Assessing the impact of climate change on building heating and cooling energy demand in Canada

被引:226
作者
Berardi, Umberto [1 ]
Jafarpur, Pouriya [2 ]
机构
[1] Ryerson Univ, Architectural Sci, Toronto, ON, Canada
[2] Ryerson Univ, Environm Sci, Toronto, ON, Canada
基金
加拿大自然科学与工程研究理事会;
关键词
Climate change; Building performance simulation; Future weather file; Statistical and dynamical downscaling; Energy use intensity; Greenhouse gas emission; TYPICAL METEOROLOGICAL YEAR; FUTURE WEATHER DATA; PERFORMANCE; GENERATION; FILES; PATTERNS;
D O I
10.1016/j.rser.2019.109681
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
In recent years, the building sector has received increasing attention with attempts to limit its energy consumptions and GHG emissions. In fact, buildings account for more than 30% of the overall energy demand worldwide, with projections for increases in this quota due to climate changes, urbanization, and higher living comfort standards. This study investigates the effects of climate changes on the heating and cooling energy demand of buildings in the most populated urban region in Canada, i.e. the city of Toronto in Ontario. Statistical and dynamical downscaling methods are utilized to generate several future weather files, starting from different baseline climates including the old Canadian Weather Year for Energy Calculation CWEC (representing the 1959-1989 period) and the new CWEC 2016 (representing the 1998-2014 period). In dynamical downscaling, a regional climate model is used to obtain a finer resolution than traditional general circulation models. The generated future weather data sets are then used for simulating the energy demand of 16 building prototypes. The simulation results show an average decrease of 18%-33% for the heating energy use intensity, and an average increase of 15%-126% for the cooling energy use intensity by 2070, depending on the baseline climatic file of use and building typology. The forecasted GHG emissions of each building prototype are then discussed. The results demonstrate the need to perform building modelling with sensitivity analysis of future climate scenarios in order to design more resilient buildings.
引用
收藏
页数:12
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