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Traffic noise prediction model of an Indian road: an increased scenario of vehicles and honking.
Environ Sci Pollut Res Int. 2020 Jul 04 [Online ahead of print]ES

Abstract

Noise is considered as an underrated and underemphasized pollutant in contrast to other pollutants of the environment. Due to the non-acute response of health effects, people are not vigilant towards consequences regarding noise pollution. The expansion of the transportation industry is contributing towards the increment in the public and private vehicular volume which causes an increment in noise pollution. For evaluation of respective scenario, the research study has been conducted on one of the minor roads of Nagpur, India; for 2 years, viz., 2012 and 2019. The study concludes an increment of 5-6 dB(A) in noise level, 4-6 times in honking, and 1.7 times in traffic volume. The study confirms increment in sound pressure by 65.9% and 81.9% for the year 2012 and 2019 during morning and evening sessions, respectively. Noise prediction model has also been developed for the abovementioned years, using multiple regression analysis, considering traffic volume, honking, and speed against noise equivalent level. Honking has been further characterized into honk by light and medium category vehicles as acoustical properties of horns vary with respect to category of vehicle and introduced into the noise prediction model. Noise prediction model for 2019 has predicted the noise level in a range of - 1.7 to + 1.4 dB (Leq) with 84% of observations in the range of - 1 to + 1 dB (Leq), when compared with observed Leq on the field. For proper management of noise pollution, a noise prediction model is essentially needed so that the noise level can be anticipated, and accordingly, measures can be outlined and executed. This increased noise level has serious impacts on human hearing capacity and overall health. Accordingly, noise mitigation preventive measures are recommended to control traffic noise in the urban environment.

Authors+Show Affiliations

Centre for Strategic Urban Management (C-SUM), CSIR-NEERI, Nehru Marg, Nagpur, Maharashtra, 440020, India.Academy of Scientific and Innovative Research (AcSIR), CSIR HRDC Campus, Ghaziabad, Uttar Pradesh, 201002, India.Centre for Strategic Urban Management (C-SUM), CSIR-NEERI, Nehru Marg, Nagpur, Maharashtra, 440020, India. r_vijay@neeri.res.in.Civil Engineering and Applied Mechanics Department (CE-AMD), Shri Govindram Seksaria Institute of Technology and Science, Indore, Madhya Pradesh, 452003, India.CSIR-NEERI, Nagpur, India.

Pub Type(s)

Journal Article

Language

eng

PubMed ID

32623675

Citation

Thakre, Chaitanya, et al. "Traffic Noise Prediction Model of an Indian Road: an Increased Scenario of Vehicles and Honking." Environmental Science and Pollution Research International, 2020.
Thakre C, Laxmi V, Vijay R, et al. Traffic noise prediction model of an Indian road: an increased scenario of vehicles and honking. Environ Sci Pollut Res Int. 2020.
Thakre, C., Laxmi, V., Vijay, R., Killedar, D. J., & Kumar, R. (2020). Traffic noise prediction model of an Indian road: an increased scenario of vehicles and honking. Environmental Science and Pollution Research International. https://doi.org/10.1007/s11356-020-09923-6
Thakre C, et al. Traffic Noise Prediction Model of an Indian Road: an Increased Scenario of Vehicles and Honking. Environ Sci Pollut Res Int. 2020 Jul 4; PubMed PMID: 32623675.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Traffic noise prediction model of an Indian road: an increased scenario of vehicles and honking. AU - Thakre,Chaitanya, AU - Laxmi,Vijaya, AU - Vijay,Ritesh, AU - Killedar,Deepak J, AU - Kumar,Rakesh, Y1 - 2020/07/04/ PY - 2020/02/25/received PY - 2020/06/29/accepted PY - 2020/7/6/entrez PY - 2020/7/6/pubmed PY - 2020/7/6/medline KW - Equivalent speed KW - Honking KW - Noise pollution KW - Noise prediction model KW - Traffic noise KW - Traffic volume JF - Environmental science and pollution research international JO - Environ Sci Pollut Res Int N2 - Noise is considered as an underrated and underemphasized pollutant in contrast to other pollutants of the environment. Due to the non-acute response of health effects, people are not vigilant towards consequences regarding noise pollution. The expansion of the transportation industry is contributing towards the increment in the public and private vehicular volume which causes an increment in noise pollution. For evaluation of respective scenario, the research study has been conducted on one of the minor roads of Nagpur, India; for 2 years, viz., 2012 and 2019. The study concludes an increment of 5-6 dB(A) in noise level, 4-6 times in honking, and 1.7 times in traffic volume. The study confirms increment in sound pressure by 65.9% and 81.9% for the year 2012 and 2019 during morning and evening sessions, respectively. Noise prediction model has also been developed for the abovementioned years, using multiple regression analysis, considering traffic volume, honking, and speed against noise equivalent level. Honking has been further characterized into honk by light and medium category vehicles as acoustical properties of horns vary with respect to category of vehicle and introduced into the noise prediction model. Noise prediction model for 2019 has predicted the noise level in a range of - 1.7 to + 1.4 dB (Leq) with 84% of observations in the range of - 1 to + 1 dB (Leq), when compared with observed Leq on the field. For proper management of noise pollution, a noise prediction model is essentially needed so that the noise level can be anticipated, and accordingly, measures can be outlined and executed. This increased noise level has serious impacts on human hearing capacity and overall health. Accordingly, noise mitigation preventive measures are recommended to control traffic noise in the urban environment. SN - 1614-7499 UR - https://www.unboundmedicine.com/medline/citation/32623675/Traffic_noise_prediction_model_of_an_Indian_road:_an_increased_scenario_of_vehicles_and_honking L2 - https://dx.doi.org/10.1007/s11356-020-09923-6 DB - PRIME DP - Unbound Medicine ER -
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