noise pollution – causes, mitigation and control …ii bonafide certificate certified that the...
TRANSCRIPT
i
NOISE POLLUTION – CAUSES, MITIGATION
AND CONTROL MEASURES FOR ATTENUATION
A THESIS
Submitted by
DASARATHY A K
In partial fulfillment for the award of the degree
of
DOCTOR OF PHILOSOPHY
Department of Civil Engineering
FACULTY OF ENGINEERING AND TECHNOLOGY
Dr. M.G.R.
EDUCATIONAL AND RESEARCH INSTITUTE
UNIVERSITY (Decl. u/s 3 of the UGC Act 1956)
CHENNAI 600095
MARCH 2015
ii
BONAFIDE CERTIFICATE
Certified that the thesis entitled, “NOISE POLLUTION – CAUSES,
MITIGATION AND CONTROL MEASURES FOR ATTENUATION” is the
bonafide work of Mr. DASARATHY, A.K. who had carried out the
research under my supervision and it is devoid of any plagiarism to the best
of my knowledge. Certified further, that to the best of my knowledge, the
work reported herein does not form part of any other thesis or dissertation
on the basis of which a degree or diploma was conferred on an earlier
occasion on this or any other scholar.
T. S. Thandavamoorthy, FIE, FIITArb
Supervisor Professor
Adiparasakthi Engineering College Melmaruvathur, Kancheepuram District and
Past Vice-President, ICI [email protected]
iii
DECLARATION BY THE CANDIDATE
I declare that the thesis entitled, ”NOISE POLLUTION – CAUSES,
MITIGATION AND CONTROL MEASURES FOR ATTENUATION”
submitted by me for the degree of Doctor of Philosophy is a bonafide
record of work carried out by me during the period from August 2007 to
July 2014 under the guidance of Dr. T.S. Thandavamoorthy and has not
formed the basis for the award of any degree, diploma, associateship,
fellowship, titles in this or any other University or other similar institution
of higher learning and devoid of any plagiarism.
I have also published several of my papers based on the thesis in
International Journals (Scopus rated) as per the list of publications
presented in the Annexure.
iv
ABSTRACT
Noise is a prominent feature of the environment including that from
sources such as transport, industry and neighborhood. Noise pollution is
becoming more and more acute, and hence many researchers are studying
the effect of noise pollution on people and its attenuation. In this thesis an
attempt has been made to find the measures for the reduction in noise
levels. Different sources have been identified that have potential for
generation of noise pollution. Sources which are identified for the study
are: noise level generated from vehicular traffic, noise from flour mill
operation, construction machinery, and so on so forth.
Therefore, the primary objective of this research is to quantify the
exceedance of noise level above permissible level at selected types of
sources, identify appropriate and innovative noise barrier designed to
attenuate noise level that has potential for implementation at the sources of
selected types in which the noise levels are high when compared to the
standards. Based on the study and evaluation conducted for this research it
is recommended here to implement three categories of innovative barriers
and their designs, namely, (i) thatched shed; (ii) cubicles made of concrete,
v
viz., normal concrete and concrete with coral shell powder (CSP); and (iii)
fly ash brick; as they are cost effective, easy to install with locally available
materials as well as beneficial to human beings in the long run.
Research involved in field measurement of the noise levels
generated by a traffic flow in an open stream as well as on a road provided
with noise barrier. The noise that is generated from the existing system of
operation is about 6% to 58% higher than the standards prescribed by the
authorities. Such a severe noise pollution has to be reduced. Hence
effective noise barrier was devised to attenuate the noise and the outputs
are presented in the form of numerical results.
From the numerical results and graphical representations, it is
concluded that the reduction of noise level is about 5 to 8% in noise
decibels through noise barriers. This will be significant when noise barriers
are used especially in residential zones where a huge noise pollution is
experienced due to vehicular traffic and construction machinery.
In conclusion it can be stated that the noise barriers suggested are
simple and they can be erected easily with locally available materials.
vi
���க�
ேபா��வர� ஒலி, ெதாழி� ம��� அ�க� ப�க�திலி��
இ�� ச�த� உ�ளி ட "ழலி� ஒலி மா#ப$வ ஒ� அ�ச�
ஆ��. ஒலி மா# நா'��நா� த(விரமாகி வ�கிற, எனேவ பல
ஆரா-.சியாள0க� ஓைச ம��� ஓைசயி3 மா#வினா�
ஏ�ப$� விைள5கைள ப67பதி� ஈ$ப $�ளன0. இ�த ஆ-வி�
ஒ� :ய�சியாக இைர.ச� அள5க� �ைற7;�கான
வழி:ைறக� க<$பி6�க7ப $�ளன. ப�ேவ� ஆதார=களி�
ஓைசயி3 மா#�கான சா�திய� உ�ள எ3� அைடயாள�
காண7ப $�ளன. இைர.ச� நிைல, வாகன ேபா��வர� ?ல�,
க $மான இய�திர=க� இ�� உ�வா�த�, ம���
மா5மி�லி3 ஓ ட� ஆகிய ஆதார=களிலி�� உ�வாவதாக
க<$பி6�க7ப $�ள
எனேவ, இ�த ஆரா-.சியி3 :த3ைம ேநா�கமாக தர�ைத
ஒ7பி$�ேபா ேபா ச�த� அள5 அதிகமாக இ����
நிைலயி�, இ�த ேத05 ?ல� ஒலி மா#ப$வைத ஆதார�ட3
ெசய�ப$�த சா�திய� உ�ள எ3��, ச�த� நிைல �ைற�க
ச�த�தைட எ3கிற ;ைமயான வ6வைம7; அைடயாள�
ஆ��. அத�காக ?3� ;ைமயான ச�த�தைட :ய�சியாக
ெசய�ப$�த இ=ேக பA�ைர�க7ப$கிற. இ�த ஆரா-.சி
vii
நட�திய ஆ-வி� ம��� மதி7ப$ீ அ67பைடயி� ஓைல
ெகா டைக, சாதாரண கா3கிC 6னா� ெச-ய7ப ட, சிறிய
அைறக�, ேசாழியினா� உ�வா�க7ப ட கா3கிC சிறிய
அைறக�, சா�ப� ெச=கலி� ஆன சிறிய அைறக� ேரா ேடார�
அைம�க பA�ைர�க7ப $�ள.
ச�த��ைறய அைம�க7ப $�ள தைடD�ள சாைலயி� உ<டா��
இைர.சைல திற�த ெவளியி� உ�ள சாைலயி� உ<டா�� இைர.ச
ேலா$ ஒ7பி $ பா0�த� எ3கிற ஆரா-.சி இதி� அட=��. ப�ேவ�
கண�கீ $��பி3 ச�த� அள5 தர�க $பாைடவிட 6% :த�
58% அதிகமாக இ��கிற என ெதAயவ�கிற . இ�நிைலயி� ஒலி
மா#ைவ �ைற�க ேவ<$�. எனேவ பயF�ள ச�த�, தைட
ச�த� அலகி3 ஆராய7ப ட ம��� ெவளிய$ீகைள எ<
:65க� வ6வ�தி� வழ=க7ப$கிற.
ACKNOWLEDGEMENT
viii
I wish to express my sincere thanks and heart-felt gratitude to our
Honorable Chancellor Thiru A.C. SHANMUGAM, and the President Thiru
A.C.S. ARUN KUMAR for their munificent permission granted to me in pursuing my
research at their esteemed institution.
I thank my project guide, Dr. T.S. Thandavamoorthy, Professor for his
kind help and timely guidance.
I extend my sincere thanks to Dr. R. Jayabalou, Former Scientist(-in charge-),
CSIR-NEERI for his constant support in completing this project.
I would also like to express my deep gratitude to my Head of the Department of
Civil Engineering, Dr. Felix Kala for providing me with all the facilities required
for the completion of the project.
My thanks are due to Er. M. Muthukumar (TNRDC) for giving all required
project information for carrying out the survey at OMR. I owe my sincere thanks to
Southern Railways, M/s Navin Housing Pvt Limited, Tambaram Municipality, M/s
K.G. Housing Pvt. Limited and M/s Eco Fly Infrastructure for their invaluable
assistance provided during the course of the thesis.
Thanks to all Staff members of Civil Engineering Department and university
members for their timely help during the project work.
I thank GOD for the door of opportunity He has opened for me. Last but
not the least I thank my PARENTS for their love, support and co-operation,
without them this work would not have been possible.
Dasarathy, A.K. TABLE OF CONTENTS
ix
CHAPTER TITLE PAGE
Abstract (English) iv
Abstract (Tamil) vi
Acknowledgement viii
Table of Contents ix
List of Figures xii
List of Tables xvi
List of Symbols and Abbreviations xviii
1 INTRODUCTION
1.1 General aspect of noise pollution 1
1.2 Sources of noise pollution 2
1.3 Effect of noise pollution 2
1.4 Present scenario in Indian context 3
1.5 Statutory guidelines 4
1.6 Objectives and Scope of this research 6
2 LITERATURE REVIEW
2.1 General 8
2.2 Purpose of Literature Review 10
2.3 Review of published papers 10
2.4 Summary of collective literatures 33
CHAPTER TITLE PAGE
x
3 METHODOLOGY
3.1 General 34
3.2 Data collection 35
3.3 Field area and exposure timings 35
3.4 Equipment 39
3.5 Parameters calculated from primary survey 39
4 OBSERVATIONS AND CALCULATIONS OF
PARAMETERS
4.1 Noise parameters from traffic survey 40
4.2 Noise parameters from vehicles Tambaram
subway 42
4.3 Construction noise and noise parameters 44
4.4 Vehicle manufacturing years – Cars 54
4.5 Noise from railway station 56
4.6 Flour mills noise during grinding operation 58
4.7 Findings from observation 60
5 RESULTS AND DISUSSIONS
5.1 Analysis of noise data 61
5.2 Solution to noise menace 71
5.3 Noise reduction 72
5.4 Comparison of noise barrier 84
5.5 Noise control barrier 86
5.6 Noise Prediction 86
xi
CHAPTER TITLE PAGE
6 MODELS FOR PREDICTION
6.1 Developing model based on traffic parameters 89
6.2 Regression analysis 89
6.3 Regression model 90
6.4 Spectral analysis 94
6.5 Theory about LFN 95
6.6 MATLAB 96
6.7 Spectral analysis for traffic stream 99
6.8 Spectral analysis for subway 100
6.9 Spectral analysis for construction noise 101
6.10 Spectral analysis for cars of different
years of manufacturing 102
6.11 Spectral analysis for Perungalathur
railway station 103
6.12 Spectral analysis flour mills and traffic stream 104
6.13 Spectral analysis for noise reduction barriers 106
6.14 Power Spectrum 112
7 CONCLUSIONS 124
REFERENCES 129
PUBLICATIONS 135
ANNEXURE I 136
xii
List of Figures
Figure No. Figure Description Page
No.
1.1 Traffic congestion in the study area 3
3.1 Flow Chart of Methodology 34
3.2 Noise level meter and the digital display of
observation 39
4.1 Comparison of noise level with CPCB standards 41
4.2 Location of Tambaram subway 42
4.3 Noise parameters at Tambaram subway 43
4.4 Comparison of noise level with standards 44
4.5 Mixer machine in operation 45
4.6 Noise parameters for mixer machine operation 46
4.7 Vibrator machine in operation 47
4.8 Noise parameters for vibrator machine operation 47
4.9(a) Driven piling operation 48
4.9(b) Concreting of driven pile 49
4.10 Noise parameters for piling operation 49
4.11 Variation of pile operation in a day 50
xiii
List of Figures
Figure No. Figure Description Page
No.
4.12 Marble cutting process 51
4.13 Noise parameters for marble cutting operation 52
4.14 Jack hammer operation 53
4.15 Noise parameters for jack hammer operation 54
4.16 Noise parameters for vehicle manufacturing years 55
4.17 Perungalathur railway station and adjoining places 56
4.18 Level crossing near Perungalathur railway station 57
4.19 Noise parameters for the railway station location 57
4.20 Flour mill selected for observation 59
4.21 Noise parameters for flour mill operation 59
5.1 Comparison of Leq with CPCB standards for both
locations
61
5.2 Noise level compared with CPCB standards 63
5.3 Noise level compared with CPCB standards 64
5.4 Perungalathur station and level crossing location 66
5.5 Noise parameters for the railway station location 67
xiv
List of Figures
Figure No. Figure Description Page
No.
5.6 Noise parameters for cars 68
5.7 Flour mills operation compared with standards of
CPCB
69
5.8 Comparison between a traffic streams with flour
mill noise level
70
5.9 Thatched leaves noise barrier at Toll Plaza location 74
5.10 Thatched leaves noise barrier at SRP tools Junction 74
5.11 Concrete noise barriers as cubicles at SRP Tools
location
77
5.12 Concrete noise barriers as cubicle at Toll Plaza
location
78
5.13 Noise parameter for Toll Plaza location 78
5.14 Noise parameter for SRP tools location 79
5.15 View of noise barrier as a cubicle made of fly ash at Toll
Plaza location
81
5.16 View of noise barrier as a cubicle made of fly ash at
SRP tools location
81
5.17 Noise parameters at Toll Plaza with and without fly
ash cubicles
82
5.18 Noise parameters at SRP Tools with and without fly
ash cubicles
82
5.19 Details of noise reduction at both locations 83
xv
List of Figures
Figure No. Figure Description Page
No.
6.1 R value corresponding to Leq value 91
6.2 Distribution of predicted Leq and measured values 92
6.3 Frequency distribution 95
6.4 Spectrum of open traffic stream at SRP tools
location
99
6.5 Spectrum of Tambaram Subway 100
6.6 Spectrum of Construction noise 101
6.7 Spectrum of Cars manufactured in different years 103
6.8 Spectrum of railway station, level crossing and
outside traffic
104
6.9 Spectrum of flour mills 105
6.10 Spectrum of flour mills and open traffic 105
6.11 Spectrum of thatched shed to attenuate noise 107
6.12 Spectrum of cubicles made of concrete cubes 107
6.13 Spectrum of cubicles made of fly ash bricks 108
6.14 Power spectrum for traffic stream 115
6.15 Power spectrum for Kolapakkam Porur Road 115
6.16 Power spectrum for jack hammer 116
6.17 Power spectrum for flour mill – mirchi 116
6.18 Power spectrum for Perungalathur level crossing 117
6.19 Power spectrum for Perungalathur railway station 117
6.20 Power spectrum for thatched shed second layer 118
6.21 Power spectrum for concrete cubicles 118
6.22 Power spectrum for fly ash cubicles 118
xvi
List of Tables
Table No. Table Description Page
No.
1.1 Comparison of noise levels from different studies in
India
4
1.2 Guidelines on noise pollution by MoEF (GOI) 5
1.3 Permissible noise levels by CPCB 5
3.1 Details of noise pollution from pedestrian sources and
noise generation hours
36
3.2 Details of noise pollution sources and noise generation
hours
36
3.3 Noise duration of different years of manufacturing of
car
37
3.4 Details of noise pollution from railway station and
crossing
37
3.5 Details of noise pollution from flour mills and
exposure time in hours
38
3.6 Details of traffic noise recorded using barriers 38
4.1 Consolidated values of noise parameters for Toll Plaza
location (dBA)
40
4.2 Consolidated values of noise parameters for SRP tools
location (dBA) 40
xvii
List of Tables
Table No. Table Description
Page
No.
5.1 Showing noise parameters for noise barrier made of
thatched shed
75
5.2 Details of noise reduction at both locations 76
5.3 Details of noise reduction at both locations 80
5.4 Details of noise reduction at both locations 83
5.5 Comparison of all barriers provided in the study area 85
6.1 Variables used and their respective representation 90
6.2 Comparison of predicted model with other developed
models.
93
6.3
6.4
6.5
File Management Commands
Frequency and power distribution
Max energy and corresponding frequency
97
120
123
Annexure I Frequency range and corresponding decibel range for
values presented: Table A
131
xviii
List of symbols and abbreviations
AM Anti Meridian
Ave Average
cm Centimeter
contd Continued
CPCB Central Pollution Control Board
CSP Coral Shell Powder
dBA Decibel at A scale
e.g Example
eq Equivalent
FFT Fast Fourier Transformation
GOI Government of India
HCV Heavy Commercial Vehicle
HGV Heavy Geared Vehicle
hr Hour
Hz Hertz
IRC Indian Road Congress
KMPH Kilo Meter Per Hour
KPR Kolapakkam Porur Road
LCV Light Commercial Vehicle
LFN Low Frequency Noise
LGV Light Geared Vehicle
xix
List of symbols and abbreviations
m Meter
Max Maximum
MCI Medical Council of India
Min Minimum
Mins Minutes
mm Millimeter
MoEF Ministry of Environment and Forest
NC Noise Climate
NGO Non Governmental Organisation
No Number
Np Noise pollution
OMR Old Mahabalipuram Road
PM Post Meridian
SD Standard Deviation
Sec Seconds
Sl. No Serial Number
TNI Traffic Noise Index
2D Two Dimensional
3D Three Dimensional
% Percentage
1
CHAPTER 1
INTRODUCTION
1.1 General aspect of noise pollution
Sound that is unwanted or disrupts one’s quality of life is called as noise. When
there is a lot of noise in the environment beyond certain limit, it is termed as noise
pollution. Sound becomes undesirable when it disturbs the normal activities such as
working, sleeping, and during conversations. It is an underrated environmental problem
because of the fact that it can’t be seen, smelt, or tasted. World Health Organization
(Report 2001) stated that “Noise must be recognized as a major threat to human well-
being”
Noise is normally defined as 'unwanted sound'. A more precise definition could
be: noise is audible sound that causes disturbance, impairment or health damage. The
terms 'noise' and 'sound' are often synonymously used when purely acoustical
dimension is meant (e.g., noise level, noise indicator, noise regulation, noise limit, noise
standard, noise action plan, aircraft noise, road traffic noise, occupational noise, etc.).
The link between exposure and outcome (other terms: endpoint, reaction, response) is
given by reasonably well-established exposure-response. Managing noise is crucial for
enhancing the living condition of a dwelling. Noise can be generated internally within a
building (e.g., noise from surrounding neighbors’ voices, music or appliances) or
externally (e.g., traffic noise from automobiles, buses, trains, aircraft, industrial
activities or surrounding construction activities). Noises (or impact of sounds) are
transmitted through building materials from sound sources such as vehicular or foot
traffic, banging, or objects being dropped to the floor and can also be associated with
vibrations. The design solutions for limiting air‐borne and structure‐borne noises are not
always the same as stated by Li et al (2000).
2
1.2 Sources of noise pollution
� Transportation systems are the main source of noise pollution in urban areas.
� Construction of buildings, highways, and roads cause a lot of noise, due to the
usage of air compressors, bulldozers, loaders, dump trucks, and pavement
breakers.
� Industrial noise also adds to the already unfavorable state of noise pollution.
� Loud speakers, plumbing, boilers, generators, air conditioners, fans, and vacuum
cleaners add to the existing noise pollution as per environmental protection
bureau (Anon. 2010a).
1.3 Effect of noise pollution
The effects of noise are seldom catastrophic, and are often only transitory, but
adverse effects can be cumulative with prolonged or repeated exposure. Sleep
disruption, the masking of speech and television, and the inability to enjoy one's
property or leisure time impair the quality of life. In addition, noise can interfere with
the teaching and learning process; disrupt the performance of certain tasks, and increase
the incidence of anti-social behavior (Mangalekar et al 2012).
� According to the MCI, there are direct links between noise and health. Also,
noise pollution adversely affects the lives of millions of people.
� Noise pollution can damage physiological and psychological health.
� High blood pressure, stress related illness, sleep disruption, hearing loss, and
productivity loss are the problems related to noise pollution.
� It can also cause memory loss, severe depression, and panic attacks.
Noise is a disturbance to the human environment and is escalating at such a high
rate that it will become a major threat to the quality of human lives. Noise in all
localities, especially urban areas, has been increasing rapidly during the last few
decades. To prevent this and ensure that the level of pollution emission will not exceed
the legal limits, Gilchrist et al (2003) have described some positive measures to
eliminate the noise pollution.
3
1.4 Present scenario in the Indian context
In India, the problem of noise pollution is wide spread. Several studies report
that noise level in metropolitan cities exceeds specified standard limits. Figure 1.1
shows the existing traffic condition in the study area selected for the research work.
Figure 1.1 Traffic congestion in the study area
Road traffic is a major source of noise in urban areas with far-reaching and wide range
effect to human. India as a developing country, traffic noise pollution is serious enough
in its urban and suburban areas. A simple comparison in Table 1.1 shows the present
noise levels at different places in India.
4
Table 1.1 Comparison of noise levels from different studies in India
City name Silent zone Residential
zone
Commercial
zone
Industrial
zone
Kolhapur Mangalekar et al (2012)
50.02 58.88 65.52 74.28
Melmaruvathur Dinesh Kumar et al (2012)
36.50-92.60 51.40-102.40 42.60-102.40 40.20-99.20
Vishakapatnam Vidyasagar et al (2006)
43.0-60.00 45.00-77.00 70.00-90.00
Ambur Thangadurai et al (2005)
47.20-80.40 30.60-83.60 40.00-96.40
Burdwan Datta et al (2006)
60.00-90.00 69.00-110.00
Bolpur- Santiniketan Pratapkumar et al (2006)
20.50-78.50 25.00-80.50 42.00-98.00
Gwalior Kursheed et al (2010)
45.50-69.30 51.70-77.20 64.50-119.20
Lucknow Narendra et al (2004)
67.70-78.90 74.80-84.20
Dehradun Avinash et al (2010)
55.60-104.80
55.30-107.60 59.60-118.20 74.80-104.30
Mangalore Sanjeeb et al (2012)
43.20-97.20 50.60-97.00 56.00-99.00 51.00-91.80
Chidambaram Balashanmugam et al (2013)
54.33-84.33 57.00-75.60 86.00-101.00
OMR (Present study 2012) 44-105
From the observed noise level in various studies carried out in different parts of India it
was found that, all other urban areas faced similar trend of noise pollution. Thus, there
is a need to create awareness among the people and educate the citizens about the rising
noise pollution; health effects, etc. Therefore a key message that has to be disseminated
is that control of noise at individual’s level will control noise pollution. There are many
legal provisions to control or check the noise pollution. Many laws and acts have been
amended to prevent the noise pollution but serious implementation of these laws has not
yet taken shape.
1.5 Statutory Guide Lines
The relevant guideline specified by competent authorities like MoEF and CPCB (2000)
are shown in Table 1.2 and Table 1.3
5
Table 1.2 Guidelines on noise pollution by MoEF (GOI)
Category of Domestic Appliances/ Construction
Equipments
Noise limits in dBA
(a) Window air conditioners of 1 tonne to 1.5 tonne 68
(b) Air Coolers 60
(c) Refrigerators 46
(d) Diesel Generator for domestic purposes 85 - 90
(e) Compactors (rollers), front loaders, concrete
mixers, cranes (movable), vibrators and saw 75
Construction Activities – measures of abatement
Acoustic barriers should be placed near construction sites.
The maximum noise levels near the construction site should be limited to 75 dBA
Leq (5 min.) in industrial areas and to 65 dBA Leq (5 min.) in other areas.
There should be fencing around the construction site to prevent people coming
near the site.
Materials need not be stockpiled and unused equipment to be placed between noisy
operating equipments and other areas.
Constructing temporary earth bund around the site using soil, etc., this normally is
hauled away from the construction site.
Table 1.3 Permissible noise levels by CPCB (2000)
Sl. No Zone Noise Level in dBA
Day Time Night Time
1 Industrial 75 70
2 Commercial 65 55
3 Residential 55 45
4 Silence 50 40
6
1.5 Objectives and Scope of this research
The objectives of this research are to measure the noise pollution levels
generated due to vehicles and machinery and also to devise a cost effective, viable
simple solution for noise attenuation.
� To determine the level of noise pollution along the noise disturbed places
� To check whether any noise attenuation is required
� To evaluate the existing noise control measures
� To suggest suitable noise attenuation measures to reduce noise pollution
� To analyse the attenuation of noise by providing the noise barrier
� To compare the efficacy of different noise barriers and suggest suitable
barrier depending upon its adaptability
� To develop noise models to predict noise pollution
� To do spectrum analysis on noise levels generated using MATLAB
software
The scope of the research conducted based on the above objectives was
recording of noise levels recorded at different noise generating sources viz.,
vehicular traffic, flour mills, construction machinery and railway stations. A
detailed study has been arrived and noise levels were recorded, compared and
presented. Attenuation of noise levels using barriers of different materials was tried
to find a cost effective noise attenuator and a comparative study made.
Noise levels due to road traffic varying spatially in different time periods are to
be measured. A comprehensive study has to be conducted with a view to understand
the noise related problem. A collective measurement technique has to be adopted
for the accurate determination of the acoustical environment of an area and source
of noise generation. The noise levels are proposed to be recorded by conducting
onsite measurements of noise levels using noise meters for a period of 8 hours and
all the values are logged. The noise levels are to be used for calculating equivalent
noise level and compared with the CPCB and MoEF guidelines. At all places of
study it was found that the noise levels measured were above the acceptable
standards. Hence an urgent need to control the noise pollution and to attenuate noise
with cost effective simple solutions is necessitated in developing countries like
India. The study also covers a review of the existing control measures and suggests
7
improvement such as barrier provision to attenuate noise levels. Three different
types of noise attenuating barriers viz., thatched shed, concrete cubicles and fly ash
cubicles are proposed to be constructed on a traffic road. Noise levels are to be
measured within and outside the barriers and a comparative study is to be carried
out. The reduction in noise levels due to the provision of barriers is to be
established.
It is also proposed to address the problem of low frequency noise as people’s
hearing sensitivity varies from one individual to another that is often the case that a
low frequency noise which is heard by one person is not heard by another. An A-
weighting network capturing low frequency noise is to be utilised to analyse
frequency spectrum through FFT (Fast Fourier Transform) analyser to arrive a band
spectrum displaying the amount of LFN generated in all sources of noises.
8
CHAPTER 2
LITERATURE REVIEW
2.1 General
Human needs for transportation has always been evolving and growing with
time. In early days man had depended on himself and animals for carrying on
transportation tasks. According to history, wheeled vehicles had existed some thousand
years ago. Presently solid wheeled vehicles combined with automatic controls have
come into existence. India seems to be one of the lands where roads received
considerable attention quite early to serve the needs for the transportation requirements.
Road development is very important for economic development of any region.
In order to increase the efficiency of the transportation system new roads are laid and
existing one are being improved.
Traditionally road work is labor intensive and requires deployment of heavy
machinery. Well mechanized operations are carried out in metropolitan areas. Since
road projects are generally intended to improve the economic and social well being of
people increased road capacity and improved pavements can lower the costs of vehicle
use and also reduce the transportation costs for both freight and passenger traffic.
With all the important aspects of road projects it has significant positive aspects
and negative aspects on nearby communities and the natural environment. Primary
disturbance to the natural environment may include aesthetic, air quality, circulation,
traffic pattern, social disturbance, soil erosion, noise hindrance, water quality, and wild
life, etc. There are other secondary effects such as change in land use, social
development, mass movement, etc.
