Pavimento urbano e desempenho térmico: modelos microclimáticos aplicados ao planejamento do território

Abstract

This study aims to develop microclimate models to evaluate the interaction between pavements and the built environment, thereby supporting territorial planning. Two models were used: the physical PAVSCAM (PAVment and Street Canyon Model) and the numerical ENVI-met. The research also analyzed measurement and simulation errors, and errors related to the scale of analysis. It explored the relationship between changes in urban pavements and responses measured by the Universal Thermal Climate Index (UTCI) across different Brazilian climates. Additionally, the AHP-Gaussian multi-criteria methodology was applied to identify the optimal urban pavement solution. Throughout the study, different urban forms, albedos, and thermal masses were assessed. Findings revealed that the highest average heat flows occur in canyons with graphite-colored concrete pavements, particularly in areas with shorter buildings, due to increased pavement exposure to solar radiation. For real urban scale estimates, the study recommends using ENVI-met data (MAE = ±0.59) or physical models (MAE = ±0.66) in comparison to on-site measurements. Regarding thermal comfort, the UTCI showed significant variation in hot and dry areas. East-west oriented streets without shade experienced increased thermal stress in the late afternoon, attributed to higher albedo or thermal inertia. Concrete pavements exhibited a rise in thermal stress from “Strong” to “Very Strong,” indicating that high albedo or inertia surfaces can lead to discomfort in urban canyons. While high-albedo materials like concrete can enhance thermal conditions in cooler and wetter zones by promoting heat dissipation and lowering air temperatures, their benefits are not universally applicable, particularly during the late hours of the day. The results provide essential tools for analyzing urban pavements and integrating them into climate-responsive projects within tropical contexts. By complementing field data with these new perspectives, the study enables a more robust and effective analysis for urban pavement planning, ensuring infrastructures are better adapted to local climatic conditions.