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DOI: https://doi.org/10.4491/eer.2021.249
Urban road traffic noise on human exposure assessment using geospatial technology
Pachaivannan Partheeban1, Krishnamurthy Karthik2, Partheeban Navin Elamparithi3, Krishnan Somasundaram4, and Baskaran Anuradha5
1Department of Civil Engineering, Chennai Institute of Technology, Kundrathur, Chennai 600069, India
2Department of Civil Engineering, New Prince Shri Bhavani College of Engineering and Technology, Gowrivakkam, Chennai 600073, India
3Department of Computer Science and Engineering, National Institute of Technology, Tiruchirappalli 620015, India
4Department of Computer Science and Engineering, Chennai Institute of Technology, Kundrathur, Chennai 600069, India
5Department of Civil Engineering, Chennai Institute of Technology, Kundrathur, Chennai 600069, India
Corresponding Author: Pachaivannan Partheeban ,Tel: +91-9841159199, Email: parthi011@yahoo.co.in
Received: May 20, 2021;  Accepted: September 29, 2021.
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ABSTRACT
The sounds produced by humans, industries, transport and animals in the atmosphere that pose a threat to the health of humans or animals can be characterized as noise pollution. Adverse effects due to noise exposure can involve speech communication interference and declining learning skills of children. Highway traffic noise contributes to 80% of all noise. It has grown to a massive scale because of growth in population along the roads leading to a rapid change in land use and has evolved into a common reality in various Indian cities. The main objective of this work is to develop a road traffic noise prediction model using ArcGIS 10.3 for the busy corridors of Chennai. The collected data includes traffic volume, speed, and noise level in lateral and vertical directions. Noise levels were measured in 9 locations using a noise level meter. It is observed that the noise levels vary from 50 dB to 96 dB. It is found that the noise problem is severe in 18% of the area, and 6.3% of people are exposed to the traffic noise problem. The results obtained in this study show that the city is affected by severe noise pollution due to road traffic.
Keywords: Exposure Assessment | GIS | Maps | Noise Pollution | Traffic Speed | Traffic Volume
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