Environmental impact arising out of any project falls in four categories
• Direct impact
• In direct impact
9
• Cumulative impact
• Post impact
The above impacts are further categorized according to nature as
• Positive and negative impact
• Random, predictable, and sensitive impact
• Local, wide spread impact and adverse impact
• Temporary, permanent and tertiary impact
• Short and long term impacts
Impacts are sometimes easier for inventory, assessment and control, since the
relationship between cause and effect is usually obvious. In some cases impacts are
more difficult to measure and ultimately important to profound for consequences. Over
time they can affect larger geographical areas of environment than anticipated.
To qualify environmental impact by the type of effect they have on the environment
is not sufficient. Impact must also be categorized according to their seriousness. The
most damaging and longest lasting impact will obviously be the first to be avoided and
mitigated.
Additionally there can be effects on vegetation, water flow and siltation. Road work
in build up areas can be a source for dust and noise. The most pronounced effects of
road transport were exhaust gases and noise emitted by vehicles. In metropolitan areas
there is a high level of air pollution as well as noise pollution along road ways.
Most of the impacts can be mitigated through proper engineering design and applying
environmentally appropriate construction methods.
To mitigate these adverse impacts a range of measures are available. But how far those
measures are successful is to be researched (Dasarathy and Thandavamorthy 2013a).
It is now becoming important that environment friendly measure is mandatory.
The consequences are to be analyzed at the planning stage and it has to be monitored
continuously. Now a day, post impact study is given less important after completion
and commissioning of any project. This thesis will focus on a particular source of
environmental pollution like noise pollution and compare with the help of publications
in the literature. The researcher is able to demonstrate how far the mitigating measures
10
which are the primary functions for Environmental Impact Assessment studies are
insufficient.
2.2 Purpose of literature review
In this chapter an extensive review of literature has been carried out with regard
to noise pollution, causes, and sources for different aspects. These reviews will
emphasis on all formations relating to environmental considerations for the occurrence
of any noise pollution.
To qualify noise pollution by the type of effect they have on the environment is
not sufficient. Impact must also be categorized according to their seriousness. The most
damaging and longest lasting impact will obviously be the first to be avoided and
mitigated. The collection of literature ranges from the year 1986 to the year 2014. The
references are arranged in a systematic manner to assist realization of the objective of
the study. Even though some of the references are not directly related to the thesis but
are still included because of their usefulness and relevance.
Extensive survey of literature in terms of research reports, technical papers, journal
articles, conference proceedings, websites and brochures containing theoretical
calculations, experimental calculations, field applications and practical stimulations of
barriers was carried out.
2.3 Review of published papers
The published papers available in the open literature are collected and categorized
based on the following headings
• Noise pollution defining the noise and explaining about noise pollution causes,
effects and mitigation measures.
• Noise pollution and its health effects
• Noise from different sources
• Noise generation from construction operations
• Noise guidelines from competent authorities
• Noise control measures
• Noise barriers forms and types of barriers
11
• Noise prediction models
• Noise spectrum analysis for frequency distribution
The policy section of the Environmental Policy Branch Environment Protection
Authority (Report 1999) on Environmental criteria for road traffic noise from noise
report shows that there are needs for programs to complement strategies that are geared
towards reducing motor vehicle use with more effective ways of managing existing
levels of traffic noise, through influencing the nature of road design, road use and
development adjacent to roads. Maximum noise levels during the night-time period (10
pm – 7 am) should be assessed to analyze possible affects on sleep. The assessment
should encompass the likely maximum noise levels due to road traffic, the extent to
which these maximum noise levels exceed ambient noise levels, and the number of
noise events from road traffic during the night on an hourly basis for a ‘typical’ night.
Noise levels that are attributable to sources other than road traffic, including sirens on
emergency vehicles, should be discarded. When describing the measurement and
analysis procedures used in any monitoring program, details of the method used to be
given to determine maximum noise levels.
Noise pollution levels in Visakhapatnam City (India) have been reported by Vidya
Sagar and Nageswara Rao (2006). Visakhapatnam is an industrial and sea port city
located on the east coast of India. A hospital (RCD hospital), residential area (Lawson’s
Bay Colony), traffic zone (Jagadamba junction, Andhra Pradesh State Road Transport
Corporation Complex junction and Seethammadhara junction) and industrial zone (sea
port) were chosen to monitor the noise levels. The observed noise level at RCD hospital
was more than 10 dBA at any time. The background noise at Santhi Ashram was
approximately 3 dBA less at night time and 2 dBA less at day time compared to ambient
air quality noise standards (AAQNS) for silent zone. The ambient air quality noise levels
(AAQNL) at traffic junctions were 5 dBA or more than those prescribed by AAQNS for
commercial zone and most of the values were found in the range of 80 + 10 dBA, among
which 75% values were found in the range of 110 + 10 dBA. AAQNL near port were
found in the range of 5 to 10 dBA positive shifts on AAQNS due to conveyor operation.
The AAQNL were alarming even in the absence of conveyor system, indicating the
impact of vehicular traffic. Remedial measures were suggested separately for each
situation.
12
A Draft Comprehensive Plan to Tackle Road Traffic Noise in Hong Kong the
Digest Environmental Protection Department (Anon. 2006a) Hong Kong is one of the
densest cities in the world with most of the 6.9 million people being housed in 225
square kilometers of development. Similar to other metropolitan cities, Hong Kong is
facing significant road traffic noise problems. Excessive road traffic noises deteriorate
the quality of life. Similar to other metropolitan cities, many residents in Hong Kong
are exposed to high level of road traffic noise. Although the Government has taken
many proactive actions, road traffic noise still remains the most severe environmental
noise problem. The Government would continue to adopt a "balanced, integrated,
proactive and transparent" strategy in tackling road traffic noise. All relevant
stakeholders would be consulted to conduct necessary feasibility studies and seek
funding and resources to develop and implement the proposed enhanced measures to
tackle the road traffic noise problems. Support from all stakeholders and in partnership
with them is crucial in this common endeavor to pursue a satisfactory noise
environment
Assessment of noise quality in Bolpur- Santiniketan areas of India was made by
Padhy and Padhi (2005). Noise is a prominent feature of the environment including noise
from transport, industry and neighbors. An important part of noise assessment is the
actual measurement of the noise levels. Continuous Leq measurement during day time
(0600 – 2100 hr) was carried out in residential, commercial and silence zone location of
Bolpur-Santiniketan areas during June-December, 2005. The results show that the noise
pollution in the city is wide spread throughout most of its area. The noise in this area is
composite in nature. Public participation, education, traffic management and structural
designing play a major role in noise management.
Gwalior is an important historical city of Madhya Pradesh, India. Rising level of
transportation mainly by road vehicles i.e., tempos, rickshaws, four wheelers, two
wheelers and heavy vehicles is one of the major source of augmented noise pollution in
Gwalior. The ambient noise level was measured by using Sound Level Meter SL- 4010.
The highest noise level was recorded at commercial area like railway station and
accordingly a maximum of 119.2 dBA at Batmorar and 92.7 dBA at Thathipur followed
by residential zone a maximum of 69.8 dBA at Pinto Park and 77.2 dBA at Lascar and
silence zone 64 dBA at Madhav dispensary and 65.8 dBA at Jiwaji campus were found.
13
The noise level values far exceeded the standards set by the CPCB. A cross-sectional
study on the basis of questionnaire was carried out the results of which revealed that
100% of the respondents were not wearing ear protective equipments. Noise annoyance,
headache, speech interference, etc., have been reported by various shopkeepers. Various
mitigation measures have been suggested to keep the noise level within the prescribed
standards (Wani and Jaiswal 2010).
Singh and Davar (2004) in their paper on Noise pollution - sources, effects and
control describe the life of the people. Cross-section surveys of the population in Delhi
State points out that main source of noise pollution are loudspeakers and automobiles.
However, female population is affected by religious noise a little more than male
population. Major effects of noise pollution include interference with communication,
sleeplessness, and reduced efficiency. The extreme effects e.g., deafness and mental
breakdown neither is ruled out. Generally, a request to reduce or stop the noise is made
out by the aggrieved party. However, complaints to the administration and police have
also been accepted as a way of solving this menace. Public education appears to be the
best method as suggested by the respondents. However, government and NGOs can
play a significant role in this process.
Chanhan and Pande (2010) deal with monitoring of noise pollution at different
zones of Dehradun, Uttarakhand, India. Exposure to high level of noise may cause
severe stress on the auditory and nervous system. Transportation and horn used in
vehicles are the major sources of noise pollution in Dehradun City.
The assessment of noise pollution can be made through measurements which,
however, are restricted to a limited number of points. The simulation of the sound waves
propagation enables the study of a whole region in respect to the expected sound pressure
levels as a result from existent sound sources. Of course, in order to perform a meaningful
simulation, the environmental properties as well as the characteristics of the sound sources
must be modeled. The results obtained may be gathered and presented graphically as in a
so called noise map. Actual measurements are used to verify and adjust the simulation to
the real situation. Noise mapping techniques together with standards for the calculation of
noise propagation are powerful tools to aid urban planners in correctly applying noise
abatement measures in an economically feasible way. Nevertheless, the results of such
mappings rely on a great amount of data, location and strength of noise sources, ground
14
geometry, location and geometry of buildings, etc. This work also discusses the sensitivity
of the obtained simulated noise levels to the quality and precision of the geometric data
available. Actual measurements are however, needed only to verify the model Fernando
and Pinto (2010).
A study and comparison of the noise dose on workers in a small scale industry in
West Bengal, India, was conducted by Sen and Bhattacharjee (2008). This paper refers to
a study and effect of noise dose in a small scale manufacturing sheet metal industry
situated in West Bengal of India. Different noise related data were taken from
individual machine and compared with the different noise related variables with Leq,
Lav, LAE and TWA (Time weighted average). Noise induced hearing loss (NIHL),
which is creating highly environmental pollution, causes the leading occupational
disease. For the development of age related hearing loss, it creates a major contribution.
A noise related hearing loss reduction for workers is proposed in this paper.
Agbalagba et al (2013) conducted a survey on noise pollution levels in four
selected sawmill factories in Delta State. The physical measurement assessed the noise
level of different machines in the factories and the background noise levels were
measured at 50 meters away from the factories. A mean level of machine noise
pollution (and background noise level) of 103.77 ± 4.71 dBA (78.25 dBA), 96.55 ±
1.48 dBA (72.08 dBA), 99.02 ± 3.20 dBA (72.54 dBA), 99.97 ± 3.66 dBA (79.89 dBA)
was recorded in Ozoro, Ughelli, Warri and Sapele, respectively. These recorded values
show that the noise levels in the four factories investigated are well above the federal
environmental protection agency (FEPA) recommended maximum permissible limits
for an industrial environment. This may cause hearing impairment and some
psychological effect like susceptibility to mistake, irritation, and sleeping and social
discomfort among staff and resident living in close vicinity to these factories. This is
further affirmed by the social survey which revealed the level of social discomfort and
health menace caused by machines noise from the factories on the workers and those
residing close to these factories. Recommendations were therefore made to control, and
abate this health threatening pollution effects.
Ehrampoush et al (2011) conducted a noise pollution study in Yazd city, Iran.
The aim of the study was to determine noise pollution in different parts of Yard’s city in
2010 and to compare them with current standard levels. A total of 135 samples were
15
obtained from both residential and commercial areas according to the ISO1996-2002
method in order to measure noise pressure levels. Locations included 10 streets and 5
squares of city and the measurement times were considered in the morning, afternoon
and evening. Noise level was determined in A-weighted by sound level meter model
2232. Results showed that the rate of background noise in Yazd city was high as it was
71.24 ± 4 dBA, 66.23 ± 7 dBA and 60.3 ± 4 dBA in the L10, L50 and L90, respectively.
The mean level of maximum noise pressure was 74.3dBA and mean Leq was 66.7dBA.
Comparing the noise level obtained in the present study to the standard level, it can be
obviously concluded that the noise levels are higher than that of acceptable levels in
most parts of the city. So, different preventive counter measures such as increasing
public awareness through educational programs and technical controls for the future
development of the city are crucial.
Mangalekar et al (2011) conducted a study of noise pollution in Kolhapur city,
Maharashtra, India. Kolhapur city is a district place in the state of Maharashtra, India
with population of 5,49,283. It is one of the emerging industrial and commercial cities
of Western Maharashtra. Problems of pollution along with noise pollution are
increasing with time, especially, due to the increase in the number of vehicles for
transportation. In the present study, continuous monitoring of noise levels Leq dB (A)
was carried out for three days in the month of December, 2011 at six different sites
within the Kolhapur city. On the basis of location, these sites were grouped into
industrial, commercial, residential and silent zones respectively. The average noise
level at industrial, commercial, residential and silence area were 74.28 dBA, 65.52
dBA, 58.88 dBA and 50.02 dBA, respectively. The results showed that there is an
enhanced pressure of noise at all sites due to increase in the number of vehicles and
facilities of transportation. All the sites under study showed higher sound level than the
prescribed limits of Central Pollution Control Board (CPCB).
Ambient noise level monitoring was carried out by Balashanmugam et al (2013)
at various locations of the Chidambaram town of Tamil Nadu, India during September –
November 2011. The data obtained was used to compute various noise parameters,
namely, equivalent continuous level (Leq), Noise pollution level (Lnp), Noise climate
(NC), Percentile noise levels (L10, L50, L90). The comparison of the data shows that the
noise levels at various locations of the Chidambaram town are more than the
permissible limits. Vehicular traffic and air horns are found to be the main reasons for
16
these high noise levels. This study examines the problems of reduction of individual's
efficiency in his/her respective working places because of road traffic noise pollution in
Chidambaram due to rapidly growing vehicular traffic. This paper deals with
monitoring of the disturbances caused due to vehicular road traffic interrupted by traffic
flow conditions on personal work performance. Traffic volume count and noise indices
data were collected simultaneously at ten selected sites of the town. The noise level
values far exceeded the standards set by the Central Pollution Control Board (CPCB).
Traffic noise measurements as well as social survey were conducted at different
locations along the National Highway No.17 at Mangalore, India by Mohapathra et al
(2012). Noise measurements were taken at 2 min and 5 min intervals. The measured
data were analyzed in the form of Leq value. From the survey results, perception of the
people and consequently the relationships between annoyances due to traffic noise and
other variables were established among residents, general public and shop owners with
the help of correlation analysis. Three prior models were constructed based on the
strong correlation coefficient for different degree of annoyance for different parts of a
day.
The study by Banihani and Jadaan (2012) provided an evaluation of road traffic
noise pollution in the city of Amman and its effects on residents. Statistical noise index
L10 (18 hr) was measured at nine different sites throughout the city of Amman. The
British Calculation of Road Traffic Noise (CRTN) method was used to predict noise
levels at the chosen sites. The results showed that Amman was environmentally noise
polluted at the studied locations with noise levels ranging between 80.41 dBA and
83.71 dBA; thereby exceeding the maximum allowable limit of 63 dBA. The
effectiveness of noise barrier walls in reducing noise levels was investigated. Noise
barriers 5 meter high were found to be effective in reducing noise levels below the
permissible limits at all sites. A social survey was carried out to evaluate the perceived
noise impacts of road traffic noise on residents. The results of the survey revealed that
road traffic noise was a major concern for the communities living in the vicinity of
streets.
The World Health Organization (WHO) carried out an assessment of the global
disease burden from occupational noise, as part of a larger initiative to assess the impact
of 25 risk factors in a standardized manner (Report 2001). This guide was built on the
global assessment, by providing a tool for occupational health professionals to carry out
17
more-detailed estimates of the disease burden associated with hearing loss from
occupational noise at both national or sub national levels. It was complemented by an
introductory volume on methods for assessing the environmental burden of disease. The
present guide describes how to quantify the burden of disease associated with hearing
impairment from occupational noise. The following topics are described:
− Noise characteristics and their relevance to workers’ health;
− Criteria for selecting health outcomes for the burden of disease assessment;
− Methods of assessing exposure to workplace noise, for all segments of a
population;
− Relative risk data for the main health outcome of occupational noise;
− Procedures for generating a summary measure of the burden of disease from
occupational noise;
− Sources of uncertainty in disease burden estimates;
− Policy implications.
The European Environmental Agency released a report on Good Practice guide
(Anon. 2010b) on noise exposure and potential health effects. The main purpose of this
document is to present current knowledge about the health effects of noise. The
emphasis was first of all to provide end users with practical and validated tools to
calculate health impacts of noise in all kinds of strategic noise studies such as the action
plans required by the Environmental Noise Directive (END) or any environmental
impact statements. The basis of this was a number of recent reviews carried out by well
known institutions like WHO, National Health and Environment departments and
professional organisations. No full bibliography was provided but the key statements
were referenced and in the reference list, some documents were highlighted which
might serve as further reading.
Noise is a stressor of today for man’s working and living place. Therefore, the
present study by Abolhasannejad et al (2013) was conducted aiming to compare the
noise sensitivity and annoyance among the residents of Birjand old and new districts. In
this analytical – descriptive study, using Weinstein noise sensitivity scale and the seven
point scale of noise annoyance based on ISO 15666 standards the rate of noise
sensitivity was measured as one of the attitudinal factors as well as that of noise
annoyance among individuals exposed to environmental noise. The result showed that
18
the mean total score of sensitivity was 63.5 ± 16.1 dBA. The highest and lowest scores
in noise sensitivity subscales associated with “sensitive to noise” and “attitude towards
noise in residence”, respectively. No significant difference was seen between total score
of noise sensitivity in old and new district among both sexes. Between “attitude towards
noise control” at illiterate and university education levels significant difference was
observed. Also, a significant difference was seen between noise annoyance in the old
district and job. The one way analysis of variance showed a significant difference
between annoyance degrees and noise sensitivity subscales. This research clearly
showed that most of the heavy traffic areas were located in the old district. Lack of
urbanization measures has caused noise pollution and dissatisfaction among the
residents. Regarding higher degrees of annoyance in the old district, probably caused by
heavier traffic, particularly by motorcycles and narrower streets, one can reduce noise
pollution and its subsequent physical and mental disorders by eliminating old and noisy
vehicles and expanding urban green spaces.
The report of most common sources of noise in the city (2010a) provides an
understanding of noise related problems. In order to enforce this objective, the New
York City Department of Environmental Protection (DEP) and the New York City
Police Department (NYPD) share duties based on the type of noise complaint. This
booklet is designed to provide an overview of the Noise Code and some of the most
common sounds of the city.
A study on characteristics of transportation noise sources in Klang Valley,
Malaysia by Yusoff and Karim (1997) stated that they detected the level of noise
pollution due to various modes of transportation, its effect towards the environment and
to look at some of the control measures that could be adopted to minimise the impact of
the noise emitted. Noise level measurements and recording were taken at a few selected
sites in the Klang Valley. From the hourly continuous noise levels recorded for 24
hours by using the sound level meter and noise level analyser, it had been found that
these areas were seriously polluted by these noise sources. Subsequently, the Lr, Lro,
Lo and Lq noise indices were identified and determined. Simultaneously, public survey
had also been conducted to gauge the existing public attitude and degree of awareness
towards contemporary transportation noise pollution problems.
19
A quantitative approach to construction pollution management and control
based on resource leveling by introducing parameters of construction pollution index
(CPI) and hazard magnitude (hi) was proposed by Li et al (2000). Using these
parameters, a method to predict the distribution of accumulated pollution level
generated from construction operations was presented. It was suggested that if the
pollution level exceeded the allowable limit, then construction activities needed to be
re-scheduled to ‘spread’ the pollution emissions. In doing so, pollution emission was
treated as a pseudo resource, and then applied to a GA based leveling technique to re-
schedule the project activities. The authors suggested that the proposed method for
controlling construction pollution was an effective tool that could be used by project
managers to reduce the level of pollution generated from a project at a certain period of
time. This method is useful when there is no other ways to reduce the level of pollution.
However, it is necessary to point out that the method proposed here can only
redistribute the amount of pollution over project duration so that at any specific period
of time, the level of pollution will not exceed the legal limit. In order to reduce the
overall amount of pollution, other methods, such as alternative construction
technologies, new materials, have to be applied.
As per Australian Construction Agency (2007) controlling construction noise
can pose special problems for contractors. Unlike general industry, construction
activities are not always stationary and confined at one location. Construction activities
often take place outside where they can be affected by weather, wind tunnels,
topography, atmosphere and landscaping. Construction noise makers, e.g., heavy earth
moving equipment, can move from location to location and is likely to vary
considerably in its intensity throughout a work day High noise levels on construction
worksites can be lowered by using commonly accepted engineering and administrative
controls. This booklet is filled with tips for contractors and to lower the noise levels on
construction worksites. Normally, earplugs and other types of personal protective
equipment (PPE) are used to control a worker’s exposure to noisy equipment and work
areas. However, as a rule, engineering and administrative controls should always be the
preferred method of reducing noise levels on worksites. Only, when these controls are
proven unfeasible, earplugs as a permanent solution should be considered.
Sellappan and Janakiraman (2014) have showed that untreated noise levels of
generator set were 100 dBA or more. From this it was clear that generator set noise
20
mitigation was a subject of great importance. The permissible exposure level 90 dBA
was reached at 7.0 m from G1 and 10.5m from G2 generator. The noise effects from
generators can be mitigated by introducing noise reduction screens or acoustic shields
around, or provide hard barricades to exclude the employee’s entry and minimize the
exposure in noisy zone. The combined noise exposure to workers ranges from 76.2
dBA to 92.5 dBA; this represents a cautionary risk of hearing damage to 600
construction workers involved in this work area. This scenario exists in many
construction sites wherever open generators are used for power generation and seeks
implementation of an effective hearing protection and awareness program. Furthermore,
the high cost of retrofitting a site for noise reduction makes it imperative to assess noise
performance requirements early in the on-site power system design stage. Working
closely with local regulations, a consulting engineer or acoustic specialist should be
involved in achieving the sound- attenuation goals. The first part of this paper assesses
the potential noise emissions associated with two unclosed caterpillar power generators
used in a construction site. In the second part combined noise effects of generators and
other activities are studied over a 12 hr period to establish background environmental
noise levels. The study shows large number of construction workers working nearby
generators are exposed to 100 dB (A) or more noise. The chain of noise control at the
source – along the noise path or at the receiver – and what effective steps could be
taken to mitigate the noise exposure at each stage are considered.
Gilchrist et al (2003) described a deterministic model for predicting the noise
levels that could be anticipated in the vicinity of construction operations. A growing
number of construction projects were performed in congested urban areas. Often, the
surrounding community founds these projects annoying because of noise, vibration,
dust, light, and greenhouse gas emissions. This paper focuses on one type of irritant,
noise. Common noise generators on construction sites are identified, and the elements
of a generic program for mitigating construction-related noise are outlined. Mitigation
strategies including source control, path control, and receiver control are discussed The
model uses the branch method together with standard attenuation and dissipation
equations developed in the areas of transportation and industrial engineering to estimate
the instantaneous noise level around a construction site. The Monte Carlo simulation
method is used to predict 500 possible outcomes using random determination of the
operation status of the various pieces of equipment involved. The model provides a
21
decision support tool for determining the need for noise-control measures at different
receptors
IOMA’s safety directors’ report (2003) says safety professionals know that
noise is one of those “facts-of-life” hazards wherever construction is going on. (There
seems little way around it—these projects make noise). But this mindset may be
putting workers at unnecessary risk, according to experts barriers must be placed
between the noise source and exposed workers.
_ Enclose the noise source. Use a quieter noise source or reduce the noise at the
source through engineering retrofit.
_ Increase the distance between the noise source and workers exposed to it.
_ Use active noise-control equipment, such as “white noise” generators.
_ Improve the maintenance of equipment including keeping blades sharp.
_ Purchase quieter equipment when new or replacement equipment is needed.
_ Schedule the use of a noise source when the fewest workers are present.
_ Limit the dropping of materials from heights.
_ Post noise warning signs and signs that remind workers to wear noise-
protection devices.
Study by Fernandez et al (2010) states that there are several noise sources in the
construction sector that may affect the workers along the whole construction work. So,
seven different construction sites have been considered (three housing blocks, three of
single family dwellings and one warehouse), where 40 workers have been measured. In
general, it can be stated from the data achieved that the sound environment which the
construction workers are within is quite noisy and potentially harmful to health, since
the lower limit of 80 dBA is exceeded in most of the cases, and even more, the
percentage of cases that go beyond the top limit of 87 dBA is quite high Usually, three
types of actions are considered in the working procedures of the industrial hygiene to
try to control the noise: on the source (for instance by using machines with less noise
emissions and properly labeled: on the environment (for instance by using enclosures
and barriers and on the worker (essentially by using hearing protection devices).
Noise guidelines given by MoEF and supported by CPCB standards presented
ambient air quality standards for the noise pollution from the different sources. Whereas
the increasing ambient noise levels in public places from various sources, inter-alia,
industrial activity, construction activity, generator sets, loud speakers, public address
22
terms, music systems, vehicular horns and other mechanical devices have mysterious
effects on human health and the psychological well being of the people; it is considered
necessary to regulate and control noise producing and venerating sources with the
objective of maintaining the ambient air quality standards in respect of noise. All the
factors are considered in the standards formation and they are listed.
Mitigation measures against road traffic noise in elected places prepared by
Hong Kong research library (Anon. 2006b) to tackle this subject, it had been suggested
by Members that a comprehensive study should be conducted with a view to
understanding the present government policy and mechanism in determining the need
for mitigation measures and the scope of measures, including noise barriers, which can
be put in place. The study should also cover the measures and improvement works
undertaken by other densely populated urban cities under similar circumstances. As the
mitigation of traffic noise falls within the terms of reference of the Panel on
Environmental Affairs (the EA Panel) of LegCo, it was agreed that the study be steered
by the EA Panel, with all Members, in particular members of public work
subcommittee (PWSC), invited to participate in the study.
Paper by Choudhari et al (2011) has reported that noise generated from various
industrial activities can disrupt the activities. The scope and purpose of this is to control
or minimize the noise pollution and its effects on human being. Noise control method
can be classified as noise control at source, during transmission and at the receiver.
Using these noise control methods, the noise level can be reduced up to the desired
level, i.e., 70 dBA. There are two basic ways of eliminating noise at sources; through
the design or modification of machinery itself or through isolation or enclosure of the
noise source. Noise can be controlled along the path through separation of worker from
noise sources and use of barriers or reflector. Acoustical control is one of most popular
technique available for absorbing noise. This paper presents the principles of noise
control, various noise control techniques, use of noise control materials at saw mill.
According to Queens Land University of Technology, Australia (2009) in their
high‐density livability guide on noise mitigation it is important to insulate and provide
barriers against noise, and also it is important to look at measures to control noise at the
source. Managing noisy neighbors can be achieved through following good neighbor
protocols. This factsheet focuses on ways to reduce the impacts of both air‐borne and
structure‐borne noise which may undermine the livability of dwellings for residents. It
23
was recommended guidelines for the Residents, Building Managers, Designers and
Developers for managing noise in the dwelling.
