Back to Search
Start Over
Prediction of Road Traffic Noise by CRTN Model in a Sub-Urban Town of India
- Source :
- The Global Environmental Engineers. 8:1-13
- Publication Year :
- 2021
- Publisher :
- Avanti Publishers, 2021.
-
Abstract
- Present study was undertaken for assessment of spatial characteristics of road traffic noise at varying intervals viz early morning (8-9 am), late morning (11-12 pm), afternoon (2-3 pm) and evening (6-7 pm) time at ten important locations (near school building) of G. T. Road which is passing through the Burdwan town. Digital noise meter was used for recording the traffic noise and noise contour map was constructed by using Geographical Information System (GIS). The recorded data revealed that the highest and lowest average noise 67.1 dB (A) and 86.9 dB (A), respectively. The results revealed that the performance of the CRTN model in both afternoon and evening time for predicting noise level near school building with a coefficient of determination (R2) are 0.536 and 0.544 and a mean difference of - 1.19 dB (A) and - 0.48 dB (A) between the measured and predicted values respectively. Similarly, Pearson statistics also revealed the strong correlation between measured and predicted noise level at afternoon (r = 0.732, p < 0.016) and evening time (r = 0.744, p < 0.014). However, the predicted traffic noise during early morning and late morning hour are less than 0.5. These low values are due to irregular traffic speed, traffic density and irregular building height are the appropriate reasons for low accuracy in predicting model. Finally, it may be suggested that CRTN model can be a decision tool for predicting equivalent noise level in the city like Burdwan.
- Subjects :
- Noise
Computer science
Electronic engineering
Road traffic
Subjects
Details
- ISSN :
- 24103624
- Volume :
- 8
- Database :
- OpenAIRE
- Journal :
- The Global Environmental Engineers
- Accession number :
- edsair.doi...........5a99c094b7306ad3a228fd490208e655
- Full Text :
- https://doi.org/10.15377/2410-3624.2021.08.1