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- Integrated effects of pavement simulation models and scale differences on the thermal environment of tropical cities: physical and numerical modeling experimentsPublication . Kowalski, Luiz; Lopes, António; Masiero, E.Simulation methods attempt to explain what happens in full-scale environments. However, as simplification procedures, they also have their limitations and opportunities. One of the applications is to use the output data of a physical model to calibrate numerical simulation, or even to use outputs of numerical simulations to analyze urban scale studies. But it is uncertain the error in the interaction between these models. This study aims to analyze the impact of scale analysis and pavements simulation model modification on ambient and surface temperature of asphalt pavement in a physical model of a tropical city street canyons. Therefore, a scaled outdoor experiment was conducted, and a numerical simulation model, using ENVI-met software, was used to investigate the spatiotemporal variation of air and pavement surface temperature, in urban (1:1) and reduced (1:15) scales. For studies on the surface temperature of pavements, within the temperature range of 12 ºC to 37 ºC, it is recommended to calibrate physical models using as input, data derived from numerical simulation models, yielding a mean absolute percentage error (MAPE) of 4.9%. For estimating data in real-world urban scale, within the air temperature range of 15 ºC to 37 ºC, it is proposed to use output data from simulated models in ENVI-met, that presented a mean absolute error (MAE) of ± 0.59 or physical models (MAE = ± 0.66). These results would be useful for the development of urban surface temperatures parametrizations.
- Designing streets for people: a multicriteria decision-making studyPublication . Kowalski, Luiz; Masiero, Érico; Lopes, António; Dos, Santos; Simões, Gomes; Stanujkić, DragišaDesigning Streets for People involves selecting appropriate materials, determining the optimal configuration, and finding the best solution based on technical criteria for urban structures. This paper aims to identify the best solution by comparing two multicriteria decision-making methods: the WISP (Weighted Sum-Product) and AHP-Gaussian, which represents a recent algorithm for the Analytical Hierarchy Process (AHP) decision- making. We created a matrix with eight factors (cost, braking distance, lifetime, sidewalk width, carbon footprint, electricity consumption, and pavement temperature) to choose between four pavement options (concrete and asphalt with different sidewalk widths). The WISP recommended a concrete pavement and 2.0-meter sidewalk. The least viable option was asphalt pavement with a 1.2-meter sidewalk, due to its higher carbon footprint (12%), increased air temperatures (10%), and greater public lighting expenses (11%). WISP allows for assigning weights to criteria with robustness, computational effectiveness, and transparency. Conversely, AHP-Gaussian incorporates a sensitivity feature that lets decision-makers assign weights based on statistical analysis. Despite each method's limitations, both are suitable for urban projects, estimating decisions based on multiple technical aspects, thereby promoting more integrated and efficient choices
- Air pollution dynamics: the role of meteorological factors in PM10 concentration patterns across urban areasPublication . Girotti, Carolina; Kowalski, Luiz; Silva, Tiago; Correia, Ezequiel; R. Prata Shimomura, Alessandra; Akira Kurokawa, Fernando; Lopes, AntónioAir pollution is a major health problem in urban areas, influenced by traffic and atmospheric conditions. This study investigates the relationship between meteorological factors—wind direction, wind speed, boundary layer height, and atmospheric stability conditions —street trees, and PM10 concentration in three urban canyons: Avenida da Liberdade and Estrada de Benfica in Lisbon, and Marginal Tietê in São Paulo. Five years of hourly meteorological data and PM10 concentrations were analysed. Despite differences in scale and traffic volume, the results show that PM10 concentration patterns were similar in both Lisbon study areas. These areas also indicated a significant influence of atmospheric variables such as wind speed, boundary layer height, and atmospheric stability conditions. Tietê, with a higher vehicle density and different atmospheric conditions (lower wind speeds and greater atmospheric stability), presents higher PM10 peaks. Seasonal analysis revealed distinct patterns influenced by atmospheric instability, wind speed, and direction. In winter, areas with dense street tree cover had reduced PM10 levels, while those without showed higher concentrations due to increased stability. Wind direction played a crucial role, favouring the pollutant dispersal in canyons with parallel winds. The Factorial Analysis of Mixed Data method identified qualitative variables linked to the seasons, wind direction, and presence of trees. PM10 levels below the were associated with the summer and autumn period, parallel winds, and street trees, while levels above the limit were linked to winter period and areas without street trees. By integrating big data analytics with environmental monitoring, this research underscores the importance of considering the local atmospheric conditions and environmental variables in the urban air quality management. Thus, it demonstrates that the traffic volume alone does not determine PM10 concentrations; instead, the interplay of multiple factors, including meteorological conditions and urban planning, played a crucial role. This study provides valuable insights for developing effective strategies to mitigate urban air pollution and protect public health.