The role of green roofs on microclimate mitigation effect to local climates in summer

Abstract

Although there is a large body of previous studies on the cooling effect of green roofs on urban heat islands (UHIs), more empirical studies with an experimental setting measuring the role of green roof on mitigating urban heat should be considered. The purpose of this research is to determine the air temperature difference between green and bare roofs located on two buildings in the same local climate zone, and calculate the expected cooling effect extended from the green roof to the local climate. The study site consisted of an extensive green roof and a bare roof which were close to each other and were located in a highly built-up same area. During the three and a half clean days of testing in the middle of summer, air temperature data were collected from each roof using an air temperature logger and a local automatic weather station close to both roofs; these data were then converted to hourly data. The data were analyzed by the t test, ANOVA test, and a regression analysis to determine the heat mitigation effect of green roofs. As a result, the green roof's air temperature showed much lower than the bare roof's and followed the local station's air temperature change during the day. At night the air temperature difference between the two roofs was only slight and the green roof's air temperature kept lower than the local station's. Thus, even extensive green roofs can reduce air temperature through their cooling effects from their vegetation and substrates against solar radiation. The established models reported that the green roof contributed to lowering air temperatures in a local climate zone, while the bare roof made such zones more heated. The findings of this study contribute to the existing literature by proving that green roofs can be expected to help cool down not only at the small scale with building units, but also at the broader scale of urban district area. The study also gives field-experimented values to be used as updated variables to local climate simulation models.