Modeling the effect of climate change on U.S. state-level buildings energy demands in an integrated assessment framework

Abstract

ObjectiveBecause long-term socioeconomic transformation and energy service expansion show large spatial heterogeneity, advanced understanding of climate change impact on buildings energy use at the sub-national level will offer useful insights into climate policy and regional energy system planning. MethodsIn this study, we present a detailed buildings energy model with U.S. state-level representation, nested in an integrated assessment framework of the Global Change Assessment Model (GCAM). We project state-level buildings energy demand and its spatial pattern through the end of the century, considering the impact of climate change based on the estimates of heating and cooling degree days derived from downscaled USGS CASCaDE temperature data. ResultsThe results indicate that climate change has a large impact on heating and cooling buildings energy and fuel use at the state level and that the 48 U.S. contiguous states exhibit a large spatial heterogeneity (ranges from −10% to+10% for total, −10% to+20% for electricity use and −20% to −5% for oil and gas use in the A2 scenario). Sensitivity analysis explores the potential implications of multiple driving forces, including climate action that would both change the price of energy and reduce climate change, the choice of climate models, and population and GDP growth. In addition, the 50-state building model is compared to a comparable version of the model which represents the entire United States as one region. ConclusionsThe study clearly demonstrates the spatially varying nature of fuel consumption changes that might occur from a changing climate. Although the study illustrates the importance of incorporating climate change into infrastructure-planning exercises, it also demonstrates that uncertainties about underlying drivers still must weigh heavily on these planning decisions. Finally, the study demonstrates that the 50-state building model provides both insights at the regional level and potentially better national-level estimates. Practice implicationThe findings from this study will help the climate-based policy decision and energy system, especially utility planning related to the buildings sector at the U.S. state and regional level facing the potential climate change.