According to the course conducted by Birla Institute of Technology and Science
(BITS) Pilani (Anon. 2013) identifies the sources of noise pollution. Once identified,
the reason(s) for increased noise levels to be assessed. Now, efforts shall be made to
reduce the undesired noise levels from (unwanted) noise generating sources. This leads
to marginal reduction of noise levels. It is still unbearable scientific methods of noise
control. The Statutory Regulations have prescribed the noise level exposure limits. The
public may complain to the Statutory Board for violation of noise level limits by any
noise generator. Suitable action will be taken to attenuate the noise levels and
controlling pollution. It is advisable that suitable noise control measures be taken and
reduces the interference of Statutory Board. It is high time that everyone should do this
a bit in curbing the noise pollution, which is otherwise becoming as effective as SLOW
POISONING.
As per Colin et al (2010) on engineering noise control defines the noise problem
and set a good basis for the control strategy. The following factors should be
considered:
_ Type of noise
_ Noise levels and temporal pattern
_ Frequency distribution
_ Noise sources (location, power, and directivity)
_ Noise propagation pathways, through air or through structure
_ Room acoustics (reverberation).
In addition, other factors have to be considered; for example, number of exposed
workers, type of work, etc. If one or two workers are exposed to noise pollution,
expensive engineering measures may not be the most adequate solution and
other control options should be considered; for example, a combination of
personal protection and limitation of exposure. The need for control or
otherwise in a particular situation is determined by evaluating noise levels at
noisy locations in a facility where personnel spend time.
24
As per Indian Institute of Technology Roorkee (Anon. 2012) explains the
control techniques to vehicle noise and vibration, and number of ways in which the
final sound radiation may be influenced:
�Reduction at the source of combustion forces and mechanical forces.
�Reduction of the vibration transmission between the sources and the outer
surface.
�Reduction of the sound radiation of the outer surface.
The Report on the Status of Rubberized Asphalt Traffic Noise Reduction in
Sacramento County (1993) is a joint study prepared for the Sacramento County Public
Works Agency, Transportation Division by the Sacramento County Department of
Environmental Review and Assessment and Bollard and Brennan, Inc., consultants in
acoustics and noise control engineering. The purpose of this report is to document the
effectiveness of rubberized asphalt as a traffic noise mitigation measure. Rubberized
asphalt is a bituminous mix, consisting of blended aggregates, recycled rubber and
binding agents. The rubber is often obtained from used tires. Studies conducted locally,
nationally, and internationally, have shown that rubberized asphalt can reduce the noise
pollution that is associated with roadway traffic. The specific findings of this analysis
are based primarily on a series of traffic noise level measurements conducted along the
Alta Arden Expressway, between Howe and Watt Avenues, from 1993 to the present.
The conclusions of the 6-year study indicate that the use of rubberized asphalt on Alta
Arden Expressway resulted in an average four (4) decibel reduction in traffic noise
levels as compared to the conventional asphalt overlay used on Bond Road. This noise
reduction continued to occur six (6) years after the paving with rubberized asphalt. This
degree of noise attenuation is significant, as it represents a 60% reduction in traffic
noise energy, and a clearly perceptible decrease in traffic noise. This traffic noise
attenuation from rubberized paving is similar to the results documented in several non-
related studies conducted in recent years at other locations, both nationally and
internationally (Milford et al 2012) have measured and investigated noise barriers, facade
insulation, quieter road surfaces and development and production of quieter vehicles The
purpose of this paper is to provide support when strategies, plans and positions for future
actions are discussed in order to reduce adverse noise effects more effectively. The paper
compares the effectiveness of different types of noise measures to reduce noise disturbance and
25
adverse effects in relation to the cost of the measures. The measures investigated are noise
barriers, facade insulation, quieter road surfaces and development and production of quieter
vehicles. This approach is in accordance with the traffic noise optimisation TNO report, where
it is argued that 44 % of the people are exposed to noise levels above 55 dB in total. Data from
European Environmental Agency (EEA) for agglomerations report that 51 % of inhabitants in
agglomerations are exposed to noise above Lden 55 dB. Some roads have restrictions or very low
traffic flow, and as a consequence about 10 % of the population is hardly exposed to any traffic
noise (TNO, 2011). In this paper no traffic noise exposure equate to exposure less than 40 dB.
In conclusion the authors gave handling noise at source is by far the most cost effective measure
to reduce noise annoyance.
Study by Dasarathy and Thandavamoorthy (2013b) focuses on the noise
reduction by way of providing a noise enclosure which is an apt technique to reduce
noise. This is suitable for all the places, low cost technique and does not require skilled
manpower for installation, flexible in altering the design, and can be installed in critical
places where other measures are ineffective. To address the problem of noise effects on
roads, a porous natural material called thatched leaves is used as a sound barrier and
implemented on the road side. The sound barrier is installed as a rectangular shed of
size 1.5 m × 1.2 m × 2.0 m on the side of the road. The thatched hut is a simple barrier
for noise attenuation and easily erectable. The percentage reduction of noise level
ranges from 13 to 19 by the provision of thatched leaves and it shows that the noise
level can be reduced considerably. The selected area is a suitable location because of
highly congested place the provision of noise barrier as an enclosure found to be a
suitable alternative solution for noise control measure.
The primary goal of the project report prepared by Arizona Department of
Transportation (ADOT) (Anon. 2006c) was to identify innovative noise barrier designs
that had the potential to be implemented in Arizona. The study initially focused on
gathering existing literature on noise barrier materials and designs that were non-
conventional. Literature was collected on dozens of noise barrier research projects in 12
countries around the world. The results of the previous research studies were compiled
into a matrix to assist in evaluating the various barrier designs and materials. The
evaluation matrix was used to score the barrier designs based on their acoustic
performance, as well as economic, constructability, maintenance, and aesthetic
considerations. An attempt was made to identify the processes by which ADOT selects
26
and approves various barrier designs for implementation on a project. Based on the
research and evaluation conducted for this study, it was recommended that two
innovative barrier designs be implemented in Arizona – the T-top design with
absorptive material placed on the top of the horizontal portion of the barrier and a
vertical barrier with absorptive material applied to the face of the barrier. These two
barrier designs have been shown in the available literature to reduce noise levels by up
to 3 decibels, which could reduce overall barrier heights by as much as 5 feet compared
with a conventional noise barrier of concrete or masonry block construction.
The paper presented at International conference NOISE – CON 2010 at Portugal
by António et al (2010) gave a choice for an economically ideal solution of
environmental noise barrier. It acknowledged both the cost of its main components and
the benefits it can provide, through time. An algorithm based on benefit/cost ratio
(BCR) analysis was created to achieve a systematic analysis tool. It calculated the BCR
for any potential noise barrier. The cost of a barrier could be described with known or
quantifiable parameters such as barrier height, thickness, materials, initial investment
costs, maintenance costs, replacement costs due to accidents, etc. The benefits
associated with a solution were defined by computable parameters such as sound
absorption, sound reduction, insertion loss, and even intangible parameters such as its
visual impact and environmental impact. Each benefit was weighed regarding its
importance. Using the necessary parameters it was possible to calculate the BCR of a
barrier for any number of years of life expectancy.
According to Sagarzazu (2011) gave a bibliographical revision concerning
acoustic absorbing materials, also known as poroelastics. These absorbing materials are
a passive medium used extensively in the industry to reduce noise. This review presents
the fundamental parameters that define each of the parts comprising these materials, as
well as current experimental methods used to measure said parameters. Further along,
the principle- models of characterization was analysed in order to study the behavior of
poroelastic materials. Given the lack of accuracy of the standing wave method three
absorbing materials were characterized using said principle models. A comparison
between measurements with the standing wave method and the predicted surface
impedance with the models were shown.
In the study done by Ozturk et al (2012) the barriers used for reducing traffic
noise were being examined by means of performance and construction cost. First a
27
noise prediction was made in the sample highway under certain traffic conditions in
order to determine the noise barrier requirement and the results were confirmed by
measurement. According to the noise prediction equations used in Turkey, Germany
and Canada, the effects of heavy vehicle ratio, average traffic flow speed and hourly
total vehicle quantity change on noise level and barrier requirement were examined, so
assessment could be made for highways having different traffic specifications than the
sample highway. In the continuation of the study, the working principle of noise
barriers and effects of barrier position and height on reducing noise were researched in
order to determine the construction costs of barriers in Turkey and Canada at different
heights and made from different materials. All calculated or observed results showed
that noise barrier construction was necessary and 3 m tall barrier could not perform the
desired noise reduction at all distances while 5 and 7 m tall barriers could. It was
concluded that the actual noise reduction performance was not defined by the surface
mass of used material but by the height of the barrier and the related distances.
Mutairi et al (2009) gave a model by a detailed process which involves the
following steps. Problem identification: The problem of urban traffic noise pollution is
universal and in the past few decades it has grown to the point that it has become a
major concern for both the public and the policy-makers. Approach: In a
comprehensive 18 month research project, traffic-generated noise was monitored at 47
roadway locations in fourteen districts in metropolitan Kuwait in 2004-2005.
Simultaneously with noise, traffic flow variables of volume-by mix and traffic speed
were also measured. Measurements of noise and traffic flow variables were performed
for a period of 20 min at each location, repeated 3-5 times, during peak and off-peak
hours to account for time-fluctuation of these variables. At each district, a sample of
freeway, arterial, collector and local residential streets were included in the noise and
traffic flow monitoring plan. In addition to the analysis of noise, flow and their
interrelationships, two models-regressions and the traffic noise model, were employed
to predict noise pollutions from traffic. Results: Findings indicated that traffic noise is
at or above, the standard outdoor limits in most locations and especially at arterial
roadways and freeways. Recommendations concerning measured to improve the
problem of urban traffic noise pollution in Kuwait are also made. Conclusion: Findings
of this research project had shown that level of traffic generated noise pollution in
Kuwait urban area is high enough to adversely affect the welfare activities and
28
productivities of its residents. With the rapidly growing rate of infrastructural
development and unplanned urban land-use change, it is almost certain, that problem of
urban traffic noise pollution will soon assume a critical dimension and will be a cause
of increasing concern for both public and responsible policy-makers. The quality of
urban life will undoubtedly be adversely affected.
Karantonis et al (2008) provided an update of information presented in a paper
presented at the AAS Acoustics 2008 conference in Geelong, Victoria. In particular this
paper presents results of traffic noise modeling using CadnaA and SoundPLAN and
compares both to noise measurements for three large recent road projects in NSW.
CadnaA is a well known and internationally accepted noise modeling package, and its
acceptance and use in Australia amongst acoustic professionals is growing fast. To
assist the Australian acoustical profession, the appropriateness and accuracy of CadnaA
under Australian conditions is currently being verified, and this paper presents actual
project results for this purpose. Unlike CadnaA, the SoundPLAN noise prediction
model is extensively used in Australia, particularly for road traffic noise predictions,
and has been recognized and accepted nationally by various regulatory authorities
including the major road authorities and environmental agencies. The aim of this paper
was to provide additional comparative data for predicted traffic noise levels using the
Calculation of Road Traffic Noise (CoRTN) algorithms as implemented by
SoundPLAN and the CadnaA noise models for three large recent road projects in NSW.
These three projects offered features and characteristics that differed significantly from
the projects reported in the 2008 paper. Results from this study re-confirmed that the
CadnaA noise modeling package was accurate and effective for modeling road traffic
noise in Australia.
Fan Dan Qun et al (1986) gave the medium term prediction of noise and
evaluation of noise pollution in “microscopic” way using computer and was a new
research work in China. In this paper, some investigations including the methods of
prediction and evaluating urban traffic pollution have been reported. Models for
vehicles flow and propagation of noise in urban areas have been setup. Finally a set of
computer programs for these purposes was given. Models and computer programs had
been tested in more than 70 cities of China. It was proved that they could be used in
medium and long term prediction of urban traffic noise pollution in China and they
were of great values in evaluating the extent of urban traffic noise pollution.
29
Models were developed by Golmohammadi et al (2007, 2009). Background:
The recognition of road traffic noise as one of the main sources of environmental
pollution had led to develop models that enabled to predict noise level from
fundamental variables. Traffic noise prediction models were required as aids for
designing roads and highways. In addition, sometimes were used in the assessment of
existing or envisaged changes in traffic noise conditions. In this paper a statistical
modeling approach had been used for predicting road traffic noise in Iranian road
conditions. Methods: The study was performed during 2005-2006 in Hamadan city, in
the west of Iran. The data set consisted of 282 noise measurements. The entire data set
was utilized to develop a new model for Iranian condition using regression analysis.
Result: The developed model had twelve explanatory variables in order to achieve a
proper fit for measured values of Leq (R2 = 0.913). Conclusion: The proposed road
traffic noise model could be effectively used as a decision support tools for prediction
of traffic noise index of Leq(30 min) in Iran's cities.
Modeling free flowing vehicular traffic noise was developed by Sooriyaarachchi
and Sonnadara (2008). Traffic noise of 650 vehicles classified into 8 vehicle classes
was measured in several locations within the Western Province of Sri Lanka in order to
extract the necessary coefficients to develop a road traffic noise prediction model. The
model was developed to predict the traffic noise generated from free-flowing vehicles
in roadways. Traffic flow data used for constructing this model was limited to vehicle
noise, vehicle class, vehicle speed and the distance from the traffic flow line. It is
shown that the predictions could be made within ±11 dBA accuracy with respect to the
actual experimental observations. Microsoft .Net® platform was used for the
development of the traffic simulator based on the model parameters.
Evaluation and mitigation of road traffic noise in Amman, Jordan done by
Jadaan et al (2012, 2013) provided an evaluation of road traffic noise pollution in
Amman, the capital of Jordan through measuring and predicting the statistical noise
index L10 (18 hr) at selected sites using the British calculation of road traffic noise
(CRTN) method after validation. The measured and future noise levels were found high
and exceeded the maximum allowable limit of 63 dBA at all survey sites calling for the
need to apply mitigation measures. The effectiveness of noise barriers in reducing noise
levels was investigated and 3-5 m noise barriers were found appropriate.
30
The investigation of noise attenuation by plants and the corresponding noise –
reducing spectrum by Fan et al (2010) stated as noise pollution was becoming more and
more serious, many researchers were studying the noise attenuation effect provided by
plants. This article examines six kinds of evergreens as research subjects so as to
compare the different arrangements and densities of plants and their effect on noise
attenuation. The authors studied the relationship between each of the plant’s
characteristics (the characteristics include leaf area, leaf fresh weight, leaf tactility, and
leaf shape) and their average relative noise attenuation. The authors then generated the
noise reducing spectrum of the six plants. The results showed that there was a notable
difference in noise reducing effects for low frequency and high frequency when plants
were arranged differently. Also every plant demonstrated a specific noise reducing
spectrum. By quantifying noise attenuation species to achieve the mutual benefits of
plant varieties and establish an ecotype sound barrier model with effective density and
arrangement.
Proposed criteria for the assessment of low frequency noise disturbance by
Moorhouse et al (2005) was to recommend a method for assessing low frequency noise
(LFN), suitable for use by Environmental Health Officers (EHOs) in the UK. A general
introduction to LFN was given, in which it was argued that a method of assessment was
needed both from the sufferer’s point of view, because there is currently not much to
protect them against LFN, and from the Environmental Health Officer’s point of view,
where guidance is needed in determining whether a nuisance exists. Criteria already in
use in Germany, Sweden, Denmark, the Netherlands and Poland were reviewed and
compared. Experience from these countries in applying the criteria was also reviewed,
and was found to be generally positive. A complementary set of field and laboratory
studies was conducted in order to establish the best form for an assessment method. In
the field studies, eleven cases of reported LFN were investigated, as well as five control
cases where no complaints about LFN had been received. Analysis of recordings made
over three to five days at each location distinguished three groupings: positively
identified LFN, unidentified, and marginal. Three cases were positively identified,
meaning that the various national criteria were exceeded and there was correlation
between the resident’s logged comments and the LFN level. Five cases were
unidentified: the criteria were generally not exceeded, (except perhaps by traffic noise),
and there was a lack of correlation between comments and noise levels. Three cases
31
were marginal in that the LFN was marginal with respect to the criteria and did not
correlate with comments. It was concluded that the criteria were successful at
distinguishing cases where an engineering solution could be applied from those where
no such solution could be found.
Noise prediction simulation and noise reduction technology at low-frequencies
by Kaneuchi and Nishimura (2011) developed a noise prediction simulation and a
noise-reduction technology which could be used for low-frequency noise whose
propagation was difficult to predict and to reduce. For developing a method of noise
prediction simulation, the validity of the geometrical acoustic method and the wave
acoustic method was evaluated and confirmed. The interference mainly occurs near a
wall and in enclosed space at low frequencies. The wave acoustic method could be used
in the situation where the interference was dominant. It was confirmed that the
environmental noise impact of gas equipment could be predicted by using the
geometrical acoustic method and the wave acoustic method as the situation demands.
Additionally, for reducing the low-frequency noise in three-dimensional space, an ANC
system whose second sound source was set next to the noise source was developed.
Although its noise-reduction effect was restricted to the frequencies in the range of 20
Hz to 100 Hz, the noise at the peak frequency depending on the rotating speed of the
machine was reduced by about 15 dB. As a result of developing pre- and post-
operational measures, it became possible to suppress successfully the undesirable effect
of the noises from the system exerts on its surroundings.
The analysis with MATLAB given by Wendy and Angel (2005) was used to
define exploratory data analysis. It was an area of statistics and data analysis, where the
idea was to first explore the data set, often using methods from descriptive statistics,
scientific visualization, data tours, dimensionality reduction, and others. This
exploration is done without any pre-conceived notions or hypotheses. Indeed, the idea
was to use the results of the exploration to guide and to develop the subsequent
hypothesis tests, models, etc. It was closely related to the field of data mining, and
many of the EDA tools discussed in this book are part of the toolkit for knowledge
discovery and data mining.
According to Christoph (2001) on spectrum analysis is intended to familiarize
the uninitiated reader with the field of spectrum analysis. To understand complex
measuring instruments it is useful to know the theoretical background of spectrum
32
analysis. Even for the experienced user of spectrum analyzers it may be helpful to recall
some background information in order to avoid measurement errors that are likely to be
made in practice. In addition to dealing with the fundamentals, this book provides an
insight into typical applications such as phase noise and channel power measurements.
In low frequency noise technical research support for DEFRA Noise Programme
(Report 2001) possible causes and possible effects of low frequency noise were
described, and a procedure for investigating complaints concerning low frequency noise
is set out. Some general advice was given regarding the measurement of low frequency
noise, but a detailed measurement procedure was not given. A further detailed report on
the subject of the measurement of low frequency noise may be produced in due course.
In the field of low frequency noise and its perception, there are still a number of factors
that make it difficult to derive specific, quantitative guidelines by which to judge the
acceptability or otherwise of a given level of noise at low frequency. This document,
therefore, tries to offer suggestions which may be helpful in explaining some of the
factors most commonly affecting the outcome of investigations.
Traffic noise spectrum analysis: Dynamic modeling vs. Experimental
observations developed by Leclercq et al (2010) compares two different representations
for the assessment of urban noise frequency spectrum (i) a static one based on mean
vehicle speeds and flow rates and (ii) a dynamic one which considers vehicle
interactions along the network. The two representations were compared on their
suitability to match real on field noise levels, recorded on a three lane quite busy street.
Representations (i) falls in reproducing spectra evolves that correspond to this site. In
particular, it underestimates low frequencies, what can conceal the real impact of traffic
flow on urban sound quality. Representation (ii) greatly improves estimation. It
quarantines accurate environmental noise assessment, since it reproduces all traffic
situations that are encountered in the site. Moreover, its base structure allows for the
evaluation of spectra variations, with a good accuracy.
Tandel and Macwan (2012) carried out assessment and modeling of urban
traffic noise at major arterial roads of Surat. In India, transportation demands in urban
areas continue to increase rapidly as a result of both of population growth and changes
in travel patterns. The recognition of road traffic noise as one of the main sources of
environmental pollution has led to develop models that enable to predict noise level
from fundamental variables. Therefore, this study was carried out to generate a noise
33
prediction model and to analyze various parameters affecting road traffic noise. The
model, when validated gives quite satisfactory results. The study reveals that present
noise level at all three major arterial roads exceed the limit prescribed by CPCB. Based
on the finding, it can be said that the persons nearby these roads are exposed to
significantly high noise levels and hence necessary mitigation measures should be
adopted.
2.4 Summary of collective literatures
Findings from a large body of studies show that traffic noise causes non-
auditors' stress effects such as changes in the physiological systems, e.g., elevated blood
pressure, various cognitive deficits, poor sustained attention, memory/concentration
problems, sleep disturbances, psychosocial stress disturbance. A series of reports on
traffic noise prediction of national scope have been published, but they lack detailed
information and its application on Indian condition.
Hence, this research is to analyze the outcome of noise barriers provided and the
objectives are arrived based on the above listed literatures.
34
CHAPTER 3
3 METHODOLOGY
3.1 General
The methodology adopted includes a study of existing condition, real- time work
made to explore the general system followed in the noise pollution mitigation
measure. The methodology is presented as a flow chart in Figure 3.1
Figure 3.1 Flow Chart of Methodology
Literature Review
Objectives and Scope of research
Data Collection / Field Study and
Exposure Timings
Analysis for each Source
Results and Discussion
Conclusion
Problem Identification – Causes,
Sources, Effects, Mitigation
35
3.2 Data Collection
Data collection is the process of measuring and gathering information on
variables of interest, in an established systematic fashion that enables one to answer
stated research questions, test hypotheses, and evaluate outcomes. The data collection
component of research is common to all fields of study including physical and social
sciences, humanities, business, etc. While methods vary by discipline, the emphasis on
ensuring accurate and honest collection remains the same. The goal for all data
collection is to capture quality evidence that then translates to rich data analysis and
allows the building of a convincing and credible answer to questions that have been
posed.
Since the formal problem identified is about noise pollution a formal data
collection process is necessary as it ensures that data gathered are both defined and
accurate and that subsequent decisions based on arguments embodied in the findings are
valid. The process provides both a baseline from which to measure and in certain cases
a target on what to improve.
3.3 Field Area and Exposure Timings
The important aspect with respect to noise pollution is collecting information
about noise levels, source from where noise is created and its time of exposure. The
following are the different sources of noise to record observations.
3.3.1 Traffic noise – Noise levels were recorded at OMR (Old Mahabalipuram Road)
near Toll Plaza and SRP tools intersection, Perungalathur and Kolapakkam Road in
Chennai, Tamil Nadu, India.
• The noise levels were recorded from morning 10.00 AM to 18.00 PM at an
interval of 10 sec from Monday through Saturday at both locations.
• Total volume of vehicles for the entire period was recorded.
• Number of vehicles/Hr according to the type of vehicle such as bus, car,
two- wheeler, auto, LGV, and HGV were taken at an interval of two hours in
morning and afternoon during peak and non-peak hour.
36
• Speed of the vehicle was recorded by the way of moving car method at SRP
tools.
• Noise measurements were taken at distances of 0.90 m and 1.10 m from nearest
road border
• The height of noise measurement was 1.30 m above the road surface
3.3.2 Pedestrian noise – Pedestrian movement existed in a subway, noise level was
recorded where pedestrians were receiving the noise intensity. The noise level was
recorded near Tambaram, a suburb of Chennai pedestrian subway both inside and
outside the subway as shown in Table 3.1.
Table 3.1 Details of noise pollution from pedestrian sources and noise generation
hours
Place of noise pollution
measurement carried out
No. of hours of
survey conducted
Pedestrian location 8 hours for five days
Inside subway 8 hours for two days
3.3.3 Construction noise
Construction noise is predominant, especially cities like Chennai where construction
activity is in full swing. Construction machinery or equipments which create more
noise level during operation are selected and shown in Table 3.2.
Table 3.2 Details of noise pollution sources and noise generation hrs
Place of noise pollution measurement
carried out
No. of hours survey
conducted
Bored pile (during drilling, driving the
casing and concreting)
6 hours at two points
Vibrator (during concreting ) 45 min. at three locations
Mixer machine (when concreting work in
progress )
4 hours at two locations
Jack hammer demolishing work 6 hours at two points
Marble cutting machine for laying flooring 6 hours at two points
37
3.3.4 Noise generated by vehicle of different year of manufacturing
Car was chosen as a vehicle because it predominantly exists in more traffic volume and is
shown in Table 3.3.
Table 3.3 Noise duration of different years of manufacturing of car
Place of noise pollution
measurement carried out
No. of hours of
survey conducted
Cars of different years of
manufacturing (2002-2012)
10 mins.
3.3.5 Noise at Railway station and level crossing locations
Comparatively railway stations are less prone for noise pollution but the level
crossing are prone for severe noise level increment. Perungalathur railway station, a
suburb of Chennai and the level crossing nearby was selected because from there south
bound district buses are operated and diverted. The movement of people is very severe
in the selected area of study. Noise pollution levels studied is shown in Table 3.4.
Table 3.4 Details of noise pollution from railway station and crossing
Place of noise pollution
measurement carried out
No. of hours of
survey conducted
Railway station
8 hours for two days Level crossing
Outside railway station
3.3.6 Flour mill noise
Rice flouring, mirchi (chilli) flouring, seekakai (soap nut) flouring – these type of
flour mills are predominant in South East Asian countries like India. These types of
flour mills which are located very near to the vicinity of residential colonies generate
more noise during operation of machines. Three flouring operations for the study have
been selected as shown in Table 3.5.
38
Table 3.5 Details of noise pollution from flour mills and exposure time in hours
Place No of exposure time
Rice flour 2 min 5 sec Mirchi (chilli) flour 3 min 25 sec Seekakai (soapnut) flour 3 min 10 sec
3.3.7 Traffic noise with barriers
The noise barriers provided for reducing noise pollution is expensive. With costs
frequently reaching hundreds of Euros per square meter of barrier it is highly important
to choose the cost effective best solution. Four types of barriers were selected as shown
in Table 3.6.
Table 3.6 Details of traffic noise recorded using barriers
Sl.
No.
Type of
barrier Location Duration Size of barrier Nature of exposure
1
Thatched Shed
barrier
Toll Plaza
3 hours
Length 1.50 m Width 1.20 m Height 2.0 m
Open place 1 hour Shed with one layer of
thatched leaves 1 hour Shed with two layer of
thatched leaves
2
SRP tools
3 hours Open place 1 hour Shed with one layer of
thatched leaves 1 hour Shed with two layer of
thatched leaves
3
Concrete barrier
Toll Plaza
1 hour
Length 0.60 m Width 0.60 m Height 0.60m
Open place Cubicle with M30 mix concrete Cubicle with M30 mix concrete with CSP
4
SRP tools
Open place Cubicle with M30 mix concrete Cubicle with M30 mix concrete with CSP
5 Fly Ash Brick barrier
Toll Plaza
1 hour
Length 1.00 m Width 1.00 m Height 0.60 m
Open place Cubicle with fly ash bricks
6
SRP tools
Open place Cubicle with fly ash bricks
39
3.4 Equipment
An important part of noise assessment is the actual measurement of the noise
levels. The ‘A’ weighted network was used as it corresponds very closely to a person’s
hearing sensitivity. The noise level at all locations were measured with the help of HTC
make Sound Level Meter (3241 – c type II data logger) on a digital display type shown in
Figure 3.2
Figure 3.2 Noise level meter and the digital display of observation
3.5 Parameters Calculated From Primary Survey
The following noise parameters L10, L50, L90, Leq, Lnp, Lmin, Lmax, Lave, NI and
NC were calculated (Dinesh Kumar et al 2012).
