Andrea Zonato

and 7 more

In the present work, the sensitivity of near-surface air temperature and building energy consumption to different rooftop mitigation strategies in the urban environment is evaluated by means of numerical simulations in idealized urban areas, covering a large spectra of possible urban structures, for typical summer and winter conditions. Rooftop mitigation stategies considered include cool roofs, green roofs and rooftop photovoltaic panels. In particular, the latter two rooftop technologies are simulated using two novel parameterization schemes, incorporated in the mesoscale model Weather Research and Fore-5 casting (WRF), coupled with a multilayer urban canopy parameterization and a building energy model (BEP+BEM). Results indicate that near-surface air temperature within the city is reduced by all the RMSs during the summer period: cool roofs are the most efficient in decreasing air temperature (up to 1°C on average), followed by irrigated green roofs with grass vegetation and photovoltaic panels. Green roofs reveal to be the most efficient strategy in reducing the energy consumption by air conditioning systems, up to 45%, because of their waterproof insulating layer, while electricity produced by photovoltaic 10 panels overcomes energy demand by air conditioning systems. During wintertime, green roofs maintain a higher near-surface air temperature than standard roofs, because of their higher thermal capacity and the consequent release of sensible heat during nighttime. On the other hand, photovoltaic panels (during nighttime) and cool roofs (during daytime) reduce near-surface air temperature, resulting in a reduced thermal comfort. Green roofs are the most efficient rooftop mitigation strategy in reducing energy consumption by heating, and are able to reduce the energy demand up to 40% for low rise buildings, while cool roofs 15 always increase consumption due to the decreased temperature. The results presented here show that the novel parameterization schemes implemented in the WRF model can be a valuable tool to evaluate the effects of mitigation strategies in the urban environment. Moreover, this study demonstrates that all rooftop technologies present multiple benefits for the urban environment , showing that green roofs are the most efficient in increasing thermal comfort and diminish energy consumption, while photovoltaic panels can reduce the dependence on fossil fuel consumption through electricity generation.

Andrea Zonato

and 7 more

This paper describes and evaluates novel parameterizations for accounting for the effect of rooftop mitigation strategies on the urban environment, in the context of the mesoscale model Weather Research and Forecasting (WRF), coupled with a urban canopy parameterization and a building energy model (BEP+BEM). Through the new implementation, the sensitivity of near-surface air temperature and building energy consumption to different rooftop mitigation strategies is evaluated by means of numerical simulations in idealized urban areas, for typical summer and winter conditions. Rooftop mitigation strategies considered include cool roofs, green roofs and rooftop photovoltaic panels. Results indicate that near-surface air temperature is reduced by all the RMSs during the summer period: cool roofs are the most efficient in decreasing air temperature (up to 1 °C on average), followed by green roofs and photovoltaic panels. Green roofs reveal to be the most efficient strategy in reducing the energy consumption by air conditioning systems, up to 45%, while electricity produced by photovoltaic panels overcomes energy demand by air conditioning systems. During wintertime, green roofs maintain a higher near-surface air temperature than standard roofs. On the other hand, photovoltaic panels and cool roofs reduce near-surface air temperature, resulting in a reduced thermal comfort. The results presented here show that the novel parameterization schemes implemented in the WRF model can be a valuable tool to evaluate the effects of mitigation strategies in the urban environment. The new model is available as part of the public release of WRF in version 4.3.