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In previous work from this laboratory, it has been found that the urban heat island intensity (UHI) can be scaled with the urban length scale and the wind speed, through the time-dependent energy balance. The heating of the urban surfaces during the daytime sets the initial temperature, and this overheating is dissipated during the night-time through mean convection motion over the urban surface. This may appear to be in contrast to the classical work by Oke (1973). However, in this work, we show that if the population density is used in converting the population data into urbanized area, then a good agreement with the current theory is found. An additional parameter is the “urban flow parameter,” which depends on the urban building characteristics and affects the horizontal convection of heat due to wind. This scaling can be used to estimate the UHI intensity in any cities and therefore predict the required energy consumption during summer months. In addition, all urbanized surfaces are expected to exhibit this scaling, so that increase in the surface temperature in large energy-consumption or energy-producing facilities (e.g., solar electric or thermal power plants) can be estimated.

There have been many studies on the causes and impact of the heat island effect (e.g., [

In previous work from this laboratory, we have shown that scaling of the urban heat island effect based on time-dependent energy balance works quite well in understanding and predicting the UHI dependence on the urban length scale and wind speeds [

Temperature decay as a function of time, in Phoenix, AZ, for years 1960 to 2010, using (

A brief summary of the scaling is given below. The starting point is the fundamental energy balance equation [

If we integrate while retaining only the first term on the right-hand side, we obtain the temporal evolution of the UHI intensity. This assumes that the convection effect is much stronger than the heat flux term:

On the other hand, if we consider the other extreme case of zero wind speed and retain only the heat flux term, then we obtain

The effect of the wind speed on the UHI intensity in Seoul, Korea, St. Louis, USA, and Melbourne, Australia. The theoretical lines are obtained using (

In this work, we have used the data reported by Oke [

Figure

UHI intensity as a function of the urban length scale. Symbols represent data as reported by Oke [

Thus far, in this and our previous work [

Figures

The effect of the wind speed on the UHI intensity in Chambly, Marieville, St. Basile-Le Grand, St. Cesaire, St. Pie, Ste. Angele-de Monnoir, and Ste. Madeline. Symbols represent data as reported by Oke [

The effect of the wind speed on the UHI intensity in Chambly, Marieville, and St. Basile-Le Grand.

The effects of wind speed on UHI intensity for St. Cesaire, St. Pie, and Ste. Angele-de Monnoir.

Effects of the urban length scale and the wind speed on the urban heat island effect can be quantified through time-dependent energy balance. The heating of the urban surfaces during the daytime sets the initial temperature, and this overheating is cooled during the nighttime through mean convection motion over the urban surface, resulting in an exponential decay in the temperature. This overheating is cooled during the nighttime, through mean convection motion over the urban surface, resulting in an exponential decay in the temperature. The solution to the time-dependent energy balance equation reproduces this temporal decay with good accuracy, with the main factors being the length scale of the urban area and the wind speed. The minimum temperature reached at the end of night-time cooling period then corresponds to the UHI intensity, which increases with increasing urban length scale and decreasing wind speed. The wind speed effect is also accurately retraced using this method; however, different correction factors are required for different cities, indicating the effects of the urban surface heat content, structural morphology, and density. Thus, using a small number of readily available data for the urban length scale and the wind speed, the UHI intensity can be described with possible projections for future trends. This approach can be used in planning of energy resources, as well as any large areas of concrete surfaces needed for renewable or other power generation. About one-third of the electric power goes to satisfy the residential consumption in United States, and thus understanding of the electricity demand due to UHI increase is a key component in planning for renewable energy production.

The authors declare that there is no conflict of interests regarding the publication of this paper.