Summary Building stocks constitute enduring components of urban infrastructure systems, but little research exists on their residence time or changing environmental impacts. Using Los Angeles County, California, as a case study, a framework is developed for assessing the changes of building stocks in cities (i.e., a generalizable framework for estimating the construction and deconstruction rates), the residence time of buildings and their materials, and the associated embedded environmental impacts. In Los Angeles, previous land‐use decisions prove not easily reversible, and past building stock investments may continue to constrain the energy performance of buildings. The average age of the building stock has increased steadily since 1920 and more rapidly after the post–World War II construction surge in the 1950s. Buildings will likely endure for 60 years or longer, making this infrastructure a quasi‐permanent investment. The long residence time, combined with the physical limitations on outward growth, suggest that the Los Angeles building stock is unlikely to have substantial spatial expansion in the future. The construction of buildings requires a continuous investment in material, monetary, and energetic resources, resulting in environmental impacts. The long residence time of structures implies a commitment to use and maintain the infrastructure, potentially creating barriers to an urban area's ability to improve energy efficiency. The immotility of buildings, coupled with future environmental goals, indicates that urban areas will be best positioned by instituting strategies that ensure reductions in life cycle (construction, use, and demolition) environmental impacts.

Climate change could significantly affect consumer demand for energy in buildings, as changing temperatures may alter heating and cooling loads. Warming climates could also lead to the increased adoption and use of cooling technologies in buildings. We assess residential electricity and natural gas demand in Los Angeles, California under multiple climate change projections and investigate the potential for energy efficiency to offset increased demand. We calibrate residential energy use against metered data, accounting for differences in building materials and appliances. Under temperature increases, we find that without policy intervention, residential electricity demand could increase by as much as 41–87% between 2020 and 2060. However, aggressive policies aimed at upgrading heating/cooling systems and appliances could result in electricity use increases as low as 28%, potentially avoiding the installation of new generation capacity. We therefore recommend aggressive energy efficiency, in combination with low-carbon generation sources, to offset projected increases in residential energy demand.

Buildings are responsible for 36% of CO 2 emissions in the U.S. and will thus be integral to climate change mitigation. We use Scout, a reproducible model of U.S. building energy use, to assess whether buildings can reduce CO 2 emissions 80% by 2050, finding that aggressive efficiency measures and low-carbon electrification can reduce emissions 72%-78%. The analysis establishes a basis for periodic reassessment of building technology development pathways that can drive longterm reductions in U.S. CO 2 emissions.

Buildings contribute 40% of global greenhouse gas emissions; therefore, strategies that can substantially reduce emissions from the building stock are key components of broader efforts to mitigate climate change and achieve sustainable development goals. Models that represent the energy use of the building stock at scale under various scenarios of technology deployment have become essential tools for the development and assessment of such strategies. Within the past decade, the capabilities of building stock energy models have improved considerably, while model transferability and sharing has increased. Given these advancements, a new scheme for classifying building stock energy models is needed to facilitate communication of modeling approaches and the handling of important model dimensions. In this article, we present a new building stock energy model classification framework that leverages international modeling expertise from the participants of the International Energy Agency's Annex 70 on Building Energy Epidemiology. Drawing from existing classification studies, we propose a multi-layer quadrant scheme that classifies modeling techniques by their design (top-down or bottom-up) and degree of transparency (black-box or white-box); hybrid techniques are also addressed. The quadrant scheme is unique from previous classification approaches in its non-hierarchical organization, coverage of and ability to incorporate emerging modeling techniques, and treatment of additional modeling dimensions. The new classification framework will be complemented by a reporting protocol and online registry of existing models as part of ongoing work in Annex 70 to increase the interpretability and utility of building stock energy models for energy policy making.

Summary This synthesis article presents an overview of an urban metabolism (UM) approach using mixed methods and multiple sources of data for Los Angeles, California. We examine electric energy use in buildings and greenhouse gas emissions from electricity, and calculate embedded infrastructure life cycle effects, water use and solid waste streams in an attempt to better understand the urban flows and sinks in the Los Angeles region (city and county). This quantification is being conducted to help policy‐makers better target energy conservation and efficiency programs, pinpoint best locations for distributed solar generation, and support the development of policies for greater environmental sustainability. It provides a framework to which many more UM flows can be added to create greater understanding of the study area's resource dependencies. Going forward, together with policy analysis, UM can help untangle the complex intertwined resource dependencies that cities must address as they attempt to increase their environmental sustainability.