaces (p value = 0.22), F2 and
GL2 (p value = 0.07), PD1 and SBM2 (p value = 0.12),
G and PD2 (p value = 0.43), and GL1 and GL2 (p
value = 0.19). The findings showed that the noise
data were not normal (P<0.05) for four workplaces:
SBM1, G, GL1, GL2, and PS2, according to the one-
sample Kolmogorov-Smirnov (KS) test. Therefore,
the noise levels showed significant heterogeneity
among these workplaces. The results of the one-
sample t-test showed that the noise levels for all
workplaces, except for those of the SC2 and SBM1
workplaces, were significantly different, with a
standard value of 85 dB (A) (P<0.05). The present
research concluded that 79.47% of all the
measured stations were within the safe limit (69
≤SPL<85 dB(A)) and that 20.53% were within the
high-risk limit (SPL ≥ 85 dB(A)).
5.2. Spatial pattern analysis of the noise level
For the noise data, noise-themed maps of the
workplaces were created using the Golden
Software Surfer's IDW technique. The results of the
noise spatial distribution for each workplace are
shown in Fig. 3. For SC1 and SC2 workplaces, the
thematic maps showed that the highest noise
values (> 85 dB (A)) were in the vicinity of the sand
screens. The stone crusher's funnels were the area
around which the lowest noise values were
interpolated. High levels of noise were present in
the SBM1 and SBM2 workspaces, close to
equipment such as sprays and ball millings. For the
PD1 and PD2 workplaces, the highest noise level
was interpolated around the press. The G
workplace had a sieve, fourteen ball millings, and
twenty-one mixers. In this workplace, the highest
noise was interpolated around the ball milling, and
the lowest noise was around the mixer. The highest
noise level was interpolated at the digital printing
device, ceramic side wear device, glazing device,
engobe device, water cabin, fan, and brush,
according to the spatial distribution of noise in the
GL1 and GL2 workplaces. The furnace entry and
center sections of the furnace were interpolated to
have the highest noise levels for the F1 and F2
workplaces, respectively. The load/unload and
shearing device areas of the PS1 and PS2
workplaces had the highest noise levels, according
to the spatial distribution of the noise.
Table 2. The weighting factor based on the rule of 3 dB (A) studied in the ceramic industry.
Noise contour (dB (A))
Lower limit
Upper limit
Weight factor (Wi)
69
72
0.0312
72
75
0.0625
75
78
0.0125
78
81
0.25
81
84
0.5
84
87
1
87
90
2
90
93
4
93
96
8
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Table 3. Descriptive statistics of noise levels in workplaces in the ceramic industry.
Workplace
N total
Min
Max
Mean
SD
Skew.
Kur.
T test
K. S
CV
-
dB(A)
Sig.
%
SC1
26
84.5
93.7
89.97a
2.22
-0.87
0.70
0.00
0.06
2.47
SC2
28
79.4
91.2
86.21b
3.86
-0.28
-1.28
0.10
0.18
4.47
SBM1
66
78
92.5
84.65c
2.67
0.35
1.20
0.30
0.02
3.15
SBM2
82
76.5
88.8
83.28d
2.70
-0.35
-0.15
0.00
0.20
3.24
PD1
46
74.6
85.9
79.30g
3.08
0.22
-0.82
0.00
0.20
3.89
PD2
30
77.5
85.1
81.01f
2.05
0.20
-0.91
0.00
0.20
2.53
G
44
76.8
87
81.53ef
2.74
-0.11
-0.88
0.00
0.05
3.36
GL1
51
69
82.5
76.50hi
2.59
-0.64
1.92
0.00
0.00
3.38
GL2
48
72.7
82.5
77.36i
2.34
0.32
-0.49
0.00
0.05
3.02
F1
33
76
82
79.44g
1.65
-0.46
-0.80
0.00
0.20
2.08
F2
32
75.5
80.7
78.55gh
1.27
-0.58
-0.02
0.00
0.20
1.62
PS1
40
75.1
90.4
82.54de
4.04
0.06
-0.94
0.00
0.20
4.89
PS2
39
72.1
85.5
78.93g
4.91
-0.03
-1.75
0.00
0.00
6.22
Total
565
69.00
93.70
81.48
2.78
-
-
-
-
3.41
Table abbreviations: N total→ total number of samples measured; Min→ minimum; Max→ maximum; SD→ standard deviation; K. S →
one-sample Kolmogorov–Smirnov test; CV→ coefficient of variation; T test → one-sample t test; Kur. → Kurtosis; Skew. → Skewness.
