As the urgency to mitigate climate change intensifies, the achievement of zero carbon targets in the built environment has become a critical objective. Building retrofitting plays a vital role in reducing energy consumption and carbon emissions in existing buildings. This paper presents an approach that combines Building Information Modeling (BIM) with multiple domains to strive for zero carbon targets in building retrofit projects. The proposed approach is based on a dynamic multi-parameter analysis that integrates indoor comfort, energy savings, CO_2eq reduction, and the social cost of carbon while considering investment costs. Renewable energy technologies, such as photovoltaic panels and solar thermal systems, are emphasized to achieve the desired zero-carbon outcomes. Real-time monitoring mechanisms enable continuous performance evaluation and adaptive retrofit strategies for further energy savings. This approach is validated through a case study of an existing thermal bath building, known as “Terme Lucane”, located in southern Italy. The results of the study demonstrate significant reductions in energy consumption and carbon emissions, highlighting the potential of the proposed approach to achieve zero carbon targets through the integration of multi-data BIM implementation. These findings offer a promising pathway for building retrofit projects aiming for zero carbon targets through multi-data BIM modeling.

One of the primary global objectives is to decrease building energy consumption to promote energy efficiency and environmental sustainability. The large-scale food retail trade sector accounts for over 15% of total primary energy consumption in Europe, posing a significant challenge to the transition towards green energy. This study proposes a simple method for energy efficiency, environmental sustainability, and cost-saving assessment and improvement in large-scale food retail trade buildings. It aims to analyze the energy and environmental performance of building–plant systems, establishing an interactive network to assess intervention potential for the energy transition. The investigation focuses on the proper selection and analysis of the benefits of retrofit solution implementation, emphasizing potential energy savings in current and future climate change scenarios. Dynamic simulation with the Building Energy Model (BEM) was used to evaluate the impacts of building–plant system retrofit solutions, such as high thermal insulation, photovoltaic (PV) panels, Light Emitting Diode (LED) installation, waste heat recovery, and improvement in refrigeration units. The results show a reduction in annual energy consumption for the PV panel installation by up to 29% and lighting systems with high-quality LED to 60%. Additionally, CO₂ emissions can be decreased by up to 41% by combining these two strategies.

Artificial lighting accounts for roughly 30% of total electricity use in supermarkets and significantly affects product perception, customer experience, and purchasing behavior. Increasing the availability of natural light, combined with appropriate architectural energy retrofitting strategies, offers a major opportunity to reduce electricity demand. This study proposes a data-driven framework for evaluating energy retrofit strategies in commercial buildings, integrating Building Information Modeling (BIM) and Building Energy Modeling (BEM). A parametric methodology is used to evaluate multiple architectural retrofitting scenarios aimed at enhancing daylighting and reducing artificial lighting demand, while improving energy efficiency and environmental performance. The scenarios investigated include variations in skylight geometry and orientation, glazing type, photovoltaic integration, and advanced lighting controls. Three Key Performance Indicators (KPIs)—real energy effectiveness, lighting control performance, and environmental impact—are used to assess how design modifications influence energy use, indoor lighting quality, and environmental performance. The methodology is applied to three real food-retail buildings in Italy. Results show that lighting energy consumption can be reduced by up to 60% in scenarios combining LED technology with smart control systems, while total building electricity savings vary across case studies depending on building characteristics and usage patterns. Environmental impact reductions of approximately 15–20% are achieved, reflecting both operational and life-cycle improvements. The study demonstrates the potential of parametric architectural retrofitting to support multi-criteria decision-making for sustainable refurbishment of food-retail environments.