Abstract
Green roofs (GRs) and green walls (GWs) are good strategies for urban greenery. This study explores the cooling load benefits of GRs and GWs simultaneously for comparison. EnergyPlus simulation programme is used for estimating annual cooling load reduction for different buildings and scenarios in Hong Kong. In simulating GR, a built-in thermal model is used. For GWs, a self-developed thermal model is used, which has been developed and validated in our previous study. The simulation covers a single-storey building and two multi-storey buildings, each with four different coverage areas for GR and GWs. The GWs are assumed to be on building facade facing the west, east, north, and south. Results reveal that both GRs and GWs are capable of protecting building envelop from reaching higher temperatures and of reducing cooling load. In a single-storey building with an equal area of GR and GW, GR is more effective in energy saving. However, in a multi-storey building GR can provide energy benefits only to the topmost floor. An equal area of GW can provide benefits to multiple floors, which may result in higher benefit. Furthermore, the available area for GWs is larger. When considering the effect of orientation of GW, the west-facing GW contributes to the highest annual energy saving. It should be noted that the effect of orientation may differ with location and climatic conditions, and also with the shading effect of surrounding buildings. Therefore, installation of GRs or GWs should be considered case by case, taking into consideration the scale and surroundings of the building, the climatic condition, and area of greenery coverage.
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Acknowledgements
The work described in this paper was supported by the Hong Kong PhD Fellowship Scheme at the City University of Hong Kong and a grant from the Research Grants Council of the Hong Kong Special Administrative Region, China (Project No. 11274516).
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Dahanayake, K.C., Chow, C.L. Comparing reduction of building cooling load through green roofs and green walls by EnergyPlus simulations. Build. Simul. 11, 421–434 (2018). https://doi.org/10.1007/s12273-017-0415-7
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DOI: https://doi.org/10.1007/s12273-017-0415-7