Fig. 3. Spatial pattern of SPL in workplaces
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Fig. 3. (Continued) Spatial pattern of SPL in workplaces
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Fig. 3. (Continued) Spatial pattern of SPL in workplaces.
5.3. Continuous noise index of WHC
When multiple devices are operating
simultaneously, there may be an issue with
continuous noise pollution, as evidenced by
increased WHC index readings. Table 4 and Figure
4 display the findings of the WHC's continuous
noise index estimation. The predicted range of this
index's value for the ceramic industry was 0.056 to
0.99. The average WHC index value for the ceramic
industry came out to be 0.63, indicating that
workers were negatively impacted by constant
noise brought on by multiple devices operating at
the same time. The value of the WHC index for
workplaces was organized in descending order as
follows: SC1> SC2> SBM1> SBM2> PS2> G> PD2> PS1>
F1> PD1> GL2> F2> GL1. When the WHC index is near
1, it means that working conditions are not good for
employees and that wearing personal protective
equipment is essential. As a result, the predicted
values of this index for the workplaces in SC1, SC2,
SBM1, SBM2, and PS2 were very close to 1, indicating
that the workers there did not have pleasant
working conditions.
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Table 4. The value of the constituent parameters of the WHC index.
Workplace
Class (dB (A))
Designation area
between contours
S0i (m2)
S0 (m2)
K65-85dB (A)
SC1
84-85
+84
1.41
514.72
0.93
85-94
+85
513.30
1
SC2
79.4-80
+79.4
3.40
504.06
0.29
80-85
+80
192.32
0.93
85-91.2
+85
308.34
1
SBM1
87-80
+87
12.37
1082.39
0.29
80-85
+80
512.50
0.93
85-92.5
+85
557.52
1
SBM2
76.5-80
+76.5
61.15
951.26
0.29
80-85
+80
507.14
0.93
85-88.8
+85
382.97
1
PD1
74.6-80
+74.6
396.50
643.05
0.091
80-85
+80
245.21
0.93
85-85.9
+85
1.33
1
PD2
77.5-80
+77.5
155.51
607.99
0.17
80-85
+80
452.48
0.93
85-85.1
+85
0
1
G
76.8-80
+76.8
144.20
861.11
0.15
80-85
+80
657.48
0.93
85-87
+85
59.43
1
GL1
69-70
+69
2.00
833.31
0.025
70-80
+70
807.40
0.031
80-82.5
+80
23.91
0.93
GL2
72.7-80
+72.7
842.31
1032.23
0.058
80-82.5
+80
189.92
0.93
F1
76-80
+76
408.80
817.49
0.12
80-82
+80
408.69
0.93
F2
75.5-80
+75.5
810.87
811.43
0.11
80-80.7
+80
0.56
0.93
PS1
75.1-80
+75.1
170.34
676.02
0.10
80-85
+80
324.37
0.93
85-90.5
+85
181.47
1
PS2
76.5-80
+76.5
61.15
951.26
0.14
80-85
+80
507.14
0.93
85-88.8
+85
382.97
1
Fig. 4. WHC index value for workplaces.
5.4. Prioritization of noise control
In Table 5, the values of parameters for NCPI
calculation are displayed. Furthermore, the
workplace priorities for the use of noise control
measures are shown in Figure 5. NCPI values in this
study ranged from 0.124 to 3.99. Since the SC1
workplace had the greatest degree of noise
pollution, with an NCPI score of 3.99, the workplace
was given priority for the execution of noise control
measures. Moreover, the SC2 workplace came in
second, while SBM1 came in third. The GL1 workplace
was deemed to be the least important.
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Table 5. Values of parameters for NCPI calculation.
