We may be retrofitting wrong: How LCA exposes hidden trade-offs of carbon footprint and costs of optimal energy retrofitting upgrades

This study presents a Life Cycle Assessment (LCA)-based multi-objective optimization model for energy retrofitting of residential buildings. Using a cradle-to-cradle scope to capture GWP impact category, we assess operational and embodied emissions throughout the building's life cycle. A Non-dominated Sorting Genetic Algorithm (NSGA-II) is employed to optimize retrofit measures for passive and active systems, aiming to minimize Life Cycle Costs (LCC) and Life Cycle Carbon Footprint (LCCF). Applied to a typical German single-family house, the model not only reveals significant differences between LCA-based and conventional operational-energy optimization, but also demonstrates how system-level retrofit decisions change when LCA is integrated. Results show that conventional optimization produces solutions not only more costly and carbon-intensive, but also sub-optimal, as they fail to account for impacts of other building life cycle phases. In contrast, the LCA-based method achieves average reductions of 33 % in LCCF and 17 % in LCC, with maximum reductions of 53 % and 47 %, respectively. Further analysis reveals that the true LCCF and LCC impacts of the conventional method are, on average, 61 % and 203 % higher, respectively. Moreover, system-level analysis indicates that integrating LCA leads to reduced thickness of insulation layers, a slightly more cautious adoption of photovoltaics, and a shift in preferred HVAC configurations, favoring systems such as heat pumps. These findings underscore the study's innovative contribution in illustrating how incorporating LCA into the optimization process fundamentally reshapes retrofit choices at the system level, revealing potential misalignments in current renovation practices that prioritize passive measures over more impactful active systems.