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      Assessing the changing urban sound environment during the COVID-19 lockdown period using short-term acoustic measurements

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          The implementation of lockdown measures due to the COVID-19 outbreak has resulted in wide-ranging social and environmental implications. Among the environmental impacts is a decrease in urban noise levels which has so far been observed at the city scale via noise mapping efforts conducted through the framework of the Environmental Noise Directive. This study aims to understand how lockdown measures have manifested at a local level to better determine how the person-level experience of the urban soundscape has been affected and how these affects differ across urban space typologies. Taking London as a case study, a series of 30-second binaural recordings were taken at 11 locations representing a cross-section of urban public spaces with varying compositions of sound sources during Spring 2019 (pre-lockdown, N = 620) and Spring 2020 (during-lockdown, N = 481). Five acoustic and psychoacoustic metrics ( LA eq , LA 10, LA 90, Loudness, Sharpness) were calculated for each recording and their changes from the pre-lockdown scenario to the lockdown scenario are investigated. Clustering analysis was performed which grouped the locations into 3 types of urban settings based on their acoustic characteristics. An average reduction of 5.4 dB ( LA eq ) was observed, however significant differences in the degree of reduction were found across the locations, ranging from a 10.7 dB to a 1.2 dB reduction. This study confirms the general reduction in noise levels due to the nationally imposed lockdown measures, identifies trends which vary depending on the urban context and discusses the implications for the limits of urban noise reduction.

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          Author and article information

          Noise Mapping
          Walter de Gruyter GmbH
          August 07 2020
          August 07 2020
          : 7
          : 1
          : 123-134
          [1 ]Institute for Environmental Design and Engineering, University College London, WC1H 0NNLondon, United Kingdom
          © 2020


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