RICS and a group of founding members have launched CLEAR - the Coalition for Life cycle Emissions Alignment and Reporting, to align how whole life carbon emissions from buildings and infrastructure are measured and reported. The Global Building Data Initiative, which Martin Röck helped found and serves as chief scientist, is among the founding members.
The founding group spans assessment, design, materials, software and standards: 2050 Materials, AECOM, Arcadis, ASHRAE, Autodesk, Avison Young, Buro Happold, GBDI, Heidelberg Materials, Mace Consult, Morgan Sindall, ORIS Materials Intelligence, Turner & Townsend, WAP (an SLR company), WBCSD and We2Sure.
What it actually sets out to do
- Quantify the divergence first. Analyse and measure the differences between the leading carbon measurement approaches, rather than asserting that they disagree and moving on.
- Then harmonise. Develop a framework for bringing assessment and reporting methodologies into line.
- Then help others start aligned. Produce guidance so that countries and policymakers building methodologies now can build them globally consistent from the outset, instead of harmonising painfully later.
It is positioned to support the Market Transformation Action Agenda and the Buildings Breakthrough, which are pushing in the same direction.
Why we care about this one
The practical consequence for an assessor is a move away from modelling every project from scratch towards assessments that are comparable, with models and data that survive a change of jurisdiction. For the people building tools and standards, it means building once and scaling across markets, with cleaner interoperability with BIM and LCA software and benchmarking data that can actually be compared.
This is the problem our own work keeps running into from the other side. A global buildings database is only as useful as the comparability of what goes into it, and every benchmark study we have worked on has begun by reconciling datasets that were never meant to be reconciled. Harmonising the methods is the part that makes the data worth collecting.
More at rics.org.