A layered dynamic material flow framework for modeling building renovations

Abstract

Abstract Dynamic material flow analysis (dMFA) is widely used to study the material demands of residential building stocks. In most of the studies conducted to date, buildings are modeled as homogeneous units instead of a system of components. A limitation of this assumption is that the material flow dynamics from renovations cannot be fully captured. In this study, we develop a cohort-based, layered dMFA framework that explicitly links renovation lifetimes to structural lifetimes, while allowing for different building layers to be renovated independently. This framework tracks the temporal evolution of building cohorts and applies a lifetime convolution approach to ensure that renovation probabilities are conditional on building survival. Cohort-specific material intensities are further differentiated across structural, skin, and space layers. We apply the framework to residential buildings in Sweden using a unique set of building inventory and disaggregated material intensity data. Compared with conventional monolithic renovation models, the layered lifetime approach reduces the estimated renovated floor area by approximately 10%, with larger differences seen for older cohorts that are approaching demolition. These corrections translate into substantial changes in renovation-related material flows. The results demonstrate that neglecting lifetime interdependencies between building components and structures leads to inflated estimates of the demand for renovation. By conceptualizing buildings as systems that have components with interrelated lifetimes, this study advances dMFA methods for renovation modeling.