par Hermand, Séverine ;Bouillard, Philippe ;Khan, Ahmed Z.
Référence International 29th PLEA (Passive & Low Energy Architecture) Conference(10-12 September 2013: Munich, Germany), Sustainable Architecture for a Renewable Future
Publication Publié, 2013
Publication dans des actes
Résumé : This work aims at exploring the effects of the urban texture on building energy consumption in Belgium. The focus of this study is in Brussels, Belgium located in an Oceanic climate (Köppen climate classification) where an important number of challenges in terms of urban planning exist. Indeed, since Brussels is limited by its political boundaries, the capital needs to work with the density and the reconversion of the brownfield in order to accommodate more than 170 000 new inhabitants by 2020. The hypothesis is: open spaces in Brussels, have an energetic impact on buildings’ envelope surrounding the “in-between spaces”. The motivation for this work is not only showing the urban strategy in Brussels in terms of sustainable renovation, but also understanding which would be the best strategies to design the open spaces on a given site. An analysis of the LT method and DEM’s will be provided in order to outline a methodological framework for assessing the role of in between spaces on the energetic performance of buildings in the Brussels-Capital Region. This kind of analysis is particularly well adapted for the district scale or block. Because the production level of greenhouse gas emissions is not the same in all cities (eg "Oslo produces ten times less greenhouse gas emissions per capita than Melbourne, despite comparable levels of life") degree of freedom seems to be available in the urban design. Moreover, studies like the study of the Urban Morphology Lab, CSTB, Paris has shown “that an efficient urban fabric alone can reduce energy consumption and carbon emissions by a factor of 2 ». Using analytical and visual tools we will demonstrate how the European capital could design and manage open spaces to provide a social and energy efficient model.