Scenario-based dynamic life-cycle assessment of large-space public buildings using a dual-functional unit approach: Gymnasium cases across climate zones in China

Large-space public buildings such as gymnasiums combine material-intensive long-span structures, large enclosed volumes, and event-driven occupancy, yet their life-cycle carbon performance remains insufficiently understood. Static life-cycle assessment (LCA) overlooks time-dependent variations in emission factors and cannot capture the distinct physical and service drivers of embodied and operational emissions in such typologies. This study develops a scenario-based dynamic LCA (DLCA) framework integrating five time-varying factors—temporal adjustment of material emission factors, electricity grid decarbonisation, climate change, envelope and HVAC degradation, and evolving usage patterns—and proposes a dual-functional unit (Dual-FU) approach that normalises embodied emissions by enclosed volume (kg CO₂e/m³) and operational emissions by delivered service (kg CO₂e/person-hour). Greenhouse gas emissions are characterised using static GWP₁₀₀ factors based on IPCC AR6, with temporal dynamics captured at the inventory and scenario levels. Applied to three gymnasiums across distinct climate zones in China, the framework reveals that dynamic assessment reduces total life-cycle emissions by 7.0–34.6% relative to the static baseline, with grid decarbonisation as the dominant driver (10.3–40.8% reduction). Under dynamic conditions the embodied-carbon share rises to 44.1%, underscoring the growing importance of early-stage material and structural decisions. The Dual-FU framework resolves distortions inherent in conventional area-based normalisation: the volume-based unit eliminates the systematic bias that penalises high-volume geometries, while the service-based unit distinguishes efficiency gains from changes in utilisation intensity. These findings demonstrate that incorporating temporal dynamics and typology-sensitive functional units into life-cycle GHG assessment provides a more reliable basis for differentiated carbon benchmarking of large-space public buildings across climate and regional contexts.