Workplace
Class (dB
(A))
Weight
factor
(Wi)
Number of
workers exposed
to noise (Pi)
Exposure time
to noise (ti)
SC1
84-87
1
0
7.5
210
52.58
87-90
2
2
7.5
90-93
4
4
7.5
93-94
8
1
7.5
SC2
79.4-81
0.25
0
7.5
86.25
37.5
81-84
0.5
1
7.5
84-87
1
1
7.5
87-90
2
1
7.5
90-91.2
4
2
7.5
SBM1
78-81
0.25
1
7.5
91.87
67.5
81-84
0.5
2
7.5
84-87
1
3
7.5
87-90
2
2
7.5
90-92.5
4
1
7.5
SBM2
76.5-78
0.0125
0
7.5
84.37
90
78-81
0.25
3
7.5
81-84
0.5
3
7.5
84-87
1
3
7.5
87-88.8
2
3
7.5
PD1
74.6-75
0.0625
3
7.5
22.31
90
75-78
0.0125
3
7.5
78-81
0.25
3
7.5
81-84
0.5
2
7.5
84-85.9
1
1
7.5
PD2
77.5-78
0.0125
0
7.5
58.12
105
78-81
0.25
5
7.5
81-84
0.5
5
7.5
84-85.1
1
4
7.5
G
76.8-78
0.0125
0
7.5
56.25
82.5
78-81
0.25
2
7.5
81-84
0.5
4
7.5
84-87
1
5
7.5
GL1
69-72
0.0312
3
7.5
20.57
165
72-75
0.0625
0
7.5
75-78
0.0125
12
7.5
78-81
0.25
4
7.5
81-82.5
0.5
3
7.5
GL2
72.7-75
0.0625
1
7.5
42.46
187.5
75-78
0.0125
8
7.5
78-81
0.25
10
7.5
81-82.5
0.5
6
7.5
F1
76-78
0.0125
2
7.5
45.18
150
78-81
0.25
12
7.5
81-82
0.5
6
7.5
F2
75.5-78
0.0125
2
7.5
28.31
127.5
78-80.7
0.25
15
7.5
PS1
75.1-78
0.0125
3
7.5
127.78
150
78-81
0.25
4
7.5
81-84
0.5
6
7.5
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Workplace
Class (dB
(A))
Weight
factor
(Wi)
Number of
workers exposed
to noise (Pi)
Exposure time
to noise (ti)
84-87
1
3
7.5
87-90
2
3
7.5
90-90.5
4
1
7.5
PS2
72.1-75
0.0625
8
7.5
56.62
195
75-78
0.0125
4
7.5
78-81
0.25
4
7.5
81-84
0.5
8
7.5
84-85.5
1
2
7.5
Fig.5. Prioritization of workplaces based on NCPI.
6. Discussion
6.1. Noise exposure assessment
According to the Centers for Disease Control and
Prevention (CDC), the third-most common chronic
physical condition is noise-induced hearing loss
(NIHL). Disease prevention is more cost-effective
and superior to therapy. Workers may be able to
prevent NIHL by being aware that undesired noise
can be damaging, as well as by knowing the real
safe noise exposure limit [49,50]. Thirteen
workplaces where workers in the ceramic sector
were directly exposed to noise were examined for
this study. The average noise level in the studied
ceramic industry workplaces was measured at
81.48 dB (A). The industry, as a whole, uses a
variety of equipment that can produce noise levels
up to 93 dB (A). The study's findings demonstrated
that the stone crusher workplace was mostly
responsible for noise emissions. In this workplace,
there were large jaw crushers and large-toothed
kibbler rollers that could make coarse primary
crushing of moderately dry or brittle clays. These
crushers compress the mineral lumps between a
stationary and a moving hard surface. Impact
forces are used to reduce particle size; raw
materials are broken into little bits by the fast-
revolving hammers. Noise emissions from this
process exceed the allowable limit. The ceramic
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industry uses other advanced mechanical
equipment, such as conveyor belts, sprays, ball
milling, stirrers, slurry dryers, presses, pumps, glaze
drain tanks, roll box transfer machines, furnaces,
color router printing machines, polishers, chillers,
pelletizer machines, and ceramic cutting and
processing machines. These result in distinct noise
exposure profiles for workers in the ceramic
industry based on the type of work they do with the
equipment, giving rise to distinct occupational
classes.
