Uncertainty analysis for variables affecting the whole life carbon performance of nearly zero energy residential building renovation

This study investigates the impact of retrofit strategies on the whole-life greenhouse gas emissions (wLCE) and global cost (GC) for two representative Belgian residential archetypes. Six renovation alternatives combining envelope, system, and renewable energy upgrades are optimized using the Non-dominated Sorting Genetic Algorithm (NSGA-II) within a dynamic simulation framework integrating building energy modelling, life-cycle costing, and life-cycle assessment. Uncertainty analysis (UA) based on Latin Hypercube Sampling assesses the sensitivity of wLCE and GC to future electricity mix scenarios, climate change, energy prices, occupants’ behavior, materials’ service life and quantities. A clear trade-off emerges: deeper emission reductions entail higher investment and life-cycle costs. The best compromise for both archetypes is the intermediate retrofit using biobased materials (S.01b), while high-performance options (S.02a–S.02b) achieve the lowest wLCE but require substantially higher investment. Environmental payback periods range from 14 to 30 years, confirming retrofit effectiveness in reducing wLCE, whereas economic payback exceeds 50 years due to current energy market conditions and limited carbon taxation. Finally, UA reveals that energy price variability most strongly influences GC, while electricity mix, climate change, and occupants’ type have the greatest effect on wLCE. Temperature setpoints, materials service life, and materials quantities strongly impact both indicators. This study highlights the need for revised policy frameworks and stronger financial incentives to improve retrofit financial feasibility and accelerate the transition towards cost-effective, low-carbon building renovations.