L10, L50, L90 = noise level exceeded for 10%, 50%, 90% of the time in noise recording
Leq = L50 + (L10 - L90 )2/60
Lnp, = Leq + (L10 - L90 )
NI = L90 + (L10 - L90 ) – 30
NC = (L10 - L90)
Lmin, Lmax, Lave from data logger of sound level meter.
40
CHAPTER 4
4 Observations and Calculation of Parameters
4.1 Noise parameters from traffic survey at Toll Plaza and SRP Tools
Using the noise level meter traffic noise was recorded at the sensitive locations
selected as study area. The noise level is recorded using the noise level meter. The noise
level is recorded for duration of about 8 hours at both locations. The noise level was
recorded for six days from Monday to Saturday. The noise parameters such as Noise
equivalent level, noise pollution level and noise index were calculated. These are
presented in Table 4.1 and Table 4.2 for both the locations.
Table 4.1 Consolidated values of noise parameters for Toll Plaza location (dBA)
Day L10 L50 L90 Leq Lnp TNI LMAX LMIN LAVE
Monday 63.2 72.9 57.1 73.32 79.42 33.2 78.8 44.4 60.32
Tuesday 61.1 57.3 66.3 57.75 52.55 31.1 70.5 50.9 64.27
Wednesday 73.2 77.7 67.3 78.28 84.18 43.2 105.6 51.9 70.65
Thursday 73.2 77.3 62.4 79.24 90.04 43.2 105.6 51.9 74.59
Friday 71.8 59.3 55.4 63.78 80.18 41.8 83.9 44.4 61.2
Saturday 64.2 67.2 58.7 62.1 67.6 34.2 90.5 50.9 61.97
Table 4.2 Consolidated values of noise parameters for SRP tools location (dBA)
Day L10 L50 L90 Leq Lnp TNI LMAX LMIN LAVE
Monday 63.2 72.7 57.1 73.32 79.42 33.2 78.8 44.4 63.39
Tuesday 71.2 61.7 57.1 65.01 79.11 41.2 83.9 44.4 63.45
Wednesday 69.1 60.8 63.1 61.4 67.4 39.1 90.5 50.9 63.66
Thursday 63.2 72.7 57.1 73.32 79.42 33.2 79.9 44.4 63.57
Friday 71.8 69.3 71.4 69.3 69.7 41.8 83.39 44.4 64.69
Saturday 74.2 61.6 58.7 66.7 84.2 46.2 90.5 50.9 63.76
41
The observations show that noise level is in the range of about 44.4 dBA (Lmin)
to 105.6 dBA (Lmax). The noise level is 10 dBA more on Wednesday when compared
to other days at both the locations. The average noise level is in the range of 61.2 dBA
to 74.59 dBA. During 90% of the time the noise level is in the range of 55.4 dBA to
71.4 dBA. The equivalent noise level is in the range of 57.75 dBA to 79.24 dBA.
During Saturday the noise level is equivalent to a week day value which shows that the
traffic volume is existed on that day. Further recorded noise level is compared with
standards prescribed and are presented in Figure 4.1.
Figure 4.1 Comparison of noise level with the standards given by CPCB
Figure 4.1 shows Leq, Lmin, Lmax and Lave compared with the CPCB
standards. The noise level prescribed by the CPCB is 55 dBA where as the noise level
Leq is in the range of 57.75dBA to 79.24 dBA, Lmax is in the range of 70.5 dBA to
105.6 dBA, Lave 60.32 dBA to 74.59 dBA. Lmin value is in 44.4 dBA to 51.9 dBA.
This value is very close to the CPCB standards whereas this minimum value is not
reflected in L10, L50 and L90 values. This shows that the Lmin existed for very short
duration that too when the traffic is at calming.
0
20
40
60
80
100
120
Toll
Plaza
SRP
tools
Toll
Plaza
SRP
tools
Toll
Plaza
SRP
tools
Toll
Plaza
SRP
tools
Toll
Plaza
SRP
tools
Toll
Plaza
SRP
tools
MONDAY TUESDAY WEDNESDAY THURSDAY FRIDAY SATURDAY
De
cib
el
Lev
el
in d
BA
Day / Location
LMIN
LAVE
LMAX
Leq
LCPCB
42
4.2 Noise parameters from vehicles at Tambaram Subway
The pedestrians are most affected persons due to generation of noise pollution. This as a
measure, a congested location is selected to identify the level of existing noise
generated due to vehicular movement. The place selected is Tambaram, Chennai a
suburban hub for the south bound traffic from Chennai. Subway location and
surrounding place are shown in Figure 4.2.
Figure 4.2 Location of Tambaram Subway
The noise level was recorded outside the subway for 5 days and the noise level
was recorded inside the subway for two days. The noise level recorded using the noise
level meter. The noise level recorded for duration of about 8 hours at both locations.
43
The noise parameters such as Noise equivalent level, noise pollution level and noise
index were calculated. These are presented in Figure 4.3 for the both the locations.
Figure 4.3 Noise parameters at Tambaram subway
Observations show that noise level is in the range of about 49.3 dBA (Lmin) to
97.5 dBA (Lmax). The noise level L10 is above 77 dBA on all days including inside and
outside the subway. L50 noise level is between 60.15 dBA to 69.82 dBA and this shows
that during 50% of the time the noise pollution existed. L90 the predominant time of
presence in noise level is 53 dBA to 65 dBA, there is significance level of noise on the
subway which in turn has impact on the pedestrians. Moreover the movement of
pedestrians is 700 persons / 15 mins which is a primary survey conducted to exactly
indentify the pedestrian movement. On an average the noise level falls between 62 dBA
to 72 dBA. This is an indication for the existence of noise level in that area. Similarly
the noise level Leq is a measure to represent the noise level from 67 dBA to 87 dBA.
Further recorded noise level Lmin, Lmax, Lave, L10, L50, L90 and Leq are compared
with standards prescribed and are presented in Figure 4.4.
0
20
40
60
80
100
120
140
Mon Wed Fri Sat Sun Thurs Tues
Out side
Subway
Inside
Subway
De
cib
el
lev
el
in d
BA
Day / Location
L10
L50
L90
Leq
Lnp
TNI
NC
LMAX
LMIN
LAVE
44
Figure 4.4 Comparison of noise level with standards
Figure 4.4 shows that the noise level Lmin is very close to the value given by CPCB
standards. The predominant time of survey shows that noise level existed at all time.
The Leq level was 24.52 dBA more than the CPCB standards. The pedestrians are
subjected to severe noise injection due to vehicular movement throughout the day. Also
there is substantial presence of hawkers near the subway where there are about 75
hawking shops in the vicinity. Approximately about 125 persons are facing the severity
of the noise during the entire day due to traffic. They also spend considerable time of
the day in selling their commodities in this environment of noise pollution.
4.3 Construction noise and noise parameters
The disturbance in terms of severity of noise caused during the construction
process and their impact vary depending on the nature of the activities being performed,
the equipment being used, and the physical nature of the surrounding environment i.e.,
urban area versus green field conditions Gilchrist et al (2003).
Controlling construction noise can pose special problems, at the same time,
there have been not many studies related to pollution control in construction sites. There
have also been some studies engaged to the quantitative measurement and effective
0
20
40
60
80
100
120
Mon Wed Fri Sat Sun Thurs Tues
Out side
Subway
Inside
Subway
de
cib
el
lev
el
in d
BA
Day / Location
L10
L50
L90
Leq
LMAX
LMIN
LAVE
LCPCB
45
control of construction pollution, using methods such as life-cycle costing; efficient
energy consumption; reduction, reuse, and recycle of construction and demolition
material/debris; degradation and abatement of construction noise and dust; and
environmental impact assessment Li et al (2000), Hassan et al (2012) and Transit noise
and vibration assessment (2000). Construction noise makers, e.g., heavy earth moving
equipment, jack hammer, marble cutting machine, mixer machine operation and
vibrator machines are taken as examples for this study.
4.3.1 Mixer Machine Operation
The operation of mixer machine shown in Figure 4.5 is manual and a person
will be used to operate. The mixer machine is used for concreting works which
completes in a day of work. Usually in residential construction and large construction
involving huge quantity of concrete, site mixer machine for concreting is preferred. The
loading of ingredients for mixing components is carried by the laborers associated with
the work. The mixer machine is usually operated for middle level construction sites and
is predominant in rural areas and suburban areas. The operation selected for the study
purpose is a multi-storeyed and residential building construction site. The operation
considered is 4 hours during casting of concreting. The noise parameters calculated are
presented in Figure 4.6.
Figure 4.5 Mixer machine in operation
46
Figure 4.6 Noise parameters for mixer machine operation
The presence of noise is significance in the Figure 4.6. It shows that the noise
level Lave is 75.84 dBA which is equivalent to CPCB standards. Leq noise levels at
both locations are 86.54dBA and 76.55 dBA, respectively. The Lmin value is in the
range of about 46.3dBA to 60.1dBA. The maximum noise level is 93.7 dBA. The L50
noise level is an ideal indicator that the noise pollution is 50% of the time it reaches the
permissible limit given by the CPCB. Both the locations are similar in generating noise
pollution and the values correspond to its presence.
4.3.2 Vibrator Operation
The vibrator is a mechanically operated machine used in construction sites for
compacting the concrete. The vibrators used are usually needle type of vibrators of 40
mm and 60 mm needle diameters. It is usually run for about 2 to 3 minutes of operation
per unit quantity of concrete pouring. The vibrator operation considered is during
concreting work for duration of about 45 min at three locations. The operation is shown
in Figure 4.7.
0
10
20
30
40
50
60
70
80
90
100
L10 L50 L90 LMIN LAVE LMAX Leq LCPCB
De
cib
al
lev
el
in d
BA
Noise parameters
Mixer 2
Mixer 1
47
Figure 4.7 Vibrator machine in operation
The noise is generated from the motor attached with the needle which in turn
rotates for compaction. The operator is bound to start, run for few minutes and stop
frequently. This operation is done by laborers present in the work place and in turn they
receive the amount of noise generated from it. The noise level is recorded and the noise
parameters are presented in Figure 4.8.
Figure 4.8 Noise parameters for vibrator machine operation
0
20
40
60
80
100
120
L10 L50 L90 LMIN LAVE LMAX Leq LCPCB
de
cib
el
lev
el
in d
BA
Noise parameters
Vibrator3
Vibrator2
Vibrator 1
48
The noise level Leq is 71.12 dBA and 90.31 dBA, respectively. The noise level is
reaching the permissible limit mentioned by the CPCB which is 75 dBA. Here the noise
generation existed in the few hours of operating simple machinery like vibrator needle
in construction. The Lmax noise level is 81.1 dBA and 98.3 dBA shown in Figure 4.8
and reaches the peak point equivalent to CPCB standards.
4.3.3 Piling Operation
Multi-storeyed construction nowadays opts for foundation using piles. The
operation of piling is done through manual or machinery. Manual operation does not
require sophisticated equipments, whereas the mechanical operation requires full
fledged machinery arrangements for piling operation that too when the depth of
foundation exceeds more than 10 m it is always preferable to go for driven piling
operation. During driven piling operation noise generation is enormous and this
operation considered as a noise source for evaluation. The piling operation considered
is shown in Figure 4.9(a) and Figure 4.9(b).
Figure 4.9(a) Driven piling operation
49
Figure 4.9(b) Concreting of driven pile
The study area considered is a high rise building near Chennai. The piling
operation is a multiple stage process wherein it involves staging, erection of jig,
centering, driving operation, insertion of casing with bentonite solution, reinforcement
erection, pouring of concrete, and finally disassembly of entire jig arrangements. The
entire operation will have duration of about 6 to 7 hours. During the entire duration of
operation the machine will be in running condition and the noise generation is
enormous. Even though the operation and process will have minimum labour
involvement but the surrounding area for a radius of 20 m will have noise generation.
The noise level meter is placed during the entire operation and the noise is recorded at
two piling points. The noise level observed, recorded and noise parameters are
calculated and are presented in Figure 4.10.
Figure 4.10 Noise parameters for piling operation
0
50
100
150
L10 L50 L90 LMIN LAVE LMAX Leq
De
cib
al
lev
el
in d
BA
Noise parameters
Pile 2
Pile 1
50
The noise level recorded shows that the Lmin noise level is 72 dBA to 78 dBA.
The noise level is maximum of 119.9 dBA, where as the Lave is 100.46 dBA. This
shows that the noise level is predominant. During the piling operation, 90% of its
timing the noise level is 82 dBA. The generation of noise is from the attached machine
and the hydraulic operation involved in the process. The noise level generated is
uniform, and during the entire operation of one piling the noise is predominantly
exposed. The noise generation for the entire duration of piling is shown in Figure 4.11.
Figure 4.11 Variation of pile operation in a day
The Figure 4.11 represents the noise level with an amplitude in a range of 92
dBA to 110 dBA. Thus, the piling is a source of severe noise generation and it creates
pollution. The piling operation is carried out in open stream and the dissipation of noise
is minimal that shows that the severity of noise.
4.3.4 Marble cutting operation
The process of marble cutting occurs during laying of marbles in the flooring.
This operation is tedious because the marble plate will come in an irregular shape and
the person laying the plate will fine tune to accommodate by simply using a tool for
cutting. This operation generates louder noise. The laborers working near the marble
cutting operation and the process is shown in Figure 4.12.
0
20
40
60
80
100
120
140
00
:05
:10
00
:18
:50
00
:32
:30
00
:46
:10
00
:59
:50
01
:13
:30
01
:27
:10
01
:40
:50
01
:54
:30
02
:08
:10
02
:21
:50
02
:35
:30
02
:49
:10
03
:02
:50
03
:16
:30
03
:30
:10
03
:43
:50
03
:57
:30
04
:11
:10
04
:24
:50
04
:38
:30
04
:52
:10
05
:05
:50
05
:19
:30
05
:33
:10
05
:46
:50
de
cib
el
lev
el
Time Duration
51
Figure 4.12 Marble cutting process
The marble cutting operation is a process involving sizing of marble to a
definite shape. This involves the chiseling of edges of the marble using a tool which is
mechanized. The tool will have a sharp toothed axe and in turn cut the required shapes
of marble plates. The marble plate is usually laid for the flooring. The person who lays
the floor will always use the cutting tool till the completion of the entire work. The
noise level generated will be heard for the entire complex as well as neighborhoods.
Noise level meter is placed in the near range of a laborer and noise levels are recorded.
The noise parameters are shown in Figure 4.13.
52
Figure 4.13 Noise parameters for marble cutting operation
The marble cutting generates significant noise is shown in Figure 4.13. The Lmin
value itself is 97 dBA. The maximum level Lmax is 109 dBA. The Leq value is 98.97
dBA which is equal to L90 value which is in the range of 98 dBA to 104.8 dBA. The
Lave value is in the order of 101 dBA to 106 dBA. Hence the values resembles that the
noise pollution is existed.
4.3.5 Jack hammer operation
The operation of jack hammer is associated with demolition and rehabilitation
works. Usually the jack hammer is used to cut the solid concrete which is highly
difficult to cut by manual operations. Concrete which attains its full strength requires an
equipment to cut where ever it is necessary. The jack hammer equipment is nothing but
a power hammer / driller which in turn penetrates into the solid concrete using rotary
operation of rock drillers having a needle size 40mm shown in Figure 4.14. The noise
generation is enormous; the operator who operates the jack hammer uses ear plugs to
save from noise pollution. But the intensity of noise penetration is spread all over the
structure there by subjected to severe noise pollution.
90
92
94
96
98
100
102
104
106
108
110
L10 L50 L90 LMIN LAVE LMAX Leq
De
cib
al
lev
el
in d
BA
Noise parametersMarble2
Marble 1
53
Figure 4.14 Jack hammer operation
The present study considered this aspect and the noise level is recorded during the
jack hammer operation for a pile cap work and the duration of recording is for a period
of 6 hours. The noise meter placed at a distance of 4 m radius from the hammer and the
observations were recorded. The noise parameters are shown in Figure 4.15.
54
Figure 4.15 Noise parameters for jack hammer operation
It is quite interesting to show the observations of jack hammer operation. The
Lmin itself is about 83 dBA and 86 dBA respectively at both locations. Likewise the
maximum level is around 127.9 dBA. During the 90% of the operation of jack hammer
the value of noise level is 97.6 dBA . The Leq is 98.97 dBA which is equal to the L90
value. Moreover the average noise level is 108.47 dBA to 117 dBA at both points
selected for the study. Here the noise is present at all times, operator uses ear plugs to
reduce the noise intensity the dissipation of noise is very limited the surrounding place
is affected by severe noise.
4.4 Vehicle manufacturing year of car and corresponding noise parameters
The traffic noise is usually related to performance of vehicles. The automobiles
which flow on the traffic stream are bound to have noise generation due to efficiency of
the vehicle. The performance is indicated by the certain parameters like deceleration,
acceleration, age of vehicles, and use of alternate fuels etc .Out of this, age of vehicle
has been considered as a parameter and the corresponding noise level is noted by
considering different manufacturing year of the vehicle. The vehicle considered is car
0
20
40
60
80
100
120
140
L10 L50 L90 LMIN LAVE LMAX Leq
De
cib
al
lev
el
in d
BA
Noise parametersJack Hammer 2
Jack Hammer 1
55
which is relevant to the traffic equivalency given by Indian Road Congress (IRC)
guidelines.
A car is allowed to run on ideal condition without deceleration and acceleration. The
noise level is noted near the driver area outside the car and duration of the running is
about 10min. The age of vehicle considered here is a manufacturing year starting from
2002 to 2012. The noise level is recorded and the readings are noted. Noise parameters
are presented in Figure 4.16.
Figure 4.16 Noise parameters for vehicle manufacturing years
Noise parameters calculated from the recorded noise level are presented in Figure
4.16. The observations show that the graph is having a descending slope with respect to
age of the vehicle. The age of vehicle starting from the year 2002 show that the decibel
levels are in the range of 72.8 dBA which is Lmin, 79.9 dBA Lmax, 75.76 dBA Leq,
and the L90 is 76.8 dBA. The 2012 vehicle show Lmin as 56.8 dBA, Lmax as 62.8 dBA,
Leq as 57.83 dBA, L90 as 60.8 dBA. The trend is sloping with respect to age of the
vehicle which contributes for the noise generation. The noise is reducing considerably
to a value of like Leq as 18 dBA from 2002 to 2012. The entire process of recording is
without the ‘on road test’ and the operation is on the human perception to receive the
noise.
0
10
20
30
40
50
60
70
80
90
2002 2004 2006 2008 2010 2012
De
cib
el
lev
el
in d
BA
Year of Manufacturing
L10
L50
L90
LMIN
LAVE
LMAX
Leq
56
4.5 Noise from railway station, level crossing and on road side and the
corresponding noise parameters
Noise from the trains, at railway stations, near level crossing and adjoining roads
is a source of information. Here, a place located at Perungalathur, Tamilnadu, India was
considered. This location is paramount for all south bound movement of traffic from
Chennai. It is a useful link from all sources of national highways across Chennai.
Presently all the south bound intercity buses uses from Chennai, the headquarters of
Tamil Nadu State, uses this place for alighting and boarding passengers who are
transiting from Chennai city to go for down south. Presently the traffic congestion is
severe and another feature is the railway station which is located adjoining to the
national highway. The railway station is bounded by two level crossings one on North
and the other on South. The location of the present study area is shown in Figure 4.17.
The noise level is recorded at three different locations. The locations are railway
station, level crossing and in between track and the national highway. The noise at the
railway station will be exclusively from the trains which are coming from the
neighboring stations. The next location is at the level crossing point and the level
crossing is shown in Figure 4.18.
Figure 4.17 Perungalathur railway station and adjoining places
57
Figure 4.18 Level crossing near Perungalathur railway station
The level crossing is severely trafficked due to movement of vehicles. The
national highway which is adjoining the railway station and track is chosen as the
location for conducting noise survey. Each location is surveyed for two days and each
day for about 8 hours duration. The noise level meter is placed near the railway station
from a distance of about 1 m from the end of the platform. In the level crossing the
noise level meter is placed at a distance of 3 m from the track. On the highway location
it is on the road since there is no designated platform located. The noise level recorded
was calculated for noise parameters and Figure 4.19 shows the observations.
Figure 4.19 Noise parameters for the railway station location
0
20
40
60
80
100
120
Day 1 Day 2 Day 1 Day 2 Day 1 Day 2
Railway
station
Level
crossing
Road side
de
cib
el l
ev
el
in d
BA
Location / Day
L10 L50 L90 LMIN LAVE LMAX Leq
58
The observations made at railway stations and the adjoining places are shown in
Figure 4.19. It shows that railway stations are less prone for noise pollution. The
observation from railway station shows values of Lmin, L90 and L50 are 43.7 dBA,
53.16 dBA and 50.5 dBA, respectively. The noise level of Lmax of 87.4 dBA and L10
of 85.4 dBA are more or less similar and show that the noise generation is marginal.
The cause for the noise exceeding the required level such as 55 dBA mentioned by
CPCB standards is because of air horn ignited from the train. This air horn is for a
period of 10 seconds only and at times only when required. The Leq level is 62.93 dBA
which is the equivalent level with respect to the standards and which is marginally
higher than the standards.
Considering the observations at the level crossing and the road side both are of
similar nature. The representations are shown in Figure 4.19. Figure 4.19 shows that
Lmax level is 107.1 dBA at the Level crossing and 109.1 dBA on the road side. Both
are subjected to vehicular traffic and congested movement. All corresponding values for
both cases, viz., L10 105.1dBA and 104.7 dBA, L50 85.9 dBA and 84.9 dBA,L90 84.81
dBA and 86.4 dBA,Lmin 80.8 dBA and 82.4 dBA, Lave 89.3 dBA and 90.3 dBA,
respectively are calculated and are having similar trend on the vehicular movement to
display noise levels at both the locations. The Perungalathur and adjoining location of
residential zone should have a sound level of 55 dBA. However the noise level
generated is very much on the higher side. The pedestrian movement is 992
persons/hour and this indicates movement of persons and utilization level of the
selected place.
4.6 Flour mills noise during grinding operation
Country like India where people use instant flouring of grains rather packed and
previously powdered grains. The instant flouring operation is carried out in flour mills.
The flour mills are located in the residential areas and the flour mills are having three to
five machines which grind the products for the required smoothness. A flour mill has
been considered here as a source of noise generator and the flour mill is shown in
Figure 4.20.
59
Figure 4.20 Flour mill selected for observation
The flour mills normally consist of grinding machines for rice, mirchi (chilli),
seekakai and spare for maintenance. The flouring operation is carried out whenever
required. The noise generation is enormous and the surrounding place is disturbed with
annoyance in such a way that people are bound to face a lot of health effects. Here, we
consider three flouring operations like rice, mirchi and seekakai as noise generator. The
noise level is recorded for a duration of 2 to 4 minutes during the operation of the
machines. The duration is considered for a set of grinding operation. This operation of
grinding existed for more than 25 to 30 sets in a day of work. The noise meter is placed
at a distance and the noise levels were recorded. The noise parameters are calculated
and shown in Figure 4.21.
Figure 4.21 Noise parameters for flour mills operation
80
85
90
95
100
105
110
RICE FLOUR MIRCHI FLOUR SEEYAKAI FLOUR
De
cib
el
lev
el
in d
BA
Flouring operationL10 L50 L90 Lmin Lavg LMax Leq
60
The flour mill operation is specific in country like India. Here, people mostly use
instant powder mix rather than already powdered mix. The noise generation is more
acute than the other sources. The noise parameters represented in Figure 4.21 show that
the noise pollution existed. The Lmin valve is 89.8 dBA, 90 dBA and 93.8 dBA for the
three flouring operations, respectively. This itself is an indicator for the noise pollution
about the flouring operation. The Lmax is 102.5 dBA, 103.5 dBA and 106.5 dBA,
respectively. All the values of noise parameters are in the range of 92.2 dBA to 106.8
dBA for all the flouring operations. The grinding operation of mirchi is around 3.2 dBA
higher than the other operations. This is because mirchi grinding is operated under
stressful condition, mirchi is in the form of flakes and the fine grain requires extra
power of rotation of machinery. The flour mills are located at the residential localities
and sometimes even in crowded locations. People transiting, utilizing and staying near
the mills are bound to face a lot of hard ships in the form of noise which is significant
from the above test results.
4.7 Findings from observation
It is generally found that people feel much pain in their ears and migraine during
duty hours as well as after duty hours. This study suggests that noise induced hearing
loss is a great challenge in environmental pollution. This noise exposure and
occupational noise exposure both interfere with their activities in their personal life as
well as their healthy living. The findings of this study also indicated the high density
residential area like OMR affected by noise pollution that took a developed residential
area in the vicinity. Indeed some control measures and proper planning has to be
implemented to overcome the adverse effects from noise pollution and for the well
being of the residents.
61
CHAPTER 5
RESULTS AND DISCUSSION
5.1 Analysis of Noise Data
All the observations from the primary survey are presented in each phases and
the results are arrived. Each noise parameters has its own implications but mostly the
noise level like L10, L50, L90, Leq, Lmin, Lmax, Lave were considered for result analysis. The
observations are compared with the standards prescribed by the competent authorities like
MoEF and CPCB (2000).
5.1.1 Results Based on Traffic Noise
The noise parameters calculated from the traffic noise are compared with MoEF
standards and presented in Figure 5.1 for both the locations.
Figure 5.1 Comparison of Leq with CPCB standards for both locations
0
10
20
30
40
50
60
70
80
90
MONDAY TUESDAY WEDNESDAY THURSDAY FRIDAY SATURDAY
De
cib
el
lev
el
in d
BA
Day of Survey TOLL PLAZA SRP TOOLS
CPCB
62
None of the two places recorded below 55 dBA. The values are in the range of
44 dBA and 105 dBA. The highest noise level recorded was during Wednesdays and
Thursdays. The scenario is same at both the sample points. The high level of noise
existed when compared to the standards laid down by CPCB.
The Leq level is alone compared with the CPCB where as if we observe from
the Table 4.1 and Table 4.2 it is clear that L10, L50, L90 values representing the time
duration of noise levels existed. These values show an increase of around 2.7 dBA to
22.7 dBA from standards set by CPCB. The noise level is generated because of
excessive number of vehicles that are plying along the OMR and the noise intensity
heard at surrounding places.
It is high time to evaluate a measure so that the noise intensity can be reduced.
The road way width is two-way and four lane highway, whereas in Chennai this case is
not predominant and the lane width is at times two lanes alone. The road way width is
also limited to and the people are subjected to severity of noise pollution.
In order to furnish the existence of noise pollution across the other states,
observed noise level at OMR areas are compared with other studies carried out in
different parts of India and it was found that, other urban areas also faced the similar
trend of noise pollution (Table 1.1). Thus, there is a need to create awareness among the
people about the rising noise pollution.
