Temporal and spatial stratification for the estimation of nocturnal long-term noise levels. (February 2019)

• Record Type: Journal Article
• Authors: Quintero, G.; Romeu, J.; Balastegui, A.
• Is Part Of: Environmental pollution. Volume 245(2019)
• Page Start: 666
• Page End: 674
• Publication Date: 2019-02
• Subjects: Noise assessment -- Land use -- Night period -- Leisure noise -- Cluster analysis; Pollution -- Periodicals; Pollution -- Environmental aspects -- Periodicals; Environmental Pollution -- Periodicals; Pollution -- Périodiques; Pollution -- Aspect de l'environnement -- Périodiques; Pollution -- Effets physiologiques -- Périodiques; Pollution; Pollution -- Environmental aspects; Periodicals; Electronic journals; 363.73
• DOI: 10.1016/j.envpol.2018.11.052
• Languages: English
• ISSNs: 0269-7491

Abstract

Abstract: Noise pollution in cities is mainly caused by the vehicular traffic but, depending on the place under assessment, it could be affected by the land use. For noise assessment and strategic noise mapping, the night period equivalent level ( L n i g h t ), which evaluates sleep disturbance, is one of the requirements of the European Directive 2002/49/EC to be presented for the equivalent time of one year. This research aims to find the influence of the land use in the weekdays stratification to improve the accuracy of the long-term noise level estimation for the night period. It is found that depending on the land use of the place under assessment, the weekdays temporal and spatial stratification could be affected by leisure activities. From a statistical analysis based on a clustering procedure of L n i g h t samples in 19 points, it is observed that both, temporal and spatial stratification depend on the intensity of the surrounding leisure activity, and not on traffic. Following these stratification criteria, a sampling method is presented that reduces by 47% the number of days needed to estimate the annual levels with respect to random sampling. Graphical abstract: Highlights: Night noise behaviour depends on the land use. Cluster analysis is used to find the temporal stratas and spatial classes (Lnight). Temporal stratas are divided in Monday to Thursday and Friday to Saturday. Four different streets classes are found, related to different leisure activities. Long term estimation based on proposed stratification reduces sampling cost by 47%.