Conductive heat flux (G) at pavement surfaces plays a vital role in managing internal temperature variations. G can be calculated either as the residual of solar absorption, heat convection, and long-wave radiation, or as the product of thermal conductivity and the temperature gradient near the surface. Both methods, however, are subject to uncertainties due to measurement parameters. For the two methods, this study formulates the uncertainty of the conductive heat flux at the pavement surface. The experiment was designed to measure pavement interior temperatures and external weather data so that the uncertainties of the two methods can be quantified and compared. It was found that ∆G estimated by the residual method is significantly higher than that calculated using conductivity and temperature gradient. The key factors influencing ∆G in the residual method, in order, are wind speed, incident solar radiation, and reflectivity, with other factors such as surface and air temperatures, relative humidity, and emissivity having minimal impact. In contrast, the primary contributors to ∆G in the conductivity and temperature gradient method are the temperature gradient and thermal conductivity. The residual method is crucial for predicting pavement temperatures when no pre-installed temperature sensors are available, and enhancing wind speed measurement precision can significantly reduce the uncertainty of G. The study finds that the approach of estimating G through conductivity and temperature gradient showed lower uncertainty than the residual method, particularly in complex urban environments.
Huang et al. (Wed,) studied this question.