To reduce noise pollution, several measures can be implemented such as proper
maintenance of vehicles and roads, plantation of trees and application of appropriate
technology of providing noise barriers and enclosures will go a long way in the
abatement of high level of noise.
5.1.2 Results Based on Vehicular Noise on Pedestrian
The pedestrians are the persons who directly receive the noise pollution from the road
traffic. The road users are subjected to severe noise impact and this is shown in this
research. The noise level Leq is compared with the CPCB standards in the case of
Tambaram subway and is shown in Figure 5.2.
63
Figure 5.2 Noise level compared with CPCB standards
The noise level is higher than the CPCB standards by about 12.66 dBA to 22.67
dBA at both locations. On Saturdays and Sundays the noise levels are higher than the
normal days and show that the traffic is uniform through the week.
o The noise is predominant on all days both inside and outside the subway
o Leq level outside the subway is 72 dBA to 85 dBA and inside is 65 dBA to 80
dBA.
o The pedestrian rate is 700 persons/15 min and the vehicle rate is 1200
vehicle/hour. This rate shows that people suffer due to severity of existing noise
level.
o The location of subway very close to the highway and the subway surrounded
by crowded hawkers making the provision of a noise attenuating measure to
eliminate noise a difficult task.
5.1.3 Results Based on Noise Generated From Machinery (Construction)
Construction noise makers, e.g., heavy earth moving equipment, jack hammer,
marble cutting machine and vibrator machines are taken as examples for this study. The
noise parameters calculated from the primary survey are compared with the standards
set by MoEF and are presented in Figure 5.3.
0
10
20
30
40
50
60
70
80
90
100
Mon Wed Fri Sat Sun Thurs Tues
Out side
Subway
Inside
Subway
de
cib
el
lev
el
in d
BA
Day / Location
Leq
LCPCB
64
Figure 5.3 Noise level compared with CPCB standards
Figure 5.3 shows the simple comparison of Leq level with CPCB standards. The
CPCB standards set for the construction works is shown in Table 1.2. The construction
is multi activity oriented work and it involves different kinds of operation
simultaneously. The standard set by MoEF states that the noise limiting values are 75
dBA for compactors, vibrators, mixer, cranes and saw. Apart from these limits there are
certain rules to be complied for the construction activity like noise level should not be
maintained for more than 5 min interval, acoustic barriers to be provided, provision of
fencing around the sites and temporary earth bund around site using soil. From MoEF
guidelines the observations are now compared and shown that except mixer machine
and vibrator all the others are generating excessive noise. The noise level is 3 dBA
higher on the piling operation, 23.9 dBA on marble cutting and jack hammer operation.
The operation of all these three is for the entire day of work.
• Except the operation of vibrator and mixer all the equipment are above that
standard prescribed by the MoEF.
• The Leq level of MoEF is 75 dBA, where as it is observed the level is increased
from 6% to 58% from the machinery.
• The Lmin, Lmax and Lave levels are quite higher than the standards except in
vibrator equipment.
0.00
20.00
40.00
60.00
80.00
100.00
120.00
Mixer Vibrator Pile Marble Jack
Hammer
De
cib
al
lev
el
in d
BA
Construction activity
Leq
LCPCB
65
• The standards are prescribed for only 5 min of operation, whereas the machinery
operation is spread for a period of 2 to 8 hours depending upon the scale of
work.
• The level of noise for piling is presented in Figure 4.11 shows the intensity of
noise existed with respect to the time.
At present, there is no specific and detailed legislation to control the noise
pollution in construction except the guidelines given for a specific work.
The construction is a multi operational activity which consists of utilization of
different equipments like jack hammer, electrical conduit cutting, earth moving
equipment, and so on. The present construction now going in tech savvy way, it is high
time to evolve a standard for specific equipments. Moreover, the operations like jack
hammer not only disturbs the existing workers but also the surrounding residential areas
are affected when it is operated.
Normally, earplugs and other types of personal protective equipment (PPE) are
used to control a worker’s exposure to noisy equipment and work areas (Sellappan et al
2014). But this is of not much in use because the existing noise control measure is also
very limited to the present need. So, it is high time to evaluate the control measures
available so as to enable the authorities to provide a suitable control measure. The
control suggested by the researcher is based on the observations from his successive
studies done on these aspects.
5.1.4 Results from railway station and near locations
Railway stations are less prone for noise pollution but the level crossing and the
road side locations are subjected to severe noise pollution. Figure 5.4 shows the
intensity of vehicle crossing at Perungalathur railway road crossing.
66
Figure 5.4 Perungalathur station and level crossing location
The railway stations are receiving noise from the air horn alone. The trains
usually move at a speed of 70 to 100 KMPH and dissipate less noise. When the driver
of the train realizes the necessity of application of air horn he in turn presses the button.
Since the Perungalathur railway station and adjoining places prone for movement of
passengers as well as pedestrians frequent application of air horn existed. The Figure
5.5 shows the noise level at the Perungalathur railway station and nearby locations. The
noise level Lmin is around 37.7 dBA and L90 is 47.7 dBA in the railway station
premises. This shows noise is always at minimum level. The maximum noise of 87.4
dBA and the L10 of 85.4 dBA show that the noise is because of air horn alone in the
railway stations.
Figure 5.5 Noise parameters for the railway station location
o The influence of noise is limited to traffic alone
not prone for much noise pollution
o Figure 5.4 show clogged traffic and movement of pedestrian where as the
intensity of noise is around 81dBA
o The place is highly integrated by mass movement of pedestrians due to change
over facility near the railway station.
o The noise intensity fro
not less than 75dBA (Lmin) from Figure
crossing
Noise attenuation is need of the hour
control measures are limited here but the option of barrier will be right method due to
space constraints
0
20
40
60
80
100
120
Day 1
Railway
station
de
cib
el
lev
el
in d
BA
L10
oise parameters for the railway station location
The influence of noise is limited to traffic alone, whereas the railway station is
not prone for much noise pollution
show clogged traffic and movement of pedestrian where as the
intensity of noise is around 81dBA from Figure 5.5.
The place is highly integrated by mass movement of pedestrians due to change
over facility near the railway station.
The noise intensity from the primary data shows that the noise level is al
not less than 75dBA (Lmin) from Figure 5.5 in both outside the station and level
Noise attenuation is need of the hour because the noise is predominant. Noise
control measures are limited here but the option of barrier will be right method due to
Day 1Day 2
Day 1Day 2
Day 1Day 2Railway
station Level
crossing Road side
Location / Day
L50 L90 LMIN LMAX Leq
67
oise parameters for the railway station location
whereas the railway station is
show clogged traffic and movement of pedestrian where as the
The place is highly integrated by mass movement of pedestrians due to change
that the noise level is always
in both outside the station and level
the noise is predominant. Noise
control measures are limited here but the option of barrier will be right method due to
68
5.1.5 Results based on year of manufacturing of vehicle (Car)
Car was selected as a parameter for recording observation. The car was allowed
to run without deceleration and acceleration. The relevant noise parameters for this case
are shown in Figure 5.6.
Figure 5.6 Noise parameters for cars
o It is obvious that the vehicle manufacturing and the age of vehicle to run in
traffic stream has significance in contributing to the noise generation.
o Figure 5.6 shows that the noise generation is on down side giving an inference
of deterioration of engine for noise generation
o The Leq level was 78 dBA in the year 2002 and 58 dBA in the year 2012.
o The noise level was measured in an open environment and noise reflection was
marginal
o It is ideal to compare with CPCB standards to show the characteristics of
vehicle during non-operating condition in traffic. However it is generating noise
shown in Figure 5.6.
o Age of vehicle – an important aspect to be analysed for the noise generation.
0
10
20
30
40
50
60
70
80
90
2002 2004 2006 2008 2010 2012
De
cib
el
lev
el
in d
BA
Year of Manufacturing
L10
L50
L90
LMIN
LAVE
LMAX
Leq
LCPCB
69
5.1.6 Results based on flour mills operation
Rice flouring, mirchi flouring, seekakai flouring – these type of flour mills are
predominant in country like India. These types of flour mills are located very near to the
vicinity of residential colony and generate more noise during its grinding operation. The
noises levels are now compared with the standards prescribed by CPCB are presented in
Figure 5.7.
Figure 5.7 Flour mills operation compared with standards of CPCB
The noise levels at the flour mills were excessive as shown in Figure 5.7. The
CPCB has followed the guidelines set by MoEF and was used for comparison. The
flour mills show increase in noise with respect to the standards. All the flour mills are
having Leq level as 93 dBA for rice flour, 96 dBA for mirchi flour and 92 dBA for
seekakai mills operation an increase of about 18 dBA to 21 dBA with respect to the
standards. Of all the flour mills, mirchi flour machine showed more noise pollution. It
showed a 3 dBA increase with respect to other operations. The flour mills operation is a
day to day work and the process carried through all day of week. The flour mills are
located very near to the residential localities and are surrounded by three sides with
walls and front side open. Around 10 sqm of area is provided for the flourmills and the
front side is always open. Since the provision of flour mills are near to the residential
0
20
40
60
80
100
120
RICE FLOUR MIRCHI FLOUR SEEYAKAI FLOUR
De
cib
el
lev
el
in d
BA
Flouring operation
Leq LCPCB
70
colonies and lot of publics will be walking through the roads, it was decided to compare
the level of pollution emitted to a road where human interface existed. The comparison
is shown in Figure 5.8.
Figure 5.8 Comparison between traffic streams with flour mill noise level
To arrive at a meaningful comparison of noise pollution the process identified is
that the people are considered for the effects they face and who are affected directly
because of excessive noise generation. Two sources are identified for comparing noise
pollution one is due to traffic where the pedestrians are facing the hardships and other is
flour mills operation which is situated near the residential localities. The traffic survey
was already done on the OMR road and the noise parameters are calculated and the
observations are already presented in previous chapter 4. Another road indentified for
survey is Kollapakkam-Porur road (KPR) which is running through the residential
localities with less traffic. The comparison and the results are indentified and presented
in Figure 5.8.
o The traffic noise level Leq at OMR was 80.43 dBA which was 46% higher than
the standards set by CPCB of 45 dBA whereas at KRP Leq was 11% higher than
the standards.
0
20
40
60
80
100
120
OMR KPR RICE FLOUR MIRCHI FLOUR SEEYAKAI
FLOUR
De
cib
el
lev
el
in d
BA
Location
L10 L50 L90 Lmin Lavg
LMax Leq LCPCB LMoEF
71
o This was because the volume of traffic at KPR was very less. The noise level
Lmin to Lmax was in the range of 59.30 dBA to 87.90 dBA, at an average
intensity of 75.53 dBA at OMR.
o The corresponding traffic noise level at KPR was 39.90 dBA to 84.30 dBA, at
an average of 47.80 dBA.
o The traffic noise level Lmin at OMR was 59.30 dBA which was well above the
CPCB level of 55 dBA whereas the Lmin at KRP was 39.90dBA which was
well below the standards.
o Noise level L90 - noise level exceeded for 90% of the time in noise recording -
was 66.80 dBA, which was 21% higher than the standards in OMR whereas in
the KPR L90 was 42.20dBA which was well below the standards.
o Noise level high due to the floor mills operation when compared to standards.
o Flour mills are 18dBA to 21dBA higher than the MoEF standards.
o Whereas when compared with CPCB standards on the source specific it shows
that the noise levels in the mills are 38 dBA to 41 dBA more than the standards.
o Both cases of traffic and flour mills are subjected to severe noise intensity. If the
vehicles are less then no noise and the flour mills are not operated then there
will not be any noise.
o The two traffic noise locations show that vehicles contribute to generation of
noise among the humans.
o Both the scenario show that the humans are intervened in both the location but
the only change is noise source.
It is generally found that the people feel much pain in their ears and migraine during
duty hours as well as after duty hours. This study suggests that noise induced hearing
loss is a great challenge to environmental pollution. This noise exposure and
occupational noise exposure both interfere with their activities in the personal life of
people as well as their healthy living. The findings of this study also indicated the high
density residential area like OMR is affected by noise pollution that took a developed
residential area in the vicinity. Indeed some control measures and proper planning has
to be implemented to overcome the adverse effects from noise pollution and for the well
being of the residents.
72
5.2 Solution to noise menace
To tackle this noise menace; a slow poison – A comprehensive study should be
conducted as suggested from this study. With the present government policy and
mechanism in determining the need for mitigation measures to control noise pollution
in the country, an ideal solution is needed. Hence, a noise barrier is an ideal tool to
attenuate the noise which can be put in a place where noise intensity is high and the
surrounding environment is affected. Further study focuses with a suitable barrier
design as a control measure to attenuate noise.
5.3 Noise reduction
It is frequently necessary to use techniques that lower the level of noise on the
road side or at source. A variety of methods are available for noise reduction but they
can be basically grouped as follows: passive and active medium. Active medium differ
from passive mediums in that it is necessary to apply external energy in the noise
reducing process. The absorbing materials, as such, are passive mediums that lower
noise by disseminating energy and turning it into heat given by Environmental
Protection Department Hong Kong (Anon. 2006a).
The techniques employed for noise control can be broadly classified as
• Control at source
• Control in the transmission path
• Using protective equipment.
Out of all the three techniques noise control using transmission path is employed here
to reduce noise against traffic. The control measure is by providing noise barrier in the form
of cubicles and noise reduction is observed.
An attempt has been made to find the noise levels reduction at OMR section; two
sensitive places selected along OMR. It was observed that the noise levels were above
the standards prescribed by the CPCB standards at open stream where as inside barrier
reduction was considerable by about 3% to 20%.
73
5.3.1 Noise barrier
Noise barriers are typically constructed of cast-in-place concrete or masonry block in
certain areas, where space allows and where soil material is available, earth berms are
constructed as noise barriers. The barriers effectively reduce noise levels, but often
cause undesirable secondary impacts, such as blocked views of houses, blocking the
entry point for houses, frontal view, scenic features, and decreased visibility from the
roadway, large shadows cast across a resident’s front yard and backyard for extended
periods of the day. Raising noise barriers to achieve further noise reduction often
exacerbates these secondary impacts (Anon. 2006c). Innovative noise barrier designs
and treatments have been successfully implemented in other countries for a number of
years. These innovative designs have allowed the construction of a noise wall as a
traditional wall. Some of the innovative materials and designs that have been researched
and used in other jurisdictions include transparent panels, semi-translucent concrete
materials, acoustical treatments, and specially designed top treatments, such as curved
or angled tops, irregular top edges, or T-top treatments. Many of these designs have
their own advantages and disadvantages (Anon. 2006c). This research paper deals with
one such barrier: provision along the road side to find the noise levels reduction at
OMR.
The noise barrier selected were
• Noise barrier made of thatched leaves (porous material)
• Noise barrier made of plain cement concrete (non porous material)
• Noise barrier made of fly ash bricks (non porous material)
5.3.2 Barrier made of thatched leaves
A porous plant material called thatched leaves made of coconut leaves was used
as a sound barrier to construct a room on the road side near the sites of measurement.
The sound barrier was installed as a rectangular shed of size 1.5 m × 1.2 m × 2.0 m on
the side of the road as shown in Figure 5.9 and Figure 5.10. Continuous recordings of
Leq measurement during day time was carried out at both study areas. The results showed
that the noise pollution at the places of measurements was wide spread throughout most
74
of its time. The noise in this area was composite in nature consists of transport noise as
well as other sources. After the introduction of the shed there was a considerable reduction
in the level of noise inside the shed. An attempt was made to find the reduction in noise
levels at OMR section; two sensitive places were selected along OMR. It was observed
that the noise levels were above the standards prescribed by the CPCB (Central
Pollution Control Board, New Delhi) at outside the shed whereas inside the shed the
reduction was considerable by about 19%.
Figure 5.9 Thatched leaves noise barrier at Toll Plaza location
75
Figure 5.10 Thatched leaves noise barrier at SRP tools Junction
The noise results show that noise reduction is due to the introduction of barriers.
Noise parameters were calculated and the noise levels are compared with CPCB
standards are shown in Table 5.1.
Table 5.1 Noise parameters for noise barrier made of thatched shed
Location DATA TIME L10 L50 L90 LMIN LAVE LMAX Leq LCPCB
TOLL Past Data (2012)
With Out Shed 73.2 77.7 61.1 49.07 63.39 84.1 69.08 55
TOLL Present Data (2013)
With Out Shed 82.1 84.1 60.1 50.1 61.81 94.2 71.01 55
TOLL Present Data (2013)
With First Layer In Shed 73.2 74.2 61.1 42.4 63.48 81.7 62.12 55
TOLL
Present Data (2013)
With Second Layer In
Shed
66.2 67.2 60.1 38.4 59.89 76.7 59.61 55
SRP Past Data (2012)
With Out Shed 71.2 61.7 62.1 46.57 63.75 84.5 68.18 55
SRP Present Data (2013)
With Out Shed 85.2 84.5 65.1 59.3 75.53 87.9 72.17 55
SRP Present Data (2013)
With First Layer In Shed 79.9 77.2 61.8 59.8 66.11 79.6 61.13 55
SRP
Present Data (2013)
With Second Layer In
Shed
66.2 62.2 59.6 48.4 60.02 75.3 58.22 55
76
• The observations show that noise reduction is attained because of providing
noise barrier.
• Location of installation of noise barrier is same as the noise recorded in the
traffic stream
• Leq at the time of traffic data recorded was 69.08 dBA at Toll Plaza and 68.18
dBA at SRP location but during the time of observation at installation of barrier
the values are 71.01 dBA 72.17 dBA, respectively.
• The above statement shows that noise level is increasing or not up to the
standards.
• The results of noise level with barrier Leq level is 62.12 dBA and 59.61 dBA at
Toll Plaza location for first layer and second layer of thatched leaves whereas at
SRP location 61.13 dBA and 58.22 dBA, respectively.
• Noise reduction is possible and noise reduction is predominant when two layers
of thatched leaves barriers are provided.
• Noise reduction and the percentage of noise reduction are shown in Table 5.2.
Table 5.2 Details of noise reduction at both locations
Parameter
% Increase of noise
from past (2012) to
present date of
recording (2013)
% of noise
reduction due to
shed consisting of
first layer
% of noise
reduction due to
shed consisting of
second layer
Toll
Plaza
SRP
tools
Toll
Plaza
SRP
tools
Toll
Plaza
SRP
tools
Leq 3 6 13 15 16 19
LMAX 12 4 13 9 19 14
LMIN 2 28 15 0 23 19
LAVE 2 18 3 12 3 21
• The noise Leq is increased from the past data collected in 2012 to present date of
recording in 2013
• The increase in noise level is 3 to 6 % from the past data to present data
77
• The Table 5.2 shows that there is a considerable reduction on providing barrier
• The percentage reduction of noise level ranges from 3 to 10
• The provision of thatched leaves shows that the noise level can be reduced
considerably.
• The selected area is a suitable location because of highly congested place
• The provision of noise barrier as an enclosure found to be a suitable alternative
solution for noise control measure.
• This is suitable for all places, low cost technique not requiring skilled manpower
for installation, flexible in altering the design, can be installed in critical places
where other measures are ineffective.
5.3.3 Noise barrier made of plain cement concrete and coral shell powder concrete
The noise barrier provided was cement concrete blocks made of plain cement,
aggregates and partial replacement of cement with powder made from coral shells with
aggregates. Plain cement concrete were nothing but conventional 100% cement
concrete blocks and Coral Shell Powder (CSP) blocks are cement concrete blocks
where cement is partially replaced by about 10% during concrete mixing. The M30
mix concrete was used for both types of concrete blocks. The blocks are of size 15 cm ×
15 cm × 15 cm. The blocks were stacked as cubicles as shown in Figure 5.11 and
Figure 5.12 at both locations.
The noise barrier was installed as rectangular cubicles of size 0.60 m × 0.60 m ×
0.60 m on the side of the road. Figure 5.11 and Figure 5.12 shows a schematic view of a
noise barrier as concrete cubicles constructed both with conventional concrete and CSP
concrete at the selected locations. Continuous noise level is recorded and duration of
noise recording is presented in previous chapter. Noise level is first recorded in traffic
stream, followed by providing noise barrier in the form of cubicles. Noise meter is then
placed inside the cubicles at both type of concrete blocks noise levels were recorded.
Noise levels recorded were calculated for noise parameters and are presented in Figure
5.13 and Figure 5.14.
78
Figure 5.11 Concrete noise barriers as cubicles at SRP Tools location
Figure 5.12 Concrete noise barriers as cubicle at Toll Plaza location
Figure 5.1
Figure 5.14 N
Noise levels recorded are compared with the CPCB
calculated and are presented in Figure 5.
Results show that there is considerable reduction by the provision of noise barrier
• Noise level leq is 69.08
0
20
40
60
80
100
LMINLAVE
De
cib
el
lev
el
in d
BA
Noise parameter
0
20
40
60
80
100
LMINLAVE
De
cib
el
lev
el
in d
BA
Noise parameter
13 Noise parameter for Toll Plaza location
14 Noise parameter for SRP tools location
Noise levels recorded are compared with the CPCB standards. All noise parameters
calculated and are presented in Figure 5.13 and Figure 5.14.
Results show that there is considerable reduction by the provision of noise barrier
Noise level leq is 69.08 dBA on the year 2012 and it was increased to 73.3
LAVELMAX
Leq
Toll plaza
Noise parameter
Past data (2012) with out
barrier
Present data (2013) with out
barrier
Cubicles made of normal
concrete
Cubicles made of CSP
concrete
LCPCB
LAVELMAX
Leq
SPR Tools
Noise parameter
Past data (2012) with out
barrier
Present data (2013) with out
barrier
Cubicles made of normal
concrete
Cubicles made of CSP
concrete
LCPCB
79
All noise parameters
Results show that there is considerable reduction by the provision of noise barrier
on the year 2012 and it was increased to 73.3 dBA
Past data (2012) with out
Present data (2013) with out
Cubicles made of normal
Cubicles made of CSP
Past data (2012) with out
Present data (2013) with out
Cubicles made of normal
Cubicles made of CSP
80
in 2013 at Toll Plaza location, similar trend is continued in SRP tools location.
• Noise level is 60.5 dBA and 61.1 dBA inside both cubicles at Toll Plaza
location, where as 58.85 dBA and 59.64 dBA at SRP tools location
• Noise level is reduced inside the cubicles and the reduction is shown in Table
5.3.
• Noise level maximum is 86.1 dBA in 2012 and which has been increased to 98.2
dBA in 2013
• Day to day the noise level is increasing, this is due to number of vehicles keeps
on increasing.
• The comparison of CPCB standards also show that noise level is increasing at a
rate of about 18.33 dBA
• Noise pollution is at negligible level inside the cubicle and the levels are slightly
equal to CPCB standards.
Table 5.3 Details of noise reduction at both locations
Reduction of noise level from present data to cubicles made of normal concrete
Reduction of noise level from present data to cubicles made of CSP concrete
All values are in Decibels
Toll Plaza SRP tools Toll Plaza SRP tools
Leq 11.2 11.31 10.8 10.6
• The reduction shown in Table 5.3 shows that noise is reduced by about 106 dBA
to 11.31 dBA by providing noise barrier in the form of cubicles.
• The conventional concrete and CSP concrete shows that barrier can be provided
as pre-cast unit along the road sides.
• Even though the test is carried as a construction of concrete cubicle there is no
significance loss of noise reflection because the concrete is plain cement
concrete.
• The CSP concrete gives noise reduction of 16.64% which is equal to the normal
concrete.
• The concrete shed as a barrier shows that the noise level can be reduced
considerably
81
• The CSP concrete shows equal reduction of noise with respect to normal
concrete
• There will be a considerable reduction in utilising the cement because CSP is
used as partial replacement.
• The cost is reduced when compared to normal concrete.
• The CSP will be an alternate material for cement because now the cost of
cement escalates daily.
• The selected area is a suitable location because of highly congested place
5.3.4 Noise barrier made of fly ash bricks.
The noise barrier provided was constructed with bricks that are made of fly ash.
The blocks were of size 230 mm × 115 mm × 75 mm (which is a standard size of bricks
used in construction industry). The blocks were then placed along road side and stacked
for the required size as mentioned below and constructed as an enclosure. The enclosure
was installed as a square cubicle of size 1.0 m × 1.0 m × 0.60 m on the side of the road
shown in Figure 5.15 and 5.16.
Figure 5.15 View of noise barrier as a cubicle made of fly ash at Toll Plaza location
82
Figure 5.16 View of noise barrier as a cubicle made of fly ash at SRP tools location
For both locations the process of noise reduction is achieved by reducing the
noise along its transmission path. Here, another way of reducing the noise was used by
providing a cubicle form of enclosure made of fly ash bricks. The data collected from
survey is for duration of about an hour and result is presented in chapter 4. Noise levels
were recorded and noise parameters calculated. The noise levels are further compared
with noise levels prescribed by CPCB and presented in Figure 5.17 and Figure 5.18 in
respect of both the locations.
Figure 5.17 Noise parameters at Toll Plaza with and without fly ash cubicles
0
20
40
60
80
100
120
L10 L50 L90 LMIN LAVE LMAX Leq
De
cib
el
lev
el
in
dB
A
Noise parameters
Toll plaza with fly ash shed Toll plaza with out fly ash shed LCPCB
83
Figure 5.18 Noise parameters at SRP Tools with and without fly ash cubicles
From Figure 5.17 and Figure 5.18, it is inferred that the noise level is above the
standards. The noise parameters L10, L50, L90, LMIN, LAVE, LMAX and Leq for Toll plaza
location with flyash bricks as an enclosure are 81.6 dBA, 71.6 dBA, 67.4 dBA, 71.77
dBA, 93.7 dBA, 64 dBA and 75.29 dBA, respectively; whereas noise level without
enclosures shows the following results 86 dBA, 76.4 dBA, 69 dBA, 75.64 dBA, 98.5
dBA, 63 dBA and 78.02 dBA, respectively. The noise levels are more without
enclosures. The traffic is similar to the past data recorded in 2012 and the results are
also similar. Noise level is reduced and the reduction due to enclosure is shown in
Figure 5.19 for both locations. If results are compared with CPCB standards at both
locations, noise levels are more than standards. Noise in the enclosure is slightly equal
to the standards.
0
20
40
60
80
100
120
L10 L50 L90 LMIN LAVE LMAX Leq
De
cib
el
lev
el
in
dB
A
Noise parameters
Srp tolls with fly ash shed Srp tolls with out fly ash shed LCPCB
Figure 5.19
From the results it is shown that there
of barriers. The noise reduction and its percentage are shown in Table
Table 5.4 D
Parameter
Leq
LMAX
LMIN
LAVE
• The result shows that the noise pollution existed.
• Noise levels are at an increasing trend from the year 2012 to year 2014.
• Noise levels are 69.08
dBA in the year 2014. When compared with CPCB levels increment is around
20dBA.
• Even the minimum sound level of 63dB
55dBA.
• This shows that there is an urgent need for controlling the noise pollution.
• Figure 5.19 shows that there is a considerable reduction on providing noise
barrier.