The findings of noise exposure values documented
in prior research indicated that the mean noise
levels in the studies ceramic sector were
comparatively lower than those in other industries:
textiles (weaving: 88–86 dB (A), and preparing: 63–
93 dB (A)) in Ethiopia [51], beverage cans
manufacturing (92–98 dB (A)), steel reinforcement
forming for concrete (91–95 dB (A)), steel sheets
forming and processing (87–91 dB (A)) in Saudi
Arabia [52], manufacturing industry (82.8 dB (A))
in China [53], automotive industry (85 dB (A)) in
China [54], transportation equipment
manufacturing industry (84.3-90.3 dB (A)) in
China [55], construction equipment operators (>85
dB (A)) in Iran [56], automotive assembly industry
(83.41 dB (A)) in Iran [57], ceramic industry (82.3 -
92.6 dB (A)) in Iran [26], workshops of car oil
change (95 dB (A)) and aluminum makers (98.4 dB
(A)) in Iran [58], food manufacturing (90–92 dB
(A)) in US, food processing (88–94 dB (A)) in UK,
paper manufacturing (90–92 dB (A)) in US, printing
and publishing (82–93 dB (A)) in US, petroleum and
coal products manufacturing (87–92 dB (A)) in US
[59], chemical industry (91–100 dB (A)) in South
Korea [60], steel industry (90–100 dB (A)) in UK
[59], small scale hand tools manufacturing
industry (81-110 dB (A)) in India [61], and
petrochemical industry (88–93 dB (A)) in Iran [62].
Nonetheless, the noise levels and exposure profile
may vary based on the industry's equipment type
and manufacturing process.
6.2. Evaluation of indices
Ibáñez-Forés et al. [63] suggested using the WHC
index to evaluate the efficacy of anti-noise
solutions for machinery and equipment used in the
tile and ceramic industry. Nevertheless, there
aren't many noise climate studies that use the
WHC index. As such, comparing the findings of this
study to those of other studies is not
straightforward. There is only one study by Kosała
& Stępień that used the WHC index to evaluate
continuous noise pollution during two working
shifts in quarries. They concluded that shift 2
workers would gain more from this in terms of
acoustics because WHC values close to zero
indicated a positive acoustic environment in the
quarry [10]. However, the current study's findings
demonstrated that the ceramic industry's noise
climate was not ideal. Stone crusher workers in the
ceramic sector were at high risk of exposure to
noise.
Noise emission prevention comprises management
techniques that reduce the quantity of noise.
Eliminating the source of dangerous noise is the
best course of action, according to Oltean
Dumbrava et al. If removal is not an option, the
next best option to protect workers from dangerous
noise might be to replace noisy equipment with
quieter equipment. If the first two control
approaches are ineffective in reducing hazardous
noise, engineering controls may be built to either
remove the noise at the source or lower it to
tolerable levels. The workplace must be physically
altered to implement engineering controls.
Redesigning machinery to eliminate noise sources
and building barriers to keep workers from being
affected by noise are two examples of these
modifications [64]. The NCPI index was used in this
study to prioritize noise management in the
ceramic industry's workplaces. The ceramics sector
has not prioritized noise management via the NCPI
until recently. Because of this, it is not feasible to
compare the findings of this investigation with
those of previous investigations. However, this
index has been utilized in the rubber sector to
determine which areas to prioritize when it comes
to noise management.
According to estimates from Gol Mohammadi et
al., the tire industry's NCPI values varied from
0.006 to 1.369. The weighting factor for the noise
pressure level in this investigation was determined
using the 3 dB (A) criterion [65]. Furthermore, a
study on estimating NCPI values in the oil refinery
business was carried out by Mousavi et al.
According to their findings, the NCPI ranged from
0.84 to 1.25 in various workplaces [32]. The current
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study's findings demonstrated that the NCPI was a
thorough index that could be utilized for planning
and managing noise control in the ceramic
industry, as well as for prioritizing workplaces.
