Por favor, use este identificador para citar o enlazar este ítem: https://doi.org/10.1016/j.jenvman.2022.115725

Título: Tools for evaluation and prediction of industrial noise sources. Application to a wastewater treatment plant
Fecha de publicación: 18-jul-2022
Editorial: Elsevier Ltd.
Cita bibliográfica: Journal of Environmental Management 319 (2022) 115725
ISSN: 0301-4797
Materias relacionadas: CDU::6 - Ciencias aplicadas
Palabras clave: Noise prediction
Noise modelling
Noise pollution
Noise mapping
Industrial noise
Noise source apportionment
Resumen: In recent years, acoustic pollution caused by noise has considerably increased in many countries. Particularly in Spain, the noisiest country in Europe. It is sometimes difficult to predict the noise levels that a new installation or an expansion of industrial equipment will cause in the surroundings. This work introduces a new methodology for the prediction, evaluation, and analysis of industrial noise sources, as well as a novel tool for predicting and categorizing outdoor noise from its measurement at their sources. A Wastewater Treatment Plant (WWTP) has been used to demonstrate the applicability and validity of this methodology. The continuous level of acoustic pressure equivalent has been measured in different points of the plant using an integrating sound level meter. From these values, noise maps have been built to obtain detailed information of the industrial noise generated in the installation. Also, the typical frequency patterns of each type of source have been used for the calculation of source noise apportionments. To achieve this objective, several noise sources have been selected to provide information about their contribution to the industrial noise in the WWTP surrounding area. Finally, predictions have been validated using actual measurements. This methodology is a useful tool to predict personal exposure to noise and the impact on the environment. This information can be used, in particular, to propose mitigation actions.
Autor/es principal/es: Durán del Amor, María del Mar
Baeza Caracena, Antonia
Llorens, Mercedes
Esquembre, Francisco
Facultad/Departamentos/Servicios: Facultades, Departamentos, Servicios y Escuelas::Departamentos de la UMU::Ingeniería Química
Facultades, Departamentos, Servicios y Escuelas::Departamentos de la UMU::Matemáticas
Versión del editor: https://www.sciencedirect.com/science/article/pii/S0301479722012981
URI: http://hdl.handle.net/10201/137634
DOI: https://doi.org/10.1016/j.jenvman.2022.115725
Tipo de documento: info:eu-repo/semantics/article
Número páginas / Extensión: 12
Derechos: info:eu-repo/semantics/openAccess
Atribución-NoComercial 4.0 Internacional
Descripción: © 2022 The Authors. This manuscript version is made available under the CC-BY-NC 4.0 license http://creativecommons.org/licenses/by-nc /4.0/ This document is the published manuscript version of a published work that appeared in final form in Journal of Environmental Management
Aparece en las colecciones:Artículos: Matemáticas

Ficheros en este ítem:
Fichero Descripción TamañoFormato 
1-s2.0-S0301479722012981-main.pdf11,62 MBAdobe PDFVista previa
Visualizar/Abrir


Este ítem está sujeto a una licencia Creative Commons Licencia Creative Commons Creative Commons