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- W3046284889 endingPage "141300" @default.
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- W3046284889 abstract "Given the large transformation and fast-growing population that the Greater Toronto Area (GTA) is facing, and the increasing impact of climate change in urbanized areas, it is crucial to investigate strategies that could mitigate the effects of heat waves. In this paper, the effects of greenery enhancements are investigated using mesoscale and microscale simulations performed by the Weather Research and Forecasting model and the ENVI-met model, respectively. In particular, two vulnerable areas located in the GTA are investigated. Comparing the results of simulations with measurements show the differences in how mesoscale and microscale models predict the meteorological processes happening within the urban canopy and the local climate. Then, two mitigation scenarios, a moderate green scenario (MGS) and an intensive green scenario (IGS) are assessed considering different increases in the vegetation area. The results of the mesoscale simulations show that by increasing the greenery canopy, the maximum daily air temperature decreases by 1.6 to 2.3 °C, while the relative humidity increases by 10% to 12%. The microscale simulations show that increasing the tree canopy would cool the air temperature by 0.5 °C to 1.4 °C locally. Overall, depending on wind conditions and the arrangement of buildings and existing green areas, the cooling effect is shown to have an impact on up to 250 m downwind from the new green area locations. Finally, this study demonstrates that both mesoscale (WRF) and microscale (ENVI-met) modeling confirm similar results in how greenery enhancements may improve the human thermal comfort in the continental climate of the GTA." @default.
- W3046284889 created "2020-08-07" @default.
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- W3046284889 date "2020-12-01" @default.
- W3046284889 modified "2023-10-16" @default.
- W3046284889 title "Effects of greenery enhancements for the resilience to heat waves: A comparison of analysis performed through mesoscale (WRF) and microscale (Envi-met) modeling" @default.
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- W3046284889 doi "https://doi.org/10.1016/j.scitotenv.2020.141300" @default.
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