Development of pavement temperature predictive models using thermophysical properties to assess urban climates in the built environment

• Established pavement temperature predictive models using thermophysical properties.
• Utilized conventional and modified asphalt and cement concrete paving mixtures.
• Correlated thermophysical properties with pavement temperature predictions.
• Validated predictive models with field test results that had excellent correlations.
• Adjudged models to be robust tools to assess urban climates in built environment.

This study developed pavement temperature predictive models based on the characterized thermophysical properties of different pavements to assess urban climates in the built environment. A database comprising of six pavement types including conventional and modified asphalt, and cement concrete mixtures was available with their thermophysical properties: specific heat capacity, thermal conductivity and material density. Models were developed to predict temperature at the surface, and at 40 mm depth using the measured thermophysical properties, and recorded climatological parameters: air temperature, wind speed, and relative humidity. The two predictive models were robust and rational depicted by low bias and high precision. An increase in heat capacity increased pavement surface temperature indicating that higher energy is required to raise the pavement temperature, and also be able to release as much energy as stored, which would be best suitable at different times of the day to counter urban heat island (UHI) effects. An increase in thermal conductivity decreased pavement temperature illustrating that the pavement would store more heat within the system for a longer duration, and may release this heat at a particular timeframe changing the urban climate at that moment. An increase in wind speed by about 1 m/s increased pavement temperature by 1 °C, and this may increase UHI if there is already higher temperature in the environment. Overall, based on rational correlations between model predictions and actual field measurements it is recommended that the pavement temperatures of the systems be comfortably predicted for pavements using the developed models.