0
10
20
30
40
50
60
70
80
90
Toll plaza
De
cib
el
lev
el
in
dB
A
Past data (2012) with out barrier
With out fly ash cubilces
LCPCB
19 Details of noise reduction at both locations
shown that there is considerable noise reduction by the installation
of barriers. The noise reduction and its percentage are shown in Table 5.4.
Details of Noise Reduction at both locations
arameter % Reduction of Noise from enclosure
Toll plaza SRP tools
5.12 6.77
4.87 4.23
--- ---
3.50 2.79 The result shows that the noise pollution existed.
Noise levels are at an increasing trend from the year 2012 to year 2014.
levels are 69.08 dBA in the year 2012, 73 dBA in the year 2013 and 75.08
year 2014. When compared with CPCB levels increment is around
Even the minimum sound level of 63dBA is higher than the limiting value of
This shows that there is an urgent need for controlling the noise pollution.
shows that there is a considerable reduction on providing noise
Leq Leq
Toll plaza SRP tools
Noise parametersPast data (2012) with out barrier Past data (2013) with out barrier
With out fly ash cubilces With fly ash cubilces
84
considerable noise reduction by the installation
.
Noise levels are at an increasing trend from the year 2012 to year 2014.
2013 and 75.08
year 2014. When compared with CPCB levels increment is around
is higher than the limiting value of
This shows that there is an urgent need for controlling the noise pollution.
shows that there is a considerable reduction on providing noise
Past data (2013) with out barrier
85
• The reduction of pollution inside the barrier comes to about 7% from the
existing road condition
• Even though the reduction is partial but the percentage reduction is significant if
number of vehicles increased.
• Normally, the provision of noise barrier is a cost incurring operation, however,
this type of low cost effective barriers were constructed along highly congested
locations where noise pollution is heavy.
• This is suitable for all locations, low cost technique, not requiring skilled
manpower for installation, flexible in altering the design and can be installed in
critical places where other measures are ineffective.
5.4 Comparison of noise barriers
The barriers effectively reduce noise levels, but often cause undesirable
secondary impacts, such as blocked views of mountains and other scenic features,
decreased visibility from the roadway, or large shadows cast across a resident’s
backyard for extended periods of the day. Raising noise barriers to achieve further noise
reduction often exacerbates these secondary impacts. Following the identification of
available innovative noise barrier designs, a comparison was created to evaluate best
designs. The comparison is shown as table in annexure. Evaluation criteria generally
grouped into performance, material availability, economic considerations,
constructability considerations, maintenance considerations, and aesthetic
considerations. The comparison is shown in Table 5.5.
86
Table 5.5 Comparison of all barriers provided in the study area
Sl.
No.
Comparison
description
Thatched leaves
(1 layer and 2 layers)
Concrete M30 grade
(normal and CSP concrete)
Fly Ash bricks
1 Type of material Porous material Non porous material Non porous material
2 Cost of barrier Low cost barrier High initial cost High when compared to
thatched and low when
compared to concrete
3 Installation Installation is easy It can be pre casted and fixed
3 Suitability Suitable for temporary noise
attenuation
Highly suitable for permanent attenuation
4 Adaptability Due to porous and flexible
adaptability is limited to short
term measure
Meant for long term measure where sure of noise attenuation
5 Aesthetic Aesthetically not ideal but
depending upon usage it can be
installed
Aesthetically ideal and can be a good suitable attenuator
6 Climate
sustainability
The barrier sustainability is
limited to 3 months to 6 months
Permanent barrier only casting and cost involved
7 Environment
friendly
It reduces noise – it is as good
as other material
Waste material like CSP was
used as partial replacement of
cement - utilisation of waste
material has been achieved
Here also we use waste
material like fly ash
8 Percentage of
noise reduction
3% to 10% 11% to 20% 3% to 7%
87
5.5 Noise control barrier
At the present time, the active noise control barrier design is mostly theoretical
and has only seen limited field test installations. There have not been any practical real-
world installations of the active noise control barrier design.
Based on the research and evaluation conducted for this study, it was
recommended that three innovative noise barriers design to be implemented in places
where noise pollution is more than the standards. Barriers are of two different kinds
such as porous and non porous material but have potential to attenuate noise levels. The
barrier which is porous in nature like thatched leaves can be applied as a vertical noise
barrier facing highway traffic. This barrier reduces noise by absorbing noise and
eliminating reflected noise off the face of the barrier. When the traffic is high the noise
levels will also be high in that locations these form of barrier can be installed and the
noise reduction can be attained. In addition during specific requirements like festivals,
special engagements and public meetings these forms of barriers can be erected.
Because these are light in weight, easy to handle, eco friendly and cost effective. The
other form of barrier like concrete blocks, concrete made of CSP blocks and fly ash
bricks blocks which are non porous and has potential to reduce noise by about 15% in
decibel levels can be installed in places where noise source is high like flour mills,
subway, jack hammer, marble cutting places and other noise generating sources.
5.6 Noise prediction
An important factor for the life quality in urban centers like Chennai is related to
the noise levels to which the population is submitted. Several factors interfere with the
amount of noise pollution throughout the city. Among them, and as one of the most
important, is the traffic noise which has been shown in previous chapters. A major
challenge is the quantification of the noise effects on the population. For this reason, to
establish pre- and post-operational measures against such noise problems, noise
prediction simulation is adopted.
88
5.6.1 Noise model necessity
Criteria of road traffic noise in India are based on Leq, therefore any model that
estimates Leq is applicable. As the type of vehicle, noise emission and road structure in
India especially in Chennai is different from other countries. The empirical models such
as FHWA, Stefano, Li, Parida, Gundugdu, Tansatcha and Lam (Golmohammad et al
2007) are not suitable for prediction of road traffic noise in Indian condition. Here, the
mode of transport is from bi cycle , two wheeler, car, share auto, auto, LCV, HCV, Bus
and sometimes bullock carts as per Saxena (1989) and Staff Reporter (2013). In this
thesis a statistical model for predicting -weighted equivalent level is proposed for
Indian condition to design a road traffic noise prediction model from traffic variables.
5.6.2 Contributors for predicting noise
There are more than 10 factors such as volume of vehicles, mode of vehicles,
speed of the vehicles, number of pedestrians, pavement width, surface of pavement,
height of building from road way, observation of noise level from its source, etc.
Golmohammad et al (2009). The list is enormous that contributes to the generation of
noise among the humans. Measuring all the variables for predicting road traffic noise is
difficult and also it is a long term process. Therefore in this research a compact model
with four variables were adopted to obtain a prediction of noise level. The purpose of
this study is to introduce a compact road traffic noise model from traffic variables and
conditions for the city like Chennai. The researcher has suggested the basic parameters
such as volume of vehicles, mode of vehicles, sound source distance from observation
point and speed of vehicles as exploratory factors to predict equivalent sound level.
5.6.3 Study area and data collected
The OMR selected for study purpose the sampling locations were Toll Plaza at
Perungudi and an intersection by name SPR Tools where traffic noise was recorded.
The following data were collected by conducting primary survey.
89
• The noise levels were recorded from morning 10.00 AM to 18.00 PM at an
interval of 10 sec from Monday through Saturday at both locations.
• Total volume of vehicles for the entire period.
• No of vehicle/ hr according to the mode of vehicle such as bus, car, LGV, two
wheeler, share auto and HGV.
• The above details have been taken at a sampling rate of two hours on morning
and afternoon and at peak and non peak hour.
• Speed of the vehicle by way of moving car method at SRP tools.
• Noise measurements were taken at a distance of 0.90 m and 1.10 m from the nearest
road band
• The height of noise measurement is 130cm above the road surface
It was assumed that only these modes of vehicles types contribute to the road traffic
noise and that all vehicles can be categorized into one of these classes. The noise levels
vary within the selected categories due to their variations within the classes and the
condition of the vehicles, mode of operation of vehicles and speed of vehicles.
90
CHAPTER 6
MODELS FOR PREDICTION
6.1 Developing model based on traffic parameters
Using the contributing parameters, the urban traffic noise pollution for the
whole city could be predicted as described below. The method of prediction was to find
out mathematical and physical models that could be applied to real like scenario and for
future development. As the traffic noise pollution was not the same as other types of
pollution, the multiple linear regression method was the best suitable method, since
traffic varied statistically.
The choice of prediction models can be divided into two steps: first to find out
the prediction function and its dependent variable y and independent variable x1, x2, x3
etc., that means to set up a relationship between traffic noise level and some parameters
such as traffic volume, vehicle's type, driving speed, etc; then to establish dependent
variables y. Once the values of y are determined, the prediction can be arrived. The
situations of traffic noise pollution in the future can be predicted using the obtained
regression equation Saxena (1989).
6.2 Regression analysis
Regression analysis is nowadays the most common method employed in traffic
forecasting analysis. The approach is to derive linear equation based on results of the
survey. These relationships are presented in the following forms:
y = a0 + b1x1 + b2x2 + b3x3 + ……….
where, y = dependent variable
a0 , b1, b2 , b3 = Constants (coefficient of regression).
x1 , x2 , x3 = Independent variable
In case of traffic analysis like trip generation it is always the case that variables
are truly independent. For example, vehicle ownership of a house hold is an important
factor for trip generation, but vehicle ownership itself depends on income, household
size, location etc. For structuring regression model, it is necessary to make choice of
91
only those variables which are independent, and have significant effect on end results.
Variables should be continuous in nature, but this is not true always where as zonal
averages make it true.
All of the collected data were entered in the statistical sheet of Excel and SPSS
software. Multiple linear regression models were applied to develop a new model for
Chennai city. The scatter plot of the data would be generated to show if there was any
relationship between Leq and mean vehicles' speed as well as vehicles flow. Therefore,
for the fitted model, the transformation of flow and speed of vehicles were considered.
The developed model and their relationship between them were arrived at and the most
possible R (correlation factor) value was found. The correlation between independent
variable and dependent variable and the cases considered is presented in Table 6.1.
Table 6.1 Variables used and their respective representation
Sl.
No.
Location Case
considered
Dependent
variable
Independent variable
1
Toll Plaza
and
SRP
Tools
C1 – C6
Leq
Type of Vehicles –
Car/LGV/Two-wheeler/Bus/HGV 2
3
C7 – C12 Speed of all type of vehicles
(Car/LGV/Two-
wheeler/Bus/HGV
C 13 Total Vehicles / hour
4 C14 Distance from the source
5 C15 All the above parameters
6.3 Regression Model
The developed model has most possible entrance variable for estimation traffic
noise (Leq). Four groups of independent variables were considered to assist dependent
variable Leq in the model. This designed model can predict Leq at distances of about 0.90 m
to 1.10 m from the roadside edge. Several papers described about modeling of noise
pollution and prediction of noise Leq. The results are shown in Figure 6.1.
92
Figure 6.1 R value corresponding to Leq value
Following results are arrived from the regression model
The primary survey predicts that mean Leq is 69.56 ± 2% dBA of the average
value. The results show that the R value for Leq is in the range of -0.09 to 1, which
implies to all the independent variables. The mean speed of all modes of vehicles is also
±4% of the average value. The regression model developed has 13 independent
variables and one dependent variable of four set each. Based on Figure 6.1 which shows
the Leq dependency with significance R value of 0.99 this consists of both total volume
of vehicle and mode of vehicles.
The significance of this is that both in their volume exhibits noise generation at
the source. Speed of the vehicles contributes less regression for prediction of model.
Hence the speed is considered for finding the correlation factor R value when all the
variables are considered.
The equation for noise prediction is presented below show as a sample for one and two
variables.
Case 1 (Independent variable as Car)
y = a + bx1
where y = dependent variable (Leq)
a,b are the coefficients
x1 = independent variable (number of cars)
‐1.50
‐1.00
‐0.50
0.00
0.50
1.00
C1 C2 C3 C4 C5 C6 C7 C8 C9 C10 C11 C12 C13 C14
R v
alv
e -
corr
ela
ted
wit
h L
eq
independent variable
Leq
Leq
93
y = 62.49 + 0.0247x1 where R value is 0.596
Similarly if two sets of independent variables are considered (number of cars and speed
of cars)
y = a + b1x1 + b2x2
Where y = dependent variable (Leq)
a,b are the coefficients
x1, x2 = independent variable (number of cars and journey speed of car)
y = -1.3150 + 0.0067x1 + 1.2426x 2 where R value is 0.9362
Likewise for the entire variable can predict the noise Leq value and the R value is
plotted in Figure 6.1.
The predicted and observed value is shown in Figure 6.2 where one can obtain a
residual statistics of about 64.79dbA minimum and 74.45dbA maximum with a
difference of about -1.19dbA to 1.23dbA.
Figure 6.2 Distribution of predicted Leq and measured values
Model suggested by the present researcher is applicable for all condition of road
traffic existed in country like India. Here, pattern of traffic is not uniform and also the mode
of transportation is from public transportation vehicles to private transportation. The share
of private transportation is about 70% of total volume Staff Reporter (2013). The control
measures are limited and the noise is predominant at all the places (Dasarathy and
Thandavamoorthy 2013b).
94
The predicted model is compared with the model study conducted around other
cities and are presented in Table 6.2. There the model is developed based on the certain
independent variables and software for predicting the noise models. The traffic pattern
is complex nowadays and the growth of vehicles is phenomenal. The model with
multiple linear regressions is most common method adopted in traffic analysis. Here,
the consideration is that the independent variable is true to its independence and
continuous in nature (Saxena 1989). For constructing regression models it is necessary
to choose the variables which are contributing to predicting the required noise level
Leq. The present study used a simple method of regression model for predicting traffic
noise level leq. The correlation also has a good range of R value for predicting noise
level.
Table 6.2 Comparison of predicted model with other developed models.
Noise model by
authors
Parameters considered Mathematical
or Software
Mean SD Differenc
e
Measured Leq Mode of Vehicles, total
number of vehicles,
journey speed
Multiple Linear
regression
69.56 3.99
Suggested model
(present study) 69.62 3.49 +0.07
Model by
Golmohammadi et
al (2007)
Mean speed, number of
vehicles in different mode,
distance
Mathematical 69.69 3.45 +0.365
Model by
Golmohammadi
et al (2009)
Mean speed, number of
vehicles, number of trucks,
distance
Mathematical 68.27 3.81 -0.77
Model by
Dan Qun (1989)
Traffic flow, population
near, distance
Mathematical 72.3
±0.10 to -
1.30
Model by
Sooriyaarachchi
et al (2008)
Spot speed, mode of
vehicles, distance
Mathematical
±10.91dBA
Model by
Karantonis et al
(2010)
Total vehicles, mean speed
of vehicles, barriers
provided.etc,
CadnaA and
soundPLAN
75.2 4.8 ±2.3
Model by
Mutairi et al (2009)
Light vehicle ,heavy
vehicle, mean speed of
vehicles number of lanes
US AHWA ±1.0 to 2.0dBA
Model by
Dinesh Kumar
et al (2012)
Growth of vehicles, Lyons Model R2 = 1 to 0.7
95
This study focused on developing a suitable model for noise prediction in
Chennai. The noise prediction models are used as a solution for designing noise
reduction measures and also control measures. Several studies developed regression
models but suitability to the mixed flow of traffic in Chennai is needed now. This
research is the result of noise survey conducted in Chennai in the year 2012, can be
applied to any amount of traffic pattern and has high chance of predicting noise level
with a distance of around 1.0 m from the carriage way.
6.4 Spectral analysis
Noise frequency spectrum influences sound quality especially low frequency
noise (LFN) which gives raise to same level of concern as neighborhood noise and can
have a serious effect on the quality of life of those affected by it. The sources of LFN
may vary from vehicle noise from traffic, wind mills, machinery from industries and
some sensitive equipments. Frequency carries a vital role in detecting sound quality and
propagation. Noise frequency spectrum is taken into account to preciously assess noise
attenuation and mitigation measures
Compared with other environmental noise standards it may initially seem too
stringent to required levels of LFN to be reduced to around the threshold of hearing.
However, there is a growing experience that such low limits are needed to provide
adequate protection from LFN. This is because of the strong reactions and the apparent
difficulty in habituating to LFN (Noise Programme Department of the Environment,
Northern Ireland 2001).
The form of the reference curve has been discussed above. Most existing curves
are based on thresholds of audibility, which have been established for many subjects
over many years, and provides one with the most comprehensive and reliable data about
hearing in the low frequency range. Regarding fluctuations, there is much less data
available. It is not possible to determine the effect of fluctuations through field studies;
for one thing it would not be practicable to survey enough cases, and for another, there
is too much variation between field studies, including the personal situation of the
subjects, the length of exposure and the character of the sound. To establish the effect
96
of fluctuations there is a need to measure the reactions of several people to the same
sound, and this can best be done by setting up tests in the laboratory.
There are limitations in laboratory testing of LFN. In particular, the disturbance
in the field often includes an element of ‘sensitization’ to exposure over extended time,
and this factor cannot be reproduced in the laboratory. Nevertheless, the annoyance of a
sound can be judged by most subjects after a few minutes.
Frequency Composition of Sound is represented in Figure 6.3
Figure 6.3 Frequency distribution
Since the LFN is multiple frequency composition sound, frequency spectrum is
obtained through Fourier Analysis from Brüel & Kjær Sound and Vibration
Measurement A/S (Anon. 2010c).
6.5 Theory about LFN
The LFN problem could occur anywhere in the range 10 –150 Hz but were
usually associated with noise in the 40 – 60 Hz range. The commonest cause of such
noise is industry but there can be many other causes, some of them domestic
(refrigerators, oil fired boilers, and washing machines) and some associated with road
vehicles. Sometimes LFN seems more like vibration than noise and it can cause
structural vibration. It is in any case likely that the business of identifying the source of
LFN will be laborious and may not always be conclusive. LFN is sometimes confused
with vibration. This is mainly due to the fact that certain parts of the human body can
resonate at various low frequencies. For example the chest wall can resonate at
97
frequencies of about 50 to 100 Hz and the head at 20 to 30 Hz (Noise Programme
Department of the Environment, Northern Ireland 2001).
As the A-weighting network attenuates low frequencies by a large amount, any
measurements made of the noise should be with the instrumentation set to linear. For a
preliminary analysis, measurements should be by conducting noise survey and detailed
analysis would need the use of narrower frequency bands or even a FFT (Fast Fourier
Transform) analyses (Can et al 2010).
Spectral analysis was used to determine the frequency composition of sounds.
Spectrum is built by a series of sine waves and Fast Fourier spectral analysis was
carried for the present study. The spectrum analysis is run through MATLAB tool for
each cases and are represented in separate figures.
The procedure adopted for the spectral analysis is each noise source data
recorded through the noise meter is logged. Data which were received from sound level
meter is converted in to signal as an input to the FFT analysis using MATLAB.
6.6 MATLAB
MATLAB is a technical computing environment developed by The MathWorks,
Inc. for computation and data visualization. It is both an interactive system and a
programming language, whose basic data element is an array: scalar, vector, matrix, or
multi-dimensional array. Besides basic array operations, it offers programming features
similar to those of other computing languages, e.g., functions, control flow, etc.
Martinez (2005).
� MATLAB is a program for doing numerical computation. It was originally
designed for solving linear algebra type problems using matrices. Its name is
derived from MATrix Laboratory.
� MATLAB has since been expanded and now has built-in functions for solving
problems requiring data analysis, signal processing, optimization, and several
other types of scientific computations. It also contains functions for 2-D and 3-
D graphics and animation.
98
� Writing User Defined Functions and m-files which can be executed by
specifying some inputs and supply some desired outputs (Christoph 2001).
� The coding language telling procedure to be adopted for the execution of signal
data from the noise meter and FFT process in the MATLAB.
� This coding language is written in command at the beginning of the m-file and
has to be saved as the m-file with a file name and the same as the function name
has to be retrieved for analysis.
A sample coding language is mentioned and it is written with necessary procedure
and options of performing FFT analysis. Commands can be entered interactively at the
command line or saved them in an m-file. So, it is important to know some commands
for file management. Some of the commands shown in Table 6.3 can be used to list,
view, and delete files. Variables created in a session (and not deleted) live in the
MATLAB workspace. It can recall the variable at any time by typing in the variable
name with no punctuation at the end. It is to be noted that MATLAB is case sensitive,
so Temp, temp, and TEMP represent different variables. MATLAB remembers the
commands that one enters in the command history. There is a separate command history
window available via the View menu and certain desktop layouts. One can use this to
re-execute old file with new in formations.
Table 6.3 File Management Commands
Command Usage
dir, less Shows the files in the present directory.
delete filename Deletes filename.
cd, pwd Show the present directory.
cd dir, chdir Changes the directory. There is a pop-up menu on the
toolbar that allows the user to change directory.
type filename Lists the contents of filename
edit filename Brings up filename in the editor.
which filename Displays the path to filename. This can help
determine whether a file is part of the standard
MATLAB package.
what Lists the .m files and .mat files that are in the current
directory.
clc;
clear all;
99
close all;
NNN = 10000;
Fs = 200;
F=1000;
YY2=load('f:\SRP TOOLS\With CSP concrete shed.txt');
YY3=load('f:\SRP TOOLS\With normal concrete shed.txt');
YY4=load('f:\SRP TOOLS\With out shed.txt');
l=length(YY2);
T=0:(l-1);
N=512;
figure;
plot(T,YY2); hold on;
hold off;
title('Noise Signal');
xlabel('Time(s)');
ylabel('magnitude(db)');grid on;
for i=1:N/2
freq(i)=(i/256)*(Fs/2);
end
y=fft(YY2,N);
y=fft(YY3,N);
y=fft(YY4,N);
figure;
plot(freq(1:256),YY2(1:256),freq(1:256),YY3(1:256),freq(1:256),YY4(1:256)); hold
on
title('Noise Signal');
xlabel('Frequency(Hz)');
ylabel('Magnitude(db)');grid on;
figure;
title('Noise Signal');
xlabel('Frequency(Hz)');
ylabel('Magnitude(db)');grid on;
plot(freq(1:256),abs(ifft(1:256))/256,'r');
100
hold off;
If more was known about the effects of noise pollution, however, it would be
possible to know exactly how noise effects the environment, and at that frequencies,
making it possible to enact laws limiting noise pollution specifically and with greater
effect, and to learn how much noise is dangerous to humans and the environment.
6.7 Spectral analysis for traffic stream
The noise frequency is random and sample spectrum analysis (Figure 6.4) shows
that the frequency is of range 20 Hz to 40 Hz with a decibel level of 53 dBA to 74 dBA.
The peak frequency of 85 Hz occurred at a sound intensity of 80 dBA. This show that
usually low frequency noise is also has frequency distribution.
Frequency distribution here is oscillatory representation that shows that noise
levels uniformly penetrate into the atmosphere. Noise spectrum shows that noise levels
lie between 61 dBA to 79 dBA during all range of frequencies this implies that it is like
a band width.
Figure 6.4 Spectrum of open traffic stream at SRP tools location
0 10 20 30 40 50 60 70 80 90 10045
50
55
60
65
70
75
80Noise Signal
Frequency(Hz)
Ma
gn
itu
de
(db
)
Open stream on friday
101
The band width implies the noise intensity is dissipating noise during entire day of
operation of traffic. The variation of frequency is from higher to lower during all part of
the noise signal occurrence.
6.8 Spectral analysis for subway
Subway locations were noise levels recorded and the level of annoyance was
shown in chapter 4. The spectral Figure 6.5 shows that the frequency of noise decibels
is uniform both inside as well as outside.
Figure 6.5 Spectrum of Tambaram Subway
The level of frequency is at times staggering level. The frequency level at
outside the subway is always on the higher range than the inside the subway. Most of
the time inside the subway the noise level is the range between 60 dBA to 70 dBA with
a frequency range of 10 Hz to 82 Hz.
0 10 20 30 40 50 60 70 80 90 10050
55
60
65
70
75
80
85
90Noise Signal
Frequency(Hz)
Ma
gn
itu
de
(db
)
Inside Subway
Out side subway
102
Whereas the frequency ranges of 80 Hz to 90 Hz occurs with a decibel level of
75 dBA outside the subway. The maximum decibel level 88 dBA reaches at a frequency
of 77 Hz inside the subway. Outside the subway the maximum decibel level of 84 dBA
reaches on different frequencies. This show that noise frequency is predominant at
outside the subway with a higher decibel level.
6.9 Spectral analysis for construction noise
Construction noise is usually a hindrance to the human interface. Lots of
construction activities require machinery. Noise generation due to machinery nowadays
has become annoyance. The spectral Figure 6.6 shows some light on the frequency
representation of noise levels. Here, noise levels are interpreted for the frequency
representation.
Except the marble cutting operation all other operations falls like a band width
in a frequency range of 0 to 200 Hz with a decibel range of 70 dBA to 80 dBA in the
case of mixer machine and vibrator operation.
Figure 6.6 Spectrum of construction noise
Whereas the decibel range is 90 dBA to 100 dBA for piling work, jack hammer
shows a decibel level of 100 dBA to 120 dBA. The band width form of frequency
0 20 40 60 80 100 120 140 160 180 20060
70
80
90
100
110
120
130Noise Signal
Frequency(Hz)
Ma
gn
itu
de
(db
)
Jack hammer
Pile operation
Marble cutting
Vibrator
Mixer machine
103
representation shows that uniform level of noise is generated as a source. Also, the
noise frequency is a periodic function and the occurrences are in sighted in Figure 6.6.
Marble cutting shows a uniform and linear noise frequency and all other noise levels
represent a periodic relation.
The peak decibel level of 101 dBA occurred at a frequency of 192 Hz. The
frequency form shows that the noise level is uniform and at all times. As in the noise
levels frequency variation shows a staggered level of noise annoyance and it is high
time to attenuate the noise pollution. This staggered form reflects an oscillating nature
of noise generation. This will lead to damages in the form of vibrations and physical
damages in the form of health hazards. It is high time to evaluate an immediate measure
so that during construction operation like jack hammer and piling work noise generation
is considerably reduced.
6.10 Spectral analysis for cars of different years of manufacturing
The spectral Figure 6.7 shows that noise frequency distribution is in wave form.
The noise frequency shows a peak frequency in all ranges. The peak decibel value 80
dBA and corresponding frequency for year 2002 lies in 15 Hz, 25 Hz and 85 Hz
respectively in the year 2004 and the peak decibel level of 77 dBA lies in 25 Hz, 70 Hz,
85 Hz and 90 Hz respectively. In other years the peak value is lies in 10 to 40Hz only.
Here the car is allowed to accelerate implies the noise signal emission is due to running
of car engine alone. Frequency spectrum curve gives a pattern which tells us that the
noise generation is raising and falling. We get to know from that car engine runs like
frequency curve pattern.
104
Figure 6.7 Spectrum of cars manufactured in different years
6.11 Spectral analysis for Perungalathur railway station
The noise frequency curve shown in Figure 6.8 presents a simple comparison
curves. The spectrum is drawn and compared for open traffic, level crossing and
railway station location. The multiple peak frequency occurrences are sighted in all the
curves. The degree of frequency representation is uniform in all cases. For every 10 Hz
of frequency the decibel value is moving from higher range to lower range.