Actually, by integrating helpful criteria to
determine how different workplaces contribute to
noise pollution, NCPI establishes a framework for
prioritizing and ranking noise control solutions. In
this study, interviews with senior staff members
and managers in each workplace helped identify
the number of workers, the length of exposure, and
the locations of the workers' workspaces. The
numbers obtained for the sound emission rate were
then used to calculate the NCPI.
The SC1 and SC2 workplaces were given top priority
in regard to noise control measures, according to
the NCPI calculation results. Using SDMats is
consistent with the NIOSH Prevention by Design
(PtD) approach, which advocates "engineering
out" hazardous noise before exposure occurs.
Accordingly, the main approach to noise control in
this workplace is to swap out noisy machinery or
equipment for quieter models. By blocking a noise
source's path, e.g., by covering a noisy motor with
insulation, one can also reduce noise. The third
workplace where reducing noise emissions was
given top priority was SBM2. Ball mills were found
to have the largest estimated contributions to
noise emissions in these workplaces. The main
sources of noise in ball milling are collisions
between the processed material, the cylinder wall
lining, and the metal balls in the drum. In essence,
ball mill noise is steady-state noise with high sound
energy and low, medium, and high-frequency
components spread over a broad frequency
spectrum. The best solution to reduce ball milling
noise pollution is to use a soundproof cover, replace
the manganese steel cover with a rubber cover,
improve ventilation, reduce heat loss, and add a
chamber to the ball milling. In some studies, the
cylinder muffler method has been proposed, in
which an elastic buffer is installed between the
inner wall and the lining plate to effectively remove
noise from the ball milling [66]. For other
workplaces, noise control methods can be applied,
as presented in various studies [64]. It is frequently
possible to reduce the amount of noise in these
workplaces by taking direct action at the source of
the noise. Compressors, motors for the handling
and preparation equipment, and pneumatic filter
cleaning systems are a few examples of the primary
sources of noise. Building up noise-blocking walls or
enclosing noisy equipment are two ways to
accomplish noise protection. Additionally, the air
gap between the first and second walls ensures a
higher level of noise shielding, which makes double
walls or sheathing in a double-shelled building
extremely efficient. The pressing machines used in
the ceramic industry, especially those handling
granule shaping applications, constitute major
components of harmful noise. The frequent use of
pneumatic hammers and stamping machines also
produces dangerous noise. When pressing
machines are used extensively and do not receive
proper maintenance, they always produce
abnormally loud noises [64]. Because the
aforementioned procedures are ineffective in
reducing vibrations and noise from multiple
facilities, such as presses and mixing facilities,
vibration insulation is required to prevent the
transfer of vibrations and noise.
Other effective methods to lessen vibration and
noise include metal suspensions, rubber-metal
connections, felt, rubber, and cork components;
additionally, a bitumen layer or a single engine bed
can be used to insulate the entire base from
vibration. Using silencers near the source of noise
and swapping out fast-turning fans for larger ones
with a slower rotation are two other ways to lessen
noise emissions at work. When belt drives are
utilized in place of gears and hydraulic or
pneumatic equipment is substituted for
mechanical equipment, noise reduction can be
substantial. Additionally, noise is reduced by
replacing the silencers on schedule. The majority of
the dangerous noise produced by cutting and
packaging equipment can be greatly reduced with
a competent maintenance program. Examples
include making sure that all moving components
are properly lubricated, aligning and balancing
squaring equipment, and maintaining the right
alignment and balance of color router printing,
polishing, drying, and pelletizer machines [67,68].
Since the hazards cannot be totally removed by
removal, replacement, or engineering controls, the
next step is to reduce noise exposure by utilizing
administrative controls. For instance, the ceramics
sector might change the work schedules to avoid
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exposing workers to excessive noise. The final
option for removing exposure to dangerous noise is
to implement a hearing loss prevention program
(HLPP) [7]. However, HLPP is typically less effective
than removal, replacement, and engineering
controls because it depends on human activities to
reduce noise. The Occupational Safety and Health
Administration (OSHA) advises wearing personal
protective equipment (PPE) and implementing a
hearing conservation program. Earmuffs and
earplugs are examples of single hearing protection
devices that should be worn when the noise level is
85 dB (A) or greater [7]. Commonly used hearing
protection devices offer either single or dual
protection. A dual-protection tool used when the
noise level for an 8-hour exposure is more than 105
dB (A) is the earplug with earmuff combination.
