Estimativa da emissividade do céu claro e da radiação de onda longa descendente com foco na simulação termo energética de edificações

Abstract

The lack of measured downward longwave radiation (DLR) data in Brazil, combined with the use of sky temperature models that are not locally calibrated, introduces significant uncertainties in building energy simulations. These limitations compromise the accuracy of longwave radiative heat exchange estimations, which in turn influence the building’s overall energy balance. This study investigated the impact of sky temperature parameterization on the prediction of thermal and energy performance of buildings, aiming to improve the reliability of simulations across different Brazilian climate zones. Four clear-sky emissivity models — Brunt (1932), Clark e Allen (1978), Idso (1981) e Martin and Berdahl (1984) — implemented in the EnergyPlus software were analyzed and calibrated using data representative of Brazil's main climate groups: tropical, dry, and temperate. The results showed that the models, both in their original formulations and in the version calibrated by Li et al. (2017) and implemented in EnergyPlus, tend to overestimate DLR. After calibration, the locally adjusted version of the Berdahl and Martin (1984) model demonstrated the best agreement with actual atmospheric conditions. Based on 577 TMYx weather files, the average radiative sky cooling (RSC) potential across Brazil was estimated at 53 W/m², with a standard deviation of approximately 15 W/m². The potential was higher in dry regions and significantly lower in humid areas. Computational simulations of a single-story reference dwelling indicated that DLR overestimation could lead to an increase of more than 20% in the annual Total Thermal Load, particularly in buildings with low thermal resistance roofing and predominantly nighttime occupancy. Despite the advances, limitations remain regarding the availability of radiometric data and information on sky cover, which still restrict the generalization of the models. These findings underscore the need to expand atmospheric data collection and to further explore the use of RSC as a passive cooling strategy in the Brazilian context. The results enabled the refinement of sky temperature models, enhancing the accuracy of energy simulations across diverse climatic conditions.