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Ph.D.
(Engineering & Technology)
ASSESSMENT AND ANALYSIS OF TRAFFIC NOISE POLLUTION :
A CASE STUDY OF AHMEDABAD

Ph.D. Scholar : Jha Shivendra Kumar
Research Supervisor : Dr. Piyush J. Patel

Regi. No.: 16146051002
Abstract :
The Automobile Industry has changed human life making it faster and more comfortable.
We cannot think of modern life without vehicles. However, problems associated with
these automobiles are many; one of them is ‘Noise pollution’. Expanding urbanization has
posed serious concern and about noise pollution globally. In India, this is aggravated on
account of demography, indiscipline and inadequate road infrastructures due to limited
resources. Recently, it is established that noise affect and human health adversely.
Hence, with the projected level of urbanization, it is apprehended that noise pollution may
be one of the serious and concern to urban planners. An accurate and thorough analysis
of this problem is therefore necessary for in depth perception of sources of noise
generation and their specific contribution to the combined level of noise. Moreover, the
noise menace is location specific issue that needs extensive surveys in the different
locations/zones of different cities and elaborate analysis thereof. This will help the
planners and pollution control authorities to arrive at pragmatic solution and for this,
major sources and conditions of noise generation are necessary to be identified and
synthesized.

Ahmedabad is a fast-growing city in Western India, facing acute traffic problems and as
such, noise pollution is also associated. The prime purpose of this study is to measure
traffic noise level at selected seven prime intersections of Ahmedabad city, categorized
on the basis of commercial, industrial and residential area. Study is aimed at
characterization of traffic noise to identify shares of the parameters like traffic volume,
speed, honking and distance from the intersection. A combination of various parameters
has been ascertained affecting the noise level. Regression analysis is resorted to
correlate the significance of input parameters with respect to noise level using ANNOVA
&SPSS 14 software.

The primary measurements were carried out at selected intersections in commercial,
residential and industrial areas installing noise meters and cameras with manual
monitoring. Noise levels were measured during identified peak times and non-peak hours,
in different seasons, using SLM 109, Larson Davis system 824, Sound Meter 4033 SD and
Sound level meter SL-4001 CLASS 2 noise meter. Further, parameters was categorized

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