0 10 20 30 40 50 60 70 80 90 10055
60
65
70
75
80Noise Signal
Frequency(Hz)
Ma
gn
itu
de
(db
)
Year 2002
Year 2010
Year 2012
Year 2008
Year 2006
Year 2004
105
Figure 6.8 Spectrum of railway station, level crossing and outside traffic
The frequency is in cluster and in the range of 50 Hz to 80 Hz, because the
decibel value is almost like an amplitude band in the range of 47 dBA to 57 dBA at
railway station location, 88 dBA to 92 dBA at level crossing and open traffic stream
location.The random signal variation representing spectrum analysis shows that the
frequency is in the range of 20 Hz to 40 Hz with a decibel level of 53 dBA to 74 dBA.
The peak frequency of 85 Hz occurred at a sound intensity of 80 dBA. This shows that
usually LFN also has frequency distribution for both open traffic and level crossing
locations.
6.12 Spectral analysis for flour mills and traffic stream
The noise frequency curves have shown in Figure 6.9 and Figure 6.10 displays
spectra. Figure 6.9 is a simple multiple level curve representing flour mills operation
alone. Multiple frequency spectra are observed and there are a series of peak noise
decibel levels. The different peaks represent the noise levels are not uniform. The peak
decibel level 94 dBA in rice and seekakai operation is having a frequency of 92 Hz and
22 Hz, respectively.
0 10 20 30 40 50 60 70 80 90 10040
50
60
70
80
90
100
110Noise Signal
Frequency(Hz)
Ma
gn
itu
de
(db
)
Out side railway station (traffic stream)
Level crossing
Railway station
106
Whereas with the same frequency the noise level in mirchi operation is 114 dBA. The
noise signal is then compared with traffic stream of noise generation. The flour mills
are subjected to severe effect of the peoples living in the surrounding places. The flour
mills are located near residential localities.
Figure 6.9 Spectrum of flour mills
Figure 6.10 Spectrum of flour mills and open traffic
0 10 20 30 40 50 60 70 80 90 10085
90
95
100
105
110
115Noise Signal
Frequency(Hz)
Ma
gn
itu
de
(db
)
Mirchi
Rice
Seeyakai
0 10 20 30 40 50 60 70 80 90 10040
50
60
70
80
90
100
110
120Noise Signal
Frequency(Hz)
Ma
gn
itu
de
(db
)
OMR
KPR
MIRCHI
SEEY AKAI
RICE
107
The traffic which is severe along the highway also thrust severe noise impact on
people using the highway. This instance is shown as a spectral frequency curve in
Figure 6.10. For every 10 Hz of frequency the decibel value is moving from higher
range to lower range. The frequency curve is not uniform for the KPR, where as OMR
traffic curve is segmental curve in representing the noise signal level.
The multiple peaks representation of decibel levels corresponding to the
frequency shows vehicles are more in OMR where as it is less in KPR. The peak
decibel level is 69 dBA in KPR and is having 42 Hz as frequency, where as the peak
level of 84 dBA happens in different frequencies. The band width formation of about 10
dBA from 60 dBA to 70 dBA is occurred in OMR traffic stream for a frequency 10 Hz
to 75 Hz.
This shows that the noise level is uniform throughout the time. When compared
to the noise signal from traffic stream the flour mill operation the frequency spectrum is
showing a uniform decibel level. The noise levels are uniform though out the operation
and the peak variance of noise levels are at every frequency intervals.
The human interface is subjected to severity on the uniform rate of noise signal
emission. The frequency represents a non periodic form which is explicit in flourmills
operation than the traffic stream. This is also another indicator for noise levels present
throughout the time of operation. This shows that usually low frequency noise also has
frequency distribution.
6.13 Spectral analysis for noise reduction barriers
The barriers considered are three types, namely thatched shed barrier, normal
concrete cubicle barrier and CSP concrete barrier, and fly ash bricks barrier. The noise
levels recorded allowed consideration for producing frequency distribution as spectrum
analysis. The results are shown in three different Figures 6.11, Figure 6.12, and Figure
6.13, respectively.
108
Figure 6.11 Spectrum of thatched shed to attenuate noise
Figure 6.12 Spectrum of cubicles made of concrete cubes
0 10 20 30 40 50 60 70 80 90 10045
50
55
60
65
70
75
80
85
90Noise Signal
Frequency(Hz)
Ma
gn
itu
de
(db
)
Open stream with out barrier
Tatched leaves as barrier first layer
Tatched leaves as barrier second layer
0 10 20 30 40 50 60 70 80 90 10045
50
55
60
65
70
75
80
85
90Noise Signal
Frequency(Hz)
Ma
gn
itu
de
(db
)
With enclosure (CSP)
With enclosure (normal)
With out enclosure
109
Figure 6.13 Spectrum of cubicles made of fly ash bricks
Noise attenuation can be achieved by different ways of providing a noise control
measure. Here, noise attenuation was achieved by providing a barrier form of noise
control measure. The barrier is made of thatched leaves which are porous material. A
shed was constructed like structure where noise levels are recorded inside the shed.
The thatched leaves were stacked by first layer and second layer, noise levels
were recorded in the case of both layers. The noise levels recorded were compared with
the noise levels recorded at outside the shed to indicate the noise attenuation. The noise
levels recorded were analyzed for spectrum to arrive noise reduction spectrum. Figure
6.11 to Figure 6.13 show spectral analysis and frequency spectrum for all the cases.
While observing the frequency spectrum of the noise signal it is found that there are
multiple peaks around every 10 Hz over the frequency range from 0 to 100 Hz.
The three different frequency spectrums drawn for noise levels show the
following observations. The second layer of thatched leaves shows that lowest noise
level of 48 dBA at a frequency of 75 Hz and 85 Hz. Whereas the frequency of noise
recorded without barrier is 15 Hz for a lowest noise level of 55 dBA. Same way the
0 10 20 30 40 50 60 70 80 90 10040
50
60
70
80
90
100Noise Signal
Frequency(Hz)
Ma
gn
itu
de
(db
)
With fly ash cubicles as barrier
Present data (2013)-open stream
Past data (2012) - open stream
110
peak noise level of 76 dBA for second layer thatched leaves shows a frequency of 21
Hz, frequency of open stream is 75 Hz for the maximum noise level of 88 dBA.
This way the representation of multiple frequency distributions existed for each
frequency value. This staggered form reflects that a noise level is not uniform and at
times peak to its range. In the second layer of thatched leaves shed most of the decibel
values falls between 18 Hz to 82 Hz for a decibel value range of 53 dBA to 61 dBA.
The open stream between the decibel levels of 70 dBA to 80 dBA the frequency 0 to 70
Hz. Cluster of multiple peak show the maximum noise levels existed at all time of
traffic stream in open traffic and also on attenuating barrier. The noise attenuation refers
to noise having different frequency shows noise waves spread through time factors.
Similar way of representation was observed for both the concrete cubicles
shown in Figure 6.12 and for fly ash type of barriers in Figure 6.13. All in the entire
spectrum indicates that noise attenuation is possible by providing barriers. The noise
reducing capability of the barriers is associated with the type as well as its material
properties. Consequently it is presumed that noise reduction associated with frequency
distribution of noise levels existed.
The low frequency noise problems could occur anywhere in the range 10 – 150
Hz but were usually associated with noise in the range of 40 – 60 Hz. The commonest
cause of such noise is industry but there can be many other causes, some of them
domestic (refrigerators, oil-fired boilers, and washing machines) and some associated
with road vehicles.
Sometimes low frequency noise seems more like vibration than noise and it can cause
structural vibration.
It has also been postulated that non-acoustic sources such as high intensity
electromagnetic fields or radar microwaves may create for some people the illusion of
LFN. It will be apparent that LFN presents particular problems for those who have to
deal with complaints about it. It is in any case likely that the business of identifying the
source of LFN will be laborious and may not always be conclusive (Noise Programme
Department of the Environment, Northern Ireland 2001).
111
It is accepted that this problem, though it generates comparatively few
complaints, is a real one. Much remains to be done to extend the understanding of the
nature of LFN and how best to detect and deal with it.
Let the spectrum analysis be catagorized with a simple statement stating the
frequency range with decibel range. The table in Annexure II shows the different
sources of noises, noise levels range and respective frequency in 10 to 40 Hz, 41 to 70
Hz and 71 to 100 Hz.
It is observed that each noise source has its own range of frequency representation.
• The open traffic stream has decibel level of around 51 dBA to 77 dBA around
10 Hz to 100 Hz. This significantly shows that noise levels are predominant at
all times of the survey.
• Tambaram subway shows a different structure when compared to open traffic
stream. The observations are inside the subway and the noise levels are uniform
where it is in the range of 55 dBA to 75 dBA in the respective frequency range.
Whereas outside the subway between 10 Hz to 40 Hz category the noise levels
are 60 dBA – 84 dBA. In the other frequency range the noise levels falls in 69
dBA to 84 dBA. This shows that noise levels are on most of the time higher than
69 dBA.
• Construction operation shows a different range of frequency distribution.
Multiple peak levels show that all activities considered are showing the
maximum to minimum decibel levels in all frequency range. The decibel levels
of jack hammer operation, marble cutting, piling, mixer machine and vibrator
show a peak levels as 127 dBA, 100 dBA, 113 dBA, 97 dBA and 81 dBA
respectively, which are peak levels in all frequency distribution. This shows that
noise levels are not incidental or sudden and the signal presence is always
emitted through each operation of work.
• Four mills generate severe noise effect due to its geographical location. These
mills are operated near the vicinity of people and residential localities. There are
minor variations with respect to maximum value to minimum value in decibel
112
levels. The frequency distribution shows that noise levels are at constant rate
and the dissipation of noise is throughout.
• Barrier provision shows a frequency distribution in a different manner. Multiple
peaks of noise decibel levels are reflected in each category of frequency range
between 41 to 70 Hz. As LFN usually falls in this range, the attenuating barriers
are representing this type of noise levels in the frequency range. Also, open
stream of traffic is severe in all cases of barrier installed places.
The examples show a relationship between the waveform of a signal from noise
levels in the time domain compared to its spectrum in the frequency domain. Most
natural sound signals are complex in shape. The primary result of a frequency analysis
is to show that the signal is composed of a number of discrete frequencies at individual
levels present simultaneously. The number of discrete frequencies displayed is a
function of the accuracy of the frequency analysis which normally can be defined by the
user. This observation together with frequency masking - limitations in the capability of
ears to discriminate closely spaced frequencies at low sound levels in the presence of
higher sounds - is the foundation for the calculation of the loudness of stationary
signals. Loudness of non-stationary signals also needs to take the temporal masking of
the human perception into account.
A suitable experimental analysis for investigating problems in measuring the noise
pollution generated by noise generating sources by using a traditional sound observer
spectrum analysis was presented. Due to the pulsed and noise-like behavior of the
observed signals show LFN existed and serious attenuating measure has to be carried at
the earliest to attenuate noise levels. Most frequency spectra of exterior tyre/road noise
display a prominent peak in the range of 40 to 70 Hz. This research identifies and
examines this peak, analyses its causes and suggests some noise reduction possibilities
through attenuating barriers.
Noise spectra composed of a mix of different sources of noise having a clear
dominance range of 40 to 70 Hz. From this fact, one might be tempted to speculate that
the peak is due to the oscillatory pattern of noise geometry and resulting impact
frequencies. But this could at most be only a partial reason, since the peak frequency
113
relation between different sources of noise generation is the same also for pattern less
type of noise generators.
Having analyzed plenty of data from wave files recorded at selected locations under
different traffic conditions it was observed that the noise power is higher at lower
frequencies in most of the cases and as one goes to higher frequencies, the noise power
rapidly falls down. Later a stage is reached where the noise power is found to be more
or less same with random fluctuations.
6.14 Power Spectrum
Power spectrum estimation can be defined as the method of finding power
values of hidden frequency components in the harmonics of a measured noisy signal,
and is a highly recommended problem in practice. Many applications in engineering
and biomedicine ranging from synthetic aperture radar for image analysis, radar for
determining range of a target, sonar for positioning, speech recognition, heart rate
variability analysis, time series analysis in seismology etc., can be recognized as
spectrum estimation problems. Non parametric power spectrum estimation methods do
not assume any rational functional form but allow the form of estimator to be
determined entirely by the data. Consequently, many methods have been proposed and
developed achieving the spectrum estimation. Some of these methods are called
classical methods and others are called modern methods from national semiconductor
instruments (National 1980).
6.14.1 Power Spectral Density (PSD)
The PSD is the magnitude of the spectrum normalized to a 1 Hz bandwidth.
This measurement approximates what the spectrum would look like if each frequency
component were really a 1 Hz wide piece of the spectrum at each frequency bin. PSD
means when measuring broadband signals (such as noise) amplitude of the spectrum
changes with the frequency span. This is because the line width changes, so the
frequency bins have a different noise bandwidth. The PSD, on the other hand,
normalizes all measurements to a 1 Hz bandwidth, and the noise spectrum becomes
114
independent of the span. This allows measurements with different spans to be
compared. If the noise is Gaussian in nature, the amount of noise amplitude in other
bandwidths may be approximated by scaling the PSD measurement by the square root
of the band width. Thus, the PSD is displayed in units of V/√Hz or dBV/√Hz. Since the
PSD uses the magnitude of the spectrum, the PSD is a real quantity. There is no real or
imaginary part, or phase.
Power Spectral Density (PSD) is the frequency response of a random or periodic signal.
It tells us where the average power is distributed as a function of frequency.
The PSD of a random time signal x(t) can be expressed in one of two ways that are
equivalent to each other
1. The PSD is the average of the Fourier transform magnitude squared, over a large
time interval
====−−−−
−−−−∞∞∞∞→→→→ ∫∫∫∫2
2
2
1dtetx
TEfS ftj
T
TTx
ππππ)(lim)(
2. The PSD is the Fourier transform of the auto-correlation function.
dteRfS
ftjT
Txx
ππππττττ2−−−−
−−−−∫∫∫∫==== )()(
{{{{ }}}})(*)()( ττττττττ ++++==== txtxERx
• The power can be calculated from a random signal over a given band of
frequencies as follows:
1. Total Power in x(t): ∫∫∫∫∞∞∞∞
∞∞∞∞−−−−
======== )()( 0xx RdffSP
2. Power in x(t) in range f1 - f2: ∫∫∫∫ ========
2
112 0
f
fxx RdffSP )()(
The PSD for each signal looks more or less flat across the frequency band.
This type of noise is referred to as white, and if one had taken an infinitesimally small
115
time increment, he/she would see this flatness across the entire frequency band as per
stand for research systems (Stanford 2014).
The reason that there is some variation about the constant level is that one
didn’t take a large enough (i.e., infinite) time sequence of random numbers to calculate
the PSD from. The estimate of the PSD (as calculated in MATLAB) becomes more
accurate as the sample size becomes infinite.
6.14.2 Energy and Power
The total energy in a signal f(t) is equal to the area under the square of the
magnitude of its Fourier transform łF(f)ł2 is typically called the energy density, spectral
density, or power spectral density function and łF(f)ł2 df describes the density of signal
energy contained in the differential frequency band from f to f ± df. In many electrical
engineering applications, the instantaneous signal power is desired and is generally
assumed to be equal to the square of the signal amplitudes i.e., f2(t). Having established
the definitions of this section, energy can now be expressed in terms of power, P(t),
with power being the time rate of change of energy As a final clarifying note, again,
łF(f)ł2 and P(t), as used in equations (1) and (2), are commonly called energy density,
spectral density, or power spectral density functions, PSD. Further, PSD may be
interpreted as the average power associated with a bandwidth of one Hertz centered at f
Hertz.
Here this research estimated the power spectral density of a wide sense
stationary random signal with available low frequency noise signal. The resulting
signals from one after another are processed using MATLAB after the signal data are
processed for FFT analyser. The performance of finding the power spectrum is tested
on different sets of noise signal like traffic stream, flour mills, constructions noise and
barrier type of structures the results are presented in individual cases.
Figures 6.14 to 6.22 show the power spectrum of noise levels recorded for the
different sources. It displays the energy dissipation levels in different forms. Also the
dependence of time is noticed in measuring the noise levels.
116
Figure 6.14 Power spectrum for traffic stream
Figure 6.15 Power spectrum for Kolapakkam Porur Road
0 10 20 30 40 50 60 70 80 90 1002782
2784
2786
2788
2790
2792
2794
2796
2798Spectral density with Random Noise
Frequency (Hz)
Po
we
r in
wa
tt/H
z
traffic at OMR
0 10 20 30 40 50 60 70 80 90 100566
568
570
572
574
576
578Spectral density with Random Noise
Frequency (Hz)
Porur Kolapakkam Road
117
0 10 20 30 40 50 60 70 80 90 1001120
1122
1124
1126
1128
1130
1132
1134
Figure 6.16 Power spectrum for jack hammer
Figure 6.17 Power spectrum for flour mill – mirchi
0 10 20 30 40 50 60 70 80 90 1002124
2126
2128
2130
2132
2134
2136
2138Spectral density with Random Noise
Frequency (Hz)
Po
we
r w
att
/Hz
118
0 10 20 30 40 50 60 70 80 901374
1376
1378
1580
1382
1384
1386
1388Spectral density with Random Noise
Frequency (Hz)
Power in watt/Hz
Figure 6.18 Power spectrum for perungalathur level crossing
Figure 6.19 Power spectrum for Perungalathur railway station
0 10 20 30 40 50 60 70 80 90 1001576
1577
1578
1579
1580
1581
1582
1583
1584
1585
119
Figure 6.20 Power spectrum for thatched shed second layer
Figure 6.21 Power spectrum for concrete cubicles
Figure 6.22 Power spectrum for fly ash cubicles
0 10 20 30 40 50 60 70 80 90 100348
350
352
354
356
358
360
362Spectrdom Noise
Frequency (Hz)
pow
er
in w
att
/Hz
Tatched shed second layer
0 10 20 30 40 50 60 70 80 90 100362
364
366
368
370
372
374
Frequency (Hz)
Pow
er
watt
/Hz
fly ash bricks cubicles
0 10 20 30 40 50 60 70 80 90 100319
321
323
325Spectral density with Random
Frequency (Hz)
power watt/Hz
120
Power spectrum characterizes the signal’s energy distribution in the frequency
domain, and can answer most of the power of the signal resides at low or high
frequencies. By performing power spectral analysis some important features of signals
were discovered that are not obvious in the time waveform of the signal. Here, the wave
forms are sinusoidal and at times as a band width form. The noise signals are random
the energy representations varies with different sources. The power is distributed over a
time period exhibits a non linearity of the noise present. If traffic noise at two locations
like OMR and KPR is consider the difference in energy levels could be found which is
displayed in Figure 6.14 and 6.15. Similar form of representations is identified for
other locations. Figure 6.20, Figure 6.21 and Figure 6.22 show the spectrum for noise
attenuating barriers. When we compare with open stream of traffic shown in Figure
6.14 at each 10 Hz frequency the power level is not uniform. There is wave form in
open traffic from peak to normal during short level of frequency. Whereas in the battier
types the variance is like a band with at a selected power level. In the case of
comparison of machinery if noise from jack hammer and flour mills were considered as
presented in Figure 6.16 and Figure 6.17 similar pattern of power representation is
observed.
The periodic spike signal like in Figure 6.17 and Figure 6.18 produces periodic
peaks, called harmonics, on PSD although the spikes in the time series occur at a fixed
interval. Here, this type of signals is found in other figure too. This reflects that data
were contaminated by sparks caused by some kind of rotational machinery such as a
motor. The combined presentation of frequency and the energy output is presented in
Table 6.4
Power spectral density function (PSD) shows the strength of the variations
(energy) as a function of frequency. In other words, it shows at which frequencies
variations are strong and at which frequencies variations are weak with respect to the
noise source and time domain.
Power spectrum density analysis with a simple way of presented in Table 6.4
shows the different sources of noises, frequency in 10 to 40 Hz, 41 to 70 Hz and 71 to
100 Hz and power in the respective ranges.
121
Table 6.4 Frequency range and corresponding energy range
Frequency range in Hz
Location Energy range watts / Hz
10 to 40
Traffic stream
OMR 2792-2785 41 to 70
71 to 100
10 to 40
KPR
569-577
41 to 70 566-576
71 to 100 567-576
10 to 40
Perunglalathur raliway station
and level crossing
Railway station
1376-1381 41 to 70 71 to 100 10 to 40
Level crossing
1577-1584 41 to 70 1577-1582 71 to 100 1577-1582
10 to 100 Flour mill Mirchi 1123-1129
10 to 100 Construction
operation Jack
hammer 2127-2135
10 to 40 Thatched
shed barrier Second layer
353-357 41 to 70 352-358 71 to 100 352-359
10 to 100 Concrete Barrier
cubicles Normal concrete
321-323
10 to 40 Fly ash brick
barrier cubicles Fly ash bricks
352‐357
41 to 70 352‐358
71 to 100 352‐354
It is observed that each noise source has its own range of power spectrum emission.
• The open traffic stream at OMR has decibel level of around 51 dBA to 77 dBA
around 10 Hz to 100 Hz and energy level of around 2792 to 2785 watt/HZ.
Where as in the KPR it is on the 569-576. This show the sound energy emission
is significant level and the volume of vehicles contribute to the excessive level
of difference in frequencies.
• Construction operation of jack hammer and flour mill operation were considered
for power spectrum density and the Table 6.4 shows the following observations.
The noise levels are 93 dBA to 127 dBA for 10 Hz to 200 Hz and energy level
of around 2127 to 2135 Watt/Hz for jack hammer where as for flourmill
operation like mirchi show 105 dBA to 115 dBA, 10 Hz to 100 Hz and 1123 Hz
122
to 1127 Watt/Hz, respectively. The multiple distribution on the power spectrum
figure show that the variance with respect to machinery is more than the
reduction of noise levels.
• Railway station location and the level crossing location show an equal
distribution of energy like 1376 Hz to 1381 Hz and 1571 Watt/Hz to 1583
Watt/Hz, respectively.
• Barrier provision shows a power distribution in a different manner. All the
barriers are of equal power level of 321 Watt/Hz to 357 Watt/Hz. This power is
similar to all frequency range of 10 Hz to 100 Hz.
• Usually low frequency noise does not damage structures. However LFN with
high energy as indicated in Table 6.4 may become detrimental to structures.
Consider the situation, suppose if one is standing on the passenger-loading platform of
the commuter railway line. As the commuter train approaches the station, it gradually
slows down and the train leaves the station it will move in a designated speed. During
this process of slowing down and speeding up the operating engineer sounds the horn at
a constant frequency with a definite pitch he/she will perceive the sound propagation
through waves. The same can be from any source of noise because the signal
transmission through waves to the affected persons. This phenomenon is called Doppler
Effect where source of waves is moving with respect to an observer. Sometimes these
excessive waves create shock wave where the source of waves travelling in high speed.
The distance between the waves goes to zero and so the frequency becomes very high.
More importantly, all of the energy gets concentrated into a very small distance – this is
called a shock wave. In this case, the observer does not hear the approaching source at
all until the shock wave hits with all of the energy in the wave. For sound waves, this
can cause a very loud noise, called a sonic boom. Any time a source exceeds the speed
of the wave, a shock wave will be formed.
Let us consider the following news item in the print media.
A portion of the false ceiling near the first floor check-in counters at the new domestic
terminal of Chennai airport collapsed in the wee hours of Sunday. In the fourth such
incident in the airport in Chennai since last month, a portion of false ceiling collapsed at
the old Anna International terminal on Wednesday. About ten panels of the false ceiling
123
near bay number 28 came crashing down around 3.30 am. However, none was injured
in the incident, airport sources said. A statement from Airport Authority of India said
the slabs measuring 2 feet × 2 feet fell in the international arrival area, which is due for
renovation. “At the time of the incident there was no movement of passengers and the
place was cleaned in an hour,” it said. The airport has been witnessing a spate of
mishaps such as false ceiling falling and glass panels cracking at its new domestic and
international terminals, built at a cost of over Rs. 2,000 crores and raising questions
about the quality of the construction. Since March 31 alone, three incidents of collapse
of granite slabs and glass panels had been reported at the new terminals (Staff Reporter
2014). The above incident reflects a sonic boom is creating in the airport terminal areas
where the excessive sound wave propagates with respect to the noise intensity. Also the
LFN is prevailing due to speeding of aircrafts rather than taking off or landing. The
serious of incident reflects that the incidents are to be addressed. This condition is now
prevailing at the current study where we can say that the noise levels are about more
than 100 dBA to 125 dBA at flourmills and traffic places on OMR. It reveals that here
the LFN about 40 Hz to 60 Hz generates equal amount of energy formation.
This research began looking more closely at the composition of generating sonic booms
including the LFN content. Sound waves influence sonic boom how loud and irritating
it can be perceived by listeners on the ground. Table 6.5 indicates the maximum energy concentration to respective frequency
level for each source of noise. The volume of traffic, noise level at OMR is severe and
noise intensity is about 104 dBA (max level) that shows that the max energy output is
about 2794 Watt/Hz for a frequency of 69 Hz. Correspondingly, the less traffic place
like KPR show a 577 Watt/Hz with a frequency of 40 Hz.
124
Table 6.5 Max energy and corresponding frequency range
Similarly, if noise intensity and the energy output were compared a trend is
observed that if the noise level is lower there is a possibility of energy dissipation on
LFN. This may lead to a source for vibration which includes construction and
excavation equipment, rail and road traffic, and industrial machinery. Low-frequency,
airborne pressure waves are emitted by some heavy vehicles, aircraft and machinery
.This phenomenon can also cause vibration in buildings. Some vibration sources give
rise to audible effects such as structure-borne noise and secondary rattling of building
elements or contents. Yes, high frequency sound waves do possess more energy.
However, that doesn't mean that their vibrations can be felt. Lower frequency sound
waves (at the very bottom of the human hearing range) produce vibrations that can be
felt. The amount of energy in a wave is related to its amplitude. Large-amplitude
earthquakes produce large ground displacements, as seen. Loud sounds have higher
pressure amplitudes and come from larger-amplitude source vibrations than soft sounds.
Max Energy in Watts / Hz
Location Corresponding Frequency in Hz
2794 Traffic stream
OMR 69
577 KPR 40
1583 Perunglalathur railway station and level crossing
Railway station
74
1384 Level crossing
32
1131 Flour mill Mirchi 68
2135 Construction operation
Jack hammer
69
361 Thatched shed barrier
Second layer
32
324 Concrete Barrier cubicles
Normal concrete
68
372 Fly ash brick barrier cubicles
Fly ash bricks
51
125
CHAPTER 7
CONCLUSIONS
From the research carried out in this thesis the following conclusions are drawn.
Knowingly or unknowingly everyone contributes to noise pollution, because
most of the day-to-day activities of human beings generate some noise. Often neglected,
noise pollution adversely affects the human being leading to irritation, loss of
concentration, loss of hearing.
• One has to identify the sources of noise pollution. Once identified, the
reason(s) for increased noise levels are to be assessed.
• It is generally found that the people feel much pain in their ears and
migraine during duty hours as well as after duty hours due to increase in
noise level.
• The findings of this study also indicated that the high density residential
area like OMR is affected by noise pollution.
