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Version 4.2 by Emily West on 2022/01/10 14:39
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Emily West 2.1 1 = 4.1.1 - LDEN – Day-evening-night noise level =
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5 |=(% style="width: 79px;" %)Topic|=(% style="width: 139px;" %)Urban challenges|=(% style="width: 666px;" %)Sub-challenges
6 |(% style="width:79px" %)Social|(% style="width:139px" %)4 - Public Health and Wellbeing|(% style="width:666px" %)4.1 Acoustics
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10 ====== **Description** ======
11 )))|(% style="width:730px" %)The LDEN is an acoustic indicator for sound environment. LDEN is expressed in dB(A) because it is based on a combination of equivalent sound pressure levels Leq,T (energetic summation through logarithmic law), calculated with the A ponderation on 3 periods (day, evening, night), depending on the sound source emission (i.e. road traffic conditions). Thus LDEN is a daily equivalent sound pressure level (T=00h-24h), with a 0dB(A) penalty increase for the Day period (T=6h-18h), a 5dB(A) penalty increase for the Evening period (T=18h-22h) and a 10dB(A) penalty increase for the Night period (T=22h-6h)
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13 ===== **Scale as linked to D2.2 framework** =====
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15 * City
16 * Neighborhood
17 * Street
18 * Household
19 * Object
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22 ====== **Data source [ link to data framework]** ======
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24 * Georeferenced data for built-up area: data from OPEN STREET MAP (OSM)
25 * Road traffic counts: data from district, city or regional agencies
26 * NBS data: qualitative information given by N4C consortium (when different scenarios will be available by other WPs and when additional functionalities will be integrated in numerical software)
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29 ====== **Needs** ======
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31 * Required tool:
32 * Measured LDEN (in situ measurements): integrating sonometer, either professional, low-cost or even smartphone [[http:~~/~~/noise-planet.org/noisecapture.html>>http://noise-planet.org/noisecapture.html]]
33 * Simulated LDEN (numerical predictions): noise prediction software, e.g. open-source tool “NoiseModelling” http:~/~/noise-planet.org/noisemodelling.html
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36 ====== **Expected Outputs** ======
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38 * quantitative
39 * units: decibels with A ponderation: “dB(A)”
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42 ====== **Calculation methods** ======
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44 [[image:1641470704668-864.png]]
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47 ====== **Links and references** ======
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68 * Liu, J., J. Kang, T. Luo, H. Behm, et T. Coppack. 2013. « Spatiotemporal variability of soundscapes in a multiple functional urban area ». Landscape and Urban Planning 115: 1‑9.
69 * Marquis-Favre, C., E. Premat, et D. Aubrée. 2005. « Noise and its Effects – A Review on Qualitative Aspects of Sound. Part II: Noise and Annoyance ». Acta Acustica united with Acustica 91 (4): 626‑42.
70 * Marquis-Favre, C., E. Premat, D. Aubrée, et M. Vallet. 2005. « Noise and its Effects – A Review on Qualitative Aspects of Sound. Part I: Notions and Acoustic Ratings ». Acta Acustica united with Acustica 91 (4): 613‑25
71 * Miedema, Henk M. E. 2004. « Relationship between exposure to multiple noise sources and noise annoyance ». The Journal of the Acoustical Society of America 116 (2): 949‑57. doi:10.1121/1.1766305
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73 * Rychtarikova, M., et G. Vermeir. 2013. « Soundscape categorization on the basis of objective acoustical parameters ». Appl. Acoust. 74: 240‑47
74 * Torija, A.J., et I.H. Flindell. 2014. « Differences in subjective loudness and annoyance depending on the road traffic noise spectrum ». J. Acoust. Soc. Amer. 135 (1): 1‑4
75 * Torija, A.J., et D.P. Ruiz. 2015. « A general procedure to generate models for urban environmental-noise pollution using feature selection and machine learning methods ». Science of the Total Environment 505: 680‑93
76 * Torija, A.J., D.P. Ruiz, et A.F. Ramos-Ridao. 2013. « Application of a methodology for categorizing and differentiating urban soundscapes using acoustical descriptors and semantic-differential attributes ». J. Acoust. Soc. Amer. 134 (1): 791‑802
77 * Van Renterghem, T., J. Forssén, K. Attenborough, P. Jean, J. Defrance, M. Hornikx, et J. Kang. 2015. « Using natural means to reduce surface transport noise during propagation outdoors ». Appl. Acoust. 92: 86‑101
78 * Viollon, S., C. Lavandier, et C. Drake. 2002. « Influence of Visual Setting on Sound Ratings in an Urban Environment ». Appl. Acoust. 63 (5): 493‑511. doi:10.1016/S0003-682X(01)00053-6
79 * Watts, G., L. Chinn, et N. Godfrey. 1999. « The effects of vegetation on the perception of traffic noise ». Appl. Acoust. 56 (1): 39‑56.
80 * Wilson, D.K., N. Wayant, E.T. Nykaza, C.L. Pettit, et C.M. Armstrong. 2015. « Hierarchical modeling approach to community noise annoyance ». J. Acoust. Soc. Amer. 138 (3): 1731‑1731
81 * Yang, F., Z. Bao, et Z. Zhu. 2011. « An assessment of psychological noise reduction by landscape plants ». Int. J. Environ. Res. Public Health 8: 1032‑48
82 * Yu, L., et J. Kang. 2010. « Factors influencing the sound preference in urban open space ». Appl. Acoust. 71: 622‑33
83 * Zhang, B., L. Shi, et G. Di. 2003. « The influence of the visibility of the source on the subjective annoyance due to its noise ». Appl. Acoust. 64 (4): 1205‑15
84 * http:~/~/noise-planet.org/noisecapture.html
85 * http:~/~/noise-planet.org/noisemodelling.html
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