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Land use regression modelling of community noise in São Paulo, Brazil

Raess, M. and Brentani, A. and Ledebur de Antas de Campos, B. and Flückiger, B. and de Hoogh, K. and Fink, G. and Röösli, M.. (2021) Land use regression modelling of community noise in São Paulo, Brazil. Environmental research, 199. p. 111231.

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Abstract

Noise pollution has negative health consequences, which becomes increasingly relevant with rapid urbanization. In low- and middle-income countries research on health effects of noise is hampered by scarce exposure data and noise maps. In this study, we developed land use regression (LUR) models to assess spatial variability of community noise in the Western Region of Sao Paulo, Brazil.We measured outdoor noise levels continuously at 42 homes once or twice during one week in the summer and the winter season. These measurements were integrated with various geographic information system variables to develop LUR models for predicting average A-weighted (dB(A)) day-evening-night equivalent sound levels (Lden) and night sound levels (Lnight). A supervised mixed linear regression analysis was conducted to test potential noise predictors for various buffer sizes and distances between home and noise source.Noise exposure levels in the study area were high with a site average Lden of 69.3 dB(A) ranging from 60.3 to 82.3 dB(A), and a site average Lnight of 59.9 dB(A) ranging from 50.7 to 76.6 dB(A). LUR models had a good fit with a R(2) of 0.56 for Lden and 0.63 for Lnight in a leave-one-site-out cross validation. Main predictors of noise were the inverse distance to medium roads, count of educational facilities within a 400 m buffer, mean Normalized Difference Vegetation Index (NDVI) within a 100 m buffer, residential areas within a 50 m (Lden) or 25 m (Lnight) buffer and slum areas within a 400 m buffer. Our study suggests that LUR modelling with geographic predictor data is a promising and efficient approach for noise exposure assessment in low- and middle-income countries, where noise maps are not available.
Faculties and Departments:09 Associated Institutions > Swiss Tropical and Public Health Institute (Swiss TPH)
09 Associated Institutions > Swiss Tropical and Public Health Institute (Swiss TPH) > Department of Epidemiology and Public Health (EPH) > Environmental Exposures and Health Systems Research > Physical Hazards and Health (Röösli)
09 Associated Institutions > Swiss Tropical and Public Health Institute (Swiss TPH) > Department of Epidemiology and Public Health (EPH) > Health Interventions > Malaria Interventions (Lengeler)
09 Associated Institutions > Swiss Tropical and Public Health Institute (Swiss TPH) > Department of Epidemiology and Public Health (EPH) > Household Economics and Health Systems Research > Epidemiology and Household Economics (Fink)
06 Faculty of Business and Economics > Departement Wirtschaftswissenschaften > Professuren Wirtschaftswissenschaften > Epidemiology and Household Economics (Fink)
UniBasel Contributors:Flückiger, Benjamin and Raess, Michelle and Ledebur de Antas de Campos, Bartolomeu and de Hoogh, Kees and Fink, Günther and Röösli, Martin
Item Type:Article, refereed
Article Subtype:Research Article
ISSN:1096-0953
Note:Publication type according to Uni Basel Research Database: Journal article
Language:English
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Last Modified:20 Dec 2022 15:08
Deposited On:20 Dec 2022 15:08

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