Healthy and Energy-Efficient Building Retrofits: A Systematic Review of CFD, Digital Twins, and Occupant-Centred Intelligence

Abstract

Abstract

Building retrofits are essential for reducing carbon emissions, improving energy efficiency, and upgrading ageing building stocks. However, interventions such as insulation, airtightness improvement, glazing replacement, and HVAC modernisation can also modify airflow, pollutant transport, thermal comfort, moisture balance, overheating risk, and occupant health. This systematic review examines the role of Computational Fluid Dynamics (CFD), Digital Twins (DTs), occupant behaviour modelling, and machine learning in supporting intelligent, health-centred retrofit strategies. Using a PRISMA-informed methodology, studies applying CFD, DTs, or hybrid approaches to retrofit performance assessment were synthesised. The findings show that conventional energy models are useful for estimating annual energy demand but often fail to capture local airflow patterns, contaminant hotspots, thermal stratification, ventilation effectiveness, and occupant exposure risks. CFD provides detailed insight into airflow, heat transfer, pollutant dispersion, moisture transport, ventilation performance, and airborne infection transmission. Occupant behaviour, including walking, window opening, door use, and occupancy schedules, strongly influences airflow and contaminant pathways, especially in airtight retrofitted buildings. DTs further enhance retrofit assessment by integrating sensor data, predictive simulation, and adaptive control for continuous performance optimisation. Machine learning methods are increasingly used to accelerate CFD predictions, reconstruct indoor environmental fields, and support near-real-time decision-making. Although retrofits can improve winter comfort and reduce heating demand, they may also increase overheating, CO₂ concentrations, VOC accumulation, moisture-related problems, and infection vulnerability when ventilation is inadequate. To address these trade-offs, this review proposes a Retrofit Suitability Index (RSI) integrating energy efficiency, indoor air quality, thermal comfort, health protection, affordability, and user acceptance for healthier, resilient, occupant-centred retrofits.