Component-based model for building material stock and waste-flow characterization: A case in the Île-de-France region

Abstract

Building demolition is one of the main sources of waste generation in urban areas and is a growing problem for cities due to the generated environmental impacts. To promote high levels of circular economy, it is necessary to better understand the waste-flow composition; nevertheless, material flow studies typically focus on low levels of detail. This article presents a model based on a bottom-up macro-component approach, which allows the multiscale characterization of construction materials and the estimation of demolition waste flows, a model that we call the BTP-flux model. Data mining, analytical techniques, and geographic information system (GIS) tools were used to assess different datasets available at the national level and develop a common database for French buildings: BDNB. Generic information for buildings in the BDNB is then enriched by coupling every building with a catalog of macro-components (TyPy), thus allowing the building’s physical description. Subsequently, stock and demolition flows are calculated by aggregation and classified into 32 waste categories. The BTP-flux model was applied in Île-de-France in a sample of 101,320 buildings for residential and non-residential uses, representative of the assessed population (1,968,242 buildings). In the case of Île-de-France, the building stock and the total demolition flows were estimated at 1382 Mt and 4065 kt, respectively. For its inter-regional areas—departments—, stock and demolition waste can vary between 85 and 138 tons/cap and 0.263 and 0.486 tons/cap/year, respectively. The mean of the total demolition wastes was estimated at 0.33 tons/cap/year for the region. Results could encourage scientists, planners, and stakeholders to develop pathways towards a circular economy in the construction sector by implementing strategies for better management of waste recovery and reintegrating in economic circuits, while preserving a maximum of their added value.