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      A Taxonomy Proposal for the Assessment of the Changes in Soundscape Resulting from the COVID-19 Lockdown

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          Abstract

          Many countries around the world have chosen lockdown and restrictions on people’s mobility as the main strategies to combat the COVID-19 pandemic. These actions have significantly affected environmental noise and modified urban soundscapes, opening up an unprecedented opportunity for research in the field. In order to enable these investigations to be carried out in a more harmonized and consistent manner, this paper makes a proposal for a set of indicators that will enable to address the challenge from a number of different approaches. It proposes a minimum set of basic energetic indicators, and the taxonomy that will allow their communication and reporting. In addition, an extended set of descriptors is outlined which better enables the application of more novel approaches to the evaluation of the effect of this new soundscape on people’s subjective perception.

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          Most cited references44

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          A principal components model of soundscape perception.

          There is a need for a model that identifies underlying dimensions of soundscape perception, and which may guide measurement and improvement of soundscape quality. With the purpose to develop such a model, a listening experiment was conducted. One hundred listeners measured 50 excerpts of binaural recordings of urban outdoor soundscapes on 116 attribute scales. The average attribute scale values were subjected to principal components analysis, resulting in three components: Pleasantness, eventfulness, and familiarity, explaining 50, 18 and 6% of the total variance, respectively. The principal-component scores were correlated with physical soundscape properties, including categories of dominant sounds and acoustic variables. Soundscape excerpts dominated by technological sounds were found to be unpleasant, whereas soundscape excerpts dominated by natural sounds were pleasant, and soundscape excerpts dominated by human sounds were eventful. These relationships remained after controlling for the overall soundscape loudness (Zwicker's N(10)), which shows that 'informational' properties are substantial contributors to the perception of soundscape. The proposed principal components model provides a framework for future soundscape research and practice. In particular, it suggests which basic dimensions are necessary to measure, how to measure them by a defined set of attribute scales, and how to promote high-quality soundscapes.
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            A survey on exposure-response relationships for road, rail, and aircraft noise annoyance: Differences between continuous and intermittent noise

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              Intermittency ratio: A metric reflecting short-term temporal variations of transportation noise exposure

              Most environmental epidemiology studies model health effects of noise by regressing on acoustic exposure metrics that are based on the concept of average energetic dose over longer time periods (i.e. the L eq and related measures). Regarding noise effects on health and wellbeing, average measures often cannot satisfactorily predict annoyance and somatic health effects of noise, particularly sleep disturbances. It has been hypothesized that effects of noise can be better explained when also considering the variation of the level over time and the frequency distribution of event-related acoustic measures, such as for example, the maximum sound pressure level. However, it is unclear how this is best parametrized in a metric that is not correlated with the L eq, but takes into account the frequency distribution of events and their emergence from background. In this paper, a calculation method is presented that produces a metric which reflects the intermittency of road, rail and aircraft noise exposure situations. The metric termed intermittency ratio (IR) expresses the proportion of the acoustical energy contribution in the total energetic dose that is created by individual noise events above a certain threshold. To calculate the metric, it is shown how to estimate the distribution of maximum pass-by levels from information on geometry (distance and angle), traffic flow (number and speed) and single-event pass-by levels per vehicle category. On the basis of noise maps that simultaneously visualize L eq , as well as IR, the differences of both metrics are discussed.
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                Author and article information

                Journal
                Int J Environ Res Public Health
                Int J Environ Res Public Health
                ijerph
                International Journal of Environmental Research and Public Health
                MDPI
                1661-7827
                1660-4601
                12 June 2020
                June 2020
                : 17
                : 12
                : 4205
                Affiliations
                [1 ]Instrumentation and Applied Acoustics Research group (I2A2), Universidad Politécnica de Madrid, 28031 Madrid, Spain; luisgascosanchez@ 123456gmail.com (L.G.); g.dearcas@ 123456upm.es (G.d.A.)
                [2 ]UMRAE, Univ Gustave Eiffel, IFSTTAR, CEREMA, 44340 Bouguenais, France; pierre.aumond@ 123456univ-eiffel.fr (P.A.); arnaud.can@ 123456ifsttar.fr (A.C.)
                [3 ]Institute for Highway Engineering and Transport Planning, Graz University of Technology, 8010 Graz, Austria; peter.lercher.at@ 123456gmail.com
                [4 ]Empa, Swiss Federal Laboratories for Material Science and Technology, Laboratory for Acoustics/Noise Control, 8600 Dübendorf, Switzerland; jean-marc.wunderli@ 123456empa.ch
                [5 ]ETIS Laboratory, UMR 8051, CY Cergy Paris University, ENSEA, CNRS, F-95302 Cergy-Pontoise Cedex, France; catherine.lavandier@ 123456cyu.fr
                [6 ]Bruitparif, 93200 Saint-Denis, France; Carlos.Ribeiro@ 123456bruitparif.fr
                [7 ]Acoucite, Observatoire de l’environnement sonore de la Métropole de Lyon, 69007 Lyon, France; patricio.munoz@ 123456acoucite.org
                [8 ]Environmental Protection Agency of Tuscany Region, Pisa Department, 56127 Pisa, Italy
                Author notes
                Author information
                https://orcid.org/0000-0003-3265-3244
                https://orcid.org/0000-0001-8834-4251
                https://orcid.org/0000-0002-4976-9879
                https://orcid.org/0000-0002-5956-8229
                https://orcid.org/0000-0003-1699-7389
                https://orcid.org/0000-0003-4867-0954
                Article
                ijerph-17-04205
                10.3390/ijerph17124205
                7345807
                32545587
                95f995aa-7720-4962-a6d4-310e7e854e4e
                © 2020 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( http://creativecommons.org/licenses/by/4.0/).

                History
                : 16 May 2020
                : 05 June 2020
                Categories
                Communication

                Public health
                covid-19,noise,soundscape,metrics,indicators,descriptors,sound,lockdown
                Public health
                covid-19, noise, soundscape, metrics, indicators, descriptors, sound, lockdown

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