Proposição de metodologia e de modelo preditivo para avaliação da sensação térmica em espaços abertos em Curitiba - Rossi, Francine Aidie (2012)
Urban planning and modifications in open spaces are able to promote the improvement of outdoor thermal conditions and thus qualitatively influence the use of open spaces. In this context, this research aims to analyze the thermal sensation of the population of Curitiba and propose a model for predicting thermal sensation suited to local climatic conditions. The study was carried out at the pedestrian street Rua XV de November and adjacent streets. As a whole, fifteen monitoring campaigns were carried out (14 days in the period between January and August 2009 and one day in June 2010), encompassing fifteen different urban situations. The surveys took place between 10h00 and 15h00 on week days and weather data were monitored and personal data collected, using questionnaires. The method comprised four steps: analysis of the relationship between urban characteristics and thermal sensation; analysis of observed thermal sensation vote; analysis of calculated thermal sensation expressed by the indeces PMV, PET and UTCI and proposal of a thermal sensation predictive model for Curitiba. From the analysis of urban attributes and their relationship with climatic variables and thermal sensation, it was concluded that the canyon orientation and the vertical profile of the facades are important to understand the behavior of the climatic variables and to propose suggestions to improve the thermal comfort in urban environment. The analysis of PMV, PET and UTCI indeces showed the need for calibration to evaluate the thermal sensation of the population of Curitiba. The analysis between the observed thermal sensation and the climatic variables showed that the three categories of thermal sensation are mixed among themselves, with no clear distinction between the group of comfort and cold/heat discomfort, making difficult the definition of climatic zones of thermal comfort for Curitiba. Regarding both statistical methods used to develop the thermal sensation predictive model, the Linear Discriminant Function performed better than the Logistic Regression Model and the total success rate of 53% is adequate for the thermal sensation evaluation of the population analyzed.