Noise Mapping and Variance of Road Traffic Noise: Identification of Most Noise Impacting Vehicular Type in an Urban Region

Urban road traffic noise is a major concern in developing as well as developed countries. Often it is difficult to identify the most noise impacting vehicular type especially in urban region with mixed vehicular flow. Herein, we analysed in a systematic way to identify the most noise impacting vehicular type at Hyderabad city of India. The road traffic noise across the corridor-3 metro line known as the blue line metro was chosen in the present study because, it stretches from north to south connecting 23 stations comprising major residential and commercial locations of the city. The noise levels were analysed as per CPCB guidelines. The noise pollution quantifying parameters such as Noise Climate (NC), Noise Pollution Level (LNP), and Traffic Noise Index (TNI) were analysed across the lane. A systematic analysis revealed that, the twowheelers are the most noise impacting vehicles in the daytime whereas four-wheelers in the nighttime. Noise map generated using the IDW spatial interpolation method shows the noise impacted regions across the metro lane stretching ~27 km of the city. The methodological pattern in the present investigation can be useful tool in identifying the most noise impacting vehicular type in any region with a mixed vehicular flow

Noise Mapping and Variance of Road Traffic Noise: Identification of Most Noise Impacting Vehicular Type in an Urban Region

823-832Urban road traffic noise is a major concern in developing as well as developed countries. Often it is difficult to identify the most noise impacting vehicular type especially in urban region with mixed vehicular flow. Herein, we analysed in a systematic way to identify the most noise impacting vehicular type at Hyderabad city of India. The road traffic noise across the corridor-3 metro line known as the blue line metro was chosen in the present study because, it stretches from north to south connecting 23 stations comprising major residential and commercial locations of the city. The noise levels were analysed as per CPCB guidelines. The noise pollution quantifying parameters such as Noise Climate (NC), Noise Pollution Level (LNP), and Traffic Noise Index (TNI) were analysed across the lane. A systematic analysis revealed that, the twowheelers are the most noise impacting vehicles in the daytime whereas four-wheelers in the nighttime. Noise map generated using the IDW spatial interpolation method shows the noise impacted regions across the metro lane stretching ~27 km of the city. The methodological pattern in the present investigation can be useful tool in identifying the most noise impacting vehicular type in any region with a mixed vehicular flow