Urban heat mitigation through green infrastructure: a modeling approach

• Ano de defesa: 2025
• Autor(a) principal: Oukawa, Gabriel Yoshikazu Cortez
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: eng
• Instituição de defesa: Universidade Tecnológica Federal do Paraná; Londrina; Brasil; Programa de Pós-Graduação em Engenharia Ambiental; UTFPR
• Palavras-chave em Português: Arborização das cidades; Ilha de calor urbana; Conforto humano; Temperatura atmosférica; Trees in cities; Urban heat island; Human comfort; Atmospheric temperature; CNPQ::ENGENHARIAS::ENGENHARIA SANITARIA; Engenharia/Tecnologia/Gestão
• Link de acesso: http://repositorio.utfpr.edu.br/jspui/handle/1/36391

The fast-paced urbanization contributes to the intensification of urban heat islands (UHI) and can amplify the effects of climate change. Nature-based solutions (NBS), such as urban greening, are widely promoted as a cost-effective strategy to mitigate UHI and enhance thermal comfort. However, the planning and implementation of these solutions face challenges, and their effectiveness also depends on local factors, such as urban morphology, and external influences, such as regional atmospheric circulation. Modeling techniques can be used to assess the benefits of tree planting, simulate future scenarios, and develop methodologies that aid informed decision-making. This Master’s thesis examines the UHI, urban heat stress, and urban greening strategies in Londrina, Brazil, through statistical and numerical modeling approaches. Random forest models, developed using a broad pool of spatial and temporal predictors, simulated air temperature (Tair) and UHI intensity (UHII) at high spatial (10 m) and temporal (1 hr) resolutions. The impact of different tree cover scenarios was evaluated in three regions of the city during winter and summer. The Universal Thermal Climate Index (UTCI) was simulated with the SOLWEIG numerical model at high spatial (2 m) and temporal (1 hr) resolutions to assess how increased tree cover can potentially improve thermal comfort across both seasons. Four scenarios were analyzed, including the development of an algorithm that optimizes the use of urban spaces for tree planting. The models predicting Tair and UHII demonstrated high explanatory power (R² ≥ 0.82), and direct UHII modeling identified the local variables that most influence UHI, such as local climate zones 2 (compact midrise), 4 (open highrise) and 8 (large lowrise). In the enhanced tree cover scenarios, reductions in UHII of up to 65% in winter and 55% in summer were observed in the northern region of the city, while the city center and southern region experienced smaller reductions (3-27%). The spatial analysis of UTCI revealed that the city center and adjacent neighborhoods suffer from longer periods of heat stress, with the center experiencing about 200 hr above the very strong heat stress threshold (≥ 38 ºC) in summer. The most ambitious tree cover expansion scenario resulted in UTCI reductions of up to 2.1°C. These results suggest that urban greening plays a key role in reducing UHII but that complementary measures, such as retrofitting buildings to improve ventilation, could further enhance thermal comfort, especially in densely urbanized areas. The methodologies developed in this research are crucial for decision-making regarding the population’s exposure to urban heat stress, identifying the most critical areas, as well as assessing the benefits of increasing tree canopy cover for thermal comfort.