Since the workers in the investigated workplaces
were not subjected to such elevated noise levels for
7.5 hours, it was anticipated that wearing earplugs
would greatly reduce noise levels. The effective A-
weighted noise level (ENL) for earplugs with a noise
reduction rating (NRR) of 31 dB (A) was determined
using the following formula in accordance with
NIOSH standards [7]:
(6)
Figure 6 illustrates the daily noise dosage
computed in the absence and in the presence of
earplugs with an NRR of 31 dB (A). The figure shows
how wearing earplugs can lower the daily noise
dosage (D) to acceptable levels in the majority of
areas in the production zones. As an illustration,
employees in the stone crusher workplace who did
not wear earplugs were subjected to a daily noise
dose that could vary from 1069 to 7445% with an
average of 4231.16%; however, when earplugs were
worn, this daily noise dose was lowered to less than
16%. Therefore, when wearing protective gear
made up of earmuffs and earplugs, the ENL further
decreased. Thus, it is recommended that
employees who must spend a lot of time in the
workplace use these dual protection devices.
Fig. 6. Average daily dose of noise.
The HLPP program for the ceramic sector can be
divided into three phases based on the NIOSH
standard: before employment, after employment,
and administrative actions for remedy. During the
pre-employment stage, it is recommended to do
audiometric testing on all field workers and
maintain a log of their audiogram results,
particularly the Hearing Threshold Level (HTL), to
assess any changes in their hearing from their
baseline audiogram. At the post-employment
stage, it is recommended to conduct a periodic
assessment of noise levels in the workplace,
conduct an annual audiometric evaluation of staff
members, and mandate the use of hearing
protection devices (earmuffs in the control room
and earplugs everywhere in the workplace) by all
workers. Administrative remedies include raising
employee awareness of potential noise-related
harm to their auditory systems, enforcing
engineered solutions for dominating noise sources,
establishing long-term circulation between
employees inside and outside of workplaces every
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week, and periodically evaluating the efficacy of
implemented HLPP.
6.3. Research limitations
Limitation 1: It can be challenging to estimate noise
exposure levels using personal sound exposure
meters (PSEMs) after accounting for the
attenuation provided by hearing protection.
Recording at least the C-weighted sound levels is
required to compute this attenuation using the
simplest estimation approach (the denominated
SNR method). The primary issue is that most
measurement devices do not allow for the
simultaneous recording of two distinct weighted
sound levels. This means that two separate
measurements of noise levels must be made over
the course of two working days. The first
measurement should be an A-weighted sound level
in order to meet the upper and lower exposure
action values; the second measurement should be
a C-weighted sound level to account for the
attenuation provided by the hearing protector
devices.
Limitation 2: The limitations of current noise
mapping approaches are numerous. One drawback
of these methods is that they only work with sound
levels within specific frequency ranges and do not
offer temporal or spectral information about the
sound waves. Another drawback is that the existing
methodology measures a smaller region with high-
quality equipment and then extrapolates the data,
which may overlook additional noise sources and
amplify or lessen environmental effects.
Furthermore, the existing methods can be
expensive and time-consuming, needing millions of
calculations to produce a noise map with an
acceptable level of accuracy and sophisticated
geometrical calculations for every receiver site. The
uncertainty around noise maps can also impact
how they are interpreted for worker safety
planning, emphasizing the importance of
comprehending the statistical significance of the
findings. These limitations call for the development
of new noise mapping prediction technologies that
can enhance the current methods and provide
better spatial and temporal coverage.
Limitation 3: Future research must address the
limitations of the analyzed indexes. A drawback is
the methodology and assessment of noise exposure
do not evaluate several criteria, including age,
weight, and gender of the workers. It is also
assumed that workers spend most of their time in
fixed workplaces. Future research should,
therefore, create indices that consider both the
workplace's volatility and the demographic
characteristics of the workers.
