Arup collaborated with SkenarioLabs to model city-scale retrofit interventions across Leeds, Newcastle, and Nottingham.
Arup Group Limited, founded in 1946, is a British multinational corporation that provides global services in all aspects of the built environment – from design to engineering, architecture, planning, and consulting. Arup employs around 16,000 people across 35 countries, having participated in various projects in more than 160 countries.
With over 300 councils in the UK having declared a climate emergency, many are taking action to reduce carbon emissions and manage impact locally. In 2020, BEIS commissioned the City Decarbonisation Delivery Programme, which focused on methods to decarbonise heat across several major UK cities.
The primary challenge in tackling large-scale decarbonisation, particularly when dealing with large portfolios of highly heterogeneous building stock, is the lack of access to extensive data. Limitations in the ability to model the impact of retrofit scenarios across thousands of properties obscure the path to net zero.
Arup collaborated with SkenarioLabs to develop virtual representations of several thousand non-domestic, publicly-owned properties across Leeds, Nottingham and Newcastle. The model included multiple building types and provided a solid baseline for further iteration and scenario analysis.
The SkenarioLabs platform enables property data to be quickly collected, collated and analysed. Plus our machine-learning-led models provide a set of derived assumptions in instances where data is unavailable, which can be updated and replaced as required.
By leveraging SkenarioLabs’ advanced modelling capabilities and Arup’s extensive expertise, we successfully delivered comprehensive, high-quality analysis for our clients.
This work marked the beginning of our partnership, which has since expanded to fulfil several projects for local and central governments across the UK. Our collaborative efforts provide significant value through both a time and cost-saving. Engineers are freed from lengthy data collection and cleansing processes, and can instead focus their efforts on detailed analysis concerning interventions and systems design.
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