Distinctly Ambitiouswww.hw.ac.uk

Distinctly Ambitiouswww.hw.ac.uk

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% of occupied hours > 28°C

Current climate Med emission, 2030 Med emission, 2050 Med emission, 2080

Overheating threshold

The risk of buildings overheating in a low-carbon climate change futureProf PFG Banfilla , Dr DP Jenkinsa, Prof G Gibsonb, Dr G Menziesa, Dr S Patidarb, Dr M Gula

aUrban Energy Research Group, School of Built EnvironmentbSchool of Mathematical and Computer Sciences

The projectThe aim of the project was to design a method that enabled probabilistic climate projections to be incorporated into building design. The focus was on using such a method to identify the potential risks of buildings “failing” in the future due to climate and inappropriate design. The main failure criteria concerned thermal comfort and HVAC systems. The work combines statistical and building sciences with various user feedback techniques to adequately convey the opinions of practitioners.

LCF regression toolThe LCF tool uses Principal Component Analysis to identify a correlation between hourly climate variables and building simulation outputs. With a regression relationship established, the tool is applied to hundreds of climate files (such as those from the Weather Generator) to produce hourly internal temperatures, heating loads and cooling loads for each climate file. This information can then be collated into useful output, as shown below:

Applying UKCP09The UK Climate Projections 2009, through the Weather Generator, can provide thousands of equally probable climate descriptions across several emission scenarios and timelines to 2099.

Manually processing all this climate information through detailed building simulation is impractical. The LCF project applied statistical techniques to detailed dynamic building simulation as a form of model emulation. This allows the full spectrum of climate projections to be processed through a given building design.

PractitionersTo understand the requirements of building designers, a series of focus groups, questionnaires and interviews were carried out . This also provided feedback for the application of the tool, influencing the form of output provided where complex probabilistic information is generated alongside more immediately intuitive colour-coded risk analysis.

The feedback suggested that the risk of future overheating was highest in the non-domestic sector, although dwellings in the south of the UK might also cause concern. There was a general agreement that a clear and concise mechanism for quantifying this risk would be welcome.

Prof Phil BanfillP.F.G.Banfill@hw.ac.uk

% chance of failure81-10061-8041-6021-400-20

No Adaptation With adaptations

2030, LowCurrent climate

2080, Low2050, High

2050, Medium2050, Low2030, High

2030, Medium

2080, Medium2080, High

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