Climatic Change

, Volume 119, Issue 3–4, pp 979–992 | Cite as

The effect of global climate change, population distribution, and climate mitigation on building energy use in the U.S. and China

  • Yuyu ZhouEmail author
  • Jiyong Eom
  • Leon Clarke


Climate change will affect the energy system in a number of ways, one of which is through changes in demands for heating and cooling in buildings. Understanding the potential effect of climate change on heating and cooling demands requires taking into account not only the manner in which the building sector might evolve over time, but also important uncertainty about the nature of climate change itself. In this study, we explore the uncertainty in climate change impacts on heating and cooling requirement by constructing estimates of heating and cooling degree days (HDD/CDDs) for both reference (no-policy) and 550 ppmv CO2 concentration pathways built from three different Global Climate Models (GCMs) output and three scenarios of gridded population distribution. The implications that changing climate and population distribution might have for building energy consumption in the U.S. and China are then explored by using the results of HDD/CDDs as inputs to a detailed, building energy model, nested in the long-term global integrated assessment framework, Global Change Assessment Model (GCAM). The results across the modeled changes in climate and population distributions indicate that unabated climate change would cause building sector’s final energy consumption to decrease modestly (6 % decrease or less depending on climate models) in both the U.S. and China by the end of the century as decreased heating consumption more than offsets increased cooling using primarily electricity. However, global climate change virtually has negligible effect on total CO2 emissions in the buildings sector in both countries. The results also indicate more substantial implications for the fuel mix with increases in electricity and decreases in other fuels, which may be consistent with climate mitigation goals. The variation in results across all scenarios due to variation of population distribution is smaller than variation due to the use of different climate models.


Building Energy Integrate Assessment Model Building Sector Heating Energy Building Energy Consumption 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



The authors are grateful for research support provided by Environmental Protection Agency, the Global Technology Strategy Project, and the Integrated Assessment Research Program in the Office of Science of the U.S. Department of Energy for funding this research. The Pacific Northwest National Laboratory is operated for DOE by Battelle Memorial Institute under contract DE‐AC05‐76RL01830. The authors would like to thank James J. Dooley and three anonymous reviewers for constructive comments and the many colleagues and organizations that shared data used in this project. The views and opinions expressed in this paper are those of the authors alone.

Supplementary material

10584_2013_772_MOESM1_ESM.docx (4.5 mb)
ESM 1 (DOCX 4617 kb)


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Copyright information

© Springer Science+Business Media Dordrecht 2013

Authors and Affiliations

  1. 1.Joint Global Change Research InstitutePacific Northwest National Laboratory/University of MarylandCollege ParkUSA
  2. 2.Graduate School of Management of TechnologySogang UniversitySeoulRepublic of Korea

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