Prospective Life-Cycle Cost and Environmental Assessment of MWCNT-Reinforced Self-Sensing Ternary Mortar for Historic Masonry Restoration: A Field Case Study

Historic masonry restoration requires compatible materials and decision-support frameworks that account for long-term economic, environmental, and monitoring-related implications. This study presents a prospective, scenario-based comparison of two complete restoration strategies for a real historic masonry case study: a conventional ternary restoration mortar combined with periodic visual inspection and an MWCNT-reinforced ternary restoration mortar combined with embedded electrical-resistance monitoring. Life-cycle costs were assessed over a 30-year reference period using Activity-Based Costing, while environmental performance was evaluated using the Environmental Footprint (EF) 3.2 method. The nano-reinforced approach had a 14.72% higher initial implementation cost and a 29.19% higher cost before the future intervention when monitoring expenditure was included. Under the assumed future intervention cases, however, its calculated 30-year life-cycle cost was lower by 11.25%, 16.63%, and 9.58% under the expected, optimistic, and pessimistic cases, respectively. Monte Carlo analysis yielded a lower median cost for the nano-reinforced approach, although the 95% uncertainty interval of the paired cost difference crossed zero. Inclusion of the screening-level SHM hardware inventory resulted in a 5.83% higher baseline climate-change impact for the nano-reinforced approach, with 103.87 kg CO2 eq compared with 98.15 kg CO2 eq for the conventional approach. Lower climate-change impacts emerged only after application of the assumed future intervention extents, with calculated reductions of 5.45%, 6.32%, and 5.14% across the three cases. The results therefore indicate that the comparative performance of the monitoring-enabled strategy is conditional on the adopted intervention assumptions and system boundaries rather than on demonstrated improvements in intrinsic durability. The proposed framework provides a structured basis for evaluating how material selection, monitoring requirements, and future intervention planning jointly influence long-term restoration decisions.