DOI: 10.5281/zenodo.10631464
title: Scout Benchmark Scenarios for U.S. Building Energy and CO2 Emissions to 2050

description: Overview and Intended Use Cases

These scenarios establish a range of futures for U.S. buildings sector energy use and CO2 emissions to 2050 using Scout, a reproducible and granular model of U.S. building energy use, emissions, and consumer costs developed by the U.S. national labs for the U.S. Department of Energy's Building Technologies Office (BTO).

Scout benchmark scenario data are suitable for the following example use cases:



Setting high-level policy goals for U.S. buildings sector energy use, electricity demand, and CO2 emissions over both the near- and long-term (e.g., X% building CO2 emissions reductions vs. 2005 levels by 2030, Y% reductions vs. 2005 levels by 2050);

Exploring the effects of key deployment dynamics driving U.S. buildings sector energy and CO2 emissions to 2050 that could be affected by policy levers (e.g., raising minimum technology performance levels; improving market penetration of commercially available technologies; accelerating electrification and/or retrofit rates; introducing breakthrough technologies to the market);

Determining priority segments (regions, building types, and end use/technology types) and sequencing of U.S. buildings sector energy and CO2 emissions reductions and/or changes in total consumption by fuel type to 2050 under a given set of assumptions;

Identifying the energy and CO2 impacts or cost effectiveness of specific technologies or operational approaches of interest—in isolation or after considering competition with other measures in a scenario portfolio; and/or

Exploring the total cost of deploying different portfolios of building energy efficiency and end-use electrification measures, as well as the total consumer energy cost savings potential of those portfolios.           


Scenario Summary

A total of 5 scenarios explore total building energy use, CO2 emissions, and technology and energy costs from 2024–2050 under varying levels of demand-side deployment of building efficiency and electrification measures and parallel decarbonization of buildings’ electricity supply. Narrative descriptions of these scenarios are as follows:



Stated Policies: Existing policies and regulations (mainly IRA for buildings) lead to modestly accelerated deployment of HPs/HPWHs but not other efficiency measures in the buildings sector. The power sector decarbonizes consistent with a “Mid-case (with tax credit phaseout)” scenario.

Mid: Policy makers rely mostly on market-based instruments to moderately increase deployment of efficient technology and fuel switching to heat pumps. The power sector decarbonizes consistent with a “Mid-case with 95% Decarbonization by 2050 (without tax credit phaseout)” scenario.

High: Policy makers use both regulations and market-based instruments to dramatically accelerate deployment of high efficiency technologies and fuel switching to heat pumps, though building technologies with breakthrough increases in performance at low cost do not materialize on the market. The power sector decarbonizes consistent with a “Mid-case with 100% Decarbonization by 2035 (without tax credit phaseout)” scenario.

Breakthrough: Research and innovation breakthroughs lead to market availability of cost-effective, high-performance building technologies by 2030; these, coupled with accelerated deployment of high efficiency technologies and fuel switching to heat pumps, lead to aggressive buildings sector transformation. The power sector decarbonizes consistent with a “Mid-case with 100% Decarbonization by 2035 (without tax credit phaseout)” scenario.

Inefficient Electrification Sensitivity: Policy makers use regulations and market-based instruments to encourage fuel switching but do not include provisions that require switching to efficient heat pumps, resulting in a substantial amount of switching to inefficient electric resistance heating and water heating technologies. The power sector decarbonizes consistent with a “Mid-case (with tax credit phaseout)” scenario.


The key input dimensions that are varied to produce the above range of scenarios are as follows:



Market-available technology performance range: the energy performance levels of building technologies available for purchase by end use consumers, bounded by a minimum performance “floor” and maximum performance “ceiling”;

Load electrification rate and efficiency: the rate at which fossil-fired equipment is converted to electric service, and the efficiency level of the electric equipment;          

Early retrofits: the fraction of consumers that choose to replace existing building equipment and/or envelope components before the end of their useful lifetimes; and

Power grid decarbonization: the annual average CO2 emissions intensity of the electricity supplied to the buildings sector across the modeled time horizon (2024–2050), resolved by grid region.          


Refer to the attached “Scenario_Guide" PDF for further scenario details and results; instructions for reproducing scenario results are available in “Scenario_Execution” XLSX.

Results data are reported as an annual time series (2024–2050) at both a national and regional (EMM grid region) spatial resolution. While not reflected in this dataset, annual time series data may be further translated to a sub-annual, hourly resolution for integration with grid modeling—please contact the authors for more information.

What's New in This Version

This set of benchmark scenarios provides an update to Version 5 of the Scout Benchmark Scenarios (June 2023) using the same scenario definitions but an updated set of baseline and measure input data alongside several minor methodological changes.    

The following scenario features are new in this dataset:



Reference case data and energy use projections updated to AEO 2023, including updates to energy and stock and technology cost, performance, and lifetime data; updated site-source energy conversions, CO2 emissions intensities, and energy prices; and revised peak and take period definitions that are consistent with 2023 EMM projections.

Integration of federal and state cost incentives from AEO 2023 (see AEO2023 Issues in Focus: Inflation Reduction Act Cases in the AEO2023 for details); these incentives reduce the initial cost of upgrades for applicable measures.

Revised method for allocating end use electricity baselines in AEO from census divisions to EMM regions and states by using End Use Load Profiles (EULP) data. EULP data now also underpin updated, EMM-resolved hourly load baseline shapes.

Retail price projections for grid scenarios are updated to match those produced by NREL under the Department of Energy’s DECARB Initiative (these are similar to but differ in slight ways from NREL’s Standard Scenarios). Three scenarios are included: 



Stated Policies: includes moderate estimates for inputs such as technology costs, fuel prices, and demand growth with no nascent technologies and electric sector policies that match current federal laws and regulations (including IRA & BIL); achieves an 88% reduction in building site electricity emissions intensity (Mt CO2/quad site) from 2005 levels by 2050.

Mid: consistent with Stated Policies except achieves 97% reduction in building site electricity emissions intensity from 2005 levels by 2050.

High: includes low demand growth projections with advanced inputs for technology costs and allowance of transmission expansion between regions (without limitations based on historical build rates); federal policies are consistent with implemented laws (including IRA & BIL); building electricity is fully decarbonized after 2035.

The previous version of the benchmark datasets used retail price data from EIA’s Annual Energy Outlook scenarios.



In contrast to Version 5, measures in the “best available” measure tier are not deployed with load flexibility features.