Forecasting the U.S. Residential Renewable Electricity Mix: A Time-Series Approach for 50-Year Building GWP Projections (1949–2080)

Assessments of building operational Global Warming Potential (GWP) often rely on static representations of today's electricity grid, overlooking the influence of long-term grid decarbonization on future emissions. This study presents a dynamic forecasting framework to project the evolution of the U.S. residential electricity mix and its implications for operational GWP through 2080. Using 75 years of historical electricity data from the U.S. Energy Information Administration (EIA), Autoregressive Integrated Moving Average (ARIMA) models are applied to estimate baseline trends in renewable electricity adoption. To account for long-term uncertainty, statistical forecasts are calibrated using scenario envelopes informed by EIA, IEA, and NREL energy outlooks. Results show that under a mid-ambition scenario, renewable electricity exceeds 50% of the residential mix by mid-century. Incorporating these dynamics reduces cumulative 50-year operational GWP by approximately 31% relative to static grid assumptions, indicating that static approaches substantially overestimate long-term operational impacts. The proposed framework provides a transparent and replicable method for integrating evolving electricity systems into prospective operational LCA of buildings.