To meet climate-change mitigation needs, one must go beyond operational energy consumption and related greenhouse gas (GHG) emissions of buildings and address their full life cycle. Considering global GHG reduction targets, the results of this study emphasise the urgent need to reduce GHG emissions of buildings by optimising both operational and embodied impacts.

In this work, the authors propose a data-driven approach that enables large-scale automatic analysis of heat load patterns in district heating networks without requiring prior knowledge.