• Indeed some control measures and proper planning has to be
implemented to overcome the adverse effects from noise pollution and
for the well being of the residents.
• This thesis explores the sources, effects, reactions and suggestions for
controlling the excessive noise generated from road traffic.
• Exposure to noise pollution exceeding 75 decibels for more than eight
hours daily for a long period of time can cause health hazards.
• The traffic noise recorded in open traffic stream at Chennai at two
sensitive places was not below 44 dBA and 105 dBA.
• Survey conducted for different sources of noises show noise pollution
existed. At all sources noise levels are higher than the standards
prescribed by MoEF guidelines.
126
• Pedestrians are severely affected both inside and outside the subway.
Noise decibel levels are 30 dBA more than the MoEF standards. This
reflects how the people who are using road way affected by the severity
of noise
• A comprehensive measure is immediately required and a measure to
attenuate noise is tested and it has proved that noise can be reduced in
Indian condition.
• City like Chennai where construction activities are in brisk phase here
certain operations of machinery show that noise levels are high
• Machinery like jack hammer and marble cutting show a 23 dBA higher
noise levels than standards. There is marginal increase in level due to
piling and running of mixer machine.
• As construction activity is now getting advanced, one needs to consider
different noise standards for different equipments. There are now limited
equipments standards.
• Open traffic stream shows that vehicle contributes less noise levels. The
principle contributor car has been identified as a guide to evaluate noise
levels.
• Different years manufacturing of cars were considered and show that
there is noise level reduction of about 20 dBA from year 2002 to 2012.
This reflects age of the vehicles contribute to noise pollution.
• Railway stations are less prone for noise levels. Noise levels recorded
show a value of 63 dBA even though the station is partly congested one
and passengers are frequently using this station. The nearby area like
level crossing and open traffic show a decibel level of 97 dBA which is
42 dBA more than the standards.
• The need for noise pollution assessment in some flour mills is
demonstrated in this study. The physical measurement reveals that the
noise level status in the three operations of flour machinery is far above
the MoEF guidelines. Thus, the noise pollution level is having impact on
the flour mill employees as well as the public who are residing nearby
the mills and also who uses the mills for flouring.
127
• Flour mills have peoples interference, open traffic are also prone for the
same. The study compared these two aspects and had shown, if less
number of vehicles are operated then noise levels will be considerably
reduced.
• Survey conducted in Kolapakkan-Porur road reflects that noise levels 47
dBA where as OMR noise levels are 80.43 dBA and flourmills show a
noise levels of above 92 dBA.
• There is a need to create awareness among the people and educate the
citizens about the rising noise pollution, health effects, etc.
The excessive noise could cause hearing impairment while this social survey
revealed the level of social and health menace caused by the presence of these mills to
the employees and the people residing in these environments.
The most cost effective measure to reduce noise annoyance is to reduce the
vehicle noise. It has cost measure to reduce noise. Particularly, city like Chennai where
the traffic is more and the use of private transportation becomes higher. The regulatory
measures are minimal and it is high time to focus on alternate measure to reduce noise
pollution. The most suitable non- expensive measure is providing noise barriers.
It has been proved that by providing noise barrier such as thatched leaves, fly
ash brick barriers, noise attenuation of about 3% to 10% was achieved. Where as if
barriers like concrete are provided the noise attenuation can be of about 20%. The noise
barriers are, however, as distinct from façade insulation, also helps to reduce noise in
the outdoor areas.
Presently, this study gives three different noise barriers namely thatched leaves
shed, fly ash (a pollutant) bricks and concrete barrier in form of enclosures. There are
advantages and disadvantages on each barrier nevertheless all attenuate noise to some
extent. Sometimes a severe noise reduction is required, and local measures are the only
alternative.
Such measures are of importance for adapting to local needs like provision of
thatched leaves and sensitive locations where heavier noise recorded may opt for
concrete made of normal concrete or CSP (a pollutant) concrete which will always be of
great importance when helping those exposed to the highest noise levels. CSP concrete
gives equal attenuation that of normal concrete, this proves that low cost barriers are
128
also can be provided. The waste material is recycled to use as a partial binder to get
equal strength that of normal concrete.
The recognition of road traffic noise as one of the main sources of
environmental pollution led to design models that enable one to predict traffic noise
level, to be used as aids for designing roads, change in traffic pattern and highways
planning. In this study a statistical modeling approach has been used for predicting road
traffic noise in Chennai road conditions.
The data sets consisted of more than 3000 measurements on a single day and at
two locations along OMR were considered. The entire data set was utilized to develop a
new model for Chennai traffic condition to predict noise and to be used as a tool for
further prediction. Thus this research suggests the prediction value is ±2% dBA value
accuracy for the developed Leq model.
The individual ear, for the common of people, is not aware at low frequencies.
At low levels of noise, the creature ear attenuates sound by about 25 dB at 100 Hz, 40
dB at 50 Hz and 70 dB at 20 Hz
At upper levels, the effect is not so striking with the attenuation being about 5
dB. This means that frequencies in the region of 20 Hz may not be audible unless the
level exceeds about 70 dB. The A-weighting network found on most sound level meters
is intended to reflect this response.
This study presents LFN for all the noise source considered and an assessment
of urban noise frequency spectrum were drawn using MATLAB software. The results
show multiple peak noise levels variance in every 10 Hz of frequency intervals. Noise
levels were severe and show maximum to minimum in the frequency range of 40 Hz to
70 Hz. Spectra were drawn for all the cases of noise generation.
It has been proposed to estimate PSD for a wide range of stationary random
signals with available low frequency noise. A modified design of algorithm is based on
FFT analysis using MATLAB. The power spectral density simulation results show that
the improved spectral estimation accuracy and shifting of frequency peaks towards the
low frequency region.
The simulation results present a good argument with the published work. In all
cases, the contribution of noise source generated creates waves in the vicinity of the
source. The PSD results obtained indicate that in contrast to high-frequency fields, low-
129
frequency acoustic fields on opposite sides are much more closely connected than
previously believed possible.
Likely practical applications are related to the air–material interface, which occupies
about two-thirds of the surface and are seriously related to each other. The PSD value is
in the range between maximum energy level of 2794 Watts/Hz to a minimum of 324
Watts/Hz. This range spread over all the sources of noise recorded. There is a reduction
of energy in the barriers attenuating energy levels and found to be a value of 324
watts/Hz for a frequency of 51 Hz.
It is clear that LFN a fact of inconsistent transparency can occur where most of
the sound power generated by a source in a noise can be passed into a place. The
results indicate that LFN should not be ignored since there is a possibility of creation of
sonic boom which may be detrimental to the structures. The places where noise survey
was conducted were surrounded by glass facade structures, residential colonies and high
raise buildings with insulating panels, which may conduct acoustic signals through the
air interface. It is high time to evaluate the above to attenuate the noise prorogation
waves by proper mitigation measures.
Noise reduction is the most paramount problem and at any cost this nuisance has
to be reduced. Based on this consideration the thesis addresses the issue of reducing
noise along highway to suite Indian working condition. Here, investigation was carried
out by providing a noise barrier in the form of enclosure.
Knowledge gained from this research
From the study the researcher learned the presence of noise pollution in the
traffic, construction sites, flour mills, etc., and its seriousness. It needs to attenuate
noise by way of providing barriers. Further the researcher learned the effectiveness of
barriers. There are advantages and disadvantages using barrier, there are indirect
benefits of using cost effective barriers like thatched leaves. Also effective use of waste
products like CSP and fly ash show the energy dissipation is marginal in generation of
pollution. This study also tackles the twin problems of noise pollution and
environmental degradation that are created by wastes.
130
REFERENCES
Agbalagba, EO, Akpata, AKO, & Olali, SA 2013 'Investigation of Noise Pollution
Levels of Four Selected Sawmill Factories in Delta State, Nigeria' Advances in Applied
Acoustics (AIAAS), vol.2, issue 3, pp. 83-90
Al-Mutairi, N, Al-Rukaibi, F & Koushki, P 2009 'Measurements and Model Calibration
of Urban Traffic Noise Pollution' American Journal of Environmental Sciences, vol. 5,
no-5, pp. 613-617
Andy Moorhouse, David Waddington & Mags Adams 2005 ' Proposed criteria for the
assessment of low frequency noise disturbance Prepared for Defra' Acoustics Research
Centre, Salford University Project report
Avinash Chauhan & Krishnakumar Pande 2010 'Study of noise levels in different
Zones of Dehradun City', Journal of report and opinion, vol.2, issue-7, pp. 65-68
Balashanmugam, P, Ramanathan, AR, Nehrukumar, V, Balasubramaniyan, V 2013
'Assessment of Noise Pollution in Chidambaram Town', International Journal of
Research in Engineering and Technology, vol. 2, issue. 10, pp. 85 -93
Can, A, Leclercq, L, Lelong, J & Botteldooren, D 2010 'Traffic noise spectrum
analysis: dynamic modelling vs. Experimental observations' Journal of applied
acoustics, vol.71, issue 8, pp. 7645-770
Carvalhoa, APO & Oliveirab, PD, S 2010 'Model of a Benefit/cost Ratio Analysis for
Comparison of Environmental Noise Barriers' Proceedings of NOISE CON 2010,
Baltimore, Maryland, Laboratory of Acoustics, FEUP - Faculty of Engineering
University of Porto, 4200-465 Porto, Portugal
Choudri, VP., Deepak and Ramesh, C., 2011, 'Assesment and control of sawmill
noise,' Proc. International Conference on Chemical and Biological Environmental
Sciences, Bangkok pp 299-303
Christoph Rauscher 2001 'Fundamentals of Spectrum Analysis' Rohde & Schwarz
GmbH & Co. Press, KG Germany edition, Germany
Colin, H, Hansen, Berenice, I & Goelzer, F 2010 'Engineering noise control' World
Health Organization, University of Adelaide, South Australia 5005,
AUSTRALIA,Chapter10 pp. 1-52
Dasarathy, AK & Thandavamoorthy, TS 2013a 'Noise Pollution in Chennai - A Case
Study', Asia Pacific Journal of Research, vol. 1, issue. XI, pp. 143-148
131
Dasarathy, AK & Thandavamoorthy, TS 2013b 'Attenuation of noise using barrier in
the form of enclosures', Journal of Applied Research, vol. 3, issue. 8, pp. 83-89
Datta, JK, Sadhu, S, Gupta, S, Saha, R, Mondal, NK & Mukhopadhyay, B 2006 'Noise
pollution in Burdwan town & its impact', Journal of Environmental Biology, vol. 27,
pp.609-612
Dinesh Kumar, R, Mathivanan, V, Ponmaran, P & Pradeepraj, V 2012 'A Case Study of
Traffic Noise in and around Melmaruvathur', A Project Report, Anna University
Elancheliyan Sellappan & Krishnakumar Janakiraman 2014 'Environmental noise from
construction site power systems and its mitigation', Journal of Noise & Vibration
Worldwide, pp. 14 to 22
Fan Dan-Qun, Liu Ke & Chen Qian 1989 'Prediction and Evaluation of Pollution of
Urban Traffic Noise in China', Science in China Series A, vol. 32, No. 1, pp. 93-100
Fernando, A, N & Castro Pinto 2010 'Urban Noise Pollution Assessment Techniques,
Methods and Techniques in Urban Engineering', Armando Carlos de Pina Filho and
Aloisio Carlos de Pina (Ed.), 96-4, InTech, available from:http://www.intechopen.com
/books/methods-and-techniques-in- urban engineering / urban-noise-pollution-
assessment- techniques
Gilchrist, A, Allouche, EN & Cowan, N 2003 'Prediction and mitigation of construction
noise in an urban environment', Canadian Journal of Civil Engineering, vol. 30, pp.
659–672
Golmohammadi, R, Abbaspour, M, Nassiri, P & and Mahjub, H 2007 'Road Traffic
Noise Model', Journal of Environmental Health Science and Engineering, vol. 7, No. 1,
pp. 13-17
Golmohammadi, R, Abbaspour, M, Nassiri, P & and Mahjub, H 2009 'A Compact
Model For Predicting Road Traffic Noise', Journal of Environmental Health Science
and Engineering, vol. 6, No. 3, pp. 181-186
Heng Li, Zhen Chen, Conrad TC, Wong & Peter, E, D, Love 2000 'A quantitative
approach to construction pollution control based on resource levelling', Journal of
Construction Engineering and Management. ASCE, vol. 126(4), pp. 320-324
Ingunn Milford, Sigve, J, Aasebo & Kjell Strommer 2012 'Value of money in road
traffic noise abatement' Procedia Social and Behavioral Sciences, online on
www.sciencedirect.com.
132
Jadaan, K, Al-Dakhlallah, A (Tomah), Goussous, J & Gammoh, H 2013 'Evaluation
and Mitigation of Road Traffic Noise in Amman, Jordan', Journal of Traffic and
Logistics Engineering, vol. 1, no. 1, pp. 51-53
Ken Kaneuchi & Koichi Nishimura 2011 'Noise Prediction Simulation And Noise
Reduction Technology At Low-Frequencies' Proceedings of International Gas Union
Research Conference, Japan, pp. 1-12
Khursheed Ahmed Wani & Jaiswal, YK 2010 'Assessment of noise Pollution in
Gwalior M.P., India', Journal of Advances in Bio Research, vol. 1, pp. 54-60
Mangalekar, SB, Jadhav, AS & Raut, PD 2012 'Study of Noise Pollution in Kolhapur
City, Maharashtra, India', Universal Journal of Environmental Research and
Technology, vol. 2, issue. 1, pp. 65-69
Marcos, D, Fernandez, Samuel Quintana, Jose A. Ballesteros & Noelia Chavarria 2010
'Are workers in the construction sector overexposed to noise', Journal of Noise &
Vibration Worldwide, pp. 11-15
Mohammad Hassan Ehrampoush, Gholam Hossein Halwani, Abolfazl Barkhordarl &
Mohsen Zare 2012 'Noise pollution in urban environments a study in YAZD city',
Pollution Journal of Environmental Studies, vol. 21, pp. 1015-1100
NarendraSingh & Davar,S,C 2004 'Noise Pollution – Sources, Effects and Control',
Journal of Human Ecology, vol. 6, issue. 3, pp. 181-187
Peter Karantonis, Tracy Gowen & Mathew Simon 2010 'Further Comparison of Traffic
Noise Predictions Using the CadnaA and SoundPLAN Noise Prediction Models',
Proceedings of 20th International Congress on Acoustics, ICA 2010, Sydney, pp. 23-27
Pratapkumar Padhy & Bijaya Kumar Padhi 2006 'Assessments of noise quality in
Bolpur and Santiniketan areas -India', Journal of Environmental Research and
Development, vol. 3, no. 1, pp. 301-306
Qais Banihani & Khair Jadaan 2012 'Assessment of Road Traffic Noise Pollution at
Selected Sites in Amman, Jordan: Magnitude, Control and Impact on the Community',
Jordan Journal of Civil Engineering, vol. 6, no. 2, pp. 267-278
Sagartzazua, X, Hervellab, L & Pagaldaya, JM 2012 'Review in Sound Absorbing
Materials', Arrasate-Mondragón Spain Inc. Publications, Spain
Sanjeeb Mohapathra, Mrityunjay Basankopp & Shrihari, S 2012 'Public Reception And
Response To Traffic Noise Induced Annoyance: A Case Study At Mangalore, India',
Nitk Research Bulletin, vol. 21, no. 2, pp. 39-50
133
Saxena, SC 1989 'A Course in Traffic Planning and Design', first edn. V, Nemichand
and Bros., Roorkee
Sooriyaarachchi, RT & Sonnadara, DUJ 2008 'Modelling Free Flowing Vehicular
Traffic Noise', Journal of Institution of Engineers, vol. 40, no. 2, pp. 43-47
Sumiani Yusoff 1997 'Study on Characteristics of Transportation Noise Sources in
Klang Valley, Malaysia', Journal of Eastern Asia Society Transportation s, vol. 2, no.6,
pp.2053-2069
Tandel, BN & Macwan, JEM 2013 'Assessment And Modeling Of Urban Traffic
Noise At Major Arterial Roads Of Surat, India', Journal of Environmental Research
And Development, vol. 7, no. 4A, pp. 1703-1709
Thangadurai, N, Venkateswaran, P & Jeevanraj, S 2005 'Evaluation and analysis of
noise quality of Ambur, TamilNadu, India' Journal of Environmental Sci and Engg,
vol. 47, pp. 7-12
Tirtharaj Sen, Pijush Kanti Bhattacharjee, Debamalya Banerjee & Bijan Sarkar, 2010
'Study and Comparison of the Noise Dose on Workers in a Small Scale Industry in
West Bengal, India', International Journal of Environmental Science and Development,
vol.1, no. 4, pp. 364 – 370
Turgut Öztürk, Zübeyde ÖZTÜRK & Metehan ÇALIS 2012 'A case study on acoustic
performance and Construction costs of noise barriers', Scientific Research and Essays,
vol. 7, issue. 50, pp. 4213-4229
Vahideh Abolhasannejad, Mohammad Reza Monazzam & Narjes Moasheri 2013
'Comparison of Noise Sensitivity and Annoyance Among the Residents of Birjand Old
and New Urban Districts', Current World Environment, vol. 8(1), pp. 29-36
Vidyasagar, T & Rao, GN 2006 'Noise Pollution Levels in Visakhapatnam City
(India)', Journal of Environmental Science and Engineering, vol. 48, no. 2, pp. 139-142
Wendy, L, Martinez & Angel R. Martinez 2005 'Exploratory Data Analysis with
MATLAB' Chapman & Hall/CRC Press, London SW15 2NU
Yang Fan, Bao Zhiyi, Zhu Zhujun & Liu Jiani 2010 'The investigation of noise
attenuation by plants and corresponding noise reduction', Journal of Environmental
Health, vol. 72, pp.8-12
134
Web reference
Annual Report 2005-2006 to combat noise pollution Activities of the West Bengal
Pollution Control Board (WBPCB), www.wbpcb.gov.in/html/ annualreps/ar0607/
part1.pdf
Anon. 2012 'Report on Noise and Vibrations' Indian Institute of Technology – Roorkee a
ppt presentation.http://www.iitro.in/publications/ppt presentations/html
Anon. 2000 'Transit noise and vibrations assessment' Inc. Publications United States,
chapter 12, pp. 12-1 to 12-12, www.fta.dot.gov/documents/FTA_Noise_and_Vibration
Manual.pdf
Anon. 2000 'The Ambient Air Quality Noise Standards in Respect of Noise as per GOI,
MoEF Notification Environment (Protection) Act 1986 as amended in 2000' CPCB
Chennai, www.envfor.nic.in/legis/noise/noise.html
Anon. 2001 'Environmental health criteria of noise' World Health Organisation, (WHO)
Occupational and community noise, Fact sheet 258, Geneva, www.who.int/quantifying_
ehimpacts/publications/en/ebd9.pdf
Anon. 2006a 'Plan to tackle road traffic noise in Hong Kong' A Draft Comprehensive Plan
Prepared by Environmental Protection Department, Hong Kong, www.epd.gov.hk/epd/
english/environmentinhk/noise/.../LNRS-final.pdf
Anon. 2006b 'Mitigation measures against road traffic noise in selected places' Prepared
by Jackie WU Research and Library Services Division Legislative Council Secretariat,
Hong Kong, www.epd.gov.hk/epd/english/environmentinhk/noise/.../LNRS-final.pdf
Anon. 2006c 'Evaluation of benefits and opportunities for innovative noise barrier design'
A Comprehensive plan prepared by Arizona Department of Transportation [ADOT].
Anon. 2010a 'Understanding the most common sources of noise in the city' New York City
Department of Environmental Protection Bureau of Environmental Compliance 59-17
Junction Blvd, 11th Fl, Flushing, NY, www.nyc.gov/html/dep/pdf/noise_code_guide.pdf
Anon. 2010b 'Good Practice Guide on Noise Exposure and Potential Health Effects'
European Environment Agency – 36, pp ISBN 978-92-9213-140-1 doi:10.2800/54080
Anon. 2010c 'A basic frequency analysis of sound' lecture notes issued by Brüel & Kjær
Sound and Vibration Measurement A/S www.bksv.com/
Anon. 2013 'Noise Pollution and its Control' BITS, Pilani http://discovery.bitspilani.ac.in/
dlpd/courses/coursecontent/coursematerial %5Cetzc362%5C noice_pollution_notes.pdf
135
Controlling noise on construction sites as a BP guide' Australian Construction Agency,
Australia 2007, pp. 1 to 19, www.safeworkaustralia.gov.au/ sites/.../Occupational_ Noise
Environmental criteria for road traffic noise Published by, Environment Protection
Authority 1999, www.epa.nsw.gov.au/resources/noise/2011236nswroadnoisepolicy.pdf
IOMA’s safety director’s report on ' noise hazards at construction sites: there are answers'
Institute of management and administration 2001 pp. 1-3, lib.imps.ac.ir/pdfTemp/
9780123820129.pdf
National Semiconductor Application Note 255, 1980 Japan pp. 1 to 27,
www.ti.com/lit/an /snoa719/snoa719.pdf
Report on Low Frequency Noise Technical Research Support for DEFRA Noise
Programme Department of the Environment, Northern Ireland Scottish Executive
National Assembly for Wales 2001, nf-hrup.si/pdf_files/LFN_scotland.pdf
Report on the Status of Rubberized Asphalt Traffic Noise Reduction in Sacramento
County Prepared by: Sacramento County Department of Environmental Review and
Assessment, Inc. Consultants in Acoustics and Noise Control Engineering 1999,
http://www.ra-foundation.org/report-on-the-status-of-rubberized-asphalt-traffic-noise-
reduction-in-sacramento-county
Stanford Research Systems About FFT Spectrum Analyzers Application Note #1http;
www.thinkSRS.com 2014
Staff Reporter, 2013, 'City’s Transport Network, 'The Times of India, vol. 6, issue 299,
December 18, pp. 1-2
Staff Reporter, 2014 the hindu.com/news/cities/chennai/section-of-false-ceiling-
collapses-at-chennai-airports-old-international-terminal/ article5940502.ece April 23
136
PUBLICATIONS
International Journal
[1] Dasarathy, AK & Thandavamoorthy, TS 2014 ‘Noise Reduction Using Concrete
Barriers: A Case Study’, International Journal Earth Sciences and Engineering, vol. 7,
no. 4, pp. 1449-1452
[2] Dasarathy, AK & Thandavamoorthy, TS 2014 ‘Noise reduction due to an enclosure
constructed by fly ash bricks’, International Journal Applied Environmental Sciences,
vol. 9, no. 4, pp. 1749-1757
[3] Dasarathy, AK & Thandavamoorthy, TS 2014 ‘Construction noise pollution and its
attenuation’, International Journal of Earth Sciences and Engineering, vol. 7, no. 5, pp.
1458-1462
National Journal
[1] Dasarathy, AK & Thandavamoorthy, TS 2013 ‘Attenuation of noise using barrier
in the form of enclosures’, Journal of Applied Research, vol. 3, issue. 8, pp. 83-89
[2] Dasarathy, AK & Thandavamoorthy, TS 2013 ‘Noise pollution in chennai - A case
study’, Asia Pacific Journal of Research, vol. 1, issue. 9, pp. 143-148
[3] Dasarathy, AK & Thandavamoorthy, TS 2013 ‘Pollution due to noise from selected
places’, IOSR Journal of Mechanical and Civil Engineering, vol. 10, issue. 3, pp.
12-16
[4] Dasarathy, AK & Thandavamoorthy, TS 2013 ‘Coral shell powder and its strength’,
Journal of Research in Civil and Environmental Engineering , pp. 113-122
[5] Dasarathy, AK & Thandavamoorthy, TS 2014 ‘Prediction of noise pollution by
Linear regression analysis’, International Journal of Civil and Structural
Engineering, Feb,pp. 113-122
137
Annexure I
Table -1 (Frequency range and corresponding decibel range)
Frequency range in Hz
Location Decibel level range (dBA)
10 to 40
Traffic stream Traffic stream
51-75
41 to 70 59-77
71 to 100 55-75
10 to 40
Subway
Inside
55-72
41 to 70 55-75
71 to 100 58-75
10 to 40
Outside
60-84
41 to 70 69-84
71 to 100 69-84
10 to 40
Perunglalathur raliway station
Railway station
45-59
41 to 70 45-55
71 to 100 45-55
10 to 40 Level
crossing
80-92
41 to 70 80-94
71 to 100 80-98
10 to 40 Open
trafffic
89-97
41 to 70 85-95
71 to 100 83-100
10 to 60
Construction operation
Jack hammer
93-127
61 to 140 95-127
141 to 200 95-127
10 to 60 Marble cutting
93
61 to 140 100
141 to 200 101
10 to 60 Piling
operation
72-112
61 to 140 81-113
141 to 200 82-113
10 to 60 Mixer
machine
65-94
61 to 140 65-97
141 to 200 65-97
10 to 60
Vibrator
61-81
61 to 140 62-81
141 to 200 62-81
138
Annexure I
Table -1 (Frequency range and corresponding decibel range) contd.
Frequency range in Hz
Location Decibel level range (dBA)
10 to 40
Cars having different year
of manufacturing
2002 76-79
41 to 70 76-79 71 to 100 73-79 10 to 40
2004 62-77
41 to 70 70-77 71 to 100 69-79 10 to 40
2006 64-71
41 to 70 64-69 71 to 100 65-69 10 to 40
2008 64-66
41 to 70 66-68 71 to 100 62-68 10 to 40
2010 57-64
41 to 70 57-64 71 to 100 57-61 10 to 40
2012 55-59
41 to 70 55-59 71 to 100 55-59 10 to 40
Flour mills and
open traffic
Rice
90-98
41 to 70 90-94
71 to 100 90-94
10 to 40
Mirchi
105-115
41 to 70 105-115
71 to 100 108-115
10 to 40
Seekakai
90-98
41 to 70 90-94
71 to 100 90-94
10 to 40
OMR
58-83
41 to 70 51-74
71 to 100 55-82
10 to 40
KPR
47-61
41 to 70 45-60
71 to 100 48-60
139
Annexure I
Table -1 (Frequency range and corresponding decibel range) contd.
Frequency range inHz
Location Decibel level range (dBA)
10 to 40
Thatched shed barrier
Open stream
59-88
41 to 70 62-88
71 to 100 69-84
10 to 40
First Layer
60-74
41 to 70 60-75
71 to 100 60-80
10 to 40 Second layer
52-76
41 to 70 50-72
71 to 100 48-69
10 to 40
Concrete barrier
Open stream
60-88
41 to 70 61-89
71 to 100 61-89
10 to 40 Normal concrete cubicles
49-76
41 to 70 50-76
71 to 100 48-76
10 to 40 CSP Concrete cubicles
49-76
41 to 70 50-76
71 to 100 48-76
10 to 40
Fly ash brick barrier
Open stream (2012)
65-85
41 to 70 65-79
71 to 100 64-87
10 to 40 Open stream (2013)
68-91
41 to 70 69-88
71 to 100 65-95
10 to 40 Fly ash bricks
cubicles
51‐74
41 to 70 50‐77
71 to 100 49‐69