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Towards net-zero carbon buildings: tackling uncertainty when predicting carbon footprints (UNCARB)

This research will improve how uncertainty is treated during life cycle assessment (LCA) of construction products and of whole buildings.

Budget

£344,000

Project status

Complete

Duration

16 Aug 2021 to 19 Jul 2024

To counter significant levels of climate change and biodiversity loss, the UK and numerous other countries have set targets for net-zero greenhouse gas emissions. Rapid reductions in the built environment are crucial, since it drives 42% of global energy-related carbon dioxide emissions.

To achieve net-zero carbon buildings, we must reduce both:

  • operational carbon: emissions caused by a building's operational use
  • embodied carbon: emissions caused by 'everything else', such as materials manufactured, transportation to site, refurbishment, and disposal

Given the huge amount of construction required for new build and retrofit around the world, it's critical to address embodied carbon while we continue to tackle operational carbon. The UK Government's 'Industrial Strategy: Construction Sector Deal' aims to halve the greenhouse gas emissions from the built environment by 2025, and to shift focus from operational to whole-life performance. Since May 2019, over 1000 architecture and engineering practices have committed to reducing both embodied and operational carbon (these are together referred to as whole-life carbon (WLC)). The Royal Institute of British Architects has set WLC targets for 2030 and 2050 in its 'Climate Challenge', and the new London Plan will require all 'referable planning applications' to calculate and reduce WLC.

However, there are persistent challenges to predicting embodied (and therefore whole-life) carbon, and thus minimising it in practice. In particular, uncertainty is typically ignored.

Tackling uncertainty

At the levels of individual construction products and whole buildings, models are typically deterministic in nature, producing single-point estimates of WLC. In practice, it is unclear how confident designers and engineers can be that one option will be lower carbon than another. In other scientific disciplines, probabilistic approaches are more common, producing results with confidence intervals and using statistical significance tests when making comparisons. Such rigour is essential for predicting the WLC of buildings to ensure that low-carbon design intentions are achieved in reality.

Our research aims to significantly improve the treatment of uncertainty when predicting the WLC of construction products and of whole buildings. We will work with project partners across the supply-chain of low-carbon buildings, including product manufacturing, low-carbon policy, and the design of structures and buildings. At product level, we will improve the treatment and communication of uncertainty in Environmental Product Declarations. At building level, we will develop and test a probabilistic approach for predicting whole-life carbon through the design process. To achieve impact, we will engage international initiatives and standards that will define industry practice into the future.

Our partners

During our project, we'll consult and engage a steering group of the following project partners:

  • Ben Hopkins, Bennetts Associates
  • Chris Foster, EuGeos Ltd
  • Grant Stratton, Integral Engineering
  • Jess Hrivnak, RIBA
  • Joe Jack Williams, FeildenCleggBradleyStudios
  • Joe Williams, Integral Engineering
  • Jonathan Roynon, Buro Happold
  • Katarzyna Lewandowska, Bennetts Associates
  • Mirko Farnetani, Skidmore, Owings & Merrill
  • Nick Coleman, Tata Steel
  • Pat Hermon, BRE
  • Simon Sturgis, Targeting Zero
  • Stephen Richardson, World Green Building Council
  • Tim Mander, Mander Engineering
  • Will Arnold, IStructE

Acknowledgements

As well as our steering group, we'd like to thank the following for their interactions before or during the project:

  • Pascal Lesage
  • Sophie Parsons
  • Phil Northcott
  • Stacey Smedley
  • Mina Hasman
  • Craig Jones
  • Tim Young

Research outputs

View project outputs

Contact us

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