Initial approximation of the implications for architecture due to climate change

被引:31
作者
Andric, Ivan [1 ]
Le Corre, Olivier [2 ]
Lacarriere, Bruno [2 ]
Ferrao, Paulo [3 ]
Al-Ghamdi, Sami G. [1 ]
机构
[1] Hamad Bin Khalifa Univ, Coll Sci & Engn, Div Sustainable Dev, Doha, Qatar
[2] IMT Atlantique, Dept Syst Energet & Environm, UMR CNRS GEPEA, Nantes, France
[3] IN Ctr Innovat Technol & Policy Res, Inst Super Tecn, Lisbon, Portugal
关键词
Climate change; building modelling; architectural simulation; heating demand; cooling demand; COOLING ENERGY DEMAND; LIFE-CYCLE ASSESSMENT; BUILDING HEAT DEMAND; RESIDENTIAL BUILDINGS; OFFICE BUILDINGS; REGIONAL CLIMATE; GREEN FACADES; CHANGE IMPACT; ADAPTATION MEASURES; LIVING WALLS;
D O I
10.1080/17512549.2018.1562980
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
This review paper organizes and summarizes the literature regarding climate change impacts on future building energy demand. The approaches used for the creation of future weather climate and building renovation scenarios, as well as building energy modeling at different scales, are evaluated. In general, it can be concluded that future heating demand could decrease (7-52%), while cooling demand could increase significantly (up to 1050%). The decrease/increase rates varied significantly depending on the climate and case study building(s) considered, with buildings and building energy systems located in extreme climates being more sensitive to such changes. The main uncertainty of the predicted increase/decrease rates can be assigned to climate models and forecasted weather data. Nonetheless, such forecast and risk assessment are necessary for sustainable development of urban environment and associated energy systems. Further development of dynamic large-scale building energy simulation tools is required, along with the development of large-scale building renovation measures and strategies that take into account additional aspects (such as economic and societal). Moreover, continuous efforts are required in further climate models' improvement and uncertainty reduction.
引用
收藏
页码:337 / 367
页数:31
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