Elsa Buvik’s scientific contributions

Addressing greenhouse gas emissions in the built environment is crucial due to its significant contribution to the total equivalent CO 2 emissions. Recent efforts have primarily focused on enhancing energy efficiency, resulting in notable reductions in energy consumption. However, the next phase of decarbonization in the building sector is increasingly emphasizing the use of materials with lower embodied energy and CO 2 . A novel hybrid unitized façade (HUF) system has been developed, specifically designed for cold climates, that integrates aluminium and timber. This study aims to assess the carbon footprint of the HUF system, where timber is used to partially replace high-embodied-energy aluminium frame. For this, a comprehensive cradle-to-grave life cycle assessment using One Click LCA, combined with a building energy tool that incorporates future weather data, is employed. This assessment includes the materials and quantities involved in constructing a HUF unit, incorporating their specific environmental product declarations. The study explores two strategies for long-term sustainability: (i) examining the impact of retrofitting the façade system elements in accordance with their respective service life and (ii) examining the impact of a complete retrofit of the façade system at 30 years. This evaluation will be conducted for a generic office building model in Oslo. The study aims to contribute to sustainable practices in the building sector, offering insights for policy and industry, particularly in the context of climate change mitigation. The global warming potential for HUF unit in Oslo is 129 kg CO 2 e/m ² for scenario RCP 4.5 and 128 kg CO 2 e/m ² for RCP 8.5.

Life Cycle Assessment is necessary for evaluating the environmental impacts of buildings throughout their life cycle, considering factors such as energy consumption, emissions, and resource utilization. However, Dynamic Life Cycle Assessment introduces a temporal dimension, acknowledging that a building's environmental performance evolves due to technological advancements, occupancy behavior, and changing environmental conditions. This paper reviews DLCA, focusing on uncertainties arising from parameter, scenario, and model variability, and emphasizes the integration of technologies like Building Information Modeling, the Internet of Things, and machine learning to enhance real-time data collection and predictive analytics. An extensive review of 430 papers, refined to 180, reveals that 55 % of publications are in environmental sciences, with significant contributions from the United Kingdom (27.8 %), France (24.1 %), and China (18.1 %). Key findings include significant variations in embodied greenhouse gas emissions for materials like aluminum and the dynamic aspects of transportation impacts, which extend beyond traditional metrics to include operational efficiency over time. Uncertainties in all LCA stages (A1 to D) are addressed, focusing on service life, operational energy and water use, and transportation needs. Advanced methodologies, including a proposed framework for a hybrid LCA approach that integrates process-based and input-output methods, are suggested to enhance the comprehensiveness of assessments. The integration of real-time monitoring and predictive analytics further improves the adaptability and precision of LCA models, emphasizing the necessity of continuous updates and scenario analyses to capture future conditions accurately. This study paves the way for future research aimed at mitigating major sources of uncertainty, promoting more sustainable building practices, and advancing the field of dynamic LCA.