6.4. Future research outlooks
The issues and ramifications of noise in the ceramic
industry could be the subject of several major areas
of future study. Here are some potential research
directions:
• Regulatory frameworks
Evaluate the effectiveness of existing noise
regulations and standards in the ceramic industry
and propose updates or new guidelines based on
scientific evidence.
Explore international best practices in regulating
industrial noise and assess their applicability in
different industrial contexts.
• Technological innovations
Investigate the integration of artificial intelligence
and machine learning algorithms for predictive
maintenance of noisy industrial equipment in the
ceramic industry to prevent malfunctions that lead
to increased noise levels.
Explore the use of sound-absorbing materials and
structures in industrial design to reduce noise
propagation and improve acoustic comfort.
• Human health impacts
Conduct longitudinal studies to better understand
the long-term health effects of exposure to
industrial noise on workers, including
cardiovascular, psychological, and cognitive
impacts.
Investigate the relationship between noise
exposure and sleep disturbances, stress levels, and
overall quality of life among workers in the ceramic
industry.
• Cross-disciplinary research
Foster collaboration between acousticians,
engineers, public health experts, urban planners,
and policymakers to address the multifaceted
challenges of noise pollution in the ceramic
industry.
Encourage interdisciplinary research projects that
consider both technological solutions and the
S. Shojaee Barjoee et al. / Advances in Environmental Technology 11(1) 2025, 91-115.
110
110
social implications of noise on workers of the
ceramic industry.
• Research on multi-criteria decision-
making techniques
As a supplement to the NCPI method, noise control
techniques can be prioritized using multi-criteria
decision-making techniques such as fuzzy
hierarchical analysis, Vikor, and TOPSIS. Mousavi et
al. determined the weights of effective criteria for
selecting the optimal noise reduction solution in an
oil refinery distillation unit using the FAHP
hierarchical analysis approach. Using the TOPSIS
technique, they concluded that the optimum
method for reducing noise was to construct an
enclosed chamber [69]. Also, Ishaqi et al. ranked
the requirements and remedies for noise control in
a glass manufacturing company using the AHP
hierarchical analysis approach. With a final weight
of 0.113, they determined that applying a full
partition between the two main components was
the optimum noise reduction option [70]. Only the
ceramics industry was the subject of the current
investigation. Consequently, it is advised additional
research be carried out in additional operational
workplaces and the NCPI index be used to rank
noise control strategies across a range of sectors.
The best options can then be chosen by applying
multi-criteria decision-making techniques like ANP
and FAHP.
7. Conclusion
The study demonstrated that some machinery and
equipment used in the operating process of the
ceramic industry had excessive noise levels. In
general, the noise level in some workplaces, such as
stone crushers, was unfavorable. The acoustic
climate studies in the ceramic industry include the
indices that are discussed in the article. The
continuous noise index could be used to evaluate
the efficacy of anti-noise solutions for machinery
and equipment used in the ceramics sector. Higher
WHC index values suggested that there may be a
continuous noise pollution issue if multiple
machines were operated simultaneously during a
shift. The areas where operational staff were next
to the machine were potentially dangerously noisy
workplaces. These workplaces should have
soundproof enclosures. According to the NCPI
method's results, stone crushers were the top
priority for remedial action to lower worker noise
exposure. The expectation was that using earplugs
would significantly lower noise levels since
employees in the analyzed settings were not
exposed to 105 dB (A) noise levels for 7.5 hours.
Future research is necessary to better differentiate
between various sound sources in terms of
frequency, time pattern (fluctuation, emergence),
and acoustic indices, as there is growing evidence
of varying human responses to different sound
sources. More longitudinal studies are required. To
further advance our understanding of the human
response to the wide range of potential negative
effects of noise on health and quality of life, cross-
sectional studies that use competing sound indices
to assess noise exposure in greater detail, including
background, could be helpful.
Acknowledgements
We would like to thank the ceramic industry for the
support of this research project.
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How to site this paper:
Shojaee Barjoee, S., Rodionov, V., & Vaziri Sereshk, A.M. (2025). Noise Climate Assessment
in Ceramic Industries (Iran) Using Acoustic Indices and Its Control Solutions. Advances in
Environmental Technology, 11(1), 91-115. DOI: 10.22104/AET.2024.6922.1899
