Evaluating climate change pathways through a building's lifecycle based on Dynamic Life Cycle Assessment

Climate change impact of a building was evaluated through a Dynamic Life Cycle Assessment (DLCA) methodology with the aim at demonstrating the feasibility of DLCA and the usefulness of such approach in the building sector. The methodology uses dynamic thermal simulation for energy consumption, databases for the building sector, a new developed database for temporal parameters of buildings, DyPLCA tool for dynamic LCI calculation. Clime change indicators were obtained in function of time for 500 years time span: radiative forcing, cumulated radiative forcing and global mean temperature change. Results revealed that each building component has its own climate footprint from which mitigation actions can be deduced. Results should always be placed in the climate context, in this case, the critical period 2030–2050, a turning point for limiting the temperature increase at 1.5 °C, with an objective of zero net emission beyond 2050. Dynamic indicators are well adapted for accounting the effect of biogenic CO2 and can be used to simulate strategies for GHGs neutralization. The main outcome of the comparison DLCA – LCA is that the results can be greatly different, especially when biogenic carbon is present (case of bio-based materials): i) the ranking and proportion of the contributors can change according to the time horizon for a given dynamic indicator (cumulative radiative forcing and global mean temperature change), ii) the ranking and proportion of the contributors can be different between the considered indicators, demonstrating the need of a more detailed assessment in the context of the imminent climate target. •A full dynamic LCA for buildings was demonstrated through a case study.•The evolution in time of the building and its components was quantified.•Temporal LCI was calculated for all foreground and background processes.•Dynamic indicators bring out rich information for climate mitigation decisions.•Bio-based systems promise near net zero effects for dynamic climate indicators.