Integrated effects of pavement simulation models and scale differences on the thermal environment of tropical cities: physical and numerical modeling experiments

被引：0

作者：

L. F. Kowalski ^{[1
]}

A. M. S. Lopes ^{[2
]}

E. Masiero ^{[3
]}

机构：

[1] Federal University of São Carlos,Centre of Geographical Studies, Institute of Geography and Spatial Planning

[2] Civil Engineering Department (DECiv),TERRA Associate Laboratory

[3] University of Lisbon,undefined

[4] University of Lisbon,undefined

来源：

City and Built Environment | / 2卷 / 1期

关键词：

Albedo; Urban Pavement; Microclimate; Pavement and Street Canyon Model (PAVSCAM); Scaled Model; ENVI-met;

D O I：

10.1007/s44213-024-00032-5

中图分类号：

学科分类号：

摘要：

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.

引用