The thermal comfort of pedestrians in a humid subtropical climate according to different thermal perception ratings.

This study aims to evaluate agreement among subjective thermal comfort, thermal sensation, thermal perception, and thermal tolerance indices, according to pedestrians in downtown Santa Maria, southern Brazil, which has a humid subtropical climate (Cfa). Between August 2015 and July 2016 (three periods), 1728 questionnaires were applied. Evaluation of the dependence of statistical variables was based on gender and age, at three periods of time: August 2015 (864 respondents), January 2016 (432 respondents), and July 2016 (432 respondents). Statistical evaluation was based on Pearson's chi-square test using RStudio software, and a significance level (α) of 5% for thermal comfort, thermal sensation, thermal preference, and thermal tolerance was used. Results indicated that age and gender affect the relationship between the variables. Thermal comfort and thermal tolerance presented the best correlation and coherence, regardless of age or gender. This study contributes to knowledge on the local microclimate and can contribute to urban planning to implement strategies that improve pedestrians' thermal comfort.

Use of noise prediction models for road noise mapping in locations that do not have a standardized model: a short systematic review.

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.