Nonlinear uncertainty of the long term average level calculated from short term average sound levels

Makarewicz, Rufin; Galuszka, Michal

doi:10.3397/1.3701047

Cited by 6 publications

(3 citation statements)

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“…The reduced time length may represent a good compromise between the need of sample accuracy and costs of monitoring. However, the estimated values are affected by uncertainty, whose amount depends on the ratio between the measurement time and the medium long-term time, as well as on the variability of the noise immission at the measurement point; on this issue for instance, see Makarewicz and Gałuszkab ( 2012 ), Can et al ( 2011 ), and Brocolini et al ( 2013 ).…”

Section: Estimate Of Daytime L Aeqd Fromentioning

confidence: 99%

Cluster categorization of urban roads to optimize their noise monitoring

Zambon

Benocci

Brambilla

2015

Environ Monit Assess

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Road traffic in urban areas is recognized to be associated with urban mobility and public health, and it is often the main source of noise pollution. Lately, noise maps have been considered a powerful tool to estimate the population exposure to environmental noise, but they need to be validated by measured noise data. The project Dynamic Acoustic Mapping (DYNAMAP), co-funded in the framework of the LIFE 2013 program, is aimed to develop a statistically based method to optimize the choice and the number of monitoring sites and to automate the noise mapping update using the data retrieved from a low-cost monitoring network. Indeed, the first objective should improve the spatial sampling based on the legislative road classification, as this classification is mainly based on the geometrical characteristics of the road, rather than its noise emission. The present paper describes the statistical approach of the methodology under development and the results of its preliminary application to a limited sample of roads in the city of Milan. The resulting categorization of roads, based on clustering the 24-h hourly LAeqh, looks promising to optimize the spatial sampling of noise monitoring toward a description of the noise pollution due to complex urban road networks more efficient than that based on the legislative road classification.

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Section: Estimate Of Daytime L Aeqd Fromentioning

confidence: 99%

Cluster categorization of urban roads to optimize their noise monitoring

Zambon

Benocci

Brambilla

2015

Environ Monit Assess

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“…affected by road traffic or other environmental noise sources. Theoretical approaches by Makarewicz et al [6] proposed that the long-term average sound level L AeqT can be approximated by a few, m, short-term, τ, average sound levels, L Aeqτ , so that mτ << T, and the uncertainty of such approximation should be calculated by nonlinear uncertainty of L Aeqτ for m<10. The analysis of 5 years of continuous noise measurements carried out at one site in Valencia yielded Gaja et al [7] to conclude that a random day strategy gives a more accurate estimate of the annual equivalent level from the 24-h noise level than a consecutive day's strategy.…”

Section: Introductionmentioning

confidence: 99%

“…Comparison between experimental data and values from equation(6) of probability that ε t is within k= ± 0.5 dB for the L Aeqh estimate from the five measurement times regardless the cluster membership Comparison of probability that ε t is within the E range for the L Aeqh estimate for the five measurement times.L Aeqd -L Aeqn =7.4 [dB] Aeqd -7.4=63.0 -7.4=55.6 [dB(A)]…”

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confidence: 99%

Prediction of Accuracy of Temporal Sampling Applied to Non-Urban Road Traffic Noise

Brambilla¹,

Gallo²,

Zambon³

2015

J Pollut Eff Cont

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Stabilisation patterns of hourly urban sound levels

Gajardo

Morillas

2014

Environ Monit Assess

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In this paper, the stabilisation times for all 24 h of the day are analysed for 12 measurement stations located in the Spanish town of Malaga and throughout 5 years (2007-2011) of sampling environmental noise levels. For the results to be generalised to sound level measurements made in other streets or cities where there have been no long-term measurements, this study was developed for different road types and urban shapes. This distinction was made according to the types of roads indicated in other studies in which a statistically significant relationship was found between noise levels and the road type. The final objective of the study is to determine the capacity to estimate and approximate the real equivalent hourly noise level (L Aeq,1h) from the integration of a number of consecutive minutes (short-term measurements) less than 60 (L Aeq,1h ≈ L Aeq,T being T ≤ 60 min). Clearly, this strategy would save time and resources by making measurements of reduced duration. In summary and according to this analysis, a short-time measurement of 15 min is adequate to work with 90% confidence levels and errors of ±2 dB, with 80% confidence levels and errors of ±1 dB, and 50% confidence levels and errors of ±0.5 dB. However, it is necessary to consider the measurement hour period to achieve these levels of confidence due to the high variability throughout the day.

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Nonlinear uncertainty of the long term average level calculated from short term average sound levels

Cited by 6 publications

References 0 publications

Cluster categorization of urban roads to optimize their noise monitoring

Cluster categorization of urban roads to optimize their noise monitoring

Prediction of Accuracy of Temporal Sampling Applied to Non-Urban Road Traffic Noise

Stabilisation patterns of hourly urban sound levels

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