Sampling approaches to predict urban street noise levels using fixed and temporary microphones
- Author
- Arnaud Can (UGent) , Timothy Van Renterghem (UGent) , Michaël Rademaker (UGent) , Samuel Dauwe (UGent) , Pieter Thomas (UGent) , Bernard De Baets (UGent) and Dick Botteldooren (UGent)
- Organization
- Abstract
- Requirements for static (prediction of L(den) and diurnal averaged noise pattern) and dynamic (prediction of 15 min and 60 min evolution of L(Aeq) and statistical levels L(A90), L(A50) and L(A10)) noise level monitoring are investigated in this paper. Noise levels are measured for 72 consecutive days at 5 neighboring streets in an inner-city noise measurement network in Gent, Flanders, Belgium. We present a method to make predictions based on a fixed monitoring station, combined with short-term sampling at temporary stations. It is shown that relying on a fixed station improves the estimation of L(den) at other locations, and allows for the reduction of the number of samples needed and their duration; L(den) is estimated with an error that does not exceed 1.5 dB(A) to 3.4 dB(A) according to the location, for 90% of the 3 x 15 min samples. Also the diurnal averaged noise pattern can be estimated with a good accuracy in this way. It was shown that there is an optimal location for the fixed station which can be found by short-term measurements only. Short-term level predictions were shown to be more difficult; 7 day samples were needed to build models able to estimate the evolution of L(Aeq, 60min) with a RMSE ranging between 1.4 dB(A) and 3.7 dB(A). These higher values can be explained by the very pronounced short-term variations appearing in typical streets, which are not correlated between locations. On the other hand, moderately accurate predictions can be achieved, even based on short-term sampling (a 3 x 15 minute sampling duration seems to be sufficient for many of the accuracy goals set related to static and dynamic monitoring). Finally, the method proposed also allows for the prediction of the evolution of statistical indicators.
- Keywords
- EXPOSURE, SOUND, DYNAMICS, SOUNDSCAPES, ROAD TRAFFIC NOISE, IBCN, ANNOYANCE
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Citation
Please use this url to cite or link to this publication: http://hdl.handle.net/1854/LU-2043487
- MLA
- Can, Arnaud, et al. “Sampling Approaches to Predict Urban Street Noise Levels Using Fixed and Temporary Microphones.” JOURNAL OF ENVIRONMENTAL MONITORING, vol. 13, no. 10, 2011, pp. 2710–19, doi:10.1039/c1em10292c.
- APA
- Can, A., Van Renterghem, T., Rademaker, M., Dauwe, S., Thomas, P., De Baets, B., & Botteldooren, D. (2011). Sampling approaches to predict urban street noise levels using fixed and temporary microphones. JOURNAL OF ENVIRONMENTAL MONITORING, 13(10), 2710–2719. https://doi.org/10.1039/c1em10292c
- Chicago author-date
- Can, Arnaud, Timothy Van Renterghem, Michaël Rademaker, Samuel Dauwe, Pieter Thomas, Bernard De Baets, and Dick Botteldooren. 2011. “Sampling Approaches to Predict Urban Street Noise Levels Using Fixed and Temporary Microphones.” JOURNAL OF ENVIRONMENTAL MONITORING 13 (10): 2710–19. https://doi.org/10.1039/c1em10292c.
- Chicago author-date (all authors)
- Can, Arnaud, Timothy Van Renterghem, Michaël Rademaker, Samuel Dauwe, Pieter Thomas, Bernard De Baets, and Dick Botteldooren. 2011. “Sampling Approaches to Predict Urban Street Noise Levels Using Fixed and Temporary Microphones.” JOURNAL OF ENVIRONMENTAL MONITORING 13 (10): 2710–2719. doi:10.1039/c1em10292c.
- Vancouver
- 1.Can A, Van Renterghem T, Rademaker M, Dauwe S, Thomas P, De Baets B, et al. Sampling approaches to predict urban street noise levels using fixed and temporary microphones. JOURNAL OF ENVIRONMENTAL MONITORING. 2011;13(10):2710–9.
- IEEE
- [1]A. Can et al., “Sampling approaches to predict urban street noise levels using fixed and temporary microphones,” JOURNAL OF ENVIRONMENTAL MONITORING, vol. 13, no. 10, pp. 2710–2719, 2011.
@article{2043487, abstract = {{Requirements for static (prediction of L(den) and diurnal averaged noise pattern) and dynamic (prediction of 15 min and 60 min evolution of L(Aeq) and statistical levels L(A90), L(A50) and L(A10)) noise level monitoring are investigated in this paper. Noise levels are measured for 72 consecutive days at 5 neighboring streets in an inner-city noise measurement network in Gent, Flanders, Belgium. We present a method to make predictions based on a fixed monitoring station, combined with short-term sampling at temporary stations. It is shown that relying on a fixed station improves the estimation of L(den) at other locations, and allows for the reduction of the number of samples needed and their duration; L(den) is estimated with an error that does not exceed 1.5 dB(A) to 3.4 dB(A) according to the location, for 90% of the 3 x 15 min samples. Also the diurnal averaged noise pattern can be estimated with a good accuracy in this way. It was shown that there is an optimal location for the fixed station which can be found by short-term measurements only. Short-term level predictions were shown to be more difficult; 7 day samples were needed to build models able to estimate the evolution of L(Aeq, 60min) with a RMSE ranging between 1.4 dB(A) and 3.7 dB(A). These higher values can be explained by the very pronounced short-term variations appearing in typical streets, which are not correlated between locations. On the other hand, moderately accurate predictions can be achieved, even based on short-term sampling (a 3 x 15 minute sampling duration seems to be sufficient for many of the accuracy goals set related to static and dynamic monitoring). Finally, the method proposed also allows for the prediction of the evolution of statistical indicators.}}, author = {{Can, Arnaud and Van Renterghem, Timothy and Rademaker, Michaël and Dauwe, Samuel and Thomas, Pieter and De Baets, Bernard and Botteldooren, Dick}}, issn = {{1464-0325}}, journal = {{JOURNAL OF ENVIRONMENTAL MONITORING}}, keywords = {{EXPOSURE,SOUND,DYNAMICS,SOUNDSCAPES,ROAD TRAFFIC NOISE,IBCN,ANNOYANCE}}, language = {{eng}}, number = {{10}}, pages = {{2710--2719}}, title = {{Sampling approaches to predict urban street noise levels using fixed and temporary microphones}}, url = {{http://doi.org/10.1039/c1em10292c}}, volume = {{13}}, year = {{2011}}, }
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