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Faced with the accelerated growth of cities and the consequent increase in the number of motor vehicles, urban noise levels caused by vehicular traffic have increased considerably. To assess noise levels in cities and implement noise control measures or identify the problem’s location in different urban areas, it is necessary to obtain the noise levels to which people are exposed. Noise maps are tools that have applications as they are cartographic representations of the noise level distribution in an area and over a period of time. This article aims to identify, select, evaluate, and synthesize information, through a systematic literature review, on using different road noise prediction models, in sound mapping computer programs in countries that do not have a standard noise prediction model. The analysis period was from 2018 to 2022. From a previous analysis of articles, the choice of topic was based on identifying various models for predicting road noise in countries without a standardized sound mapping model. The papers compiled by a systematic literature review showed that studies concentrated in China, Brazil, and Ecuador, the most used traffic noise prediction models, were the RLS-90 and the NMPB, and the most used mapping programs were SoundPLAN and ArcGIS with a grid size of 10 × 10 m. Most measurements were carried out during a 15-min period at a height from the ground level of 1.5 m. In addition, it was observed that research on noise maps in countries that do not have a local model has been increasing over time.
Faced with the accelerated growth of cities and the consequent increase in the number of motor vehicles, urban noise levels caused by vehicular traffic have increased considerably. To assess noise levels in cities and implement noise control measures or identify the problem’s location in different urban areas, it is necessary to obtain the noise levels to which people are exposed. Noise maps are tools that have applications as they are cartographic representations of the noise level distribution in an area and over a period of time. This article aims to identify, select, evaluate, and synthesize information, through a systematic literature review, on using different road noise prediction models, in sound mapping computer programs in countries that do not have a standard noise prediction model. The analysis period was from 2018 to 2022. From a previous analysis of articles, the choice of topic was based on identifying various models for predicting road noise in countries without a standardized sound mapping model. The papers compiled by a systematic literature review showed that studies concentrated in China, Brazil, and Ecuador, the most used traffic noise prediction models, were the RLS-90 and the NMPB, and the most used mapping programs were SoundPLAN and ArcGIS with a grid size of 10 × 10 m. Most measurements were carried out during a 15-min period at a height from the ground level of 1.5 m. In addition, it was observed that research on noise maps in countries that do not have a local model has been increasing over time.
Resumo Este artigo relata um estudo sobre a evolução do ruído urbano na cidade de São Carlos, SP, a partir de medições acústicas durante um período de pandemia da Covid-19, e propõe modelos de predição do nível de pressão sonora equivalente (LAeq), com o objetivo de verificar a influência da variação da composição do tráfego veicular no ruído medido. Um estudo de caso é apresentado, considerando cinco pontos amostrais no centro do município. Medições acústicas foram realizadas concomitantemente com a contagem de veículos. Com base nos dados coletados, analisou-se a variação da composição do tráfego e do ruído medido ao decorrer das flexibilizações das medidas restritivas. Modelos de regressão múltipla foram elaborados para observar a influência de cada tipo de veículo na geração do ruído urbano. Os resultados obtidos indicaram a redução do nível de ruído abaixo dos limites estipulados pela NBR 10151:2019, na 1ª medição (maio de 2020). Na última medição (novembro de 2021), os níveis LAeq estiveram superiores aos medidos antes do período pandêmico, mesmo com a vigência de algumas medidas de restrição. Os modelos de regressão propostos evidenciaram a contribuição das motocicletas no ruído urbano e o coeficiente de correlação (R²) dos modelos foram superiores a 0,75, validando os modelos gerados.
Faced with the accelerated growth of cities and the consequent increase in the number of motor vehicles, urban noise levels, caused by vehicular traffic, have increased considerably. In order to assess noise levels in cities and to successfully implement noise control measures or to identify the location of the problem in different urban areas, it is first necessary to obtain information on the noise levels to which people are exposed. Noise maps are tools that have several potential applications as they are cartographic representations of the noise level distribution in area and over a period of time. This article aims to identify, select, evaluate and synthesize information, through a Systematic Literature Review, on the use of different road noise prediction models, in sound mapping computer programs in countries that do not have a standard noise prediction model. From a previous analysis of articles, the choice of topic was based on the identification of a variety of different models for predicting road noise in countries that do not have a standardized model for the use of sound mapping. The papers compiled by SLR showed that studies concentrated in China, Brazil and Ecuador, and that the most used traffic noise prediction models were the RLS-90 and the NMPB, and the most used mapping programs were SoundPLAN and ArcGIS with a grid size of 10 x 10 m. Most measurements were carried out during a 15 min period at a height from ground level of 1.5 m.
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