How the Physical Properties of the Leaves of Common Plants Affect Dependent Acoustic Characterization in Urban Areas of Istanbul, Turkey


Saglam S.

CONTEMPORARY PROBLEMS OF ECOLOGY, vol.15, no.5, pp.566-578, 2022 (SCI-Expanded, Scopus) identifier identifier

  • Publication Type: Article / Article
  • Volume: 15 Issue: 5
  • Publication Date: 2022
  • Doi Number: 10.1134/s1995425522050146
  • Journal Name: CONTEMPORARY PROBLEMS OF ECOLOGY
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, BIOSIS, CAB Abstracts, Environment Index, Geobase, Pollution Abstracts, Veterinary Science Database
  • Page Numbers: pp.566-578
  • Keywords: plant leaves, urban areas, sound absorption coefficient, impedance tube, pulse-echo method, sound attenuation, SOUND-ABSORPTION PERFORMANCE, ABSORBERS, WASTES, FIBERS
  • Istanbul University-Cerrahpasa Affiliated: Yes

Abstract

To date, several ecological studies have addressed the influences of environmental noise. However, fundamental studies on noise reduction depending on the acoustic characterization of natural materials are still lacking. The present study quantitatively evaluates experimental data on sound absorption and attenuation of untreated plant leaves commonly found in urban areas. The leaves of English Ivy (Hedera helix L.), Horse Chestnut (Aesculus hippocastanum L.), Hortensia (Hydrangea macrophylla (Thunb.) Ser.), Japanese Privet (Ligustrum japonicum Thunb.), Laurel (Laurus nobilis L.), Linden (Tilia tomentosa Moench), Magnolia (Magnolia grandiflora L.), Osmanthus (Osmanthus heterophyllus (G.Don) P.S.Green), Plane Tree (Platanus orientalis L.), and Cherry Laurel (Prunus laurocerasus L.) were collected from branches of healthy plants grown under identical climate and soil conditions. To acoustically characterize plant leaves, impedance tube and pulse-echo techniques were used to experimentally determine the normal incidence sound absorption coefficient (SAC), speed of sound and sound attenuation coefficient (SC) values, respectively. In addition, as more effective numerical outputs, the normalized SAC (SAC ') and normalized NRC (NRC ') values were calculated by empirical modelling. As a statistical approach, multiple regression was also conducted to predict the dependent acoustic variables based on the independent physical parameters of the samples.