Pathways for sustainable material use and GHG emission reductions from housing stock evolution in US counties to 2060
Abstract
As a contribution to this session we demonstrate results of a housing stock and material flow model for all counties in the United States. We describe a novel method for generating building stock and archetype characterizations at a local level, combining data from multiple sources at various geographical resolution, and using a sampling algorithm to generate representative samples of the residential building stock. These samples are then used to estimate building stock and archetype characteristics at any geographic resolution included in the source data. Material and GHG intensities are estimated for 50 building archetypes defined by building type, size, foundation type, stories, and main framing material. Weighted average intensities are then calculated for three main housing types in each county based on the local prevalence of each archetype. We combine the county material and greenhouse gas intensity data with our county-level housing stock model to estimate material flows and emissions associated with housing construction and demolition in all US counties from 2020 to 2060. Floor area per capita, material flows and GHG emissions can be reduced by increasing the share of smaller and multifamily homes in new construction. We use insights gained during this research to reflect on some of the discussion questions outlines for this session. Benefits and wider potential of bottom-up material flow analyses include identification of material demand and waste generation at local levels, which can enable circular use of materials and building components, and identification of lowest-intensity archetypes which can be prioritized to minimize emissions from new construction. Data gaps include material and GHG intensity characterization of high-rise building archetypes, and emissions from construction site energy use and transport.
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