Journal of Environmental Biology

Assessment, analysis and appraisal of road traffic noise
pollution in Rourkela city, India

Shreerup Goswami¹*, Bijay Kumar Swain²?and Santosh Kumar Panda³

¹Department of Geology, Ravenshaw University, Cuttack-753 003, India

?????????????????? ²Department of Environmental Science, Utkal University, Bhubaneswar-751 004, India

?????????????????? ³Department of Physics, Dr. J.N.College, Rasalpur, Balasore-756 021, India

*Corresponding Author email : goswamishreerup@gmail.com

Publication Data

Paper received:

08 April 2012

Revised received:

15 November 2012

Re-revised received:

26 December 2012

Accepted:

25 January 2013

Abstract

The problem of road traffic noise pollution has become a concern for both the public and the policy makers. Noise level was assessed in 12 different squares of Rourkela city during different specified times (7-10 a.m., 11 a.m.-2 p.m., 3-6 p.m., 7-10 p.m., 10 p.m.-12 midnight and 4-6 a.m.). Noise descriptors such as Leq, traffic noise index, noise pollution level, noise climate, Lday, Levening, Lnight?and Lden?were assessed to reveal the extent of noise pollution due to heavy traffic in this city. The equivalent noise levels of all the 12 squares were found to be much beyond the permissible limit (70dB during day time and 55dB during night time). Appallingly, even the minimum Leq?and NPL values were more than 82 dB and 96 dB during day time and 69 dB and 91 dB during night time respectively. Lden?values of investigated squares ranged from 83.4 to 86.1 dB and were even more than the day time permissible limit of traffic noise. The prediction model was used in the present study to predict noise pollution level instead of Leq. Comparison of predicted with that of the actual measured data demonstrated that the model used for the prediction has the ability to calibrate the multi-component traffic noise and yield reliable results close to that by direct measurement. Lastly, it is inferred that the dimension of the traffic generated noise pollution in Rourkela is critical.

Key words

Noise prediction model, Noise pollution level, Noise climate, Traffic noise

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